@article {1107, title = {NRXN3 is a novel locus for waist circumference: a genome-wide association study from the CHARGE Consortium.}, journal = {PLoS Genet}, volume = {5}, year = {2009}, month = {2009 Jun}, pages = {e1000539}, abstract = {
Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4x10(-7))]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3x10(-8) for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4x10(-6), 0.024 z-score units (0.10 kg/m(2)) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95\% CI 1.07-1.19; p = 3.2x10(-5) per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity.
}, keywords = {Aged, Body Mass Index, Cohort Studies, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Nerve Tissue Proteins, Obesity, Polymorphism, Single Nucleotide, Waist Circumference}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1000539}, author = {Heard-Costa, Nancy L and Zillikens, M Carola and Monda, Keri L and Johansson, Asa and Harris, Tamara B and Fu, Mao and Haritunians, Talin and Feitosa, Mary F and Aspelund, Thor and Eiriksdottir, Gudny and Garcia, Melissa and Launer, Lenore J and Smith, Albert V and Mitchell, Braxton D and McArdle, Patrick F and Shuldiner, Alan R and Bielinski, Suzette J and Boerwinkle, Eric and Brancati, Fred and Demerath, Ellen W and Pankow, James S and Arnold, Alice M and Chen, Yii-Der Ida and Glazer, Nicole L and McKnight, Barbara and Psaty, Bruce M and Rotter, Jerome I and Amin, Najaf and Campbell, Harry and Gyllensten, Ulf and Pattaro, Cristian and Pramstaller, Peter P and Rudan, Igor and Struchalin, Maksim and Vitart, Veronique and Gao, Xiaoyi and Kraja, Aldi and Province, Michael A and Zhang, Qunyuan and Atwood, Larry D and Dupuis, Jos{\'e}e and Hirschhorn, Joel N and Jaquish, Cashell E and O{\textquoteright}Donnell, Christopher J and Vasan, Ramachandran S and White, Charles C and Aulchenko, Yurii S and Estrada, Karol and Hofman, Albert and Rivadeneira, Fernando and Uitterlinden, Andr{\'e} G and Witteman, Jacqueline C M and Oostra, Ben A and Kaplan, Robert C and Gudnason, Vilmundur and O{\textquoteright}Connell, Jeffrey R and Borecki, Ingrid B and van Duijn, Cornelia M and Cupples, L Adrienne and Fox, Caroline S and North, Kari E} } @article {1237, title = {Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index.}, journal = {Nat Genet}, volume = {42}, year = {2010}, month = {2010 Nov}, pages = {937-48}, abstract = {Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and \~{} 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 {\texttimes} 10$^{-}$$^{8}$), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
}, keywords = {Body Height, Body Mass Index, Body Size, Body Weight, Chromosome Mapping, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Obesity, Polymorphism, Single Nucleotide}, issn = {1546-1718}, doi = {10.1038/ng.686}, author = {Speliotes, Elizabeth K and Willer, Cristen J and Berndt, Sonja I and Monda, Keri L and Thorleifsson, Gudmar and Jackson, Anne U and Lango Allen, Hana and Lindgren, Cecilia M and Luan, Jian{\textquoteright}an and M{\"a}gi, Reedik and Randall, Joshua C and Vedantam, Sailaja and Winkler, Thomas W and Qi, Lu and Workalemahu, Tsegaselassie and Heid, Iris M and Steinthorsdottir, Valgerdur and Stringham, Heather M and Weedon, Michael N and Wheeler, Eleanor and Wood, Andrew R and Ferreira, Teresa and Weyant, Robert J and Segr{\`e}, Ayellet V and Estrada, Karol and Liang, Liming and Nemesh, James and Park, Ju-Hyun and Gustafsson, Stefan and Kilpel{\"a}inen, Tuomas O and Yang, Jian and Bouatia-Naji, Nabila and Esko, T{\~o}nu and Feitosa, Mary F and Kutalik, Zolt{\'a}n and Mangino, Massimo and Raychaudhuri, Soumya and Scherag, Andre and Smith, Albert Vernon and Welch, Ryan and Zhao, Jing Hua and Aben, Katja K and Absher, Devin M and Amin, Najaf and Dixon, Anna L and Fisher, Eva and Glazer, Nicole L and Goddard, Michael E and Heard-Costa, Nancy L and Hoesel, Volker and Hottenga, Jouke-Jan and Johansson, Asa and Johnson, Toby and Ketkar, Shamika and Lamina, Claudia and Li, Shengxu and Moffatt, Miriam F and Myers, Richard H and Narisu, Narisu and Perry, John R B and Peters, Marjolein J and Preuss, Michael and Ripatti, Samuli and Rivadeneira, Fernando and Sandholt, Camilla and Scott, Laura J and Timpson, Nicholas J and Tyrer, Jonathan P and van Wingerden, Sophie and Watanabe, Richard M and White, Charles C and Wiklund, Fredrik and Barlassina, Christina and Chasman, Daniel I and Cooper, Matthew N and Jansson, John-Olov and Lawrence, Robert W and Pellikka, Niina and Prokopenko, Inga and Shi, Jianxin and Thiering, Elisabeth and Alavere, Helene and Alibrandi, Maria T S and Almgren, Peter and Arnold, Alice M and Aspelund, Thor and Atwood, Larry D and Balkau, Beverley and Balmforth, Anthony J and Bennett, Amanda J and Ben-Shlomo, Yoav and Bergman, Richard N and Bergmann, Sven and Biebermann, Heike and Blakemore, Alexandra I F and Boes, Tanja and Bonnycastle, Lori L and Bornstein, Stefan R and Brown, Morris J and Buchanan, Thomas A and Busonero, Fabio and Campbell, Harry and Cappuccio, Francesco P and Cavalcanti-Proen{\c c}a, Christine and Chen, Yii-Der Ida and Chen, Chih-Mei and Chines, Peter S and Clarke, Robert and Coin, Lachlan and Connell, John and Day, Ian N M and den Heijer, Martin and Duan, Jubao and Ebrahim, Shah and Elliott, Paul and Elosua, Roberto and Eiriksdottir, Gudny and Erdos, Michael R and Eriksson, Johan G and Facheris, Maurizio F and Felix, Stephan B and Fischer-Posovszky, Pamela and Folsom, Aaron R and Friedrich, Nele and Freimer, Nelson B and Fu, Mao and Gaget, Stefan and Gejman, Pablo V and Geus, Eco J C and Gieger, Christian and Gjesing, Anette P and Goel, Anuj and Goyette, Philippe and Grallert, Harald and Gr{\"a}ssler, J{\"u}rgen and Greenawalt, Danielle M and Groves, Christopher J and Gudnason, Vilmundur and Guiducci, Candace and Hartikainen, Anna-Liisa and Hassanali, Neelam and Hall, Alistair S and Havulinna, Aki S and Hayward, Caroline and Heath, Andrew C and Hengstenberg, Christian and Hicks, Andrew A and Hinney, Anke and Hofman, Albert and Homuth, Georg and Hui, Jennie and Igl, Wilmar and Iribarren, Carlos and Isomaa, Bo and Jacobs, Kevin B and Jarick, Ivonne and Jewell, Elizabeth and John, Ulrich and J{\o}rgensen, Torben and Jousilahti, Pekka and Jula, Antti and Kaakinen, Marika and Kajantie, Eero and Kaplan, Lee M and Kathiresan, Sekar and Kettunen, Johannes and Kinnunen, Leena and Knowles, Joshua W and Kolcic, Ivana and K{\"o}nig, Inke R and Koskinen, Seppo and Kovacs, Peter and Kuusisto, Johanna and Kraft, Peter and Kval{\o}y, Kirsti and Laitinen, Jaana and Lantieri, Olivier and Lanzani, Chiara and Launer, Lenore J and Lecoeur, C{\'e}cile and Lehtim{\"a}ki, Terho and Lettre, Guillaume and Liu, Jianjun and Lokki, Marja-Liisa and Lorentzon, Mattias and Luben, Robert N and Ludwig, Barbara and Manunta, Paolo and Marek, Diana and Marre, Michel and Martin, Nicholas G and McArdle, Wendy L and McCarthy, Anne and McKnight, Barbara and Meitinger, Thomas and Melander, Olle and Meyre, David and Midthjell, Kristian and Montgomery, Grant W and Morken, Mario A and Morris, Andrew P and Mulic, Rosanda and Ngwa, Julius S and Nelis, Mari and Neville, Matt J and Nyholt, Dale R and O{\textquoteright}Donnell, Christopher J and O{\textquoteright}Rahilly, Stephen and Ong, Ken K and Oostra, Ben and Par{\'e}, Guillaume and Parker, Alex N and Perola, Markus and Pichler, Irene and Pietil{\"a}inen, Kirsi H and Platou, Carl G P and Polasek, Ozren and Pouta, Anneli and Rafelt, Suzanne and Raitakari, Olli and Rayner, Nigel W and Ridderstr{\r a}le, Martin and Rief, Winfried and Ruokonen, Aimo and Robertson, Neil R and Rzehak, Peter and Salomaa, Veikko and Sanders, Alan R and Sandhu, Manjinder S and Sanna, Serena and Saramies, Jouko and Savolainen, Markku J and Scherag, Susann and Schipf, Sabine and Schreiber, Stefan and Schunkert, Heribert and Silander, Kaisa and Sinisalo, Juha and Siscovick, David S and Smit, Jan H and Soranzo, Nicole and Sovio, Ulla and Stephens, Jonathan and Surakka, Ida and Swift, Amy J and Tammesoo, Mari-Liis and Tardif, Jean-Claude and Teder-Laving, Maris and Teslovich, Tanya M and Thompson, John R and Thomson, Brian and T{\"o}njes, Anke and Tuomi, Tiinamaija and van Meurs, Joyce B J and van Ommen, Gert-Jan and Vatin, Vincent and Viikari, Jorma and Visvikis-Siest, Sophie and Vitart, Veronique and Vogel, Carla I G and Voight, Benjamin F and Waite, Lindsay L and Wallaschofski, Henri and Walters, G Bragi and Widen, Elisabeth and Wiegand, Susanna and Wild, Sarah H and Willemsen, Gonneke and Witte, Daniel R and Witteman, Jacqueline C and Xu, Jianfeng and Zhang, Qunyuan and Zgaga, Lina and Ziegler, Andreas and Zitting, Paavo and Beilby, John P and Farooqi, I Sadaf and Hebebrand, Johannes and Huikuri, Heikki V and James, Alan L and K{\"a}h{\"o}nen, Mika and Levinson, Douglas F and Macciardi, Fabio and Nieminen, Markku S and Ohlsson, Claes and Palmer, Lyle J and Ridker, Paul M and Stumvoll, Michael and Beckmann, Jacques S and Boeing, Heiner and Boerwinkle, Eric and Boomsma, Dorret I and Caulfield, Mark J and Chanock, Stephen J and Collins, Francis S and Cupples, L Adrienne and Smith, George Davey and Erdmann, Jeanette and Froguel, Philippe and Gr{\"o}nberg, Henrik and Gyllensten, Ulf and Hall, Per and Hansen, Torben and Harris, Tamara B and Hattersley, Andrew T and Hayes, Richard B and Heinrich, Joachim and Hu, Frank B and Hveem, Kristian and Illig, Thomas and Jarvelin, Marjo-Riitta and Kaprio, Jaakko and Karpe, Fredrik and Khaw, Kay-Tee and Kiemeney, Lambertus A and Krude, Heiko and Laakso, Markku and Lawlor, Debbie A and Metspalu, Andres and Munroe, Patricia B and Ouwehand, Willem H and Pedersen, Oluf and Penninx, Brenda W and Peters, Annette and Pramstaller, Peter P and Quertermous, Thomas and Reinehr, Thomas and Rissanen, Aila and Rudan, Igor and Samani, Nilesh J and Schwarz, Peter E H and Shuldiner, Alan R and Spector, Timothy D and Tuomilehto, Jaakko and Uda, Manuela and Uitterlinden, Andre and Valle, Timo T and Wabitsch, Martin and Waeber, G{\'e}rard and Wareham, Nicholas J and Watkins, Hugh and Wilson, James F and Wright, Alan F and Zillikens, M Carola and Chatterjee, Nilanjan and McCarroll, Steven A and Purcell, Shaun and Schadt, Eric E and Visscher, Peter M and Assimes, Themistocles L and Borecki, Ingrid B and Deloukas, Panos and Fox, Caroline S and Groop, Leif C and Haritunians, Talin and Hunter, David J and Kaplan, Robert C and Mohlke, Karen L and O{\textquoteright}Connell, Jeffrey R and Peltonen, Leena and Schlessinger, David and Strachan, David P and van Duijn, Cornelia M and Wichmann, H-Erich and Frayling, Timothy M and Thorsteinsdottir, Unnur and Abecasis, Goncalo R and Barroso, In{\^e}s and Boehnke, Michael and Stefansson, Kari and North, Kari E and McCarthy, Mark I and Hirschhorn, Joel N and Ingelsson, Erik and Loos, Ruth J F} } @article {1234, title = {Hundreds of variants clustered in genomic loci and biological pathways affect human height.}, journal = {Nature}, volume = {467}, year = {2010}, month = {2010 Oct 14}, pages = {832-8}, abstract = {Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10\% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16\% of phenotypic variation (approximately 20\% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
}, keywords = {Body Height, Chromosomes, Human, Pair 3, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Metabolic Networks and Pathways, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide}, issn = {1476-4687}, doi = {10.1038/nature09410}, author = {Lango Allen, Hana and Estrada, Karol and Lettre, Guillaume and Berndt, Sonja I and Weedon, Michael N and Rivadeneira, Fernando and Willer, Cristen J and Jackson, Anne U and Vedantam, Sailaja and Raychaudhuri, Soumya and Ferreira, Teresa and Wood, Andrew R and Weyant, Robert J and Segr{\`e}, Ayellet V and Speliotes, Elizabeth K and Wheeler, Eleanor and Soranzo, Nicole and Park, Ju-Hyun and Yang, Jian and Gudbjartsson, Daniel and Heard-Costa, Nancy L and Randall, Joshua C and Qi, Lu and Vernon Smith, Albert and M{\"a}gi, Reedik and Pastinen, Tomi and Liang, Liming and Heid, Iris M and Luan, Jian{\textquoteright}an and Thorleifsson, Gudmar and Winkler, Thomas W and Goddard, Michael E and Sin Lo, Ken and Palmer, Cameron and Workalemahu, Tsegaselassie and Aulchenko, Yurii S and Johansson, Asa and Zillikens, M Carola and Feitosa, Mary F and Esko, T{\~o}nu and Johnson, Toby and Ketkar, Shamika and Kraft, Peter and Mangino, Massimo and Prokopenko, Inga and Absher, Devin and Albrecht, Eva and Ernst, Florian and Glazer, Nicole L and Hayward, Caroline and Hottenga, Jouke-Jan and Jacobs, Kevin B and Knowles, Joshua W and Kutalik, Zolt{\'a}n and Monda, Keri L and Polasek, Ozren and Preuss, Michael and Rayner, Nigel W and Robertson, Neil R and Steinthorsdottir, Valgerdur and Tyrer, Jonathan P and Voight, Benjamin F and Wiklund, Fredrik and Xu, Jianfeng and Zhao, Jing Hua and Nyholt, Dale R and Pellikka, Niina and Perola, Markus and Perry, John R B and Surakka, Ida and Tammesoo, Mari-Liis and Altmaier, Elizabeth L and Amin, Najaf and Aspelund, Thor and Bhangale, Tushar and Boucher, Gabrielle and Chasman, Daniel I and Chen, Constance and Coin, Lachlan and Cooper, Matthew N and Dixon, Anna L and Gibson, Quince and Grundberg, Elin and Hao, Ke and Juhani Junttila, M and Kaplan, Lee M and Kettunen, Johannes and K{\"o}nig, Inke R and Kwan, Tony and Lawrence, Robert W and Levinson, Douglas F and Lorentzon, Mattias and McKnight, Barbara and Morris, Andrew P and M{\"u}ller, Martina and Suh Ngwa, Julius and Purcell, Shaun and Rafelt, Suzanne and Salem, Rany M and Salvi, Erika and Sanna, Serena and Shi, Jianxin and Sovio, Ulla and Thompson, John R and Turchin, Michael C and Vandenput, Liesbeth and Verlaan, Dominique J and Vitart, Veronique and White, Charles C and Ziegler, Andreas and Almgren, Peter and Balmforth, Anthony J and Campbell, Harry and Citterio, Lorena and De Grandi, Alessandro and Dominiczak, Anna and Duan, Jubao and Elliott, Paul and Elosua, Roberto and Eriksson, Johan G and Freimer, Nelson B and Geus, Eco J C and Glorioso, Nicola and Haiqing, Shen and Hartikainen, Anna-Liisa and Havulinna, Aki S and Hicks, Andrew A and Hui, Jennie and Igl, Wilmar and Illig, Thomas and Jula, Antti and Kajantie, Eero and Kilpel{\"a}inen, Tuomas O and Koiranen, Markku and Kolcic, Ivana and Koskinen, Seppo and Kovacs, Peter and Laitinen, Jaana and Liu, Jianjun and Lokki, Marja-Liisa and Marusic, Ana and Maschio, Andrea and Meitinger, Thomas and Mulas, Antonella and Par{\'e}, Guillaume and Parker, Alex N and Peden, John F and Petersmann, Astrid and Pichler, Irene and Pietil{\"a}inen, Kirsi H and Pouta, Anneli and Ridderstr{\r a}le, Martin and Rotter, Jerome I and Sambrook, Jennifer G and Sanders, Alan R and Schmidt, Carsten Oliver and Sinisalo, Juha and Smit, Jan H and Stringham, Heather M and Bragi Walters, G and Widen, Elisabeth and Wild, Sarah H and Willemsen, Gonneke and Zagato, Laura and Zgaga, Lina and Zitting, Paavo and Alavere, Helene and Farrall, Martin and McArdle, Wendy L and Nelis, Mari and Peters, Marjolein J and Ripatti, Samuli and van Meurs, Joyce B J and Aben, Katja K and Ardlie, Kristin G and Beckmann, Jacques S and Beilby, John P and Bergman, Richard N and Bergmann, Sven and Collins, Francis S and Cusi, Daniele and den Heijer, Martin and Eiriksdottir, Gudny and Gejman, Pablo V and Hall, Alistair S and Hamsten, Anders and Huikuri, Heikki V and Iribarren, Carlos and K{\"a}h{\"o}nen, Mika and Kaprio, Jaakko and Kathiresan, Sekar and Kiemeney, Lambertus and Kocher, Thomas and Launer, Lenore J and Lehtim{\"a}ki, Terho and Melander, Olle and Mosley, Tom H and Musk, Arthur W and Nieminen, Markku S and O{\textquoteright}Donnell, Christopher J and Ohlsson, Claes and Oostra, Ben and Palmer, Lyle J and Raitakari, Olli and Ridker, Paul M and Rioux, John D and Rissanen, Aila and Rivolta, Carlo and Schunkert, Heribert and Shuldiner, Alan R and Siscovick, David S and Stumvoll, Michael and T{\"o}njes, Anke and Tuomilehto, Jaakko and van Ommen, Gert-Jan and Viikari, Jorma and Heath, Andrew C and Martin, Nicholas G and Montgomery, Grant W and Province, Michael A and Kayser, Manfred and Arnold, Alice M and Atwood, Larry D and Boerwinkle, Eric and Chanock, Stephen J and Deloukas, Panos and Gieger, Christian and Gr{\"o}nberg, Henrik and Hall, Per and Hattersley, Andrew T and Hengstenberg, Christian and Hoffman, Wolfgang and Lathrop, G Mark and Salomaa, Veikko and Schreiber, Stefan and Uda, Manuela and Waterworth, Dawn and Wright, Alan F and Assimes, Themistocles L and Barroso, In{\^e}s and Hofman, Albert and Mohlke, Karen L and Boomsma, Dorret I and Caulfield, Mark J and Cupples, L Adrienne and Erdmann, Jeanette and Fox, Caroline S and Gudnason, Vilmundur and Gyllensten, Ulf and Harris, Tamara B and Hayes, Richard B and Jarvelin, Marjo-Riitta and Mooser, Vincent and Munroe, Patricia B and Ouwehand, Willem H and Penninx, Brenda W and Pramstaller, Peter P and Quertermous, Thomas and Rudan, Igor and Samani, Nilesh J and Spector, Timothy D and V{\"o}lzke, Henry and Watkins, Hugh and Wilson, James F and Groop, Leif C and Haritunians, Talin and Hu, Frank B and Kaplan, Robert C and Metspalu, Andres and North, Kari E and Schlessinger, David and Wareham, Nicholas J and Hunter, David J and O{\textquoteright}Connell, Jeffrey R and Strachan, David P and Wichmann, H-Erich and Borecki, Ingrid B and van Duijn, Cornelia M and Schadt, Eric E and Thorsteinsdottir, Unnur and Peltonen, Leena and Uitterlinden, Andr{\'e} G and Visscher, Peter M and Chatterjee, Nilanjan and Loos, Ruth J F and Boehnke, Michael and McCarthy, Mark I and Ingelsson, Erik and Lindgren, Cecilia M and Abecasis, Goncalo R and Stefansson, Kari and Frayling, Timothy M and Hirschhorn, Joel N} } @article {1150, title = {Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function.}, journal = {Nat Genet}, volume = {42}, year = {2010}, month = {2010 Jan}, pages = {45-52}, abstract = {Spirometric measures of lung function are heritable traits that reflect respiratory health and predict morbidity and mortality. We meta-analyzed genome-wide association studies for two clinically important lung-function measures: forced expiratory volume in the first second (FEV(1)) and its ratio to forced vital capacity (FEV(1)/FVC), an indicator of airflow obstruction. This meta-analysis included 20,890 participants of European ancestry from four CHARGE Consortium studies: Atherosclerosis Risk in Communities, Cardiovascular Health Study, Framingham Heart Study and Rotterdam Study. We identified eight loci associated with FEV(1)/FVC (HHIP, GPR126, ADAM19, AGER-PPT2, FAM13A, PTCH1, PID1 and HTR4) and one locus associated with FEV(1) (INTS12-GSTCD-NPNT) at or near genome-wide significance (P < 5 x 10(-8)) in the CHARGE Consortium dataset. Our findings may offer insights into pulmonary function and pathogenesis of chronic lung disease.
}, keywords = {Databases, Genetic, Female, Forced Expiratory Volume, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Lung, Lung Diseases, Male, Meta-Analysis as Topic, Polymorphism, Single Nucleotide, Spirometry, Vital Capacity}, issn = {1546-1718}, doi = {10.1038/ng.500}, author = {Hancock, Dana B and Eijgelsheim, Mark and Wilk, Jemma B and Gharib, Sina A and Loehr, Laura R and Marciante, Kristin D and Franceschini, Nora and van Durme, Yannick M T A and Chen, Ting-Hsu and Barr, R Graham and Schabath, Matthew B and Couper, David J and Brusselle, Guy G and Psaty, Bruce M and van Duijn, Cornelia M and Rotter, Jerome I and Uitterlinden, Andr{\'e} G and Hofman, Albert and Punjabi, Naresh M and Rivadeneira, Fernando and Morrison, Alanna C and Enright, Paul L and North, Kari E and Heckbert, Susan R and Lumley, Thomas and Stricker, Bruno H C and O{\textquoteright}Connor, George T and London, Stephanie J} } @article {1236, title = {Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution.}, journal = {Nat Genet}, volume = {42}, year = {2010}, month = {2010 Nov}, pages = {949-60}, abstract = {Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 {\texttimes} 10$^{-}$$^{9}$ to P = 1.8 {\texttimes} 10$^{-}$$^{4}$$^{0}$) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 {\texttimes} 10$^{-}${\textthreesuperior} to P = 1.2 {\texttimes} 10$^{-}${\textonesuperior}{\textthreesuperior}). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
}, keywords = {Adipose Tissue, Age Factors, Chromosome Mapping, Female, Genome, Human, Genome-Wide Association Study, Humans, Male, Meta-Analysis as Topic, Polymorphism, Single Nucleotide, Sex Characteristics, Waist-Hip Ratio}, issn = {1546-1718}, doi = {10.1038/ng.685}, author = {Heid, Iris M and Jackson, Anne U and Randall, Joshua C and Winkler, Thomas W and Qi, Lu and Steinthorsdottir, Valgerdur and Thorleifsson, Gudmar and Zillikens, M Carola and Speliotes, Elizabeth K and M{\"a}gi, Reedik and Workalemahu, Tsegaselassie and White, Charles C and Bouatia-Naji, Nabila and Harris, Tamara B and Berndt, Sonja I and Ingelsson, Erik and Willer, Cristen J and Weedon, Michael N and Luan, Jian{\textquoteright}an and Vedantam, Sailaja and Esko, T{\~o}nu and Kilpel{\"a}inen, Tuomas O and Kutalik, Zolt{\'a}n and Li, Shengxu and Monda, Keri L and Dixon, Anna L and Holmes, Christopher C and Kaplan, Lee M and Liang, Liming and Min, Josine L and Moffatt, Miriam F and Molony, Cliona and Nicholson, George and Schadt, Eric E and Zondervan, Krina T and Feitosa, Mary F and Ferreira, Teresa and Lango Allen, Hana and Weyant, Robert J and Wheeler, Eleanor and Wood, Andrew R and Estrada, Karol and Goddard, Michael E and Lettre, Guillaume and Mangino, Massimo and Nyholt, Dale R and Purcell, Shaun and Smith, Albert Vernon and Visscher, Peter M and Yang, Jian and McCarroll, Steven A and Nemesh, James and Voight, Benjamin F and Absher, Devin and Amin, Najaf and Aspelund, Thor and Coin, Lachlan and Glazer, Nicole L and Hayward, Caroline and Heard-Costa, Nancy L and Hottenga, Jouke-Jan and Johansson, Asa and Johnson, Toby and Kaakinen, Marika and Kapur, Karen and Ketkar, Shamika and Knowles, Joshua W and Kraft, Peter and Kraja, Aldi T and Lamina, Claudia and Leitzmann, Michael F and McKnight, Barbara and Morris, Andrew P and Ong, Ken K and Perry, John R B and Peters, Marjolein J and Polasek, Ozren and Prokopenko, Inga and Rayner, Nigel W and Ripatti, Samuli and Rivadeneira, Fernando and Robertson, Neil R and Sanna, Serena and Sovio, Ulla and Surakka, Ida and Teumer, Alexander and van Wingerden, Sophie and Vitart, Veronique and Zhao, Jing Hua and Cavalcanti-Proen{\c c}a, Christine and Chines, Peter S and Fisher, Eva and Kulzer, Jennifer R and Lecoeur, C{\'e}cile and Narisu, Narisu and Sandholt, Camilla and Scott, Laura J and Silander, Kaisa and Stark, Klaus and Tammesoo, Mari-Liis and Teslovich, Tanya M and Timpson, Nicholas John and Watanabe, Richard M and Welch, Ryan and Chasman, Daniel I and Cooper, Matthew N and Jansson, John-Olov and Kettunen, Johannes and Lawrence, Robert W and Pellikka, Niina and Perola, Markus and Vandenput, Liesbeth and Alavere, Helene and Almgren, Peter and Atwood, Larry D and Bennett, Amanda J and Biffar, Reiner and Bonnycastle, Lori L and Bornstein, Stefan R and Buchanan, Thomas A and Campbell, Harry and Day, Ian N M and Dei, Mariano and D{\"o}rr, Marcus and Elliott, Paul and Erdos, Michael R and Eriksson, Johan G and Freimer, Nelson B and Fu, Mao and Gaget, Stefan and Geus, Eco J C and Gjesing, Anette P and Grallert, Harald and Gr{\"a}ssler, J{\"u}rgen and Groves, Christopher J and Guiducci, Candace and Hartikainen, Anna-Liisa and Hassanali, Neelam and Havulinna, Aki S and Herzig, Karl-Heinz and Hicks, Andrew A and Hui, Jennie and Igl, Wilmar and Jousilahti, Pekka and Jula, Antti and Kajantie, Eero and Kinnunen, Leena and Kolcic, Ivana and Koskinen, Seppo and Kovacs, Peter and Kroemer, Heyo K and Krzelj, Vjekoslav and Kuusisto, Johanna and Kvaloy, Kirsti and Laitinen, Jaana and Lantieri, Olivier and Lathrop, G Mark and Lokki, Marja-Liisa and Luben, Robert N and Ludwig, Barbara and McArdle, Wendy L and McCarthy, Anne and Morken, Mario A and Nelis, Mari and Neville, Matt J and Par{\'e}, Guillaume and Parker, Alex N and Peden, John F and Pichler, Irene and Pietil{\"a}inen, Kirsi H and Platou, Carl G P and Pouta, Anneli and Ridderstr{\r a}le, Martin and Samani, Nilesh J and Saramies, Jouko and Sinisalo, Juha and Smit, Jan H and Strawbridge, Rona J and Stringham, Heather M and Swift, Amy J and Teder-Laving, Maris and Thomson, Brian and Usala, Gianluca and van Meurs, Joyce B J and van Ommen, Gert-Jan and Vatin, Vincent and Volpato, Claudia B and Wallaschofski, Henri and Walters, G Bragi and Widen, Elisabeth and Wild, Sarah H and Willemsen, Gonneke and Witte, Daniel R and Zgaga, Lina and Zitting, Paavo and Beilby, John P and James, Alan L and K{\"a}h{\"o}nen, Mika and Lehtim{\"a}ki, Terho and Nieminen, Markku S and Ohlsson, Claes and Palmer, Lyle J and Raitakari, Olli and Ridker, Paul M and Stumvoll, Michael and T{\"o}njes, Anke and Viikari, Jorma and Balkau, Beverley and Ben-Shlomo, Yoav and Bergman, Richard N and Boeing, Heiner and Smith, George Davey and Ebrahim, Shah and Froguel, Philippe and Hansen, Torben and Hengstenberg, Christian and Hveem, Kristian and Isomaa, Bo and J{\o}rgensen, Torben and Karpe, Fredrik and Khaw, Kay-Tee and Laakso, Markku and Lawlor, Debbie A and Marre, Michel and Meitinger, Thomas and Metspalu, Andres and Midthjell, Kristian and Pedersen, Oluf and Salomaa, Veikko and Schwarz, Peter E H and Tuomi, Tiinamaija and Tuomilehto, Jaakko and Valle, Timo T and Wareham, Nicholas J and Arnold, Alice M and Beckmann, Jacques S and Bergmann, Sven and Boerwinkle, Eric and Boomsma, Dorret I and Caulfield, Mark J and Collins, Francis S and Eiriksdottir, Gudny and Gudnason, Vilmundur and Gyllensten, Ulf and Hamsten, Anders and Hattersley, Andrew T and Hofman, Albert and Hu, Frank B and Illig, Thomas and Iribarren, Carlos and Jarvelin, Marjo-Riitta and Kao, W H Linda and Kaprio, Jaakko and Launer, Lenore J and Munroe, Patricia B and Oostra, Ben and Penninx, Brenda W and Pramstaller, Peter P and Psaty, Bruce M and Quertermous, Thomas and Rissanen, Aila and Rudan, Igor and Shuldiner, Alan R and Soranzo, Nicole and Spector, Timothy D and Syv{\"a}nen, Ann-Christine and Uda, Manuela and Uitterlinden, Andre and V{\"o}lzke, Henry and Vollenweider, Peter and Wilson, James F and Witteman, Jacqueline C and Wright, Alan F and Abecasis, Goncalo R and Boehnke, Michael and Borecki, Ingrid B and Deloukas, Panos and Frayling, Timothy M and Groop, Leif C and Haritunians, Talin and Hunter, David J and Kaplan, Robert C and North, Kari E and O{\textquoteright}Connell, Jeffrey R and Peltonen, Leena and Schlessinger, David and Strachan, David P and Hirschhorn, Joel N and Assimes, Themistocles L and Wichmann, H-Erich and Thorsteinsdottir, Unnur and van Duijn, Cornelia M and Stefansson, Kari and Cupples, L Adrienne and Loos, Ruth J F and Barroso, In{\^e}s and McCarthy, Mark I and Fox, Caroline S and Mohlke, Karen L and Lindgren, Cecilia M} } @article {1347, title = {Association of genetic variants and incident coronary heart disease in multiethnic cohorts: the PAGE study.}, journal = {Circ Cardiovasc Genet}, volume = {4}, year = {2011}, month = {2011 Dec}, pages = {661-72}, abstract = {BACKGROUND: Genome-wide association studies identified several single nucleotide polymorphisms (SNP) associated with prevalent coronary heart disease (CHD), but less is known of associations with incident CHD. The association of 13 published CHD SNPs was examined in 5 ancestry groups of 4 large US prospective cohorts.
METHODS AND RESULTS: The analyses included incident coronary events over an average 9.1 to 15.7 follow-up person-years in up to 26 617 white individuals (6626 events), 8018 black individuals (914 events), 1903 Hispanic individuals (113 events), 3669 American Indian individuals (595 events), and 885 Asian/Pacific Islander individuals (66 events). We used Cox proportional hazards models (with additive mode of inheritance) adjusted for age, sex, and ancestry (as needed). Nine loci were statistically associated with incident CHD events in white participants: 9p21 (rs10757278; P=4.7 {\texttimes} 10(-41)), 16q23.1 (rs2549513; P=0.0004), 6p24.1 (rs499818; P=0.0002), 2q36.3 (rs2943634; P=6.7 {\texttimes} 10(-6)), MTHFD1L (rs6922269, P=5.1 {\texttimes} 10(-10)), APOE (rs429358; P=2.7{\texttimes}10(-18)), ZNF627 (rs4804611; P=5.0 {\texttimes} 10(-8)), CXCL12 (rs501120; P=1.4 {\texttimes} 10(-6)) and LPL (rs268; P=2.7 {\texttimes} 10(-17)). The 9p21 region showed significant between-study heterogeneity, with larger effects in individuals age 55 years or younger and in women. Inclusion of coronary revascularization procedures among the incident CHD events introduced heterogeneity. The SNPs were not associated with CHD in black participants, and associations varied in other US minorities.
CONCLUSIONS: Prospective analyses of white participants replicated several reported cross-sectional CHD-SNP associations.
}, keywords = {Aged, Aged, 80 and over, Continental Population Groups, Coronary Disease, Female, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Prospective Studies}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.111.960096}, author = {Franceschini, Nora and Carty, Cara and B{\r u}zkov{\'a}, Petra and Reiner, Alex P and Garrett, Tiana and Lin, Yi and V{\"o}ckler, Jens-S and Hindorff, Lucia A and Cole, Shelley A and Boerwinkle, Eric and Lin, Dan-Yu and Bookman, Ebony and Best, Lyle G and Bella, Jonathan N and Eaton, Charles and Greenland, Philip and Jenny, Nancy and North, Kari E and Taverna, Darin and Young, Alicia M and Deelman, Ewa and Kooperberg, Charles and Psaty, Bruce and Heiss, Gerardo} } @article {1274, title = {A bivariate genome-wide approach to metabolic syndrome: STAMPEED consortium.}, journal = {Diabetes}, volume = {60}, year = {2011}, month = {2011 Apr}, pages = {1329-39}, abstract = {OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of \~{}2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from \~{}9\% of the variance in triglycerides, 5.8\% of high-density lipoprotein cholesterol, 3.6\% of fasting glucose, and 1.4\% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.
}, keywords = {Adult, Aged, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Meta-Analysis as Topic, Metabolic Syndrome, Middle Aged, Phenotype, Polymorphism, Single Nucleotide}, issn = {1939-327X}, doi = {10.2337/db10-1011}, author = {Kraja, Aldi T and Vaidya, Dhananjay and Pankow, James S and Goodarzi, Mark O and Assimes, Themistocles L and Kullo, Iftikhar J and Sovio, Ulla and Mathias, Rasika A and Sun, Yan V and Franceschini, Nora and Absher, Devin and Li, Guo and Zhang, Qunyuan and Feitosa, Mary F and Glazer, Nicole L and Haritunians, Talin and Hartikainen, Anna-Liisa and Knowles, Joshua W and North, Kari E and Iribarren, Carlos and Kral, Brian and Yanek, Lisa and O{\textquoteright}Reilly, Paul F and McCarthy, Mark I and Jaquish, Cashell and Couper, David J and Chakravarti, Aravinda and Psaty, Bruce M and Becker, Lewis C and Province, Michael A and Boerwinkle, Eric and Quertermous, Thomas and Palotie, Leena and Jarvelin, Marjo-Riitta and Becker, Diane M and Kardia, Sharon L R and Rotter, Jerome I and Chen, Yii-Der Ida and Borecki, Ingrid B} } @article {1568, title = {A gene-centric association scan for Coagulation Factor VII levels in European and African Americans: the Candidate Gene Association Resource (CARe) Consortium.}, journal = {Hum Mol Genet}, volume = {20}, year = {2011}, month = {2011 Sep 01}, pages = {3525-34}, abstract = {Polymorphisms in several distinct genomic regions, including the F7 gene, were recently associated with factor VII (FVII) levels in European Americans (EAs). The genetic determinants of FVII in African Americans (AAs) are unknown. We used a 50,000 single nucleotide polymorphism (SNP) gene-centric array having dense coverage of over 2,000 candidate genes for cardiovascular disease (CVD) pathways in a community-based sample of 16,324 EA and 3898 AA participants from the Candidate Gene Association Resource (CARe) consortium. Our aim was the discovery of new genomic loci and more detailed characterization of existing loci associated with FVII levels. In EAs, we identified three new loci associated with FVII, of which APOA5 on chromosome 11q23 and HNF4A on chromosome 20q12-13 were replicated in a sample of 4289 participants from the Whitehall II study. We confirmed four previously reported FVII-associated loci (GCKR, MS4A6A, F7 and PROCR) in CARe EA samples. In AAs, the F7 and PROCR regions were significantly associated with FVII. Several of the FVII-associated regions are known to be associated with lipids and other cardiovascular-related traits. At the F7 locus, there was evidence of at least five independently associated SNPs in EAs and three independent signals in AAs. Though the variance in FVII explained by the existing loci is substantial (20\% in EA and 10\% in AA), larger sample sizes and investigation of lower frequency variants may be required to identify additional FVII-associated loci in EAs and AAs and further clarify the relationship between FVII and other CVD risk factors.
}, keywords = {Adult, African Americans, Aged, Cardiovascular Diseases, European Continental Ancestry Group, Factor VII, Female, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide}, issn = {1460-2083}, doi = {10.1093/hmg/ddr264}, author = {Taylor, Kira C and Lange, Leslie A and Zabaneh, Delilah and Lange, Ethan and Keating, Brendan J and Tang, Weihong and Smith, Nicholas L and Delaney, Joseph A and Kumari, Meena and Hingorani, Aroon and North, Kari E and Kivimaki, Mika and Tracy, Russell P and O{\textquoteright}Donnell, Christopher J and Folsom, Aaron R and Green, David and Humphries, Steve E and Reiner, Alexander P} } @article {1303, title = {Genetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Jun}, pages = {e1002138}, abstract = {For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS-identified variants in diverse population-based studies. We genotyped 49 GWAS-identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (~20,000), African American (~9,000), American Indian (~6,000), Mexican American/Hispanic (~2,500), Japanese/East Asian (~690), and Pacific Islander/Native Hawaiian (~175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92\%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48\%, 61\%, and 57\%), American Indians (45\%, 64\%, and 77\%), and Mexican Americans/Hispanics (57\%, 56\%, and 86\%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits.
}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Continental Population Groups, Female, Gene Frequency, Genetics, Population, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Lipid Metabolism, Lipoproteins, HDL, Lipoproteins, LDL, Male, Middle Aged, Molecular Epidemiology, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Triglycerides, Young Adult}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002138}, author = {Dumitrescu, Logan and Carty, Cara L and Taylor, Kira and Schumacher, Fredrick R and Hindorff, Lucia A and Ambite, Jos{\'e} L and Anderson, Garnet and Best, Lyle G and Brown-Gentry, Kristin and B{\r u}zkov{\'a}, Petra and Carlson, Christopher S and Cochran, Barbara and Cole, Shelley A and Devereux, Richard B and Duggan, Dave and Eaton, Charles B and Fornage, Myriam and Franceschini, Nora and Haessler, Jeff and Howard, Barbara V and Johnson, Karen C and Laston, Sandra and Kolonel, Laurence N and Lee, Elisa T and MacCluer, Jean W and Manolio, Teri A and Pendergrass, Sarah A and Quibrera, Miguel and Shohet, Ralph V and Wilkens, Lynne R and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Buyske, Steven and Kooperberg, Charles and North, Kari E and Crawford, Dana C} } @article {6096, title = {Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function.}, journal = {Nat Genet}, volume = {43}, year = {2011}, month = {2011 Sep 25}, pages = {1082-90}, abstract = {Pulmonary function measures reflect respiratory health and are used in the diagnosis of chronic obstructive pulmonary disease. We tested genome-wide association with forced expiratory volume in 1 second and the ratio of forced expiratory volume in 1 second to forced vital capacity in 48,201 individuals of European ancestry with follow up of the top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P < 5 {\texttimes} 10(-8)) with pulmonary function in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (also known as EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1 and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.
}, keywords = {Child, European Continental Ancestry Group, Genome-Wide Association Study, Humans, Pulmonary Disease, Chronic Obstructive, Respiratory Function Tests}, issn = {1546-1718}, doi = {10.1038/ng.941}, author = {Soler Artigas, Maria and Loth, Daan W and Wain, Louise V and Gharib, Sina A and Obeidat, Ma{\textquoteright}en and Tang, Wenbo and Zhai, Guangju and Zhao, Jing Hua and Smith, Albert Vernon and Huffman, Jennifer E and Albrecht, Eva and Jackson, Catherine M and Evans, David M and Cadby, Gemma and Fornage, Myriam and Manichaikul, Ani and Lopez, Lorna M and Johnson, Toby and Aldrich, Melinda C and Aspelund, Thor and Barroso, In{\^e}s and Campbell, Harry and Cassano, Patricia A and Couper, David J and Eiriksdottir, Gudny and Franceschini, Nora and Garcia, Melissa and Gieger, Christian and Gislason, Gauti Kjartan and Grkovic, Ivica and Hammond, Christopher J and Hancock, Dana B and Harris, Tamara B and Ramasamy, Adaikalavan and Heckbert, Susan R and Heli{\"o}vaara, Markku and Homuth, Georg and Hysi, Pirro G and James, Alan L and Jankovic, Stipan and Joubert, Bonnie R and Karrasch, Stefan and Klopp, Norman and Koch, Beate and Kritchevsky, Stephen B and Launer, Lenore J and Liu, Yongmei and Loehr, Laura R and Lohman, Kurt and Loos, Ruth J F and Lumley, Thomas and Al Balushi, Khalid A and Ang, Wei Q and Barr, R Graham and Beilby, John and Blakey, John D and Boban, Mladen and Boraska, Vesna and Brisman, Jonas and Britton, John R and Brusselle, Guy G and Cooper, Cyrus and Curjuric, Ivan and Dahgam, Santosh and Deary, Ian J and Ebrahim, Shah and Eijgelsheim, Mark and Francks, Clyde and Gaysina, Darya and Granell, Raquel and Gu, Xiangjun and Hankinson, John L and Hardy, Rebecca and Harris, Sarah E and Henderson, John and Henry, Amanda and Hingorani, Aroon D and Hofman, Albert and Holt, Patrick G and Hui, Jennie and Hunter, Michael L and Imboden, Medea and Jameson, Karen A and Kerr, Shona M and Kolcic, Ivana and Kronenberg, Florian and Liu, Jason Z and Marchini, Jonathan and McKeever, Tricia and Morris, Andrew D and Olin, Anna-Carin and Porteous, David J and Postma, Dirkje S and Rich, Stephen S and Ring, Susan M and Rivadeneira, Fernando and Rochat, Thierry and Sayer, Avan Aihie and Sayers, Ian and Sly, Peter D and Smith, George Davey and Sood, Akshay and Starr, John M and Uitterlinden, Andr{\'e} G and Vonk, Judith M and Wannamethee, S Goya and Whincup, Peter H and Wijmenga, Cisca and Williams, O Dale and Wong, Andrew and Mangino, Massimo and Marciante, Kristin D and McArdle, Wendy L and Meibohm, Bernd and Morrison, Alanna C and North, Kari E and Omenaas, Ernst and Palmer, Lyle J and Pietil{\"a}inen, Kirsi H and Pin, Isabelle and Pola Sbreve Ek, Ozren and Pouta, Anneli and Psaty, Bruce M and Hartikainen, Anna-Liisa and Rantanen, Taina and Ripatti, Samuli and Rotter, Jerome I and Rudan, Igor and Rudnicka, Alicja R and Schulz, Holger and Shin, So-Youn and Spector, Tim D and Surakka, Ida and Vitart, Veronique and V{\"o}lzke, Henry and Wareham, Nicholas J and Warrington, Nicole M and Wichmann, H-Erich and Wild, Sarah H and Wilk, Jemma B and Wjst, Matthias and Wright, Alan F and Zgaga, Lina and Zemunik, Tatijana and Pennell, Craig E and Nyberg, Fredrik and Kuh, Diana and Holloway, John W and Boezen, H Marike and Lawlor, Debbie A and Morris, Richard W and Probst-Hensch, Nicole and Kaprio, Jaakko and Wilson, James F and Hayward, Caroline and K{\"a}h{\"o}nen, Mika and Heinrich, Joachim and Musk, Arthur W and Jarvis, Deborah L and Gl{\"a}ser, Sven and Jarvelin, Marjo-Riitta and Ch Stricker, Bruno H and Elliott, Paul and O{\textquoteright}Connor, George T and Strachan, David P and London, Stephanie J and Hall, Ian P and Gudnason, Vilmundur and Tobin, Martin D} } @article {1313, title = {The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study.}, journal = {Am J Epidemiol}, volume = {174}, year = {2011}, month = {2011 Oct 01}, pages = {849-59}, abstract = {Genetic studies have identified thousands of variants associated with complex traits. However, most association studies are limited to populations of European descent and a single phenotype. The Population Architecture using Genomics and Epidemiology (PAGE) Study was initiated in 2008 by the National Human Genome Research Institute to investigate the epidemiologic architecture of well-replicated genetic variants associated with complex diseases in several large, ethnically diverse population-based studies. Combining DNA samples and hundreds of phenotypes from multiple cohorts, PAGE is well-suited to address generalization of associations and variability of effects in diverse populations; identify genetic and environmental modifiers; evaluate disease subtypes, intermediate phenotypes, and biomarkers; and investigate associations with novel phenotypes. PAGE investigators harmonize phenotypes across studies where possible and perform coordinated cohort-specific analyses and meta-analyses. PAGE researchers are genotyping thousands of genetic variants in up to 121,000 DNA samples from African-American, white, Hispanic/Latino, Asian/Pacific Islander, and American Indian participants. Initial analyses will focus on single nucleotide polymorphisms (SNPs) associated with obesity, lipids, cardiovascular disease, type 2 diabetes, inflammation, various cancers, and related biomarkers. PAGE SNPs are also assessed for pleiotropy using the "phenome-wide association study" approach, testing each SNP for associations with hundreds of phenotypes. PAGE data will be deposited into the National Center for Biotechnology Information{\textquoteright}s Database of Genotypes and Phenotypes and made available via a custom browser.
}, keywords = {Epidemiologic Methods, Epidemiologic Research Design, Ethnic Groups, Genetic Association Studies, Genetics, Population, Genome-Wide Association Study, Humans, Interinstitutional Relations, Multifactorial Inheritance, National Human Genome Research Institute (U.S.), Phenotype, Pilot Projects, Research Design, Risk Factors, United States}, issn = {1476-6256}, doi = {10.1093/aje/kwr160}, author = {Matise, Tara C and Ambite, Jose Luis and Buyske, Steven and Carlson, Christopher S and Cole, Shelley A and Crawford, Dana C and Haiman, Christopher A and Heiss, Gerardo and Kooperberg, Charles and Marchand, Loic Le and Manolio, Teri A and North, Kari E and Peters, Ulrike and Ritchie, Marylyn D and Hindorff, Lucia A and Haines, Jonathan L} } @article {1345, title = {A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains.}, journal = {PLoS Genet}, volume = {7}, year = {2011}, month = {2011 Oct}, pages = {e1002322}, abstract = {Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55\% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.
}, keywords = {African Americans, Apolipoprotein C-I, Blood Glucose, Dyslipidemias, European Continental Ancestry Group, Genetic Association Studies, Genetic Predisposition to Disease, Genome, Human, Humans, Metabolic Syndrome, Obesity, Abdominal, Phenotype, Phospholipase C gamma, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Ubiquitin-Protein Ligases, Vascular Diseases}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002322}, author = {Avery, Christy L and He, Qianchuan and North, Kari E and Ambite, Jos{\'e} L and Boerwinkle, Eric and Fornage, Myriam and Hindorff, Lucia A and Kooperberg, Charles and Meigs, James B and Pankow, James S and Pendergrass, Sarah A and Psaty, Bruce M and Ritchie, Marylyn D and Rotter, Jerome I and Taylor, Kent D and Wilkens, Lynne R and Heiss, Gerardo and Lin, Dan Yu} } @article {1359, title = {Association between chromosome 9p21 variants and the ankle-brachial index identified by a meta-analysis of 21 genome-wide association studies.}, journal = {Circ Cardiovasc Genet}, volume = {5}, year = {2012}, month = {2012 Feb 01}, pages = {100-12}, abstract = {BACKGROUND: Genetic determinants of peripheral arterial disease (PAD) remain largely unknown. To identify genetic variants associated with the ankle-brachial index (ABI), a noninvasive measure of PAD, we conducted a meta-analysis of genome-wide association study data from 21 population-based cohorts.
METHODS AND RESULTS: Continuous ABI and PAD (ABI <=0.9) phenotypes adjusted for age and sex were examined. Each study conducted genotyping and imputed data to the ≈2.5 million single nucleotide polymorphisms (SNPs) in HapMap. Linear and logistic regression models were used to test each SNP for association with ABI and PAD using additive genetic models. Study-specific data were combined using fixed effects inverse variance weighted meta-analyses. There were a total of 41 692 participants of European ancestry (≈60\% women, mean ABI 1.02 to 1.19), including 3409 participants with PAD and with genome-wide association study data available. In the discovery meta-analysis, rs10757269 on chromosome 9 near CDKN2B had the strongest association with ABI (β=-0.006, P=2.46{\texttimes}10(-8)). We sought replication of the 6 strongest SNP associations in 5 population-based studies and 3 clinical samples (n=16 717). The association for rs10757269 strengthened in the combined discovery and replication analysis (P=2.65{\texttimes}10(-9)). No other SNP associations for ABI or PAD achieved genome-wide significance. However, 2 previously reported candidate genes for PAD and 1 SNP associated with coronary artery disease were associated with ABI: DAB21P (rs13290547, P=3.6{\texttimes}10(-5)), CYBA (rs3794624, P=6.3{\texttimes}10(-5)), and rs1122608 (LDLR, P=0.0026).
CONCLUSIONS: Genome-wide association studies in more than 40 000 individuals identified 1 genome wide significant association on chromosome 9p21 with ABI. Two candidate genes for PAD and 1 SNP for coronary artery disease are associated with ABI.
}, keywords = {Adult, Age Factors, Aged, Aged, 80 and over, Alleles, Ankle Brachial Index, Chromosomes, Human, Pair 9, Cohort Studies, Cyclin-Dependent Kinase Inhibitor p15, Female, Genome-Wide Association Study, Genotype, HapMap Project, Humans, Logistic Models, Male, Middle Aged, Peripheral Vascular Diseases, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Sex Factors}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.111.961292}, author = {Murabito, Joanne M and White, Charles C and Kavousi, Maryam and Sun, Yan V and Feitosa, Mary F and Nambi, Vijay and Lamina, Claudia and Schillert, Arne and Coassin, Stefan and Bis, Joshua C and Broer, Linda and Crawford, Dana C and Franceschini, Nora and Frikke-Schmidt, Ruth and Haun, Margot and Holewijn, Suzanne and Huffman, Jennifer E and Hwang, Shih-Jen and Kiechl, Stefan and Kollerits, Barbara and Montasser, May E and Nolte, Ilja M and Rudock, Megan E and Senft, Andrea and Teumer, Alexander and van der Harst, Pim and Vitart, Veronique and Waite, Lindsay L and Wood, Andrew R and Wassel, Christina L and Absher, Devin M and Allison, Matthew A and Amin, Najaf and Arnold, Alice and Asselbergs, Folkert W and Aulchenko, Yurii and Bandinelli, Stefania and Barbalic, Maja and Boban, Mladen and Brown-Gentry, Kristin and Couper, David J and Criqui, Michael H and Dehghan, Abbas and den Heijer, Martin and Dieplinger, Benjamin and Ding, Jingzhong and D{\"o}rr, Marcus and Espinola-Klein, Christine and Felix, Stephan B and Ferrucci, Luigi and Folsom, Aaron R and Fraedrich, Gustav and Gibson, Quince and Goodloe, Robert and Gunjaca, Grgo and Haltmayer, Meinhard and Heiss, Gerardo and Hofman, Albert and Kieback, Arne and Kiemeney, Lambertus A and Kolcic, Ivana and Kullo, Iftikhar J and Kritchevsky, Stephen B and Lackner, Karl J and Li, Xiaohui and Lieb, Wolfgang and Lohman, Kurt and Meisinger, Christa and Melzer, David and Mohler, Emile R and Mudnic, Ivana and Mueller, Thomas and Navis, Gerjan and Oberhollenzer, Friedrich and Olin, Jeffrey W and O{\textquoteright}Connell, Jeff and O{\textquoteright}Donnell, Christopher J and Palmas, Walter and Penninx, Brenda W and Petersmann, Astrid and Polasek, Ozren and Psaty, Bruce M and Rantner, Barbara and Rice, Ken and Rivadeneira, Fernando and Rotter, Jerome I and Seldenrijk, Adrie and Stadler, Marietta and Summerer, Monika and Tanaka, Toshiko and Tybjaerg-Hansen, Anne and Uitterlinden, Andr{\'e} G and van Gilst, Wiek H and Vermeulen, Sita H and Wild, Sarah H and Wild, Philipp S and Willeit, Johann and Zeller, Tanja and Zemunik, Tatijana and Zgaga, Lina and Assimes, Themistocles L and Blankenberg, Stefan and Boerwinkle, Eric and Campbell, Harry and Cooke, John P and de Graaf, Jacqueline and Herrington, David and Kardia, Sharon L R and Mitchell, Braxton D and Murray, Anna and M{\"u}nzel, Thomas and Newman, Anne B and Oostra, Ben A and Rudan, Igor and Shuldiner, Alan R and Snieder, Harold and van Duijn, Cornelia M and V{\"o}lker, Uwe and Wright, Alan F and Wichmann, H-Erich and Wilson, James F and Witteman, Jacqueline C M and Liu, Yongmei and Hayward, Caroline and Borecki, Ingrid B and Ziegler, Andreas and North, Kari E and Cupples, L Adrienne and Kronenberg, Florian} } @article {6633, title = {Consistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium.}, journal = {Diabetes}, volume = {61}, year = {2012}, month = {2012 Jun}, pages = {1642-7}, abstract = {Common genetic risk variants for type 2 diabetes (T2D) have primarily been identified in populations of European and Asian ancestry. We tested whether the direction of association with 20 T2D risk variants generalizes across six major racial/ethnic groups in the U.S. as part of the Population Architecture using Genomics and Epidemiology Consortium (16,235 diabetes case and 46,122 control subjects of European American, African American, Hispanic, East Asian, American Indian, and Native Hawaiian ancestry). The percentage of positive (odds ratio [OR] >1 for putative risk allele) associations ranged from 69\% in American Indians to 100\% in European Americans. Of the nine variants where we observed significant heterogeneity of effect by racial/ethnic group (P(heterogeneity) < 0.05), eight were positively associated with risk (OR >1) in at least five groups. The marked directional consistency of association observed for most genetic variants across populations implies a shared functional common variant in each region. Fine-mapping of all loci will be required to reveal markers of risk that are important within and across populations.
}, keywords = {Adult, Aged, Aged, 80 and over, Alleles, Diabetes Mellitus, Type 2, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Metagenomics, Middle Aged, Population Groups, Risk, Risk Factors}, issn = {1939-327X}, doi = {10.2337/db11-1296}, author = {Haiman, Christopher A and Fesinmeyer, Megan D and Spencer, Kylee L and B{\r u}zkov{\'a}, Petra and Voruganti, V Saroja and Wan, Peggy and Haessler, Jeff and Franceschini, Nora and Monroe, Kristine R and Howard, Barbara V and Jackson, Rebecca D and Florez, Jose C and Kolonel, Laurence N and Buyske, Steven and Goodloe, Robert J and Liu, Simin and Manson, JoAnn E and Meigs, James B and Waters, Kevin and Mukamal, Kenneth J and Pendergrass, Sarah A and Shrader, Peter and Wilkens, Lynne R and Hindorff, Lucia A and Ambite, Jose Luis and North, Kari E and Peters, Ulrike and Crawford, Dana C and Le Marchand, Lo{\"\i}c and Pankow, James S} } @article {6634, title = {Evaluation of the metabochip genotyping array in African Americans and implications for fine mapping of GWAS-identified loci: the PAGE study.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e35651}, abstract = {The Metabochip is a custom genotyping array designed for replication and fine mapping of metabolic, cardiovascular, and anthropometric trait loci and includes low frequency variation content identified from the 1000 Genomes Project. It has 196,725 SNPs concentrated in 257 genomic regions. We evaluated the Metabochip in 5,863 African Americans; 89\% of all SNPs passed rigorous quality control with a call rate of 99.9\%. Two examples illustrate the value of fine mapping with the Metabochip in African-ancestry populations. At CELSR2/PSRC1/SORT1, we found the strongest associated SNP for LDL-C to be rs12740374 (p = 3.5 {\texttimes} 10(-11)), a SNP indistinguishable from multiple SNPs in European ancestry samples due to high correlation. Its distinct signal supports functional studies elsewhere suggesting a causal role in LDL-C. At CETP we found rs17231520, with risk allele frequency 0.07 in African Americans, to be associated with HDL-C (p = 7.2 {\texttimes} 10(-36)). This variant is very rare in Europeans and not tagged in common GWAS arrays, but was identified as associated with HDL-C in African Americans in a single-gene study. Our results, one narrowing the risk interval and the other revealing an associated variant not found in Europeans, demonstrate the advantages of high-density genotyping of common and rare variation for fine mapping of trait loci in African American samples.
}, keywords = {African Americans, Cardiovascular Diseases, Cholesterol Ester Transfer Proteins, Cholesterol, HDL, Cholesterol, LDL, Chromosomes, Human, Cohort Studies, Gene Frequency, Genome-Wide Association Study, Genotype, Humans, Metabolic Diseases, Polymorphism, Single Nucleotide, Quantitative Trait Loci}, issn = {1932-6203}, doi = {10.1371/journal.pone.0035651}, author = {Buyske, Steven and Wu, Ying and Carty, Cara L and Cheng, Iona and Assimes, Themistocles L and Dumitrescu, Logan and Hindorff, Lucia A and Mitchell, Sabrina and Ambite, Jose Luis and Boerwinkle, Eric and B{\r u}zkov{\'a}, Petra and Carlson, Chris S and Cochran, Barbara and Duggan, David and Eaton, Charles B and Fesinmeyer, Megan D and Franceschini, Nora and Haessler, Jeffrey and Jenny, Nancy and Kang, Hyun Min and Kooperberg, Charles and Lin, Yi and Le Marchand, Lo{\"\i}c and Matise, Tara C and Robinson, Jennifer G and Rodriguez, Carlos and Schumacher, Fredrick R and Voight, Benjamin F and Young, Alicia and Manolio, Teri A and Mohlke, Karen L and Haiman, Christopher A and Peters, Ulrike and Crawford, Dana C and North, Kari E} } @article {6083, title = {Fine-mapping and initial characterization of QT interval loci in African Americans.}, journal = {PLoS Genet}, volume = {8}, year = {2012}, month = {2012}, pages = {e1002870}, abstract = {The QT interval (QT) is heritable and its prolongation is a risk factor for ventricular tachyarrhythmias and sudden death. Most genetic studies of QT have examined European ancestral populations; however, the increased genetic diversity in African Americans provides opportunities to narrow association signals and identify population-specific variants. We therefore evaluated 6,670 SNPs spanning eleven previously identified QT loci in 8,644 African American participants from two Population Architecture using Genomics and Epidemiology (PAGE) studies: the Atherosclerosis Risk in Communities study and Women{\textquoteright}s Health Initiative Clinical Trial. Of the fifteen known independent QT variants at the eleven previously identified loci, six were significantly associated with QT in African American populations (P<=1.20{\texttimes}10(-4)): ATP1B1, PLN1, KCNQ1, NDRG4, and two NOS1AP independent signals. We also identified three population-specific signals significantly associated with QT in African Americans (P<=1.37{\texttimes}10(-5)): one at NOS1AP and two at ATP1B1. Linkage disequilibrium (LD) patterns in African Americans assisted in narrowing the region likely to contain the functional variants for several loci. For example, African American LD patterns showed that 0 SNPs were in LD with NOS1AP signal rs12143842, compared with European LD patterns that indicated 87 SNPs, which spanned 114.2 Kb, were in LD with rs12143842. Finally, bioinformatic-based characterization of the nine African American signals pointed to functional candidates located exclusively within non-coding regions, including predicted binding sites for transcription factors such as TBX5, which has been implicated in cardiac structure and conductance. In this detailed evaluation of QT loci, we identified several African Americans SNPs that better define the association with QT and successfully narrowed intervals surrounding established loci. These results demonstrate that the same loci influence variation in QT across multiple populations, that novel signals exist in African Americans, and that the SNPs identified as strong candidates for functional evaluation implicate gene regulatory dysfunction in QT prolongation.
}, keywords = {African Americans, Aged, Computational Biology, Electrocardiography, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Metagenomics, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Risk Factors, Tachycardia, United States}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1002870}, author = {Avery, Christy L and Sethupathy, Praveen and Buyske, Steven and He, Qianchuan and Lin, Dan-Yu and Arking, Dan E and Carty, Cara L and Duggan, David and Fesinmeyer, Megan D and Hindorff, Lucia A and Jeff, Janina M and Klein, Liviu and Patton, Kristen K and Peters, Ulrike and Shohet, Ralph V and Sotoodehnia, Nona and Young, Alicia M and Kooperberg, Charles and Haiman, Christopher A and Mohlke, Karen L and Whitsel, Eric A and North, Kari E} } @article {6175, title = {FTO genotype is associated with phenotypic variability of body mass index.}, journal = {Nature}, volume = {490}, year = {2012}, month = {2012 Oct 11}, pages = {267-72}, abstract = {There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using \~{}170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7\%, corresponding to a difference of \~{}0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
}, keywords = {Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Body Height, Body Mass Index, Co-Repressor Proteins, Female, Genetic Variation, Genome-Wide Association Study, Humans, Male, Nerve Tissue Proteins, Phenotype, Polymorphism, Single Nucleotide, Proteins, Repressor Proteins}, issn = {1476-4687}, doi = {10.1038/nature11401}, author = {Yang, Jian and Loos, Ruth J F and Powell, Joseph E and Medland, Sarah E and Speliotes, Elizabeth K and Chasman, Daniel I and Rose, Lynda M and Thorleifsson, Gudmar and Steinthorsdottir, Valgerdur and M{\"a}gi, Reedik and Waite, Lindsay and Smith, Albert Vernon and Yerges-Armstrong, Laura M and Monda, Keri L and Hadley, David and Mahajan, Anubha and Li, Guo and Kapur, Karen and Vitart, Veronique and Huffman, Jennifer E and Wang, Sophie R and Palmer, Cameron and Esko, T{\~o}nu and Fischer, Krista and Zhao, Jing Hua and Demirkan, Ayse and Isaacs, Aaron and Feitosa, Mary F and Luan, Jian{\textquoteright}an and Heard-Costa, Nancy L and White, Charles and Jackson, Anne U and Preuss, Michael and Ziegler, Andreas and Eriksson, Joel and Kutalik, Zolt{\'a}n and Frau, Francesca and Nolte, Ilja M and van Vliet-Ostaptchouk, Jana V and Hottenga, Jouke-Jan and Jacobs, Kevin B and Verweij, Niek and Goel, Anuj and Medina-G{\'o}mez, Carolina and Estrada, Karol and Bragg-Gresham, Jennifer Lynn and Sanna, Serena and Sidore, Carlo and Tyrer, Jonathan and Teumer, Alexander and Prokopenko, Inga and Mangino, Massimo and Lindgren, Cecilia M and Assimes, Themistocles L and Shuldiner, Alan R and Hui, Jennie and Beilby, John P and McArdle, Wendy L and Hall, Per and Haritunians, Talin and Zgaga, Lina and Kolcic, Ivana and Polasek, Ozren and Zemunik, Tatijana and Oostra, Ben A and Junttila, M Juhani and Gr{\"o}nberg, Henrik and Schreiber, Stefan and Peters, Annette and Hicks, Andrew A and Stephens, Jonathan and Foad, Nicola S and Laitinen, Jaana and Pouta, Anneli and Kaakinen, Marika and Willemsen, Gonneke and Vink, Jacqueline M and Wild, Sarah H and Navis, Gerjan and Asselbergs, Folkert W and Homuth, Georg and John, Ulrich and Iribarren, Carlos and Harris, Tamara and Launer, Lenore and Gudnason, Vilmundur and O{\textquoteright}Connell, Jeffrey R and Boerwinkle, Eric and Cadby, Gemma and Palmer, Lyle J and James, Alan L and Musk, Arthur W and Ingelsson, Erik and Psaty, Bruce M and Beckmann, Jacques S and Waeber, G{\'e}rard and Vollenweider, Peter and Hayward, Caroline and Wright, Alan F and Rudan, Igor and Groop, Leif C and Metspalu, Andres and Khaw, Kay Tee and van Duijn, Cornelia M and Borecki, Ingrid B and Province, Michael A and Wareham, Nicholas J and Tardif, Jean-Claude and Huikuri, Heikki V and Cupples, L Adrienne and Atwood, Larry D and Fox, Caroline S and Boehnke, Michael and Collins, Francis S and Mohlke, Karen L and Erdmann, Jeanette and Schunkert, Heribert and Hengstenberg, Christian and Stark, Klaus and Lorentzon, Mattias and Ohlsson, Claes and Cusi, Daniele and Staessen, Jan A and van der Klauw, Melanie M and Pramstaller, Peter P and Kathiresan, Sekar and Jolley, Jennifer D and Ripatti, Samuli and Jarvelin, Marjo-Riitta and de Geus, Eco J C and Boomsma, Dorret I and Penninx, Brenda and Wilson, James F and Campbell, Harry and Chanock, Stephen J and van der Harst, Pim and Hamsten, Anders and Watkins, Hugh and Hofman, Albert and Witteman, Jacqueline C and Zillikens, M Carola and Uitterlinden, Andr{\'e} G and Rivadeneira, Fernando and Zillikens, M Carola and Kiemeney, Lambertus A and Vermeulen, Sita H and Abecasis, Goncalo R and Schlessinger, David and Schipf, Sabine and Stumvoll, Michael and T{\"o}njes, Anke and Spector, Tim D and North, Kari E and Lettre, Guillaume and McCarthy, Mark I and Berndt, Sonja I and Heath, Andrew C and Madden, Pamela A F and Nyholt, Dale R and Montgomery, Grant W and Martin, Nicholas G and McKnight, Barbara and Strachan, David P and Hill, William G and Snieder, Harold and Ridker, Paul M and Thorsteinsdottir, Unnur and Stefansson, Kari and Frayling, Timothy M and Hirschhorn, Joel N and Goddard, Michael E and Visscher, Peter M} } @article {5864, title = {Genetic determinants of the ankle-brachial index: a meta-analysis of a cardiovascular candidate gene 50K SNP panel in the candidate gene association resource (CARe) consortium.}, journal = {Atherosclerosis}, volume = {222}, year = {2012}, month = {2012 May}, pages = {138-47}, abstract = {BACKGROUND: Candidate gene association studies for peripheral artery disease (PAD), including subclinical disease assessed with the ankle-brachial index (ABI), have been limited by the modest number of genes examined. We conducted a two stage meta-analysis of \~{}50,000 SNPs across \~{}2100 candidate genes to identify genetic variants for ABI.
METHODS AND RESULTS: We studied subjects of European ancestry from 8 studies (n=21,547, 55\% women, mean age 44-73 years) and African American ancestry from 5 studies (n=7267, 60\% women, mean age 41-73 years) involved in the candidate gene association resource (CARe) consortium. In each ethnic group, additive genetic models were used (with each additional copy of the minor allele corresponding to the given beta) to test each SNP for association with continuous ABI (excluding ABI>1.40) and PAD (defined as ABI<0.90) using linear or logistic regression with adjustment for known PAD risk factors and population stratification. We then conducted a fixed-effects inverse-variance weighted meta-analyses considering a p<2{\texttimes}10(-6) to denote statistical significance.
RESULTS: In the European ancestry discovery meta-analyses, rs2171209 in SYTL3 (β=-0.007, p=6.02{\texttimes}10(-7)) and rs290481 in TCF7L2 (β=-0.008, p=7.01{\texttimes}10(-7)) were significantly associated with ABI. None of the SNP associations for PAD were significant, though a SNP in CYP2B6 (p=4.99{\texttimes}10(-5)) was among the strongest associations. These 3 genes are linked to key PAD risk factors (lipoprotein(a), type 2 diabetes, and smoking behavior, respectively). We sought replication in 6 population-based and 3 clinical samples (n=15,440) for rs290481 and rs2171209. However, in the replication stage (rs2171209, p=0.75; rs290481, p=0.19) and in the combined discovery and replication analysis the SNP-ABI associations were no longer significant (rs2171209, p=1.14{\texttimes}10(-3); rs290481, p=8.88{\texttimes}10(-5)). In African Americans, none of the SNP associations for ABI or PAD achieved an experiment-wide level of significance.
CONCLUSIONS: Genetic determinants of ABI and PAD remain elusive. Follow-up of these preliminary findings may uncover important biology given the known gene-risk factor associations. New and more powerful approaches to PAD gene discovery are warranted.
}, keywords = {Adult, African Americans, Aged, Ankle Brachial Index, Aryl Hydrocarbon Hydroxylases, Cytochrome P-450 CYP2B6, European Continental Ancestry Group, Female, Humans, Male, Middle Aged, Oxidoreductases, N-Demethylating, Peripheral Arterial Disease, Polymorphism, Single Nucleotide, Risk Factors, Transcription Factor 7-Like 2 Protein}, issn = {1879-1484}, doi = {10.1016/j.atherosclerosis.2012.01.039}, author = {Wassel, Christina L and Lamina, Claudia and Nambi, Vijay and Coassin, Stefan and Mukamal, Kenneth J and Ganesh, Santhi K and Jacobs, David R and Franceschini, Nora and Papanicolaou, George J and Gibson, Quince and Yanek, Lisa R and van der Harst, Pim and Ferguson, Jane F and Crawford, Dana C and Waite, Lindsay L and Allison, Matthew A and Criqui, Michael H and McDermott, Mary M and Mehra, Reena and Cupples, L Adrienne and Hwang, Shih-Jen and Redline, Susan and Kaplan, Robert C and Heiss, Gerardo and Rotter, Jerome I and Boerwinkle, Eric and Taylor, Herman A and Eraso, Luis H and Haun, Margot and Li, Mingyao and Meisinger, Christa and O{\textquoteright}Connell, Jeffrey R and Shuldiner, Alan R and Tybj{\ae}rg-Hansen, Anne and Frikke-Schmidt, Ruth and Kollerits, Barbara and Rantner, Barbara and Dieplinger, Benjamin and Stadler, Marietta and Mueller, Thomas and Haltmayer, Meinhard and Klein-Weigel, Peter and Summerer, Monika and Wichmann, H-Erich and Asselbergs, Folkert W and Navis, Gerjan and Mateo Leach, Irene and Brown-Gentry, Kristin and Goodloe, Robert and Assimes, Themistocles L and Becker, Diane M and Cooke, John P and Absher, Devin M and Olin, Jeffrey W and Mitchell, Braxton D and Reilly, Muredach P and Mohler, Emile R and North, Kari E and Reiner, Alexander P and Kronenberg, Florian and Murabito, Joanne M} } @article {6092, title = {Genome-wide association studies identify CHRNA5/3 and HTR4 in the development of airflow obstruction.}, journal = {Am J Respir Crit Care Med}, volume = {186}, year = {2012}, month = {2012 Oct 01}, pages = {622-32}, abstract = {RATIONALE: Genome-wide association studies (GWAS) have identified loci influencing lung function, but fewer genes influencing chronic obstructive pulmonary disease (COPD) are known.
OBJECTIVES: Perform meta-analyses of GWAS for airflow obstruction, a key pathophysiologic characteristic of COPD assessed by spirometry, in population-based cohorts examining all participants, ever smokers, never smokers, asthma-free participants, and more severe cases.
METHODS: Fifteen cohorts were studied for discovery (3,368 affected; 29,507 unaffected), and a population-based family study and a meta-analysis of case-control studies were used for replication and regional follow-up (3,837 cases; 4,479 control subjects). Airflow obstruction was defined as FEV(1) and its ratio to FVC (FEV(1)/FVC) both less than their respective lower limits of normal as determined by published reference equations.
MEASUREMENTS AND MAIN RESULTS: The discovery meta-analyses identified one region on chromosome 15q25.1 meeting genome-wide significance in ever smokers that includes AGPHD1, IREB2, and CHRNA5/CHRNA3 genes. The region was also modestly associated among never smokers. Gene expression studies confirmed the presence of CHRNA5/3 in lung, airway smooth muscle, and bronchial epithelial cells. A single-nucleotide polymorphism in HTR4, a gene previously related to FEV(1)/FVC, achieved genome-wide statistical significance in combined meta-analysis. Top single-nucleotide polymorphisms in ADAM19, RARB, PPAP2B, and ADAMTS19 were nominally replicated in the COPD meta-analysis.
CONCLUSIONS: These results suggest an important role for the CHRNA5/3 region as a genetic risk factor for airflow obstruction that may be independent of smoking and implicate the HTR4 gene in the etiology of airflow obstruction.
}, keywords = {Aged, Female, Forced Expiratory Volume, Genome-Wide Association Study, Humans, Male, Middle Aged, Nerve Tissue Proteins, Polymorphism, Single Nucleotide, Pulmonary Disease, Chronic Obstructive, Receptors, Nicotinic, Receptors, Serotonin, 5-HT4, Smoking, Vital Capacity}, issn = {1535-4970}, doi = {10.1164/rccm.201202-0366OC}, author = {Wilk, Jemma B and Shrine, Nick R G and Loehr, Laura R and Zhao, Jing Hua and Manichaikul, Ani and Lopez, Lorna M and Smith, Albert Vernon and Heckbert, Susan R and Smolonska, Joanna and Tang, Wenbo and Loth, Daan W and Curjuric, Ivan and Hui, Jennie and Cho, Michael H and Latourelle, Jeanne C and Henry, Amanda P and Aldrich, Melinda and Bakke, Per and Beaty, Terri H and Bentley, Amy R and Borecki, Ingrid B and Brusselle, Guy G and Burkart, Kristin M and Chen, Ting-Hsu and Couper, David and Crapo, James D and Davies, Gail and Dupuis, Jos{\'e}e and Franceschini, Nora and Gulsvik, Amund and Hancock, Dana B and Harris, Tamara B and Hofman, Albert and Imboden, Medea and James, Alan L and Khaw, Kay-Tee and Lahousse, Lies and Launer, Lenore J and Litonjua, Augusto and Liu, Yongmei and Lohman, Kurt K and Lomas, David A and Lumley, Thomas and Marciante, Kristin D and McArdle, Wendy L and Meibohm, Bernd and Morrison, Alanna C and Musk, Arthur W and Myers, Richard H and North, Kari E and Postma, Dirkje S and Psaty, Bruce M and Rich, Stephen S and Rivadeneira, Fernando and Rochat, Thierry and Rotter, Jerome I and Soler Artigas, Maria and Starr, John M and Uitterlinden, Andr{\'e} G and Wareham, Nicholas J and Wijmenga, Cisca and Zanen, Pieter and Province, Michael A and Silverman, Edwin K and Deary, Ian J and Palmer, Lyle J and Cassano, Patricia A and Gudnason, Vilmundur and Barr, R Graham and Loos, Ruth J F and Strachan, David P and London, Stephanie J and Boezen, H Marike and Probst-Hensch, Nicole and Gharib, Sina A and Hall, Ian P and O{\textquoteright}Connor, George T and Tobin, Martin D and Stricker, Bruno H} } @article {6088, title = {Genome-wide joint meta-analysis of SNP and SNP-by-smoking interaction identifies novel loci for pulmonary function.}, journal = {PLoS Genet}, volume = {8}, year = {2012}, month = {2012}, pages = {e1003098}, abstract = {Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV(1)), and its ratio to forced vital capacity (FEV(1)/FVC). Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA) of single nucleotide polymorphism (SNP) and SNP-by-smoking (ever-smoking or pack-years) associations on FEV(1) and FEV(1)/FVC across 19 studies (total N = 50,047). We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest P(JMA = )5.00{\texttimes}10(-11)), HLA-DQB1 and HLA-DQA2 (smallest P(JMA = )4.35{\texttimes}10(-9)), and KCNJ2 and SOX9 (smallest P(JMA = )1.28{\texttimes}10(-8)) were associated with FEV(1)/FVC or FEV(1) in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years) interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.
}, keywords = {Forced Expiratory Volume, Gene Expression, Genome, Human, Genome-Wide Association Study, HLA-DQ Antigens, HLA-DQ beta-Chains, Humans, Lung, Nerve Tissue Proteins, Polymorphism, Single Nucleotide, Potassium Channels, Inwardly Rectifying, Pulmonary Disease, Chronic Obstructive, Receptors, Cell Surface, Smoking, SOX9 Transcription Factor, Vital Capacity}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1003098}, author = {Hancock, Dana B and Soler Artigas, Maria and Gharib, Sina A and Henry, Amanda and Manichaikul, Ani and Ramasamy, Adaikalavan and Loth, Daan W and Imboden, Medea and Koch, Beate and McArdle, Wendy L and Smith, Albert V and Smolonska, Joanna and Sood, Akshay and Tang, Wenbo and Wilk, Jemma B and Zhai, Guangju and Zhao, Jing Hua and Aschard, Hugues and Burkart, Kristin M and Curjuric, Ivan and Eijgelsheim, Mark and Elliott, Paul and Gu, Xiangjun and Harris, Tamara B and Janson, Christer and Homuth, Georg and Hysi, Pirro G and Liu, Jason Z and Loehr, Laura R and Lohman, Kurt and Loos, Ruth J F and Manning, Alisa K and Marciante, Kristin D and Obeidat, Ma{\textquoteright}en and Postma, Dirkje S and Aldrich, Melinda C and Brusselle, Guy G and Chen, Ting-Hsu and Eiriksdottir, Gudny and Franceschini, Nora and Heinrich, Joachim and Rotter, Jerome I and Wijmenga, Cisca and Williams, O Dale and Bentley, Amy R and Hofman, Albert and Laurie, Cathy C and Lumley, Thomas and Morrison, Alanna C and Joubert, Bonnie R and Rivadeneira, Fernando and Couper, David J and Kritchevsky, Stephen B and Liu, Yongmei and Wjst, Matthias and Wain, Louise V and Vonk, Judith M and Uitterlinden, Andr{\'e} G and Rochat, Thierry and Rich, Stephen S and Psaty, Bruce M and O{\textquoteright}Connor, George T and North, Kari E and Mirel, Daniel B and Meibohm, Bernd and Launer, Lenore J and Khaw, Kay-Tee and Hartikainen, Anna-Liisa and Hammond, Christopher J and Gl{\"a}ser, Sven and Marchini, Jonathan and Kraft, Peter and Wareham, Nicholas J and V{\"o}lzke, Henry and Stricker, Bruno H C and Spector, Timothy D and Probst-Hensch, Nicole M and Jarvis, Deborah and Jarvelin, Marjo-Riitta and Heckbert, Susan R and Gudnason, Vilmundur and Boezen, H Marike and Barr, R Graham and Cassano, Patricia A and Strachan, David P and Fornage, Myriam and Hall, Ian P and Dupuis, Jos{\'e}e and Tobin, Martin D and London, Stephanie J} } @article {6179, title = {Impact of ancestry and common genetic variants on QT interval in African Americans.}, journal = {Circ Cardiovasc Genet}, volume = {5}, year = {2012}, month = {2012 Dec}, pages = {647-55}, abstract = {BACKGROUND: Ethnic differences in cardiac arrhythmia incidence have been reported, with a particularly high incidence of sudden cardiac death and low incidence of atrial fibrillation in individuals of African ancestry. We tested the hypotheses that African ancestry and common genetic variants are associated with prolonged duration of cardiac repolarization, a central pathophysiological determinant of arrhythmia, as measured by the electrocardiographic QT interval.
METHODS AND RESULTS: First, individual estimates of African and European ancestry were inferred from genome-wide single-nucleotide polymorphism (SNP) data in 7 population-based cohorts of African Americans (n=12,097) and regressed on measured QT interval from ECGs. Second, imputation was performed for 2.8 million SNPs, and a genome-wide association study of QT interval was performed in 10 cohorts (n=13,105). There was no evidence of association between genetic ancestry and QT interval (P=0.94). Genome-wide significant associations (P<2.5 {\texttimes} 10(-8)) were identified with SNPs at 2 loci, upstream of the genes NOS1AP (rs12143842, P=2 {\texttimes} 10(-15)) and ATP1B1 (rs1320976, P=2 {\texttimes} 10(-10)). The most significant SNP in NOS1AP was the same as the strongest SNP previously associated with QT interval in individuals of European ancestry. Low probability values (P<10(-5)) were observed for SNPs at several other loci previously identified in genome-wide association studies in individuals of European ancestry, including KCNQ1, KCNH2, LITAF, and PLN.
CONCLUSIONS: We observed no difference in duration of cardiac repolarization with global genetic indices of African American ancestry. In addition, our genome-wide association study extends the association of polymorphisms at several loci associated with repolarization in individuals of European ancestry to include individuals of African ancestry.
}, keywords = {Adult, African Americans, Aged, Electrocardiography, European Continental Ancestry Group, Female, Genealogy and Heraldry, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.112.962787}, author = {Smith, J Gustav and Avery, Christy L and Evans, Daniel S and Nalls, Michael A and Meng, Yan A and Smith, Erin N and Palmer, Cameron and Tanaka, Toshiko and Mehra, Reena and Butler, Anne M and Young, Taylor and Buxbaum, Sarah G and Kerr, Kathleen F and Berenson, Gerald S and Schnabel, Renate B and Li, Guo and Ellinor, Patrick T and Magnani, Jared W and Chen, Wei and Bis, Joshua C and Curb, J David and Hsueh, Wen-Chi and Rotter, Jerome I and Liu, Yongmei and Newman, Anne B and Limacher, Marian C and North, Kari E and Reiner, Alexander P and Quibrera, P Miguel and Schork, Nicholas J and Singleton, Andrew B and Psaty, Bruce M and Soliman, Elsayed Z and Solomon, Allen J and Srinivasan, Sathanur R and Alonso, Alvaro and Wallace, Robert and Redline, Susan and Zhang, Zhu-Ming and Post, Wendy S and Zonderman, Alan B and Taylor, Herman A and Murray, Sarah S and Ferrucci, Luigi and Arking, Dan E and Evans, Michele K and Fox, Ervin R and Sotoodehnia, Nona and Heckbert, Susan R and Whitsel, Eric A and Newton-Cheh, Christopher} } @article {6091, title = {Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways.}, journal = {Nat Genet}, volume = {44}, year = {2012}, month = {2012 Sep}, pages = {991-1005}, abstract = {Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.
}, keywords = {Adult, Animals, Blood Glucose, Fasting, Female, Gene Frequency, Genome-Wide Association Study, Humans, Insulin, Male, Metabolic Networks and Pathways, Mice, Osmolar Concentration, Quantitative Trait Loci}, issn = {1546-1718}, doi = {10.1038/ng.2385}, author = {Scott, Robert A and Lagou, Vasiliki and Welch, Ryan P and Wheeler, Eleanor and Montasser, May E and Luan, Jian{\textquoteright}an and M{\"a}gi, Reedik and Strawbridge, Rona J and Rehnberg, Emil and Gustafsson, Stefan and Kanoni, Stavroula and Rasmussen-Torvik, Laura J and Yengo, Loic and Lecoeur, C{\'e}cile and Shungin, Dmitry and Sanna, Serena and Sidore, Carlo and Johnson, Paul C D and Jukema, J Wouter and Johnson, Toby and Mahajan, Anubha and Verweij, Niek and Thorleifsson, Gudmar and Hottenga, Jouke-Jan and Shah, Sonia and Smith, Albert V and Sennblad, Bengt and Gieger, Christian and Salo, Perttu and Perola, Markus and Timpson, Nicholas J and Evans, David M and Pourcain, Beate St and Wu, Ying and Andrews, Jeanette S and Hui, Jennie and Bielak, Lawrence F and Zhao, Wei and Horikoshi, Momoko and Navarro, Pau and Isaacs, Aaron and O{\textquoteright}Connell, Jeffrey R and Stirrups, Kathleen and Vitart, Veronique and Hayward, Caroline and Esko, T{\~o}nu and Mihailov, Evelin and Fraser, Ross M and Fall, Tove and Voight, Benjamin F and Raychaudhuri, Soumya and Chen, Han and Lindgren, Cecilia M and Morris, Andrew P and Rayner, Nigel W and Robertson, Neil and Rybin, Denis and Liu, Ching-Ti and Beckmann, Jacques S and Willems, Sara M and Chines, Peter S and Jackson, Anne U and Kang, Hyun Min and Stringham, Heather M and Song, Kijoung and Tanaka, Toshiko and Peden, John F and Goel, Anuj and Hicks, Andrew A and An, Ping and M{\"u}ller-Nurasyid, Martina and Franco-Cereceda, Anders and Folkersen, Lasse and Marullo, Letizia and Jansen, Hanneke and Oldehinkel, Albertine J and Bruinenberg, Marcel and Pankow, James S and North, Kari E and Forouhi, Nita G and Loos, Ruth J F and Edkins, Sarah and Varga, Tibor V and Hallmans, G{\"o}ran and Oksa, Heikki and Antonella, Mulas and Nagaraja, Ramaiah and Trompet, Stella and Ford, Ian and Bakker, Stephan J L and Kong, Augustine and Kumari, Meena and Gigante, Bruna and Herder, Christian and Munroe, Patricia B and Caulfield, Mark and Antti, Jula and Mangino, Massimo and Small, Kerrin and Miljkovic, Iva and Liu, Yongmei and Atalay, Mustafa and Kiess, Wieland and James, Alan L and Rivadeneira, Fernando and Uitterlinden, Andr{\'e} G and Palmer, Colin N A and Doney, Alex S F and Willemsen, Gonneke and Smit, Johannes H and Campbell, Susan and Polasek, Ozren and Bonnycastle, Lori L and Hercberg, Serge and Dimitriou, Maria and Bolton, Jennifer L and Fowkes, Gerard R and Kovacs, Peter and Lindstr{\"o}m, Jaana and Zemunik, Tatijana and Bandinelli, Stefania and Wild, Sarah H and Basart, Hanneke V and Rathmann, Wolfgang and Grallert, Harald and Maerz, Winfried and Kleber, Marcus E and Boehm, Bernhard O and Peters, Annette and Pramstaller, Peter P and Province, Michael A and Borecki, Ingrid B and Hastie, Nicholas D and Rudan, Igor and Campbell, Harry and Watkins, Hugh and Farrall, Martin and Stumvoll, Michael and Ferrucci, Luigi and Waterworth, Dawn M and Bergman, Richard N and Collins, Francis S and Tuomilehto, Jaakko and Watanabe, Richard M and de Geus, Eco J C and Penninx, Brenda W and Hofman, Albert and Oostra, Ben A and Psaty, Bruce M and Vollenweider, Peter and Wilson, James F and Wright, Alan F and Hovingh, G Kees and Metspalu, Andres and Uusitupa, Matti and Magnusson, Patrik K E and Kyvik, Kirsten O and Kaprio, Jaakko and Price, Jackie F and Dedoussis, George V and Deloukas, Panos and Meneton, Pierre and Lind, Lars and Boehnke, Michael and Shuldiner, Alan R and van Duijn, Cornelia M and Morris, Andrew D and Toenjes, Anke and Peyser, Patricia A and Beilby, John P and K{\"o}rner, Antje and Kuusisto, Johanna and Laakso, Markku and Bornstein, Stefan R and Schwarz, Peter E H and Lakka, Timo A and Rauramaa, Rainer and Adair, Linda S and Smith, George Davey and Spector, Tim D and Illig, Thomas and de Faire, Ulf and Hamsten, Anders and Gudnason, Vilmundur and Kivimaki, Mika and Hingorani, Aroon and Keinanen-Kiukaanniemi, Sirkka M and Saaristo, Timo E and Boomsma, Dorret I and Stefansson, Kari and van der Harst, Pim and Dupuis, Jos{\'e}e and Pedersen, Nancy L and Sattar, Naveed and Harris, Tamara B and Cucca, Francesco and Ripatti, Samuli and Salomaa, Veikko and Mohlke, Karen L and Balkau, Beverley and Froguel, Philippe and Pouta, Anneli and Jarvelin, Marjo-Riitta and Wareham, Nicholas J and Bouatia-Naji, Nabila and McCarthy, Mark I and Franks, Paul W and Meigs, James B and Teslovich, Tanya M and Florez, Jose C and Langenberg, Claudia and Ingelsson, Erik and Prokopenko, Inga and Barroso, In{\^e}s} } @article {6084, title = {Novel loci associated with PR interval in a genome-wide association study of 10 African American cohorts.}, journal = {Circ Cardiovasc Genet}, volume = {5}, year = {2012}, month = {2012 Dec}, pages = {639-46}, abstract = {BACKGROUND: The PR interval, as measured by the resting, standard 12-lead ECG, reflects the duration of atrial/atrioventricular nodal depolarization. Substantial evidence exists for a genetic contribution to PR, including genome-wide association studies that have identified common genetic variants at 9 loci influencing PR in populations of European and Asian descent. However, few studies have examined loci associated with PR in African Americans.
METHODS AND RESULTS: We present results from the largest genome-wide association study to date of PR in 13 415 adults of African descent from 10 cohorts. We tested for association between PR (ms) and ≈2.8 million genotyped and imputed single-nucleotide polymorphisms. Imputation was performed using HapMap 2 YRI and CEU panels. Study-specific results, adjusted for global ancestry and clinical correlates of PR, were meta-analyzed using the inverse variance method. Variation in genome-wide test statistic distributions was noted within studies (λ range: 0.9-1.1), although not after genomic control correction was applied to the overall meta-analysis (λ: 1.008). In addition to generalizing previously reported associations with MEIS1, SCN5A, ARHGAP24, CAV1, and TBX5 to African American populations at the genome-wide significance level (P<5.0 {\texttimes} 10(-8)), we also identified a novel locus: ITGA9, located in a region previously implicated in SCN5A expression. The 3p21 region harboring SCN5A also contained 2 additional independent secondary signals influencing PR (P<5.0 {\texttimes} 10(-8)).
CONCLUSIONS: This study demonstrates the ability to map novel loci in African Americans as well as the generalizability of loci associated with PR across populations of African, European, and Asian descent.
}, keywords = {Adult, African Americans, Cohort Studies, Electrocardiography, Female, Genetic Loci, Genome-Wide Association Study, Humans, Male, Meta-Analysis as Topic, Middle Aged, Polymorphism, Single Nucleotide}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.112.963991}, author = {Butler, Anne M and Yin, Xiaoyan and Evans, Daniel S and Nalls, Michael A and Smith, Erin N and Tanaka, Toshiko and Li, Guo and Buxbaum, Sarah G and Whitsel, Eric A and Alonso, Alvaro and Arking, Dan E and Benjamin, Emelia J and Berenson, Gerald S and Bis, Josh C and Chen, Wei and Deo, Rajat and Ellinor, Patrick T and Heckbert, Susan R and Heiss, Gerardo and Hsueh, Wen-Chi and Keating, Brendan J and Kerr, Kathleen F and Li, Yun and Limacher, Marian C and Liu, Yongmei and Lubitz, Steven A and Marciante, Kristin D and Mehra, Reena and Meng, Yan A and Newman, Anne B and Newton-Cheh, Christopher and North, Kari E and Palmer, Cameron D and Psaty, Bruce M and Quibrera, P Miguel and Redline, Susan and Reiner, Alex P and Rotter, Jerome I and Schnabel, Renate B and Schork, Nicholas J and Singleton, Andrew B and Smith, J Gustav and Soliman, Elsayed Z and Srinivasan, Sathanur R and Zhang, Zhu-Ming and Zonderman, Alan B and Ferrucci, Luigi and Murray, Sarah S and Evans, Michele K and Sotoodehnia, Nona and Magnani, Jared W and Avery, Christy L} } @article {1544, title = {Ultraconserved elements in the human genome: association and transmission analyses of highly constrained single-nucleotide polymorphisms.}, journal = {Genetics}, volume = {192}, year = {2012}, month = {2012 Sep}, pages = {253-66}, abstract = {Ultraconserved elements in the human genome likely harbor important biological functions as they are dosage sensitive and are able to direct tissue-specific expression. Because they are under purifying selection, variants in these elements may have a lower frequency in the population but a higher likelihood of association with complex traits. We tested a set of highly constrained SNPs (hcSNPs) distributed genome-wide among ultraconserved and nearly ultraconserved elements for association with seven traits related to reproductive (age at natural menopause, number of children, age at first child, and age at last child) and overall [longevity, body mass index (BMI), and height] fitness. Using up to 24,047 European-American samples from the National Heart, Lung, and Blood Institute Candidate Gene Association Resource (CARe), we observed an excess of associations with BMI and height. In an independent replication panel the most strongly associated SNPs showed an 8.4-fold enrichment of associations at the nominal level, including three variants in previously identified loci and one in a locus (DENND1A) previously shown to be associated with polycystic ovary syndrome. Finally, using 1430 family trios, we showed that the transmissions from heterozygous parents to offspring of the derived alleles of rare (frequency <= 0.5\%) hcSNPs are not biased, particularly after adjusting for the rates of genotype missingness and error in the data. The lack of transmission bias ruled out an immediately and strongly deleterious effect due to the rare derived alleles, consistent with the observation that mice homozygous for the deletion of ultraconserved elements showed no overt phenotype. Our study also illustrated the importance of carefully modeling potential technical confounders when analyzing genotype data of rare variants.
}, keywords = {Alleles, Animals, Body Height, Body Mass Index, Child, Conserved Sequence, Dogs, Evolution, Molecular, Female, Genetic Fitness, Genetic Variation, Genome, Human, Genotype, Humans, Inheritance Patterns, Male, Mice, Pedigree, Phenotype, Polymorphism, Single Nucleotide, Rats, Reproduction, Young Adult}, issn = {1943-2631}, doi = {10.1534/genetics.112.141945}, author = {Chiang, Charleston W K and Liu, Ching-Ti and Lettre, Guillaume and Lange, Leslie A and Jorgensen, Neal W and Keating, Brendan J and Vedantam, Sailaja and Nock, Nora L and Franceschini, Nora and Reiner, Alex P and Demerath, Ellen W and Boerwinkle, Eric and Rotter, Jerome I and Wilson, James G and North, Kari E and Papanicolaou, George J and Cupples, L Adrienne and Murabito, Joanne M and Hirschhorn, Joel N} } @article {6827, title = {Association of functional polymorphism rs2231142 (Q141K) in the ABCG2 gene with serum uric acid and gout in 4 US populations: the PAGE Study.}, journal = {Am J Epidemiol}, volume = {177}, year = {2013}, month = {2013 May 1}, pages = {923-32}, abstract = {A loss-of-function mutation (Q141K, rs2231142) in the ATP-binding cassette, subfamily G, member 2 gene (ABCG2) has been shown to be associated with serum uric acid levels and gout in Asians, Europeans, and European and African Americans; however, less is known about these associations in other populations. Rs2231142 was genotyped in 22,734 European Americans, 9,720 African Americans, 3,849 Mexican Americans, and 3,550 American Indians in the Population Architecture using Genomics and Epidemiology (PAGE) Study (2008-2012). Rs2231142 was significantly associated with serum uric acid levels (P = 2.37 {\texttimes} 10(-67), P = 3.98 {\texttimes} 10(-5), P = 6.97 {\texttimes} 10(-9), and P = 5.33 {\texttimes} 10(-4) in European Americans, African Americans, Mexican Americans, and American Indians, respectively) and gout (P = 2.83 {\texttimes} 10(-10), P = 0.01, and P = 0.01 in European Americans, African Americans, and Mexican Americans, respectively). Overall, the T allele was associated with a 0.24-mg/dL increase in serum uric acid level (P = 1.37 {\texttimes} 10(-80)) and a 1.75-fold increase in the odds of gout (P = 1.09 {\texttimes} 10(-12)). The association between rs2231142 and serum uric acid was significantly stronger in men, postmenopausal women, and hormone therapy users compared with their counterparts. The association with gout was also significantly stronger in men than in women. These results highlight a possible role of sex hormones in the regulation of ABCG2 urate transporter and its potential implications for the prevention, diagnosis, and treatment of hyperuricemia and gout.
}, keywords = {Adult, African Americans, Age Distribution, ATP-Binding Cassette Transporters, Comorbidity, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genetics, Population, Genome-Wide Association Study, Gout, Hormone Replacement Therapy, Humans, Indians, North American, Male, Mexican Americans, Middle Aged, Neoplasm Proteins, Polymorphism, Genetic, Postmenopause, Sex Distribution, United States, Uric Acid}, issn = {1476-6256}, doi = {10.1093/aje/kws330}, author = {Zhang, Lili and Spencer, Kylee L and Voruganti, V Saroja and Jorgensen, Neal W and Fornage, Myriam and Best, Lyle G and Brown-Gentry, Kristin D and Cole, Shelley A and Crawford, Dana C and Deelman, Ewa and Franceschini, Nora and Gaffo, Angelo L and Glenn, Kimberly R and Heiss, Gerardo and Jenny, Nancy S and K{\"o}ttgen, Anna and Li, Qiong and Liu, Kiang and Matise, Tara C and North, Kari E and Umans, Jason G and Kao, W H Linda} } @article {6065, title = {Effects of smoking on the genetic risk of obesity: the population architecture using genomics and epidemiology study.}, journal = {BMC Med Genet}, volume = {14}, year = {2013}, month = {2013 Jan 11}, pages = {6}, abstract = {BACKGROUND: Although smoking behavior is known to affect body mass index (BMI), the potential for smoking to influence genetic associations with BMI is largely unexplored.
METHODS: As part of the {\textquoteright}Population Architecture using Genomics and Epidemiology (PAGE){\textquoteright} Consortium, we investigated interaction between genetic risk factors associated with BMI and smoking for 10 single nucleotide polymorphisms (SNPs) previously identified in genome-wide association studies. We included 6 studies with a total of 56,466 subjects (16,750 African Americans (AA) and 39,716 European Americans (EA)). We assessed effect modification by testing an interaction term for each SNP and smoking (current vs. former/never) in the linear regression and by stratified analyses.
RESULTS: We did not observe strong evidence for interactions and only observed two interactions with p-values <0.1: for rs6548238/TMEM18, the risk allele (C) was associated with BMI only among AA females who were former/never smokers (β = 0.018, p = 0.002), vs. current smokers (β = 0.001, p = 0.95, p(interaction) = 0.10). For rs9939609/FTO, the A allele was more strongly associated with BMI among current smoker EA females (β = 0.017, p = 3.5 x 10(-5)), vs. former/never smokers (β = 0.006, p = 0.05, p(interaction) = 0.08).
CONCLUSIONS: These analyses provide limited evidence that smoking status may modify genetic effects of previously identified genetic risk factors for BMI. Larger studies are needed to follow up our results.
CLINICAL TRIAL REGISTRATION: NCT00000611.
}, keywords = {Adolescent, Adult, African Americans, Aged, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Body Mass Index, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Humans, Male, Membrane Proteins, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Proteins, Risk Factors, Smoking, Young Adult}, issn = {1471-2350}, doi = {10.1186/1471-2350-14-6}, author = {Fesinmeyer, Megan D and North, Kari E and Lim, Unhee and B{\r u}zkov{\'a}, Petra and Crawford, Dana C and Haessler, Jeffrey and Gross, Myron D and Fowke, Jay H and Goodloe, Robert and Love, Shelley-Ann and Graff, Misa and Carlson, Christopher S and Kuller, Lewis H and Matise, Tara C and Hong, Ching-Ping and Henderson, Brian E and Allen, Melissa and Rohde, Rebecca R and Mayo, Ping and Schnetz-Boutaud, Nathalie and Monroe, Kristine R and Ritchie, Marylyn D and Prentice, Ross L and Kolonel, Lawrence N and Manson, JoAnn E and Pankow, James and Hindorff, Lucia A and Franceschini, Nora and Wilkens, Lynne R and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Peters, Ulrike} } @article {6626, title = {Fine Mapping and Identification of BMI Loci in African Americans.}, journal = {Am J Hum Genet}, volume = {93}, year = {2013}, month = {2013 Oct 3}, pages = {661-71}, abstract = {Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8~{\texttimes} 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6~{\texttimes} 10(-8)) and DHX34 (rs4802349, p = 1.2~{\texttimes} 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.
}, keywords = {Adult, African Americans, Aged, Aged, 80 and over, Body Mass Index, Female, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Male, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Young Adult}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2013.08.012}, author = {Gong, Jian and Schumacher, Fredrick and Lim, Unhee and Hindorff, Lucia A and Haessler, Jeff and Buyske, Steven and Carlson, Christopher S and Rosse, Stephanie and B{\r u}zkov{\'a}, Petra and Fornage, Myriam and Gross, Myron and Pankratz, Nathan and Pankow, James S and Schreiner, Pamela J and Cooper, Richard and Ehret, Georg and Gu, C Charles and Houston, Denise and Irvin, Marguerite R and Jackson, Rebecca and Kuller, Lew and Henderson, Brian and Cheng, Iona and Wilkens, Lynne and Leppert, Mark and Lewis, Cora E and Li, Rongling and Nguyen, Khanh-Dung H and Goodloe, Robert and Farber-Eger, Eric and Boston, Jonathan and Dilks, Holli H and Ritchie, Marylyn D and Fowke, Jay and Pooler, Loreall and Graff, Misa and Fernandez-Rhodes, Lindsay and Cochrane, Barbara and Boerwinkle, Eric and Kooperberg, Charles and Matise, Tara C and Le Marchand, Lo{\"\i}c and Crawford, Dana C and Haiman, Christopher A and North, Kari E and Peters, Ulrike} } @article {6289, title = {Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study.}, journal = {PLoS Biol}, volume = {11}, year = {2013}, month = {2013 Sep}, pages = {e1001661}, abstract = {The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25\% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.
}, keywords = {African Americans, Asian Americans, Body Mass Index, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Hispanic Americans, Humans, Indians, North American, Lipids, Metagenomics, Oceanic Ancestry Group, Polymorphism, Single Nucleotide}, issn = {1545-7885}, doi = {10.1371/journal.pbio.1001661}, author = {Carlson, Christopher S and Matise, Tara C and North, Kari E and Haiman, Christopher A and Fesinmeyer, Megan D and Buyske, Steven and Schumacher, Fredrick R and Peters, Ulrike and Franceschini, Nora and Ritchie, Marylyn D and Duggan, David J and Spencer, Kylee L and Dumitrescu, Logan and Eaton, Charles B and Thomas, Fridtjof and Young, Alicia and Carty, Cara and Heiss, Gerardo and Le Marchand, Lo{\"\i}c and Crawford, Dana C and Hindorff, Lucia A and Kooperberg, Charles L} } @article {6631, title = {Genetic risk factors for BMI and obesity in an ethnically diverse population: results from the population architecture using genomics and epidemiology (PAGE) study.}, journal = {Obesity (Silver Spring)}, volume = {21}, year = {2013}, month = {2013 Apr}, pages = {835-46}, abstract = {OBJECTIVE: Several genome-wide association studies (GWAS) have demonstrated that common genetic variants contribute to obesity. However, studies of this complex trait have focused on ancestrally European populations, despite the high prevalence of obesity in some minority groups.
DESIGN AND METHODS: As part of the "Population Architecture using Genomics and Epidemiology (PAGE)" Consortium, we investigated the association between 13 GWAS-identified single-nucleotide polymorphisms (SNPs) and BMI and obesity in 69,775 subjects, including 6,149 American Indians, 15,415 African-Americans, 2,438 East Asians, 7,346 Hispanics, 604 Pacific Islanders, and 37,823 European Americans. For the BMI-increasing allele of each SNP, we calculated β coefficients using linear regression (for BMI) and risk estimates using logistic regression (for obesity defined as BMI >= 30) followed by fixed-effects meta-analysis to combine results across PAGE sites. Analyses stratified by racial/ethnic group assumed an additive genetic model and were adjusted for age, sex, and current smoking. We defined "replicating SNPs" (in European Americans) and "generalizing SNPs" (in other racial/ethnic groups) as those associated with an allele frequency-specific increase in BMI.
RESULTS: By this definition, we replicated 9/13 SNP associations (5 out of 8 loci) in European Americans. We also generalized 8/13 SNP associations (5/8 loci) in East Asians, 7/13 (5/8 loci) in African Americans, 6/13 (4/8 loci) in Hispanics, 5/8 in Pacific Islanders (5/8 loci), and 5/9 (4/8 loci) in American Indians.
CONCLUSION: Linkage disequilibrium patterns suggest that tagSNPs selected for European Americans may not adequately tag causal variants in other ancestry groups. Accordingly, fine-mapping in large samples is needed to comprehensively explore these loci in diverse populations.
}, keywords = {Alleles, Body Mass Index, Ethnic Groups, Gene Frequency, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Metagenomics, Obesity, Phenotype, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1930-739X}, doi = {10.1002/oby.20268}, author = {Fesinmeyer, Megan D and North, Kari E and Ritchie, Marylyn D and Lim, Unhee and Franceschini, Nora and Wilkens, Lynne R and Gross, Myron D and B{\r u}zkov{\'a}, Petra and Glenn, Kimberly and Quibrera, P Miguel and Fernandez-Rhodes, Lindsay and Li, Qiong and Fowke, Jay H and Li, Rongling and Carlson, Christopher S and Prentice, Ross L and Kuller, Lewis H and Manson, JoAnn E and Matise, Tara C and Cole, Shelley A and Chen, Christina T L and Howard, Barbara V and Kolonel, Laurence N and Henderson, Brian E and Monroe, Kristine R and Crawford, Dana C and Hindorff, Lucia A and Buyske, Steven and Haiman, Christopher A and Le Marchand, Lo{\"\i}c and Peters, Ulrike} } @article {6290, title = {Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {BMC Med Genet}, volume = {14}, year = {2013}, month = {2013 Sep 25}, pages = {98}, abstract = {BACKGROUND: Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S.
METHODS: As part of the {\textquoteright}Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites.
RESULTS: Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 {\texttimes} 10-15), versus 3/9 in AA (p= 0.03 to 6 {\texttimes} 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only.
CONCLUSIONS: Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.
}, keywords = {Adaptor Proteins, Signal Transducing, Adult, African Americans, Aged, Alleles, Asian Continental Ancestry Group, Blood Glucose, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Female, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Genomics, Hispanic Americans, Humans, Indians, North American, Insulin, Male, Middle Aged, Polymorphism, Single Nucleotide, Transcription Factor 7-Like 2 Protein}, issn = {1471-2350}, doi = {10.1186/1471-2350-14-98}, author = {Fesinmeyer, Megan D and Meigs, James B and North, Kari E and Schumacher, Fredrick R and B{\r u}zkov{\'a}, Petra and Franceschini, Nora and Haessler, Jeffrey and Goodloe, Robert and Spencer, Kylee L and Voruganti, Venkata Saroja and Howard, Barbara V and Jackson, Rebecca and Kolonel, Laurence N and Liu, Simin and Manson, JoAnn E and Monroe, Kristine R and Mukamal, Kenneth and Dilks, Holli H and Pendergrass, Sarah A and Nato, Andrew and Wan, Peggy and Wilkens, Lynne R and Le Marchand, Lo{\"\i}c and Ambite, Jose Luis and Buyske, Steven and Florez, Jose C and Crawford, Dana C and Hindorff, Lucia A and Haiman, Christopher A and Peters, Ulrike and Pankow, James S} } @article {6287, title = {Genome-wide association of body fat distribution in African ancestry populations suggests new loci.}, journal = {PLoS Genet}, volume = {9}, year = {2013}, month = {2013}, pages = {e1003681}, abstract = {Central obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values<5.0 {\texttimes} 10(-6) were followed-up (stage 2) in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA) WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24{\texttimes}10(-8) for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48{\texttimes}10(-8) for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5 {\texttimes} 10(-8); RREB1: p = 5.7 {\texttimes} 10(-8)). Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region) in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02). In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept that there are fat distribution loci that are independent of generalized adiposity.
}, keywords = {Adiposity, African Continental Ancestry Group, Body Fat Distribution, European Continental Ancestry Group, Female, Genetic Loci, Genome-Wide Association Study, Humans, Male, Obesity, Polymorphism, Single Nucleotide, Waist-Hip Ratio}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1003681}, author = {Liu, Ching-Ti and Monda, Keri L and Taylor, Kira C and Lange, Leslie and Demerath, Ellen W and Palmas, Walter and Wojczynski, Mary K and Ellis, Jaclyn C and Vitolins, Mara Z and Liu, Simin and Papanicolaou, George J and Irvin, Marguerite R and Xue, Luting and Griffin, Paula J and Nalls, Michael A and Adeyemo, Adebowale and Liu, Jiankang and Li, Guo and Ruiz-Narvaez, Edward A and Chen, Wei-Min and Chen, Fang and Henderson, Brian E and Millikan, Robert C and Ambrosone, Christine B and Strom, Sara S and Guo, Xiuqing and Andrews, Jeanette S and Sun, Yan V and Mosley, Thomas H and Yanek, Lisa R and Shriner, Daniel and Haritunians, Talin and Rotter, Jerome I and Speliotes, Elizabeth K and Smith, Megan and Rosenberg, Lynn and Mychaleckyj, Josyf and Nayak, Uma and Spruill, Ida and Garvey, W Timothy and Pettaway, Curtis and Nyante, Sarah and Bandera, Elisa V and Britton, Angela F and Zonderman, Alan B and Rasmussen-Torvik, Laura J and Chen, Yii-Der Ida and Ding, Jingzhong and Lohman, Kurt and Kritchevsky, Stephen B and Zhao, Wei and Peyser, Patricia A and Kardia, Sharon L R and Kabagambe, Edmond and Broeckel, Ulrich and Chen, Guanjie and Zhou, Jie and Wassertheil-Smoller, Sylvia and Neuhouser, Marian L and Rampersaud, Evadnie and Psaty, Bruce and Kooperberg, Charles and Manson, JoAnn E and Kuller, Lewis H and Ochs-Balcom, Heather M and Johnson, Karen C and Sucheston, Lara and Ordovas, Jose M and Palmer, Julie R and Haiman, Christopher A and McKnight, Barbara and Howard, Barbara V and Becker, Diane M and Bielak, Lawrence F and Liu, Yongmei and Allison, Matthew A and Grant, Struan F A and Burke, Gregory L and Patel, Sanjay R and Schreiner, Pamela J and Borecki, Ingrid B and Evans, Michele K and Taylor, Herman and Sale, Mich{\`e}le M and Howard, Virginia and Carlson, Christopher S and Rotimi, Charles N and Cushman, Mary and Harris, Tamara B and Reiner, Alexander P and Cupples, L Adrienne and North, Kari E and Fox, Caroline S} } @article {6152, title = {Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture.}, journal = {Nat Genet}, volume = {45}, year = {2013}, month = {2013 May}, pages = {501-12}, abstract = {Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
}, keywords = {Anthropometry, Body Height, Body Mass Index, Case-Control Studies, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Meta-Analysis as Topic, Obesity, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Waist-Hip Ratio}, issn = {1546-1718}, doi = {10.1038/ng.2606}, author = {Berndt, Sonja I and Gustafsson, Stefan and M{\"a}gi, Reedik and Ganna, Andrea and Wheeler, Eleanor and Feitosa, Mary F and Justice, Anne E and Monda, Keri L and Croteau-Chonka, Damien C and Day, Felix R and Esko, T{\~o}nu and Fall, Tove and Ferreira, Teresa and Gentilini, Davide and Jackson, Anne U and Luan, Jian{\textquoteright}an and Randall, Joshua C and Vedantam, Sailaja and Willer, Cristen J and Winkler, Thomas W and Wood, Andrew R and Workalemahu, Tsegaselassie and Hu, Yi-Juan and Lee, Sang Hong and Liang, Liming and Lin, Dan-Yu and Min, Josine L and Neale, Benjamin M and Thorleifsson, Gudmar and Yang, Jian and Albrecht, Eva and Amin, Najaf and Bragg-Gresham, Jennifer L and Cadby, Gemma and den Heijer, Martin and Eklund, Niina and Fischer, Krista and Goel, Anuj and Hottenga, Jouke-Jan and Huffman, Jennifer E and Jarick, Ivonne and Johansson, Asa and Johnson, Toby and Kanoni, Stavroula and Kleber, Marcus E and K{\"o}nig, Inke R and Kristiansson, Kati and Kutalik, Zolt{\'a}n and Lamina, Claudia and Lecoeur, C{\'e}cile and Li, Guo and Mangino, Massimo and McArdle, Wendy L and Medina-G{\'o}mez, Carolina and M{\"u}ller-Nurasyid, Martina and Ngwa, Julius S and Nolte, Ilja M and Paternoster, Lavinia and Pechlivanis, Sonali and Perola, Markus and Peters, Marjolein J and Preuss, Michael and Rose, Lynda M and Shi, Jianxin and Shungin, Dmitry and Smith, Albert Vernon and Strawbridge, Rona J and Surakka, Ida and Teumer, Alexander and Trip, Mieke D and Tyrer, Jonathan and van Vliet-Ostaptchouk, Jana V and Vandenput, Liesbeth and Waite, Lindsay L and Zhao, Jing Hua and Absher, Devin and Asselbergs, Folkert W and Atalay, Mustafa and Attwood, Antony P and Balmforth, Anthony J and Basart, Hanneke and Beilby, John and Bonnycastle, Lori L and Brambilla, Paolo and Bruinenberg, Marcel and Campbell, Harry and Chasman, Daniel I and Chines, Peter S and Collins, Francis S and Connell, John M and Cookson, William O and de Faire, Ulf and de Vegt, Femmie and Dei, Mariano and Dimitriou, Maria and Edkins, Sarah and Estrada, Karol and Evans, David M and Farrall, Martin and Ferrario, Marco M and Ferrieres, Jean and Franke, Lude and Frau, Francesca and Gejman, Pablo V and Grallert, Harald and Gr{\"o}nberg, Henrik and Gudnason, Vilmundur and Hall, Alistair S and Hall, Per and Hartikainen, Anna-Liisa and Hayward, Caroline and Heard-Costa, Nancy L and Heath, Andrew C and Hebebrand, Johannes and Homuth, Georg and Hu, Frank B and Hunt, Sarah E and Hypp{\"o}nen, Elina and Iribarren, Carlos and Jacobs, Kevin B and Jansson, John-Olov and Jula, Antti and K{\"a}h{\"o}nen, Mika and Kathiresan, Sekar and Kee, Frank and Khaw, Kay-Tee and Kivimaki, Mika and Koenig, Wolfgang and Kraja, Aldi T and Kumari, Meena and Kuulasmaa, Kari and Kuusisto, Johanna and Laitinen, Jaana H and Lakka, Timo A and Langenberg, Claudia and Launer, Lenore J and Lind, Lars and Lindstr{\"o}m, Jaana and Liu, Jianjun and Liuzzi, Antonio and Lokki, Marja-Liisa and Lorentzon, Mattias and Madden, Pamela A and Magnusson, Patrik K and Manunta, Paolo and Marek, Diana and M{\"a}rz, Winfried and Mateo Leach, Irene and McKnight, Barbara and Medland, Sarah E and Mihailov, Evelin and Milani, Lili and Montgomery, Grant W and Mooser, Vincent and M{\"u}hleisen, Thomas W and Munroe, Patricia B and Musk, Arthur W and Narisu, Narisu and Navis, Gerjan and Nicholson, George and Nohr, Ellen A and Ong, Ken K and Oostra, Ben A and Palmer, Colin N A and Palotie, Aarno and Peden, John F and Pedersen, Nancy and Peters, Annette and Polasek, Ozren and Pouta, Anneli and Pramstaller, Peter P and Prokopenko, Inga and P{\"u}tter, Carolin and Radhakrishnan, Aparna and Raitakari, Olli and Rendon, Augusto and Rivadeneira, Fernando and Rudan, Igor and Saaristo, Timo E and Sambrook, Jennifer G and Sanders, Alan R and Sanna, Serena and Saramies, Jouko and Schipf, Sabine and Schreiber, Stefan and Schunkert, Heribert and Shin, So-Youn and Signorini, Stefano and Sinisalo, Juha and Skrobek, Boris and Soranzo, Nicole and Stan{\v c}{\'a}kov{\'a}, Alena and Stark, Klaus and Stephens, Jonathan C and Stirrups, Kathleen and Stolk, Ronald P and Stumvoll, Michael and Swift, Amy J and Theodoraki, Eirini V and Thorand, Barbara and Tr{\'e}gou{\"e}t, David-Alexandre and Tremoli, Elena and van der Klauw, Melanie M and van Meurs, Joyce B J and Vermeulen, Sita H and Viikari, Jorma and Virtamo, Jarmo and Vitart, Veronique and Waeber, G{\'e}rard and Wang, Zhaoming and Widen, Elisabeth and Wild, Sarah H and Willemsen, Gonneke and Winkelmann, Bernhard R and Witteman, Jacqueline C M and Wolffenbuttel, Bruce H R and Wong, Andrew and Wright, Alan F and Zillikens, M Carola and Amouyel, Philippe and Boehm, Bernhard O and Boerwinkle, Eric and Boomsma, Dorret I and Caulfield, Mark J and Chanock, Stephen J and Cupples, L Adrienne and Cusi, Daniele and Dedoussis, George V and Erdmann, Jeanette and Eriksson, Johan G and Franks, Paul W and Froguel, Philippe and Gieger, Christian and Gyllensten, Ulf and Hamsten, Anders and Harris, Tamara B and Hengstenberg, Christian and Hicks, Andrew A and Hingorani, Aroon and Hinney, Anke and Hofman, Albert and Hovingh, Kees G and Hveem, Kristian and Illig, Thomas and Jarvelin, Marjo-Riitta and J{\"o}ckel, Karl-Heinz and Keinanen-Kiukaanniemi, Sirkka M and Kiemeney, Lambertus A and Kuh, Diana and Laakso, Markku and Lehtim{\"a}ki, Terho and Levinson, Douglas F and Martin, Nicholas G and Metspalu, Andres and Morris, Andrew D and Nieminen, Markku S and Nj{\o}lstad, Inger and Ohlsson, Claes and Oldehinkel, Albertine J and Ouwehand, Willem H and Palmer, Lyle J and Penninx, Brenda and Power, Chris and Province, Michael A and Psaty, Bruce M and Qi, Lu and Rauramaa, Rainer and Ridker, Paul M and Ripatti, Samuli and Salomaa, Veikko and Samani, Nilesh J and Snieder, Harold and S{\o}rensen, Thorkild I A and Spector, Timothy D and Stefansson, Kari and T{\"o}njes, Anke and Tuomilehto, Jaakko and Uitterlinden, Andr{\'e} G and Uusitupa, Matti and van der Harst, Pim and Vollenweider, Peter and Wallaschofski, Henri and Wareham, Nicholas J and Watkins, Hugh and Wichmann, H-Erich and Wilson, James F and Abecasis, Goncalo R and Assimes, Themistocles L and Barroso, In{\^e}s and Boehnke, Michael and Borecki, Ingrid B and Deloukas, Panos and Fox, Caroline S and Frayling, Timothy and Groop, Leif C and Haritunian, Talin and Heid, Iris M and Hunter, David and Kaplan, Robert C and Karpe, Fredrik and Moffatt, Miriam F and Mohlke, Karen L and O{\textquoteright}Connell, Jeffrey R and Pawitan, Yudi and Schadt, Eric E and Schlessinger, David and Steinthorsdottir, Valgerdur and Strachan, David P and Thorsteinsdottir, Unnur and van Duijn, Cornelia M and Visscher, Peter M and Di Blasio, Anna Maria and Hirschhorn, Joel N and Lindgren, Cecilia M and Morris, Andrew P and Meyre, David and Scherag, Andre and McCarthy, Mark I and Speliotes, Elizabeth K and North, Kari E and Loos, Ruth J F and Ingelsson, Erik} } @article {6163, title = {Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake.}, journal = {Am J Clin Nutr}, volume = {97}, year = {2013}, month = {2013 Jun}, pages = {1395-402}, abstract = {BACKGROUND: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.
OBJECTIVE: The objective of the study was to identify common genetic variants that are associated with macronutrient intake.
DESIGN: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 {\texttimes} 10(-6) were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data.
RESULTS: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β {\textpm} SE: 0.25 {\textpm} 0.04\%; P = 1.68 {\texttimes} 10(-8)) and lower fat (β {\textpm} SE: -0.21 {\textpm} 0.04\%; P = 1.57 {\texttimes} 10(-9)) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)-increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β {\textpm} SE: 0.10 {\textpm} 0.02\%; P = 9.96 {\texttimes} 10(-10)), independent of BMI (after adjustment for BMI, β {\textpm} SE: 0.08 {\textpm} 0.02\%; P = 3.15 {\texttimes} 10(-7)).
CONCLUSION: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).
}, keywords = {Alleles, Atherosclerosis, Body Mass Index, Dietary Carbohydrates, Dietary Fats, Dietary Proteins, Energy Intake, European Continental Ancestry Group, Fibroblast Growth Factors, Follow-Up Studies, Gene-Environment Interaction, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Life Style, Obesity, Polymorphism, Single Nucleotide, Prospective Studies, Quantitative Trait Loci, Surveys and Questionnaires}, issn = {1938-3207}, doi = {10.3945/ajcn.112.052183}, author = {Tanaka, Toshiko and Ngwa, Julius S and van Rooij, Frank J A and Zillikens, M Carola and Wojczynski, Mary K and Frazier-Wood, Alexis C and Houston, Denise K and Kanoni, Stavroula and Lemaitre, Rozenn N and Luan, Jian{\textquoteright}an and Mikkil{\"a}, Vera and Renstrom, Frida and Sonestedt, Emily and Zhao, Jing Hua and Chu, Audrey Y and Qi, Lu and Chasman, Daniel I and de Oliveira Otto, Marcia C and Dhurandhar, Emily J and Feitosa, Mary F and Johansson, Ingegerd and Khaw, Kay-Tee and Lohman, Kurt K and Manichaikul, Ani and McKeown, Nicola M and Mozaffarian, Dariush and Singleton, Andrew and Stirrups, Kathleen and Viikari, Jorma and Ye, Zheng and Bandinelli, Stefania and Barroso, In{\^e}s and Deloukas, Panos and Forouhi, Nita G and Hofman, Albert and Liu, Yongmei and Lyytik{\"a}inen, Leo-Pekka and North, Kari E and Dimitriou, Maria and Hallmans, G{\"o}ran and K{\"a}h{\"o}nen, Mika and Langenberg, Claudia and Ordovas, Jose M and Uitterlinden, Andr{\'e} G and Hu, Frank B and Kalafati, Ioanna-Panagiota and Raitakari, Olli and Franco, Oscar H and Johnson, Andrew and Emilsson, Valur and Schrack, Jennifer A and Semba, Richard D and Siscovick, David S and Arnett, Donna K and Borecki, Ingrid B and Franks, Paul W and Kritchevsky, Stephen B and Lehtim{\"a}ki, Terho and Loos, Ruth J F and Orho-Melander, Marju and Rotter, Jerome I and Wareham, Nicholas J and Witteman, Jacqueline C M and Ferrucci, Luigi and Dedoussis, George and Cupples, L Adrienne and Nettleton, Jennifer A} } @article {5879, title = {Higher magnesium intake is associated with lower fasting glucose and insulin, with no evidence of interaction with select genetic loci, in a meta-analysis of 15 CHARGE Consortium Studies.}, journal = {J Nutr}, volume = {143}, year = {2013}, month = {2013 Mar}, pages = {345-53}, abstract = {Favorable associations between magnesium intake and glycemic traits, such as fasting glucose and insulin, are observed in observational and clinical studies, but whether genetic variation affects these associations is largely unknown. We hypothesized that single nucleotide polymorphisms (SNPs) associated with either glycemic traits or magnesium metabolism affect the association between magnesium intake and fasting glucose and insulin. Fifteen studies from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided data from up to 52,684 participants of European descent without known diabetes. In fixed-effects meta-analyses, we quantified 1) cross-sectional associations of dietary magnesium intake with fasting glucose (mmol/L) and insulin (ln-pmol/L) and 2) interactions between magnesium intake and SNPs related to fasting glucose (16 SNPs), insulin (2 SNPs), or magnesium (8 SNPs) on fasting glucose and insulin. After adjustment for age, sex, energy intake, BMI, and behavioral risk factors, magnesium (per 50-mg/d increment) was inversely associated with fasting glucose [β = -0.009 mmol/L (95\% CI: -0.013, -0.005), P < 0.0001] and insulin [-0.020 ln-pmol/L (95\% CI: -0.024, -0.017), P < 0.0001]. No magnesium-related SNP or interaction between any SNP and magnesium reached significance after correction for multiple testing. However, rs2274924 in magnesium transporter-encoding TRPM6 showed a nominal association (uncorrected P = 0.03) with glucose, and rs11558471 in SLC30A8 and rs3740393 near CNNM2 showed a nominal interaction (uncorrected, both P = 0.02) with magnesium on glucose. Consistent with other studies, a higher magnesium intake was associated with lower fasting glucose and insulin. Nominal evidence of TRPM6 influence and magnesium interaction with select loci suggests that further investigation is warranted.
}, keywords = {Blood Glucose, Female, Genetic Loci, Humans, Insulin, Magnesium, Male, Polymorphism, Single Nucleotide, Trace Elements, TRPM Cation Channels}, issn = {1541-6100}, doi = {10.3945/jn.112.172049}, author = {Hruby, Adela and Ngwa, Julius S and Renstrom, Frida and Wojczynski, Mary K and Ganna, Andrea and Hallmans, G{\"o}ran and Houston, Denise K and Jacques, Paul F and Kanoni, Stavroula and Lehtim{\"a}ki, Terho and Lemaitre, Rozenn N and Manichaikul, Ani and North, Kari E and Ntalla, Ioanna and Sonestedt, Emily and Tanaka, Toshiko and van Rooij, Frank J A and Bandinelli, Stefania and Djouss{\'e}, Luc and Grigoriou, Efi and Johansson, Ingegerd and Lohman, Kurt K and Pankow, James S and Raitakari, Olli T and Riserus, Ulf and Yannakoulia, Mary and Zillikens, M Carola and Hassanali, Neelam and Liu, Yongmei and Mozaffarian, Dariush and Papoutsakis, Constantina and Syv{\"a}nen, Ann-Christine and Uitterlinden, Andr{\'e} G and Viikari, Jorma and Groves, Christopher J and Hofman, Albert and Lind, Lars and McCarthy, Mark I and Mikkil{\"a}, Vera and Mukamal, Kenneth and Franco, Oscar H and Borecki, Ingrid B and Cupples, L Adrienne and Dedoussis, George V and Ferrucci, Luigi and Hu, Frank B and Ingelsson, Erik and K{\"a}h{\"o}nen, Mika and Kao, W H Linda and Kritchevsky, Stephen B and Orho-Melander, Marju and Prokopenko, Inga and Rotter, Jerome I and Siscovick, David S and Witteman, Jacqueline C M and Franks, Paul W and Meigs, James B and McKeown, Nicola M and Nettleton, Jennifer A} } @article {6630, title = {The influence of obesity-related single nucleotide polymorphisms on BMI across the life course: the PAGE study.}, journal = {Diabetes}, volume = {62}, year = {2013}, month = {2013 May}, pages = {1763-7}, abstract = {Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among >34,000 European Americans, aged 18-100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near FTO, GNPDA2, MTCH2, TMEM18, and NEGR1) with BMI across four distinct epochs of adulthood: 1) young adulthood (ages 18-25 years), adulthood (ages 26-49 years), middle-age adulthood (ages 50-69 years), and older adulthood (ages >=70 years); or 2) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the FTO (rs8050136) variant with BMI across the four adulthood epochs (P = 0.0006), with larger effects in young adults relative to older adults (β [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m{\texttwosuperior}, respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of GNPDA2, MTCH2, TMEM18, and NEGR1 with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for FTO, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data.
}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Aging, Body Mass Index, Cohort Studies, Cross-Sectional Studies, European Continental Ancestry Group, Female, Genetic Association Studies, Health Surveys, Humans, Male, Middle Aged, Obesity, Polymorphism, Single Nucleotide, Proteins, United States, Young Adult}, issn = {1939-327X}, doi = {10.2337/db12-0863}, author = {Graff, Mariaelisa and Gordon-Larsen, Penny and Lim, Unhee and Fowke, Jay H and Love, Shelly-Ann and Fesinmeyer, Megan and Wilkens, Lynne R and Vertilus, Shawyntee and Ritchie, Marilyn D and Prentice, Ross L and Pankow, Jim and Monroe, Kristine and Manson, JoAnn E and Le Marchand, Lo{\"\i}c and Kuller, Lewis H and Kolonel, Laurence N and Hong, Ching P and Henderson, Brian E and Haessler, Jeff and Gross, Myron D and Goodloe, Robert and Franceschini, Nora and Carlson, Christopher S and Buyske, Steven and B{\r u}zkov{\'a}, Petra and Hindorff, Lucia A and Matise, Tara C and Crawford, Dana C and Haiman, Christopher A and Peters, Ulrike and North, Kari E} } @article {6627, title = {Investigation of gene-by-sex interactions for lipid traits in diverse populations from the population architecture using genomics and epidemiology study.}, journal = {BMC Genet}, volume = {14}, year = {2013}, month = {2013}, pages = {33}, abstract = {BACKGROUND: High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels are influenced by both genes and the environment. Genome-wide association studies (GWAS) have identified ~100 common genetic variants associated with HDL-C, LDL-C, and/or TG levels, mostly in populations of European descent, but little is known about the modifiers of these associations. Here, we investigated whether GWAS-identified SNPs for lipid traits exhibited heterogeneity by sex in the Population Architecture using Genomics and Epidemiology (PAGE) study.
RESULTS: A sex-stratified meta-analysis was performed for 49 GWAS-identified SNPs for fasting HDL-C, LDL-C, and ln(TG) levels among adults self-identified as European American (25,013). Heterogeneity by sex was established when phet < 0.001. There was evidence for heterogeneity by sex for two SNPs for ln(TG) in the APOA1/C3/A4/A5/BUD13 gene cluster: rs28927680 (p(het) = 7.4 x 10(-7)) and rs3135506 (p(het) = 4.3 x 10(-4)one SNP in PLTP for HDL levels (rs7679; p(het) = 9.9 x 10(-4)), and one in HMGCR for LDL levels (rs12654264; p(het) = 3.1 x 10(-5)). We replicated heterogeneity by sex in five of seventeen loci previously reported by genome-wide studies (binomial p = 0.0009). We also present results for other racial/ethnic groups in the supplementary materials, to provide a resource for future meta-analyses.
CONCLUSIONS: We provide further evidence for sex-specific effects of SNPs in the APOA1/C3/A4/A5/BUD13 gene cluster, PLTP, and HMGCR on fasting triglyceride levels in European Americans from the PAGE study. Our findings emphasize the need for considering context-specific effects when interpreting genetic associations emerging from GWAS, and also highlight the difficulties in replicating interaction effects across studies and across racial/ethnic groups.
}, keywords = {Female, Genetic Heterogeneity, Genome, Human, Genome-Wide Association Study, Humans, Lipids, Male, Polymorphism, Single Nucleotide, Population Groups}, issn = {1471-2156}, doi = {10.1186/1471-2156-14-33}, author = {Taylor, Kira C and Carty, Cara L and Dumitrescu, Logan and B{\r u}zkov{\'a}, Petra and Cole, Shelley A and Hindorff, Lucia and Schumacher, Fred R and Wilkens, Lynne R and Shohet, Ralph V and Quibrera, P Miguel and Johnson, Karen C and Henderson, Brian E and Haessler, Jeff and Franceschini, Nora and Eaton, Charles B and Duggan, David J and Cochran, Barbara and Cheng, Iona and Carlson, Chris S and Brown-Gentry, Kristin and Anderson, Garnet and Ambite, Jose Luis and Haiman, Christopher and Le Marchand, Lo{\"\i}c and Kooperberg, Charles and Crawford, Dana C and Buyske, Steven and North, Kari E and Fornage, Myriam} } @article {6094, title = {Lack of associations of ten candidate coronary heart disease risk genetic variants and subclinical atherosclerosis in four US populations: the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {Atherosclerosis}, volume = {228}, year = {2013}, month = {2013 Jun}, pages = {390-9}, abstract = {BACKGROUND: A number of genetic variants have been discovered by recent genome-wide association studies for their associations with clinical coronary heart disease (CHD). However, it is unclear whether these variants are also associated with the development of CHD as measured by subclinical atherosclerosis phenotypes, ankle brachial index (ABI), carotid artery intima-media thickness (cIMT) and carotid plaque.
METHODS: Ten CHD risk single nucleotide polymorphisms (SNPs) were genotyped in individuals of European American (EA), African American (AA), American Indian (AI), and Mexican American (MA) ancestry in the Population Architecture using Genomics and Epidemiology (PAGE) study. In each individual study, we performed linear or logistic regression to examine population-specific associations between SNPs and ABI, common and internal cIMT, and plaque. The results from individual studies were meta-analyzed using a fixed effect inverse variance weighted model.
RESULTS: None of the ten SNPs was significantly associated with ABI and common or internal cIMT, after Bonferroni correction. In the sample of 13,337 EA, 3809 AA, and 5353 AI individuals with carotid plaque measurement, the GCKR SNP rs780094 was significantly associated with the presence of plaque in AI only (OR~=~1.32, 95\% confidence interval: 1.17, 1.49, P~=~1.08~{\texttimes}~10(-5)), but not in the other populations (P~=~0.90 in EA and P~=~0.99 in AA). A 9p21 region SNP, rs1333049, was nominally associated with plaque in EA (OR~=~1.07, P~=~0.02) and in AI (OR~=~1.10, P~=~0.05).
CONCLUSIONS: We identified a significant association between rs780094 and plaque in AI populations, which needs to be replicated in future studies. There was little evidence that the index CHD risk variants identified through genome-wide association studies in EA influence the development of CHD through subclinical atherosclerosis as assessed by cIMT and ABI across ancestries.
}, keywords = {African Americans, Aged, Ankle Brachial Index, Asymptomatic Diseases, Carotid Artery Diseases, Carotid Intima-Media Thickness, Coronary Disease, European Continental Ancestry Group, Female, Gene Frequency, Genetic Association Studies, Genetic Predisposition to Disease, Humans, Indians, North American, Linear Models, Logistic Models, Male, Mexican Americans, Middle Aged, Odds Ratio, Phenotype, Polymorphism, Single Nucleotide, Predictive Value of Tests, Risk Assessment, Risk Factors, United States}, issn = {1879-1484}, doi = {10.1016/j.atherosclerosis.2013.02.038}, author = {Zhang, Lili and B{\r u}zkov{\'a}, Petra and Wassel, Christina L and Roman, Mary J and North, Kari E and Crawford, Dana C and Boston, Jonathan and Brown-Gentry, Kristin D and Cole, Shelley A and Deelman, Ewa and Goodloe, Robert and Wilson, Sarah and Heiss, Gerardo and Jenny, Nancy S and Jorgensen, Neal W and Matise, Tara C and McClellan, Bob E and Nato, Alejandro Q and Ritchie, Marylyn D and Franceschini, Nora and Kao, W H Linda} } @article {6078, title = {A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry.}, journal = {Nat Genet}, volume = {45}, year = {2013}, month = {2013 Jun}, pages = {690-6}, abstract = {Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 {\texttimes} 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 {\texttimes} 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 {\texttimes} 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 {\texttimes} 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.
}, keywords = {African Americans, Body Mass Index, Case-Control Studies, Gene Frequency, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Obesity, Polymorphism, Single Nucleotide}, issn = {1546-1718}, doi = {10.1038/ng.2608}, author = {Monda, Keri L and Chen, Gary K and Taylor, Kira C and Palmer, Cameron and Edwards, Todd L and Lange, Leslie A and Ng, Maggie C Y and Adeyemo, Adebowale A and Allison, Matthew A and Bielak, Lawrence F and Chen, Guanjie and Graff, Mariaelisa and Irvin, Marguerite R and Rhie, Suhn K and Li, Guo and Liu, Yongmei and Liu, Youfang and Lu, Yingchang and Nalls, Michael A and Sun, Yan V and Wojczynski, Mary K and Yanek, Lisa R and Aldrich, Melinda C and Ademola, Adeyinka and Amos, Christopher I and Bandera, Elisa V and Bock, Cathryn H and Britton, Angela and Broeckel, Ulrich and Cai, Quiyin and Caporaso, Neil E and Carlson, Chris S and Carpten, John and Casey, Graham and Chen, Wei-Min and Chen, Fang and Chen, Yii-der I and Chiang, Charleston W K and Coetzee, Gerhard A and Demerath, Ellen and Deming-Halverson, Sandra L and Driver, Ryan W and Dubbert, Patricia and Feitosa, Mary F and Feng, Ye and Freedman, Barry I and Gillanders, Elizabeth M and Gottesman, Omri and Guo, Xiuqing and Haritunians, Talin and Harris, Tamara and Harris, Curtis C and Hennis, Anselm J M and Hernandez, Dena G and McNeill, Lorna H and Howard, Timothy D and Howard, Barbara V and Howard, Virginia J and Johnson, Karen C and Kang, Sun J and Keating, Brendan J and Kolb, Suzanne and Kuller, Lewis H and Kutlar, Abdullah and Langefeld, Carl D and Lettre, Guillaume and Lohman, Kurt and Lotay, Vaneet and Lyon, Helen and Manson, JoAnn E and Maixner, William and Meng, Yan A and Monroe, Kristine R and Morhason-Bello, Imran and Murphy, Adam B and Mychaleckyj, Josyf C and Nadukuru, Rajiv and Nathanson, Katherine L and Nayak, Uma and N{\textquoteright}diaye, Amidou and Nemesure, Barbara and Wu, Suh-Yuh and Leske, M Cristina and Neslund-Dudas, Christine and Neuhouser, Marian and Nyante, Sarah and Ochs-Balcom, Heather and Ogunniyi, Adesola and Ogundiran, Temidayo O and Ojengbede, Oladosu and Olopade, Olufunmilayo I and Palmer, Julie R and Ruiz-Narvaez, Edward A and Palmer, Nicholette D and Press, Michael F and Rampersaud, Evandine and Rasmussen-Torvik, Laura J and Rodriguez-Gil, Jorge L and Salako, Babatunde and Schadt, Eric E and Schwartz, Ann G and Shriner, Daniel A and Siscovick, David and Smith, Shad B and Wassertheil-Smoller, Sylvia and Speliotes, Elizabeth K and Spitz, Margaret R and Sucheston, Lara and Taylor, Herman and Tayo, Bamidele O and Tucker, Margaret A and Van Den Berg, David J and Edwards, Digna R Velez and Wang, Zhaoming and Wiencke, John K and Winkler, Thomas W and Witte, John S and Wrensch, Margaret and Wu, Xifeng and Yang, James J and Levin, Albert M and Young, Taylor R and Zakai, Neil A and Cushman, Mary and Zanetti, Krista A and Zhao, Jing Hua and Zhao, Wei and Zheng, Yonglan and Zhou, Jie and Ziegler, Regina G and Zmuda, Joseph M and Fernandes, Jyotika K and Gilkeson, Gary S and Kamen, Diane L and Hunt, Kelly J and Spruill, Ida J and Ambrosone, Christine B and Ambs, Stefan and Arnett, Donna K and Atwood, Larry and Becker, Diane M and Berndt, Sonja I and Bernstein, Leslie and Blot, William J and Borecki, Ingrid B and Bottinger, Erwin P and Bowden, Donald W and Burke, Gregory and Chanock, Stephen J and Cooper, Richard S and Ding, Jingzhong and Duggan, David and Evans, Michele K and Fox, Caroline and Garvey, W Timothy and Bradfield, Jonathan P and Hakonarson, Hakon and Grant, Struan F A and Hsing, Ann and Chu, Lisa and Hu, Jennifer J and Huo, Dezheng and Ingles, Sue A and John, Esther M and Jordan, Joanne M and Kabagambe, Edmond K and Kardia, Sharon L R and Kittles, Rick A and Goodman, Phyllis J and Klein, Eric A and Kolonel, Laurence N and Le Marchand, Lo{\"\i}c and Liu, Simin and McKnight, Barbara and Millikan, Robert C and Mosley, Thomas H and Padhukasahasram, Badri and Williams, L Keoki and Patel, Sanjay R and Peters, Ulrike and Pettaway, Curtis A and Peyser, Patricia A and Psaty, Bruce M and Redline, Susan and Rotimi, Charles N and Rybicki, Benjamin A and Sale, Mich{\`e}le M and Schreiner, Pamela J and Signorello, Lisa B and Singleton, Andrew B and Stanford, Janet L and Strom, Sara S and Thun, Michael J and Vitolins, Mara and Zheng, Wei and Moore, Jason H and Williams, Scott M and Ketkar, Shamika and Zhu, Xiaofeng and Zonderman, Alan B and Kooperberg, Charles and Papanicolaou, George J and Henderson, Brian E and Reiner, Alex P and Hirschhorn, Joel N and Loos, Ruth J F and North, Kari E and Haiman, Christopher A} } @article {6292, title = {No evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population.}, journal = {Hum Genet}, volume = {132}, year = {2013}, month = {2013 Dec}, pages = {1427-31}, abstract = {Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP {\texttimes} smoking interactions.
}, keywords = {Cholesterol, HDL, Cholesterol, LDL, Cohort Studies, Ethnic Groups, Female, Gene Frequency, Gene-Environment Interaction, Genetics, Population, Genome-Wide Association Study, Humans, Lipid Metabolism, Male, Polymorphism, Single Nucleotide, Prevalence, Smoking, Triglycerides, Young Adult}, issn = {1432-1203}, doi = {10.1007/s00439-013-1375-3}, author = {Dumitrescu, Logan and Carty, Cara L and Franceschini, Nora and Hindorff, Lucia A and Cole, Shelley A and B{\r u}zkov{\'a}, Petra and Schumacher, Fredrick R and Eaton, Charles B and Goodloe, Robert J and Duggan, David J and Haessler, Jeff and Cochran, Barbara and Henderson, Brian E and Cheng, Iona and Johnson, Karen C and Carlson, Chris S and Love, Shelly-Anne and Brown-Gentry, Kristin and Nato, Alejandro Q and Quibrera, Miguel and Shohet, Ralph V and Ambite, Jose Luis and Wilkens, Lynne R and Le Marchand, Lo{\"\i}c and Haiman, Christopher A and Buyske, Steven and Kooperberg, Charles and North, Kari E and Fornage, Myriam and Crawford, Dana C} } @article {6111, title = {Post-genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {Ann Hum Genet}, volume = {77}, year = {2013}, month = {2013 Sep}, pages = {416-25}, abstract = {Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age-dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or >=50 years of age; females: pre- or postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet < 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 1.74E-03, I(2) = 89.8), with a significant association in older males (P = 1.39E-06) but not younger males (P = 0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes.
}, keywords = {Adult, Aged, European Continental Ancestry Group, Female, Genetic Association Studies, Genome-Wide Association Study, Humans, Lipids, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Risk Factors}, issn = {1469-1809}, doi = {10.1111/ahg.12027}, author = {Dumitrescu, Logan and Carty, Cara L and Franceschini, Nora and Hindorff, Lucia A and Cole, Shelley A and B{\r u}zkov{\'a}, Petra and Schumacher, Fredrick R and Eaton, Charles B and Goodloe, Robert J and Duggan, David J and Haessler, Jeff and Cochran, Barbara and Henderson, Brian E and Cheng, Iona and Johnson, Karen C and Carlson, Chris S and Love, Shelly-Ann and Brown-Gentry, Kristin and Nato, Alejandro Q and Quibrera, Miguel and Anderson, Garnet and Shohet, Ralph V and Ambite, Jose Luis and Wilkens, Lynne R and Marchand, Loic Le and Haiman, Christopher A and Buyske, Steven and Kooperberg, Charles and North, Kari E and Fornage, Myriam and Crawford, Dana C} } @article {6028, title = {Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits.}, journal = {PLoS Genet}, volume = {9}, year = {2013}, month = {2013 Jun}, pages = {e1003500}, abstract = {Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5\%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5{\texttimes}10(-8)), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.
}, keywords = {Anthropometry, Body Height, Body Mass Index, Body Weight, Body Weights and Measures, Female, Genetic Loci, Genome, Human, Genome-Wide Association Study, Humans, Male, Polymorphism, Single Nucleotide, Sex Characteristics, Waist Circumference, Waist-Hip Ratio}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1003500}, author = {Randall, Joshua C and Winkler, Thomas W and Kutalik, Zolt{\'a}n and Berndt, Sonja I and Jackson, Anne U and Monda, Keri L and Kilpel{\"a}inen, Tuomas O and Esko, T{\~o}nu and M{\"a}gi, Reedik and Li, Shengxu and Workalemahu, Tsegaselassie and Feitosa, Mary F and Croteau-Chonka, Damien C and Day, Felix R and Fall, Tove and Ferreira, Teresa and Gustafsson, Stefan and Locke, Adam E and Mathieson, Iain and Scherag, Andre and Vedantam, Sailaja and Wood, Andrew R and Liang, Liming and Steinthorsdottir, Valgerdur and Thorleifsson, Gudmar and Dermitzakis, Emmanouil T and Dimas, Antigone S and Karpe, Fredrik and Min, Josine L and Nicholson, George and Clegg, Deborah J and Person, Thomas and Krohn, Jon P and Bauer, Sabrina and Buechler, Christa and Eisinger, Kristina and Bonnefond, Am{\'e}lie and Froguel, Philippe and Hottenga, Jouke-Jan and Prokopenko, Inga and Waite, Lindsay L and Harris, Tamara B and Smith, Albert Vernon and Shuldiner, Alan R and McArdle, Wendy L and Caulfield, Mark J and Munroe, Patricia B and Gr{\"o}nberg, Henrik and Chen, Yii-Der Ida and Li, Guo and Beckmann, Jacques S and Johnson, Toby and Thorsteinsdottir, Unnur and Teder-Laving, Maris and Khaw, Kay-Tee and Wareham, Nicholas J and Zhao, Jing Hua and Amin, Najaf and Oostra, Ben A and Kraja, Aldi T and Province, Michael A and Cupples, L Adrienne and Heard-Costa, Nancy L and Kaprio, Jaakko and Ripatti, Samuli and Surakka, Ida and Collins, Francis S and Saramies, Jouko and Tuomilehto, Jaakko and Jula, Antti and Salomaa, Veikko and Erdmann, Jeanette and Hengstenberg, Christian and Loley, Christina and Schunkert, Heribert and Lamina, Claudia and Wichmann, H Erich and Albrecht, Eva and Gieger, Christian and Hicks, Andrew A and Johansson, Asa and Pramstaller, Peter P and Kathiresan, Sekar and Speliotes, Elizabeth K and Penninx, Brenda and Hartikainen, Anna-Liisa and Jarvelin, Marjo-Riitta and Gyllensten, Ulf and Boomsma, Dorret I and Campbell, Harry and Wilson, James F and Chanock, Stephen J and Farrall, Martin and Goel, Anuj and Medina-G{\'o}mez, Carolina and Rivadeneira, Fernando and Estrada, Karol and Uitterlinden, Andr{\'e} G and Hofman, Albert and Zillikens, M Carola and den Heijer, Martin and Kiemeney, Lambertus A and Maschio, Andrea and Hall, Per and Tyrer, Jonathan and Teumer, Alexander and V{\"o}lzke, Henry and Kovacs, Peter and T{\"o}njes, Anke and Mangino, Massimo and Spector, Tim D and Hayward, Caroline and Rudan, Igor and Hall, Alistair S and Samani, Nilesh J and Attwood, Antony Paul and Sambrook, Jennifer G and Hung, Joseph and Palmer, Lyle J and Lokki, Marja-Liisa and Sinisalo, Juha and Boucher, Gabrielle and Huikuri, Heikki and Lorentzon, Mattias and Ohlsson, Claes and Eklund, Niina and Eriksson, Johan G and Barlassina, Cristina and Rivolta, Carlo and Nolte, Ilja M and Snieder, Harold and van der Klauw, Melanie M and van Vliet-Ostaptchouk, Jana V and Gejman, Pablo V and Shi, Jianxin and Jacobs, Kevin B and Wang, Zhaoming and Bakker, Stephan J L and Mateo Leach, Irene and Navis, Gerjan and van der Harst, Pim and Martin, Nicholas G and Medland, Sarah E and Montgomery, Grant W and Yang, Jian and Chasman, Daniel I and Ridker, Paul M and Rose, Lynda M and Lehtim{\"a}ki, Terho and Raitakari, Olli and Absher, Devin and Iribarren, Carlos and Basart, Hanneke and Hovingh, Kees G and Hypp{\"o}nen, Elina and Power, Chris and Anderson, Denise and Beilby, John P and Hui, Jennie and Jolley, Jennifer and Sager, Hendrik and Bornstein, Stefan R and Schwarz, Peter E H and Kristiansson, Kati and Perola, Markus and Lindstr{\"o}m, Jaana and Swift, Amy J and Uusitupa, Matti and Atalay, Mustafa and Lakka, Timo A and Rauramaa, Rainer and Bolton, Jennifer L and Fowkes, Gerry and Fraser, Ross M and Price, Jackie F and Fischer, Krista and Krjut{\r a} Kov, Kaarel and Metspalu, Andres and Mihailov, Evelin and Langenberg, Claudia and Luan, Jian{\textquoteright}an and Ong, Ken K and Chines, Peter S and Keinanen-Kiukaanniemi, Sirkka M and Saaristo, Timo E and Edkins, Sarah and Franks, Paul W and Hallmans, G{\"o}ran and Shungin, Dmitry and Morris, Andrew David and Palmer, Colin N A and Erbel, Raimund and Moebus, Susanne and N{\"o}then, Markus M and Pechlivanis, Sonali and Hveem, Kristian and Narisu, Narisu and Hamsten, Anders and Humphries, Steve E and Strawbridge, Rona J and Tremoli, Elena and Grallert, Harald and Thorand, Barbara and Illig, Thomas and Koenig, Wolfgang and M{\"u}ller-Nurasyid, Martina and Peters, Annette and Boehm, Bernhard O and Kleber, Marcus E and M{\"a}rz, Winfried and Winkelmann, Bernhard R and Kuusisto, Johanna and Laakso, Markku and Arveiler, Dominique and Cesana, Giancarlo and Kuulasmaa, Kari and Virtamo, Jarmo and Yarnell, John W G and Kuh, Diana and Wong, Andrew and Lind, Lars and de Faire, Ulf and Gigante, Bruna and Magnusson, Patrik K E and Pedersen, Nancy L and Dedoussis, George and Dimitriou, Maria and Kolovou, Genovefa and Kanoni, Stavroula and Stirrups, Kathleen and Bonnycastle, Lori L and Nj{\o}lstad, Inger and Wilsgaard, Tom and Ganna, Andrea and Rehnberg, Emil and Hingorani, Aroon and Kivimaki, Mika and Kumari, Meena and Assimes, Themistocles L and Barroso, In{\^e}s and Boehnke, Michael and Borecki, Ingrid B and Deloukas, Panos and Fox, Caroline S and Frayling, Timothy and Groop, Leif C and Haritunians, Talin and Hunter, David and Ingelsson, Erik and Kaplan, Robert and Mohlke, Karen L and O{\textquoteright}Connell, Jeffrey R and Schlessinger, David and Strachan, David P and Stefansson, Kari and van Duijn, Cornelia M and Abecasis, Goncalo R and McCarthy, Mark I and Hirschhorn, Joel N and Qi, Lu and Loos, Ruth J F and Lindgren, Cecilia M and North, Kari E and Heid, Iris M} } @article {6628, title = {A systematic mapping approach of 16q12.2/FTO and BMI in more than 20,000 African Americans narrows in on the underlying functional variation: results from the Population Architecture using Genomics and Epidemiology (PAGE) study.}, journal = {PLoS Genet}, volume = {9}, year = {2013}, month = {2013}, pages = {e1003171}, abstract = {Genetic variants in intron 1 of the fat mass- and obesity-associated (FTO) gene have been consistently associated with body mass index (BMI) in Europeans. However, follow-up studies in African Americans (AA) have shown no support for some of the most consistently BMI-associated FTO index single nucleotide polymorphisms (SNPs). This is most likely explained by different race-specific linkage disequilibrium (LD) patterns and lower correlation overall in AA, which provides the opportunity to fine-map this region and narrow in on the functional variant. To comprehensively explore the 16q12.2/FTO locus and to search for second independent signals in the broader region, we fine-mapped a 646-kb region, encompassing the large FTO gene and the flanking gene RPGRIP1L by investigating a total of 3,756 variants (1,529 genotyped and 2,227 imputed variants) in 20,488 AAs across five studies. We observed associations between BMI and variants in the known FTO intron 1 locus: the SNP with the most significant p-value, rs56137030 (8.3 {\texttimes} 10(-6)) had not been highlighted in previous studies. While rs56137030was correlated at r(2)>0.5 with 103 SNPs in Europeans (including the GWAS index SNPs), this number was reduced to 28 SNPs in AA. Among rs56137030 and the 28 correlated SNPs, six were located within candidate intronic regulatory elements, including rs1421085, for which we predicted allele-specific binding affinity for the transcription factor CUX1, which has recently been implicated in the regulation of FTO. We did not find strong evidence for a second independent signal in the broader region. In summary, this large fine-mapping study in AA has substantially reduced the number of common alleles that are likely to be functional candidates of the known FTO locus. Importantly our study demonstrated that comprehensive fine-mapping in AA provides a powerful approach to narrow in on the functional candidate(s) underlying the initial GWAS findings in European populations.
}, keywords = {Adaptor Proteins, Signal Transducing, Adult, African Americans, Aged, Aged, 80 and over, Alleles, Body Mass Index, Chromosome Mapping, Continental Population Groups, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Metagenomics, Middle Aged, Obesity, Proteins}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1003171}, author = {Peters, Ulrike and North, Kari E and Sethupathy, Praveen and Buyske, Steve and Haessler, Jeff and Jiao, Shuo and Fesinmeyer, Megan D and Jackson, Rebecca D and Kuller, Lew H and Rajkovic, Aleksandar and Lim, Unhee and Cheng, Iona and Schumacher, Fred and Wilkens, Lynne and Li, Rongling and Monda, Keri and Ehret, Georg and Nguyen, Khanh-Dung H and Cooper, Richard and Lewis, Cora E and Leppert, Mark and Irvin, Marguerite R and Gu, C Charles and Houston, Denise and B{\r u}zkov{\'a}, Petra and Ritchie, Marylyn and Matise, Tara C and Le Marchand, Lo{\"\i}c and Hindorff, Lucia A and Crawford, Dana C and Haiman, Christopher A and Kooperberg, Charles} } @article {6629, title = {Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.}, journal = {PLoS Genet}, volume = {9}, year = {2013}, month = {2013 Mar}, pages = {e1003379}, abstract = {Genome-wide association studies (GWAS) have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 {\texttimes} 10(-4) in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74\% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.
}, keywords = {African Americans, Apolipoproteins A, Cholesterol, HDL, Cholesterol, LDL, European Continental Ancestry Group, Genome-Wide Association Study, Humans, Lipoproteins, HDL, Lipoproteins, LDL, Proprotein Convertases, Serine Endopeptidases, Triglycerides}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1003379}, author = {Wu, Ying and Waite, Lindsay L and Jackson, Anne U and Sheu, Wayne H-H and Buyske, Steven and Absher, Devin and Arnett, Donna K and Boerwinkle, Eric and Bonnycastle, Lori L and Carty, Cara L and Cheng, Iona and Cochran, Barbara and Croteau-Chonka, Damien C and Dumitrescu, Logan and Eaton, Charles B and Franceschini, Nora and Guo, Xiuqing and Henderson, Brian E and Hindorff, Lucia A and Kim, Eric and Kinnunen, Leena and Komulainen, Pirjo and Lee, Wen-Jane and Le Marchand, Lo{\"\i}c and Lin, Yi and Lindstr{\"o}m, Jaana and Lingaas-Holmen, Oddgeir and Mitchell, Sabrina L and Narisu, Narisu and Robinson, Jennifer G and Schumacher, Fred and Stan{\v c}{\'a}kov{\'a}, Alena and Sundvall, Jouko and Sung, Yun-Ju and Swift, Amy J and Wang, Wen-Chang and Wilkens, Lynne and Wilsgaard, Tom and Young, Alicia M and Adair, Linda S and Ballantyne, Christie M and B{\r u}zkov{\'a}, Petra and Chakravarti, Aravinda and Collins, Francis S and Duggan, David and Feranil, Alan B and Ho, Low-Tone and Hung, Yi-Jen and Hunt, Steven C and Hveem, Kristian and Juang, Jyh-Ming J and Kes{\"a}niemi, Antero Y and Kuusisto, Johanna and Laakso, Markku and Lakka, Timo A and Lee, I-Te and Leppert, Mark F and Matise, Tara C and Moilanen, Leena and Nj{\o}lstad, Inger and Peters, Ulrike and Quertermous, Thomas and Rauramaa, Rainer and Rotter, Jerome I and Saramies, Jouko and Tuomilehto, Jaakko and Uusitupa, Matti and Wang, Tzung-Dau and Boehnke, Michael and Haiman, Christopher A and Chen, Yii-der I and Kooperberg, Charles and Assimes, Themistocles L and Crawford, Dana C and Hsiung, Chao A and North, Kari E and Mohlke, Karen L} } @article {6580, title = {ADAM19 and HTR4 variants and pulmonary function: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {350-8}, abstract = {BACKGROUND: The pulmonary function measures of forced expiratory volume in 1 second (FEV1) and its ratio to forced vital capacity (FVC) are used in the diagnosis and monitoring of lung diseases and predict cardiovascular mortality in the general population. Genome-wide association studies (GWASs) have identified numerous loci associated with FEV1 and FEV1/FVC, but the causal variants remain uncertain. We hypothesized that novel or rare variants poorly tagged by GWASs may explain the significant associations between FEV1/FVC and 2 genes: ADAM19 and HTR4.
METHODS AND RESULTS: We sequenced ADAM19 and its promoter region along with the ≈21-kb portion of HTR4 harboring GWAS single-nucleotide polymorphisms for pulmonary function and analyzed associations with FEV1/FVC among 3983 participants of European ancestry from Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Meta-analysis of common variants in each region identified statistically significant associations (316 tests; P<1.58{\texttimes}10(-4)) with FEV1/FVC for 14 ADAM19 single-nucleotide polymorphisms and 24 HTR4 single-nucleotide polymorphisms. After conditioning on the sentinel GWASs hit in each gene (ADAM19 rs1422795, minor allele frequency=0.33 and HTR4 rs11168048, minor allele frequency=0.40], 1 single-nucleotide polymorphism remained statistically significant (ADAM19 rs13155908, minor allele frequency=0.12; P=1.56{\texttimes}10(-4)). Analysis of rare variants (minor allele frequency <1\%) using sequence kernel association test did not identify associations with either region.
CONCLUSIONS: Sequencing identified 1 common variant associated with FEV1/FVC independent of the sentinel ADAM19 GWAS hit and supports the original HTR4 GWAS findings. Rare variants do not seem to underlie GWAS associations with pulmonary function for common variants in ADAM19 and HTR4.
}, keywords = {ADAM Proteins, Aged, Aged, 80 and over, Aging, Cohort Studies, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Diseases, Humans, Lung, Male, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000066}, author = {London, Stephanie J and Gao, Wei and Gharib, Sina A and Hancock, Dana B and Wilk, Jemma B and House, John S and Gibbs, Richard A and Muzny, Donna M and Lumley, Thomas and Franceschini, Nora and North, Kari E and Psaty, Bruce M and Kovar, Christie L and Coresh, Josef and Zhou, Yanhua and Heckbert, Susan R and Brody, Jennifer A and Morrison, Alanna C and Dupuis, Jos{\'e}e} } @article {6598, title = {Evidence of heterogeneity by race/ethnicity in genetic determinants of QT interval.}, journal = {Epidemiology}, volume = {25}, year = {2014}, month = {2014 Nov}, pages = {790-8}, abstract = {BACKGROUND: QT interval (QT) prolongation is an established risk factor for ventricular tachyarrhythmia and sudden cardiac death. Previous genome-wide association studies in populations of the European descent have identified multiple genetic loci that influence QT, but few have examined these loci in ethnically diverse populations.
METHODS: Here, we examine the direction, magnitude, and precision of effect sizes for 21 previously reported SNPs from 12 QT loci, in populations of European (n = 16,398), African (n = 5,437), American Indian (n = 5,032), Hispanic (n = 1,143), and Asian (n = 932) descent as part of the Population Architecture using Genomics and Epidemiology (PAGE) study. Estimates obtained from linear regression models stratified by race/ethnicity were combined using inverse-variance weighted meta-analysis. Heterogeneity was evaluated using Cochran{\textquoteright}s Q test.
RESULTS: Of 21 SNPs, 7 showed consistent direction of effect across all 5 populations, and an additional 9 had estimated effects that were consistent across 4 populations. Despite consistent direction of effect, 9 of 16 SNPs had evidence (P < 0.05) of heterogeneity by race/ethnicity. For these 9 SNPs, linkage disequilibrium plots often indicated substantial variation in linkage disequilibrium patterns among the various racial/ethnic groups, as well as possible allelic heterogeneity.
CONCLUSIONS: These results emphasize the importance of analyzing racial/ethnic groups separately in genetic studies. Furthermore, they underscore the possible utility of trans-ethnic studies to pinpoint underlying casual variants influencing heritable traits such as QT.
}, keywords = {Aged, Continental Population Groups, Electrocardiography, Female, Genetic Predisposition to Disease, Haplotypes, Humans, Long QT Syndrome, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Quantitative Trait, Heritable, Risk Factors}, issn = {1531-5487}, doi = {10.1097/EDE.0000000000000168}, author = {Seyerle, Amanda A and Young, Alicia M and Jeff, Janina M and Melton, Phillip E and Jorgensen, Neal W and Lin, Yi and Carty, Cara L and Deelman, Ewa and Heckbert, Susan R and Hindorff, Lucia A and Jackson, Rebecca D and Martin, Lisa W and Okin, Peter M and Perez, Marco V and Psaty, Bruce M and Soliman, Elsayed Z and Whitsel, Eric A and North, Kari E and Laston, Sandra and Kooperberg, Charles and Avery, Christy L} } @article {6368, title = {Gene-centric meta-analyses for central adiposity traits in up to 57 412 individuals of European descent confirm known loci and reveal several novel associations.}, journal = {Hum Mol Genet}, volume = {23}, year = {2014}, month = {2014 May 01}, pages = {2498-510}, abstract = {Waist circumference (WC) and waist-to-hip ratio (WHR) are surrogate measures of central adiposity that are associated with adverse cardiovascular events, type 2 diabetes and cancer independent of body mass index (BMI). WC and WHR are highly heritable with multiple susceptibility loci identified to date. We assessed the association between SNPs and BMI-adjusted WC and WHR and unadjusted WC in up to 57 412 individuals of European descent from 22 cohorts collaborating with the NHLBI{\textquoteright}s Candidate Gene Association Resource (CARe) project. The study population consisted of women and men aged 20-80 years. Study participants were genotyped using the ITMAT/Broad/CARE array, which includes \~{}50 000 cosmopolitan tagged SNPs across \~{}2100 cardiovascular-related genes. Each trait was modeled as a function of age, study site and principal components to control for population stratification, and we conducted a fixed-effects meta-analysis. No new loci for WC were observed. For WHR analyses, three novel loci were significantly associated (P < 2.4 {\texttimes} 10(-6)). Previously unreported rs2811337-G near TMCC1 was associated with increased WHR (β {\textpm} SE, 0.048 {\textpm} 0.008, P = 7.7 {\texttimes} 10(-9)) as was rs7302703-G in HOXC10 (β = 0.044 {\textpm} 0.008, P = 2.9 {\texttimes} 10(-7)) and rs936108-C in PEMT (β = 0.035 {\textpm} 0.007, P = 1.9 {\texttimes} 10(-6)). Sex-stratified analyses revealed two additional novel signals among females only, rs12076073-A in SHC1 (β = 0.10 {\textpm} 0.02, P = 1.9 {\texttimes} 10(-6)) and rs1037575-A in ATBDB4 (β = 0.046 {\textpm} 0.01, P = 2.2 {\texttimes} 10(-6)), supporting an already established sexual dimorphism of central adiposity-related genetic variants. Functional analysis using ENCODE and eQTL databases revealed that several of these loci are in regulatory regions or regions with differential expression in adipose tissue.
}, keywords = {Adiposity, Adult, Aged, Aged, 80 and over, Body Mass Index, European Continental Ancestry Group, Female, Genome-Wide Association Study, Humans, Male, Middle Aged, Waist Circumference, Waist-Hip Ratio, Young Adult}, issn = {1460-2083}, doi = {10.1093/hmg/ddt626}, author = {Yoneyama, Sachiko and Guo, Yiran and Lanktree, Matthew B and Barnes, Michael R and Elbers, Clara C and Karczewski, Konrad J and Padmanabhan, Sandosh and Bauer, Florianne and Baumert, Jens and Beitelshees, Amber and Berenson, Gerald S and Boer, Jolanda M A and Burke, Gregory and Cade, Brian and Chen, Wei and Cooper-Dehoff, Rhonda M and Gaunt, Tom R and Gieger, Christian and Gong, Yan and Gorski, Mathias and Heard-Costa, Nancy and Johnson, Toby and Lamonte, Michael J and McDonough, Caitrin and Monda, Keri L and Onland-Moret, N Charlotte and Nelson, Christopher P and O{\textquoteright}Connell, Jeffrey R and Ordovas, Jose and Peter, Inga and Peters, Annette and Shaffer, Jonathan and Shen, Haiqinq and Smith, Erin and Speilotes, Liz and Thomas, Fridtjof and Thorand, Barbara and Monique Verschuren, W M and Anand, Sonia S and Dominiczak, Anna and Davidson, Karina W and Hegele, Robert A and Heid, Iris and Hofker, Marten H and Huggins, Gordon S and Illig, Thomas and Johnson, Julie A and Kirkland, Susan and K{\"o}nig, Wolfgang and Langaee, Taimour Y and McCaffery, Jeanne and Melander, Olle and Mitchell, Braxton D and Munroe, Patricia and Murray, Sarah S and Papanicolaou, George and Redline, Susan and Reilly, Muredach and Samani, Nilesh J and Schork, Nicholas J and van der Schouw, Yvonne T and Shimbo, Daichi and Shuldiner, Alan R and Tobin, Martin D and Wijmenga, Cisca and Yusuf, Salim and Hakonarson, Hakon and Lange, Leslie A and Demerath, Ellen W and Fox, Caroline S and North, Kari E and Reiner, Alex P and Keating, Brendan and Taylor, Kira C} } @article {6582, title = {Genome-wide association analysis identifies six new loci associated with forced vital capacity.}, journal = {Nat Genet}, volume = {46}, year = {2014}, month = {2014 Jul}, pages = {669-77}, abstract = {Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analysis of FVC in 52,253 individuals from 26 studies and followed up the top associations in 32,917 additional individuals of European ancestry. We found six new regions associated at genome-wide significance (P < 5 {\texttimes} 10(-8)) with FVC in or near EFEMP1, BMP6, MIR129-2-HSD17B12, PRDM11, WWOX and KCNJ2. Two loci previously associated with spirometric measures (GSTCD and PTCH1) were related to FVC. Newly implicated regions were followed up in samples from African-American, Korean, Chinese and Hispanic individuals. We detected transcripts for all six newly implicated genes in human lung tissue. The new loci may inform mechanisms involved in lung development and the pathogenesis of restrictive lung disease.
}, keywords = {Cohort Studies, Databases, Genetic, Follow-Up Studies, Forced Expiratory Volume, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Lung Diseases, Meta-Analysis as Topic, Polymorphism, Single Nucleotide, Prognosis, Quantitative Trait Loci, Respiratory Function Tests, Spirometry, Vital Capacity}, issn = {1546-1718}, doi = {10.1038/ng.3011}, author = {Loth, Daan W and Soler Artigas, Maria and Gharib, Sina A and Wain, Louise V and Franceschini, Nora and Koch, Beate and Pottinger, Tess D and Smith, Albert Vernon and Duan, Qing and Oldmeadow, Chris and Lee, Mi Kyeong and Strachan, David P and James, Alan L and Huffman, Jennifer E and Vitart, Veronique and Ramasamy, Adaikalavan and Wareham, Nicholas J and Kaprio, Jaakko and Wang, Xin-Qun and Trochet, Holly and K{\"a}h{\"o}nen, Mika and Flexeder, Claudia and Albrecht, Eva and Lopez, Lorna M and de Jong, Kim and Thyagarajan, Bharat and Alves, Alexessander Couto and Enroth, Stefan and Omenaas, Ernst and Joshi, Peter K and Fall, Tove and Vi{\~n}uela, Ana and Launer, Lenore J and Loehr, Laura R and Fornage, Myriam and Li, Guo and Wilk, Jemma B and Tang, Wenbo and Manichaikul, Ani and Lahousse, Lies and Harris, Tamara B and North, Kari E and Rudnicka, Alicja R and Hui, Jennie and Gu, Xiangjun and Lumley, Thomas and Wright, Alan F and Hastie, Nicholas D and Campbell, Susan and Kumar, Rajesh and Pin, Isabelle and Scott, Robert A and Pietil{\"a}inen, Kirsi H and Surakka, Ida and Liu, Yongmei and Holliday, Elizabeth G and Schulz, Holger and Heinrich, Joachim and Davies, Gail and Vonk, Judith M and Wojczynski, Mary and Pouta, Anneli and Johansson, Asa and Wild, Sarah H and Ingelsson, Erik and Rivadeneira, Fernando and V{\"o}lzke, Henry and Hysi, Pirro G and Eiriksdottir, Gudny and Morrison, Alanna C and Rotter, Jerome I and Gao, Wei and Postma, Dirkje S and White, Wendy B and Rich, Stephen S and Hofman, Albert and Aspelund, Thor and Couper, David and Smith, Lewis J and Psaty, Bruce M and Lohman, Kurt and Burchard, Esteban G and Uitterlinden, Andr{\'e} G and Garcia, Melissa and Joubert, Bonnie R and McArdle, Wendy L and Musk, A Bill and Hansel, Nadia and Heckbert, Susan R and Zgaga, Lina and van Meurs, Joyce B J and Navarro, Pau and Rudan, Igor and Oh, Yeon-Mok and Redline, Susan and Jarvis, Deborah L and Zhao, Jing Hua and Rantanen, Taina and O{\textquoteright}Connor, George T and Ripatti, Samuli and Scott, Rodney J and Karrasch, Stefan and Grallert, Harald and Gaddis, Nathan C and Starr, John M and Wijmenga, Cisca and Minster, Ryan L and Lederer, David J and Pekkanen, Juha and Gyllensten, Ulf and Campbell, Harry and Morris, Andrew P and Gl{\"a}ser, Sven and Hammond, Christopher J and Burkart, Kristin M and Beilby, John and Kritchevsky, Stephen B and Gudnason, Vilmundur and Hancock, Dana B and Williams, O Dale and Polasek, Ozren and Zemunik, Tatijana and Kolcic, Ivana and Petrini, Marcy F and Wjst, Matthias and Kim, Woo Jin and Porteous, David J and Scotland, Generation and Smith, Blair H and Viljanen, Anne and Heli{\"o}vaara, Markku and Attia, John R and Sayers, Ian and Hampel, Regina and Gieger, Christian and Deary, Ian J and Boezen, H Marike and Newman, Anne and Jarvelin, Marjo-Riitta and Wilson, James F and Lind, Lars and Stricker, Bruno H and Teumer, Alexander and Spector, Timothy D and Mel{\'e}n, Erik and Peters, Marjolein J and Lange, Leslie A and Barr, R Graham and Bracke, Ken R and Verhamme, Fien M and Sung, Joohon and Hiemstra, Pieter S and Cassano, Patricia A and Sood, Akshay and Hayward, Caroline and Dupuis, Jos{\'e}e and Hall, Ian P and Brusselle, Guy G and Tobin, Martin D and London, Stephanie J} } @article {6604, title = {Large-scale genome-wide association studies and meta-analyses of longitudinal change in adult lung function.}, journal = {PLoS One}, volume = {9}, year = {2014}, month = {2014}, pages = {e100776}, abstract = {BACKGROUND: Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function.
METHODS: We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis.
RESULTS: The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P = 5.71 {\texttimes} 10(-7)). In addition, meta-analysis using the five cohorts with >=3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P = 2.18 {\texttimes} 10(-8)) at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively.
CONCLUSIONS: In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function.
}, keywords = {Adult, Chromosomes, Human, Pair 11, Female, Gene Expression Regulation, Genetic Loci, Genome-Wide Association Study, Humans, Longitudinal Studies, Male, Respiration}, issn = {1932-6203}, doi = {10.1371/journal.pone.0100776}, author = {Tang, Wenbo and Kowgier, Matthew and Loth, Daan W and Soler Artigas, Maria and Joubert, Bonnie R and Hodge, Emily and Gharib, Sina A and Smith, Albert V and Ruczinski, Ingo and Gudnason, Vilmundur and Mathias, Rasika A and Harris, Tamara B and Hansel, Nadia N and Launer, Lenore J and Barnes, Kathleen C and Hansen, Joyanna G and Albrecht, Eva and Aldrich, Melinda C and Allerhand, Michael and Barr, R Graham and Brusselle, Guy G and Couper, David J and Curjuric, Ivan and Davies, Gail and Deary, Ian J and Dupuis, Jos{\'e}e and Fall, Tove and Foy, Millennia and Franceschini, Nora and Gao, Wei and Gl{\"a}ser, Sven and Gu, Xiangjun and Hancock, Dana B and Heinrich, Joachim and Hofman, Albert and Imboden, Medea and Ingelsson, Erik and James, Alan and Karrasch, Stefan and Koch, Beate and Kritchevsky, Stephen B and Kumar, Ashish and Lahousse, Lies and Li, Guo and Lind, Lars and Lindgren, Cecilia and Liu, Yongmei and Lohman, Kurt and Lumley, Thomas and McArdle, Wendy L and Meibohm, Bernd and Morris, Andrew P and Morrison, Alanna C and Musk, Bill and North, Kari E and Palmer, Lyle J and Probst-Hensch, Nicole M and Psaty, Bruce M and Rivadeneira, Fernando and Rotter, Jerome I and Schulz, Holger and Smith, Lewis J and Sood, Akshay and Starr, John M and Strachan, David P and Teumer, Alexander and Uitterlinden, Andr{\'e} G and V{\"o}lzke, Henry and Voorman, Arend and Wain, Louise V and Wells, Martin T and Wilk, Jemma B and Williams, O Dale and Heckbert, Susan R and Stricker, Bruno H and London, Stephanie J and Fornage, Myriam and Tobin, Martin D and O{\textquoteright}Connor, George T and Hall, Ian P and Cassano, Patricia A} } @article {6605, title = {Loss-of-function mutations in APOC3, triglycerides, and coronary disease.}, journal = {N Engl J Med}, volume = {371}, year = {2014}, month = {2014 Jul 3}, pages = {22-31}, abstract = {BACKGROUND: Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype.
METHODS: We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons.
RESULTS: An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G{\textrightarrow}A and IVS3+1G{\textrightarrow}T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39\% lower than levels in noncarriers (P<1{\texttimes}10(-20)), and circulating levels of APOC3 in carriers were 46\% lower than levels in noncarriers (P=8{\texttimes}10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40\% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95\% confidence interval, 0.47 to 0.75; P=4{\texttimes}10(-6)).
CONCLUSIONS: Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.).
}, keywords = {African Continental Ancestry Group, Apolipoprotein C-III, Coronary Disease, European Continental Ancestry Group, Exome, Genotype, Heterozygote, Humans, Liver, Mutation, Risk Factors, Sequence Analysis, DNA, Triglycerides}, issn = {1533-4406}, doi = {10.1056/NEJMoa1307095}, author = {Crosby, Jacy and Peloso, Gina M and Auer, Paul L and Crosslin, David R and Stitziel, Nathan O and Lange, Leslie A and Lu, Yingchang and Tang, Zheng-Zheng and Zhang, He and Hindy, George and Masca, Nicholas and Stirrups, Kathleen and Kanoni, Stavroula and Do, Ron and Jun, Goo and Hu, Youna and Kang, Hyun Min and Xue, Chenyi and Goel, Anuj and Farrall, Martin and Duga, Stefano and Merlini, Pier Angelica and Asselta, Rosanna and Girelli, Domenico and Olivieri, Oliviero and Martinelli, Nicola and Yin, Wu and Reilly, Dermot and Speliotes, Elizabeth and Fox, Caroline S and Hveem, Kristian and Holmen, Oddgeir L and Nikpay, Majid and Farlow, Deborah N and Assimes, Themistocles L and Franceschini, Nora and Robinson, Jennifer and North, Kari E and Martin, Lisa W and DePristo, Mark and Gupta, Namrata and Escher, Stefan A and Jansson, Jan-H{\r a}kan and Van Zuydam, Natalie and Palmer, Colin N A and Wareham, Nicholas and Koch, Werner and Meitinger, Thomas and Peters, Annette and Lieb, Wolfgang and Erbel, Raimund and K{\"o}nig, Inke R and Kruppa, Jochen and Degenhardt, Franziska and Gottesman, Omri and Bottinger, Erwin P and O{\textquoteright}Donnell, Christopher J and Psaty, Bruce M and Ballantyne, Christie M and Abecasis, Goncalo and Ordovas, Jose M and Melander, Olle and Watkins, Hugh and Orho-Melander, Marju and Ardissino, Diego and Loos, Ruth J F and McPherson, Ruth and Willer, Cristen J and Erdmann, Jeanette and Hall, Alistair S and Samani, Nilesh J and Deloukas, Panos and Schunkert, Heribert and Wilson, James G and Kooperberg, Charles and Rich, Stephen S and Tracy, Russell P and Lin, Dan-Yu and Altshuler, David and Gabriel, Stacey and Nickerson, Deborah A and Jarvik, Gail P and Cupples, L Adrienne and Reiner, Alex P and Boerwinkle, Eric and Kathiresan, Sekar} } @article {6579, title = {Sequence variation in TMEM18 in association with body mass index: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {344-9}, abstract = {BACKGROUND: Genome-wide association studies for body mass index (BMI) previously identified a locus near TMEM18. We conducted targeted sequencing of this region to investigate the role of common, low-frequency, and rare variants influencing BMI.
METHODS AND RESULTS: We sequenced TMEM18 and regions downstream of TMEM18 on chromosome 2 in 3976 individuals of European ancestry from 3 community-based cohorts (Atherosclerosis Risk in Communities, Cardiovascular Health Study, and Framingham Heart Study), including 200 adults selected for high BMI. We examined the association between BMI and variants identified in the region from nucleotide position 586 432 to 677 539 (hg18). Rare variants (minor allele frequency, <1\%) were analyzed using a burden test and the sequence kernel association test. Results from the 3 cohort studies were meta-analyzed. We estimate that mean BMI is 0.43 kg/m(2) higher for each copy of the G allele of single-nucleotide polymorphism rs7596758 (minor allele frequency, 29\%; P=3.46{\texttimes}10(-4)) using a Bonferroni threshold of P<4.6{\texttimes}10(-4). Analyses conditional on previous genome-wide association study single-nucleotide polymorphisms associated with BMI in the region led to attenuation of this signal and uncovered another independent (r(2)<0.2), statistically significant association, rs186019316 (P=2.11{\texttimes}10(-4)). Both rs186019316 and rs7596758 or proxies are located in transcription factor binding regions. No significant association with rare variants was found in either the exons of TMEM18 or the 3{\textquoteright} genome-wide association study region.
CONCLUSIONS: Targeted sequencing around TMEM18 identified 2 novel BMI variants with possible regulatory function.
}, keywords = {Adult, Aged, Aging, Body Mass Index, Cohort Studies, Female, Genetic Association Studies, Genetic Variation, Genome-Wide Association Study, Genomics, Heart Diseases, Humans, Male, Membrane Proteins, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Young Adult}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.13.000067}, author = {Liu, Ching-Ti and Young, Kristin L and Brody, Jennifer A and Olden, Matthias and Wojczynski, Mary K and Heard-Costa, Nancy and Li, Guo and Morrison, Alanna C and Muzny, Donna and Gibbs, Richard A and Reid, Jeffrey G and Shao, Yaming and Zhou, Yanhua and Boerwinkle, Eric and Heiss, Gerardo and Wagenknecht, Lynne and McKnight, Barbara and Borecki, Ingrid B and Fox, Caroline S and North, Kari E and Cupples, L Adrienne} } @article {6547, title = {Sequencing of 2 subclinical atherosclerosis candidate regions in 3669 individuals: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study.}, journal = {Circ Cardiovasc Genet}, volume = {7}, year = {2014}, month = {2014 Jun}, pages = {359-64}, abstract = {BACKGROUND: Atherosclerosis, the precursor to coronary heart disease and stroke, is characterized by an accumulation of fatty cells in the arterial intimal-medial layers. Common carotid intima media thickness (cIMT) and plaque are subclinical atherosclerosis measures that predict cardiovascular disease events. Previously, genome-wide association studies demonstrated evidence for association with cIMT (SLC17A4) and plaque (PIK3CG).
METHODS AND RESULTS: We sequenced 120 kb around SLC17A4 (6p22.2) and 251 kb around PIK3CG (7q22.3) among 3669 European ancestry participants from the Atherosclerosis Risk in Communities (ARIC) study, Cardiovascular Health Study (CHS), and Framingham Heart Study (FHS) in Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Primary analyses focused on 438 common variants (minor allele frequency >=1\%), which were independently meta-analyzed. A 3{\textquoteright} untranslated region CCDC71L variant (rs2286149), upstream from PIK3CG, was the most significant finding in cIMT (P=0.00033) and plaque (P=0.0004) analyses. A SLC17A4 intronic variant was also associated with cIMT (P=0.008). Both were in low linkage disequilibrium with the genome-wide association study single nucleotide polymorphisms. Gene-based tests including T1 count and sequence kernel association test for rare variants (minor allele frequency <1\%) did not yield statistically significant associations. However, we observed nominal associations for rare variants in CCDC71L and SLC17A3 with cIMT and of the entire 7q22 region with plaque (P=0.05).
CONCLUSIONS: Common and rare variants in PIK3CG and SLC17A4 regions demonstrated modest association with subclinical atherosclerosis traits. Although not conclusive, these findings may help to understand the genetic architecture of regions previously implicated by genome-wide association studies and identify variants within these regions for further investigation in larger samples.
}, keywords = {Aged, Aged, 80 and over, Aging, Atherosclerosis, Class Ib Phosphatidylinositol 3-Kinase, Cohort Studies, European Continental Ancestry Group, Female, Genetic Variation, Genome-Wide Association Study, Genomics, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Sodium-Phosphate Cotransporter Proteins, Type I}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.113.000116}, author = {Bis, Joshua C and White, Charles C and Franceschini, Nora and Brody, Jennifer and Zhang, Xiaoling and Muzny, Donna and Santibanez, Jireh and Gibbs, Richard and Liu, Xiaoming and Lin, Honghuang and Boerwinkle, Eric and Psaty, Bruce M and North, Kari E and Cupples, L Adrienne and O{\textquoteright}Donnell, Christopher J} } @article {6577, title = {Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol.}, journal = {Am J Hum Genet}, volume = {94}, year = {2014}, month = {2014 Feb 06}, pages = {233-45}, abstract = {Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.
}, keywords = {Adult, Aged, Apolipoproteins E, Cholesterol, LDL, Cohort Studies, Dyslipidemias, Exome, Female, Follow-Up Studies, Gene Frequency, Genetic Code, Genome-Wide Association Study, Genotype, Humans, Lipase, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Proprotein Convertase 9, Proprotein Convertases, Receptors, LDL, Sequence Analysis, DNA, Serine Endopeptidases}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2014.01.010}, author = {Lange, Leslie A and Hu, Youna and Zhang, He and Xue, Chenyi and Schmidt, Ellen M and Tang, Zheng-Zheng and Bizon, Chris and Lange, Ethan M and Smith, Joshua D and Turner, Emily H and Jun, Goo and Kang, Hyun Min and Peloso, Gina and Auer, Paul and Li, Kuo-Ping and Flannick, Jason and Zhang, Ji and Fuchsberger, Christian and Gaulton, Kyle and Lindgren, Cecilia and Locke, Adam and Manning, Alisa and Sim, Xueling and Rivas, Manuel A and Holmen, Oddgeir L and Gottesman, Omri and Lu, Yingchang and Ruderfer, Douglas and Stahl, Eli A and Duan, Qing and Li, Yun and Durda, Peter and Jiao, Shuo and Isaacs, Aaron and Hofman, Albert and Bis, Joshua C and Correa, Adolfo and Griswold, Michael E and Jakobsdottir, Johanna and Smith, Albert V and Schreiner, Pamela J and Feitosa, Mary F and Zhang, Qunyuan and Huffman, Jennifer E and Crosby, Jacy and Wassel, Christina L and Do, Ron and Franceschini, Nora and Martin, Lisa W and Robinson, Jennifer G and Assimes, Themistocles L and Crosslin, David R and Rosenthal, Elisabeth A and Tsai, Michael and Rieder, Mark J and Farlow, Deborah N and Folsom, Aaron R and Lumley, Thomas and Fox, Ervin R and Carlson, Christopher S and Peters, Ulrike and Jackson, Rebecca D and van Duijn, Cornelia M and Uitterlinden, Andr{\'e} G and Levy, Daniel and Rotter, Jerome I and Taylor, Herman A and Gudnason, Vilmundur and Siscovick, David S and Fornage, Myriam and Borecki, Ingrid B and Hayward, Caroline and Rudan, Igor and Chen, Y Eugene and Bottinger, Erwin P and Loos, Ruth J F and S{\ae}trom, P{\r a}l and Hveem, Kristian and Boehnke, Michael and Groop, Leif and McCarthy, Mark and Meitinger, Thomas and Ballantyne, Christie M and Gabriel, Stacey B and O{\textquoteright}Donnell, Christopher J and Post, Wendy S and North, Kari E and Reiner, Alexander P and Boerwinkle, Eric and Psaty, Bruce M and Altshuler, David and Kathiresan, Sekar and Lin, Dan-Yu and Jarvik, Gail P and Cupples, L Adrienne and Kooperberg, Charles and Wilson, James G and Nickerson, Deborah A and Abecasis, Goncalo R and Rich, Stephen S and Tracy, Russell P and Willer, Cristen J} } @article {6844, title = {Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians.}, journal = {Am J Clin Nutr}, volume = {102}, year = {2015}, month = {2015 Nov}, pages = {1266-78}, abstract = {BACKGROUND: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.
OBJECTIVE: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.
DESIGN: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.
RESULTS: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95\% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95\% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95\% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.
CONCLUSION: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).
}, keywords = {Blood Glucose, Cohort Studies, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hyperglycemia, Hyperinsulinism, Insulin, Insulin Resistance, Insulin-Secreting Cells, Meat, Meat Products, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors}, issn = {1938-3207}, doi = {10.3945/ajcn.114.101238}, author = {Fretts, Amanda M and Follis, Jack L and Nettleton, Jennifer A and Lemaitre, Rozenn N and Ngwa, Julius S and Wojczynski, Mary K and Kalafati, Ioanna Panagiota and Varga, Tibor V and Frazier-Wood, Alexis C and Houston, Denise K and Lahti, Jari and Ericson, Ulrika and van den Hooven, Edith H and Mikkil{\"a}, Vera and Kiefte-de Jong, Jessica C and Mozaffarian, Dariush and Rice, Kenneth and Renstrom, Frida and North, Kari E and McKeown, Nicola M and Feitosa, Mary F and Kanoni, Stavroula and Smith, Caren E and Garcia, Melissa E and Tiainen, Anna-Maija and Sonestedt, Emily and Manichaikul, Ani and van Rooij, Frank J A and Dimitriou, Maria and Raitakari, Olli and Pankow, James S and Djouss{\'e}, Luc and Province, Michael A and Hu, Frank B and Lai, Chao-Qiang and Keller, Margaux F and Per{\"a}l{\"a}, Mia-Maria and Rotter, Jerome I and Hofman, Albert and Graff, Misa and K{\"a}h{\"o}nen, Mika and Mukamal, Kenneth and Johansson, Ingegerd and Ordovas, Jose M and Liu, Yongmei and M{\"a}nnist{\"o}, Satu and Uitterlinden, Andr{\'e} G and Deloukas, Panos and Sepp{\"a}l{\"a}, Ilkka and Psaty, Bruce M and Cupples, L Adrienne and Borecki, Ingrid B and Franks, Paul W and Arnett, Donna K and Nalls, Mike A and Eriksson, Johan G and Orho-Melander, Marju and Franco, Oscar H and Lehtim{\"a}ki, Terho and Dedoussis, George V and Meigs, James B and Siscovick, David S} } @article {6802, title = {Gene {\texttimes} dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry.}, journal = {Hum Mol Genet}, volume = {24}, year = {2015}, month = {2015 Aug 15}, pages = {4728-38}, abstract = {Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphisms were genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjusted WHR~and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.
}, keywords = {Adult, Body Mass Index, Case-Control Studies, Diet, Western, Epistasis, Genetic, European Continental Ancestry Group, Female, Genetic Loci, Genome-Wide Association Study, Humans, Male, Obesity, Polymorphism, Single Nucleotide}, issn = {1460-2083}, doi = {10.1093/hmg/ddv186}, author = {Nettleton, Jennifer A and Follis, Jack L and Ngwa, Julius S and Smith, Caren E and Ahmad, Shafqat and Tanaka, Toshiko and Wojczynski, Mary K and Voortman, Trudy and Lemaitre, Rozenn N and Kristiansson, Kati and Nuotio, Marja-Liisa and Houston, Denise K and Per{\"a}l{\"a}, Mia-Maria and Qi, Qibin and Sonestedt, Emily and Manichaikul, Ani and Kanoni, Stavroula and Ganna, Andrea and Mikkil{\"a}, Vera and North, Kari E and Siscovick, David S and Harald, Kennet and McKeown, Nicola M and Johansson, Ingegerd and Rissanen, Harri and Liu, Yongmei and Lahti, Jari and Hu, Frank B and Bandinelli, Stefania and Rukh, Gull and Rich, Stephen and Booij, Lisanne and Dmitriou, Maria and Ax, Erika and Raitakari, Olli and Mukamal, Kenneth and M{\"a}nnist{\"o}, Satu and Hallmans, G{\"o}ran and Jula, Antti and Ericson, Ulrika and Jacobs, David R and van Rooij, Frank J A and Deloukas, Panos and Sjogren, Per and K{\"a}h{\"o}nen, Mika and Djouss{\'e}, Luc and Perola, Markus and Barroso, In{\^e}s and Hofman, Albert and Stirrups, Kathleen and Viikari, Jorma and Uitterlinden, Andr{\'e} G and Kalafati, Ioanna P and Franco, Oscar H and Mozaffarian, Dariush and Salomaa, Veikko and Borecki, Ingrid B and Knekt, Paul and Kritchevsky, Stephen B and Eriksson, Johan G and Dedoussis, George V and Qi, Lu and Ferrucci, Luigi and Orho-Melander, Marju and Zillikens, M Carola and Ingelsson, Erik and Lehtim{\"a}ki, Terho and Renstrom, Frida and Cupples, L Adrienne and Loos, Ruth J F and Franks, Paul W} } @article {6860, title = {Integrative pathway genomics of lung function and airflow obstruction.}, journal = {Hum Mol Genet}, volume = {24}, year = {2015}, month = {2015 Dec 1}, pages = {6836-48}, abstract = {Chronic respiratory disorders are important contributors to the global burden of disease. Genome-wide association studies (GWASs) of lung function measures have identified several trait-associated loci, but explain only a modest portion of the phenotypic variability. We postulated that integrating pathway-based methods with GWASs of pulmonary function and airflow obstruction would identify a broader repertoire of genes and processes influencing these traits. We performed two independent GWASs of lung function and applied gene set enrichment analysis to one of the studies and validated the results using the second GWAS. We identified 131 significantly enriched gene sets associated with lung function and clustered them into larger biological modules involved in diverse processes including development, immunity, cell signaling, proliferation and arachidonic acid. We found that enrichment of gene sets was not driven by GWAS-significant variants or loci, but instead by those with less stringent association P-values. Next, we applied pathway enrichment analysis to a meta-analyzed GWAS of airflow obstruction. We identified several biologic modules that functionally overlapped with those associated with pulmonary function. However, differences were also noted, including enrichment of extracellular matrix (ECM) processes specifically in the airflow obstruction study. Network analysis of the ECM module implicated a candidate gene, matrix metalloproteinase 10 (MMP10), as a putative disease target. We used a knockout mouse model to functionally validate MMP10{\textquoteright}s role in influencing lung{\textquoteright}s susceptibility to cigarette smoke-induced emphysema. By integrating pathway analysis with population-based genomics, we unraveled biologic processes underlying pulmonary function traits and identified a candidate gene for obstructive lung disease.
}, keywords = {Airway Obstruction, Animals, Cell Proliferation, European Continental Ancestry Group, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Immune System, Lung, Male, Metabolic Networks and Pathways, Mice, Phenotype, Polymorphism, Single Nucleotide, Signal Transduction}, issn = {1460-2083}, doi = {10.1093/hmg/ddv378}, author = {Gharib, Sina A and Loth, Daan W and Soler Artigas, Maria and Birkland, Timothy P and Wilk, Jemma B and Wain, Louise V and Brody, Jennifer A and Obeidat, Ma{\textquoteright}en and Hancock, Dana B and Tang, Wenbo and Rawal, Rajesh and Boezen, H Marike and Imboden, Medea and Huffman, Jennifer E and Lahousse, Lies and Alves, Alexessander C and Manichaikul, Ani and Hui, Jennie and Morrison, Alanna C and Ramasamy, Adaikalavan and Smith, Albert Vernon and Gudnason, Vilmundur and Surakka, Ida and Vitart, Veronique and Evans, David M and Strachan, David P and Deary, Ian J and Hofman, Albert and Gl{\"a}ser, Sven and Wilson, James F and North, Kari E and Zhao, Jing Hua and Heckbert, Susan R and Jarvis, Deborah L and Probst-Hensch, Nicole and Schulz, Holger and Barr, R Graham and Jarvelin, Marjo-Riitta and O{\textquoteright}Connor, George T and K{\"a}h{\"o}nen, Mika and Cassano, Patricia A and Hysi, Pirro G and Dupuis, Jos{\'e}e and Hayward, Caroline and Psaty, Bruce M and Hall, Ian P and Parks, William C and Tobin, Martin D and London, Stephanie J} } @article {6568, title = {Mendelian randomization of blood lipids for coronary heart disease.}, journal = {Eur Heart J}, volume = {36}, year = {2015}, month = {2015 Mar 01}, pages = {539-50}, abstract = {AIMS: To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization.
METHODS AND RESULTS: We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 {\texttimes} 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P <= 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95\% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95\% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95\% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95\% CI: 1.24, 2.11 and 1.61; 95\% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95\% CI: 0.59, 1.75).
CONCLUSION: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.
}, keywords = {Case-Control Studies, Cholesterol, HDL, Coronary Artery Disease, Female, Gene Frequency, Genotype, Genotyping Techniques, Humans, Male, Mendelian Randomization Analysis, Middle Aged, Polymorphism, Single Nucleotide, Risk Assessment, Triglycerides}, issn = {1522-9645}, doi = {10.1093/eurheartj/eht571}, author = {Holmes, Michael V and Asselbergs, Folkert W and Palmer, Tom M and Drenos, Fotios and Lanktree, Matthew B and Nelson, Christopher P and Dale, Caroline E and Padmanabhan, Sandosh and Finan, Chris and Swerdlow, Daniel I and Tragante, Vinicius and van Iperen, Erik P A and Sivapalaratnam, Suthesh and Shah, Sonia and Elbers, Clara C and Shah, Tina and Engmann, Jorgen and Giambartolomei, Claudia and White, Jon and Zabaneh, Delilah and Sofat, Reecha and McLachlan, Stela and Doevendans, Pieter A and Balmforth, Anthony J and Hall, Alistair S and North, Kari E and Almoguera, Berta and Hoogeveen, Ron C and Cushman, Mary and Fornage, Myriam and Patel, Sanjay R and Redline, Susan and Siscovick, David S and Tsai, Michael Y and Karczewski, Konrad J and Hofker, Marten H and Verschuren, W Monique and Bots, Michiel L and van der Schouw, Yvonne T and Melander, Olle and Dominiczak, Anna F and Morris, Richard and Ben-Shlomo, Yoav and Price, Jackie and Kumari, Meena and Baumert, Jens and Peters, Annette and Thorand, Barbara and Koenig, Wolfgang and Gaunt, Tom R and Humphries, Steve E and Clarke, Robert and Watkins, Hugh and Farrall, Martin and Wilson, James G and Rich, Stephen S and de Bakker, Paul I W and Lange, Leslie A and Davey Smith, George and Reiner, Alex P and Talmud, Philippa J and Kivimaki, Mika and Lawlor, Debbie A and Dudbridge, Frank and Samani, Nilesh J and Keating, Brendan J and Hingorani, Aroon D and Casas, Juan P} } @article {7259, title = {Fine-mapping, novel loci identification, and SNP association transferability in a genome-wide association study of QRS duration in African Americans.}, journal = {Hum Mol Genet}, year = {2016}, month = {2016 Aug 29}, abstract = {The electrocardiographic QRS duration, a measure of ventricular depolarization and conduction, is associated with cardiovascular mortality. While single nucleotide polymorphisms (SNPs) associated with QRS duration have been identified at 22 loci in populations of European descent, the genetic architecture of QRS duration in non-European populations is largely unknown. We therefore performed a genome-wide association study (GWAS) meta-analysis of QRS duration in 13,031 African Americans from ten cohorts and a transethnic GWAS meta-analysis with additional results from populations of European descent. In the African American GWAS, a single genome-wide significant SNP association was identified (rs3922844, P = 4 {\texttimes} 10(-14)) in intron 16 of SCN5A, a voltage-gated cardiac sodium channel gene. The QRS-prolonging rs3922844 C allele was also associated with decreased SCN5A RNA expression in human atrial tissue (P = 1.1 {\texttimes} 10(-4)). High density genotyping revealed that the SCN5A association region in African Americans was confined to intron 16. Transethnic GWAS meta-analysis identified novel SNP associations on chromosome 18 in MYL12A (rs1662342, P = 4.9 {\texttimes} 10(-8)) and chromosome 1 near CD1E and SPTA1 (rs7547997, P = 7.9 {\texttimes} 10(-9)). The 22 QRS loci previously identified in populations of European descent were enriched for significant SNP associations with QRS duration in African Americans (P = 9.9 {\texttimes} 10(-7)), and index SNP associations in or near SCN5A, SCN10A, CDKN1A, NFIA, HAND1, TBX5 and SETBP1 replicated in African Americans. In summary, rs3922844 was associated with QRS duration and SCN5A expression, two novel QRS loci were identified using transethnic meta-analysis, and a significant proportion of QRS-SNP associations discovered in populations of European descent were transferable to African Americans when adequate power was achieved.
}, issn = {1460-2083}, doi = {10.1093/hmg/ddw284}, author = {Evans, Daniel S and Avery, Christy L and Nalls, Mike A and Li, Guo and Barnard, John and Smith, Erin N and Tanaka, Toshiko and Butler, Anne M and Buxbaum, Sarah G and Alonso, Alvaro and Arking, Dan E and Berenson, Gerald S and Bis, Joshua C and Buyske, Steven and Carty, Cara L and Chen, Wei and Chung, Mina K and Cummings, Steven R and Deo, Rajat and Eaton, Charles B and Fox, Ervin R and Heckbert, Susan R and Heiss, Gerardo and Hindorff, Lucia A and Hsueh, Wen-Chi and Isaacs, Aaron and Jamshidi, Yalda and Kerr, Kathleen F and Liu, Felix and Liu, Yongmei and Lohman, Kurt K and Magnani, Jared W and Maher, Joseph F and Mehra, Reena and Meng, Yan A and Musani, Solomon K and Newton-Cheh, Christopher and North, Kari E and Psaty, Bruce M and Redline, Susan and Rotter, Jerome I and Schnabel, Renate B and Schork, Nicholas J and Shohet, Ralph V and Singleton, Andrew B and Smith, Jonathan D and Soliman, Elsayed Z and Srinivasan, Sathanur R and Taylor, Herman A and Van Wagoner, David R and Wilson, James G and Young, Taylor and Zhang, Zhu-Ming and Zonderman, Alan B and Evans, Michele K and Ferrucci, Luigi and Murray, Sarah S and Tranah, Gregory J and Whitsel, Eric A and Reiner, Alex P and Sotoodehnia, Nona} } @article {7593, title = {A genome-wide association study meta-analysis of clinical fracture in 10,012 African American women.}, journal = {Bone Rep}, volume = {5}, year = {2016}, month = {2016 Dec}, pages = {233-242}, abstract = {BACKGROUND: Osteoporosis is a major public health problem associated with excess disability and mortality. It is estimated that 50-70\% of the variation in osteoporotic fracture risk is attributable to genetic factors. The purpose of this hypothesis-generating study was to identify possible genetic determinants of fracture among African American (AA) women in a GWAS meta-analysis.
METHODS: Data on clinical fractures (all fractures except fingers, toes, face, skull or sternum) were analyzed among AA female participants in the Women{\textquoteright}s Health Initiative (WHI) (N~=~8155), Cardiovascular Health Study (CHS) (N~=~504), BioVU (N~=~704), Health ABC (N~=~651), and the Johnston County Osteoarthritis Project (JoCoOA) (N~=~291). Affymetrix (WHI) and Illumina (Health ABC, JoCoOA, BioVU, CHS) GWAS panels were used for genotyping, and a 1:1 ratio of YRI:CEU HapMap haplotypes was used as an imputation reference panel. We used Cox proportional hazard models or logistic regression to evaluate the association of ~~2.5 million SNPs with fracture risk, adjusting for ancestry, age, and geographic region where applicable. We conducted a fixed-effects, inverse variance-weighted meta-analysis. Genome-wide significance was set at P~<~5~{\texttimes}~10-~8.
RESULTS: One SNP, rs12775980 in an intron of SVIL on chromosome 10p11.2, reached genome-wide significance (P~=~4.0~{\texttimes}~10-~8). Although this SNP has a low minor allele frequency (0.03), there was no evidence for heterogeneity of effects across the studies (I2~=~0). This locus was not reported in any previous osteoporosis-related GWA studies. We also interrogated previously reported GWA-significant loci associated with fracture or bone mineral density in our data. One locus (SMOC1) generalized, but overall there was not substantial evidence of generalization. Possible reasons for the lack of generalization are discussed.
CONCLUSION: This GWAS meta-analysis of fractures in African American women identified a potentially novel locus in the supervillin gene, which encodes a platelet-associated factor and was previously associated with platelet thrombus formation in African Americans. If validated in other populations of African descent, these findings suggest potential new mechanisms involved in fracture that may be particularly important among African Americans.
}, issn = {2352-1872}, doi = {10.1016/j.bonr.2016.08.005}, author = {Taylor, Kira C and Evans, Daniel S and Edwards, Digna R Velez and Edwards, Todd L and Sofer, Tamar and Li, Guo and Liu, Youfang and Franceschini, Nora and Jackson, Rebecca D and Giri, Ayush and Donneyong, Macarius and Psaty, Bruce and Rotter, Jerome I and LaCroix, Andrea Z and Jordan, Joanne M and Robbins, John A and Lewis, Beth and Stefanick, Marcia L and Liu, Yongmei and Garcia, Melissa and Harris, Tamara and Cauley, Jane A and North, Kari E} } @article {7257, title = {Multiethnic Exome-Wide Association Study of Subclinical Atherosclerosis.}, journal = {Circ Cardiovasc Genet}, year = {2016}, month = {2016 Nov 21}, abstract = {BACKGROUND: -The burden of subclinical atherosclerosis in asymptomatic individuals is heritable and associated with elevated risk of developing clinical coronary heart disease (CHD). We sought to identify genetic variants in protein-coding regions associated with subclinical atherosclerosis and the risk of subsequent CHD.
METHODS AND RESULTS: -We studied a total of 25,109 European ancestry and African-American participants with coronary artery calcification (CAC) measured by cardiac computed tomography and 52,869 with common carotid intima media thickness (CIMT) measured by ultrasonography within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Participants were genotyped for 247,870 DNA sequence variants (231,539 in exons) across the genome. A meta-analysis of exome-wide association studies was performed across cohorts for CAC and CIMT. APOB p.Arg3527Gln was associated with four-fold excess CAC (P = 3{\texttimes}10(-10)). The APOE ε2 allele (p.Arg176Cys) was associated with both 22.3\% reduced CAC (P = 1{\texttimes}10(-12)) and 1.4\% reduced CIMT (P = 4{\texttimes}10(-14)) in carriers compared with non-carriers. In secondary analyses conditioning on LDL cholesterol concentration, the ε2 protective association with CAC, although attenuated, remained strongly significant. Additionally, the presence of ε2 was associated with reduced risk for CHD (OR 0.77; P = 1{\texttimes}10(-11)).
CONCLUSIONS: -Exome-wide association meta-analysis demonstrates that protein-coding variants in APOB and APOE associate with subclinical atherosclerosis. APOE ε2 represents the first significant association for multiple subclinical atherosclerosis traits across multiple ethnicities as well as clinical CHD.
}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.116.001572}, author = {Natarajan, Pradeep and Bis, Joshua C and Bielak, Lawrence F and Cox, Amanda J and D{\"o}rr, Marcus and Feitosa, Mary F and Franceschini, Nora and Guo, Xiuqing and Hwang, Shih-Jen and Isaacs, Aaron and Jhun, Min A and Kavousi, Maryam and Li-Gao, Ruifang and Lyytik{\"a}inen, Leo-Pekka and Marioni, Riccardo E and Schminke, Ulf and Stitziel, Nathan O and Tada, Hayato and van Setten, Jessica and Smith, Albert V and Vojinovic, Dina and Yanek, Lisa R and Yao, Jie and Yerges-Armstrong, Laura M and Amin, Najaf and Baber, Usman and Borecki, Ingrid B and Carr, J Jeffrey and Chen, Yii-Der Ida and Cupples, L Adrienne and de Jong, Pim A and de Koning, Harry and de Vos, Bob D and Demirkan, Ayse and Fuster, Valentin and Franco, Oscar H and Goodarzi, Mark O and Harris, Tamara B and Heckbert, Susan R and Heiss, Gerardo and Hoffmann, Udo and Hofman, Albert and I{\v s}gum, Ivana and Jukema, J Wouter and K{\"a}h{\"o}nen, Mika and Kardia, Sharon L R and Kral, Brian G and Launer, Lenore J and Massaro, Joseph and Mehran, Roxana and Mitchell, Braxton D and Mosley, Thomas H and de Mutsert, Ren{\'e}e and Newman, Anne B and Nguyen, Khanh-Dung and North, Kari E and O{\textquoteright}Connell, Jeffrey R and Oudkerk, Matthijs and Pankow, James S and Peloso, Gina M and Post, Wendy and Province, Michael A and Raffield, Laura M and Raitakari, Olli T and Reilly, Dermot F and Rivadeneira, Fernando and Rosendaal, Frits and Sartori, Samantha and Taylor, Kent D and Teumer, Alexander and Trompet, Stella and Turner, Stephen T and Uitterlinden, Andr{\'e} G and Vaidya, Dhananjay and van der Lugt, Aad and V{\"o}lker, Uwe and Wardlaw, Joanna M and Wassel, Christina L and Weiss, Stefan and Wojczynski, Mary K and Becker, Diane M and Becker, Lewis C and Boerwinkle, Eric and Bowden, Donald W and Deary, Ian J and Dehghan, Abbas and Felix, Stephan B and Gudnason, Vilmundur and Lehtim{\"a}ki, Terho and Mathias, Rasika and Mook-Kanamori, Dennis O and Psaty, Bruce M and Rader, Daniel J and Rotter, Jerome I and Wilson, James G and van Duijn, Cornelia M and V{\"o}lzke, Henry and Kathiresan, Sekar and Peyser, Patricia A and O{\textquoteright}Donnell, Christopher J} } @article {8570, title = {A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape.}, journal = {Nat Commun}, volume = {7}, year = {2016}, month = {2016 11 23}, pages = {13357}, abstract = {Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99\% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
}, keywords = {Anthropometry, Body Size, Genome-Wide Association Study, Genotype, Humans, Models, Genetic, Principal Component Analysis}, issn = {2041-1723}, doi = {10.1038/ncomms13357}, author = {Ried, Janina S and Jeff M, Janina and Chu, Audrey Y and Bragg-Gresham, Jennifer L and van Dongen, Jenny and Huffman, Jennifer E and Ahluwalia, Tarunveer S and Cadby, Gemma and Eklund, Niina and Eriksson, Joel and Esko, T{\~o}nu and Feitosa, Mary F and Goel, Anuj and Gorski, Mathias and Hayward, Caroline and Heard-Costa, Nancy L and Jackson, Anne U and Jokinen, Eero and Kanoni, Stavroula and Kristiansson, Kati and Kutalik, Zolt{\'a}n and Lahti, Jari and Luan, Jian{\textquoteright}an and M{\"a}gi, Reedik and Mahajan, Anubha and Mangino, Massimo and Medina-G{\'o}mez, Carolina and Monda, Keri L and Nolte, Ilja M and Perusse, Louis and Prokopenko, Inga and Qi, Lu and Rose, Lynda M and Salvi, Erika and Smith, Megan T and Snieder, Harold and Stan{\v c}{\'a}kov{\'a}, Alena and Ju Sung, Yun and Tachmazidou, Ioanna and Teumer, Alexander and Thorleifsson, Gudmar and van der Harst, Pim and Walker, Ryan W and Wang, Sophie R and Wild, Sarah H and Willems, Sara M and Wong, Andrew and Zhang, Weihua and Albrecht, Eva and Couto Alves, Alexessander and Bakker, Stephan J L and Barlassina, Cristina and Bartz, Traci M and Beilby, John and Bellis, Claire and Bergman, Richard N and Bergmann, Sven and Blangero, John and Bl{\"u}her, Matthias and Boerwinkle, Eric and Bonnycastle, Lori L and Bornstein, Stefan R and Bruinenberg, Marcel and Campbell, Harry and Chen, Yii-Der Ida and Chiang, Charleston W K and Chines, Peter S and Collins, Francis S and Cucca, Fracensco and Cupples, L Adrienne and D{\textquoteright}Avila, Francesca and de Geus, Eco J C and Dedoussis, George and Dimitriou, Maria and D{\"o}ring, Angela and Eriksson, Johan G and Farmaki, Aliki-Eleni and Farrall, Martin and Ferreira, Teresa and Fischer, Krista and Forouhi, Nita G and Friedrich, Nele and Gjesing, Anette Prior and Glorioso, Nicola and Graff, Mariaelisa and Grallert, Harald and Grarup, Niels and Gr{\"a}{\ss}ler, J{\"u}rgen and Grewal, Jagvir and Hamsten, Anders and Harder, Marie Neergaard and Hartman, Catharina A and Hassinen, Maija and Hastie, Nicholas and Hattersley, Andrew Tym and Havulinna, Aki S and Heli{\"o}vaara, Markku and Hillege, Hans and Hofman, Albert and Holmen, Oddgeir and Homuth, Georg and Hottenga, Jouke-Jan and Hui, Jennie and Husemoen, Lise Lotte and Hysi, Pirro G and Isaacs, Aaron and Ittermann, Till and Jalilzadeh, Shapour and James, Alan L and J{\o}rgensen, Torben and Jousilahti, Pekka and Jula, Antti and Marie Justesen, Johanne and Justice, Anne E and K{\"a}h{\"o}nen, Mika and Karaleftheri, Maria and Tee Khaw, Kay and Keinanen-Kiukaanniemi, Sirkka M and Kinnunen, Leena and Knekt, Paul B and Koistinen, Heikki A and Kolcic, Ivana and Kooner, Ishminder K and Koskinen, Seppo and Kovacs, Peter and Kyriakou, Theodosios and Laitinen, Tomi and Langenberg, Claudia and Lewin, Alexandra M and Lichtner, Peter and Lindgren, Cecilia M and Lindstr{\"o}m, Jaana and Linneberg, Allan and Lorbeer, Roberto and Lorentzon, Mattias and Luben, Robert and Lyssenko, Valeriya and M{\"a}nnist{\"o}, Satu and Manunta, Paolo and Leach, Irene Mateo and McArdle, Wendy L and McKnight, Barbara and Mohlke, Karen L and Mihailov, Evelin and Milani, Lili and Mills, Rebecca and Montasser, May E and Morris, Andrew P and M{\"u}ller, Gabriele and Musk, Arthur W and Narisu, Narisu and Ong, Ken K and Oostra, Ben A and Osmond, Clive and Palotie, Aarno and Pankow, James S and Paternoster, Lavinia and Penninx, Brenda W and Pichler, Irene and Pilia, Maria G and Polasek, Ozren and Pramstaller, Peter P and Raitakari, Olli T and Rankinen, Tuomo and Rao, D C and Rayner, Nigel W and Ribel-Madsen, Rasmus and Rice, Treva K and Richards, Marcus and Ridker, Paul M and Rivadeneira, Fernando and Ryan, Kathy A and Sanna, Serena and Sarzynski, Mark A and Scholtens, Salome and Scott, Robert A and Sebert, Sylvain and Southam, Lorraine and Spars{\o}, Thomas Hempel and Steinthorsdottir, Valgerdur and Stirrups, Kathleen and Stolk, Ronald P and Strauch, Konstantin and Stringham, Heather M and Swertz, Morris A and Swift, Amy J and T{\"o}njes, Anke and Tsafantakis, Emmanouil and van der Most, Peter J and van Vliet-Ostaptchouk, Jana V and Vandenput, Liesbeth and Vartiainen, Erkki and Venturini, Cristina and Verweij, Niek and Viikari, Jorma S and Vitart, Veronique and Vohl, Marie-Claude and Vonk, Judith M and Waeber, G{\'e}rard and Widen, Elisabeth and Willemsen, Gonneke and Wilsgaard, Tom and Winkler, Thomas W and Wright, Alan F and Yerges-Armstrong, Laura M and Hua Zhao, Jing and Zillikens, M Carola and Boomsma, Dorret I and Bouchard, Claude and Chambers, John C and Chasman, Daniel I and Cusi, Daniele and Gansevoort, Ron T and Gieger, Christian and Hansen, Torben and Hicks, Andrew A and Hu, Frank and Hveem, Kristian and Jarvelin, Marjo-Riitta and Kajantie, Eero and Kooner, Jaspal S and Kuh, Diana and Kuusisto, Johanna and Laakso, Markku and Lakka, Timo A and Lehtim{\"a}ki, Terho and Metspalu, Andres and Nj{\o}lstad, Inger and Ohlsson, Claes and Oldehinkel, Albertine J and Palmer, Lyle J and Pedersen, Oluf and Perola, Markus and Peters, Annette and Psaty, Bruce M and Puolijoki, Hannu and Rauramaa, Rainer and Rudan, Igor and Salomaa, Veikko and Schwarz, Peter E H and Shudiner, Alan R and Smit, Jan H and S{\o}rensen, Thorkild I A and Spector, Timothy D and Stefansson, Kari and Stumvoll, Michael and Tremblay, Angelo and Tuomilehto, Jaakko and Uitterlinden, Andr{\'e} G and Uusitupa, Matti and V{\"o}lker, Uwe and Vollenweider, Peter and Wareham, Nicholas J and Watkins, Hugh and Wilson, James F and Zeggini, Eleftheria and Abecasis, Goncalo R and Boehnke, Michael and Borecki, Ingrid B and Deloukas, Panos and van Duijn, Cornelia M and Fox, Caroline and Groop, Leif C and Heid, Iris M and Hunter, David J and Kaplan, Robert C and McCarthy, Mark I and North, Kari E and O{\textquoteright}Connell, Jeffrey R and Schlessinger, David and Thorsteinsdottir, Unnur and Strachan, David P and Frayling, Timothy and Hirschhorn, Joel N and M{\"u}ller-Nurasyid, Martina and Loos, Ruth J F} } @article {6937, title = {Rare Exome Sequence Variants in CLCN6 Reduce Blood Pressure Levels and Hypertension Risk.}, journal = {Circ Cardiovasc Genet}, volume = {9}, year = {2016}, month = {2016 Feb}, pages = {64-70}, abstract = {BACKGROUND: Rare genetic variants influence blood pressure (BP).
METHODS AND RESULTS: Whole-exome sequencing was performed on DNA samples from 17 956 individuals of European ancestry and African ancestry (14 497, first-stage discovery and 3459, second-stage discovery) to examine the effect of rare variants on hypertension and 4 BP traits: systolic BP, diastolic BP, pulse pressure, and mean arterial pressure. Tests of ≈170 000 common variants (minor allele frequency, >=1\%; statistical significance, P<=2.9{\texttimes}10(-7)) and gene-based tests of rare variants (minor allele frequency, <1\%; ≈17 000 genes; statistical significance, P<=1.5{\texttimes}10(-6)) were evaluated for each trait and ancestry, followed by multiethnic meta-analyses. In the first-stage discovery, rare coding variants (splicing, stop-gain, stop-loss, nonsynonymous variants, or indels) in CLCN6 were associated with lower diastolic BP (cumulative minor allele frequency, 1.3\%; β=-3.20; P=4.1{\texttimes}10(-6)) and were independent of a nearby common variant (rs17367504) previously associated with BP. CLCN6 rare variants were also associated with lower systolic BP (β=-4.11; P=2.8{\texttimes}10(-4)), mean arterial pressure (β=-3.50; P=8.9{\texttimes}10(-6)), and reduced hypertension risk (odds ratio, 0.72; P=0.017). Meta-analysis of the 2-stage discovery samples showed that CLCN6 was associated with lower diastolic BP at exome-wide significance (cumulative minor allele frequency, 1.1\%; β=-3.30; P=5.0{\texttimes}10(-7)).
CONCLUSIONS: These findings implicate the effect of rare coding variants in CLCN6 in BP variation and offer new insights into BP regulation.
}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.115.001215}, author = {Yu, Bing and Pulit, Sara L and Hwang, Shih-Jen and Brody, Jennifer A and Amin, Najaf and Auer, Paul L and Bis, Joshua C and Boerwinkle, Eric and Burke, Gregory L and Chakravarti, Aravinda and Correa, Adolfo and Dreisbach, Albert W and Franco, Oscar H and Ehret, Georg B and Franceschini, Nora and Hofman, Albert and Lin, Dan-Yu and Metcalf, Ginger A and Musani, Solomon K and Muzny, Donna and Palmas, Walter and Raffel, Leslie and Reiner, Alex and Rice, Ken and Rotter, Jerome I and Veeraraghavan, Narayanan and Fox, Ervin and Guo, Xiuqing and North, Kari E and Gibbs, Richard A and van Duijn, Cornelia M and Psaty, Bruce M and Levy, Daniel and Newton-Cheh, Christopher and Morrison, Alanna C} } @article {7141, title = {Trans-ethnic Meta-analysis and Functional Annotation Illuminates the~Genetic Architecture of Fasting Glucose and Insulin.}, journal = {Am J Hum Genet}, volume = {99}, year = {2016}, month = {2016 Jul 7}, pages = {56-75}, abstract = {Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.
}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2016.05.006}, author = {Liu, Ching-Ti and Raghavan, Sridharan and Maruthur, Nisa and Kabagambe, Edmond Kato and Hong, Jaeyoung and Ng, Maggie C Y and Hivert, Marie-France and Lu, Yingchang and An, Ping and Bentley, Amy R and Drolet, Anne M and Gaulton, Kyle J and Guo, Xiuqing and Armstrong, Loren L and Irvin, Marguerite R and Li, Man and Lipovich, Leonard and Rybin, Denis V and Taylor, Kent D and Agyemang, Charles and Palmer, Nicholette D and Cade, Brian E and Chen, Wei-Min and Dauriz, Marco and Delaney, Joseph A C and Edwards, Todd L and Evans, Daniel S and Evans, Michele K and Lange, Leslie A and Leong, Aaron and Liu, Jingmin and Liu, Yongmei and Nayak, Uma and Patel, Sanjay R and Porneala, Bianca C and Rasmussen-Torvik, Laura J and Snijder, Marieke B and Stallings, Sarah C and Tanaka, Toshiko and Yanek, Lisa R and Zhao, Wei and Becker, Diane M and Bielak, Lawrence F and Biggs, Mary L and Bottinger, Erwin P and Bowden, Donald W and Chen, Guanjie and Correa, Adolfo and Couper, David J and Crawford, Dana C and Cushman, Mary and Eicher, John D and Fornage, Myriam and Franceschini, Nora and Fu, Yi-Ping and Goodarzi, Mark O and Gottesman, Omri and Hara, Kazuo and Harris, Tamara B and Jensen, Richard A and Johnson, Andrew D and Jhun, Min A and Karter, Andrew J and Keller, Margaux F and Kho, Abel N and Kizer, Jorge R and Krauss, Ronald M and Langefeld, Carl D and Li, Xiaohui and Liang, Jingling and Liu, Simin and Lowe, William L and Mosley, Thomas H and North, Kari E and Pacheco, Jennifer A and Peyser, Patricia A and Patrick, Alan L and Rice, Kenneth M and Selvin, Elizabeth and Sims, Mario and Smith, Jennifer A and Tajuddin, Salman M and Vaidya, Dhananjay and Wren, Mary P and Yao, Jie and Zhu, Xiaofeng and Ziegler, Julie T and Zmuda, Joseph M and Zonderman, Alan B and Zwinderman, Aeilko H and Adeyemo, Adebowale and Boerwinkle, Eric and Ferrucci, Luigi and Hayes, M Geoffrey and Kardia, Sharon L R and Miljkovic, Iva and Pankow, James S and Rotimi, Charles N and Sale, Mich{\`e}le M and Wagenknecht, Lynne E and Arnett, Donna K and Chen, Yii-Der Ida and Nalls, Michael A and Province, Michael A and Kao, W H Linda and Siscovick, David S and Psaty, Bruce M and Wilson, James G and Loos, Ruth J F and Dupuis, Jos{\'e}e and Rich, Stephen S and Florez, Jose C and Rotter, Jerome I and Morris, Andrew P and Meigs, James B} } @article {7352, title = {Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African ancestry anthropometry genetics consortium.}, journal = {PLoS Genet}, volume = {13}, year = {2017}, month = {2017 Apr 21}, pages = {e1006719}, abstract = {Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5{\texttimes}10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5\%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained <= 20 variants in the credible sets that jointly account for 99\% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.
}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1006719}, author = {Ng, Maggie C Y and Graff, Mariaelisa and Lu, Yingchang and Justice, Anne E and Mudgal, Poorva and Liu, Ching-Ti and Young, Kristin and Yanek, Lisa R and Feitosa, Mary F and Wojczynski, Mary K and Rand, Kristin and Brody, Jennifer A and Cade, Brian E and Dimitrov, Latchezar and Duan, Qing and Guo, Xiuqing and Lange, Leslie A and Nalls, Michael A and Okut, Hayrettin and Tajuddin, Salman M and Tayo, Bamidele O and Vedantam, Sailaja and Bradfield, Jonathan P and Chen, Guanjie and Chen, Wei-Min and Chesi, Alessandra and Irvin, Marguerite R and Padhukasahasram, Badri and Smith, Jennifer A and Zheng, Wei and Allison, Matthew A and Ambrosone, Christine B and Bandera, Elisa V and Bartz, Traci M and Berndt, Sonja I and Bernstein, Leslie and Blot, William J and Bottinger, Erwin P and Carpten, John and Chanock, Stephen J and Chen, Yii-Der Ida and Conti, David V and Cooper, Richard S and Fornage, Myriam and Freedman, Barry I and Garcia, Melissa and Goodman, Phyllis J and Hsu, Yu-Han H and Hu, Jennifer and Huff, Chad D and Ingles, Sue A and John, Esther M and Kittles, Rick and Klein, Eric and Li, Jin and McKnight, Barbara and Nayak, Uma and Nemesure, Barbara and Ogunniyi, Adesola and Olshan, Andrew and Press, Michael F and Rohde, Rebecca and Rybicki, Benjamin A and Salako, Babatunde and Sanderson, Maureen and Shao, Yaming and Siscovick, David S and Stanford, Janet L and Stevens, Victoria L and Stram, Alex and Strom, Sara S and Vaidya, Dhananjay and Witte, John S and Yao, Jie and Zhu, Xiaofeng and Ziegler, Regina G and Zonderman, Alan B and Adeyemo, Adebowale and Ambs, Stefan and Cushman, Mary and Faul, Jessica D and Hakonarson, Hakon and Levin, Albert M and Nathanson, Katherine L and Ware, Erin B and Weir, David R and Zhao, Wei and Zhi, Degui and Arnett, Donna K and Grant, Struan F A and Kardia, Sharon L R and Oloapde, Olufunmilayo I and Rao, D C and Rotimi, Charles N and Sale, Mich{\`e}le M and Williams, L Keoki and Zemel, Babette S and Becker, Diane M and Borecki, Ingrid B and Evans, Michele K and Harris, Tamara B and Hirschhorn, Joel N and Li, Yun and Patel, Sanjay R and Psaty, Bruce M and Rotter, Jerome I and Wilson, James G and Bowden, Donald W and Cupples, L Adrienne and Haiman, Christopher A and Loos, Ruth J F and North, Kari E} } @article {7566, title = {Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals.}, journal = {BioData Min}, volume = {10}, year = {2017}, month = {2017}, pages = {25}, abstract = {BACKGROUND: The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), and triglycerides (TG).
RESULTS: Our analysis consisted of a discovery phase using a merged dataset of five different cohorts (n~=~12,853 to n~=~16,849 depending on lipid phenotype) and a replication phase with ten independent cohorts totaling up to 36,938 additional samples. Filters are often applied before interaction testing to correct for the burden of testing all pairwise interactions. We used two different filters: 1. A filter that tested only single nucleotide polymorphisms (SNPs) with a main effect of p~<~0.001 in a previous association study. 2. A filter that only tested interactions identified by Biofilter 2.0. Pairwise models that reached an interaction significance level of p~<~0.001 in the discovery dataset were tested for replication. We identified thirteen SNP-SNP models that were significant in more than one replication cohort after accounting for multiple testing.
CONCLUSIONS: These results may reveal novel insights into the genetic etiology of lipid levels. Furthermore, we developed a pipeline to perform a computationally efficient interaction analysis with multi-cohort replication.
}, issn = {1756-0381}, doi = {10.1186/s13040-017-0145-5}, author = {Holzinger, Emily R and Verma, Shefali S and Moore, Carrie B and Hall, Molly and De, Rishika and Gilbert-Diamond, Diane and Lanktree, Matthew B and Pankratz, Nathan and Amuzu, Antoinette and Burt, Amber and Dale, Caroline and Dudek, Scott and Furlong, Clement E and Gaunt, Tom R and Kim, Daniel Seung and Riess, Helene and Sivapalaratnam, Suthesh and Tragante, Vinicius and van Iperen, Erik P A and Brautbar, Ariel and Carrell, David S and Crosslin, David R and Jarvik, Gail P and Kuivaniemi, Helena and Kullo, Iftikhar J and Larson, Eric B and Rasmussen-Torvik, Laura J and Tromp, Gerard and Baumert, Jens and Cruickshanks, Karen J and Farrall, Martin and Hingorani, Aroon D and Hovingh, G K and Kleber, Marcus E and Klein, Barbara E and Klein, Ronald and Koenig, Wolfgang and Lange, Leslie A and Mӓrz, Winfried and North, Kari E and Charlotte Onland-Moret, N and Reiner, Alex P and Talmud, Philippa J and van der Schouw, Yvonne T and Wilson, James G and Kivimaki, Mika and Kumari, Meena and Moore, Jason H and Drenos, Fotios and Asselbergs, Folkert W and Keating, Brendan J and Ritchie, Marylyn D} } @article {7557, title = {Fifteen Genetic Loci Associated With the Electrocardiographic P Wave.}, journal = {Circ Cardiovasc Genet}, volume = {10}, year = {2017}, month = {2017 Aug}, abstract = {BACKGROUND: The P wave on an ECG is a measure of atrial electric function, and its characteristics may serve as predictors for atrial arrhythmias. Increased mean P-wave duration and P-wave terminal force traditionally have been used as markers for left atrial enlargement, and both have been associated with increased risk of atrial fibrillation. Here, we explore the genetic basis of P-wave morphology through meta-analysis of genome-wide association study results for P-wave duration and P-wave terminal force from 12 cohort studies.
METHODS AND RESULTS: We included 44 456 individuals, of which 6778 (16\%) were of African ancestry. Genotyping, imputation, and genome-wide association study were performed at each study site. Summary-level results were meta-analyzed centrally using inverse-variance weighting. In meta-analyses of P-wave duration, we identified 6 significant (P<5{\texttimes}10-8) novel loci and replicated a prior association with SCN10A. We identified 3 loci at SCN5A, TBX5, and CAV1/CAV2 that were jointly associated with the PR interval, PR segment, and P-wave duration. We identified 6 novel loci in meta-analysis of P-wave terminal force. Four of the identified genetic loci were significantly associated with gene expression in 329 left atrial samples. Finally, we observed that some of the loci associated with the P wave were linked to overall atrial conduction, whereas others identified distinct phases of atrial conduction.
CONCLUSIONS: We have identified 6 novel genetic loci associated with P-wave duration and 6 novel loci associated with P-wave terminal force. Future studies of these loci may aid in identifying new targets for drugs that may modify atrial conduction or treat atrial arrhythmias.
}, keywords = {Arrhythmias, Cardiac, Caveolin 1, Caveolin 2, Electrocardiography, Genetic Loci, Genome-Wide Association Study, Genotype, Heart Atria, Humans, NAV1.5 Voltage-Gated Sodium Channel, NAV1.8 Voltage-Gated Sodium Channel, T-Box Domain Proteins}, issn = {1942-3268}, doi = {10.1161/CIRCGENETICS.116.001667}, author = {Christophersen, Ingrid E and Magnani, Jared W and Yin, Xiaoyan and Barnard, John and Weng, Lu-Chen and Arking, Dan E and Niemeijer, Maartje N and Lubitz, Steven A and Avery, Christy L and Duan, Qing and Felix, Stephan B and Bis, Joshua C and Kerr, Kathleen F and Isaacs, Aaron and M{\"u}ller-Nurasyid, Martina and M{\"u}ller, Christian and North, Kari E and Reiner, Alex P and Tinker, Lesley F and Kors, Jan A and Teumer, Alexander and Petersmann, Astrid and Sinner, Moritz F and B{\r u}zkov{\'a}, Petra and Smith, Jonathan D and Van Wagoner, David R and V{\"o}lker, Uwe and Waldenberger, Melanie and Peters, Annette and Meitinger, Thomas and Limacher, Marian C and Wilhelmsen, Kirk C and Psaty, Bruce M and Hofman, Albert and Uitterlinden, Andre and Krijthe, Bouwe P and Zhang, Zhu-Ming and Schnabel, Renate B and K{\"a}{\"a}b, Stefan and van Duijn, Cornelia and Rotter, Jerome I and Sotoodehnia, Nona and D{\"o}rr, Marcus and Li, Yun and Chung, Mina K and Soliman, Elsayed Z and Alonso, Alvaro and Whitsel, Eric A and Stricker, Bruno H and Benjamin, Emelia J and Heckbert, Susan R and Ellinor, Patrick T} } @article {7463, title = {Fine mapping of QT interval regions in global populations refines previously identified QT interval loci and identifies signals unique to African and Hispanic descent populations.}, journal = {Heart Rhythm}, volume = {14}, year = {2017}, month = {2017 Apr}, pages = {572-580}, abstract = {BACKGROUND: The electrocardiographically measured QT interval (QT) is heritable and its prolongation is an established risk factor for several cardiovascular diseases. Yet, most QT genetic studies have been performed in European ancestral populations, possibly reducing their global relevance.
OBJECTIVE: To leverage diversity and improve biological insight, we fine mapped 16 of the 35 previously identified QT loci (46\%) in populations of African American (n = 12,410) and Hispanic/Latino (n = 14,837) ancestry.
METHODS: Racial/ethnic-specific multiple linear regression analyses adjusted for heart rate and clinical covariates were examined separately and in combination after inverse-variance weighted trans-ethnic meta-analysis.
RESULTS: The 16 fine-mapped QT loci included on the Illumina Metabochip represented 21 independent signals, of which 16 (76\%) were significantly (P-value<=9.1{\texttimes}10(-5)) associated with QT. Through sequential conditional analysis we also identified three trans-ethnic novel SNPs at ATP1B1, SCN5A-SCN10A, and KCNQ1 and three Hispanic/Latino-specific novel SNPs at NOS1AP and SCN5A-SCN10A (two novel SNPs) with evidence of associations with QT independent of previous identified GWAS lead SNPs. Linkage disequilibrium patterns helped to narrow the region likely to contain the functional variants at several loci, including NOS1AP, USP50-TRPM7, and PRKCA, although intervals surrounding SLC35F1-PLN and CNOT1 remained broad in size (>100 kb). Finally, bioinformatics-based functional characterization suggested a regulatory function in cardiac tissues for the majority of independent signals that generalized and the novel SNPs.
CONCLUSION: Our findings suggest that a majority of identified SNPs implicate gene regulatory dysfunction in QT prolongation, that the same loci influence variation in QT across global populations, and that additional, novel, population-specific QT signals exist.
}, issn = {1556-3871}, doi = {10.1016/j.hrthm.2016.12.021}, author = {Avery, Christy L and Wassel, Christina L and Richard, Melissa A and Highland, Heather M and Bien, Stephanie and Zubair, Niha and Soliman, Elsayed Z and Fornage, Myriam and Bielinski, Suzette J and Tao, Ran and Seyerle, Amanda A and Shah, Sanjiv J and Lloyd-Jones, Donald M and Buyske, Steven and Rotter, Jerome I and Post, Wendy S and Rich, Stephen S and Hindorff, Lucia A and Jeff, Janina M and Shohet, Ralph V and Sotoodehnia, Nona and Lin, Dan Yu and Whitsel, Eric A and Peters, Ulrike and Haiman, Christopher A and Crawford, Dana C and Kooperberg, Charles and North, Kari E} } @article {7345, title = {Genetic loci associated with chronic obstructive pulmonary disease overlap with loci for lung function and pulmonary fibrosis.}, journal = {Nat Genet}, volume = {49}, year = {2017}, month = {2017 Mar}, pages = {426-432}, abstract = {Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide. We performed a genetic association study in 15,256 cases and 47,936 controls, with replication of select top results (P < 5 {\texttimes} 10(-6)) in 9,498 cases and 9,748 controls. In the combined meta-analysis, we identified 22 loci associated at genome-wide significance, including 13 new associations with COPD. Nine of these 13 loci have been associated with lung function in general population samples, while 4 (EEFSEC, DSP, MTCL1, and SFTPD) are new. We noted two loci shared with pulmonary fibrosis (FAM13A and DSP) but that had opposite risk alleles for COPD. None of our loci overlapped with genome-wide associations for asthma, although one locus has been implicated in joint susceptibility to asthma and obesity. We also identified genetic correlation between COPD and asthma. Our findings highlight new loci associated with COPD, demonstrate the importance of specific loci associated with lung function to COPD, and identify potential regions of genetic overlap between COPD and other respiratory diseases.
}, issn = {1546-1718}, doi = {10.1038/ng.3752}, author = {Hobbs, Brian D and de Jong, Kim and Lamontagne, Maxime and Boss{\'e}, Yohan and Shrine, Nick and Artigas, Maria Soler and Wain, Louise V and Hall, Ian P and Jackson, Victoria E and Wyss, Annah B and London, Stephanie J and North, Kari E and Franceschini, Nora and Strachan, David P and Beaty, Terri H and Hokanson, John E and Crapo, James D and Castaldi, Peter J and Chase, Robert P and Bartz, Traci M and Heckbert, Susan R and Psaty, Bruce M and Gharib, Sina A and Zanen, Pieter and Lammers, Jan W and Oudkerk, Matthijs and Groen, H J and Locantore, Nicholas and Tal-Singer, Ruth and Rennard, Stephen I and Vestbo, J{\o}rgen and Timens, Wim and Par{\'e}, Peter D and Latourelle, Jeanne C and Dupuis, Jos{\'e}e and O{\textquoteright}Connor, George T and Wilk, Jemma B and Kim, Woo Jin and Lee, Mi Kyeong and Oh, Yeon-Mok and Vonk, Judith M and de Koning, Harry J and Leng, Shuguang and Belinsky, Steven A and Tesfaigzi, Yohannes and Manichaikul, Ani and Wang, Xin-Qun and Rich, Stephen S and Barr, R Graham and Sparrow, David and Litonjua, Augusto A and Bakke, Per and Gulsvik, Amund and Lahousse, Lies and Brusselle, Guy G and Stricker, Bruno H and Uitterlinden, Andr{\'e} G and Ampleford, Elizabeth J and Bleecker, Eugene R and Woodruff, Prescott G and Meyers, Deborah A and Qiao, Dandi and Lomas, David A and Yim, Jae-Joon and Kim, Deog Kyeom and Hawrylkiewicz, Iwona and Sliwinski, Pawel and Hardin, Megan and Fingerlin, Tasha E and Schwartz, David A and Postma, Dirkje S and MacNee, William and Tobin, Martin D and Silverman, Edwin K and Boezen, H Marike and Cho, Michael H} } @article {7579, title = {Genetic loci associated with heart rate variability and their effects on cardiac disease risk.}, journal = {Nat Commun}, volume = {8}, year = {2017}, month = {2017 Jun 14}, pages = {15805}, abstract = {Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6\% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74 SCOPE: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption. METHODS AND RESULTS: A genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction <10-7) , and six independent variants (LINC01512-rs7751666, PALM2/AKAP2-rs914359, ACTA2-rs1388, PPP1R12A-rs7961195, LINC00333-rs9635058, AC098847.1-rs1791355) were evaluated meta-analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3{\textquoteright} of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 {\texttimes} 10-8) such that each serving of low-fat dairy was associated with 0.225 kg m-2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2-rs1388) approached interaction replication significance for low-fat dairy exposure. CONCLUSION: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight. Genomic analysis of longevity offers the potential to illuminate the biology of human aging. Here, using genome-wide association meta-analysis of 606,059 parents{\textquoteright} survival, we discover two regions associated with longevity (HLA-DQA1/DRB1 and LPA). We also validate previous suggestions that APOE, CHRNA3/5, CDKN2A/B, SH2B3 and FOXO3A influence longevity. Next we show that giving up smoking, educational attainment, openness to new experience and high-density lipoprotein (HDL) cholesterol levels are most positively genetically correlated with lifespan while susceptibility to coronary artery disease (CAD), cigarettes smoked per day, lung cancer, insulin resistance and body fat are most negatively correlated. We suggest that the effect of education on lifespan is principally mediated through smoking while the effect of obesity appears to act via CAD. Using instrumental variables, we suggest that an increase of one body mass index unit reduces lifespan by 7 months while 1 year of education adds 11 months to expected lifespan.Variability in human longevity is genetically influenced. Using genetic data of parental lifespan, the authors identify associations at HLA-DQA/DRB1 and LPA and find that genetic variants that increase educational attainment have a positive effect on lifespan whereas increasing BMI negatively affects lifespan. Most body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5-70~kg/m(2)) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p~<~0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants. C-reactive protein (CRP) is a circulating biomarker indicative of systemic inflammation. We aimed to evaluate genetic associations with CRP levels among non-European-ancestry populations through discovery, fine-mapping and conditional analyses. A total of 30~503 non-European-ancestry participants from 6 studies participating in the Population Architecture using Genomics and Epidemiology study had serum high-sensitivity CRP measurements and \~{}200~000 single nucleotide polymorphisms (SNPs) genotyped on the Metabochip. We evaluated the association between each SNP and log-transformed CRP levels using multivariate linear regression, with additive genetic models adjusted for age, sex, the first four principal components of genetic ancestry, and study-specific factors. Differential linkage disequilibrium patterns between race/ethnicity groups were used to fine-map regions associated with CRP levels. Conditional analyses evaluated for multiple independent signals within genetic regions. One hundred and sixty-three unique variants in 12 loci in overall or race/ethnicity-stratified Metabochip-wide scans reached a Bonferroni-corrected P-value <2.5E-7. Three loci have no (HACL1, OLFML2B) or only limited (PLA2G6) previous associations with CRP levels. Six loci had different top hits in race/ethnicity-specific versus overall analyses. Fine-mapping refined the signal in six loci, particularly in HNF1A. Conditional analyses provided evidence for secondary signals in LEPR, IL1RN and HNF1A, and for multiple independent signals in CRP and APOE. We identified novel variants and loci associated with CRP levels, generalized known CRP associations to a multiethnic study population, refined association signals at several loci and found evidence for multiple independent signals at several well-known loci. This study demonstrates the benefit of conducting inclusive genetic association studies in large multiethnic populations. Red blood cell (RBC) traits provide insight into a wide range of physiological states and exhibit moderate to high heritability, making them excellent candidates for genetic studies to inform underlying biologic mechanisms. Previous RBC trait genome-wide association studies were performed primarily in European- or Asian-ancestry populations, missing opportunities to inform understanding of RBC genetic architecture in diverse populations and reduce intervals surrounding putative functional SNPs through fine-mapping. Here, we report the first fine-mapping of six correlated (Pearson{\textquoteright}s r range: |0.04 - 0.92|) RBC traits in up to 19,036 African Americans and 19,562 Hispanic/Latinos participants of the Population Architecture using Genomics and Epidemiology (PAGE) consortium. Trans-ethnic meta-analysis of race/ethnic- and study-specific estimates for approximately 11,000 SNPs flanking 13 previously identified association signals as well as 150,000 additional array-wide SNPs was performed using inverse-variance meta-analysis after adjusting for study and clinical covariates. Approximately half of previously reported index SNP-RBC trait associations generalized to the trans-ethnic study population (p<1.7x10 ); previously unreported independent association signals within the ABO region reinforce the potential for multiple functional variants affecting the same locus. Trans-ethnic fine-mapping did not reveal additional signals at the HFE locus independent of the known functional variants. Finally, we identified a potential novel association in the Hispanic/Latino study population at the HECTD4/RPL6 locus for RBC count (p=1.9x10 ). The identification of a previously unknown association, generalization of a large proportion of known association signals, and refinement of known association signals all exemplify the benefits of genetic studies in diverse populations. This article is protected by copyright. All rights reserved. The genetic basis of supraventricular and ventricular ectopy (SVE, VE) remains largely uncharacterized, despite established genetic mechanisms of arrhythmogenesis. To identify novel genetic variants associated with SVE/VE in ancestrally diverse human populations, we conducted a genome-wide association study of electrocardiographically~identified SVE and VE in five cohorts including approximately 43,000 participants of African, European and Hispanic/Latino ancestry. In thirteen ancestry-stratified subgroups, we tested multivariable-adjusted associations of SVE and VE with single nucleotide polymorphism (SNP) dosage. We combined subgroup-specific association estimates in inverse variance-weighted, fixed-effects and Bayesian meta-analyses. We also combined fixed-effects meta-analytic t-test statistics for SVE and VE in multi-trait SNP association analyses. No loci reached genome-wide significance in trans-ethnic meta-analyses. However, we found genome-wide significant SNPs intronic to an apoptosis-enhancing gene previously associated with QRS interval duration (FAF1; lead SNP rs7545860; effect allele frequency = 0.02; P = 2.0 {\texttimes} 10) in multi-trait analysis among European ancestry participants and near a locus encoding calcium-dependent glycoproteins (DSC3; lead SNP rs8086068; effect allele frequency = 0.17) in meta-analysis of SVE (P = 4.0 {\texttimes} 10) and multi-trait analysis (P = 2.9 {\texttimes} 10) among African ancestry participants. The novel findings suggest several mechanisms by which genetic variation may predispose to ectopy in humans and highlight the potential value of leveraging pleiotropy in future studies of ectopy-related phenotypes. The role that vitamin D plays in pulmonary function remains uncertain. Epidemiological studies reported mixed findings for serum 25-hydroxyvitamin D (25(OH)D)-pulmonary function association. We conducted the largest cross-sectional meta-analysis of the 25(OH)D-pulmonary function association to date, based on nine European ancestry (EA) cohorts (n 22 838) and five African ancestry (AA) cohorts (n 4290) in the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium. Data were analysed using linear models by cohort and ancestry. Effect modification by smoking status (current/former/never) was tested. Results were combined using fixed-effects meta-analysis. Mean serum 25(OH)D was 68 (sd 29) nmol/l for EA and 49 (sd 21) nmol/l for AA. For each 1 nmol/l higher 25(OH)D, forced expiratory volume in the 1st second (FEV1) was higher by 1{\textperiodcentered}1 ml in EA (95 \% CI 0{\textperiodcentered}9, 1{\textperiodcentered}3; P<0{\textperiodcentered}0001) and 1{\textperiodcentered}8 ml (95 \% CI 1{\textperiodcentered}1, 2{\textperiodcentered}5; P<0{\textperiodcentered}0001) in AA (P race difference=0{\textperiodcentered}06), and forced vital capacity (FVC) was higher by 1{\textperiodcentered}3 ml in EA (95 \% CI 1{\textperiodcentered}0, 1{\textperiodcentered}6; P<0{\textperiodcentered}0001) and 1{\textperiodcentered}5 ml (95 \% CI 0{\textperiodcentered}8, 2{\textperiodcentered}3; P=0{\textperiodcentered}0001) in AA (P race difference=0{\textperiodcentered}56). Among EA, the 25(OH)D-FVC association was stronger in smokers: per 1 nmol/l higher 25(OH)D, FVC was higher by 1{\textperiodcentered}7 ml (95 \% CI 1{\textperiodcentered}1, 2{\textperiodcentered}3) for current smokers and 1{\textperiodcentered}7 ml (95 \% CI 1{\textperiodcentered}2, 2{\textperiodcentered}1) for former smokers, compared with 0{\textperiodcentered}8 ml (95 \% CI 0{\textperiodcentered}4, 1{\textperiodcentered}2) for never smokers. In summary, the 25(OH)D associations with FEV1 and FVC were positive in both ancestries. In EA, a stronger association was observed for smokers compared with never smokers, which supports the importance of vitamin D in vulnerable populations. Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV ), forced vital capacity (FVC) and the ratio of FEV to FVC (FEV /FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. We identified significant (P<2{\textperiodcentered}8x10 ) associations with six SNPs: a nonsynonymous variant in , which is predicted to be damaging, three intronic SNPs ( and ) and two intergenic SNPs near to and Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including and . Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease. Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of lung function and clinical relevance of implicated loci. RATIONALE: Omega-3 poly-unsaturated fatty acids (n-3 PUFAs) have anti-inflammatory properties that could benefit adults with comprised pulmonary health. OBJECTIVE: To investigate n-3 PUFA associations with spirometric measures of pulmonary function tests (PFTs) and determine underlying genetic susceptibility. METHODS: Associations of n-3 PUFA biomarkers (alpha-linolenic acid, eicosapentaenoic acid, docosapentaenoic acid [DPA], and docosahexaenoic acid [DHA]) were evaluated with PFTs (forced expiratory volume in the first second [FEV], forced vital capacity [FVC], and [FEV/FVC]) in meta-analyses across seven cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (N=16,134 of European or African ancestry). PFT-associated n-3 PUFAs were carried forward to genome-wide interaction analyses in the four largest cohorts (N=11,962) and replicated in one cohort (N=1,687). Cohort-specific results were combined using joint 2 degree-of-freedom (2df) meta-analyses of single nucleotide polymorphism (SNP) associations and their interactions with n-3 PUFAs. RESULTS: DPA and DHA were positively associated with FEV1 and FVC (P<0.025), with evidence for effect modification by smoking and by sex. Genome-wide analyses identified a novel association of rs11693320-an intronic DPP10 SNP-with FVC when incorporating an interaction with DHA, and the finding was replicated (P=9.4{\texttimes}10 across discovery and replication cohorts). The rs11693320-A allele (frequency~80\%) was associated with lower FVC (P=2.1{\texttimes}10; β= -161.0mL), and the association was attenuated by higher DHA levels (P=2.1{\texttimes}10; β=36.2mL). CONCLUSIONS: We corroborated beneficial effects of n-3 PUFAs on pulmonary function. By modeling genome-wide n-3 PUFA interactions, we identified a novel DPP10 SNP association with FVC that was not detectable in much larger studies ignoring this interaction. AIMS/HYPOTHESIS: Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits. METHODS: Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway. RESULTS: In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β~{\textpm}~SE 0.014~{\textpm}~0.004 [mmol/l], p~=~1.5~{\texttimes}~10-3) and higher fasting insulin (0.030~{\textpm}~0.005 [log e pmol/l], p~=~2.0~{\texttimes}~10-10). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the β-Klotho (KLB) locus on fasting insulin (0.030~{\textpm}~0.011 log e pmol/l, uncorrected p~=~0.006), results in the replication cohorts and combined meta-analyses were non-significant. CONCLUSIONS/INTERPRETATION: In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis. TRIAL REGISTRATION: Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses{\textquoteright} Health Study). In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (F) for >1.4 million individuals, we show that F is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: F equivalent to the offspring of first cousins is associated with a 55\% decrease [95\% CI 44-66\%] in the odds of having children. Finally, the effects of F are confirmed within full-sibling pairs, where the variation in F is independent of all environmental confounding. An individual{\textquoteright}s lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multi-ancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in Stage 1 (genome-wide discovery) and 66 studies in Stage 2 (focused follow-up), for a total of 394,584 individuals from five ancestry groups. Genetic main and interaction effects were jointly assessed by a 2 degrees of freedom (DF) test, and a 1 DF test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P~<~1~{\texttimes}~10-6) with lipid levels in Stage 1 and were evaluated in Stage 2, followed by combined analyses of Stage 1 and Stage 2. In the combined analysis of Stage 1 and Stage 2, 147 independent loci were associated with lipid levels at P~<~5~{\texttimes}~10-8 using 2 DF tests, of which 18 were novel. No genome-wide significant associations were found testing the interaction effect alone. The novel loci included several genes (PCSK5, VEGFB, and A1CF) with a putative role in lipid metabolism based on existing evidence from cellular and experimental models. The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings. Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25\% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles. Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels. Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 {\texttimes} 10). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP. Leptin influences food intake by informing the brain about the status of body fat stores. Rare mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in , and , and one intergenic variant near The missense variant Val94Met (rs17151919) in was common in individuals of African ancestry only and its association with lower leptin concentrations was specific to this ancestry (P=2x10, n=3,901). Using analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting leptin regulates early adiposity. Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is~termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP~driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues. Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95\% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95\% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (β = - 0.76, 95\% CI - 2.45 to 1.08~mmHg), 0.06~mmHg lower diastolic blood pressure (β = - 0.06, 95\% CI - 0.93 to 0.87~mmHg), or pulse pressure (β = - 0.65, 95\% CI - 1.38 to 0.69~mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses. Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 {\texttimes} 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 {\texttimes} 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 {\texttimes} 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids. Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5\%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained <=20 variants in the credible sets that jointly account for 99\% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations. Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p value <5e-8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (), synaptic function and neurotransmission (), as well as genes previously implicated in neuropsychiatric or stress-related disorders (). These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations. Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 {\texttimes} 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 {\texttimes} 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 {\texttimes} 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation. The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes). In the first 53,831 TOPMed samples, we detected more than 400~million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400~million detected variants, 97\% have frequencies of less than 1\% and 46\% are singletons that are present in only one individual (53\% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01\%. Genotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institute{\textquoteright}s Trans-Omics for Precision Medicine program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 studies per phenotype (participants recruited 1948-2012). We discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms. Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing from NHLBI{\textquoteright}s Trans-Omics for Precision Medicine Initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several GWAS identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of whole genome sequencing in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits. BACKGROUND: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing. METHODS: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90\%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap. RESULTS: We identified a multi-ethnic set-based rare-variant association (p = 3.48 {\texttimes} 10) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways. CONCLUSIONS: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response. Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3~bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders. Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs. Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease. BACKGROUND: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. METHODS: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. RESULTS: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (<5{\texttimes}10). Among them, a rare intergenic variant at novel locus, , was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; =4.99{\texttimes}10) but not stage-2 analysis (=0.11). Furthermore, a novel common variant at the known locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; =4.18{\texttimes}10) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; =7.28{\texttimes}10). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (<1{\texttimes}10 and <1{\texttimes}10, respectively). DISCUSSION: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification. We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD. We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9\% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 {\texttimes} 10), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4\% of T2D associations to a single variant with >50\% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background. Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this {\textquoteright}missing heritability{\textquoteright}. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74\% of it attributable to rare variants with minor allele frequencies between 0.01\% and 1\%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60\% to 100\% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking. Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) >=1\%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRS) with a rare variant PRS (PRS) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m), obesity (BMI >= 30 kg/m), and extreme obesity (BMI >= 40 kg/m). We built PRSs and PRSs using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRS explained 10.1\% of variation in BMI, and 18.3\% and 22.5\% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRS explained 1.49\%, and 2.97\% and 3.68\%, respectively. The PRS was associated with an increased risk of obesity and extreme obesity (OR = 1.37 per SD, = 1.7x10; OR = 1.55 per SD, = 3.8x10), which was attenuated, after adjusting for PRS (OR = 1.08 per SD, = 9.8x10; OR= 1.09 per SD, = 0.02). When PRS and PRS are combined, the increase in explained variance attributed to PRS was small (incremental Nagelkerke R = 0.24\% for obesity and 0.51\% for extreme obesity). Consistently, combining PRS to PRS provided little improvement to the prediction of obesity (PRS AUC = 0.591; PRS AUC = 0.708; PRS AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRS provides limited improvement over PRS in the prediction of obesity risk, based on these large populations. Diabetic kidney disease (DKD) is recognized as an important public health challenge. However, its genomic mechanisms are poorly understood. To identify rare variants for DKD, we conducted a whole-exome sequencing (WES) study leveraging large cohorts well-phenotyped for chronic kidney disease (CKD) and diabetes. Our two-stage whole-exome sequencing study included 4372 European and African ancestry participants from the Chronic Renal Insufficiency Cohort (CRIC) and Atherosclerosis Risk in Communities (ARIC) studies (stage-1) and 11 487 multi-ancestry Trans-Omics for Precision Medicine (TOPMed) participants (stage-2). Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex, and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test (SKAT-O) implemented within our mixed model framework. We identified four novel exome-wide significant DKD-related loci through initiating diabetes. In single variant analyses, participants carrying a rare, in-frame insertion in the DIS3L2 gene (rs141560952) exhibited a 193-fold increased odds (95\% confidence interval: 33.6, 1105) of DKD compared with non-carriers (P = 3.59 {\texttimes} 10-9). Likewise, each copy of a low-frequency KRT6B splice-site variant (rs425827) conferred a 5.31-fold higher odds (95\% confidence interval: 3.06, 9.21) of DKD (P = 2.72 {\texttimes} 10-9). Aggregate gene-based analyses further identified ERAP2 (P = 4.03 {\texttimes} 10-8) and NPEPPS (P = 1.51 {\texttimes} 10-7), which are both expressed in the kidney and implicated in renin-angiotensin-aldosterone system modulated immune response. In the largest WES study of DKD, we identified novel rare variant loci attaining exome-wide significance. These findings provide new insights into the molecular mechanisms underlying DKD. Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes. A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: "Some College" (yes/no, for any education beyond high school) and "Graduated College" (yes/no, for completing a 4-year college degree). Genome-wide significant ( < 5 {\texttimes} 10) and suggestive ( < 1 {\texttimes} 10) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals). In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (), brain (), and liver () biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue. Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects. Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7\% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5{\texttimes}10 ) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care. Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55\% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction. Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51\% were of non-European population groups. We discovered 18 BMI-associated signals ( < 5 {\texttimes} 10 ). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the and loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine. Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7\% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 {\texttimes} 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.