%0 Journal Article %J Nature %D 2010 %T Biological, clinical and population relevance of 95 loci for blood lipids. %A Teslovich, Tanya M %A Musunuru, Kiran %A Smith, Albert V %A Edmondson, Andrew C %A Stylianou, Ioannis M %A Koseki, Masahiro %A Pirruccello, James P %A Ripatti, Samuli %A Chasman, Daniel I %A Willer, Cristen J %A Johansen, Christopher T %A Fouchier, Sigrid W %A Isaacs, Aaron %A Peloso, Gina M %A Barbalic, Maja %A Ricketts, Sally L %A Bis, Joshua C %A Aulchenko, Yurii S %A Thorleifsson, Gudmar %A Feitosa, Mary F %A Chambers, John %A Orho-Melander, Marju %A Melander, Olle %A Johnson, Toby %A Li, Xiaohui %A Guo, Xiuqing %A Li, Mingyao %A Shin Cho, Yoon %A Jin Go, Min %A Jin Kim, Young %A Lee, Jong-Young %A Park, Taesung %A Kim, Kyunga %A Sim, Xueling %A Twee-Hee Ong, Rick %A Croteau-Chonka, Damien C %A Lange, Leslie A %A Smith, Joshua D %A Song, Kijoung %A Hua Zhao, Jing %A Yuan, Xin %A Luan, Jian'an %A Lamina, Claudia %A Ziegler, Andreas %A Zhang, Weihua %A Zee, Robert Y L %A Wright, Alan F %A Witteman, Jacqueline C M %A Wilson, James F %A Willemsen, Gonneke %A Wichmann, H-Erich %A Whitfield, John B %A Waterworth, Dawn M %A Wareham, Nicholas J %A Waeber, Gérard %A Vollenweider, Peter %A Voight, Benjamin F %A Vitart, Veronique %A Uitterlinden, André G %A Uda, Manuela %A Tuomilehto, Jaakko %A Thompson, John R %A Tanaka, Toshiko %A Surakka, Ida %A Stringham, Heather M %A Spector, Tim D %A Soranzo, Nicole %A Smit, Johannes H %A Sinisalo, Juha %A Silander, Kaisa %A Sijbrands, Eric J G %A Scuteri, Angelo %A Scott, James %A Schlessinger, David %A Sanna, Serena %A Salomaa, Veikko %A Saharinen, Juha %A Sabatti, Chiara %A Ruokonen, Aimo %A Rudan, Igor %A Rose, Lynda M %A Roberts, Robert %A Rieder, Mark %A Psaty, Bruce M %A Pramstaller, Peter P %A Pichler, Irene %A Perola, Markus %A Penninx, Brenda W J H %A Pedersen, Nancy L %A Pattaro, Cristian %A Parker, Alex N %A Paré, Guillaume %A Oostra, Ben A %A O'Donnell, Christopher J %A Nieminen, Markku S %A Nickerson, Deborah A %A Montgomery, Grant W %A Meitinger, Thomas %A McPherson, Ruth %A McCarthy, Mark I %A McArdle, Wendy %A Masson, David %A Martin, Nicholas G %A Marroni, Fabio %A Mangino, Massimo %A Magnusson, Patrik K E %A Lucas, Gavin %A Luben, Robert %A Loos, Ruth J F %A Lokki, Marja-Liisa %A Lettre, Guillaume %A Langenberg, Claudia %A Launer, Lenore J %A Lakatta, Edward G %A Laaksonen, Reijo %A Kyvik, Kirsten O %A Kronenberg, Florian %A König, Inke R %A Khaw, Kay-Tee %A Kaprio, Jaakko %A Kaplan, Lee M %A Johansson, Asa %A Jarvelin, Marjo-Riitta %A Janssens, A Cecile J W %A Ingelsson, Erik %A Igl, Wilmar %A Kees Hovingh, G %A Hottenga, Jouke-Jan %A Hofman, Albert %A Hicks, Andrew A %A Hengstenberg, Christian %A Heid, Iris M %A Hayward, Caroline %A Havulinna, Aki S %A Hastie, Nicholas D %A Harris, Tamara B %A Haritunians, Talin %A Hall, Alistair S %A Gyllensten, Ulf %A Guiducci, Candace %A Groop, Leif C %A Gonzalez, Elena %A Gieger, Christian %A Freimer, Nelson B %A Ferrucci, Luigi %A Erdmann, Jeanette %A Elliott, Paul %A Ejebe, Kenechi G %A Döring, Angela %A Dominiczak, Anna F %A Demissie, Serkalem %A Deloukas, Panagiotis %A de Geus, Eco J C %A de Faire, Ulf %A Crawford, Gabriel %A Collins, Francis S %A Chen, Yii-der I %A Caulfield, Mark J %A Campbell, Harry %A Burtt, Noel P %A Bonnycastle, Lori L %A Boomsma, Dorret I %A Boekholdt, S Matthijs %A Bergman, Richard N %A Barroso, Inês %A Bandinelli, Stefania %A Ballantyne, Christie M %A Assimes, Themistocles L %A Quertermous, Thomas %A Altshuler, David %A Seielstad, Mark %A Wong, Tien Y %A Tai, E-Shyong %A Feranil, Alan B %A Kuzawa, Christopher W %A Adair, Linda S %A Taylor, Herman A %A Borecki, Ingrid B %A Gabriel, Stacey B %A Wilson, James G %A Holm, Hilma %A Thorsteinsdottir, Unnur %A Gudnason, Vilmundur %A Krauss, Ronald M %A Mohlke, Karen L %A Ordovas, Jose M %A Munroe, Patricia B %A Kooner, Jaspal S %A Tall, Alan R %A Hegele, Robert A %A Kastelein, John J P %A Schadt, Eric E %A Rotter, Jerome I %A Boerwinkle, Eric %A Strachan, David P %A Mooser, Vincent %A Stefansson, Kari %A Reilly, Muredach P %A Samani, Nilesh J %A Schunkert, Heribert %A Cupples, L Adrienne %A Sandhu, Manjinder S %A Ridker, Paul M %A Rader, Daniel J %A van Duijn, Cornelia M %A Peltonen, Leena %A Abecasis, Goncalo R %A Boehnke, Michael %A Kathiresan, Sekar %K African Americans %K Animals %K Asian Continental Ancestry Group %K Cholesterol, HDL %K Cholesterol, LDL %K Coronary Artery Disease %K Europe %K European Continental Ancestry Group %K Female %K Genetic Loci %K Genome-Wide Association Study %K Genotype %K Humans %K Lipid Metabolism %K Lipids %K Liver %K Male %K Mice %K N-Acetylgalactosaminyltransferases %K Phenotype %K Polymorphism, Single Nucleotide %K Protein Phosphatase 1 %K Reproducibility of Results %K Triglycerides %X

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

%B Nature %V 466 %P 707-13 %8 2010 Aug 05 %G eng %N 7307 %1 http://www.ncbi.nlm.nih.gov/pubmed/20686565?dopt=Abstract %R 10.1038/nature09270 %0 Journal Article %J Diabetes Care %D 2010 %T Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies. %A Nettleton, Jennifer A %A McKeown, Nicola M %A Kanoni, Stavroula %A Lemaitre, Rozenn N %A Hivert, Marie-France %A Ngwa, Julius %A van Rooij, Frank J A %A Sonestedt, Emily %A Wojczynski, Mary K %A Ye, Zheng %A Tanaka, Tosh %A Garcia, Melissa %A Anderson, Jennifer S %A Follis, Jack L %A Djoussé, Luc %A Mukamal, Kenneth %A Papoutsakis, Constantina %A Mozaffarian, Dariush %A Zillikens, M Carola %A Bandinelli, Stefania %A Bennett, Amanda J %A Borecki, Ingrid B %A Feitosa, Mary F %A Ferrucci, Luigi %A Forouhi, Nita G %A Groves, Christopher J %A Hallmans, Göran %A Harris, Tamara %A Hofman, Albert %A Houston, Denise K %A Hu, Frank B %A Johansson, Ingegerd %A Kritchevsky, Stephen B %A Langenberg, Claudia %A Launer, Lenore %A Liu, Yongmei %A Loos, Ruth J %A Nalls, Michael %A Orho-Melander, Marju %A Renstrom, Frida %A Rice, Kenneth %A Riserus, Ulf %A Rolandsson, Olov %A Rotter, Jerome I %A Saylor, Georgia %A Sijbrands, Eric J G %A Sjogren, Per %A Smith, Albert %A Steingrímsdóttir, Laufey %A Uitterlinden, André G %A Wareham, Nicholas J %A Prokopenko, Inga %A Pankow, James S %A van Duijn, Cornelia M %A Florez, Jose C %A Witteman, Jacqueline C M %A Dupuis, Josée %A Dedoussis, George V %A Ordovas, Jose M %A Ingelsson, Erik %A Cupples, L Adrienne %A Siscovick, David S %A Franks, Paul W %A Meigs, James B %K Adult %K Aged %K Blood Glucose %K Edible Grain %K European Continental Ancestry Group %K Fasting %K Female %K Genetic Loci %K Genome-Wide Association Study %K Genotype %K Humans %K Insulin %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %X

OBJECTIVE: Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin.

RESEARCH DESIGN AND METHODS: Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant.

RESULTS: Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele.

CONCLUSIONS: Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations.

%B Diabetes Care %V 33 %P 2684-91 %8 2010 Dec %G eng %N 12 %1 http://www.ncbi.nlm.nih.gov/pubmed/20693352?dopt=Abstract %R 10.2337/dc10-1150 %0 Journal Article %J PLoS One %D 2012 %T Multi-ethnic analysis of lipid-associated loci: the NHLBI CARe project. %A Musunuru, Kiran %A Romaine, Simon P R %A Lettre, Guillaume %A Wilson, James G %A Volcik, Kelly A %A Tsai, Michael Y %A Taylor, Herman A %A Schreiner, Pamela J %A Rotter, Jerome I %A Rich, Stephen S %A Redline, Susan %A Psaty, Bruce M %A Papanicolaou, George J %A Ordovas, Jose M %A Liu, Kiang %A Krauss, Ronald M %A Glazer, Nicole L %A Gabriel, Stacey B %A Fornage, Myriam %A Cupples, L Adrienne %A Buxbaum, Sarah G %A Boerwinkle, Eric %A Ballantyne, Christie M %A Kathiresan, Sekar %A Rader, Daniel J %K African Americans %K Cholesterol, HDL %K Cholesterol, LDL %K European Continental Ancestry Group %K Genetic Association Studies %K Genetic Loci %K Humans %K Polymorphism, Single Nucleotide %K Triglycerides %X

BACKGROUND: Whereas it is well established that plasma lipid levels have substantial heritability within populations, it remains unclear how many of the genetic determinants reported in previous studies (largely performed in European American cohorts) are relevant in different ethnicities.

METHODOLOGY/PRINCIPAL FINDINGS: We tested a set of ∼50,000 polymorphisms from ∼2,000 candidate genes and genetic loci from genome-wide association studies (GWAS) for association with low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) in 25,000 European Americans and 9,000 African Americans in the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe). We replicated associations for a number of genes in one or both ethnicities and identified a novel lipid-associated variant in a locus harboring ICAM1. We compared the architecture of genetic loci associated with lipids in both African Americans and European Americans and found that the same genes were relevant across ethnic groups but the specific associated variants at each gene often differed.

CONCLUSIONS/SIGNIFICANCE: We identify or provide further evidence for a number of genetic determinants of plasma lipid levels through population association studies. In many loci the determinants appear to differ substantially between African Americans and European Americans.

%B PLoS One %V 7 %P e36473 %8 2012 %G eng %N 5 %1 http://www.ncbi.nlm.nih.gov/pubmed/22629316?dopt=Abstract %R 10.1371/journal.pone.0036473 %0 Journal Article %J PLoS Genet %D 2012 %T Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals. %A Dastani, Zari %A Hivert, Marie-France %A Timpson, Nicholas %A Perry, John R B %A Yuan, Xin %A Scott, Robert A %A Henneman, Peter %A Heid, Iris M %A Kizer, Jorge R %A Lyytikäinen, Leo-Pekka %A Fuchsberger, Christian %A Tanaka, Toshiko %A Morris, Andrew P %A Small, Kerrin %A Isaacs, Aaron %A Beekman, Marian %A Coassin, Stefan %A Lohman, Kurt %A Qi, Lu %A Kanoni, Stavroula %A Pankow, James S %A Uh, Hae-Won %A Wu, Ying %A Bidulescu, Aurelian %A Rasmussen-Torvik, Laura J %A Greenwood, Celia M T %A Ladouceur, Martin %A Grimsby, Jonna %A Manning, Alisa K %A Liu, Ching-Ti %A Kooner, Jaspal %A Mooser, Vincent E %A Vollenweider, Peter %A Kapur, Karen A %A Chambers, John %A Wareham, Nicholas J %A Langenberg, Claudia %A Frants, Rune %A Willems-Vandijk, Ko %A Oostra, Ben A %A Willems, Sara M %A Lamina, Claudia %A Winkler, Thomas W %A Psaty, Bruce M %A Tracy, Russell P %A Brody, Jennifer %A Chen, Ida %A Viikari, Jorma %A Kähönen, Mika %A Pramstaller, Peter P %A Evans, David M %A St Pourcain, Beate %A Sattar, Naveed %A Wood, Andrew R %A Bandinelli, Stefania %A Carlson, Olga D %A Egan, Josephine M %A Böhringer, Stefan %A van Heemst, Diana %A Kedenko, Lyudmyla %A Kristiansson, Kati %A Nuotio, Marja-Liisa %A Loo, Britt-Marie %A Harris, Tamara %A Garcia, Melissa %A Kanaya, Alka %A Haun, Margot %A Klopp, Norman %A Wichmann, H-Erich %A Deloukas, Panos %A Katsareli, Efi %A Couper, David J %A Duncan, Bruce B %A Kloppenburg, Margreet %A Adair, Linda S %A Borja, Judith B %A Wilson, James G %A Musani, Solomon %A Guo, Xiuqing %A Johnson, Toby %A Semple, Robert %A Teslovich, Tanya M %A Allison, Matthew A %A Redline, Susan %A Buxbaum, Sarah G %A Mohlke, Karen L %A Meulenbelt, Ingrid %A Ballantyne, Christie M %A Dedoussis, George V %A Hu, Frank B %A Liu, Yongmei %A Paulweber, Bernhard %A Spector, Timothy D %A Slagboom, P Eline %A Ferrucci, Luigi %A Jula, Antti %A Perola, Markus %A Raitakari, Olli %A Florez, Jose C %A Salomaa, Veikko %A Eriksson, Johan G %A Frayling, Timothy M %A Hicks, Andrew A %A Lehtimäki, Terho %A Smith, George Davey %A Siscovick, David S %A Kronenberg, Florian %A van Duijn, Cornelia %A Loos, Ruth J F %A Waterworth, Dawn M %A Meigs, James B %A Dupuis, Josée %A Richards, J Brent %A Voight, Benjamin F %A Scott, Laura J %A Steinthorsdottir, Valgerdur %A Dina, Christian %A Welch, Ryan P %A Zeggini, Eleftheria %A Huth, Cornelia %A Aulchenko, Yurii S %A Thorleifsson, Gudmar %A McCulloch, Laura J %A Ferreira, Teresa %A Grallert, Harald %A Amin, Najaf %A Wu, Guanming %A Willer, Cristen J %A Raychaudhuri, Soumya %A McCarroll, Steve A %A Hofmann, Oliver M %A Segrè, Ayellet V %A van Hoek, Mandy %A Navarro, Pau %A Ardlie, Kristin %A Balkau, Beverley %A Benediktsson, Rafn %A Bennett, Amanda J %A Blagieva, Roza %A Boerwinkle, Eric %A Bonnycastle, Lori L %A Boström, Kristina Bengtsson %A Bravenboer, Bert %A Bumpstead, Suzannah %A Burtt, Noel P %A Charpentier, Guillaume %A Chines, Peter S %A Cornelis, Marilyn %A Crawford, Gabe %A Doney, Alex S F %A Elliott, Katherine S %A Elliott, Amanda L %A Erdos, Michael R %A Fox, Caroline S %A Franklin, Christopher S %A Ganser, Martha %A Gieger, Christian %A Grarup, Niels %A Green, Todd %A Griffin, Simon %A Groves, Christopher J %A Guiducci, Candace %A Hadjadj, Samy %A Hassanali, Neelam %A Herder, Christian %A Isomaa, Bo %A Jackson, Anne U %A Johnson, Paul R V %A Jørgensen, Torben %A Kao, Wen H L %A Kong, Augustine %A Kraft, Peter %A Kuusisto, Johanna %A Lauritzen, Torsten %A Li, Man %A Lieverse, Aloysius %A Lindgren, Cecilia M %A Lyssenko, Valeriya %A Marre, Michel %A Meitinger, Thomas %A Midthjell, Kristian %A Morken, Mario A %A Narisu, Narisu %A Nilsson, Peter %A Owen, Katharine R %A Payne, Felicity %A Petersen, Ann-Kristin %A Platou, Carl %A Proença, Christine %A Prokopenko, Inga %A Rathmann, Wolfgang %A Rayner, N William %A Robertson, Neil R %A Rocheleau, Ghislain %A Roden, Michael %A Sampson, Michael J %A Saxena, Richa %A Shields, Beverley M %A Shrader, Peter %A Sigurdsson, Gunnar %A Sparsø, Thomas %A Strassburger, Klaus %A Stringham, Heather M %A Sun, Qi %A Swift, Amy J %A Thorand, Barbara %A Tichet, Jean %A Tuomi, Tiinamaija %A van Dam, Rob M %A van Haeften, Timon W %A van Herpt, Thijs %A van Vliet-Ostaptchouk, Jana V %A Walters, G Bragi %A Weedon, Michael N %A Wijmenga, Cisca %A Witteman, Jacqueline %A Bergman, Richard N %A Cauchi, Stephane %A Collins, Francis S %A Gloyn, Anna L %A Gyllensten, Ulf %A Hansen, Torben %A Hide, Winston A %A Hitman, Graham A %A Hofman, Albert %A Hunter, David J %A Hveem, Kristian %A Laakso, Markku %A Morris, Andrew D %A Palmer, Colin N A %A Rudan, Igor %A Sijbrands, Eric %A Stein, Lincoln D %A Tuomilehto, Jaakko %A Uitterlinden, Andre %A Walker, Mark %A Watanabe, Richard M %A Abecasis, Goncalo R %A Boehm, Bernhard O %A Campbell, Harry %A Daly, Mark J %A Hattersley, Andrew T %A Pedersen, Oluf %A Barroso, Inês %A Groop, Leif %A Sladek, Rob %A Thorsteinsdottir, Unnur %A Wilson, James F %A Illig, Thomas %A Froguel, Philippe %A van Duijn, Cornelia M %A Stefansson, Kari %A Altshuler, David %A Boehnke, Michael %A McCarthy, Mark I %A Soranzo, Nicole %A Wheeler, Eleanor %A Glazer, Nicole L %A Bouatia-Naji, Nabila %A Mägi, Reedik %A Randall, Joshua %A Elliott, Paul %A Rybin, Denis %A Dehghan, Abbas %A Hottenga, Jouke Jan %A Song, Kijoung %A Goel, Anuj %A Lajunen, Taina %A Doney, Alex %A Cavalcanti-Proença, Christine %A Kumari, Meena %A Timpson, Nicholas J %A Zabena, Carina %A Ingelsson, Erik %A An, Ping %A O'Connell, Jeffrey %A Luan, Jian'an %A Elliott, Amanda %A McCarroll, Steven A %A Roccasecca, Rosa Maria %A Pattou, François %A Sethupathy, Praveen %A Ariyurek, Yavuz %A Barter, Philip %A Beilby, John P %A Ben-Shlomo, Yoav %A Bergmann, Sven %A Bochud, Murielle %A Bonnefond, Amélie %A Borch-Johnsen, Knut %A Böttcher, Yvonne %A Brunner, Eric %A Bumpstead, Suzannah J %A Chen, Yii-Der Ida %A Chines, Peter %A Clarke, Robert %A Coin, Lachlan J M %A Cooper, Matthew N %A Crisponi, Laura %A Day, Ian N M %A de Geus, Eco J C %A Delplanque, Jerome %A Fedson, Annette C %A Fischer-Rosinsky, Antje %A Forouhi, Nita G %A Franzosi, Maria Grazia %A Galan, Pilar %A Goodarzi, Mark O %A Graessler, Jürgen %A Grundy, Scott %A Gwilliam, Rhian %A Hallmans, Göran %A Hammond, Naomi %A Han, Xijing %A Hartikainen, Anna-Liisa %A Hayward, Caroline %A Heath, Simon C %A Hercberg, Serge %A Hillman, David R %A Hingorani, Aroon D %A Hui, Jennie %A Hung, Joe %A Kaakinen, Marika %A Kaprio, Jaakko %A Kesaniemi, Y Antero %A Kivimaki, Mika %A Knight, Beatrice %A Koskinen, Seppo %A Kovacs, Peter %A Kyvik, Kirsten Ohm %A Lathrop, G Mark %A Lawlor, Debbie A %A Le Bacquer, Olivier %A Lecoeur, Cécile %A Li, Yun %A Mahley, Robert %A Mangino, Massimo %A Martínez-Larrad, María Teresa %A McAteer, Jarred B %A McPherson, Ruth %A Meisinger, Christa %A Melzer, David %A Meyre, David %A Mitchell, Braxton D %A Mukherjee, Sutapa %A Naitza, Silvia %A Neville, Matthew J %A Orrù, Marco %A Pakyz, Ruth %A Paolisso, Giuseppe %A Pattaro, Cristian %A Pearson, Daniel %A Peden, John F %A Pedersen, Nancy L %A Pfeiffer, Andreas F H %A Pichler, Irene %A Polasek, Ozren %A Posthuma, Danielle %A Potter, Simon C %A Pouta, Anneli %A Province, Michael A %A Rayner, Nigel W %A Rice, Kenneth %A Ripatti, Samuli %A Rivadeneira, Fernando %A Rolandsson, Olov %A Sandbaek, Annelli %A Sandhu, Manjinder %A Sanna, Serena %A Sayer, Avan Aihie %A Scheet, Paul %A Seedorf, Udo %A Sharp, Stephen J %A Shields, Beverley %A Sigurðsson, Gunnar %A Sijbrands, Eric J G %A Silveira, Angela %A Simpson, Laila %A Singleton, Andrew %A Smith, Nicholas L %A Sovio, Ulla %A Swift, Amy %A Syddall, Holly %A Syvänen, Ann-Christine %A Tönjes, Anke %A Uitterlinden, André G %A van Dijk, Ko Willems %A Varma, Dhiraj %A Visvikis-Siest, Sophie %A Vitart, Veronique %A Vogelzangs, Nicole %A Waeber, Gérard %A Wagner, Peter J %A Walley, Andrew %A Ward, Kim L %A Watkins, Hugh %A Wild, Sarah H %A Willemsen, Gonneke %A Witteman, Jaqueline C M %A Yarnell, John W G %A Zelenika, Diana %A Zethelius, Björn %A Zhai, Guangju %A Zhao, Jing Hua %A Zillikens, M Carola %A Borecki, Ingrid B %A Meneton, Pierre %A Magnusson, Patrik K E %A Nathan, David M %A Williams, Gordon H %A Silander, Kaisa %A Bornstein, Stefan R %A Schwarz, Peter %A Spranger, Joachim %A Karpe, Fredrik %A Shuldiner, Alan R %A Cooper, Cyrus %A Serrano-Ríos, Manuel %A Lind, Lars %A Palmer, Lyle J %A Hu, Frank B %A Franks, Paul W %A Ebrahim, Shah %A Marmot, Michael %A Kao, W H Linda %A Pramstaller, Peter Paul %A Wright, Alan F %A Stumvoll, Michael %A Hamsten, Anders %A Buchanan, Thomas A %A Valle, Timo T %A Rotter, Jerome I %A Penninx, Brenda W J H %A Boomsma, Dorret I %A Cao, Antonio %A Scuteri, Angelo %A Schlessinger, David %A Uda, Manuela %A Ruokonen, Aimo %A Jarvelin, Marjo-Riitta %A Peltonen, Leena %A Mooser, Vincent %A Sladek, Robert %A Musunuru, Kiran %A Smith, Albert V %A Edmondson, Andrew C %A Stylianou, Ioannis M %A Koseki, Masahiro %A Pirruccello, James P %A Chasman, Daniel I %A Johansen, Christopher T %A Fouchier, Sigrid W %A Peloso, Gina M %A Barbalic, Maja %A Ricketts, Sally L %A Bis, Joshua C %A Feitosa, Mary F %A Orho-Melander, Marju %A Melander, Olle %A Li, Xiaohui %A Li, Mingyao %A Cho, Yoon Shin %A Go, Min Jin %A Kim, Young Jin %A Lee, Jong-Young %A Park, Taesung %A Kim, Kyunga %A Sim, Xueling %A Ong, Rick Twee-Hee %A Croteau-Chonka, Damien C %A Lange, Leslie A %A Smith, Joshua D %A Ziegler, Andreas %A Zhang, Weihua %A Zee, Robert Y L %A Whitfield, John B %A Thompson, John R %A Surakka, Ida %A Spector, Tim D %A Smit, Johannes H %A Sinisalo, Juha %A Scott, James %A Saharinen, Juha %A Sabatti, Chiara %A Rose, Lynda M %A Roberts, Robert %A Rieder, Mark %A Parker, Alex N %A Paré, Guillaume %A O'Donnell, Christopher J %A Nieminen, Markku S %A Nickerson, Deborah A %A Montgomery, Grant W %A McArdle, Wendy %A Masson, David %A Martin, Nicholas G %A Marroni, Fabio %A Lucas, Gavin %A Luben, Robert %A Lokki, Marja-Liisa %A Lettre, Guillaume %A Launer, Lenore J %A Lakatta, Edward G %A Laaksonen, Reijo %A Kyvik, Kirsten O %A König, Inke R %A Khaw, Kay-Tee %A Kaplan, Lee M %A Johansson, Asa %A Janssens, A Cecile J W %A Igl, Wilmar %A Hovingh, G Kees %A Hengstenberg, Christian %A Havulinna, Aki S %A Hastie, Nicholas D %A Harris, Tamara B %A Haritunians, Talin %A Hall, Alistair S %A Groop, Leif C %A Gonzalez, Elena %A Freimer, Nelson B %A Erdmann, Jeanette %A Ejebe, Kenechi G %A Döring, Angela %A Dominiczak, Anna F %A Demissie, Serkalem %A Deloukas, Panagiotis %A de Faire, Ulf %A Crawford, Gabriel %A Chen, Yii-der I %A Caulfield, Mark J %A Boekholdt, S Matthijs %A Assimes, Themistocles L %A Quertermous, Thomas %A Seielstad, Mark %A Wong, Tien Y %A Tai, E-Shyong %A Feranil, Alan B %A Kuzawa, Christopher W %A Taylor, Herman A %A Gabriel, Stacey B %A Holm, Hilma %A Gudnason, Vilmundur %A Krauss, Ronald M %A Ordovas, Jose M %A Munroe, Patricia B %A Kooner, Jaspal S %A Tall, Alan R %A Hegele, Robert A %A Kastelein, John J P %A Schadt, Eric E %A Strachan, David P %A Reilly, Muredach P %A Samani, Nilesh J %A Schunkert, Heribert %A Cupples, L Adrienne %A Sandhu, Manjinder S %A Ridker, Paul M %A Rader, Daniel J %A Kathiresan, Sekar %K Adiponectin %K African Americans %K Asian Continental Ancestry Group %K Cholesterol, HDL %K Diabetes Mellitus, Type 2 %K European Continental Ancestry Group %K Female %K Gene Expression %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Glucose Tolerance Test %K Humans %K Insulin Resistance %K Male %K Metabolic Networks and Pathways %K Polymorphism, Single Nucleotide %K Waist-Hip Ratio %X

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

%B PLoS Genet %V 8 %P e1002607 %8 2012 %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/22479202?dopt=Abstract %R 10.1371/journal.pgen.1002607 %0 Journal Article %J Nat Genet %D 2013 %T Common variants associated with plasma triglycerides and risk for coronary artery disease. %A Do, Ron %A Willer, Cristen J %A Schmidt, Ellen M %A Sengupta, Sebanti %A Gao, Chi %A Peloso, Gina M %A Gustafsson, Stefan %A Kanoni, Stavroula %A Ganna, Andrea %A Chen, Jin %A Buchkovich, Martin L %A Mora, Samia %A Beckmann, Jacques S %A Bragg-Gresham, Jennifer L %A Chang, Hsing-Yi %A Demirkan, Ayse %A Den Hertog, Heleen M %A Donnelly, Louise A %A Ehret, Georg B %A Esko, Tõnu %A Feitosa, Mary F %A Ferreira, Teresa %A Fischer, Krista %A Fontanillas, Pierre %A Fraser, Ross M %A Freitag, Daniel F %A Gurdasani, Deepti %A Heikkilä, Kauko %A Hyppönen, Elina %A Isaacs, Aaron %A Jackson, Anne U %A Johansson, Asa %A Johnson, Toby %A Kaakinen, Marika %A Kettunen, Johannes %A Kleber, Marcus E %A Li, Xiaohui %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Magnusson, Patrik K E %A Mangino, Massimo %A Mihailov, Evelin %A Montasser, May E %A Müller-Nurasyid, Martina %A Nolte, Ilja M %A O'Connell, Jeffrey R %A Palmer, Cameron D %A Perola, Markus %A Petersen, Ann-Kristin %A Sanna, Serena %A Saxena, Richa %A Service, Susan K %A Shah, Sonia %A Shungin, Dmitry %A Sidore, Carlo %A Song, Ci %A Strawbridge, Rona J %A Surakka, Ida %A Tanaka, Toshiko %A Teslovich, Tanya M %A Thorleifsson, Gudmar %A van den Herik, Evita G %A Voight, Benjamin F %A Volcik, Kelly A %A Waite, Lindsay L %A Wong, Andrew %A Wu, Ying %A Zhang, Weihua %A Absher, Devin %A Asiki, Gershim %A Barroso, Inês %A Been, Latonya F %A Bolton, Jennifer L %A Bonnycastle, Lori L %A Brambilla, Paolo %A Burnett, Mary S %A Cesana, Giancarlo %A Dimitriou, Maria %A Doney, Alex S F %A Döring, Angela %A Elliott, Paul %A Epstein, Stephen E %A Eyjolfsson, Gudmundur Ingi %A Gigante, Bruna %A Goodarzi, Mark O %A Grallert, Harald %A Gravito, Martha L %A Groves, Christopher J %A Hallmans, Göran %A Hartikainen, Anna-Liisa %A Hayward, Caroline %A Hernandez, Dena %A Hicks, Andrew A %A Holm, Hilma %A Hung, Yi-Jen %A Illig, Thomas %A Jones, Michelle R %A Kaleebu, Pontiano %A Kastelein, John J P %A Khaw, Kay-Tee %A Kim, Eric %A Klopp, Norman %A Komulainen, Pirjo %A Kumari, Meena %A Langenberg, Claudia %A Lehtimäki, Terho %A Lin, Shih-Yi %A Lindström, Jaana %A Loos, Ruth J F %A Mach, François %A McArdle, Wendy L %A Meisinger, Christa %A Mitchell, Braxton D %A Müller, Gabrielle %A Nagaraja, Ramaiah %A Narisu, Narisu %A Nieminen, Tuomo V M %A Nsubuga, Rebecca N %A Olafsson, Isleifur %A Ong, Ken K %A Palotie, Aarno %A Papamarkou, Theodore %A Pomilla, Cristina %A Pouta, Anneli %A Rader, Daniel J %A Reilly, Muredach P %A Ridker, Paul M %A Rivadeneira, Fernando %A Rudan, Igor %A Ruokonen, Aimo %A Samani, Nilesh %A Scharnagl, Hubert %A Seeley, Janet %A Silander, Kaisa %A Stančáková, Alena %A Stirrups, Kathleen %A Swift, Amy J %A Tiret, Laurence %A Uitterlinden, André G %A van Pelt, L Joost %A Vedantam, Sailaja %A Wainwright, Nicholas %A Wijmenga, Cisca %A Wild, Sarah H %A Willemsen, Gonneke %A Wilsgaard, Tom %A Wilson, James F %A Young, Elizabeth H %A Zhao, Jing Hua %A Adair, Linda S %A Arveiler, Dominique %A Assimes, Themistocles L %A Bandinelli, Stefania %A Bennett, Franklyn %A Bochud, Murielle %A Boehm, Bernhard O %A Boomsma, Dorret I %A Borecki, Ingrid B %A Bornstein, Stefan R %A Bovet, Pascal %A Burnier, Michel %A Campbell, Harry %A Chakravarti, Aravinda %A Chambers, John C %A Chen, Yii-Der Ida %A Collins, Francis S %A Cooper, Richard S %A Danesh, John %A Dedoussis, George %A de Faire, Ulf %A Feranil, Alan B %A Ferrieres, Jean %A Ferrucci, Luigi %A Freimer, Nelson B %A Gieger, Christian %A Groop, Leif C %A Gudnason, Vilmundur %A Gyllensten, Ulf %A Hamsten, Anders %A Harris, Tamara B %A Hingorani, Aroon %A Hirschhorn, Joel N %A Hofman, Albert %A Hovingh, G Kees %A Hsiung, Chao Agnes %A Humphries, Steve E %A Hunt, Steven C %A Hveem, Kristian %A Iribarren, Carlos %A Jarvelin, Marjo-Riitta %A Jula, Antti %A Kähönen, Mika %A Kaprio, Jaakko %A Kesäniemi, Antero %A Kivimaki, Mika %A Kooner, Jaspal S %A Koudstaal, Peter J %A Krauss, Ronald M %A Kuh, Diana %A Kuusisto, Johanna %A Kyvik, Kirsten O %A Laakso, Markku %A Lakka, Timo A %A Lind, Lars %A Lindgren, Cecilia M %A Martin, Nicholas G %A März, Winfried %A McCarthy, Mark I %A McKenzie, Colin A %A Meneton, Pierre %A Metspalu, Andres %A Moilanen, Leena %A Morris, Andrew D %A Munroe, Patricia B %A Njølstad, Inger %A Pedersen, Nancy L %A Power, Chris %A Pramstaller, Peter P %A Price, Jackie F %A Psaty, Bruce M %A Quertermous, Thomas %A Rauramaa, Rainer %A Saleheen, Danish %A Salomaa, Veikko %A Sanghera, Dharambir K %A Saramies, Jouko %A Schwarz, Peter E H %A Sheu, Wayne H-H %A Shuldiner, Alan R %A Siegbahn, Agneta %A Spector, Tim D %A Stefansson, Kari %A Strachan, David P %A Tayo, Bamidele O %A Tremoli, Elena %A Tuomilehto, Jaakko %A Uusitupa, Matti %A van Duijn, Cornelia M %A Vollenweider, Peter %A Wallentin, Lars %A Wareham, Nicholas J %A Whitfield, John B %A Wolffenbuttel, Bruce H R %A Altshuler, David %A Ordovas, Jose M %A Boerwinkle, Eric %A Palmer, Colin N A %A Thorsteinsdottir, Unnur %A Chasman, Daniel I %A Rotter, Jerome I %A Franks, Paul W %A Ripatti, Samuli %A Cupples, L Adrienne %A Sandhu, Manjinder S %A Rich, Stephen S %A Boehnke, Michael %A Deloukas, Panos %A Mohlke, Karen L %A Ingelsson, Erik %A Abecasis, Goncalo R %A Daly, Mark J %A Neale, Benjamin M %A Kathiresan, Sekar %K Biological Transport %K Cholesterol, HDL %K Cholesterol, LDL %K Coronary Artery Disease %K Humans %K Polymorphism, Single Nucleotide %K Risk Factors %K Triglycerides %X

Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

%B Nat Genet %V 45 %P 1345-52 %8 2013 Nov %G eng %N 11 %R 10.1038/ng.2795 %0 Journal Article %J Nat Genet %D 2013 %T Discovery and refinement of loci associated with lipid levels. %A Willer, Cristen J %A Schmidt, Ellen M %A Sengupta, Sebanti %A Peloso, Gina M %A Gustafsson, Stefan %A Kanoni, Stavroula %A Ganna, Andrea %A Chen, Jin %A Buchkovich, Martin L %A Mora, Samia %A Beckmann, Jacques S %A Bragg-Gresham, Jennifer L %A Chang, Hsing-Yi %A Demirkan, Ayse %A Den Hertog, Heleen M %A Do, Ron %A Donnelly, Louise A %A Ehret, Georg B %A Esko, Tõnu %A Feitosa, Mary F %A Ferreira, Teresa %A Fischer, Krista %A Fontanillas, Pierre %A Fraser, Ross M %A Freitag, Daniel F %A Gurdasani, Deepti %A Heikkilä, Kauko %A Hyppönen, Elina %A Isaacs, Aaron %A Jackson, Anne U %A Johansson, Asa %A Johnson, Toby %A Kaakinen, Marika %A Kettunen, Johannes %A Kleber, Marcus E %A Li, Xiaohui %A Luan, Jian'an %A Lyytikäinen, Leo-Pekka %A Magnusson, Patrik K E %A Mangino, Massimo %A Mihailov, Evelin %A Montasser, May E %A Müller-Nurasyid, Martina %A Nolte, Ilja M %A O'Connell, Jeffrey R %A Palmer, Cameron D %A Perola, Markus %A Petersen, Ann-Kristin %A Sanna, Serena %A Saxena, Richa %A Service, Susan K %A Shah, Sonia %A Shungin, Dmitry %A Sidore, Carlo %A Song, Ci %A Strawbridge, Rona J %A Surakka, Ida %A Tanaka, Toshiko %A Teslovich, Tanya M %A Thorleifsson, Gudmar %A van den Herik, Evita G %A Voight, Benjamin F %A Volcik, Kelly A %A Waite, Lindsay L %A Wong, Andrew %A Wu, Ying %A Zhang, Weihua %A Absher, Devin %A Asiki, Gershim %A Barroso, Inês %A Been, Latonya F %A Bolton, Jennifer L %A Bonnycastle, Lori L %A Brambilla, Paolo %A Burnett, Mary S %A Cesana, Giancarlo %A Dimitriou, Maria %A Doney, Alex S F %A Döring, Angela %A Elliott, Paul %A Epstein, Stephen E %A Ingi Eyjolfsson, Gudmundur %A Gigante, Bruna %A Goodarzi, Mark O %A Grallert, Harald %A Gravito, Martha L %A Groves, Christopher J %A Hallmans, Göran %A Hartikainen, Anna-Liisa %A Hayward, Caroline %A Hernandez, Dena %A Hicks, Andrew A %A Holm, Hilma %A Hung, Yi-Jen %A Illig, Thomas %A Jones, Michelle R %A Kaleebu, Pontiano %A Kastelein, John J P %A Khaw, Kay-Tee %A Kim, Eric %A Klopp, Norman %A Komulainen, Pirjo %A Kumari, Meena %A Langenberg, Claudia %A Lehtimäki, Terho %A Lin, Shih-Yi %A Lindström, Jaana %A Loos, Ruth J F %A Mach, François %A McArdle, Wendy L %A Meisinger, Christa %A Mitchell, Braxton D %A Müller, Gabrielle %A Nagaraja, Ramaiah %A Narisu, Narisu %A Nieminen, Tuomo V M %A Nsubuga, Rebecca N %A Olafsson, Isleifur %A Ong, Ken K %A Palotie, Aarno %A Papamarkou, Theodore %A Pomilla, Cristina %A Pouta, Anneli %A Rader, Daniel J %A Reilly, Muredach P %A Ridker, Paul M %A Rivadeneira, Fernando %A Rudan, Igor %A Ruokonen, Aimo %A Samani, Nilesh %A Scharnagl, Hubert %A Seeley, Janet %A Silander, Kaisa %A Stančáková, Alena %A Stirrups, Kathleen %A Swift, Amy J %A Tiret, Laurence %A Uitterlinden, André G %A van Pelt, L Joost %A Vedantam, Sailaja %A Wainwright, Nicholas %A Wijmenga, Cisca %A Wild, Sarah H %A Willemsen, Gonneke %A Wilsgaard, Tom %A Wilson, James F %A Young, Elizabeth H %A Zhao, Jing Hua %A Adair, Linda S %A Arveiler, Dominique %A Assimes, Themistocles L %A Bandinelli, Stefania %A Bennett, Franklyn %A Bochud, Murielle %A Boehm, Bernhard O %A Boomsma, Dorret I %A Borecki, Ingrid B %A Bornstein, Stefan R %A Bovet, Pascal %A Burnier, Michel %A Campbell, Harry %A Chakravarti, Aravinda %A Chambers, John C %A Chen, Yii-Der Ida %A Collins, Francis S %A Cooper, Richard S %A Danesh, John %A Dedoussis, George %A de Faire, Ulf %A Feranil, Alan B %A Ferrieres, Jean %A Ferrucci, Luigi %A Freimer, Nelson B %A Gieger, Christian %A Groop, Leif C %A Gudnason, Vilmundur %A Gyllensten, Ulf %A Hamsten, Anders %A Harris, Tamara B %A Hingorani, Aroon %A Hirschhorn, Joel N %A Hofman, Albert %A Hovingh, G Kees %A Hsiung, Chao Agnes %A Humphries, Steve E %A Hunt, Steven C %A Hveem, Kristian %A Iribarren, Carlos %A Jarvelin, Marjo-Riitta %A Jula, Antti %A Kähönen, Mika %A Kaprio, Jaakko %A Kesäniemi, Antero %A Kivimaki, Mika %A Kooner, Jaspal S %A Koudstaal, Peter J %A Krauss, Ronald M %A Kuh, Diana %A Kuusisto, Johanna %A Kyvik, Kirsten O %A Laakso, Markku %A Lakka, Timo A %A Lind, Lars %A Lindgren, Cecilia M %A Martin, Nicholas G %A März, Winfried %A McCarthy, Mark I %A McKenzie, Colin A %A Meneton, Pierre %A Metspalu, Andres %A Moilanen, Leena %A Morris, Andrew D %A Munroe, Patricia B %A Njølstad, Inger %A Pedersen, Nancy L %A Power, Chris %A Pramstaller, Peter P %A Price, Jackie F %A Psaty, Bruce M %A Quertermous, Thomas %A Rauramaa, Rainer %A Saleheen, Danish %A Salomaa, Veikko %A Sanghera, Dharambir K %A Saramies, Jouko %A Schwarz, Peter E H %A Sheu, Wayne H-H %A Shuldiner, Alan R %A Siegbahn, Agneta %A Spector, Tim D %A Stefansson, Kari %A Strachan, David P %A Tayo, Bamidele O %A Tremoli, Elena %A Tuomilehto, Jaakko %A Uusitupa, Matti %A van Duijn, Cornelia M %A Vollenweider, Peter %A Wallentin, Lars %A Wareham, Nicholas J %A Whitfield, John B %A Wolffenbuttel, Bruce H R %A Ordovas, Jose M %A Boerwinkle, Eric %A Palmer, Colin N A %A Thorsteinsdottir, Unnur %A Chasman, Daniel I %A Rotter, Jerome I %A Franks, Paul W %A Ripatti, Samuli %A Cupples, L Adrienne %A Sandhu, Manjinder S %A Rich, Stephen S %A Boehnke, Michael %A Deloukas, Panos %A Kathiresan, Sekar %A Mohlke, Karen L %A Ingelsson, Erik %A Abecasis, Goncalo R %K African Continental Ancestry Group %K Asian Continental Ancestry Group %K Cholesterol, HDL %K Cholesterol, LDL %K Coronary Artery Disease %K European Continental Ancestry Group %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genotype %K Humans %K Lipids %K Triglycerides %X

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

%B Nat Genet %V 45 %P 1274-1283 %8 2013 Nov %G eng %N 11 %1 http://www.ncbi.nlm.nih.gov/pubmed/24097068?dopt=Abstract %R 10.1038/ng.2797 %0 Journal Article %J PLoS Genet %D 2013 %T Genome-wide association of body fat distribution in African ancestry populations suggests new loci. %A Liu, Ching-Ti %A Monda, Keri L %A Taylor, Kira C %A Lange, Leslie %A Demerath, Ellen W %A Palmas, Walter %A Wojczynski, Mary K %A Ellis, Jaclyn C %A Vitolins, Mara Z %A Liu, Simin %A Papanicolaou, George J %A Irvin, Marguerite R %A Xue, Luting %A Griffin, Paula J %A Nalls, Michael A %A Adeyemo, Adebowale %A Liu, Jiankang %A Li, Guo %A Ruiz-Narvaez, Edward A %A Chen, Wei-Min %A Chen, Fang %A Henderson, Brian E %A Millikan, Robert C %A Ambrosone, Christine B %A Strom, Sara S %A Guo, Xiuqing %A Andrews, Jeanette S %A Sun, Yan V %A Mosley, Thomas H %A Yanek, Lisa R %A Shriner, Daniel %A Haritunians, Talin %A Rotter, Jerome I %A Speliotes, Elizabeth K %A Smith, Megan %A Rosenberg, Lynn %A Mychaleckyj, Josyf %A Nayak, Uma %A Spruill, Ida %A Garvey, W Timothy %A Pettaway, Curtis %A Nyante, Sarah %A Bandera, Elisa V %A Britton, Angela F %A Zonderman, Alan B %A Rasmussen-Torvik, Laura J %A Chen, Yii-Der Ida %A Ding, Jingzhong %A Lohman, Kurt %A Kritchevsky, Stephen B %A Zhao, Wei %A Peyser, Patricia A %A Kardia, Sharon L R %A Kabagambe, Edmond %A Broeckel, Ulrich %A Chen, Guanjie %A Zhou, Jie %A Wassertheil-Smoller, Sylvia %A Neuhouser, Marian L %A Rampersaud, Evadnie %A Psaty, Bruce %A Kooperberg, Charles %A Manson, JoAnn E %A Kuller, Lewis H %A Ochs-Balcom, Heather M %A Johnson, Karen C %A Sucheston, Lara %A Ordovas, Jose M %A Palmer, Julie R %A Haiman, Christopher A %A McKnight, Barbara %A Howard, Barbara V %A Becker, Diane M %A Bielak, Lawrence F %A Liu, Yongmei %A Allison, Matthew A %A Grant, Struan F A %A Burke, Gregory L %A Patel, Sanjay R %A Schreiner, Pamela J %A Borecki, Ingrid B %A Evans, Michele K %A Taylor, Herman %A Sale, Michèle M %A Howard, Virginia %A Carlson, Christopher S %A Rotimi, Charles N %A Cushman, Mary %A Harris, Tamara B %A Reiner, Alexander P %A Cupples, L Adrienne %A North, Kari E %A Fox, Caroline S %K Adiposity %K African Continental Ancestry Group %K Body Fat Distribution %K European Continental Ancestry Group %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Male %K Obesity %K Polymorphism, Single Nucleotide %K Waist-Hip Ratio %X

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 × 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 = 2.24×10(-8) for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10(-8) for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5 × 10(-8); RREB1: p = 5.7 × 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.

%B PLoS Genet %V 9 %P e1003681 %8 2013 %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/23966867?dopt=Abstract %R 10.1371/journal.pgen.1003681 %0 Journal Article %J Am J Clin Nutr %D 2013 %T Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake. %A Tanaka, Toshiko %A Ngwa, Julius S %A van Rooij, Frank J A %A Zillikens, M Carola %A Wojczynski, Mary K %A Frazier-Wood, Alexis C %A Houston, Denise K %A Kanoni, Stavroula %A Lemaitre, Rozenn N %A Luan, Jian'an %A Mikkilä, Vera %A Renstrom, Frida %A Sonestedt, Emily %A Zhao, Jing Hua %A Chu, Audrey Y %A Qi, Lu %A Chasman, Daniel I %A de Oliveira Otto, Marcia C %A Dhurandhar, Emily J %A Feitosa, Mary F %A Johansson, Ingegerd %A Khaw, Kay-Tee %A Lohman, Kurt K %A Manichaikul, Ani %A McKeown, Nicola M %A Mozaffarian, Dariush %A Singleton, Andrew %A Stirrups, Kathleen %A Viikari, Jorma %A Ye, Zheng %A Bandinelli, Stefania %A Barroso, Inês %A Deloukas, Panos %A Forouhi, Nita G %A Hofman, Albert %A Liu, Yongmei %A Lyytikäinen, Leo-Pekka %A North, Kari E %A Dimitriou, Maria %A Hallmans, Göran %A Kähönen, Mika %A Langenberg, Claudia %A Ordovas, Jose M %A Uitterlinden, André G %A Hu, Frank B %A Kalafati, Ioanna-Panagiota %A Raitakari, Olli %A Franco, Oscar H %A Johnson, Andrew %A Emilsson, Valur %A Schrack, Jennifer A %A Semba, Richard D %A Siscovick, David S %A Arnett, Donna K %A Borecki, Ingrid B %A Franks, Paul W %A Kritchevsky, Stephen B %A Lehtimäki, Terho %A Loos, Ruth J F %A Orho-Melander, Marju %A Rotter, Jerome I %A Wareham, Nicholas J %A Witteman, Jacqueline C M %A Ferrucci, Luigi %A Dedoussis, George %A Cupples, L Adrienne %A Nettleton, Jennifer A %K Alleles %K Atherosclerosis %K Body Mass Index %K Dietary Carbohydrates %K Dietary Fats %K Dietary Proteins %K Energy Intake %K European Continental Ancestry Group %K Fibroblast Growth Factors %K Follow-Up Studies %K Gene-Environment Interaction %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genotype %K Humans %K Life Style %K Obesity %K Polymorphism, Single Nucleotide %K Prospective Studies %K Quantitative Trait Loci %K Surveys and Questionnaires %X

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 × 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 ± SE: 0.25 ± 0.04%; P = 1.68 × 10(-8)) and lower fat (β ± SE: -0.21 ± 0.04%; P = 1.57 × 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 ± SE: 0.10 ± 0.02%; P = 9.96 × 10(-10)), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 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).

%B Am J Clin Nutr %V 97 %P 1395-402 %8 2013 Jun %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/23636237?dopt=Abstract %R 10.3945/ajcn.112.052183 %0 Journal Article %J Am J Hum Genet %D 2014 %T Association of low-frequency and rare coding-sequence variants with blood lipids and coronary heart disease in 56,000 whites and blacks. %A Peloso, Gina M %A Auer, Paul L %A Bis, Joshua C %A Voorman, Arend %A Morrison, Alanna C %A Stitziel, Nathan O %A Brody, Jennifer A %A Khetarpal, Sumeet A %A Crosby, Jacy R %A Fornage, Myriam %A Isaacs, Aaron %A Jakobsdottir, Johanna %A Feitosa, Mary F %A Davies, Gail %A Huffman, Jennifer E %A Manichaikul, Ani %A Davis, Brian %A Lohman, Kurt %A Joon, Aron Y %A Smith, Albert V %A Grove, Megan L %A Zanoni, Paolo %A Redon, Valeska %A Demissie, Serkalem %A Lawson, Kim %A Peters, Ulrike %A Carlson, Christopher %A Jackson, Rebecca D %A Ryckman, Kelli K %A Mackey, Rachel H %A Robinson, Jennifer G %A Siscovick, David S %A Schreiner, Pamela J %A Mychaleckyj, Josyf C %A Pankow, James S %A Hofman, Albert %A Uitterlinden, André G %A Harris, Tamara B %A Taylor, Kent D %A Stafford, Jeanette M %A Reynolds, Lindsay M %A Marioni, Riccardo E %A Dehghan, Abbas %A Franco, Oscar H %A Patel, Aniruddh P %A Lu, Yingchang %A Hindy, George %A Gottesman, Omri %A Bottinger, Erwin P %A Melander, Olle %A Orho-Melander, Marju %A Loos, Ruth J F %A Duga, Stefano %A Merlini, Piera Angelica %A Farrall, Martin %A Goel, Anuj %A Asselta, Rosanna %A Girelli, Domenico %A Martinelli, Nicola %A Shah, Svati H %A Kraus, William E %A Li, Mingyao %A Rader, Daniel J %A Reilly, Muredach P %A McPherson, Ruth %A Watkins, Hugh %A Ardissino, Diego %A Zhang, Qunyuan %A Wang, Judy %A Tsai, Michael Y %A Taylor, Herman A %A Correa, Adolfo %A Griswold, Michael E %A Lange, Leslie A %A Starr, John M %A Rudan, Igor %A Eiriksdottir, Gudny %A Launer, Lenore J %A Ordovas, Jose M %A Levy, Daniel %A Chen, Y-D Ida %A Reiner, Alexander P %A Hayward, Caroline %A Polasek, Ozren %A Deary, Ian J %A Borecki, Ingrid B %A Liu, Yongmei %A Gudnason, Vilmundur %A Wilson, James G %A van Duijn, Cornelia M %A Kooperberg, Charles %A Rich, Stephen S %A Psaty, Bruce M %A Rotter, Jerome I %A O'Donnell, Christopher J %A Rice, Kenneth %A Boerwinkle, Eric %A Kathiresan, Sekar %A Cupples, L Adrienne %K 1-Alkyl-2-acetylglycerophosphocholine Esterase %K Adult %K African Continental Ancestry Group %K Aged %K Alleles %K Animals %K Cholesterol, HDL %K Cholesterol, LDL %K Cohort Studies %K Coronary Disease %K European Continental Ancestry Group %K Female %K Gene Frequency %K Genetic Association Studies %K Genetic Code %K Genetic Variation %K Humans %K Linear Models %K Male %K Mice %K Mice, Inbred C57BL %K Microtubule-Associated Proteins %K Middle Aged %K Phenotype %K Sequence Analysis, DNA %K Subtilisins %K Triglycerides %X

Low-frequency coding DNA sequence variants in the proprotein convertase subtilisin/kexin type 9 gene (PCSK9) lower plasma low-density lipoprotein cholesterol (LDL-C), protect against risk of coronary heart disease (CHD), and have prompted the development of a new class of therapeutics. It is uncertain whether the PCSK9 example represents a paradigm or an isolated exception. We used the "Exome Array" to genotype >200,000 low-frequency and rare coding sequence variants across the genome in 56,538 individuals (42,208 European ancestry [EA] and 14,330 African ancestry [AA]) and tested these variants for association with LDL-C, high-density lipoprotein cholesterol (HDL-C), and triglycerides. Although we did not identify new genes associated with LDL-C, we did identify four low-frequency (frequencies between 0.1% and 2%) variants (ANGPTL8 rs145464906 [c.361C>T; p.Gln121*], PAFAH1B2 rs186808413 [c.482C>T; p.Ser161Leu], COL18A1 rs114139997 [c.331G>A; p.Gly111Arg], and PCSK7 rs142953140 [c.1511G>A; p.Arg504His]) with large effects on HDL-C and/or triglycerides. None of these four variants was associated with risk for CHD, suggesting that examples of low-frequency coding variants with robust effects on both lipids and CHD will be limited.

%B Am J Hum Genet %V 94 %P 223-32 %8 2014 Feb 06 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/24507774?dopt=Abstract %R 10.1016/j.ajhg.2014.01.009 %0 Journal Article %J N Engl J Med %D 2014 %T Loss-of-function mutations in APOC3, triglycerides, and coronary disease. %A Crosby, Jacy %A Peloso, Gina M %A Auer, Paul L %A Crosslin, David R %A Stitziel, Nathan O %A Lange, Leslie A %A Lu, Yingchang %A Tang, Zheng-Zheng %A Zhang, He %A Hindy, George %A Masca, Nicholas %A Stirrups, Kathleen %A Kanoni, Stavroula %A Do, Ron %A Jun, Goo %A Hu, Youna %A Kang, Hyun Min %A Xue, Chenyi %A Goel, Anuj %A Farrall, Martin %A Duga, Stefano %A Merlini, Pier Angelica %A Asselta, Rosanna %A Girelli, Domenico %A Olivieri, Oliviero %A Martinelli, Nicola %A Yin, Wu %A Reilly, Dermot %A Speliotes, Elizabeth %A Fox, Caroline S %A Hveem, Kristian %A Holmen, Oddgeir L %A Nikpay, Majid %A Farlow, Deborah N %A Assimes, Themistocles L %A Franceschini, Nora %A Robinson, Jennifer %A North, Kari E %A Martin, Lisa W %A DePristo, Mark %A Gupta, Namrata %A Escher, Stefan A %A Jansson, Jan-Håkan %A Van Zuydam, Natalie %A Palmer, Colin N A %A Wareham, Nicholas %A Koch, Werner %A Meitinger, Thomas %A Peters, Annette %A Lieb, Wolfgang %A Erbel, Raimund %A König, Inke R %A Kruppa, Jochen %A Degenhardt, Franziska %A Gottesman, Omri %A Bottinger, Erwin P %A O'Donnell, Christopher J %A Psaty, Bruce M %A Ballantyne, Christie M %A Abecasis, Goncalo %A Ordovas, Jose M %A Melander, Olle %A Watkins, Hugh %A Orho-Melander, Marju %A Ardissino, Diego %A Loos, Ruth J F %A McPherson, Ruth %A Willer, Cristen J %A Erdmann, Jeanette %A Hall, Alistair S %A Samani, Nilesh J %A Deloukas, Panos %A Schunkert, Heribert %A Wilson, James G %A Kooperberg, Charles %A Rich, Stephen S %A Tracy, Russell P %A Lin, Dan-Yu %A Altshuler, David %A Gabriel, Stacey %A Nickerson, Deborah A %A Jarvik, Gail P %A Cupples, L Adrienne %A Reiner, Alex P %A Boerwinkle, Eric %A Kathiresan, Sekar %K African Continental Ancestry Group %K Apolipoprotein C-III %K Coronary Disease %K European Continental Ancestry Group %K Exome %K Genotype %K Heterozygote %K Humans %K Liver %K Mutation %K Risk Factors %K Sequence Analysis, DNA %K Triglycerides %X

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→A and IVS3+1G→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<1×10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P=8×10(-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=4×10(-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.).

%B N Engl J Med %V 371 %P 22-31 %8 2014 Jul 3 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/24941081?dopt=Abstract %R 10.1056/NEJMoa1307095 %0 Journal Article %J Am J Clin Nutr %D 2015 %T 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. %A Fretts, Amanda M %A Follis, Jack L %A Nettleton, Jennifer A %A Lemaitre, Rozenn N %A Ngwa, Julius S %A Wojczynski, Mary K %A Kalafati, Ioanna Panagiota %A Varga, Tibor V %A Frazier-Wood, Alexis C %A Houston, Denise K %A Lahti, Jari %A Ericson, Ulrika %A van den Hooven, Edith H %A Mikkilä, Vera %A Kiefte-de Jong, Jessica C %A Mozaffarian, Dariush %A Rice, Kenneth %A Renstrom, Frida %A North, Kari E %A McKeown, Nicola M %A Feitosa, Mary F %A Kanoni, Stavroula %A Smith, Caren E %A Garcia, Melissa E %A Tiainen, Anna-Maija %A Sonestedt, Emily %A Manichaikul, Ani %A van Rooij, Frank J A %A Dimitriou, Maria %A Raitakari, Olli %A Pankow, James S %A Djoussé, Luc %A Province, Michael A %A Hu, Frank B %A Lai, Chao-Qiang %A Keller, Margaux F %A Perälä, Mia-Maria %A Rotter, Jerome I %A Hofman, Albert %A Graff, Misa %A Kähönen, Mika %A Mukamal, Kenneth %A Johansson, Ingegerd %A Ordovas, Jose M %A Liu, Yongmei %A Männistö, Satu %A Uitterlinden, André G %A Deloukas, Panos %A Seppälä, Ilkka %A Psaty, Bruce M %A Cupples, L Adrienne %A Borecki, Ingrid B %A Franks, Paul W %A Arnett, Donna K %A Nalls, Mike A %A Eriksson, Johan G %A Orho-Melander, Marju %A Franco, Oscar H %A Lehtimäki, Terho %A Dedoussis, George V %A Meigs, James B %A Siscovick, David S %K Blood Glucose %K Cohort Studies %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Hyperglycemia %K Hyperinsulinism %K Insulin %K Insulin Resistance %K Insulin-Secreting Cells %K Meat %K Meat Products %K Middle Aged %K Polymorphism, Single Nucleotide %K Risk Factors %X

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).

%B Am J Clin Nutr %V 102 %P 1266-78 %8 2015 Nov %G eng %N 5 %1 http://www.ncbi.nlm.nih.gov/pubmed/26354543?dopt=Abstract %R 10.3945/ajcn.114.101238 %0 Journal Article %J Mol Nutr Food Res %D 2015 %T Dietary fatty acids modulate associations between genetic variants and circulating fatty acids in plasma and erythrocyte membranes: Meta-analysis of nine studies in the CHARGE consortium. %A Smith, Caren E %A Follis, Jack L %A Nettleton, Jennifer A %A Foy, Millennia %A Wu, Jason H Y %A Ma, Yiyi %A Tanaka, Toshiko %A Manichakul, Ani W %A Wu, Hongyu %A Chu, Audrey Y %A Steffen, Lyn M %A Fornage, Myriam %A Mozaffarian, Dariush %A Kabagambe, Edmond K %A Ferruci, Luigi %A Chen, Yii-Der Ida %A Rich, Stephen S %A Djoussé, Luc %A Ridker, Paul M %A Tang, Weihong %A McKnight, Barbara %A Tsai, Michael Y %A Bandinelli, Stefania %A Rotter, Jerome I %A Hu, Frank B %A Chasman, Daniel I %A Psaty, Bruce M %A Arnett, Donna K %A King, Irena B %A Sun, Qi %A Wang, Lu %A Lumley, Thomas %A Chiuve, Stephanie E %A Siscovick, David S %A Ordovas, Jose M %A Lemaitre, Rozenn N %K Acetyltransferases %K Acyltransferases %K Adaptor Proteins, Signal Transducing %K Carboxy-Lyases %K Diet %K Docosahexaenoic Acids %K Eicosapentaenoic Acid %K Erythrocyte Membrane %K Fatty Acid Desaturases %K Fatty Acids %K Fatty Acids, Omega-3 %K Female %K Humans %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %X

SCOPE: Tissue concentrations of omega-3 fatty acids may reduce cardiovascular disease risk, and genetic variants are associated with circulating fatty acids concentrations. Whether dietary fatty acids interact with genetic variants to modify circulating omega-3 fatty acids is unclear. We evaluated interactions between genetic variants and fatty acid intakes for circulating alpha-linoleic acid, eicosapentaenoic acid, docosahexaenoic acid, and docosapentaenoic acid.

METHODS AND RESULTS: We conducted meta-analyses (N = 11 668) evaluating interactions between dietary fatty acids and genetic variants (rs174538 and rs174548 in FADS1 (fatty acid desaturase 1), rs7435 in AGPAT3 (1-acyl-sn-glycerol-3-phosphate), rs4985167 in PDXDC1 (pyridoxal-dependent decarboxylase domain-containing 1), rs780094 in GCKR (glucokinase regulatory protein), and rs3734398 in ELOVL2 (fatty acid elongase 2)). Stratification by measurement compartment (plasma versus erthyrocyte) revealed compartment-specific interactions between FADS1 rs174538 and rs174548 and dietary alpha-linolenic acid and linoleic acid for docosahexaenoic acid and docosapentaenoic acid.

CONCLUSION: Our findings reinforce earlier reports that genetically based differences in circulating fatty acids may be partially due to differences in the conversion of fatty acid precursors. Further, fatty acids measurement compartment may modify gene-diet relationships, and considering compartment may improve the detection of gene-fatty acids interactions for circulating fatty acid outcomes.

%B Mol Nutr Food Res %V 59 %P 1373-83 %8 2015 Jul %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/25626431?dopt=Abstract %R 10.1002/mnfr.201400734 %0 Journal Article %J Diabetes Care %D 2015 %T Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits. %A Dashti, Hassan S %A Follis, Jack L %A Smith, Caren E %A Tanaka, Toshiko %A Garaulet, Marta %A Gottlieb, Daniel J %A Hruby, Adela %A Jacques, Paul F %A Kiefte-de Jong, Jessica C %A Lamon-Fava, Stefania %A Scheer, Frank A J L %A Bartz, Traci M %A Kovanen, Leena %A Wojczynski, Mary K %A Frazier-Wood, Alexis C %A Ahluwalia, Tarunveer S %A Perälä, Mia-Maria %A Jonsson, Anna %A Muka, Taulant %A Kalafati, Ioanna P %A Mikkilä, Vera %A Ordovas, Jose M %K Adult %K Alleles %K Blood Glucose %K Circadian Rhythm Signaling Peptides and Proteins %K Cohort Studies %K Diabetes Mellitus, Type 2 %K Diet, Fat-Restricted %K European Continental Ancestry Group %K Fasting %K Female %K Gene-Environment Interaction %K Humans %K Insulin Resistance %K Male %K Middle Aged %K Multicenter Studies as Topic %K Observational Studies as Topic %K Phenotype %K Polymorphism, Single Nucleotide %K Sleep %K Waist Circumference %X

OBJECTIVE: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153, MTNR1B-rs10830963, NR1D1-rs2314339) and cardiometabolic traits (fasting glucose [FG], HOMA-insulin resistance, BMI, waist circumference, and HDL-cholesterol) to facilitate personalized recommendations.

RESEARCH DESIGN AND METHODS: We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations and interactions between dietary intake/sleep duration and selected variants on cardiometabolic traits from 15 cohort studies including up to 28,190 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

RESULTS: We observed significant associations between relative macronutrient intakes and glycemic traits and short sleep duration (<7 h) and higher FG and replicated known MTNR1B associations with glycemic traits. No interactions were evident after accounting for multiple comparisons. However, we observed nominally significant interactions (all P < 0.01) between carbohydrate intake and MTNR1B-rs1387153 for FG with a 0.003 mmol/L higher FG with each additional 1% carbohydrate intake in the presence of the T allele, between sleep duration and CRY2-rs11605924 for HDL-cholesterol with a 0.010 mmol/L higher HDL-cholesterol with each additional hour of sleep in the presence of the A allele, and between long sleep duration (≥9 h) and MTNR1B-rs1387153 for BMI with a 0.60 kg/m(2) higher BMI with long sleep duration in the presence of the T allele relative to normal sleep duration (≥7 to <9 h).

CONCLUSIONS: Our results suggest that lower carbohydrate intake and normal sleep duration may ameliorate cardiometabolic abnormalities conferred by common circadian-related genetic variants. Until further mechanistic examination of the nominally significant interactions is conducted, recommendations applicable to the general population regarding diet—specifically higher carbohydrate and lower fat composition—and normal sleep duration should continue to be emphasized among individuals with the investigated circadian-related gene variants.

%B Diabetes Care %V 38 %P 1456-66 %8 2015 Aug %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/26084345?dopt=Abstract %R 10.2337/dc14-2709 %0 Journal Article %J Am J Clin Nutr %D 2015 %T Habitual sleep duration is associated with BMI and macronutrient intake and may be modified by CLOCK genetic variants. %A Dashti, Hassan S %A Follis, Jack L %A Smith, Caren E %A Tanaka, Toshiko %A Cade, Brian E %A Gottlieb, Daniel J %A Hruby, Adela %A Jacques, Paul F %A Lamon-Fava, Stefania %A Richardson, Kris %A Saxena, Richa %A Scheer, Frank A J L %A Kovanen, Leena %A Bartz, Traci M %A Perälä, Mia-Maria %A Jonsson, Anna %A Frazier-Wood, Alexis C %A Kalafati, Ioanna-Panagiota %A Mikkilä, Vera %A Partonen, Timo %A Lemaitre, Rozenn N %A Lahti, Jari %A Hernandez, Dena G %A Toft, Ulla %A Johnson, W Craig %A Kanoni, Stavroula %A Raitakari, Olli T %A Perola, Markus %A Psaty, Bruce M %A Ferrucci, Luigi %A Grarup, Niels %A Highland, Heather M %A Rallidis, Loukianos %A Kähönen, Mika %A Havulinna, Aki S %A Siscovick, David S %A Räikkönen, Katri %A Jørgensen, Torben %A Rotter, Jerome I %A Deloukas, Panos %A Viikari, Jorma S A %A Mozaffarian, Dariush %A Linneberg, Allan %A Seppälä, Ilkka %A Hansen, Torben %A Salomaa, Veikko %A Gharib, Sina A %A Eriksson, Johan G %A Bandinelli, Stefania %A Pedersen, Oluf %A Rich, Stephen S %A Dedoussis, George %A Lehtimäki, Terho %A Ordovas, Jose M %K Adult %K Body Mass Index %K CLOCK Proteins %K Cohort Studies %K Cross-Sectional Studies %K Diet %K Dietary Proteins %K Energy Intake %K European Continental Ancestry Group %K Fatty Acids, Unsaturated %K Female %K Gene-Environment Interaction %K Genetic Predisposition to Disease %K Humans %K Male %K Middle Aged %K Obesity %K Polymorphism, Single Nucleotide %K Sleep %K Young Adult %X

BACKGROUND: Short sleep duration has been associated with greater risks of obesity, hypertension, diabetes, and cardiovascular disease. Also, common genetic variants in the human Circadian Locomotor Output Cycles Kaput (CLOCK) show associations with ghrelin and total energy intake.

OBJECTIVES: We examined associations between habitual sleep duration, body mass index (BMI), and macronutrient intake and assessed whether CLOCK variants modify these associations.

DESIGN: We conducted inverse-variance weighted, fixed-effect meta-analyses of results of adjusted associations of sleep duration and BMI and macronutrient intake as percentages of total energy as well as interactions with CLOCK variants from 9 cohort studies including up to 14,906 participants of European descent from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium.

RESULTS: We observed a significant association between sleep duration and lower BMI (β ± SE = 0.16 ± 0.04, P < 0.0001) in the overall sample; however, associations between sleep duration and relative macronutrient intake were evident in age- and sex-stratified analyses only. We observed a significant association between sleep duration and lower saturated fatty acid intake in younger (aged 20-64 y) adults (men: 0.11 ± 0.06%, P = 0.03; women: 0.10 ± 0.05%, P = 0.04) and with lower carbohydrate (-0.31 ± 0.12%, P < 0.01), higher total fat (0.18 ± 0.09%, P = 0.05), and higher PUFA (0.05 ± 0.02%, P = 0.02) intakes in older (aged 65-80 y) women. In addition, the following 2 nominally significant interactions were observed: between sleep duration and rs12649507 on PUFA intake and between sleep duration and rs6858749 on protein intake.

CONCLUSIONS: Our results indicate that longer habitual sleep duration is associated with lower BMI and age- and sex-specific favorable dietary behaviors. Differences in the relative intake of specific macronutrients associated with short sleep duration could, at least in part, explain previously reported associations between short sleep duration and chronic metabolic abnormalities. In addition, the influence of obesity-associated CLOCK variants on the association between sleep duration and macronutrient intake suggests that longer habitual sleep duration could ameliorate the genetic predisposition to obesity via a favorable dietary profile.

%B Am J Clin Nutr %V 101 %P 135-43 %8 2015 Jan %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/25527757?dopt=Abstract %R 10.3945/ajcn.114.095026 %0 Journal Article %J Am J Clin Nutr %D 2016 %T Interaction of methylation-related genetic variants with circulating fatty acids on plasma lipids: a meta-analysis of 7 studies and methylation analysis of 3 studies in the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. %A Ma, Yiyi %A Follis, Jack L %A Smith, Caren E %A Tanaka, Toshiko %A Manichaikul, Ani W %A Chu, Audrey Y %A Samieri, Cecilia %A Zhou, Xia %A Guan, Weihua %A Wang, Lu %A Biggs, Mary L %A Chen, Yii-der I %A Hernandez, Dena G %A Borecki, Ingrid %A Chasman, Daniel I %A Rich, Stephen S %A Ferrucci, Luigi %A Irvin, Marguerite Ryan %A Aslibekyan, Stella %A Zhi, Degui %A Tiwari, Hemant K %A Claas, Steven A %A Sha, Jin %A Kabagambe, Edmond K %A Lai, Chao-Qiang %A Parnell, Laurence D %A Lee, Yu-Chi %A Amouyel, Philippe %A Lambert, Jean-Charles %A Psaty, Bruce M %A King, Irena B %A Mozaffarian, Dariush %A McKnight, Barbara %A Bandinelli, Stefania %A Tsai, Michael Y %A Ridker, Paul M %A Ding, Jingzhong %A Mstat, Kurt Lohmant %A Liu, Yongmei %A Sotoodehnia, Nona %A Barberger-Gateau, Pascale %A Steffen, Lyn M %A Siscovick, David S %A Absher, Devin %A Arnett, Donna K %A Ordovas, Jose M %A Lemaitre, Rozenn N %K Apolipoproteins E %K ATP Binding Cassette Transporter 1 %K Cholesterol, HDL %K Cohort Studies %K Diet %K DNA Methylation %K Eicosapentaenoic Acid %K Epigenesis, Genetic %K Fatty Acids %K Gene Expression Regulation %K Humans %K Lipids %K Polymorphism, Single Nucleotide %K Promoter Regions, Genetic %K Triglycerides %X

BACKGROUND: DNA methylation is influenced by diet and single nucleotide polymorphisms (SNPs), and methylation modulates gene expression.

OBJECTIVE: We aimed to explore whether the gene-by-diet interactions on blood lipids act through DNA methylation.

DESIGN: We selected 7 SNPs on the basis of predicted relations in fatty acids, methylation, and lipids. We conducted a meta-analysis and a methylation and mediation analysis with the use of data from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium and the ENCODE (Encyclopedia of DNA Elements) consortium.

RESULTS: On the basis of the meta-analysis of 7 cohorts in the CHARGE consortium, higher plasma HDL cholesterol was associated with fewer C alleles at ATP-binding cassette subfamily A member 1 (ABCA1) rs2246293 (β = -0.6 mg/dL, P = 0.015) and higher circulating eicosapentaenoic acid (EPA) (β = 3.87 mg/dL, P = 5.62 × 10(21)). The difference in HDL cholesterol associated with higher circulating EPA was dependent on genotypes at rs2246293, and it was greater for each additional C allele (β = 1.69 mg/dL, P = 0.006). In the GOLDN (Genetics of Lipid Lowering Drugs and Diet Network) study, higher ABCA1 promoter cg14019050 methylation was associated with more C alleles at rs2246293 (β = 8.84%, P = 3.51 × 10(18)) and lower circulating EPA (β = -1.46%, P = 0.009), and the mean difference in methylation of cg14019050 that was associated with higher EPA was smaller with each additional C allele of rs2246293 (β = -2.83%, P = 0.007). Higher ABCA1 cg14019050 methylation was correlated with lower ABCA1 expression (r = -0.61, P = 0.009) in the ENCODE consortium and lower plasma HDL cholesterol in the GOLDN study (r = -0.12, P = 0.0002). An additional mediation analysis was meta-analyzed across the GOLDN study, Cardiovascular Health Study, and the Multi-Ethnic Study of Atherosclerosis. Compared with the model without the adjustment of cg14019050 methylation, the model with such adjustment provided smaller estimates of the mean plasma HDL cholesterol concentration in association with both the rs2246293 C allele and EPA and a smaller difference by rs2246293 genotypes in the EPA-associated HDL cholesterol. However, the differences between 2 nested models were NS (P > 0.05).

CONCLUSION: We obtained little evidence that the gene-by-fatty acid interactions on blood lipids act through DNA methylation.

%B Am J Clin Nutr %V 103 %P 567-78 %8 2016 Feb %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/26791180?dopt=Abstract %R 10.3945/ajcn.115.112987 %0 Journal Article %J J Lipid Res %D 2017 %T Discovery and fine-mapping of loci associated with monounsaturated fatty acids through trans-ethnic meta-analysis in Chinese and European populations. %A Hu, Yao %A Tanaka, Toshiko %A Zhu, Jingwen %A Guan, Weihua %A Wu, Jason H Y %A Psaty, Bruce M %A McKnight, Barbara %A King, Irena B %A Sun, Qi %A Richard, Melissa %A Manichaikul, Ani %A Frazier-Wood, Alexis C %A Kabagambe, Edmond K %A Hopkins, Paul N %A Ordovas, Jose M %A Ferrucci, Luigi %A Bandinelli, Stefania %A Arnett, Donna K %A Chen, Yii-der I %A Liang, Shuang %A Siscovick, David S %A Tsai, Michael Y %A Rich, Stephen S %A Fornage, Myriam %A Hu, Frank B %A Rimm, Eric B %A Jensen, Majken K %A Lemaitre, Rozenn N %A Mozaffarian, Dariush %A Steffen, Lyn M %A Morris, Andrew P %A Li, Huaixing %A Lin, Xu %X

Monounsaturated fatty acids (MUFAs) are unsaturated fatty acids with one double bond and are derived from endogenous synthesis and dietary intake. Accumulating evidence has suggested that plasma and erythrocyte MUFA levels were associated with cardiometabolic disorders including cardiovascular disease (CVD), type 2 diabetes (T2D) and metabolic syndrome (MS). Previous genome-wide association studies (GWAS) have identified seven loci for plasma and erythrocyte palmitoleic acid and oleic acid levels in populations of European origin. To identify additional MUFA-associated loci and the potential causal variant at each locus, we performed ethnic-specific GWAS meta-analyses and trans-ethnic meta-analyses in over 15,000 participants of Chinese- and European-ancestry. We identified novel genome-wide significant associations for vaccenic acid at FADS1/2 and PKD2L1 [log10(Bayes factor)>=8.07] and for gondoic acid at FADS1/2 and GCKR [log10(Bayes factor)>=61619;6.22], and also observed improved fine-mapping resolutions at FADS1/2 and GCKR loci. The greatest improvement was observed at GCKR, where the number of variants in the 99% credible set was reduced from 16 (covering ~95kb) to five (covering ~20kb, including a missense variant rs1260326) after trans-ethnic meta-analysis. We also confirmed the previously reported associations of PKD2L1, FADS1/2, GCKR and HIF1AN with palmitoleic acid and of FADS1/2 and LPCAT3 with oleic acid in the Chinese-specific GWAS and trans-ethnic meta-analyses. Pathway-based analyses suggested that the identified loci were enriched in unsaturated fatty acids metabolism and signaling pathways. Our findings provided novel insight into the genetic basis relevant to MUFA metabolism and biology.

%B J Lipid Res %8 2017 Mar 15 %G eng %R 10.1194/jlr.P071860 %0 Journal Article %J Nat Genet %D 2017 %T Exome-wide association study of plasma lipids in >300,000 individuals. %A Liu, Dajiang J %A Peloso, Gina M %A Yu, Haojie %A Butterworth, Adam S %A Wang, Xiao %A Mahajan, Anubha %A Saleheen, Danish %A Emdin, Connor %A Alam, Dewan %A Alves, Alexessander Couto %A Amouyel, Philippe %A Di Angelantonio, Emanuele %A Arveiler, Dominique %A Assimes, Themistocles L %A Auer, Paul L %A Baber, Usman %A Ballantyne, Christie M %A Bang, Lia E %A Benn, Marianne %A Bis, Joshua C %A Boehnke, Michael %A Boerwinkle, Eric %A Bork-Jensen, Jette %A Bottinger, Erwin P %A Brandslund, Ivan %A Brown, Morris %A Busonero, Fabio %A Caulfield, Mark J %A Chambers, John C %A Chasman, Daniel I %A Chen, Y Eugene %A Chen, Yii-Der Ida %A Chowdhury, Rajiv %A Christensen, Cramer %A Chu, Audrey Y %A Connell, John M %A Cucca, Francesco %A Cupples, L Adrienne %A Damrauer, Scott M %A Davies, Gail %A Deary, Ian J %A Dedoussis, George %A Denny, Joshua C %A Dominiczak, Anna %A Dubé, Marie-Pierre %A Ebeling, Tapani %A Eiriksdottir, Gudny %A Esko, Tõnu %A Farmaki, Aliki-Eleni %A Feitosa, Mary F %A Ferrario, Marco %A Ferrieres, Jean %A Ford, Ian %A Fornage, Myriam %A Franks, Paul W %A Frayling, Timothy M %A Frikke-Schmidt, Ruth %A Fritsche, Lars G %A Frossard, Philippe %A Fuster, Valentin %A Ganesh, Santhi K %A Gao, Wei %A Garcia, Melissa E %A Gieger, Christian %A Giulianini, Franco %A Goodarzi, Mark O %A Grallert, Harald %A Grarup, Niels %A Groop, Leif %A Grove, Megan L %A Gudnason, Vilmundur %A Hansen, Torben %A Harris, Tamara B %A Hayward, Caroline %A Hirschhorn, Joel N %A Holmen, Oddgeir L %A Huffman, Jennifer %A Huo, Yong %A Hveem, Kristian %A Jabeen, Sehrish %A Jackson, Anne U %A Jakobsdottir, Johanna %A Jarvelin, Marjo-Riitta %A Jensen, Gorm B %A Jørgensen, Marit E %A Jukema, J Wouter %A Justesen, Johanne M %A Kamstrup, Pia R %A Kanoni, Stavroula %A Karpe, Fredrik %A Kee, Frank %A Khera, Amit V %A Klarin, Derek %A Koistinen, Heikki A %A Kooner, Jaspal S %A Kooperberg, Charles %A Kuulasmaa, Kari %A Kuusisto, Johanna %A Laakso, Markku %A Lakka, Timo %A Langenberg, Claudia %A Langsted, Anne %A Launer, Lenore J %A Lauritzen, Torsten %A Liewald, David C M %A Lin, Li An %A Linneberg, Allan %A Loos, Ruth J F %A Lu, Yingchang %A Lu, Xiangfeng %A Mägi, Reedik %A Mälarstig, Anders %A Manichaikul, Ani %A Manning, Alisa K %A Mäntyselkä, Pekka %A Marouli, Eirini %A Masca, Nicholas G D %A Maschio, Andrea %A Meigs, James B %A Melander, Olle %A Metspalu, Andres %A Morris, Andrew P %A Morrison, Alanna C %A Mulas, Antonella %A Müller-Nurasyid, Martina %A Munroe, Patricia B %A Neville, Matt J %A Nielsen, Jonas B %A Nielsen, Sune F %A Nordestgaard, Børge G %A Ordovas, Jose M %A Mehran, Roxana %A O'Donnell, Christoper J %A Orho-Melander, Marju %A Molony, Cliona M %A Muntendam, Pieter %A Padmanabhan, Sandosh %A Palmer, Colin N A %A Pasko, Dorota %A Patel, Aniruddh P %A Pedersen, Oluf %A Perola, Markus %A Peters, Annette %A Pisinger, Charlotta %A Pistis, Giorgio %A Polasek, Ozren %A Poulter, Neil %A Psaty, Bruce M %A Rader, Daniel J %A Rasheed, Asif %A Rauramaa, Rainer %A Reilly, Dermot F %A Reiner, Alex P %A Renstrom, Frida %A Rich, Stephen S %A Ridker, Paul M %A Rioux, John D %A Robertson, Neil R %A Roden, Dan M %A Rotter, Jerome I %A Rudan, Igor %A Salomaa, Veikko %A Samani, Nilesh J %A Sanna, Serena %A Sattar, Naveed %A Schmidt, Ellen M %A Scott, Robert A %A Sever, Peter %A Sevilla, Raquel S %A Shaffer, Christian M %A Sim, Xueling %A Sivapalaratnam, Suthesh %A Small, Kerrin S %A Smith, Albert V %A Smith, Blair H %A Somayajula, Sangeetha %A Southam, Lorraine %A Spector, Timothy D %A Speliotes, Elizabeth K %A Starr, John M %A Stirrups, Kathleen E %A Stitziel, Nathan %A Strauch, Konstantin %A Stringham, Heather M %A Surendran, Praveen %A Tada, Hayato %A Tall, Alan R %A Tang, Hua %A Tardif, Jean-Claude %A Taylor, Kent D %A Trompet, Stella %A Tsao, Philip S %A Tuomilehto, Jaakko %A Tybjaerg-Hansen, Anne %A van Zuydam, Natalie R %A Varbo, Anette %A Varga, Tibor V %A Virtamo, Jarmo %A Waldenberger, Melanie %A Wang, Nan %A Wareham, Nick J %A Warren, Helen R %A Weeke, Peter E %A Weinstock, Joshua %A Wessel, Jennifer %A Wilson, James G %A Wilson, Peter W F %A Xu, Ming %A Yaghootkar, Hanieh %A Young, Robin %A Zeggini, Eleftheria %A Zhang, He %A Zheng, Neil S %A Zhang, Weihua %A Zhang, Yan %A Zhou, Wei %A Zhou, Yanhua %A Zoledziewska, Magdalena %A Howson, Joanna M M %A Danesh, John %A McCarthy, Mark I %A Cowan, Chad A %A Abecasis, Goncalo %A Deloukas, Panos %A Musunuru, Kiran %A Willer, Cristen J %A Kathiresan, Sekar %K Coronary Artery Disease %K Diabetes Mellitus, Type 2 %K Exome %K Genetic Association Studies %K Genetic Predisposition to Disease %K Genetic Variation %K Genotype %K Humans %K Lipids %K Macular Degeneration %K Phenotype %K Risk Factors %X

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

%B Nat Genet %V 49 %P 1758-1766 %8 2017 Dec %G eng %N 12 %R 10.1038/ng.3977 %0 Journal Article %J Mol Nutr Food Res %D 2017 %T Genome-Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent. %A Smith, Caren E %A Follis, Jack L %A Dashti, Hassan S %A Tanaka, Toshiko %A Graff, Mariaelisa %A Fretts, Amanda M %A Kilpeläinen, Tuomas O %A Wojczynski, Mary K %A Richardson, Kris %A Nalls, Mike A %A Schulz, Christina-Alexandra %A Liu, Yongmei %A Frazier-Wood, Alexis C %A van Eekelen, Esther %A Wang, Carol %A de Vries, Paul S %A Mikkilä, Vera %A Rohde, Rebecca %A Psaty, Bruce M %A Hansen, Torben %A Feitosa, Mary F %A Lai, Chao-Qiang %A Houston, Denise K %A Ferruci, Luigi %A Ericson, Ulrika %A Wang, Zhe %A de Mutsert, Renée %A Oddy, Wendy H %A de Jonge, Ester A L %A Seppälä, Ilkka %A Justice, Anne E %A Lemaitre, Rozenn N %A Sørensen, Thorkild I A %A Province, Michael A %A Parnell, Laurence D %A Garcia, Melissa E %A Bandinelli, Stefania %A Orho-Melander, Marju %A Rich, Stephen S %A Rosendaal, Frits R %A Pennell, Craig E %A Kiefte-de Jong, Jessica C %A Kähönen, Mika %A Young, Kristin L %A Pedersen, Oluf %A Aslibekyan, Stella %A Rotter, Jerome I %A Mook-Kanamori, Dennis O %A Zillikens, M Carola %A Raitakari, Olli T %A North, Kari E %A Overvad, Kim %A Arnett, Donna K %A Hofman, Albert %A Lehtimäki, Terho %A Tjønneland, Anne %A Uitterlinden, André G %A Rivadeneira, Fernando %A Franco, Oscar H %A German, J Bruce %A Siscovick, David S %A Cupples, L Adrienne %A Ordovas, Jose M %X

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' of LINC00333) was replicated (p-interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p-interaction = 7.36 × 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.

%B Mol Nutr Food Res %8 2017 Sep 21 %G eng %R 10.1002/mnfr.201700347 %0 Journal Article %J J Clin Endocrinol Metab %D 2018 %T Trans-ethnic Evaluation Identifies Novel Low Frequency Loci Associated with 25-Hydroxyvitamin D Concentrations. %A Hong, Jaeyoung %A Hatchell, Kathryn E %A Bradfield, Jonathan P %A Andrew, Bjonnes %A Alessandra, Chesi %A Chao-Qiang, Lai %A Langefeld, Carl D %A Lu, Lingyi %A Lu, Yingchang %A Lutsey, Pamela L %A Musani, Solomon K %A Nalls, Mike A %A Robinson-Cohen, Cassianne %A Roizen, Jeffery D %A Saxena, Richa %A Tucker, Katherine L %A Ziegler, Julie T %A Arking, Dan E %A Bis, Joshua C %A Boerwinkle, Eric %A Bottinger, Erwin P %A Bowden, Donald W %A Gilsanz, Vincente %A Houston, Denise K %A Kalkwarf, Heidi J %A Kelly, Andrea %A Lappe, Joan M %A Liu, Yongmei %A Michos, Erin D %A Oberfield, Sharon E %A Palmer, Nicholette D %A Rotter, Jerome I %A Sapkota, Bishwa %A Shepherd, John A %A Wilson, James G %A Basu, Saonli %A de Boer, Ian H %A Divers, Jasmin %A Freedman, Barry I %A Grant, Struan F A %A Hakanarson, Hakon %A Harris, Tamara B %A Kestenbaum, Bryan R %A Kritchevsky, Stephen B %A Loos, Ruth J F %A Norris, Jill M %A Norwood, Arnita F %A Ordovas, Jose M %A Pankow, James S %A Psaty, Bruce M %A Sanhgera, Dharambir K %A Wagenknecht, Lynne E %A Zemel, Babette S %A Meigs, James %A Dupuis, Josée %A Florez, Jose C %A Wang, Thomas %A Liu, Ching-Ti %A Engelman, Corinne D %A Billings, Liana K %X

Context: Vitamin D inadequacy is common in the adult population of the United States. While the genetic determinants underlying vitamin D inadequacy have been studied in people of European ancestry, less is known in Hispanic or African ancestry populations.

Objective: The TRANSCEN-D (TRANS-ethniC Evaluation of vitamiN D GWAS) consortium was assembled to replicate genetic associations with 25-hydroxyvitamin D (25(OH)D) concentrations from the meta-analyses of European ancestry (SUNLIGHT) and to identify novel genetic variants related to vitamin D concentrations in African and Hispanic ancestries.

Design: Ancestry-specific (Hispanic and African) and trans-ethnic (Hispanic, African and European) meta-analyses were performed using the METAL software.

Patients or Other Participants: In total, 8,541 African-American and 3,485 Hispanic-American (from North America) participants from twelve cohorts, and 16,124 European participants from SUNLIGHT were included in the study.

Main Outcome Measure(s): Blood concentrations of 25(OH)D were measured for all participants.

Results: Ancestry-specific analyses in African and Hispanic Americans replicated SNPs in GC (2 and 4 SNPs, respectively). A potentially novel SNP (rs79666294) near the KIF4B gene was identified in the African-American cohort. Trans-ethnic evaluation replicated GC and DHCR7 region SNPs. Additionally, the trans-ethnic analyses revealed novel SNPs rs719700 and rs1410656 near the ANO6/ARID2 and HTR2A genes, respectively.

Conclusions: Ancestry-specific and trans-ethnic GWAS of 25(OH)D confirmed findings in GC and DHCR7 for African and Hispanic American samples and revealed novel findings near KIF4B, ANO6/ARID2, and HTR2A. The biological mechanisms that link these regions with 25(OH)D metabolism require further investigation.

%B J Clin Endocrinol Metab %8 2018 Jan 09 %G eng %R 10.1210/jc.2017-01802 %0 Journal Article %J Eur J Epidemiol %D 2020 %T Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood. %A Zheng, Yan %A Huang, Tao %A Wang, Tiange %A Mei, Zhendong %A Sun, Zhonghan %A Zhang, Tao %A Ellervik, Christina %A Chai, Jin-Fang %A Sim, Xueling %A van Dam, Rob M %A Tai, E-Shyong %A Koh, Woon-Puay %A Dorajoo, Rajkumar %A Saw, Seang-Mei %A Sabanayagam, Charumathi %A Wong, Tien Yin %A Gupta, Preeti %A Rossing, Peter %A Ahluwalia, Tarunveer S %A Vinding, Rebecca K %A Bisgaard, Hans %A Bønnelykke, Klaus %A Wang, Yujie %A Graff, Mariaelisa %A Voortman, Trudy %A van Rooij, Frank J A %A Hofman, Albert %A van Heemst, Diana %A Noordam, Raymond %A Estampador, Angela C %A Varga, Tibor V %A Enzenbach, Cornelia %A Scholz, Markus %A Thiery, Joachim %A Burkhardt, Ralph %A Orho-Melander, Marju %A Schulz, Christina-Alexandra %A Ericson, Ulrika %A Sonestedt, Emily %A Kubo, Michiaki %A Akiyama, Masato %A Zhou, Ang %A Kilpeläinen, Tuomas O %A Hansen, Torben %A Kleber, Marcus E %A Delgado, Graciela %A McCarthy, Mark %A Lemaitre, Rozenn N %A Felix, Janine F %A Jaddoe, Vincent W V %A Wu, Ying %A Mohlke, Karen L %A Lehtimäki, Terho %A Wang, Carol A %A Pennell, Craig E %A Schunkert, Heribert %A Kessler, Thorsten %A Zeng, Lingyao %A Willenborg, Christina %A Peters, Annette %A Lieb, Wolfgang %A Grote, Veit %A Rzehak, Peter %A Koletzko, Berthold %A Erdmann, Jeanette %A Munz, Matthias %A Wu, Tangchun %A He, Meian %A Yu, Caizheng %A Lecoeur, Cécile %A Froguel, Philippe %A Corella, Dolores %A Moreno, Luis A %A Lai, Chao-Qiang %A Pitkänen, Niina %A Boreham, Colin A %A Ridker, Paul M %A Rosendaal, Frits R %A de Mutsert, Renée %A Power, Chris %A Paternoster, Lavinia %A Sørensen, Thorkild I A %A Tjønneland, Anne %A Overvad, Kim %A Djoussé, Luc %A Rivadeneira, Fernando %A Lee, Nanette R %A Raitakari, Olli T %A Kähönen, Mika %A Viikari, Jorma %A Langhendries, Jean-Paul %A Escribano, Joaquin %A Verduci, Elvira %A Dedoussis, George %A König, Inke %A Balkau, Beverley %A Coltell, Oscar %A Dallongeville, Jean %A Meirhaeghe, Aline %A Amouyel, Philippe %A Gottrand, Frédéric %A Pahkala, Katja %A Niinikoski, Harri %A Hyppönen, Elina %A März, Winfried %A Mackey, David A %A Gruszfeld, Dariusz %A Tucker, Katherine L %A Fumeron, Frédéric %A Estruch, Ramon %A Ordovas, Jose M %A Arnett, Donna K %A Mook-Kanamori, Dennis O %A Mozaffarian, Dariush %A Psaty, Bruce M %A North, Kari E %A Chasman, Daniel I %A Qi, Lu %X

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.

%B Eur J Epidemiol %V 35 %P 685-697 %8 2020 Jul %G eng %N 7 %R 10.1007/s10654-020-00638-z