%0 Journal Article %J PLoS Genet %D 2009 %T NRXN3 is a novel locus for waist circumference: a genome-wide association study from the CHARGE Consortium. %A Heard-Costa, Nancy L %A Zillikens, M Carola %A Monda, Keri L %A Johansson, Asa %A Harris, Tamara B %A Fu, Mao %A Haritunians, Talin %A Feitosa, Mary F %A Aspelund, Thor %A Eiriksdottir, Gudny %A Garcia, Melissa %A Launer, Lenore J %A Smith, Albert V %A Mitchell, Braxton D %A McArdle, Patrick F %A Shuldiner, Alan R %A Bielinski, Suzette J %A Boerwinkle, Eric %A Brancati, Fred %A Demerath, Ellen W %A Pankow, James S %A Arnold, Alice M %A Chen, Yii-Der Ida %A Glazer, Nicole L %A McKnight, Barbara %A Psaty, Bruce M %A Rotter, Jerome I %A Amin, Najaf %A Campbell, Harry %A Gyllensten, Ulf %A Pattaro, Cristian %A Pramstaller, Peter P %A Rudan, Igor %A Struchalin, Maksim %A Vitart, Veronique %A Gao, Xiaoyi %A Kraja, Aldi %A Province, Michael A %A Zhang, Qunyuan %A Atwood, Larry D %A Dupuis, Josée %A Hirschhorn, Joel N %A Jaquish, Cashell E %A O'Donnell, Christopher J %A Vasan, Ramachandran S %A White, Charles C %A Aulchenko, Yurii S %A Estrada, Karol %A Hofman, Albert %A Rivadeneira, Fernando %A Uitterlinden, André G %A Witteman, Jacqueline C M %A Oostra, Ben A %A Kaplan, Robert C %A Gudnason, Vilmundur %A O'Connell, Jeffrey R %A Borecki, Ingrid B %A van Duijn, Cornelia M %A Cupples, L Adrienne %A Fox, Caroline S %A North, Kari E %K Aged %K Body Mass Index %K Cohort Studies %K European Continental Ancestry Group %K Female %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Male %K Middle Aged %K Nerve Tissue Proteins %K Obesity %K Polymorphism, Single Nucleotide %K Waist Circumference %X

Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4x10(-7))]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3x10(-8) for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4x10(-6), 0.024 z-score units (0.10 kg/m(2)) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07-1.19; p = 3.2x10(-5) per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity.

%B PLoS Genet %V 5 %P e1000539 %8 2009 Jun %G eng %N 6 %1 http://www.ncbi.nlm.nih.gov/pubmed/19557197?dopt=Abstract %R 10.1371/journal.pgen.1000539 %0 Journal Article %J Lancet %D 2010 %T Common genetic determinants of vitamin D insufficiency: a genome-wide association study. %A Wang, Thomas J %A Zhang, Feng %A Richards, J Brent %A Kestenbaum, Bryan %A van Meurs, Joyce B %A Berry, Diane %A Kiel, Douglas P %A Streeten, Elizabeth A %A Ohlsson, Claes %A Koller, Daniel L %A Peltonen, Leena %A Cooper, Jason D %A O'Reilly, Paul F %A Houston, Denise K %A Glazer, Nicole L %A Vandenput, Liesbeth %A Peacock, Munro %A Shi, Julia %A Rivadeneira, Fernando %A McCarthy, Mark I %A Anneli, Pouta %A de Boer, Ian H %A Mangino, Massimo %A Kato, Bernet %A Smyth, Deborah J %A Booth, Sarah L %A Jacques, Paul F %A Burke, Greg L %A Goodarzi, Mark %A Cheung, Ching-Lung %A Wolf, Myles %A Rice, Kenneth %A Goltzman, David %A Hidiroglou, Nick %A Ladouceur, Martin %A Wareham, Nicholas J %A Hocking, Lynne J %A Hart, Deborah %A Arden, Nigel K %A Cooper, Cyrus %A Malik, Suneil %A Fraser, William D %A Hartikainen, Anna-Liisa %A Zhai, Guangju %A Macdonald, Helen M %A Forouhi, Nita G %A Loos, Ruth J F %A Reid, David M %A Hakim, Alan %A Dennison, Elaine %A Liu, Yongmei %A Power, Chris %A Stevens, Helen E %A Jaana, Laitinen %A Vasan, Ramachandran S %A Soranzo, Nicole %A Bojunga, Jörg %A Psaty, Bruce M %A Lorentzon, Mattias %A Foroud, Tatiana %A Harris, Tamara B %A Hofman, Albert %A Jansson, John-Olov %A Cauley, Jane A %A Uitterlinden, André G %A Gibson, Quince %A Jarvelin, Marjo-Riitta %A Karasik, David %A Siscovick, David S %A Econs, Michael J %A Kritchevsky, Stephen B %A Florez, Jose C %A Todd, John A %A Dupuis, Josée %A Hyppönen, Elina %A Spector, Timothy D %K Canada %K Chromosomes, Human, Pair 11 %K Chromosomes, Human, Pair 4 %K Cohort Studies %K Dietary Supplements %K Europe %K European Continental Ancestry Group %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Heterozygote %K Homozygote %K Humans %K Immunoassay %K International Cooperation %K Linkage Disequilibrium %K Polymorphism, Single Nucleotide %K Seasons %K United States %K Vitamin D %K Vitamin D Deficiency %X

BACKGROUND: Vitamin D is crucial for maintenance of musculoskeletal health, and might also have a role in extraskeletal tissues. Determinants of circulating 25-hydroxyvitamin D concentrations include sun exposure and diet, but high heritability suggests that genetic factors could also play a part. We aimed to identify common genetic variants affecting vitamin D concentrations and risk of insufficiency.

METHODS: We undertook a genome-wide association study of 25-hydroxyvitamin D concentrations in 33 996 individuals of European descent from 15 cohorts. Five epidemiological cohorts were designated as discovery cohorts (n=16 125), five as in-silico replication cohorts (n=9367), and five as de-novo replication cohorts (n=8504). 25-hydroxyvitamin D concentrations were measured by radioimmunoassay, chemiluminescent assay, ELISA, or mass spectrometry. Vitamin D insufficiency was defined as concentrations lower than 75 nmol/L or 50 nmol/L. We combined results of genome-wide analyses across cohorts using Z-score-weighted meta-analysis. Genotype scores were constructed for confirmed variants.

FINDINGS: Variants at three loci reached genome-wide significance in discovery cohorts for association with 25-hydroxyvitamin D concentrations, and were confirmed in replication cohorts: 4p12 (overall p=1.9x10(-109) for rs2282679, in GC); 11q12 (p=2.1x10(-27) for rs12785878, near DHCR7); and 11p15 (p=3.3x10(-20) for rs10741657, near CYP2R1). Variants at an additional locus (20q13, CYP24A1) were genome-wide significant in the pooled sample (p=6.0x10(-10) for rs6013897). Participants with a genotype score (combining the three confirmed variants) in the highest quartile were at increased risk of having 25-hydroxyvitamin D concentrations lower than 75 nmol/L (OR 2.47, 95% CI 2.20-2.78, p=2.3x10(-48)) or lower than 50 nmol/L (1.92, 1.70-2.16, p=1.0x10(-26)) compared with those in the lowest quartile.

INTERPRETATION: Variants near genes involved in cholesterol synthesis, hydroxylation, and vitamin D transport affect vitamin D status. Genetic variation at these loci identifies individuals who have substantially raised risk of vitamin D insufficiency.

FUNDING: Full funding sources listed at end of paper (see Acknowledgments).

%B Lancet %V 376 %P 180-8 %8 2010 Jul 17 %G eng %N 9736 %1 http://www.ncbi.nlm.nih.gov/pubmed/20541252?dopt=Abstract %R 10.1016/S0140-6736(10)60588-0 %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 Hum Mol Genet %D 2010 %T Large-scale genomic studies reveal central role of ABO in sP-selectin and sICAM-1 levels. %A Barbalic, Maja %A Dupuis, Josée %A Dehghan, Abbas %A Bis, Joshua C %A Hoogeveen, Ron C %A Schnabel, Renate B %A Nambi, Vijay %A Bretler, Monique %A Smith, Nicholas L %A Peters, Annette %A Lu, Chen %A Tracy, Russell P %A Aleksic, Nena %A Heeriga, Jan %A Keaney, John F %A Rice, Kenneth %A Lip, Gregory Y H %A Vasan, Ramachandran S %A Glazer, Nicole L %A Larson, Martin G %A Uitterlinden, André G %A Yamamoto, Jennifer %A Durda, Peter %A Haritunians, Talin %A Psaty, Bruce M %A Boerwinkle, Eric %A Hofman, Albert %A Koenig, Wolfgang %A Jenny, Nancy S %A Witteman, Jacqueline C %A Ballantyne, Christie %A Benjamin, Emelia J %K ABO Blood-Group System %K Blood Platelets %K Enzyme-Linked Immunosorbent Assay %K European Continental Ancestry Group %K Fluorescence %K Genome-Wide Association Study %K Humans %K Intercellular Adhesion Molecule-1 %K P-Selectin %X

P-selectin and intercellular adhesion molecule-1 (ICAM-1) participate in inflammatory processes by promoting adhesion of leukocytes to vascular wall endothelium. Their soluble levels have been associated with adverse cardiovascular events. To identify loci affecting soluble levels of P-selectin (sP-selectin) and ICAM-1 (sICAM-1), we performed a genome-wide association study in a sample of 4115 (sP-selectin) and 9813 (sICAM-1) individuals of European ancestry as a part of The Cohorts for Heart and Aging Research in Genome Epidemiology consortium. The most significant SNP association for sP-selectin was within the SELP gene (rs6136, P = 4.05 x 10(-61)) and for sICAM-1 levels within the ICAM-1 gene (rs3093030, P = 3.53 x 10(-23)). Both sP-selectin and sICAM-1 were associated with ABO gene variants (rs579459, P = 1.86 x 10(-41) and rs649129, P = 1.22 x 10(-15), respectively) and in both cases the observed associations could be accounted for by the A1 allele of the ABO blood group. The absence of an association between ABO blood group and platelet-bound P-selectin levels in an independent subsample (N = 1088) from the ARIC study, suggests that the ABO blood group may influence cleavage of the P-selectin protein from the cell surface or clearance from the circulation, rather than its production and cellular presentation. These results provide new insights into adhesion molecule biology.

%B Hum Mol Genet %V 19 %P 1863-72 %8 2010 May 01 %G eng %N 9 %1 http://www.ncbi.nlm.nih.gov/pubmed/20167578?dopt=Abstract %R 10.1093/hmg/ddq061 %0 Journal Article %J Nat Genet %D 2010 %T New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. %A Dupuis, Josée %A Langenberg, Claudia %A Prokopenko, Inga %A Saxena, Richa %A Soranzo, Nicole %A Jackson, Anne U %A Wheeler, Eleanor %A Glazer, Nicole L %A Bouatia-Naji, Nabila %A Gloyn, Anna L %A Lindgren, Cecilia M %A Mägi, Reedik %A Morris, Andrew P %A Randall, Joshua %A Johnson, Toby %A Elliott, Paul %A Rybin, Denis %A Thorleifsson, Gudmar %A Steinthorsdottir, Valgerdur %A Henneman, Peter %A Grallert, Harald %A Dehghan, Abbas %A Hottenga, Jouke Jan %A Franklin, Christopher S %A Navarro, Pau %A Song, Kijoung %A Goel, Anuj %A Perry, John R B %A Egan, Josephine M %A Lajunen, Taina %A Grarup, Niels %A Sparsø, Thomas %A Doney, Alex %A Voight, Benjamin F %A Stringham, Heather M %A Li, Man %A Kanoni, Stavroula %A Shrader, Peter %A Cavalcanti-Proença, Christine %A Kumari, Meena %A Qi, Lu %A Timpson, Nicholas J %A Gieger, Christian %A Zabena, Carina %A Rocheleau, Ghislain %A Ingelsson, Erik %A An, Ping %A O'Connell, Jeffrey %A Luan, Jian'an %A Elliott, Amanda %A McCarroll, Steven A %A Payne, Felicity %A Roccasecca, Rosa Maria %A Pattou, François %A Sethupathy, Praveen %A Ardlie, Kristin %A Ariyurek, Yavuz %A Balkau, Beverley %A Barter, Philip %A Beilby, John P %A Ben-Shlomo, Yoav %A Benediktsson, Rafn %A Bennett, Amanda J %A Bergmann, Sven %A Bochud, Murielle %A Boerwinkle, Eric %A Bonnefond, Amélie %A Bonnycastle, Lori L %A Borch-Johnsen, Knut %A Böttcher, Yvonne %A Brunner, Eric %A Bumpstead, Suzannah J %A Charpentier, Guillaume %A Chen, Yii-Der Ida %A Chines, Peter %A Clarke, Robert %A Coin, Lachlan J M %A Cooper, Matthew N %A Cornelis, Marilyn %A Crawford, Gabe %A Crisponi, Laura %A Day, Ian N M %A de Geus, Eco J C %A Delplanque, Jerome %A Dina, Christian %A Erdos, Michael R %A Fedson, Annette C %A Fischer-Rosinsky, Antje %A Forouhi, Nita G %A Fox, Caroline S %A Frants, Rune %A Franzosi, Maria Grazia %A Galan, Pilar %A Goodarzi, Mark O %A Graessler, Jürgen %A Groves, Christopher J %A Grundy, Scott %A Gwilliam, Rhian %A Gyllensten, Ulf %A Hadjadj, Samy %A Hallmans, Göran %A Hammond, Naomi %A Han, Xijing %A Hartikainen, Anna-Liisa %A Hassanali, Neelam %A Hayward, Caroline %A Heath, Simon C %A Hercberg, Serge %A Herder, Christian %A Hicks, Andrew A %A Hillman, David R %A Hingorani, Aroon D %A Hofman, Albert %A Hui, Jennie %A Hung, Joe %A Isomaa, Bo %A Johnson, Paul R V %A Jørgensen, Torben %A Jula, Antti %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 Lyssenko, Valeriya %A Mahley, Robert %A Mangino, Massimo %A Manning, Alisa K %A Martínez-Larrad, María Teresa %A McAteer, Jarred B %A McCulloch, Laura J %A McPherson, Ruth %A Meisinger, Christa %A Melzer, David %A Meyre, David %A Mitchell, Braxton D %A Morken, Mario A %A Mukherjee, Sutapa %A Naitza, Silvia %A Narisu, Narisu %A Neville, Matthew J %A Oostra, Ben A %A Orrù, Marco %A Pakyz, Ruth %A Palmer, Colin N A %A Paolisso, Giuseppe %A Pattaro, Cristian %A Pearson, Daniel %A Peden, John F %A Pedersen, Nancy L %A Perola, Markus %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 Psaty, Bruce M %A Rathmann, Wolfgang %A Rayner, Nigel W %A Rice, Kenneth %A Ripatti, Samuli %A Rivadeneira, Fernando %A Roden, Michael %A Rolandsson, Olov %A Sandbaek, Annelli %A Sandhu, Manjinder %A Sanna, Serena %A Sayer, Avan Aihie %A Scheet, Paul %A Scott, Laura J %A Seedorf, Udo %A Sharp, Stephen J %A Shields, Beverley %A Sigurethsson, 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 Tanaka, Toshiko %A Thorand, Barbara %A Tichet, Jean %A Tönjes, Anke %A Tuomi, Tiinamaija %A Uitterlinden, André G %A van Dijk, Ko Willems %A van Hoek, Mandy %A Varma, Dhiraj %A Visvikis-Siest, Sophie %A Vitart, Veronique %A Vogelzangs, Nicole %A Waeber, Gérard %A Wagner, Peter J %A Walley, Andrew %A Walters, G Bragi %A Ward, Kim L %A Watkins, Hugh %A Weedon, Michael N %A Wild, Sarah H %A Willemsen, Gonneke %A Witteman, Jaqueline C M %A Yarnell, John W G %A Zeggini, Eleftheria %A Zelenika, Diana %A Zethelius, Björn %A Zhai, Guangju %A Zhao, Jing Hua %A Zillikens, M Carola %A Borecki, Ingrid B %A Loos, Ruth J F %A Meneton, Pierre %A Magnusson, Patrik K E %A Nathan, David M %A Williams, Gordon H %A Hattersley, Andrew T %A Silander, Kaisa %A Salomaa, Veikko %A Smith, George Davey %A Bornstein, Stefan R %A Schwarz, Peter %A Spranger, Joachim %A Karpe, Fredrik %A Shuldiner, Alan R %A Cooper, Cyrus %A Dedoussis, George V %A Serrano-Ríos, Manuel %A Morris, Andrew D %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 Pankow, James S %A Sampson, Michael J %A Kuusisto, Johanna %A Laakso, Markku %A Hansen, Torben %A Pedersen, Oluf %A Pramstaller, Peter Paul %A Wichmann, H Erich %A Illig, Thomas %A Rudan, Igor %A Wright, Alan F %A Stumvoll, Michael %A Campbell, Harry %A Wilson, James F %A Bergman, Richard N %A Buchanan, Thomas A %A Collins, Francis S %A Mohlke, Karen L %A Tuomilehto, Jaakko %A Valle, Timo T %A Altshuler, David %A Rotter, Jerome I %A Siscovick, David S %A Penninx, Brenda W J H %A Boomsma, Dorret I %A Deloukas, Panos %A Spector, Timothy D %A Frayling, Timothy M %A Ferrucci, Luigi %A Kong, Augustine %A Thorsteinsdottir, Unnur %A Stefansson, Kari %A van Duijn, Cornelia M %A Aulchenko, Yurii S %A Cao, Antonio %A Scuteri, Angelo %A Schlessinger, David %A Uda, Manuela %A Ruokonen, Aimo %A Jarvelin, Marjo-Riitta %A Waterworth, Dawn M %A Vollenweider, Peter %A Peltonen, Leena %A Mooser, Vincent %A Abecasis, Goncalo R %A Wareham, Nicholas J %A Sladek, Robert %A Froguel, Philippe %A Watanabe, Richard M %A Meigs, James B %A Groop, Leif %A Boehnke, Michael %A McCarthy, Mark I %A Florez, Jose C %A Barroso, Inês %K Adolescent %K Adult %K Alleles %K Blood Glucose %K Child %K Databases, Genetic %K Diabetes Mellitus, Type 2 %K DNA Copy Number Variations %K Fasting %K Gene Expression Regulation %K Genetic Loci %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Homeostasis %K Humans %K Meta-Analysis as Topic %K Polymorphism, Single Nucleotide %K Quantitative Trait Loci %K Quantitative Trait, Heritable %K Reproducibility of Results %X

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.

%B Nat Genet %V 42 %P 105-16 %8 2010 Feb %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/20081858?dopt=Abstract %R 10.1038/ng.520 %0 Journal Article %J PLoS Genet %D 2011 %T Genome-wide association analysis of soluble ICAM-1 concentration reveals novel associations at the NFKBIK, PNPLA3, RELA, and SH2B3 loci. %A Paré, Guillaume %A Ridker, Paul M %A Rose, Lynda %A Barbalic, Maja %A Dupuis, Josée %A Dehghan, Abbas %A Bis, Joshua C %A Benjamin, Emelia J %A Shiffman, Dov %A Parker, Alexander N %A Chasman, Daniel I %K ABO Blood-Group System %K Cohort Studies %K Female %K Gene Frequency %K Genetic Loci %K Genome, Human %K Genome-Wide Association Study %K Genotype %K Humans %K I-kappa B Kinase %K Intercellular Adhesion Molecule-1 %K Lipase %K Membrane Proteins %K Models, Genetic %K Multifactorial Inheritance %K Polymorphism, Single Nucleotide %K Proteins %K Transcription Factor RelA %X

Soluble ICAM-1 (sICAM-1) is an endothelium-derived inflammatory marker that has been associated with diverse conditions such as myocardial infarction, diabetes, stroke, and malaria. Despite evidence for a heritable component to sICAM-1 levels, few genetic loci have been identified so far. To comprehensively address this issue, we performed a genome-wide association analysis of sICAM-1 concentration in 22,435 apparently healthy women from the Women's Genome Health Study. While our results confirm the previously reported associations at the ABO and ICAM1 loci, four novel associations were identified in the vicinity of NFKBIK (rs3136642, P = 5.4 × 10(-9)), PNPLA3 (rs738409, P  =  5.8 × 10(-9)), RELA (rs1049728, P =  2.7 × 10(-16)), and SH2B3 (rs3184504, P =  2.9 × 10(-17)). Two loci, NFKBIB and RELA, are involved in NFKB signaling pathway; PNPLA3 is known for its association with fatty liver disease; and SH3B2 has been associated with a multitude of traits and disease including myocardial infarction. These associations provide insights into the genetic regulation of sICAM-1 levels and implicate these loci in the regulation of endothelial function.

%B PLoS Genet %V 7 %P e1001374 %8 2011 Apr %G eng %N 4 %1 http://www.ncbi.nlm.nih.gov/pubmed/21533024?dopt=Abstract %R 10.1371/journal.pgen.1001374 %0 Journal Article %J Genet Epidemiol %D 2011 %T Meta-analysis of gene-environment interaction: joint estimation of SNP and SNP × environment regression coefficients. %A Manning, Alisa K %A LaValley, Michael %A Liu, Ching-Ti %A Rice, Kenneth %A An, Ping %A Liu, Yongmei %A Miljkovic, Iva %A Rasmussen-Torvik, Laura %A Harris, Tamara B %A Province, Michael A %A Borecki, Ingrid B %A Florez, Jose C %A Meigs, James B %A Cupples, L Adrienne %A Dupuis, Josée %K Adult %K Aged %K Body Mass Index %K Confidence Intervals %K Diabetes Mellitus, Type 2 %K Environment %K Fasting %K Female %K Genome, Human %K Genome-Wide Association Study %K Genotype %K Humans %K Insulin %K Least-Squares Analysis %K Male %K Mathematical Computing %K Meta-Analysis as Topic %K Middle Aged %K Polymorphism, Single Nucleotide %K PPAR gamma %X

INTRODUCTION: Genetic discoveries are validated through the meta-analysis of genome-wide association scans in large international consortia. Because environmental variables may interact with genetic factors, investigation of differing genetic effects for distinct levels of an environmental exposure in these large consortia may yield additional susceptibility loci undetected by main effects analysis. We describe a method of joint meta-analysis (JMA) of SNP and SNP by Environment (SNP × E) regression coefficients for use in gene-environment interaction studies.

METHODS: In testing SNP × E interactions, one approach uses a two degree of freedom test to identify genetic variants that influence the trait of interest. This approach detects both main and interaction effects between the trait and the SNP. We propose a method to jointly meta-analyze the SNP and SNP × E coefficients using multivariate generalized least squares. This approach provides confidence intervals of the two estimates, a joint significance test for SNP and SNP × E terms, and a test of homogeneity across samples.

RESULTS: We present a simulation study comparing this method to four other methods of meta-analysis and demonstrate that the JMA performs better than the others when both main and interaction effects are present. Additionally, we implemented our methods in a meta-analysis of the association between SNPs from the type 2 diabetes-associated gene PPARG and log-transformed fasting insulin levels and interaction by body mass index in a combined sample of 19,466 individuals from five cohorts.

%B Genet Epidemiol %V 35 %P 11-8 %8 2011 Jan %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/21181894?dopt=Abstract %R 10.1002/gepi.20546 %0 Journal Article %J Circulation %D 2011 %T Meta-analysis of genome-wide association studies in >80 000 subjects identifies multiple loci for C-reactive protein levels. %A Dehghan, Abbas %A Dupuis, Josée %A Barbalic, Maja %A Bis, Joshua C %A Eiriksdottir, Gudny %A Lu, Chen %A Pellikka, Niina %A Wallaschofski, Henri %A Kettunen, Johannes %A Henneman, Peter %A Baumert, Jens %A Strachan, David P %A Fuchsberger, Christian %A Vitart, Veronique %A Wilson, James F %A Paré, Guillaume %A Naitza, Silvia %A Rudock, Megan E %A Surakka, Ida %A de Geus, Eco J C %A Alizadeh, Behrooz Z %A Guralnik, Jack %A Shuldiner, Alan %A Tanaka, Toshiko %A Zee, Robert Y L %A Schnabel, Renate B %A Nambi, Vijay %A Kavousi, Maryam %A Ripatti, Samuli %A Nauck, Matthias %A Smith, Nicholas L %A Smith, Albert V %A Sundvall, Jouko %A Scheet, Paul %A Liu, Yongmei %A Ruokonen, Aimo %A Rose, Lynda M %A Larson, Martin G %A Hoogeveen, Ron C %A Freimer, Nelson B %A Teumer, Alexander %A Tracy, Russell P %A Launer, Lenore J %A Buring, Julie E %A Yamamoto, Jennifer F %A Folsom, Aaron R %A Sijbrands, Eric J G %A Pankow, James %A Elliott, Paul %A Keaney, John F %A Sun, Wei %A Sarin, Antti-Pekka %A Fontes, João D %A Badola, Sunita %A Astor, Brad C %A Hofman, Albert %A Pouta, Anneli %A Werdan, Karl %A Greiser, Karin H %A Kuss, Oliver %A Meyer zu Schwabedissen, Henriette E %A Thiery, Joachim %A Jamshidi, Yalda %A Nolte, Ilja M %A Soranzo, Nicole %A Spector, Timothy D %A Völzke, Henry %A Parker, Alexander N %A Aspelund, Thor %A Bates, David %A Young, Lauren %A Tsui, Kim %A Siscovick, David S %A Guo, Xiuqing %A Rotter, Jerome I %A Uda, Manuela %A Schlessinger, David %A Rudan, Igor %A Hicks, Andrew A %A Penninx, Brenda W %A Thorand, Barbara %A Gieger, Christian %A Coresh, Joe %A Willemsen, Gonneke %A Harris, Tamara B %A Uitterlinden, André G %A Jarvelin, Marjo-Riitta %A Rice, Kenneth %A Radke, Dörte %A Salomaa, Veikko %A Willems van Dijk, Ko %A Boerwinkle, Eric %A Vasan, Ramachandran S %A Ferrucci, Luigi %A Gibson, Quince D %A Bandinelli, Stefania %A Snieder, Harold %A Boomsma, Dorret I %A Xiao, Xiangjun %A Campbell, Harry %A Hayward, Caroline %A Pramstaller, Peter P %A van Duijn, Cornelia M %A Peltonen, Leena %A Psaty, Bruce M %A Gudnason, Vilmundur %A Ridker, Paul M %A Homuth, Georg %A Koenig, Wolfgang %A Ballantyne, Christie M %A Witteman, Jacqueline C M %A Benjamin, Emelia J %A Perola, Markus %A Chasman, Daniel I %K Biomarkers %K C-Reactive Protein %K Cardiovascular Diseases %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Risk Factors %K Vasculitis %X

BACKGROUND: C-reactive protein (CRP) is a heritable marker of chronic inflammation that is strongly associated with cardiovascular disease. We sought to identify genetic variants that are associated with CRP levels.

METHODS AND RESULTS: We performed a genome-wide association analysis of CRP in 66 185 participants from 15 population-based studies. We sought replication for the genome-wide significant and suggestive loci in a replication panel comprising 16 540 individuals from 10 independent studies. We found 18 genome-wide significant loci, and we provided evidence of replication for 8 of them. Our results confirm 7 previously known loci and introduce 11 novel loci that are implicated in pathways related to the metabolic syndrome (APOC1, HNF1A, LEPR, GCKR, HNF4A, and PTPN2) or the immune system (CRP, IL6R, NLRP3, IL1F10, and IRF1) or that reside in regions previously not known to play a role in chronic inflammation (PPP1R3B, SALL1, PABPC4, ASCL1, RORA, and BCL7B). We found a significant interaction of body mass index with LEPR (P<2.9×10(-6)). A weighted genetic risk score that was developed to summarize the effect of risk alleles was strongly associated with CRP levels and explained ≈5% of the trait variance; however, there was no evidence for these genetic variants explaining the association of CRP with coronary heart disease.

CONCLUSIONS: We identified 18 loci that were associated with CRP levels. Our study highlights immune response and metabolic regulatory pathways involved in the regulation of chronic inflammation.

%B Circulation %V 123 %P 731-8 %8 2011 Feb 22 %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/21300955?dopt=Abstract %R 10.1161/CIRCULATIONAHA.110.948570 %0 Journal Article %J Diabetes %D 2011 %T Total zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis. %A Kanoni, Stavroula %A Nettleton, Jennifer A %A Hivert, Marie-France %A Ye, Zheng %A van Rooij, Frank J A %A Shungin, Dmitry %A Sonestedt, Emily %A Ngwa, Julius S %A Wojczynski, Mary K %A Lemaitre, Rozenn N %A Gustafsson, Stefan %A Anderson, Jennifer S %A Tanaka, Toshiko %A Hindy, George %A Saylor, Georgia %A Renstrom, Frida %A Bennett, Amanda J %A van Duijn, Cornelia M %A Florez, Jose C %A Fox, Caroline S %A Hofman, Albert %A Hoogeveen, Ron C %A Houston, Denise K %A Hu, Frank B %A Jacques, Paul F %A Johansson, Ingegerd %A Lind, Lars %A Liu, Yongmei %A McKeown, Nicola %A Ordovas, Jose %A Pankow, James S %A Sijbrands, Eric J G %A Syvänen, Ann-Christine %A Uitterlinden, André G %A Yannakoulia, Mary %A Zillikens, M Carola %A Wareham, Nick J %A Prokopenko, Inga %A Bandinelli, Stefania %A Forouhi, Nita G %A Cupples, L Adrienne %A Loos, Ruth J %A Hallmans, Göran %A Dupuis, Josée %A Langenberg, Claudia %A Ferrucci, Luigi %A Kritchevsky, Stephen B %A McCarthy, Mark I %A Ingelsson, Erik %A Borecki, Ingrid B %A Witteman, Jacqueline C M %A Orho-Melander, Marju %A Siscovick, David S %A Meigs, James B %A Franks, Paul W %A Dedoussis, George V %K Blood Glucose %K Cation Transport Proteins %K Cohort Studies %K Humans %K Polymorphism, Single Nucleotide %K Zinc %K Zinc Transporter 8 %X

OBJECTIVE: Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for β-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants.

RESEARCH DESIGN AND METHODS: We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes.

RESULTS: We observed a significant association of total zinc intake with lower fasting glucose levels (β-coefficient ± SE per 1 mg/day of zinc intake: -0.0012 ± 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (β-coefficient ± SE per A allele for 1 mg/day of greater total zinc intake: -0.0017 ± 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant.

CONCLUSIONS: Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels.

%B Diabetes %V 60 %P 2407-16 %8 2011 Sep %G eng %N 9 %1 http://www.ncbi.nlm.nih.gov/pubmed/21810599?dopt=Abstract %R 10.2337/db11-0176 %0 Journal Article %J Eur Heart J %D 2012 %T Eight genetic loci associated with variation in lipoprotein-associated phospholipase A2 mass and activity and coronary heart disease: meta-analysis of genome-wide association studies from five community-based studies. %A Grallert, Harald %A Dupuis, Josée %A Bis, Joshua C %A Dehghan, Abbas %A Barbalic, Maja %A Baumert, Jens %A Lu, Chen %A Smith, Nicholas L %A Uitterlinden, André G %A Roberts, Robert %A Khuseyinova, Natalie %A Schnabel, Renate B %A Rice, Kenneth M %A Rivadeneira, Fernando %A Hoogeveen, Ron C %A Fontes, João Daniel %A Meisinger, Christa %A Keaney, John F %A Lemaitre, Rozenn %A Aulchenko, Yurii S %A Vasan, Ramachandran S %A Ellis, Stephen %A Hazen, Stanley L %A van Duijn, Cornelia M %A Nelson, Jeanenne J %A März, Winfried %A Schunkert, Heribert %A McPherson, Ruth M %A Stirnadel-Farrant, Heide A %A Psaty, Bruce M %A Gieger, Christian %A Siscovick, David %A Hofman, Albert %A Illig, Thomas %A Cushman, Mary %A Yamamoto, Jennifer F %A Rotter, Jerome I %A Larson, Martin G %A Stewart, Alexandre F R %A Boerwinkle, Eric %A Witteman, Jacqueline C M %A Tracy, Russell P %A Koenig, Wolfgang %A Benjamin, Emelia J %A Ballantyne, Christie M %K 1-Alkyl-2-acetylglycerophosphocholine Esterase %K Aged %K Coronary Artery Disease %K Coronary Disease %K Female %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Male %K Middle Aged %K Phospholipases A2 %K Polymorphism, Single Nucleotide %X

AIMS: Lipoprotein-associated phospholipase A2 (Lp-PLA2) generates proinflammatory and proatherogenic compounds in the arterial vascular wall and is a potential therapeutic target in coronary heart disease (CHD). We searched for genetic loci related to Lp-PLA2 mass or activity by a genome-wide association study as part of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium.

METHODS AND RESULTS: In meta-analyses of findings from five population-based studies, comprising 13 664 subjects, variants at two loci (PLA2G7, CETP) were associated with Lp-PLA2 mass. The strongest signal was at rs1805017 in PLA2G7 [P = 2.4 × 10(-23), log Lp-PLA2 difference per allele (beta): 0.043]. Variants at six loci were associated with Lp-PLA2 activity (PLA2G7, APOC1, CELSR2, LDL, ZNF259, SCARB1), among which the strongest signals were at rs4420638, near the APOE-APOC1-APOC4-APOC2 cluster [P = 4.9 × 10(-30); log Lp-PLA2 difference per allele (beta): -0.054]. There were no significant gene-environment interactions between these eight polymorphisms associated with Lp-PLA2 mass or activity and age, sex, body mass index, or smoking status. Four of the polymorphisms (in APOC1, CELSR2, SCARB1, ZNF259), but not PLA2G7, were significantly associated with CHD in a second study.

CONCLUSION: Levels of Lp-PLA2 mass and activity were associated with PLA2G7, the gene coding for this protein. Lipoprotein-associated phospholipase A2 activity was also strongly associated with genetic variants related to low-density lipoprotein cholesterol levels.

%B Eur Heart J %V 33 %P 238-51 %8 2012 Jan %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/22003152?dopt=Abstract %R 10.1093/eurheartj/ehr372 %0 Journal Article %J Am J Respir Crit Care Med %D 2012 %T Genome-wide association studies identify CHRNA5/3 and HTR4 in the development of airflow obstruction. %A Wilk, Jemma B %A Shrine, Nick R G %A Loehr, Laura R %A Zhao, Jing Hua %A Manichaikul, Ani %A Lopez, Lorna M %A Smith, Albert Vernon %A Heckbert, Susan R %A Smolonska, Joanna %A Tang, Wenbo %A Loth, Daan W %A Curjuric, Ivan %A Hui, Jennie %A Cho, Michael H %A Latourelle, Jeanne C %A Henry, Amanda P %A Aldrich, Melinda %A Bakke, Per %A Beaty, Terri H %A Bentley, Amy R %A Borecki, Ingrid B %A Brusselle, Guy G %A Burkart, Kristin M %A Chen, Ting-Hsu %A Couper, David %A Crapo, James D %A Davies, Gail %A Dupuis, Josée %A Franceschini, Nora %A Gulsvik, Amund %A Hancock, Dana B %A Harris, Tamara B %A Hofman, Albert %A Imboden, Medea %A James, Alan L %A Khaw, Kay-Tee %A Lahousse, Lies %A Launer, Lenore J %A Litonjua, Augusto %A Liu, Yongmei %A Lohman, Kurt K %A Lomas, David A %A Lumley, Thomas %A Marciante, Kristin D %A McArdle, Wendy L %A Meibohm, Bernd %A Morrison, Alanna C %A Musk, Arthur W %A Myers, Richard H %A North, Kari E %A Postma, Dirkje S %A Psaty, Bruce M %A Rich, Stephen S %A Rivadeneira, Fernando %A Rochat, Thierry %A Rotter, Jerome I %A Soler Artigas, Maria %A Starr, John M %A Uitterlinden, André G %A Wareham, Nicholas J %A Wijmenga, Cisca %A Zanen, Pieter %A Province, Michael A %A Silverman, Edwin K %A Deary, Ian J %A Palmer, Lyle J %A Cassano, Patricia A %A Gudnason, Vilmundur %A Barr, R Graham %A Loos, Ruth J F %A Strachan, David P %A London, Stephanie J %A Boezen, H Marike %A Probst-Hensch, Nicole %A Gharib, Sina A %A Hall, Ian P %A O'Connor, George T %A Tobin, Martin D %A Stricker, Bruno H %K Aged %K Female %K Forced Expiratory Volume %K Genome-Wide Association Study %K Humans %K Male %K Middle Aged %K Nerve Tissue Proteins %K Polymorphism, Single Nucleotide %K Pulmonary Disease, Chronic Obstructive %K Receptors, Nicotinic %K Receptors, Serotonin, 5-HT4 %K Smoking %K Vital Capacity %X

RATIONALE: Genome-wide association studies (GWAS) have identified loci influencing lung function, but fewer genes influencing chronic obstructive pulmonary disease (COPD) are known.

OBJECTIVES: Perform meta-analyses of GWAS for airflow obstruction, a key pathophysiologic characteristic of COPD assessed by spirometry, in population-based cohorts examining all participants, ever smokers, never smokers, asthma-free participants, and more severe cases.

METHODS: Fifteen cohorts were studied for discovery (3,368 affected; 29,507 unaffected), and a population-based family study and a meta-analysis of case-control studies were used for replication and regional follow-up (3,837 cases; 4,479 control subjects). Airflow obstruction was defined as FEV(1) and its ratio to FVC (FEV(1)/FVC) both less than their respective lower limits of normal as determined by published reference equations.

MEASUREMENTS AND MAIN RESULTS: The discovery meta-analyses identified one region on chromosome 15q25.1 meeting genome-wide significance in ever smokers that includes AGPHD1, IREB2, and CHRNA5/CHRNA3 genes. The region was also modestly associated among never smokers. Gene expression studies confirmed the presence of CHRNA5/3 in lung, airway smooth muscle, and bronchial epithelial cells. A single-nucleotide polymorphism in HTR4, a gene previously related to FEV(1)/FVC, achieved genome-wide statistical significance in combined meta-analysis. Top single-nucleotide polymorphisms in ADAM19, RARB, PPAP2B, and ADAMTS19 were nominally replicated in the COPD meta-analysis.

CONCLUSIONS: These results suggest an important role for the CHRNA5/3 region as a genetic risk factor for airflow obstruction that may be independent of smoking and implicate the HTR4 gene in the etiology of airflow obstruction.

%B Am J Respir Crit Care Med %V 186 %P 622-32 %8 2012 Oct 01 %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/22837378?dopt=Abstract %R 10.1164/rccm.201202-0366OC %0 Journal Article %J PLoS Genet %D 2012 %T Genome-wide joint meta-analysis of SNP and SNP-by-smoking interaction identifies novel loci for pulmonary function. %A Hancock, Dana B %A Soler Artigas, Maria %A Gharib, Sina A %A Henry, Amanda %A Manichaikul, Ani %A Ramasamy, Adaikalavan %A Loth, Daan W %A Imboden, Medea %A Koch, Beate %A McArdle, Wendy L %A Smith, Albert V %A Smolonska, Joanna %A Sood, Akshay %A Tang, Wenbo %A Wilk, Jemma B %A Zhai, Guangju %A Zhao, Jing Hua %A Aschard, Hugues %A Burkart, Kristin M %A Curjuric, Ivan %A Eijgelsheim, Mark %A Elliott, Paul %A Gu, Xiangjun %A Harris, Tamara B %A Janson, Christer %A Homuth, Georg %A Hysi, Pirro G %A Liu, Jason Z %A Loehr, Laura R %A Lohman, Kurt %A Loos, Ruth J F %A Manning, Alisa K %A Marciante, Kristin D %A Obeidat, Ma'en %A Postma, Dirkje S %A Aldrich, Melinda C %A Brusselle, Guy G %A Chen, Ting-Hsu %A Eiriksdottir, Gudny %A Franceschini, Nora %A Heinrich, Joachim %A Rotter, Jerome I %A Wijmenga, Cisca %A Williams, O Dale %A Bentley, Amy R %A Hofman, Albert %A Laurie, Cathy C %A Lumley, Thomas %A Morrison, Alanna C %A Joubert, Bonnie R %A Rivadeneira, Fernando %A Couper, David J %A Kritchevsky, Stephen B %A Liu, Yongmei %A Wjst, Matthias %A Wain, Louise V %A Vonk, Judith M %A Uitterlinden, André G %A Rochat, Thierry %A Rich, Stephen S %A Psaty, Bruce M %A O'Connor, George T %A North, Kari E %A Mirel, Daniel B %A Meibohm, Bernd %A Launer, Lenore J %A Khaw, Kay-Tee %A Hartikainen, Anna-Liisa %A Hammond, Christopher J %A Gläser, Sven %A Marchini, Jonathan %A Kraft, Peter %A Wareham, Nicholas J %A Völzke, Henry %A Stricker, Bruno H C %A Spector, Timothy D %A Probst-Hensch, Nicole M %A Jarvis, Deborah %A Jarvelin, Marjo-Riitta %A Heckbert, Susan R %A Gudnason, Vilmundur %A Boezen, H Marike %A Barr, R Graham %A Cassano, Patricia A %A Strachan, David P %A Fornage, Myriam %A Hall, Ian P %A Dupuis, Josée %A Tobin, Martin D %A London, Stephanie J %K Forced Expiratory Volume %K Gene Expression %K Genome, Human %K Genome-Wide Association Study %K HLA-DQ Antigens %K HLA-DQ beta-Chains %K Humans %K Lung %K Nerve Tissue Proteins %K Polymorphism, Single Nucleotide %K Potassium Channels, Inwardly Rectifying %K Pulmonary Disease, Chronic Obstructive %K Receptors, Cell Surface %K Smoking %K SOX9 Transcription Factor %K Vital Capacity %X

Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV(1)), and its ratio to forced vital capacity (FEV(1)/FVC). Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA) of single nucleotide polymorphism (SNP) and SNP-by-smoking (ever-smoking or pack-years) associations on FEV(1) and FEV(1)/FVC across 19 studies (total N = 50,047). We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest P(JMA = )5.00×10(-11)), HLA-DQB1 and HLA-DQA2 (smallest P(JMA = )4.35×10(-9)), and KCNJ2 and SOX9 (smallest P(JMA = )1.28×10(-8)) were associated with FEV(1)/FVC or FEV(1) in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years) interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.

%B PLoS Genet %V 8 %P e1003098 %8 2012 %G eng %N 12 %1 http://www.ncbi.nlm.nih.gov/pubmed/23284291?dopt=Abstract %R 10.1371/journal.pgen.1003098 %0 Journal Article %J Nat Genet %D 2012 %T Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. %A Scott, Robert A %A Lagou, Vasiliki %A Welch, Ryan P %A Wheeler, Eleanor %A Montasser, May E %A Luan, Jian'an %A Mägi, Reedik %A Strawbridge, Rona J %A Rehnberg, Emil %A Gustafsson, Stefan %A Kanoni, Stavroula %A Rasmussen-Torvik, Laura J %A Yengo, Loic %A Lecoeur, Cécile %A Shungin, Dmitry %A Sanna, Serena %A Sidore, Carlo %A Johnson, Paul C D %A Jukema, J Wouter %A Johnson, Toby %A Mahajan, Anubha %A Verweij, Niek %A Thorleifsson, Gudmar %A Hottenga, Jouke-Jan %A Shah, Sonia %A Smith, Albert V %A Sennblad, Bengt %A Gieger, Christian %A Salo, Perttu %A Perola, Markus %A Timpson, Nicholas J %A Evans, David M %A Pourcain, Beate St %A Wu, Ying %A Andrews, Jeanette S %A Hui, Jennie %A Bielak, Lawrence F %A Zhao, Wei %A Horikoshi, Momoko %A Navarro, Pau %A Isaacs, Aaron %A O'Connell, Jeffrey R %A Stirrups, Kathleen %A Vitart, Veronique %A Hayward, Caroline %A Esko, Tõnu %A Mihailov, Evelin %A Fraser, Ross M %A Fall, Tove %A Voight, Benjamin F %A Raychaudhuri, Soumya %A Chen, Han %A Lindgren, Cecilia M %A Morris, Andrew P %A Rayner, Nigel W %A Robertson, Neil %A Rybin, Denis %A Liu, Ching-Ti %A Beckmann, Jacques S %A Willems, Sara M %A Chines, Peter S %A Jackson, Anne U %A Kang, Hyun Min %A Stringham, Heather M %A Song, Kijoung %A Tanaka, Toshiko %A Peden, John F %A Goel, Anuj %A Hicks, Andrew A %A An, Ping %A Müller-Nurasyid, Martina %A Franco-Cereceda, Anders %A Folkersen, Lasse %A Marullo, Letizia %A Jansen, Hanneke %A Oldehinkel, Albertine J %A Bruinenberg, Marcel %A Pankow, James S %A North, Kari E %A Forouhi, Nita G %A Loos, Ruth J F %A Edkins, Sarah %A Varga, Tibor V %A Hallmans, Göran %A Oksa, Heikki %A Antonella, Mulas %A Nagaraja, Ramaiah %A Trompet, Stella %A Ford, Ian %A Bakker, Stephan J L %A Kong, Augustine %A Kumari, Meena %A Gigante, Bruna %A Herder, Christian %A Munroe, Patricia B %A Caulfield, Mark %A Antti, Jula %A Mangino, Massimo %A Small, Kerrin %A Miljkovic, Iva %A Liu, Yongmei %A Atalay, Mustafa %A Kiess, Wieland %A James, Alan L %A Rivadeneira, Fernando %A Uitterlinden, André G %A Palmer, Colin N A %A Doney, Alex S F %A Willemsen, Gonneke %A Smit, Johannes H %A Campbell, Susan %A Polasek, Ozren %A Bonnycastle, Lori L %A Hercberg, Serge %A Dimitriou, Maria %A Bolton, Jennifer L %A Fowkes, Gerard R %A Kovacs, Peter %A Lindström, Jaana %A Zemunik, Tatijana %A Bandinelli, Stefania %A Wild, Sarah H %A Basart, Hanneke V %A Rathmann, Wolfgang %A Grallert, Harald %A Maerz, Winfried %A Kleber, Marcus E %A Boehm, Bernhard O %A Peters, Annette %A Pramstaller, Peter P %A Province, Michael A %A Borecki, Ingrid B %A Hastie, Nicholas D %A Rudan, Igor %A Campbell, Harry %A Watkins, Hugh %A Farrall, Martin %A Stumvoll, Michael %A Ferrucci, Luigi %A Waterworth, Dawn M %A Bergman, Richard N %A Collins, Francis S %A Tuomilehto, Jaakko %A Watanabe, Richard M %A de Geus, Eco J C %A Penninx, Brenda W %A Hofman, Albert %A Oostra, Ben A %A Psaty, Bruce M %A Vollenweider, Peter %A Wilson, James F %A Wright, Alan F %A Hovingh, G Kees %A Metspalu, Andres %A Uusitupa, Matti %A Magnusson, Patrik K E %A Kyvik, Kirsten O %A Kaprio, Jaakko %A Price, Jackie F %A Dedoussis, George V %A Deloukas, Panos %A Meneton, Pierre %A Lind, Lars %A Boehnke, Michael %A Shuldiner, Alan R %A van Duijn, Cornelia M %A Morris, Andrew D %A Toenjes, Anke %A Peyser, Patricia A %A Beilby, John P %A Körner, Antje %A Kuusisto, Johanna %A Laakso, Markku %A Bornstein, Stefan R %A Schwarz, Peter E H %A Lakka, Timo A %A Rauramaa, Rainer %A Adair, Linda S %A Smith, George Davey %A Spector, Tim D %A Illig, Thomas %A de Faire, Ulf %A Hamsten, Anders %A Gudnason, Vilmundur %A Kivimaki, Mika %A Hingorani, Aroon %A Keinanen-Kiukaanniemi, Sirkka M %A Saaristo, Timo E %A Boomsma, Dorret I %A Stefansson, Kari %A van der Harst, Pim %A Dupuis, Josée %A Pedersen, Nancy L %A Sattar, Naveed %A Harris, Tamara B %A Cucca, Francesco %A Ripatti, Samuli %A Salomaa, Veikko %A Mohlke, Karen L %A Balkau, Beverley %A Froguel, Philippe %A Pouta, Anneli %A Jarvelin, Marjo-Riitta %A Wareham, Nicholas J %A Bouatia-Naji, Nabila %A McCarthy, Mark I %A Franks, Paul W %A Meigs, James B %A Teslovich, Tanya M %A Florez, Jose C %A Langenberg, Claudia %A Ingelsson, Erik %A Prokopenko, Inga %A Barroso, Inês %K Adult %K Animals %K Blood Glucose %K Fasting %K Female %K Gene Frequency %K Genome-Wide Association Study %K Humans %K Insulin %K Male %K Metabolic Networks and Pathways %K Mice %K Osmolar Concentration %K Quantitative Trait Loci %X

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.

%B Nat Genet %V 44 %P 991-1005 %8 2012 Sep %G eng %N 9 %1 http://www.ncbi.nlm.nih.gov/pubmed/22885924?dopt=Abstract %R 10.1038/ng.2385 %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 Hum Mol Genet %D 2013 %T Genome-wide and gene-centric analyses of circulating myeloperoxidase levels in the charge and care consortia. %A Reiner, Alexander P %A Hartiala, Jaana %A Zeller, Tanja %A Bis, Joshua C %A Dupuis, Josée %A Fornage, Myriam %A Baumert, Jens %A Kleber, Marcus E %A Wild, Philipp S %A Baldus, Stephan %A Bielinski, Suzette J %A Fontes, João D %A Illig, Thomas %A Keating, Brendan J %A Lange, Leslie A %A Ojeda, Francisco %A Müller-Nurasyid, Martina %A Munzel, Thomas F %A Psaty, Bruce M %A Rice, Kenneth %A Rotter, Jerome I %A Schnabel, Renate B %A Tang, W H Wilson %A Thorand, Barbara %A Erdmann, Jeanette %A Jacobs, David R %A Wilson, James G %A Koenig, Wolfgang %A Tracy, Russell P %A Blankenberg, Stefan %A März, Winfried %A Gross, Myron D %A Benjamin, Emelia J %A Hazen, Stanley L %A Allayee, Hooman %K Adult %K African Americans %K Aged %K Case-Control Studies %K Complement Factor H %K Coronary Artery Disease %K European Continental Ancestry Group %K Female %K Gene Expression Regulation, Enzymologic %K Genetic Association Studies %K Genetic Variation %K Genome-Wide Association Study %K Genotype %K Humans %K Male %K Middle Aged %K Peroxidase %K Polymorphism, Single Nucleotide %K Young Adult %X

Increased systemic levels of myeloperoxidase (MPO) are associated with the risk of coronary artery disease (CAD). To identify the genetic factors that are associated with circulating MPO levels, we carried out a genome-wide association study (GWAS) and a gene-centric analysis in subjects of European ancestry and African Americans (AAs). A locus on chromosome 1q31.1 containing the complement factor H (CFH) gene was strongly associated with serum MPO levels in 9305 subjects of European ancestry (lead SNP rs800292; P = 4.89 × 10(-41)) and in 1690 AA subjects (rs505102; P = 1.05 × 10(-8)). Gene-centric analyses in 8335 subjects of European ancestry additionally identified two rare MPO coding sequence variants that were associated with serum MPO levels (rs28730837, P = 5.21 × 10(-12); rs35897051, P = 3.32 × 10(-8)). A GWAS for plasma MPO levels in 9260 European ancestry subjects identified a chromosome 17q22 region near MPO that was significantly associated (lead SNP rs6503905; P = 2.94 × 10(-12)), but the CFH locus did not exhibit evidence of association with plasma MPO levels. Functional analyses revealed that rs800292 was associated with levels of complement proteins in serum. Variants at chromosome 17q22 also had pleiotropic cis effects on gene expression. In a case-control analysis of ∼80 000 subjects from CARDIoGRAM, none of the identified single-nucleotide polymorphisms (SNPs) were associated with CAD. These results suggest that distinct genetic factors regulate serum and plasma MPO levels, which may have relevance for various acute and chronic inflammatory disorders. The clinical implications for CAD and a better understanding of the functional basis for the association of CFH and MPO variants with circulating MPO levels require further study.

%B Hum Mol Genet %V 22 %P 3381-93 %8 2013 Aug 15 %G eng %N 16 %1 http://www.ncbi.nlm.nih.gov/pubmed/23620142?dopt=Abstract %R 10.1093/hmg/ddt189 %0 Journal Article %J Hum Genet %D 2013 %T Genome-wide study identifies two loci associated with lung function decline in mild to moderate COPD. %A Hansel, Nadia N %A Ruczinski, Ingo %A Rafaels, Nicholas %A Sin, Don D %A Daley, Denise %A Malinina, Alla %A Huang, Lili %A Sandford, Andrew %A Murray, Tanda %A Kim, Yoonhee %A Vergara, Candelaria %A Heckbert, Susan R %A Psaty, Bruce M %A Li, Guo %A Elliott, W Mark %A Aminuddin, Farzian %A Dupuis, Josée %A O'Connor, George T %A Doheny, Kimberly %A Scott, Alan F %A Boezen, H Marike %A Postma, Dirkje S %A Smolonska, Joanna %A Zanen, Pieter %A Mohamed Hoesein, Firdaus A %A de Koning, Harry J %A Crystal, Ronald G %A Tanaka, Toshiko %A Ferrucci, Luigi %A Silverman, Edwin %A Wan, Emily %A Vestbo, Jorgen %A Lomas, David A %A Connett, John %A Wise, Robert A %A Neptune, Enid R %A Mathias, Rasika A %A Paré, Peter D %A Beaty, Terri H %A Barnes, Kathleen C %K Adult %K Ankyrins %K Chromosomes, Human, Pair 10 %K Chromosomes, Human, Pair 14 %K Cohort Studies %K Female %K Genome-Wide Association Study %K Hepatocyte Nuclear Factor 3-alpha %K Humans %K Linkage Disequilibrium %K Lung %K Male %K Membrane Proteins %K Middle Aged %K Polymorphism, Single Nucleotide %K Pulmonary Disease, Chronic Obstructive %X

Accelerated lung function decline is a key COPD phenotype; however, its genetic control remains largely unknown. We performed a genome-wide association study using the Illumina Human660W-Quad v.1_A BeadChip. Generalized estimation equations were used to assess genetic contributions to lung function decline over a 5-year period in 4,048 European American Lung Health Study participants with largely mild COPD. Genotype imputation was performed using reference HapMap II data. To validate regions meeting genome-wide significance, replication of top SNPs was attempted in independent cohorts. Three genes (TMEM26, ANK3 and FOXA1) within the regions of interest were selected for tissue expression studies using immunohistochemistry. Two intergenic SNPs (rs10761570, rs7911302) on chromosome 10 and one SNP on chromosome 14 (rs177852) met genome-wide significance after Bonferroni. Further support for the chromosome 10 region was obtained by imputation, the most significantly associated imputed SNPs (rs10761571, rs7896712) being flanked by observed markers rs10761570 and rs7911302. Results were not replicated in four general population cohorts or a smaller cohort of subjects with moderate to severe COPD; however, we show novel expression of genes near regions of significantly associated SNPS, including TMEM26 and FOXA1 in airway epithelium and lung parenchyma, and ANK3 in alveolar macrophages. Levels of expression were associated with lung function and COPD status. We identified two novel regions associated with lung function decline in mild COPD. Genes within these regions were expressed in relevant lung cells and their expression related to airflow limitation suggesting they may represent novel candidate genes for COPD susceptibility.

%B Hum Genet %V 132 %P 79-90 %8 2013 Jan %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/22986903?dopt=Abstract %R 10.1007/s00439-012-1219-6 %0 Journal Article %J Circ Cardiovasc Genet %D 2014 %T ADAM19 and HTR4 variants and pulmonary function: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study. %A London, Stephanie J %A Gao, Wei %A Gharib, Sina A %A Hancock, Dana B %A Wilk, Jemma B %A House, John S %A Gibbs, Richard A %A Muzny, Donna M %A Lumley, Thomas %A Franceschini, Nora %A North, Kari E %A Psaty, Bruce M %A Kovar, Christie L %A Coresh, Josef %A Zhou, Yanhua %A Heckbert, Susan R %A Brody, Jennifer A %A Morrison, Alanna C %A Dupuis, Josée %K ADAM Proteins %K Aged %K Aged, 80 and over %K Aging %K Cohort Studies %K Female %K Genetic Variation %K Genome-Wide Association Study %K Genomics %K Heart Diseases %K Humans %K Lung %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Sequence Analysis, DNA %X

BACKGROUND: The pulmonary function measures of forced expiratory volume in 1 second (FEV1) and its ratio to forced vital capacity (FVC) are used in the diagnosis and monitoring of lung diseases and predict cardiovascular mortality in the general population. Genome-wide association studies (GWASs) have identified numerous loci associated with FEV1 and FEV1/FVC, but the causal variants remain uncertain. We hypothesized that novel or rare variants poorly tagged by GWASs may explain the significant associations between FEV1/FVC and 2 genes: ADAM19 and HTR4.

METHODS AND RESULTS: We sequenced ADAM19 and its promoter region along with the ≈21-kb portion of HTR4 harboring GWAS single-nucleotide polymorphisms for pulmonary function and analyzed associations with FEV1/FVC among 3983 participants of European ancestry from Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Meta-analysis of common variants in each region identified statistically significant associations (316 tests; P<1.58×10(-4)) with FEV1/FVC for 14 ADAM19 single-nucleotide polymorphisms and 24 HTR4 single-nucleotide polymorphisms. After conditioning on the sentinel GWASs hit in each gene (ADAM19 rs1422795, minor allele frequency=0.33 and HTR4 rs11168048, minor allele frequency=0.40], 1 single-nucleotide polymorphism remained statistically significant (ADAM19 rs13155908, minor allele frequency=0.12; P=1.56×10(-4)). Analysis of rare variants (minor allele frequency <1%) using sequence kernel association test did not identify associations with either region.

CONCLUSIONS: Sequencing identified 1 common variant associated with FEV1/FVC independent of the sentinel ADAM19 GWAS hit and supports the original HTR4 GWAS findings. Rare variants do not seem to underlie GWAS associations with pulmonary function for common variants in ADAM19 and HTR4.

%B Circ Cardiovasc Genet %V 7 %P 350-8 %8 2014 Jun %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/24951661?dopt=Abstract %R 10.1161/CIRCGENETICS.113.000066 %0 Journal Article %J Circ Cardiovasc Genet %D 2014 %T Association of levels of fasting glucose and insulin with rare variants at the chromosome 11p11.2-MADD locus: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study. %A Cornes, Belinda K %A Brody, Jennifer A %A Nikpoor, Naghmeh %A Morrison, Alanna C %A Chu, Huan %A Ahn, Byung Soo %A Wang, Shuai %A Dauriz, Marco %A Barzilay, Joshua I %A Dupuis, Josée %A Florez, Jose C %A Coresh, Josef %A Gibbs, Richard A %A Kao, W H Linda %A Liu, Ching-Ti %A McKnight, Barbara %A Muzny, Donna %A Pankow, James S %A Reid, Jeffrey G %A White, Charles C %A Johnson, Andrew D %A Wong, Tien Y %A Psaty, Bruce M %A Boerwinkle, Eric %A Rotter, Jerome I %A Siscovick, David S %A Sladek, Robert %A Meigs, James B %K Aged %K Aged, 80 and over %K Aging %K Blood Glucose %K Chromosomes, Human, Pair 11 %K Cohort Studies %K Death Domain Receptor Signaling Adaptor Proteins %K Diabetes Mellitus, Type 2 %K Fasting %K Female %K Gene Frequency %K Genetic Variation %K Genome-Wide Association Study %K Genomics %K Guanine Nucleotide Exchange Factors %K Heart Diseases %K Humans %K Insulin %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Sequence Analysis, DNA %X

BACKGROUND: Common variation at the 11p11.2 locus, encompassing MADD, ACP2, NR1H3, MYBPC3, and SPI1, has been associated in genome-wide association studies with fasting glucose and insulin (FI). In the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study, we sequenced 5 gene regions at 11p11.2 to identify rare, potentially functional variants influencing fasting glucose or FI levels.

METHODS AND RESULTS: Sequencing (mean depth, 38×) across 16.1 kb in 3566 individuals without diabetes mellitus identified 653 variants, 79.9% of which were rare (minor allele frequency <1%) and novel. We analyzed rare variants in 5 gene regions with FI or fasting glucose using the sequence kernel association test. At NR1H3, 53 rare variants were jointly associated with FI (P=2.73×10(-3)); of these, 7 were predicted to have regulatory function and showed association with FI (P=1.28×10(-3)). Conditioning on 2 previously associated variants at MADD (rs7944584, rs10838687) did not attenuate this association, suggesting that there are >2 independent signals at 11p11.2. One predicted regulatory variant, chr11:47227430 (hg18; minor allele frequency=0.00068), contributed 20.6% to the overall sequence kernel association test score at NR1H3, lies in intron 2 of NR1H3, and is a predicted binding site for forkhead box A1 (FOXA1), a transcription factor associated with insulin regulation. In human HepG2 hepatoma cells, the rare chr11:47227430 A allele disrupted FOXA1 binding and reduced FOXA1-dependent transcriptional activity.

CONCLUSIONS: Sequencing at 11p11.2-NR1H3 identified rare variation associated with FI. One variant, chr11:47227430, seems to be functional, with the rare A allele reducing transcription factor FOXA1 binding and FOXA1-dependent transcriptional activity.

%B Circ Cardiovasc Genet %V 7 %P 374-382 %8 2014 Jun %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/24951664?dopt=Abstract %R 10.1161/CIRCGENETICS.113.000169 %0 Journal Article %J Nat Genet %D 2014 %T Genome-wide association analysis identifies six new loci associated with forced vital capacity. %A Loth, Daan W %A Soler Artigas, Maria %A Gharib, Sina A %A Wain, Louise V %A Franceschini, Nora %A Koch, Beate %A Pottinger, Tess D %A Smith, Albert Vernon %A Duan, Qing %A Oldmeadow, Chris %A Lee, Mi Kyeong %A Strachan, David P %A James, Alan L %A Huffman, Jennifer E %A Vitart, Veronique %A Ramasamy, Adaikalavan %A Wareham, Nicholas J %A Kaprio, Jaakko %A Wang, Xin-Qun %A Trochet, Holly %A Kähönen, Mika %A Flexeder, Claudia %A Albrecht, Eva %A Lopez, Lorna M %A de Jong, Kim %A Thyagarajan, Bharat %A Alves, Alexessander Couto %A Enroth, Stefan %A Omenaas, Ernst %A Joshi, Peter K %A Fall, Tove %A Viñuela, Ana %A Launer, Lenore J %A Loehr, Laura R %A Fornage, Myriam %A Li, Guo %A Wilk, Jemma B %A Tang, Wenbo %A Manichaikul, Ani %A Lahousse, Lies %A Harris, Tamara B %A North, Kari E %A Rudnicka, Alicja R %A Hui, Jennie %A Gu, Xiangjun %A Lumley, Thomas %A Wright, Alan F %A Hastie, Nicholas D %A Campbell, Susan %A Kumar, Rajesh %A Pin, Isabelle %A Scott, Robert A %A Pietiläinen, Kirsi H %A Surakka, Ida %A Liu, Yongmei %A Holliday, Elizabeth G %A Schulz, Holger %A Heinrich, Joachim %A Davies, Gail %A Vonk, Judith M %A Wojczynski, Mary %A Pouta, Anneli %A Johansson, Asa %A Wild, Sarah H %A Ingelsson, Erik %A Rivadeneira, Fernando %A Völzke, Henry %A Hysi, Pirro G %A Eiriksdottir, Gudny %A Morrison, Alanna C %A Rotter, Jerome I %A Gao, Wei %A Postma, Dirkje S %A White, Wendy B %A Rich, Stephen S %A Hofman, Albert %A Aspelund, Thor %A Couper, David %A Smith, Lewis J %A Psaty, Bruce M %A Lohman, Kurt %A Burchard, Esteban G %A Uitterlinden, André G %A Garcia, Melissa %A Joubert, Bonnie R %A McArdle, Wendy L %A Musk, A Bill %A Hansel, Nadia %A Heckbert, Susan R %A Zgaga, Lina %A van Meurs, Joyce B J %A Navarro, Pau %A Rudan, Igor %A Oh, Yeon-Mok %A Redline, Susan %A Jarvis, Deborah L %A Zhao, Jing Hua %A Rantanen, Taina %A O'Connor, George T %A Ripatti, Samuli %A Scott, Rodney J %A Karrasch, Stefan %A Grallert, Harald %A Gaddis, Nathan C %A Starr, John M %A Wijmenga, Cisca %A Minster, Ryan L %A Lederer, David J %A Pekkanen, Juha %A Gyllensten, Ulf %A Campbell, Harry %A Morris, Andrew P %A Gläser, Sven %A Hammond, Christopher J %A Burkart, Kristin M %A Beilby, John %A Kritchevsky, Stephen B %A Gudnason, Vilmundur %A Hancock, Dana B %A Williams, O Dale %A Polasek, Ozren %A Zemunik, Tatijana %A Kolcic, Ivana %A Petrini, Marcy F %A Wjst, Matthias %A Kim, Woo Jin %A Porteous, David J %A Scotland, Generation %A Smith, Blair H %A Viljanen, Anne %A Heliövaara, Markku %A Attia, John R %A Sayers, Ian %A Hampel, Regina %A Gieger, Christian %A Deary, Ian J %A Boezen, H Marike %A Newman, Anne %A Jarvelin, Marjo-Riitta %A Wilson, James F %A Lind, Lars %A Stricker, Bruno H %A Teumer, Alexander %A Spector, Timothy D %A Melén, Erik %A Peters, Marjolein J %A Lange, Leslie A %A Barr, R Graham %A Bracke, Ken R %A Verhamme, Fien M %A Sung, Joohon %A Hiemstra, Pieter S %A Cassano, Patricia A %A Sood, Akshay %A Hayward, Caroline %A Dupuis, Josée %A Hall, Ian P %A Brusselle, Guy G %A Tobin, Martin D %A London, Stephanie J %K Cohort Studies %K Databases, Genetic %K Follow-Up Studies %K Forced Expiratory Volume %K Genetic Loci %K Genetic Predisposition to Disease %K Genome, Human %K Genome-Wide Association Study %K Humans %K Lung Diseases %K Meta-Analysis as Topic %K Polymorphism, Single Nucleotide %K Prognosis %K Quantitative Trait Loci %K Respiratory Function Tests %K Spirometry %K Vital Capacity %X

Forced vital capacity (FVC), a spirometric measure of pulmonary function, reflects lung volume and is used to diagnose and monitor lung diseases. We performed genome-wide association study meta-analysis of FVC in 52,253 individuals from 26 studies and followed up the top associations in 32,917 additional individuals of European ancestry. We found six new regions associated at genome-wide significance (P < 5 × 10(-8)) with FVC in or near EFEMP1, BMP6, MIR129-2-HSD17B12, PRDM11, WWOX and KCNJ2. Two loci previously associated with spirometric measures (GSTCD and PTCH1) were related to FVC. Newly implicated regions were followed up in samples from African-American, Korean, Chinese and Hispanic individuals. We detected transcripts for all six newly implicated genes in human lung tissue. The new loci may inform mechanisms involved in lung development and the pathogenesis of restrictive lung disease.

%B Nat Genet %V 46 %P 669-77 %8 2014 Jul %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/24929828?dopt=Abstract %R 10.1038/ng.3011 %0 Journal Article %J Hum Genet %D 2014 %T Large multiethnic Candidate Gene Study for C-reactive protein levels: identification of a novel association at CD36 in African Americans. %A Ellis, Jaclyn %A Lange, Ethan M %A Li, Jin %A Dupuis, Josée %A Baumert, Jens %A Walston, Jeremy D %A Keating, Brendan J %A Durda, Peter %A Fox, Ervin R %A Palmer, Cameron D %A Meng, Yan A %A Young, Taylor %A Farlow, Deborah N %A Schnabel, Renate B %A Marzi, Carola S %A Larkin, Emma %A Martin, Lisa W %A Bis, Joshua C %A Auer, Paul %A Ramachandran, Vasan S %A Gabriel, Stacey B %A Willis, Monte S %A Pankow, James S %A Papanicolaou, George J %A Rotter, Jerome I %A Ballantyne, Christie M %A Gross, Myron D %A Lettre, Guillaume %A Wilson, James G %A Peters, Ulrike %A Koenig, Wolfgang %A Tracy, Russell P %A Redline, Susan %A Reiner, Alex P %A Benjamin, Emelia J %A Lange, Leslie A %K Adult %K African Americans %K Aged %K Biomarkers %K C-Reactive Protein %K Cardiovascular Diseases %K CD36 Antigens %K Female %K Genetic Loci %K Genetic Predisposition to Disease %K Genetics, Population %K Genome-Wide Association Study %K Humans %K Meta-Analysis as Topic %K Middle Aged %K Polymorphism, Single Nucleotide %K Risk Factors %X

C-reactive protein (CRP) is a heritable biomarker of systemic inflammation and a predictor of cardiovascular disease (CVD). Large-scale genetic association studies for CRP have largely focused on individuals of European descent. We sought to uncover novel genetic variants for CRP in a multiethnic sample using the ITMAT Broad-CARe (IBC) array, a custom 50,000 SNP gene-centric array having dense coverage of over 2,000 candidate CVD genes. We performed analyses on 7,570 African Americans (AA) from the Candidate gene Association Resource (CARe) study and race-combined meta-analyses that included 29,939 additional individuals of European descent from CARe, the Women's Health Initiative (WHI) and KORA studies. We observed array-wide significance (p < 2.2 × 10(-6)) for four loci in AA, three of which have been reported previously in individuals of European descent (IL6R, p = 2.0 × 10(-6); CRP, p = 4.2 × 10(-71); APOE, p = 1.6 × 10(-6)). The fourth significant locus, CD36 (p = 1.6 × 10(-6)), was observed at a functional variant (rs3211938) that is extremely rare in individuals of European descent. We replicated the CD36 finding (p = 1.8 × 10(-5)) in an independent sample of 8,041 AA women from WHI; a meta-analysis combining the CARe and WHI AA results at rs3211938 reached genome-wide significance (p = 1.5 × 10(-10)). In the race-combined meta-analyses, 13 loci reached significance, including ten (CRP, TOMM40/APOE/APOC1, HNF1A, LEPR, GCKR, IL6R, IL1RN, NLRP3, HNF4A and BAZ1B/BCL7B) previously associated with CRP, and one (ARNTL) previously reported to be nominally associated with CRP. Two novel loci were also detected (RPS6KB1, p = 2.0 × 10(-6); CD36, p = 1.4 × 10(-6)). These results highlight both shared and unique genetic risk factors for CRP in AA compared to populations of European descent.

%B Hum Genet %V 133 %P 985-95 %8 2014 Aug %G eng %N 8 %1 http://www.ncbi.nlm.nih.gov/pubmed/24643644?dopt=Abstract %R 10.1007/s00439-014-1439-z %0 Journal Article %J PLoS One %D 2014 %T Large-scale genome-wide association studies and meta-analyses of longitudinal change in adult lung function. %A Tang, Wenbo %A Kowgier, Matthew %A Loth, Daan W %A Soler Artigas, Maria %A Joubert, Bonnie R %A Hodge, Emily %A Gharib, Sina A %A Smith, Albert V %A Ruczinski, Ingo %A Gudnason, Vilmundur %A Mathias, Rasika A %A Harris, Tamara B %A Hansel, Nadia N %A Launer, Lenore J %A Barnes, Kathleen C %A Hansen, Joyanna G %A Albrecht, Eva %A Aldrich, Melinda C %A Allerhand, Michael %A Barr, R Graham %A Brusselle, Guy G %A Couper, David J %A Curjuric, Ivan %A Davies, Gail %A Deary, Ian J %A Dupuis, Josée %A Fall, Tove %A Foy, Millennia %A Franceschini, Nora %A Gao, Wei %A Gläser, Sven %A Gu, Xiangjun %A Hancock, Dana B %A Heinrich, Joachim %A Hofman, Albert %A Imboden, Medea %A Ingelsson, Erik %A James, Alan %A Karrasch, Stefan %A Koch, Beate %A Kritchevsky, Stephen B %A Kumar, Ashish %A Lahousse, Lies %A Li, Guo %A Lind, Lars %A Lindgren, Cecilia %A Liu, Yongmei %A Lohman, Kurt %A Lumley, Thomas %A McArdle, Wendy L %A Meibohm, Bernd %A Morris, Andrew P %A Morrison, Alanna C %A Musk, Bill %A North, Kari E %A Palmer, Lyle J %A Probst-Hensch, Nicole M %A Psaty, Bruce M %A Rivadeneira, Fernando %A Rotter, Jerome I %A Schulz, Holger %A Smith, Lewis J %A Sood, Akshay %A Starr, John M %A Strachan, David P %A Teumer, Alexander %A Uitterlinden, André G %A Völzke, Henry %A Voorman, Arend %A Wain, Louise V %A Wells, Martin T %A Wilk, Jemma B %A Williams, O Dale %A Heckbert, Susan R %A Stricker, Bruno H %A London, Stephanie J %A Fornage, Myriam %A Tobin, Martin D %A O'Connor, George T %A Hall, Ian P %A Cassano, Patricia A %K Adult %K Chromosomes, Human, Pair 11 %K Female %K Gene Expression Regulation %K Genetic Loci %K Genome-Wide Association Study %K Humans %K Longitudinal Studies %K Male %K Respiration %X

BACKGROUND: Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function.

METHODS: We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis.

RESULTS: The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P  =  5.71 × 10(-7)). In addition, meta-analysis using the five cohorts with ≥3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P  =  2.18 × 10(-8)) at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively.

CONCLUSIONS: In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function.

%B PLoS One %V 9 %P e100776 %8 2014 %G eng %N 7 %1 http://www.ncbi.nlm.nih.gov/pubmed/24983941?dopt=Abstract %R 10.1371/journal.pone.0100776 %0 Journal Article %J J Am Heart Assoc %D 2014 %T A low-frequency variant in MAPK14 provides mechanistic evidence of a link with myeloperoxidase: a prognostic cardiovascular risk marker. %A Waterworth, Dawn M %A Li, Li %A Scott, Robert %A Warren, Liling %A Gillson, Christopher %A Aponte, Jennifer %A Sarov-Blat, Lea %A Sprecher, Dennis %A Dupuis, Josée %A Reiner, Alex %A Psaty, Bruce M %A Tracy, Russell P %A Lin, Honghuang %A McPherson, Ruth %A Chissoe, Stephanie %A Wareham, Nick %A Ehm, Margaret G %K Adult %K Aged %K Cardiovascular Diseases %K Dyslipidemias %K Exome %K Female %K Genotype %K Humans %K Linear Models %K Logistic Models %K Male %K Metabolic Syndrome X %K Middle Aged %K Mitogen-Activated Protein Kinase 11 %K Mitogen-Activated Protein Kinase 14 %K Obesity %K Peroxidase %K Polymorphism, Single Nucleotide %K Prognosis %K Risk Factors %K Sequence Analysis, DNA %X

BACKGROUND: Genetics can be used to predict drug effects and generate hypotheses around alternative indications. To support Losmapimod, a p38 mitogen-activated protein kinase inhibitor in development for acute coronary syndrome, we characterized gene variation in MAPK11/14 genes by exome sequencing and follow-up genotyping or imputation in participants well-phenotyped for cardiovascular and metabolic traits.

METHODS AND RESULTS: Investigation of genetic variation in MAPK11 and MAPK14 genes using additive genetic models in linear or logistic regression with cardiovascular, metabolic, and biomarker phenotypes highlighted an association of RS2859144 in MAPK14 with myeloperoxidase in a dyslipidemic population (Genetic Epidemiology of Metabolic Syndrome Study), P=2.3×10(-6)). This variant (or proxy) was consistently associated with myeloperoxidase in the Framingham Heart Study and Cardiovascular Health Study studies (replication meta-P=0.003), leading to a meta-P value of 9.96×10(-7) in the 3 dyslipidemic groups. The variant or its proxy was then profiled in additional population-based cohorts (up to a total of 58 930 subjects) including Cohorte Lausannoise, Ely, Fenland, European Prospective Investigation of Cancer, London Life Sciences Prospective Population Study, and the Genetics of Obesity Associations study obesity case-control for up to 40 cardiovascular and metabolic traits. Overall analysis identified the same single nucleotide polymorphisms to be nominally associated consistently with glomerular filtration rate (P=0.002) and risk of obesity (body mass index ≥30 kg/m(2), P=0.004).

CONCLUSIONS: As myeloperoxidase is a prognostic marker of coronary events, the MAPK14 variant may provide a mechanistic link between p38 map kinase and these events, providing information consistent with current indication of Losmapimod for acute coronary syndrome. If replicated, the association with glomerular filtration rate, along with previous biological findings, also provides support for kidney diseases as alternative indications.

%B J Am Heart Assoc %V 3 %8 2014 Aug %G eng %N 4 %1 http://www.ncbi.nlm.nih.gov/pubmed/25164947?dopt=Abstract %R 10.1161/JAHA.114.001074 %0 Journal Article %J Circ Cardiovasc Genet %D 2014 %T Strategies to design and analyze targeted sequencing data: cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study. %A Lin, Honghuang %A Wang, Min %A Brody, Jennifer A %A Bis, Joshua C %A Dupuis, Josée %A Lumley, Thomas %A McKnight, Barbara %A Rice, Kenneth M %A Sitlani, Colleen M %A Reid, Jeffrey G %A Bressler, Jan %A Liu, Xiaoming %A Davis, Brian C %A Johnson, Andrew D %A O'Donnell, Christopher J %A Kovar, Christie L %A Dinh, Huyen %A Wu, Yuanqing %A Newsham, Irene %A Chen, Han %A Broka, Andi %A DeStefano, Anita L %A Gupta, Mayetri %A Lunetta, Kathryn L %A Liu, Ching-Ti %A White, Charles C %A Xing, Chuanhua %A Zhou, Yanhua %A Benjamin, Emelia J %A Schnabel, Renate B %A Heckbert, Susan R %A Psaty, Bruce M %A Muzny, Donna M %A Cupples, L Adrienne %A Morrison, Alanna C %A Boerwinkle, Eric %K Adult %K Aged %K Aged, 80 and over %K Aging %K Cohort Studies %K Female %K Genetic Variation %K Genome-Wide Association Study %K Genomics %K Heart Diseases %K Humans %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Research Design %K Sequence Analysis, DNA %X

BACKGROUND: Genome-wide association studies have identified thousands of genetic variants that influence a variety of diseases and health-related quantitative traits. However, the causal variants underlying the majority of genetic associations remain unknown. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study aims to follow up genome-wide association study signals and identify novel associations of the allelic spectrum of identified variants with cardiovascular-related traits.

METHODS AND RESULTS: The study included 4231 participants from 3 CHARGE cohorts: the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, and the Framingham Heart Study. We used a case-cohort design in which we selected both a random sample of participants and participants with extreme phenotypes for each of 14 traits. We sequenced and analyzed 77 genomic loci, which had previously been associated with ≥1 of 14 phenotypes. A total of 52 736 variants were characterized by sequencing and passed our stringent quality control criteria. For common variants (minor allele frequency ≥1%), we performed unweighted regression analyses to obtain P values for associations and weighted regression analyses to obtain effect estimates that accounted for the sampling design. For rare variants, we applied 2 approaches: collapsed aggregate statistics and joint analysis of variants using the sequence kernel association test.

CONCLUSIONS: We sequenced 77 genomic loci in participants from 3 cohorts. We established a set of filters to identify high-quality variants and implemented statistical and bioinformatics strategies to analyze the sequence data and identify potentially functional variants within genome-wide association study loci.

%B Circ Cardiovasc Genet %V 7 %P 335-43 %8 2014 Jun %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/24951659?dopt=Abstract %R 10.1161/CIRCGENETICS.113.000350 %0 Journal Article %J Hum Mol Genet %D 2015 %T Association of exome sequences with plasma C-reactive protein levels in >9000 participants. %A Schick, Ursula M %A Auer, Paul L %A Bis, Joshua C %A Lin, Honghuang %A Wei, Peng %A Pankratz, Nathan %A Lange, Leslie A %A Brody, Jennifer %A Stitziel, Nathan O %A Kim, Daniel S %A Carlson, Christopher S %A Fornage, Myriam %A Haessler, Jeffery %A Hsu, Li %A Jackson, Rebecca D %A Kooperberg, Charles %A Leal, Suzanne M %A Psaty, Bruce M %A Boerwinkle, Eric %A Tracy, Russell %A Ardissino, Diego %A Shah, Svati %A Willer, Cristen %A Loos, Ruth %A Melander, Olle %A McPherson, Ruth %A Hovingh, Kees %A Reilly, Muredach %A Watkins, Hugh %A Girelli, Domenico %A Fontanillas, Pierre %A Chasman, Daniel I %A Gabriel, Stacey B %A Gibbs, Richard %A Nickerson, Deborah A %A Kathiresan, Sekar %A Peters, Ulrike %A Dupuis, Josée %A Wilson, James G %A Rich, Stephen S %A Morrison, Alanna C %A Benjamin, Emelia J %A Gross, Myron D %A Reiner, Alex P %K Adult %K African Americans %K C-Reactive Protein %K Cardiovascular Diseases %K Cohort Studies %K European Continental Ancestry Group %K Exome %K Female %K Gene Frequency %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Hepatocyte Nuclear Factor 1-alpha %K Humans %K Male %K Plasma %K Polymorphism, Single Nucleotide %K Receptors, Interleukin-6 %K Risk Factors %X

C-reactive protein (CRP) concentration is a heritable systemic marker of inflammation that is associated with cardiovascular disease risk. Genome-wide association studies have identified CRP-associated common variants associated in ∼25 genes. Our aims were to apply exome sequencing to (1) assess whether the candidate loci contain rare coding variants associated with CRP levels and (2) perform an exome-wide search for rare variants in novel genes associated with CRP levels. We exome-sequenced 6050 European-Americans (EAs) and 3109 African-Americans (AAs) from the NHLBI-ESP and the CHARGE consortia, and performed association tests of sequence data with measured CRP levels. In single-variant tests across candidate loci, a novel rare (minor allele frequency = 0.16%) CRP-coding variant (rs77832441-A; p.Thr59Met) was associated with 53% lower mean CRP levels (P = 2.9 × 10(-6)). We replicated the association of rs77832441 in an exome array analysis of 11 414 EAs (P = 3.0 × 10(-15)). Despite a strong effect on CRP levels, rs77832441 was not associated with inflammation-related phenotypes including coronary heart disease. We also found evidence for an AA-specific association of APOE-ε2 rs7214 with higher CRP levels. At the exome-wide significance level (P < 5.0 × 10(-8)), we confirmed associations for reported common variants of HNF1A, CRP, IL6R and TOMM40-APOE. In gene-based tests, a burden of rare/lower frequency variation in CRP in EAs (P ≤ 6.8 × 10(-4)) and in retinoic acid receptor-related orphan receptor α (RORA) in AAs (P = 1.7 × 10(-3)) were associated with CRP levels at the candidate gene level (P < 2.0 × 10(-3)). This inquiry did not elucidate novel genes, but instead demonstrated that variants distributed across the allele frequency spectrum within candidate genes contribute to CRP levels.

%B Hum Mol Genet %V 24 %P 559-71 %8 2015 Jan 15 %G eng %N 2 %1 http://www.ncbi.nlm.nih.gov/pubmed/25187575?dopt=Abstract %R 10.1093/hmg/ddu450 %0 Journal Article %J Hum Mol Genet %D 2015 %T Integrative pathway genomics of lung function and airflow obstruction. %A Gharib, Sina A %A Loth, Daan W %A Soler Artigas, Maria %A Birkland, Timothy P %A Wilk, Jemma B %A Wain, Louise V %A Brody, Jennifer A %A Obeidat, Ma'en %A Hancock, Dana B %A Tang, Wenbo %A Rawal, Rajesh %A Boezen, H Marike %A Imboden, Medea %A Huffman, Jennifer E %A Lahousse, Lies %A Alves, Alexessander C %A Manichaikul, Ani %A Hui, Jennie %A Morrison, Alanna C %A Ramasamy, Adaikalavan %A Smith, Albert Vernon %A Gudnason, Vilmundur %A Surakka, Ida %A Vitart, Veronique %A Evans, David M %A Strachan, David P %A Deary, Ian J %A Hofman, Albert %A Gläser, Sven %A Wilson, James F %A North, Kari E %A Zhao, Jing Hua %A Heckbert, Susan R %A Jarvis, Deborah L %A Probst-Hensch, Nicole %A Schulz, Holger %A Barr, R Graham %A Jarvelin, Marjo-Riitta %A O'Connor, George T %A Kähönen, Mika %A Cassano, Patricia A %A Hysi, Pirro G %A Dupuis, Josée %A Hayward, Caroline %A Psaty, Bruce M %A Hall, Ian P %A Parks, William C %A Tobin, Martin D %A London, Stephanie J %K Airway Obstruction %K Animals %K Cell Proliferation %K European Continental Ancestry Group %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Genomics %K Humans %K Immune System %K Lung %K Male %K Metabolic Networks and Pathways %K Mice %K Phenotype %K Polymorphism, Single Nucleotide %K Signal Transduction %X

Chronic respiratory disorders are important contributors to the global burden of disease. Genome-wide association studies (GWASs) of lung function measures have identified several trait-associated loci, but explain only a modest portion of the phenotypic variability. We postulated that integrating pathway-based methods with GWASs of pulmonary function and airflow obstruction would identify a broader repertoire of genes and processes influencing these traits. We performed two independent GWASs of lung function and applied gene set enrichment analysis to one of the studies and validated the results using the second GWAS. We identified 131 significantly enriched gene sets associated with lung function and clustered them into larger biological modules involved in diverse processes including development, immunity, cell signaling, proliferation and arachidonic acid. We found that enrichment of gene sets was not driven by GWAS-significant variants or loci, but instead by those with less stringent association P-values. Next, we applied pathway enrichment analysis to a meta-analyzed GWAS of airflow obstruction. We identified several biologic modules that functionally overlapped with those associated with pulmonary function. However, differences were also noted, including enrichment of extracellular matrix (ECM) processes specifically in the airflow obstruction study. Network analysis of the ECM module implicated a candidate gene, matrix metalloproteinase 10 (MMP10), as a putative disease target. We used a knockout mouse model to functionally validate MMP10's role in influencing lung's susceptibility to cigarette smoke-induced emphysema. By integrating pathway analysis with population-based genomics, we unraveled biologic processes underlying pulmonary function traits and identified a candidate gene for obstructive lung disease.

%B Hum Mol Genet %V 24 %P 6836-48 %8 2015 Dec 1 %G eng %N 23 %1 http://www.ncbi.nlm.nih.gov/pubmed/26395457?dopt=Abstract %R 10.1093/hmg/ddv378 %0 Journal Article %J Nat Commun %D 2015 %T Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility. %A Wessel, Jennifer %A Chu, Audrey Y %A Willems, Sara M %A Wang, Shuai %A Yaghootkar, Hanieh %A Brody, Jennifer A %A Dauriz, Marco %A Hivert, Marie-France %A Raghavan, Sridharan %A Lipovich, Leonard %A Hidalgo, Bertha %A Fox, Keolu %A Huffman, Jennifer E %A An, Ping %A Lu, Yingchang %A Rasmussen-Torvik, Laura J %A Grarup, Niels %A Ehm, Margaret G %A Li, Li %A Baldridge, Abigail S %A Stančáková, Alena %A Abrol, Ravinder %A Besse, Céline %A Boland, Anne %A Bork-Jensen, Jette %A Fornage, Myriam %A Freitag, Daniel F %A Garcia, Melissa E %A Guo, Xiuqing %A Hara, Kazuo %A Isaacs, Aaron %A Jakobsdottir, Johanna %A Lange, Leslie A %A Layton, Jill C %A Li, Man %A Hua Zhao, Jing %A Meidtner, Karina %A Morrison, Alanna C %A Nalls, Mike A %A Peters, Marjolein J %A Sabater-Lleal, Maria %A Schurmann, Claudia %A Silveira, Angela %A Smith, Albert V %A Southam, Lorraine %A Stoiber, Marcus H %A Strawbridge, Rona J %A Taylor, Kent D %A Varga, Tibor V %A Allin, Kristine H %A Amin, Najaf %A Aponte, Jennifer L %A Aung, Tin %A Barbieri, Caterina %A Bihlmeyer, Nathan A %A Boehnke, Michael %A Bombieri, Cristina %A Bowden, Donald W %A Burns, Sean M %A Chen, Yuning %A Chen, Yii-DerI %A Cheng, Ching-Yu %A Correa, Adolfo %A Czajkowski, Jacek %A Dehghan, Abbas %A Ehret, Georg B %A Eiriksdottir, Gudny %A Escher, Stefan A %A Farmaki, Aliki-Eleni %A Frånberg, Mattias %A Gambaro, Giovanni %A Giulianini, Franco %A Goddard, William A %A Goel, Anuj %A Gottesman, Omri %A Grove, Megan L %A Gustafsson, Stefan %A Hai, Yang %A Hallmans, Göran %A Heo, Jiyoung %A Hoffmann, Per %A Ikram, Mohammad K %A Jensen, Richard A %A Jørgensen, Marit E %A Jørgensen, Torben %A Karaleftheri, Maria %A Khor, Chiea C %A Kirkpatrick, Andrea %A Kraja, Aldi T %A Kuusisto, Johanna %A Lange, Ethan M %A Lee, I T %A Lee, Wen-Jane %A Leong, Aaron %A Liao, Jiemin %A Liu, Chunyu %A Liu, Yongmei %A Lindgren, Cecilia M %A Linneberg, Allan %A Malerba, Giovanni %A Mamakou, Vasiliki %A Marouli, Eirini %A Maruthur, Nisa M %A Matchan, Angela %A McKean-Cowdin, Roberta %A McLeod, Olga %A Metcalf, Ginger A %A Mohlke, Karen L %A Muzny, Donna M %A Ntalla, Ioanna %A Palmer, Nicholette D %A Pasko, Dorota %A Peter, Andreas %A Rayner, Nigel W %A Renstrom, Frida %A Rice, Ken %A Sala, Cinzia F %A Sennblad, Bengt %A Serafetinidis, Ioannis %A Smith, Jennifer A %A Soranzo, Nicole %A Speliotes, Elizabeth K %A Stahl, Eli A %A Stirrups, Kathleen %A Tentolouris, Nikos %A Thanopoulou, Anastasia %A Torres, Mina %A Traglia, Michela %A Tsafantakis, Emmanouil %A Javad, Sundas %A Yanek, Lisa R %A Zengini, Eleni %A Becker, Diane M %A Bis, Joshua C %A Brown, James B %A Cupples, L Adrienne %A Hansen, Torben %A Ingelsson, Erik %A Karter, Andrew J %A Lorenzo, Carlos %A Mathias, Rasika A %A Norris, Jill M %A Peloso, Gina M %A Sheu, Wayne H-H %A Toniolo, Daniela %A Vaidya, Dhananjay %A Varma, Rohit %A Wagenknecht, Lynne E %A Boeing, Heiner %A Bottinger, Erwin P %A Dedoussis, George %A Deloukas, Panos %A Ferrannini, Ele %A Franco, Oscar H %A Franks, Paul W %A Gibbs, Richard A %A Gudnason, Vilmundur %A Hamsten, Anders %A Harris, Tamara B %A Hattersley, Andrew T %A Hayward, Caroline %A Hofman, Albert %A Jansson, Jan-Håkan %A Langenberg, Claudia %A Launer, Lenore J %A Levy, Daniel %A Oostra, Ben A %A O'Donnell, Christopher J %A O'Rahilly, Stephen %A Padmanabhan, Sandosh %A Pankow, James S %A Polasek, Ozren %A Province, Michael A %A Rich, Stephen S %A Ridker, Paul M %A Rudan, Igor %A Schulze, Matthias B %A Smith, Blair H %A Uitterlinden, André G %A Walker, Mark %A Watkins, Hugh %A Wong, Tien Y %A Zeggini, Eleftheria %A Laakso, Markku %A Borecki, Ingrid B %A Chasman, Daniel I %A Pedersen, Oluf %A Psaty, Bruce M %A Tai, E Shyong %A van Duijn, Cornelia M %A Wareham, Nicholas J %A Waterworth, Dawn M %A Boerwinkle, Eric %A Kao, W H Linda %A Florez, Jose C %A Loos, Ruth J F %A Wilson, James G %A Frayling, Timothy M %A Siscovick, David S %A Dupuis, Josée %A Rotter, Jerome I %A Meigs, James B %A Scott, Robert A %A Goodarzi, Mark O %K African Continental Ancestry Group %K Blood Glucose %K Diabetes Mellitus, Type 2 %K European Continental Ancestry Group %K Exome %K Fasting %K Genetic Association Studies %K Genetic Loci %K Genetic Predisposition to Disease %K Genetic Variation %K Glucagon-Like Peptide-1 Receptor %K Glucose-6-Phosphatase %K Humans %K Insulin %K Mutation Rate %K Oligonucleotide Array Sequence Analysis %K Polymorphism, Single Nucleotide %X

Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.

%B Nat Commun %V 6 %P 5897 %8 2015 %G eng %1 http://www.ncbi.nlm.nih.gov/pubmed/25631608?dopt=Abstract %R 10.1038/ncomms6897 %0 Journal Article %J Eur J Hum Genet %D 2016 %T Association of the IGF1 gene with fasting insulin levels. %A Willems, Sara M %A Cornes, Belinda K %A Brody, Jennifer A %A Morrison, Alanna C %A Lipovich, Leonard %A Dauriz, Marco %A Chen, Yuning %A Liu, Ching-Ti %A Rybin, Denis V %A Gibbs, Richard A %A Muzny, Donna %A Pankow, James S %A Psaty, Bruce M %A Boerwinkle, Eric %A Rotter, Jerome I %A Siscovick, David S %A Vasan, Ramachandran S %A Kaplan, Robert C %A Isaacs, Aaron %A Dupuis, Josée %A van Duijn, Cornelia M %A Meigs, James B %X

Insulin-like growth factor 1 (IGF-I) has been associated with insulin resistance. Genome-wide association studies (GWASs) of fasting insulin (FI) identified single-nucleotide variants (SNVs) near the IGF1 gene, raising two hypotheses: (1) these associations are mediated by IGF-I levels and (2) these noncoding variants either tag other functional variants in the region or are directly functional. In our study, analyses including 5141 individuals from population-based cohorts suggest that FI associations near IGF1 are not mediated by IGF-I. Analyses of targeted sequencing data in 3539 individuals reveal a large number of novel rare variants at the IGF1 locus and show a FI association with a subset of rare nonsynonymous variants (PSKAT=5.7 × 10(-4)). Conditional analyses suggest that this association is partly explained by the GWAS signal and the presence of a residual independent rare variant effect (Pconditional=0.019). Annotation using ENCODE data suggests that the GWAS variants may have a direct functional role in insulin biology. In conclusion, our study provides insight into variation present at the IGF1 locus and into the genetic architecture underlying FI levels, suggesting that FI associations of SNVs near IGF1 are not mediated by IGF-I and suggesting a role for both rare nonsynonymous and common functional variants in insulin biology.

%B Eur J Hum Genet %V 24 %P 1337-43 %8 2016 Aug %G eng %N 9 %1 http://www.ncbi.nlm.nih.gov/pubmed/26860063?dopt=Abstract %R 10.1038/ejhg.2016.4 %0 Journal Article %J Genome Biol %D 2016 %T DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases. %A Ligthart, Symen %A Marzi, Carola %A Aslibekyan, Stella %A Mendelson, Michael M %A Conneely, Karen N %A Tanaka, Toshiko %A Colicino, Elena %A Waite, Lindsay L %A Joehanes, Roby %A Guan, Weihua %A Brody, Jennifer A %A Elks, Cathy %A Marioni, Riccardo %A Jhun, Min A %A Agha, Golareh %A Bressler, Jan %A Ward-Caviness, Cavin K %A Chen, Brian H %A Huan, Tianxiao %A Bakulski, Kelly %A Salfati, Elias L %A Fiorito, Giovanni %A Wahl, Simone %A Schramm, Katharina %A Sha, Jin %A Hernandez, Dena G %A Just, Allan C %A Smith, Jennifer A %A Sotoodehnia, Nona %A Pilling, Luke C %A Pankow, James S %A Tsao, Phil S %A Liu, Chunyu %A Zhao, Wei %A Guarrera, Simonetta %A Michopoulos, Vasiliki J %A Smith, Alicia K %A Peters, Marjolein J %A Melzer, David %A Vokonas, Pantel %A Fornage, Myriam %A Prokisch, Holger %A Bis, Joshua C %A Chu, Audrey Y %A Herder, Christian %A Grallert, Harald %A Yao, Chen %A Shah, Sonia %A McRae, Allan F %A Lin, Honghuang %A Horvath, Steve %A Fallin, Daniele %A Hofman, Albert %A Wareham, Nicholas J %A Wiggins, Kerri L %A Feinberg, Andrew P %A Starr, John M %A Visscher, Peter M %A Murabito, Joanne M %A Kardia, Sharon L R %A Absher, Devin M %A Binder, Elisabeth B %A Singleton, Andrew B %A Bandinelli, Stefania %A Peters, Annette %A Waldenberger, Melanie %A Matullo, Giuseppe %A Schwartz, Joel D %A Demerath, Ellen W %A Uitterlinden, André G %A van Meurs, Joyce B J %A Franco, Oscar H %A Chen, Yii-Der Ida %A Levy, Daniel %A Turner, Stephen T %A Deary, Ian J %A Ressler, Kerry J %A Dupuis, Josée %A Ferrucci, Luigi %A Ong, Ken K %A Assimes, Themistocles L %A Boerwinkle, Eric %A Koenig, Wolfgang %A Arnett, Donna K %A Baccarelli, Andrea A %A Benjamin, Emelia J %A Dehghan, Abbas %X

BACKGROUND: Chronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation.

RESULTS: We performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 × 10(-7)) in the discovery panel of European ancestry and replicated (P < 2.29 × 10(-4)) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 × 10(-5)), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 × 10(-3)), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58 × 10(-5)). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants.

CONCLUSION: We have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation.

%B Genome Biol %V 17 %P 255 %8 2016 Dec 12 %G eng %N 1 %R 10.1186/s13059-016-1119-5 %0 Journal Article %J Genet Epidemiol %D 2016 %T General Framework for Meta-Analysis of Haplotype Association Tests. %A Wang, Shuai %A Zhao, Jing Hua %A An, Ping %A Guo, Xiuqing %A Jensen, Richard A %A Marten, Jonathan %A Huffman, Jennifer E %A Meidtner, Karina %A Boeing, Heiner %A Campbell, Archie %A Rice, Kenneth M %A Scott, Robert A %A Yao, Jie %A Schulze, Matthias B %A Wareham, Nicholas J %A Borecki, Ingrid B %A Province, Michael A %A Rotter, Jerome I %A Hayward, Caroline %A Goodarzi, Mark O %A Meigs, James B %A Dupuis, Josée %X

For complex traits, most associated single nucleotide variants (SNV) discovered to date have a small effect, and detection of association is only possible with large sample sizes. Because of patient confidentiality concerns, it is often not possible to pool genetic data from multiple cohorts, and meta-analysis has emerged as the method of choice to combine results from multiple studies. Many meta-analysis methods are available for single SNV analyses. As new approaches allow the capture of low frequency and rare genetic variation, it is of interest to jointly consider multiple variants to improve power. However, for the analysis of haplotypes formed by multiple SNVs, meta-analysis remains a challenge, because different haplotypes may be observed across studies. We propose a two-stage meta-analysis approach to combine haplotype analysis results. In the first stage, each cohort estimate haplotype effect sizes in a regression framework, accounting for relatedness among observations if appropriate. For the second stage, we use a multivariate generalized least square meta-analysis approach to combine haplotype effect estimates from multiple cohorts. Haplotype-specific association tests and a global test of independence between haplotypes and traits are obtained within our framework. We demonstrate through simulation studies that we control the type-I error rate, and our approach is more powerful than inverse variance weighted meta-analysis of single SNV analysis when haplotype effects are present. We replicate a published haplotype association between fasting glucose-associated locus (G6PC2) and fasting glucose in seven studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and we provide more precise haplotype effect estimates.

%B Genet Epidemiol %V 40 %P 244-52 %8 2016 Apr %G eng %N 3 %R 10.1002/gepi.21959 %0 Journal Article %J Diabetes %D 2016 %T Genome-Wide Association Study of the Modified Stumvoll Insulin Sensitivity Index Identifies BCL2 and FAM19A2 as Novel Insulin Sensitivity Loci. %A Walford, Geoffrey A %A Gustafsson, Stefan %A Rybin, Denis %A Stančáková, Alena %A Chen, Han %A Liu, Ching-Ti %A Hong, Jaeyoung %A Jensen, Richard A %A Rice, Ken %A Morris, Andrew P %A Mägi, Reedik %A Tönjes, Anke %A Prokopenko, Inga %A Kleber, Marcus E %A Delgado, Graciela %A Silbernagel, Günther %A Jackson, Anne U %A Appel, Emil V %A Grarup, Niels %A Lewis, Joshua P %A Montasser, May E %A Landenvall, Claes %A Staiger, Harald %A Luan, Jian'an %A Frayling, Timothy M %A Weedon, Michael N %A Xie, Weijia %A Morcillo, Sonsoles %A Martínez-Larrad, María Teresa %A Biggs, Mary L %A Chen, Yii-Der Ida %A Corbaton-Anchuelo, Arturo %A Færch, Kristine %A Gómez-Zumaquero, Juan Miguel %A Goodarzi, Mark O %A Kizer, Jorge R %A Koistinen, Heikki A %A Leong, Aaron %A Lind, Lars %A Lindgren, Cecilia %A Machicao, Fausto %A Manning, Alisa K %A Martín-Núñez, Gracia María %A Rojo-Martínez, Gemma %A Rotter, Jerome I %A Siscovick, David S %A Zmuda, Joseph M %A Zhang, Zhongyang %A Serrano-Ríos, Manuel %A Smith, Ulf %A Soriguer, Federico %A Hansen, Torben %A Jørgensen, Torben J %A Linnenberg, Allan %A Pedersen, Oluf %A Walker, Mark %A Langenberg, Claudia %A Scott, Robert A %A Wareham, Nicholas J %A Fritsche, Andreas %A Häring, Hans-Ulrich %A Stefan, Norbert %A Groop, Leif %A O'Connell, Jeff R %A Boehnke, Michael %A Bergman, Richard N %A Collins, Francis S %A Mohlke, Karen L %A Tuomilehto, Jaakko %A März, Winfried %A Kovacs, Peter %A Stumvoll, Michael %A Psaty, Bruce M %A Kuusisto, Johanna %A Laakso, Markku %A Meigs, James B %A Dupuis, Josée %A Ingelsson, Erik %A Florez, Jose C %X

Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 × 10(-11)), rs12454712 (BCL2; P = 2.7 × 10(-8)), and rs10506418 (FAM19A2; P = 1.9 × 10(-8)). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci.

%B Diabetes %V 65 %P 3200-11 %8 2016 Oct %G eng %N 10 %1 http://www.ncbi.nlm.nih.gov/pubmed/27416945?dopt=Abstract %R 10.2337/db16-0199 %0 Journal Article %J Am J Hum Genet %D 2016 %T Trans-ethnic Meta-analysis and Functional Annotation Illuminates the Genetic Architecture of Fasting Glucose and Insulin. %A Liu, Ching-Ti %A Raghavan, Sridharan %A Maruthur, Nisa %A Kabagambe, Edmond Kato %A Hong, Jaeyoung %A Ng, Maggie C Y %A Hivert, Marie-France %A Lu, Yingchang %A An, Ping %A Bentley, Amy R %A Drolet, Anne M %A Gaulton, Kyle J %A Guo, Xiuqing %A Armstrong, Loren L %A Irvin, Marguerite R %A Li, Man %A Lipovich, Leonard %A Rybin, Denis V %A Taylor, Kent D %A Agyemang, Charles %A Palmer, Nicholette D %A Cade, Brian E %A Chen, Wei-Min %A Dauriz, Marco %A Delaney, Joseph A C %A Edwards, Todd L %A Evans, Daniel S %A Evans, Michele K %A Lange, Leslie A %A Leong, Aaron %A Liu, Jingmin %A Liu, Yongmei %A Nayak, Uma %A Patel, Sanjay R %A Porneala, Bianca C %A Rasmussen-Torvik, Laura J %A Snijder, Marieke B %A Stallings, Sarah C %A Tanaka, Toshiko %A Yanek, Lisa R %A Zhao, Wei %A Becker, Diane M %A Bielak, Lawrence F %A Biggs, Mary L %A Bottinger, Erwin P %A Bowden, Donald W %A Chen, Guanjie %A Correa, Adolfo %A Couper, David J %A Crawford, Dana C %A Cushman, Mary %A Eicher, John D %A Fornage, Myriam %A Franceschini, Nora %A Fu, Yi-Ping %A Goodarzi, Mark O %A Gottesman, Omri %A Hara, Kazuo %A Harris, Tamara B %A Jensen, Richard A %A Johnson, Andrew D %A Jhun, Min A %A Karter, Andrew J %A Keller, Margaux F %A Kho, Abel N %A Kizer, Jorge R %A Krauss, Ronald M %A Langefeld, Carl D %A Li, Xiaohui %A Liang, Jingling %A Liu, Simin %A Lowe, William L %A Mosley, Thomas H %A North, Kari E %A Pacheco, Jennifer A %A Peyser, Patricia A %A Patrick, Alan L %A Rice, Kenneth M %A Selvin, Elizabeth %A Sims, Mario %A Smith, Jennifer A %A Tajuddin, Salman M %A Vaidya, Dhananjay %A Wren, Mary P %A Yao, Jie %A Zhu, Xiaofeng %A Ziegler, Julie T %A Zmuda, Joseph M %A Zonderman, Alan B %A Zwinderman, Aeilko H %A Adeyemo, Adebowale %A Boerwinkle, Eric %A Ferrucci, Luigi %A Hayes, M Geoffrey %A Kardia, Sharon L R %A Miljkovic, Iva %A Pankow, James S %A Rotimi, Charles N %A Sale, Michèle M %A Wagenknecht, Lynne E %A Arnett, Donna K %A Chen, Yii-Der Ida %A Nalls, Michael A %A Province, Michael A %A Kao, W H Linda %A Siscovick, David S %A Psaty, Bruce M %A Wilson, James G %A Loos, Ruth J F %A Dupuis, Josée %A Rich, Stephen S %A Florez, Jose C %A Rotter, Jerome I %A Morris, Andrew P %A Meigs, James B %X

Knowledge of the genetic basis of the type 2 diabetes (T2D)-related quantitative traits fasting glucose (FG) and insulin (FI) in African ancestry (AA) individuals has been limited. In non-diabetic subjects of AA (n = 20,209) and European ancestry (EA; n = 57,292), we performed trans-ethnic (AA+EA) fine-mapping of 54 established EA FG or FI loci with detailed functional annotation, assessed their relevance in AA individuals, and sought previously undescribed loci through trans-ethnic (AA+EA) meta-analysis. We narrowed credible sets of variants driving association signals for 22/54 EA-associated loci; 18/22 credible sets overlapped with active islet-specific enhancers or transcription factor (TF) binding sites, and 21/22 contained at least one TF motif. Of the 54 EA-associated loci, 23 were shared between EA and AA. Replication with an additional 10,096 AA individuals identified two previously undescribed FI loci, chrX FAM133A (rs213676) and chr5 PELO (rs6450057). Trans-ethnic analyses with regulatory annotation illuminate the genetic architecture of glycemic traits and suggest gene regulation as a target to advance precision medicine for T2D. Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.

%B Am J Hum Genet %V 99 %P 56-75 %8 2016 Jul 7 %G eng %N 1 %1 http://www.ncbi.nlm.nih.gov/pubmed/27321945?dopt=Abstract %R 10.1016/j.ajhg.2016.05.006 %0 Journal Article %J Nat Genet %D 2017 %T Genetic loci associated with chronic obstructive pulmonary disease overlap with loci for lung function and pulmonary fibrosis. %A Hobbs, Brian D %A de Jong, Kim %A Lamontagne, Maxime %A Bossé, Yohan %A Shrine, Nick %A Artigas, Maria Soler %A Wain, Louise V %A Hall, Ian P %A Jackson, Victoria E %A Wyss, Annah B %A London, Stephanie J %A North, Kari E %A Franceschini, Nora %A Strachan, David P %A Beaty, Terri H %A Hokanson, John E %A Crapo, James D %A Castaldi, Peter J %A Chase, Robert P %A Bartz, Traci M %A Heckbert, Susan R %A Psaty, Bruce M %A Gharib, Sina A %A Zanen, Pieter %A Lammers, Jan W %A Oudkerk, Matthijs %A Groen, H J %A Locantore, Nicholas %A Tal-Singer, Ruth %A Rennard, Stephen I %A Vestbo, Jørgen %A Timens, Wim %A Paré, Peter D %A Latourelle, Jeanne C %A Dupuis, Josée %A O'Connor, George T %A Wilk, Jemma B %A Kim, Woo Jin %A Lee, Mi Kyeong %A Oh, Yeon-Mok %A Vonk, Judith M %A de Koning, Harry J %A Leng, Shuguang %A Belinsky, Steven A %A Tesfaigzi, Yohannes %A Manichaikul, Ani %A Wang, Xin-Qun %A Rich, Stephen S %A Barr, R Graham %A Sparrow, David %A Litonjua, Augusto A %A Bakke, Per %A Gulsvik, Amund %A Lahousse, Lies %A Brusselle, Guy G %A Stricker, Bruno H %A Uitterlinden, André G %A Ampleford, Elizabeth J %A Bleecker, Eugene R %A Woodruff, Prescott G %A Meyers, Deborah A %A Qiao, Dandi %A Lomas, David A %A Yim, Jae-Joon %A Kim, Deog Kyeom %A Hawrylkiewicz, Iwona %A Sliwinski, Pawel %A Hardin, Megan %A Fingerlin, Tasha E %A Schwartz, David A %A Postma, Dirkje S %A MacNee, William %A Tobin, Martin D %A Silverman, Edwin K %A Boezen, H Marike %A Cho, Michael H %X

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide. We performed a genetic association study in 15,256 cases and 47,936 controls, with replication of select top results (P < 5 × 10(-6)) in 9,498 cases and 9,748 controls. In the combined meta-analysis, we identified 22 loci associated at genome-wide significance, including 13 new associations with COPD. Nine of these 13 loci have been associated with lung function in general population samples, while 4 (EEFSEC, DSP, MTCL1, and SFTPD) are new. We noted two loci shared with pulmonary fibrosis (FAM13A and DSP) but that had opposite risk alleles for COPD. None of our loci overlapped with genome-wide associations for asthma, although one locus has been implicated in joint susceptibility to asthma and obesity. We also identified genetic correlation between COPD and asthma. Our findings highlight new loci associated with COPD, demonstrate the importance of specific loci associated with lung function to COPD, and identify potential regions of genetic overlap between COPD and other respiratory diseases.

%B Nat Genet %V 49 %P 426-432 %8 2017 Mar %G eng %N 3 %R 10.1038/ng.3752 %0 Journal Article %J PLoS Med %D 2017 %T Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis. %A Wheeler, Eleanor %A Leong, Aaron %A Liu, Ching-Ti %A Hivert, Marie-France %A Strawbridge, Rona J %A Podmore, Clara %A Li, Man %A Yao, Jie %A Sim, Xueling %A Hong, Jaeyoung %A Chu, Audrey Y %A Zhang, Weihua %A Wang, Xu %A Chen, Peng %A Maruthur, Nisa M %A Porneala, Bianca C %A Sharp, Stephen J %A Jia, Yucheng %A Kabagambe, Edmond K %A Chang, Li-Ching %A Chen, Wei-Min %A Elks, Cathy E %A Evans, Daniel S %A Fan, Qiao %A Giulianini, Franco %A Go, Min Jin %A Hottenga, Jouke-Jan %A Hu, Yao %A Jackson, Anne U %A Kanoni, Stavroula %A Kim, Young Jin %A Kleber, Marcus E %A Ladenvall, Claes %A Lecoeur, Cécile %A Lim, Sing-Hui %A Lu, Yingchang %A Mahajan, Anubha %A Marzi, Carola %A Nalls, Mike A %A Navarro, Pau %A Nolte, Ilja M %A Rose, Lynda M %A Rybin, Denis V %A Sanna, Serena %A Shi, Yuan %A Stram, Daniel O %A Takeuchi, Fumihiko %A Tan, Shu Pei %A van der Most, Peter J %A van Vliet-Ostaptchouk, Jana V %A Wong, Andrew %A Yengo, Loic %A Zhao, Wanting %A Goel, Anuj %A Martinez Larrad, Maria Teresa %A Radke, Dörte %A Salo, Perttu %A Tanaka, Toshiko %A van Iperen, Erik P A %A Abecasis, Goncalo %A Afaq, Saima %A Alizadeh, Behrooz Z %A Bertoni, Alain G %A Bonnefond, Amélie %A Böttcher, Yvonne %A Bottinger, Erwin P %A Campbell, Harry %A Carlson, Olga D %A Chen, Chien-Hsiun %A Cho, Yoon Shin %A Garvey, W Timothy %A Gieger, Christian %A Goodarzi, Mark O %A Grallert, Harald %A Hamsten, Anders %A Hartman, Catharina A %A Herder, Christian %A Hsiung, Chao Agnes %A Huang, Jie %A Igase, Michiya %A Isono, Masato %A Katsuya, Tomohiro %A Khor, Chiea-Chuen %A Kiess, Wieland %A Kohara, Katsuhiko %A Kovacs, Peter %A Lee, Juyoung %A Lee, Wen-Jane %A Lehne, Benjamin %A Li, Huaixing %A Liu, Jianjun %A Lobbens, Stephane %A Luan, Jian'an %A Lyssenko, Valeriya %A Meitinger, Thomas %A Miki, Tetsuro %A Miljkovic, Iva %A Moon, Sanghoon %A Mulas, Antonella %A Müller, Gabriele %A Müller-Nurasyid, Martina %A Nagaraja, Ramaiah %A Nauck, Matthias %A Pankow, James S %A Polasek, Ozren %A Prokopenko, Inga %A Ramos, Paula S %A Rasmussen-Torvik, Laura %A Rathmann, Wolfgang %A Rich, Stephen S %A Robertson, Neil R %A Roden, Michael %A Roussel, Ronan %A Rudan, Igor %A Scott, Robert A %A Scott, William R %A Sennblad, Bengt %A Siscovick, David S %A Strauch, Konstantin %A Sun, Liang %A Swertz, Morris %A Tajuddin, Salman M %A Taylor, Kent D %A Teo, Yik-Ying %A Tham, Yih Chung %A Tönjes, Anke %A Wareham, Nicholas J %A Willemsen, Gonneke %A Wilsgaard, Tom %A Hingorani, Aroon D %A Egan, Josephine %A Ferrucci, Luigi %A Hovingh, G Kees %A Jula, Antti %A Kivimaki, Mika %A Kumari, Meena %A Njølstad, Inger %A Palmer, Colin N A %A Serrano Ríos, Manuel %A Stumvoll, Michael %A Watkins, Hugh %A Aung, Tin %A Blüher, Matthias %A Boehnke, Michael %A Boomsma, Dorret I %A Bornstein, Stefan R %A Chambers, John C %A Chasman, Daniel I %A Chen, Yii-Der Ida %A Chen, Yduan-Tsong %A Cheng, Ching-Yu %A Cucca, Francesco %A de Geus, Eco J C %A Deloukas, Panos %A Evans, Michele K %A Fornage, Myriam %A Friedlander, Yechiel %A Froguel, Philippe %A Groop, Leif %A Gross, Myron D %A Harris, Tamara B %A Hayward, Caroline %A Heng, Chew-Kiat %A Ingelsson, Erik %A Kato, Norihiro %A Kim, Bong-Jo %A Koh, Woon-Puay %A Kooner, Jaspal S %A Körner, Antje %A Kuh, Diana %A Kuusisto, Johanna %A Laakso, Markku %A Lin, Xu %A Liu, Yongmei %A Loos, Ruth J F %A Magnusson, Patrik K E %A März, Winfried %A McCarthy, Mark I %A Oldehinkel, Albertine J %A Ong, Ken K %A Pedersen, Nancy L %A Pereira, Mark A %A Peters, Annette %A Ridker, Paul M %A Sabanayagam, Charumathi %A Sale, Michele %A Saleheen, Danish %A Saltevo, Juha %A Schwarz, Peter Eh %A Sheu, Wayne H H %A Snieder, Harold %A Spector, Timothy D %A Tabara, Yasuharu %A Tuomilehto, Jaakko %A van Dam, Rob M %A Wilson, James G %A Wilson, James F %A Wolffenbuttel, Bruce H R %A Wong, Tien Yin %A Wu, Jer-Yuarn %A Yuan, Jian-Min %A Zonderman, Alan B %A Soranzo, Nicole %A Guo, Xiuqing %A Roberts, David J %A Florez, Jose C %A Sladek, Robert %A Dupuis, Josée %A Morris, Andrew P %A Tai, E-Shyong %A Selvin, Elizabeth %A Rotter, Jerome I %A Langenberg, Claudia %A Barroso, Inês %A Meigs, James B %K Diabetes Mellitus, Type 2 %K Genetic Variation %K Genome-Wide Association Study %K Glycated Hemoglobin A %K Humans %K Phenotype %K Risk %X

BACKGROUND: Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.

METHODS & FINDINGS: Using genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 × 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.

CONCLUSIONS: As G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.

%B PLoS Med %V 14 %P e1002383 %8 2017 Sep %G eng %N 9 %R 10.1371/journal.pmed.1002383 %0 Journal Article %J Nat Genet %D 2017 %T Rare coding variants in PLCG2, ABI3, and TREM2 implicate microglial-mediated innate immunity in Alzheimer's disease. %A Sims, Rebecca %A van der Lee, Sven J %A Naj, Adam C %A Bellenguez, Céline %A Badarinarayan, Nandini %A Jakobsdottir, Johanna %A Kunkle, Brian W %A Boland, Anne %A Raybould, Rachel %A Bis, Joshua C %A Martin, Eden R %A Grenier-Boley, Benjamin %A Heilmann-Heimbach, Stefanie %A Chouraki, Vincent %A Kuzma, Amanda B %A Sleegers, Kristel %A Vronskaya, Maria %A Ruiz, Agustin %A Graham, Robert R %A Olaso, Robert %A Hoffmann, Per %A Grove, Megan L %A Vardarajan, Badri N %A Hiltunen, Mikko %A Nöthen, Markus M %A White, Charles C %A Hamilton-Nelson, Kara L %A Epelbaum, Jacques %A Maier, Wolfgang %A Choi, Seung-Hoan %A Beecham, Gary W %A Dulary, Cécile %A Herms, Stefan %A Smith, Albert V %A Funk, Cory C %A Derbois, Céline %A Forstner, Andreas J %A Ahmad, Shahzad %A Li, Hongdong %A Bacq, Delphine %A Harold, Denise %A Satizabal, Claudia L %A Valladares, Otto %A Squassina, Alessio %A Thomas, Rhodri %A Brody, Jennifer A %A Qu, Liming %A Sánchez-Juan, Pascual %A Morgan, Taniesha %A Wolters, Frank J %A Zhao, Yi %A Garcia, Florentino Sanchez %A Denning, Nicola %A Fornage, Myriam %A Malamon, John %A Naranjo, Maria Candida Deniz %A Majounie, Elisa %A Mosley, Thomas H %A Dombroski, Beth %A Wallon, David %A Lupton, Michelle K %A Dupuis, Josée %A Whitehead, Patrice %A Fratiglioni, Laura %A Medway, Christopher %A Jian, Xueqiu %A Mukherjee, Shubhabrata %A Keller, Lina %A Brown, Kristelle %A Lin, Honghuang %A Cantwell, Laura B %A Panza, Francesco %A McGuinness, Bernadette %A Moreno-Grau, Sonia %A Burgess, Jeremy D %A Solfrizzi, Vincenzo %A Proitsi, Petra %A Adams, Hieab H %A Allen, Mariet %A Seripa, Davide %A Pastor, Pau %A Cupples, L Adrienne %A Price, Nathan D %A Hannequin, Didier %A Frank-García, Ana %A Levy, Daniel %A Chakrabarty, Paramita %A Caffarra, Paolo %A Giegling, Ina %A Beiser, Alexa S %A Giedraitis, Vilmantas %A Hampel, Harald %A Garcia, Melissa E %A Wang, Xue %A Lannfelt, Lars %A Mecocci, Patrizia %A Eiriksdottir, Gudny %A Crane, Paul K %A Pasquier, Florence %A Boccardi, Virginia %A Henández, Isabel %A Barber, Robert C %A Scherer, Martin %A Tarraga, Lluis %A Adams, Perrie M %A Leber, Markus %A Chen, Yuning %A Albert, Marilyn S %A Riedel-Heller, Steffi %A Emilsson, Valur %A Beekly, Duane %A Braae, Anne %A Schmidt, Reinhold %A Blacker, Deborah %A Masullo, Carlo %A Schmidt, Helena %A Doody, Rachelle S %A Spalletta, Gianfranco %A Jr, W T Longstreth %A Fairchild, Thomas J %A Bossù, Paola %A Lopez, Oscar L %A Frosch, Matthew P %A Sacchinelli, Eleonora %A Ghetti, Bernardino %A Yang, Qiong %A Huebinger, Ryan M %A Jessen, Frank %A Li, Shuo %A Kamboh, M Ilyas %A Morris, John %A Sotolongo-Grau, Oscar %A Katz, Mindy J %A Corcoran, Chris %A Dunstan, Melanie %A Braddel, Amy %A Thomas, Charlene %A Meggy, Alun %A Marshall, Rachel %A Gerrish, Amy %A Chapman, Jade %A Aguilar, Miquel %A Taylor, Sarah %A Hill, Matt %A Fairén, Mònica Díez %A Hodges, Angela %A Vellas, Bruno %A Soininen, Hilkka %A Kloszewska, Iwona %A Daniilidou, Makrina %A Uphill, James %A Patel, Yogen %A Hughes, Joseph T %A Lord, Jenny %A Turton, James %A Hartmann, Annette M %A Cecchetti, Roberta %A Fenoglio, Chiara %A Serpente, Maria %A Arcaro, Marina %A Caltagirone, Carlo %A Orfei, Maria Donata %A Ciaramella, Antonio %A Pichler, Sabrina %A Mayhaus, Manuel %A Gu, Wei %A Lleo, Alberto %A Fortea, Juan %A Blesa, Rafael %A Barber, Imelda S %A Brookes, Keeley %A Cupidi, Chiara %A Maletta, Raffaele Giovanni %A Carrell, David %A Sorbi, Sandro %A Moebus, Susanne %A Urbano, Maria %A Pilotto, Alberto %A Kornhuber, Johannes %A Bosco, Paolo %A Todd, Stephen %A Craig, David %A Johnston, Janet %A Gill, Michael %A Lawlor, Brian %A Lynch, Aoibhinn %A Fox, Nick C %A Hardy, John %A Albin, Roger L %A Apostolova, Liana G %A Arnold, Steven E %A Asthana, Sanjay %A Atwood, Craig S %A Baldwin, Clinton T %A Barnes, Lisa L %A Barral, Sandra %A Beach, Thomas G %A Becker, James T %A Bigio, Eileen H %A Bird, Thomas D %A Boeve, Bradley F %A Bowen, James D %A Boxer, Adam %A Burke, James R %A Burns, Jeffrey M %A Buxbaum, Joseph D %A Cairns, Nigel J %A Cao, Chuanhai %A Carlson, Chris S %A Carlsson, Cynthia M %A Carney, Regina M %A Carrasquillo, Minerva M %A Carroll, Steven L %A Diaz, Carolina Ceballos %A Chui, Helena C %A Clark, David G %A Cribbs, David H %A Crocco, Elizabeth A %A DeCarli, Charles %A Dick, Malcolm %A Duara, Ranjan %A Evans, Denis A %A Faber, Kelley M %A Fallon, Kenneth B %A Fardo, David W %A Farlow, Martin R %A Ferris, Steven %A Foroud, Tatiana M %A Galasko, Douglas R %A Gearing, Marla %A Geschwind, Daniel H %A Gilbert, John R %A Graff-Radford, Neill R %A Green, Robert C %A Growdon, John H %A Hamilton, Ronald L %A Harrell, Lindy E %A Honig, Lawrence S %A Huentelman, Matthew J %A Hulette, Christine M %A Hyman, Bradley T %A Jarvik, Gail P %A Abner, Erin %A Jin, Lee-Way %A Jun, Gyungah %A Karydas, Anna %A Kaye, Jeffrey A %A Kim, Ronald %A Kowall, Neil W %A Kramer, Joel H %A LaFerla, Frank M %A Lah, James J %A Leverenz, James B %A Levey, Allan I %A Li, Ge %A Lieberman, Andrew P %A Lunetta, Kathryn L %A Lyketsos, Constantine G %A Marson, Daniel C %A Martiniuk, Frank %A Mash, Deborah C %A Masliah, Eliezer %A McCormick, Wayne C %A McCurry, Susan M %A McDavid, Andrew N %A McKee, Ann C %A Mesulam, Marsel %A Miller, Bruce L %A Miller, Carol A %A Miller, Joshua W %A Morris, John C %A Murrell, Jill R %A Myers, Amanda J %A O'Bryant, Sid %A Olichney, John M %A Pankratz, Vernon S %A Parisi, Joseph E %A Paulson, Henry L %A Perry, William %A Peskind, Elaine %A Pierce, Aimee %A Poon, Wayne W %A Potter, Huntington %A Quinn, Joseph F %A Raj, Ashok %A Raskind, Murray %A Reisberg, Barry %A Reitz, Christiane %A Ringman, John M %A Roberson, Erik D %A Rogaeva, Ekaterina %A Rosen, Howard J %A Rosenberg, Roger N %A Sager, Mark A %A Saykin, Andrew J %A Schneider, Julie A %A Schneider, Lon S %A Seeley, William W %A Smith, Amanda G %A Sonnen, Joshua A %A Spina, Salvatore %A Stern, Robert A %A Swerdlow, Russell H %A Tanzi, Rudolph E %A Thornton-Wells, Tricia A %A Trojanowski, John Q %A Troncoso, Juan C %A Van Deerlin, Vivianna M %A Van Eldik, Linda J %A Vinters, Harry V %A Vonsattel, Jean Paul %A Weintraub, Sandra %A Welsh-Bohmer, Kathleen A %A Wilhelmsen, Kirk C %A Williamson, Jennifer %A Wingo, Thomas S %A Woltjer, Randall L %A Wright, Clinton B %A Yu, Chang-En %A Yu, Lei %A Garzia, Fabienne %A Golamaully, Feroze %A Septier, Gislain %A Engelborghs, Sebastien %A Vandenberghe, Rik %A De Deyn, Peter P %A Fernadez, Carmen Muñoz %A Benito, Yoland Aladro %A Thonberg, Håkan %A Forsell, Charlotte %A Lilius, Lena %A Kinhult-Ståhlbom, Anne %A Kilander, Lena %A Brundin, RoseMarie %A Concari, Letizia %A Helisalmi, Seppo %A Koivisto, Anne Maria %A Haapasalo, Annakaisa %A Dermecourt, Vincent %A Fiévet, Nathalie %A Hanon, Olivier %A Dufouil, Carole %A Brice, Alexis %A Ritchie, Karen %A Dubois, Bruno %A Himali, Jayanadra J %A Keene, C Dirk %A Tschanz, JoAnn %A Fitzpatrick, Annette L %A Kukull, Walter A %A Norton, Maria %A Aspelund, Thor %A Larson, Eric B %A Munger, Ron %A Rotter, Jerome I %A Lipton, Richard B %A Bullido, María J %A Hofman, Albert %A Montine, Thomas J %A Coto, Eliecer %A Boerwinkle, Eric %A Petersen, Ronald C %A Alvarez, Victoria %A Rivadeneira, Fernando %A Reiman, Eric M %A Gallo, Maura %A O'Donnell, Christopher J %A Reisch, Joan S %A Bruni, Amalia Cecilia %A Royall, Donald R %A Dichgans, Martin %A Sano, Mary %A Galimberti, Daniela %A St George-Hyslop, Peter %A Scarpini, Elio %A Tsuang, Debby W %A Mancuso, Michelangelo %A Bonuccelli, Ubaldo %A Winslow, Ashley R %A Daniele, Antonio %A Wu, Chuang-Kuo %A Peters, Oliver %A Nacmias, Benedetta %A Riemenschneider, Matthias %A Heun, Reinhard %A Brayne, Carol %A Rubinsztein, David C %A Bras, Jose %A Guerreiro, Rita %A Al-Chalabi, Ammar %A Shaw, Christopher E %A Collinge, John %A Mann, David %A Tsolaki, Magda %A Clarimon, Jordi %A Sussams, Rebecca %A Lovestone, Simon %A O'Donovan, Michael C %A Owen, Michael J %A Behrens, Timothy W %A Mead, Simon %A Goate, Alison M %A Uitterlinden, André G %A Holmes, Clive %A Cruchaga, Carlos %A Ingelsson, Martin %A Bennett, David A %A Powell, John %A Golde, Todd E %A Graff, Caroline %A De Jager, Philip L %A Morgan, Kevin %A Ertekin-Taner, Nilufer %A Combarros, Onofre %A Psaty, Bruce M %A Passmore, Peter %A Younkin, Steven G %A Berr, Claudine %A Gudnason, Vilmundur %A Rujescu, Dan %A Dickson, Dennis W %A Dartigues, Jean-François %A DeStefano, Anita L %A Ortega-Cubero, Sara %A Hakonarson, Hakon %A Campion, Dominique %A Boada, Merce %A Kauwe, John Keoni %A Farrer, Lindsay A %A Van Broeckhoven, Christine %A Ikram, M Arfan %A Jones, Lesley %A Haines, Jonathan L %A Tzourio, Christophe %A Launer, Lenore J %A Escott-Price, Valentina %A Mayeux, Richard %A Deleuze, Jean-Francois %A Amin, Najaf %A Holmans, Peter A %A Pericak-Vance, Margaret A %A Amouyel, Philippe %A van Duijn, Cornelia M %A Ramirez, Alfredo %A Wang, Li-San %A Lambert, Jean-Charles %A Seshadri, Sudha %A Williams, Julie %A Schellenberg, Gerard D %K Adaptor Proteins, Signal Transducing %K Alzheimer Disease %K Amino Acid Sequence %K Case-Control Studies %K Exome %K Gene Expression Profiling %K Gene Frequency %K Genetic Predisposition to Disease %K Genotype %K Humans %K Immunity, Innate %K Linkage Disequilibrium %K Membrane Glycoproteins %K Microglia %K Odds Ratio %K Phospholipase C gamma %K Polymorphism, Single Nucleotide %K Protein Interaction Maps %K Receptors, Immunologic %K Sequence Homology, Amino Acid %X

We identified rare coding variants associated with Alzheimer's disease in a three-stage case-control study of 85,133 subjects. In stage 1, we genotyped 34,174 samples using a whole-exome microarray. In stage 2, we tested associated variants (P < 1 × 10-4) in 35,962 independent samples using de novo genotyping and imputed genotypes. In stage 3, we used an additional 14,997 samples to test the most significant stage 2 associations (P < 5 × 10-8) using imputed genotypes. We observed three new genome-wide significant nonsynonymous variants associated with Alzheimer's disease: a protective variant in PLCG2 (rs72824905: p.Pro522Arg, P = 5.38 × 10-10, odds ratio (OR) = 0.68, minor allele frequency (MAF)cases = 0.0059, MAFcontrols = 0.0093), a risk variant in ABI3 (rs616338: p.Ser209Phe, P = 4.56 × 10-10, OR = 1.43, MAFcases = 0.011, MAFcontrols = 0.008), and a new genome-wide significant variant in TREM2 (rs143332484: p.Arg62His, P = 1.55 × 10-14, OR = 1.67, MAFcases = 0.0143, MAFcontrols = 0.0089), a known susceptibility gene for Alzheimer's disease. These protein-altering changes are in genes highly expressed in microglia and highlight an immune-related protein-protein interaction network enriched for previously identified risk genes in Alzheimer's disease. These genetic findings provide additional evidence that the microglia-mediated innate immune response contributes directly to the development of Alzheimer's disease.

%B Nat Genet %V 49 %P 1373-1384 %8 2017 Sep %G eng %N 9 %R 10.1038/ng.3916 %0 Journal Article %J Dement Geriatr Cogn Disord %D 2018 %T Genetic Variation in Genes Underlying Diverse Dementias May Explain a Small Proportion of Cases in the Alzheimer's Disease Sequencing Project. %A Blue, Elizabeth E %A Bis, Joshua C %A Dorschner, Michael O %A Tsuang, Debby W %A Barral, Sandra M %A Beecham, Gary %A Below, Jennifer E %A Bush, William S %A Butkiewicz, Mariusz %A Cruchaga, Carlos %A DeStefano, Anita %A Farrer, Lindsay A %A Goate, Alison %A Haines, Jonathan %A Jaworski, Jim %A Jun, Gyungah %A Kunkle, Brian %A Kuzma, Amanda %A Lee, Jenny J %A Lunetta, Kathryn L %A Ma, Yiyi %A Martin, Eden %A Naj, Adam %A Nato, Alejandro Q %A Navas, Patrick %A Nguyen, Hiep %A Reitz, Christiane %A Reyes, Dolly %A Salerno, William %A Schellenberg, Gerard D %A Seshadri, Sudha %A Sohi, Harkirat %A Thornton, Timothy A %A Valadares, Otto %A van Duijn, Cornelia %A Vardarajan, Badri N %A Wang, Li-San %A Boerwinkle, Eric %A Dupuis, Josée %A Pericak-Vance, Margaret A %A Mayeux, Richard %A Wijsman, Ellen M %X

BACKGROUND/AIMS: The Alzheimer's Disease Sequencing Project (ADSP) aims to identify novel genes influencing Alzheimer's disease (AD). Variants within genes known to cause dementias other than AD have previously been associated with AD risk. We describe evidence of co-segregation and associations between variants in dementia genes and clinically diagnosed AD within the ADSP.

METHODS: We summarize the properties of known pathogenic variants within dementia genes, describe the co-segregation of variants annotated as "pathogenic" in ClinVar and new candidates observed in ADSP families, and test for associations between rare variants in dementia genes in the ADSP case-control study. The participants were clinically evaluated for AD, and they represent European, Caribbean Hispanic, and isolate Dutch populations.

RESULTS/CONCLUSIONS: Pathogenic variants in dementia genes were predominantly rare and conserved coding changes. Pathogenic variants within ARSA, CSF1R, and GRN were observed, and candidate variants in GRN and CHMP2B were nominated in ADSP families. An independent case-control study provided evidence of an association between variants in TREM2, APOE, ARSA, CSF1R, PSEN1, and MAPT and risk of AD. Variants in genes which cause dementing disorders may influence the clinical diagnosis of AD in a small proportion of cases within the ADSP.

%B Dement Geriatr Cogn Disord %V 45 %P 1-17 %8 2018 %G eng %N 1-2 %R 10.1159/000485503 %0 Journal Article %J Am J Hum Genet %D 2018 %T Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders. %A Ligthart, Symen %A Vaez, Ahmad %A Võsa, Urmo %A Stathopoulou, Maria G %A de Vries, Paul S %A Prins, Bram P %A van der Most, Peter J %A Tanaka, Toshiko %A Naderi, Elnaz %A Rose, Lynda M %A Wu, Ying %A Karlsson, Robert %A Barbalic, Maja %A Lin, Honghuang %A Pool, Rene %A Zhu, Gu %A Mace, Aurelien %A Sidore, Carlo %A Trompet, Stella %A Mangino, Massimo %A Sabater-Lleal, Maria %A Kemp, John P %A Abbasi, Ali %A Kacprowski, Tim %A Verweij, Niek %A Smith, Albert V %A Huang, Tao %A Marzi, Carola %A Feitosa, Mary F %A Lohman, Kurt K %A Kleber, Marcus E %A Milaneschi, Yuri %A Mueller, Christian %A Huq, Mahmudul %A Vlachopoulou, Efthymia %A Lyytikäinen, Leo-Pekka %A Oldmeadow, Christopher %A Deelen, Joris %A Perola, Markus %A Zhao, Jing Hua %A Feenstra, Bjarke %A Amini, Marzyeh %A Lahti, Jari %A Schraut, Katharina E %A Fornage, Myriam %A Suktitipat, Bhoom %A Chen, Wei-Min %A Li, Xiaohui %A Nutile, Teresa %A Malerba, Giovanni %A Luan, Jian'an %A Bak, Tom %A Schork, Nicholas %A del Greco M, Fabiola %A Thiering, Elisabeth %A Mahajan, Anubha %A Marioni, Riccardo E %A Mihailov, Evelin %A Eriksson, Joel %A Ozel, Ayse Bilge %A Zhang, Weihua %A Nethander, Maria %A Cheng, Yu-Ching %A Aslibekyan, Stella %A Ang, Wei %A Gandin, Ilaria %A Yengo, Loic %A Portas, Laura %A Kooperberg, Charles %A Hofer, Edith %A Rajan, Kumar B %A Schurmann, Claudia %A den Hollander, Wouter %A Ahluwalia, Tarunveer S %A Zhao, Jing %A Draisma, Harmen H M %A Ford, Ian %A Timpson, Nicholas %A Teumer, Alexander %A Huang, Hongyan %A Wahl, Simone %A Liu, Yongmei %A Huang, Jie %A Uh, Hae-Won %A Geller, Frank %A Joshi, Peter K %A Yanek, Lisa R %A Trabetti, Elisabetta %A Lehne, Benjamin %A Vozzi, Diego %A Verbanck, Marie %A Biino, Ginevra %A Saba, Yasaman %A Meulenbelt, Ingrid %A O'Connell, Jeff R %A Laakso, Markku %A Giulianini, Franco %A Magnusson, Patrik K E %A Ballantyne, Christie M %A Hottenga, Jouke Jan %A Montgomery, Grant W %A Rivadineira, Fernando %A Rueedi, Rico %A Steri, Maristella %A Herzig, Karl-Heinz %A Stott, David J %A Menni, Cristina %A Frånberg, Mattias %A St Pourcain, Beate %A Felix, Stephan B %A Pers, Tune H %A Bakker, Stephan J L %A Kraft, Peter %A Peters, Annette %A Vaidya, Dhananjay %A Delgado, Graciela %A Smit, Johannes H %A Großmann, Vera %A Sinisalo, Juha %A Seppälä, Ilkka %A Williams, Stephen R %A Holliday, Elizabeth G %A Moed, Matthijs %A Langenberg, Claudia %A Räikkönen, Katri %A Ding, Jingzhong %A Campbell, Harry %A Sale, Michèle M %A Chen, Yii-der I %A James, Alan L %A Ruggiero, Daniela %A Soranzo, Nicole %A Hartman, Catharina A %A Smith, Erin N %A Berenson, Gerald S %A Fuchsberger, Christian %A Hernandez, Dena %A Tiesler, Carla M T %A Giedraitis, Vilmantas %A Liewald, David %A Fischer, Krista %A Mellström, Dan %A Larsson, Anders %A Wang, Yunmei %A Scott, William R %A Lorentzon, Matthias %A Beilby, John %A Ryan, Kathleen A %A Pennell, Craig E %A Vuckovic, Dragana %A Balkau, Beverly %A Concas, Maria Pina %A Schmidt, Reinhold %A Mendes de Leon, Carlos F %A Bottinger, Erwin P %A Kloppenburg, Margreet %A Paternoster, Lavinia %A Boehnke, Michael %A Musk, A W %A Willemsen, Gonneke %A Evans, David M %A Madden, Pamela A F %A Kähönen, Mika %A Kutalik, Zoltán %A Zoledziewska, Magdalena %A Karhunen, Ville %A Kritchevsky, Stephen B %A Sattar, Naveed %A Lachance, Genevieve %A Clarke, Robert %A Harris, Tamara B %A Raitakari, Olli T %A Attia, John R %A van Heemst, Diana %A Kajantie, Eero %A Sorice, Rossella %A Gambaro, Giovanni %A Scott, Robert A %A Hicks, Andrew A %A Ferrucci, Luigi %A Standl, Marie %A Lindgren, Cecilia M %A Starr, John M %A Karlsson, Magnus %A Lind, Lars %A Li, Jun Z %A Chambers, John C %A Mori, Trevor A %A de Geus, Eco J C N %A Heath, Andrew C %A Martin, Nicholas G %A Auvinen, Juha %A Buckley, Brendan M %A de Craen, Anton J M %A Waldenberger, Melanie %A Strauch, Konstantin %A Meitinger, Thomas %A Scott, Rodney J %A McEvoy, Mark %A Beekman, Marian %A Bombieri, Cristina %A Ridker, Paul M %A Mohlke, Karen L %A Pedersen, Nancy L %A Morrison, Alanna C %A Boomsma, Dorret I %A Whitfield, John B %A Strachan, David P %A Hofman, Albert %A Vollenweider, Peter %A Cucca, Francesco %A Jarvelin, Marjo-Riitta %A Jukema, J Wouter %A Spector, Tim D %A Hamsten, Anders %A Zeller, Tanja %A Uitterlinden, André G %A Nauck, Matthias %A Gudnason, Vilmundur %A Qi, Lu %A Grallert, Harald %A Borecki, Ingrid B %A Rotter, Jerome I %A März, Winfried %A Wild, Philipp S %A Lokki, Marja-Liisa %A Boyle, Michael %A Salomaa, Veikko %A Melbye, Mads %A Eriksson, Johan G %A Wilson, James F %A Penninx, Brenda W J H %A Becker, Diane M %A Worrall, Bradford B %A Gibson, Greg %A Krauss, Ronald M %A Ciullo, Marina %A Zaza, Gianluigi %A Wareham, Nicholas J %A Oldehinkel, Albertine J %A Palmer, Lyle J %A Murray, Sarah S %A Pramstaller, Peter P %A Bandinelli, Stefania %A Heinrich, Joachim %A Ingelsson, Erik %A Deary, Ian J %A Mägi, Reedik %A Vandenput, Liesbeth %A van der Harst, Pim %A Desch, Karl C %A Kooner, Jaspal S %A Ohlsson, Claes %A Hayward, Caroline %A Lehtimäki, Terho %A Shuldiner, Alan R %A Arnett, Donna K %A Beilin, Lawrence J %A Robino, Antonietta %A Froguel, Philippe %A Pirastu, Mario %A Jess, Tine %A Koenig, Wolfgang %A Loos, Ruth J F %A Evans, Denis A %A Schmidt, Helena %A Smith, George Davey %A Slagboom, P Eline %A Eiriksdottir, Gudny %A Morris, Andrew P %A Psaty, Bruce M %A Tracy, Russell P %A Nolte, Ilja M %A Boerwinkle, Eric %A Visvikis-Siest, Sophie %A Reiner, Alex P %A Gross, Myron %A Bis, Joshua C %A Franke, Lude %A Franco, Oscar H %A Benjamin, Emelia J %A Chasman, Daniel I %A Dupuis, Josée %A Snieder, Harold %A Dehghan, Abbas %A Alizadeh, Behrooz Z %X

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

%B Am J Hum Genet %V 103 %P 691-706 %8 2018 Nov 01 %G eng %N 5 %R 10.1016/j.ajhg.2018.09.009 %0 Journal Article %J Nat Commun %D 2018 %T Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels. %A Jiang, Xia %A O'Reilly, Paul F %A Aschard, Hugues %A Hsu, Yi-Hsiang %A Richards, J Brent %A Dupuis, Josée %A Ingelsson, Erik %A Karasik, David %A Pilz, Stefan %A Berry, Diane %A Kestenbaum, Bryan %A Zheng, Jusheng %A Luan, Jianan %A Sofianopoulou, Eleni %A Streeten, Elizabeth A %A Albanes, Demetrius %A Lutsey, Pamela L %A Yao, Lu %A Tang, Weihong %A Econs, Michael J %A Wallaschofski, Henri %A Völzke, Henry %A Zhou, Ang %A Power, Chris %A McCarthy, Mark I %A Michos, Erin D %A Boerwinkle, Eric %A Weinstein, Stephanie J %A Freedman, Neal D %A Huang, Wen-Yi %A van Schoor, Natasja M %A van der Velde, Nathalie %A Groot, Lisette C P G M de %A Enneman, Anke %A Cupples, L Adrienne %A Booth, Sarah L %A Vasan, Ramachandran S %A Liu, Ching-Ti %A Zhou, Yanhua %A Ripatti, Samuli %A Ohlsson, Claes %A Vandenput, Liesbeth %A Lorentzon, Mattias %A Eriksson, Johan G %A Shea, M Kyla %A Houston, Denise K %A Kritchevsky, Stephen B %A Liu, Yongmei %A Lohman, Kurt K %A Ferrucci, Luigi %A Peacock, Munro %A Gieger, Christian %A Beekman, Marian %A Slagboom, Eline %A Deelen, Joris %A Heemst, Diana van %A Kleber, Marcus E %A März, Winfried %A de Boer, Ian H %A Wood, Alexis C %A Rotter, Jerome I %A Rich, Stephen S %A Robinson-Cohen, Cassianne %A den Heijer, Martin %A Jarvelin, Marjo-Riitta %A Cavadino, Alana %A Joshi, Peter K %A Wilson, James F %A Hayward, Caroline %A Lind, Lars %A Michaëlsson, Karl %A Trompet, Stella %A Zillikens, M Carola %A Uitterlinden, André G %A Rivadeneira, Fernando %A Broer, Linda %A Zgaga, Lina %A Campbell, Harry %A Theodoratou, Evropi %A Farrington, Susan M %A Timofeeva, Maria %A Dunlop, Malcolm G %A Valdes, Ana M %A Tikkanen, Emmi %A Lehtimäki, Terho %A Lyytikäinen, Leo-Pekka %A Kähönen, Mika %A Raitakari, Olli T %A Mikkilä, Vera %A Ikram, M Arfan %A Sattar, Naveed %A Jukema, J Wouter %A Wareham, Nicholas J %A Langenberg, Claudia %A Forouhi, Nita G %A Gundersen, Thomas E %A Khaw, Kay-Tee %A Butterworth, Adam S %A Danesh, John %A Spector, Timothy %A Wang, Thomas J %A Hyppönen, Elina %A Kraft, Peter %A Kiel, Douglas P %X

Vitamin D is a steroid hormone precursor that is associated with a range of human traits and diseases. Previous GWAS of serum 25-hydroxyvitamin D concentrations have identified four genome-wide significant loci (GC, NADSYN1/DHCR7, CYP2R1, CYP24A1). In this study, we expand the previous SUNLIGHT Consortium GWAS discovery sample size from 16,125 to 79,366 (all European descent). This larger GWAS yields two additional loci harboring genome-wide significant variants (P = 4.7×10 at rs8018720 in SEC23A, and P = 1.9×10 at rs10745742 in AMDHD1). The overall estimate of heritability of 25-hydroxyvitamin D serum concentrations attributable to GWAS common SNPs is 7.5%, with statistically significant loci explaining 38% of this total. Further investigation identifies signal enrichment in immune and hematopoietic tissues, and clustering with autoimmune diseases in cell-type-specific analysis. Larger studies are required to identify additional common SNPs, and to explore the role of rare or structural variants and gene-gene interactions in the heritability of circulating 25-hydroxyvitamin D levels.

%B Nat Commun %V 9 %P 260 %8 2018 Jan 17 %G eng %N 1 %R 10.1038/s41467-017-02662-2 %0 Journal Article %J Br J Nutr %D 2018 %T Meta-analysis across Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium provides evidence for an association of serum vitamin D with pulmonary function. %A Xu, Jiayi %A Bartz, Traci M %A Chittoor, Geetha %A Eiriksdottir, Gudny %A Manichaikul, Ani W %A Sun, Fangui %A Terzikhan, Natalie %A Zhou, Xia %A Booth, Sarah L %A Brusselle, Guy G %A de Boer, Ian H %A Fornage, Myriam %A Frazier-Wood, Alexis C %A Graff, Mariaelisa %A Gudnason, Vilmundur %A Harris, Tamara B %A Hofman, Albert %A Hou, Ruixue %A Houston, Denise K %A Jacobs, David R %A Kritchevsky, Stephen B %A Latourelle, Jeanne %A Lemaitre, Rozenn N %A Lutsey, Pamela L %A O'Connor, George %A Oelsner, Elizabeth C %A Pankow, James S %A Psaty, Bruce M %A Rohde, Rebecca R %A Rich, Stephen S %A Rotter, Jerome I %A Smith, Lewis J %A Stricker, Bruno H %A Voruganti, V Saroja %A Wang, Thomas J %A Zillikens, M Carola %A Barr, R Graham %A Dupuis, Josée %A Gharib, Sina A %A Lahousse, Lies %A London, Stephanie J %A North, Kari E %A Smith, Albert V %A Steffen, Lyn M %A Hancock, Dana B %A Cassano, Patricia A %X

The role that vitamin D plays in pulmonary function remains uncertain. Epidemiological studies reported mixed findings for serum 25-hydroxyvitamin D (25(OH)D)-pulmonary function association. We conducted the largest cross-sectional meta-analysis of the 25(OH)D-pulmonary function association to date, based on nine European ancestry (EA) cohorts (n 22 838) and five African ancestry (AA) cohorts (n 4290) in the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium. Data were analysed using linear models by cohort and ancestry. Effect modification by smoking status (current/former/never) was tested. Results were combined using fixed-effects meta-analysis. Mean serum 25(OH)D was 68 (sd 29) nmol/l for EA and 49 (sd 21) nmol/l for AA. For each 1 nmol/l higher 25(OH)D, forced expiratory volume in the 1st second (FEV1) was higher by 1·1 ml in EA (95 % CI 0·9, 1·3; P<0·0001) and 1·8 ml (95 % CI 1·1, 2·5; P<0·0001) in AA (P race difference=0·06), and forced vital capacity (FVC) was higher by 1·3 ml in EA (95 % CI 1·0, 1·6; P<0·0001) and 1·5 ml (95 % CI 0·8, 2·3; P=0·0001) in AA (P race difference=0·56). Among EA, the 25(OH)D-FVC association was stronger in smokers: per 1 nmol/l higher 25(OH)D, FVC was higher by 1·7 ml (95 % CI 1·1, 2·3) for current smokers and 1·7 ml (95 % CI 1·2, 2·1) for former smokers, compared with 0·8 ml (95 % CI 0·4, 1·2) for never smokers. In summary, the 25(OH)D associations with FEV1 and FVC were positive in both ancestries. In EA, a stronger association was observed for smokers compared with never smokers, which supports the importance of vitamin D in vulnerable populations.

%B Br J Nutr %P 1-12 %8 2018 Sep 12 %G eng %R 10.1017/S0007114518002180 %0 Journal Article %J Wellcome Open Res %D 2018 %T Meta-analysis of exome array data identifies six novel genetic loci for lung function. %A Jackson, Victoria E %A Latourelle, Jeanne C %A Wain, Louise V %A Smith, Albert V %A Grove, Megan L %A Bartz, Traci M %A Obeidat, Ma'en %A Province, Michael A %A Gao, Wei %A Qaiser, Beenish %A Porteous, David J %A Cassano, Patricia A %A Ahluwalia, Tarunveer S %A Grarup, Niels %A Li, Jin %A Altmaier, Elisabeth %A Marten, Jonathan %A Harris, Sarah E %A Manichaikul, Ani %A Pottinger, Tess D %A Li-Gao, Ruifang %A Lind-Thomsen, Allan %A Mahajan, Anubha %A Lahousse, Lies %A Imboden, Medea %A Teumer, Alexander %A Prins, Bram %A Lyytikäinen, Leo-Pekka %A Eiriksdottir, Gudny %A Franceschini, Nora %A Sitlani, Colleen M %A Brody, Jennifer A %A Bossé, Yohan %A Timens, Wim %A Kraja, Aldi %A Loukola, Anu %A Tang, Wenbo %A Liu, Yongmei %A Bork-Jensen, Jette %A Justesen, Johanne M %A Linneberg, Allan %A Lange, Leslie A %A Rawal, Rajesh %A Karrasch, Stefan %A Huffman, Jennifer E %A Smith, Blair H %A Davies, Gail %A Burkart, Kristin M %A Mychaleckyj, Josyf C %A Bonten, Tobias N %A Enroth, Stefan %A Lind, Lars %A Brusselle, Guy G %A Kumar, Ashish %A Stubbe, Beate %A Kähönen, Mika %A Wyss, Annah B %A Psaty, Bruce M %A Heckbert, Susan R %A Hao, Ke %A Rantanen, Taina %A Kritchevsky, Stephen B %A Lohman, Kurt %A Skaaby, Tea %A Pisinger, Charlotta %A Hansen, Torben %A Schulz, Holger %A Polasek, Ozren %A Campbell, Archie %A Starr, John M %A Rich, Stephen S %A Mook-Kanamori, Dennis O %A Johansson, Asa %A Ingelsson, Erik %A Uitterlinden, André G %A Weiss, Stefan %A Raitakari, Olli T %A Gudnason, Vilmundur %A North, Kari E %A Gharib, Sina A %A Sin, Don D %A Taylor, Kent D %A O'Connor, George T %A Kaprio, Jaakko %A Harris, Tamara B %A Pederson, Oluf %A Vestergaard, Henrik %A Wilson, James G %A Strauch, Konstantin %A Hayward, Caroline %A Kerr, Shona %A Deary, Ian J %A Barr, R Graham %A de Mutsert, Renée %A Gyllensten, Ulf %A Morris, Andrew P %A Ikram, M Arfan %A Probst-Hensch, Nicole %A Gläser, Sven %A Zeggini, Eleftheria %A Lehtimäki, Terho %A Strachan, David P %A Dupuis, Josée %A Morrison, Alanna C %A Hall, Ian P %A Tobin, Martin D %A London, Stephanie J %X

Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV ), forced vital capacity (FVC) and the ratio of FEV to FVC (FEV /FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. We identified significant (P<2·8x10 ) associations with six SNPs: a nonsynonymous variant in , which is predicted to be damaging, three intronic SNPs ( and ) and two intergenic SNPs near to and Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including and . Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease.

%B Wellcome Open Res %V 3 %P 4 %8 2018 %G eng %R 10.12688/wellcomeopenres.12583.3 %0 Journal Article %J Nat Commun %D 2018 %T Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function. %A Wyss, Annah B %A Sofer, Tamar %A Lee, Mi Kyeong %A Terzikhan, Natalie %A Nguyen, Jennifer N %A Lahousse, Lies %A Latourelle, Jeanne C %A Smith, Albert Vernon %A Bartz, Traci M %A Feitosa, Mary F %A Gao, Wei %A Ahluwalia, Tarunveer S %A Tang, Wenbo %A Oldmeadow, Christopher %A Duan, Qing %A de Jong, Kim %A Wojczynski, Mary K %A Wang, Xin-Qun %A Noordam, Raymond %A Hartwig, Fernando Pires %A Jackson, Victoria E %A Wang, Tianyuan %A Obeidat, Ma'en %A Hobbs, Brian D %A Huan, Tianxiao %A Gui, Hongsheng %A Parker, Margaret M %A Hu, Donglei %A Mogil, Lauren S %A Kichaev, Gleb %A Jin, Jianping %A Graff, Mariaelisa %A Harris, Tamara B %A Kalhan, Ravi %A Heckbert, Susan R %A Paternoster, Lavinia %A Burkart, Kristin M %A Liu, Yongmei %A Holliday, Elizabeth G %A Wilson, James G %A Vonk, Judith M %A Sanders, Jason L %A Barr, R Graham %A de Mutsert, Renée %A Menezes, Ana Maria Baptista %A Adams, Hieab H H %A van den Berge, Maarten %A Joehanes, Roby %A Levin, Albert M %A Liberto, Jennifer %A Launer, Lenore J %A Morrison, Alanna C %A Sitlani, Colleen M %A Celedón, Juan C %A Kritchevsky, Stephen B %A Scott, Rodney J %A Christensen, Kaare %A Rotter, Jerome I %A Bonten, Tobias N %A Wehrmeister, Fernando César %A Bossé, Yohan %A Xiao, Shujie %A Oh, Sam %A Franceschini, Nora %A Brody, Jennifer A %A Kaplan, Robert C %A Lohman, Kurt %A McEvoy, Mark %A Province, Michael A %A Rosendaal, Frits R %A Taylor, Kent D %A Nickle, David C %A Williams, L Keoki %A Burchard, Esteban G %A Wheeler, Heather E %A Sin, Don D %A Gudnason, Vilmundur %A North, Kari E %A Fornage, Myriam %A Psaty, Bruce M %A Myers, Richard H %A O'Connor, George %A Hansen, Torben %A Laurie, Cathy C %A Cassano, Patricia A %A Sung, Joohon %A Kim, Woo Jin %A Attia, John R %A Lange, Leslie %A Boezen, H Marike %A Thyagarajan, Bharat %A Rich, Stephen S %A Mook-Kanamori, Dennis O %A Horta, Bernardo Lessa %A Uitterlinden, André G %A Im, Hae Kyung %A Cho, Michael H %A Brusselle, Guy G %A Gharib, Sina A %A Dupuis, Josée %A Manichaikul, Ani %A London, Stephanie J %X

Nearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N = 60,552), African (N = 8429), Asian (N = 9959), and Hispanic/Latino (N = 11,775) ethnicities. We identify over 50 additional loci at genome-wide significance in ancestry-specific or multiethnic meta-analyses. Using recent fine-mapping methods incorporating functional annotation, gene expression, and differences in linkage disequilibrium between ethnicities, we further shed light on potential causal variants and genes at known and newly identified loci. Several of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12. Our study highlights the utility of multiethnic and integrative genomics approaches to extend existing knowledge of the genetics of lung function and clinical relevance of implicated loci.

%B Nat Commun %V 9 %P 2976 %8 2018 Jul 30 %G eng %N 1 %R 10.1038/s41467-018-05369-0 %0 Journal Article %J Am J Respir Crit Care Med %D 2018 %T Omega-3 Fatty Acids and Genome-wide Interaction Analyses Reveal DPP10-Pulmonary Function Association. %A Xu, Jiayi %A Gaddis, Nathan C %A Bartz, Traci M %A Hou, Ruixue %A Manichaikul, Ani W %A Pankratz, Nathan %A Smith, Albert V %A Sun, Fangui %A Terzikhan, Natalie %A Markunas, Christina A %A Patchen, Bonnie K %A Schu, Matthew %A Beydoun, May A %A Brusselle, Guy G %A Eiriksdottir, Gudny %A Zhou, Xia %A Wood, Alexis C %A Graff, Mariaelisa %A Harris, Tamara B %A Ikram, M Arfan %A Jacobs, David R %A Launer, Lenore J %A Lemaitre, Rozenn N %A O'Connor, George %A Oelsner, Elizabeth C %A Psaty, Bruce M %A Ramachandran, Vasan S %A Rohde, Rebecca R %A Rich, Stephen S %A Rotter, Jerome I %A Seshadri, Sudha %A Smith, Lewis J %A Tiemeier, Henning %A Tsai, Michael Y %A Uitterlinden, André G %A Voruganti, V Saroja %A Xu, Hanfei %A Zilhão, Nuno R %A Fornage, Myriam %A Zillikens, M Carola %A London, Stephanie J %A Barr, R Graham %A Dupuis, Josée %A Gharib, Sina A %A Gudnason, Vilmundur %A Lahousse, Lies %A North, Kari E %A Steffen, Lyn M %A Cassano, Patricia A %A Hancock, Dana B %X

RATIONALE: Omega-3 poly-unsaturated fatty acids (n-3 PUFAs) have anti-inflammatory properties that could benefit adults with comprised pulmonary health.

OBJECTIVE: To investigate n-3 PUFA associations with spirometric measures of pulmonary function tests (PFTs) and determine underlying genetic susceptibility.

METHODS: Associations of n-3 PUFA biomarkers (alpha-linolenic acid, eicosapentaenoic acid, docosapentaenoic acid [DPA], and docosahexaenoic acid [DHA]) were evaluated with PFTs (forced expiratory volume in the first second [FEV], forced vital capacity [FVC], and [FEV/FVC]) in meta-analyses across seven cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (N=16,134 of European or African ancestry). PFT-associated n-3 PUFAs were carried forward to genome-wide interaction analyses in the four largest cohorts (N=11,962) and replicated in one cohort (N=1,687). Cohort-specific results were combined using joint 2 degree-of-freedom (2df) meta-analyses of single nucleotide polymorphism (SNP) associations and their interactions with n-3 PUFAs.

RESULTS: DPA and DHA were positively associated with FEV1 and FVC (P<0.025), with evidence for effect modification by smoking and by sex. Genome-wide analyses identified a novel association of rs11693320-an intronic DPP10 SNP-with FVC when incorporating an interaction with DHA, and the finding was replicated (P=9.4×10 across discovery and replication cohorts). The rs11693320-A allele (frequency~80%) was associated with lower FVC (P=2.1×10; β= -161.0mL), and the association was attenuated by higher DHA levels (P=2.1×10; β=36.2mL).

CONCLUSIONS: We corroborated beneficial effects of n-3 PUFAs on pulmonary function. By modeling genome-wide n-3 PUFA interactions, we identified a novel DPP10 SNP association with FVC that was not detectable in much larger studies ignoring this interaction.

%B Am J Respir Crit Care Med %8 2018 Sep 10 %G eng %R 10.1164/rccm.201802-0304OC %0 Journal Article %J Nat Genet %D 2018 %T Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes. %A Mahajan, Anubha %A Wessel, Jennifer %A Willems, Sara M %A Zhao, Wei %A Robertson, Neil R %A Chu, Audrey Y %A Gan, Wei %A Kitajima, Hidetoshi %A Taliun, Daniel %A Rayner, N William %A Guo, Xiuqing %A Lu, Yingchang %A Li, Man %A Jensen, Richard A %A Hu, Yao %A Huo, Shaofeng %A Lohman, Kurt K %A Zhang, Weihua %A Cook, James P %A Prins, Bram Peter %A Flannick, Jason %A Grarup, Niels %A Trubetskoy, Vassily Vladimirovich %A Kravic, Jasmina %A Kim, Young Jin %A Rybin, Denis V %A Yaghootkar, Hanieh %A Müller-Nurasyid, Martina %A Meidtner, Karina %A Li-Gao, Ruifang %A Varga, Tibor V %A Marten, Jonathan %A Li, Jin %A Smith, Albert Vernon %A An, Ping %A Ligthart, Symen %A Gustafsson, Stefan %A Malerba, Giovanni %A Demirkan, Ayse %A Tajes, Juan Fernandez %A Steinthorsdottir, Valgerdur %A Wuttke, Matthias %A Lecoeur, Cécile %A Preuss, Michael %A Bielak, Lawrence F %A Graff, Marielisa %A Highland, Heather M %A Justice, Anne E %A Liu, Dajiang J %A Marouli, Eirini %A Peloso, Gina Marie %A Warren, Helen R %A Afaq, Saima %A Afzal, Shoaib %A Ahlqvist, Emma %A Almgren, Peter %A Amin, Najaf %A Bang, Lia B %A Bertoni, Alain G %A Bombieri, Cristina %A Bork-Jensen, Jette %A Brandslund, Ivan %A Brody, Jennifer A %A Burtt, Noel P %A Canouil, Mickaël %A Chen, Yii-Der Ida %A Cho, Yoon Shin %A Christensen, Cramer %A Eastwood, Sophie V %A Eckardt, Kai-Uwe %A Fischer, Krista %A Gambaro, Giovanni %A Giedraitis, Vilmantas %A Grove, Megan L %A de Haan, Hugoline G %A Hackinger, Sophie %A Hai, Yang %A Han, Sohee %A Tybjærg-Hansen, Anne %A Hivert, Marie-France %A Isomaa, Bo %A Jäger, Susanne %A Jørgensen, Marit E %A Jørgensen, Torben %A Käräjämäki, AnneMari %A Kim, Bong-Jo %A Kim, Sung Soo %A Koistinen, Heikki A %A Kovacs, Peter %A Kriebel, Jennifer %A Kronenberg, Florian %A Läll, Kristi %A Lange, Leslie A %A Lee, Jung-Jin %A Lehne, Benjamin %A Li, Huaixing %A Lin, Keng-Hung %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jun %A Loh, Marie %A Mägi, Reedik %A Mamakou, Vasiliki %A McKean-Cowdin, Roberta %A Nadkarni, Girish %A Neville, Matt %A Nielsen, Sune F %A Ntalla, Ioanna %A Peyser, Patricia A %A Rathmann, Wolfgang %A Rice, Kenneth %A Rich, Stephen S %A Rode, Line %A Rolandsson, Olov %A Schönherr, Sebastian %A Selvin, Elizabeth %A Small, Kerrin S %A Stančáková, Alena %A Surendran, Praveen %A Taylor, Kent D %A Teslovich, Tanya M %A Thorand, Barbara %A Thorleifsson, Gudmar %A Tin, Adrienne %A Tönjes, Anke %A Varbo, Anette %A Witte, Daniel R %A Wood, Andrew R %A Yajnik, Pranav %A Yao, Jie %A Yengo, Loic %A Young, Robin %A Amouyel, Philippe %A Boeing, Heiner %A Boerwinkle, Eric %A Bottinger, Erwin P %A Chowdhury, Rajiv %A Collins, Francis S %A Dedoussis, George %A Dehghan, Abbas %A Deloukas, Panos %A Ferrario, Marco M %A Ferrieres, Jean %A Florez, Jose C %A Frossard, Philippe %A Gudnason, Vilmundur %A Harris, Tamara B %A Heckbert, Susan R %A Howson, Joanna M M %A Ingelsson, Martin %A Kathiresan, Sekar %A Kee, Frank %A Kuusisto, Johanna %A Langenberg, Claudia %A Launer, Lenore J %A Lindgren, Cecilia M %A Männistö, Satu %A Meitinger, Thomas %A Melander, Olle %A Mohlke, Karen L %A Moitry, Marie %A Morris, Andrew D %A Murray, Alison D %A de Mutsert, Renée %A Orho-Melander, Marju %A Owen, Katharine R %A Perola, Markus %A Peters, Annette %A Province, Michael A %A Rasheed, Asif %A Ridker, Paul M %A Rivadineira, Fernando %A Rosendaal, Frits R %A Rosengren, Anders H %A Salomaa, Veikko %A Sheu, Wayne H-H %A Sladek, Rob %A Smith, Blair H %A Strauch, Konstantin %A Uitterlinden, André G %A Varma, Rohit %A Willer, Cristen J %A Blüher, Matthias %A Butterworth, Adam S %A Chambers, John Campbell %A Chasman, Daniel I %A Danesh, John %A van Duijn, Cornelia %A Dupuis, Josée %A Franco, Oscar H %A Franks, Paul W %A Froguel, Philippe %A Grallert, Harald %A Groop, Leif %A Han, Bok-Ghee %A Hansen, Torben %A Hattersley, Andrew T %A Hayward, Caroline %A Ingelsson, Erik %A Kardia, Sharon L R %A Karpe, Fredrik %A Kooner, Jaspal Singh %A Köttgen, Anna %A Kuulasmaa, Kari %A Laakso, Markku %A Lin, Xu %A Lind, Lars %A Liu, Yongmei %A Loos, Ruth J F %A Marchini, Jonathan %A Metspalu, Andres %A Mook-Kanamori, Dennis %A Nordestgaard, Børge G %A Palmer, Colin N A %A Pankow, James S %A Pedersen, Oluf %A Psaty, Bruce M %A Rauramaa, Rainer %A Sattar, Naveed %A Schulze, Matthias B %A Soranzo, Nicole %A Spector, Timothy D %A Stefansson, Kari %A Stumvoll, Michael %A Thorsteinsdottir, Unnur %A Tuomi, Tiinamaija %A Tuomilehto, Jaakko %A Wareham, Nicholas J %A Wilson, James G %A Zeggini, Eleftheria %A Scott, Robert A %A Barroso, Inês %A Frayling, Timothy M %A Goodarzi, Mark O %A Meigs, James B %A Boehnke, Michael %A Saleheen, Danish %A Morris, Andrew P %A Rotter, Jerome I %A McCarthy, Mark I %X

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.

%B Nat Genet %V 50 %P 559-571 %8 2018 Apr %G eng %N 4 %R 10.1038/s41588-018-0084-1 %0 Journal Article %J Diabetologia %D 2018 %T Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis. %A McKeown, Nicola M %A Dashti, Hassan S %A Ma, Jiantao %A Haslam, Danielle E %A Kiefte-de Jong, Jessica C %A Smith, Caren E %A Tanaka, Toshiko %A Graff, Mariaelisa %A Lemaitre, Rozenn N %A Rybin, Denis %A Sonestedt, Emily %A Frazier-Wood, Alexis C %A Mook-Kanamori, Dennis O %A Li, Yanping %A Wang, Carol A %A Leermakers, Elisabeth T M %A Mikkilä, Vera %A Young, Kristin L %A Mukamal, Kenneth J %A Cupples, L Adrienne %A Schulz, Christina-Alexandra %A Chen, Tzu-An %A Li-Gao, Ruifang %A Huang, Tao %A Oddy, Wendy H %A Raitakari, Olli %A Rice, Kenneth %A Meigs, James B %A Ericson, Ulrika %A Steffen, Lyn M %A Rosendaal, Frits R %A Hofman, Albert %A Kähönen, Mika %A Psaty, Bruce M %A Brunkwall, Louise %A Uitterlinden, André G %A Viikari, Jorma %A Siscovick, David S %A Seppälä, Ilkka %A North, Kari E %A Mozaffarian, Dariush %A Dupuis, Josée %A Orho-Melander, Marju %A Rich, Stephen S %A de Mutsert, Renée %A Qi, Lu %A Pennell, Craig E %A Franco, Oscar H %A Lehtimäki, Terho %A Herman, Mark A %X

AIMS/HYPOTHESIS: Sugar-sweetened beverages (SSBs) are a major dietary contributor to fructose intake. A molecular pathway involving the carbohydrate responsive element-binding protein (ChREBP) and the metabolic hormone fibroblast growth factor 21 (FGF21) may influence sugar metabolism and, thereby, contribute to fructose-induced metabolic disease. We hypothesise that common variants in 11 genes involved in fructose metabolism and the ChREBP-FGF21 pathway may interact with SSB intake to exacerbate positive associations between higher SSB intake and glycaemic traits.

METHODS: Data from 11 cohorts (six discovery and five replication) in the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium provided association and interaction results from 34,748 adults of European descent. SSB intake (soft drinks, fruit punches, lemonades or other fruit drinks) was derived from food-frequency questionnaires and food diaries. In fixed-effects meta-analyses, we quantified: (1) the associations between SSBs and glycaemic traits (fasting glucose and fasting insulin); and (2) the interactions between SSBs and 18 independent SNPs related to the ChREBP-FGF21 pathway.

RESULTS: In our combined meta-analyses of discovery and replication cohorts, after adjustment for age, sex, energy intake, BMI and other dietary covariates, each additional serving of SSB intake was associated with higher fasting glucose (β ± SE 0.014 ± 0.004 [mmol/l], p = 1.5 × 10-3) and higher fasting insulin (0.030 ± 0.005 [log e pmol/l], p = 2.0 × 10-10). No significant interactions on glycaemic traits were observed between SSB intake and selected SNPs. While a suggestive interaction was observed in the discovery cohorts with a SNP (rs1542423) in the β-Klotho (KLB) locus on fasting insulin (0.030 ± 0.011 log e pmol/l, uncorrected p = 0.006), results in the replication cohorts and combined meta-analyses were non-significant.

CONCLUSIONS/INTERPRETATION: In this large meta-analysis, we observed that SSB intake was associated with higher fasting glucose and insulin. Although a suggestive interaction with a genetic variant in the ChREBP-FGF21 pathway was observed in the discovery cohorts, this observation was not confirmed in the replication analysis.

TRIAL REGISTRATION: Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005121 (Framingham Offspring Study), NCT00005487 (Multi-Ethnic Study of Atherosclerosis) and NCT00005152 (Nurses' Health Study).

%B Diabetologia %V 61 %P 317-330 %8 2018 Feb %G eng %N 2 %R 10.1007/s00125-017-4475-0 %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 Mol Psychiatry %D 2018 %T Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation. %A Bis, Joshua C %A Jian, Xueqiu %A Kunkle, Brian W %A Chen, Yuning %A Hamilton-Nelson, Kara L %A Bush, William S %A Salerno, William J %A Lancour, Daniel %A Ma, Yiyi %A Renton, Alan E %A Marcora, Edoardo %A Farrell, John J %A Zhao, Yi %A Qu, Liming %A Ahmad, Shahzad %A Amin, Najaf %A Amouyel, Philippe %A Beecham, Gary W %A Below, Jennifer E %A Campion, Dominique %A Charbonnier, Camille %A Chung, Jaeyoon %A Crane, Paul K %A Cruchaga, Carlos %A Cupples, L Adrienne %A Dartigues, Jean-François %A Debette, Stephanie %A Deleuze, Jean-Francois %A Fulton, Lucinda %A Gabriel, Stacey B %A Genin, Emmanuelle %A Gibbs, Richard A %A Goate, Alison %A Grenier-Boley, Benjamin %A Gupta, Namrata %A Haines, Jonathan L %A Havulinna, Aki S %A Helisalmi, Seppo %A Hiltunen, Mikko %A Howrigan, Daniel P %A Ikram, M Arfan %A Kaprio, Jaakko %A Konrad, Jan %A Kuzma, Amanda %A Lander, Eric S %A Lathrop, Mark %A Lehtimäki, Terho %A Lin, Honghuang %A Mattila, Kari %A Mayeux, Richard %A Muzny, Donna M %A Nasser, Waleed %A Neale, Benjamin %A Nho, Kwangsik %A Nicolas, Gaël %A Patel, Devanshi %A Pericak-Vance, Margaret A %A Perola, Markus %A Psaty, Bruce M %A Quenez, Olivier %A Rajabli, Farid %A Redon, Richard %A Reitz, Christiane %A Remes, Anne M %A Salomaa, Veikko %A Sarnowski, Chloe %A Schmidt, Helena %A Schmidt, Michael %A Schmidt, Reinhold %A Soininen, Hilkka %A Thornton, Timothy A %A Tosto, Giuseppe %A Tzourio, Christophe %A van der Lee, Sven J %A van Duijn, Cornelia M %A Vardarajan, Badri %A Wang, Weixin %A Wijsman, Ellen %A Wilson, Richard K %A Witten, Daniela %A Worley, Kim C %A Zhang, Xiaoling %A Bellenguez, Céline %A Lambert, Jean-Charles %A Kurki, Mitja I %A Palotie, Aarno %A Daly, Mark %A Boerwinkle, Eric %A Lunetta, Kathryn L %A DeStefano, Anita L %A Dupuis, Josée %A Martin, Eden R %A Schellenberg, Gerard D %A Seshadri, Sudha %A Naj, Adam C %A Fornage, Myriam %A Farrer, Lindsay A %X

The Alzheimer's Disease Sequencing Project (ADSP) undertook whole exome sequencing in 5,740 late-onset Alzheimer disease (AD) cases and 5,096 cognitively normal controls primarily of European ancestry (EA), among whom 218 cases and 177 controls were Caribbean Hispanic (CH). An age-, sex- and APOE based risk score and family history were used to select cases most likely to harbor novel AD risk variants and controls least likely to develop AD by age 85 years. We tested ~1.5 million single nucleotide variants (SNVs) and 50,000 insertion-deletion polymorphisms (indels) for association to AD, using multiple models considering individual variants as well as gene-based tests aggregating rare, predicted functional, and loss of function variants. Sixteen single variants and 19 genes that met criteria for significant or suggestive associations after multiple-testing correction were evaluated for replication in four independent samples; three with whole exome sequencing (2,778 cases, 7,262 controls) and one with genome-wide genotyping imputed to the Haplotype Reference Consortium panel (9,343 cases, 11,527 controls). The top findings in the discovery sample were also followed-up in the ADSP whole-genome sequenced family-based dataset (197 members of 42 EA families and 501 members of 157 CH families). We identified novel and predicted functional genetic variants in genes previously associated with AD. We also detected associations in three novel genes: IGHG3 (p = 9.8 × 10), an immunoglobulin gene whose antibodies interact with β-amyloid, a long non-coding RNA AC099552.4 (p = 1.2 × 10), and a zinc-finger protein ZNF655 (gene-based p = 5.0 × 10). The latter two suggest an important role for transcriptional regulation in AD pathogenesis.

%B Mol Psychiatry %8 2018 Aug 14 %G eng %R 10.1038/s41380-018-0112-7 %0 Journal Article %J Am J Hum Genet %D 2019 %T Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program. %A Sarnowski, Chloe %A Leong, Aaron %A Raffield, Laura M %A Wu, Peitao %A de Vries, Paul S %A DiCorpo, Daniel %A Guo, Xiuqing %A Xu, Huichun %A Liu, Yongmei %A Zheng, Xiuwen %A Hu, Yao %A Brody, Jennifer A %A Goodarzi, Mark O %A Hidalgo, Bertha A %A Highland, Heather M %A Jain, Deepti %A Liu, Ching-Ti %A Naik, Rakhi P %A O'Connell, Jeffrey R %A Perry, James A %A Porneala, Bianca C %A Selvin, Elizabeth %A Wessel, Jennifer %A Psaty, Bruce M %A Curran, Joanne E %A Peralta, Juan M %A Blangero, John %A Kooperberg, Charles %A Mathias, Rasika %A Johnson, Andrew D %A Reiner, Alexander P %A Mitchell, Braxton D %A Cupples, L Adrienne %A Vasan, Ramachandran S %A Correa, Adolfo %A Morrison, Alanna C %A Boerwinkle, Eric %A Rotter, Jerome I %A Rich, Stephen S %A Manning, Alisa K %A Dupuis, Josée %A Meigs, James B %X

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.

%B Am J Hum Genet %V 105 %P 706-718 %8 2019 Oct 03 %G eng %N 4 %R 10.1016/j.ajhg.2019.08.010 %0 Journal Article %J Nat Commun %D 2020 %T Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants. %A Zhao, Xutong %A Qiao, Dandi %A Yang, Chaojie %A Kasela, Silva %A Kim, Wonji %A Ma, Yanlin %A Shrine, Nick %A Batini, Chiara %A Sofer, Tamar %A Taliun, Sarah A Gagliano %A Sakornsakolpat, Phuwanat %A Balte, Pallavi P %A Prokopenko, Dmitry %A Yu, Bing %A Lange, Leslie A %A Dupuis, Josée %A Cade, Brian E %A Lee, Jiwon %A Gharib, Sina A %A Daya, Michelle %A Laurie, Cecelia A %A Ruczinski, Ingo %A Cupples, L Adrienne %A Loehr, Laura R %A Bartz, Traci M %A Morrison, Alanna C %A Psaty, Bruce M %A Vasan, Ramachandran S %A Wilson, James G %A Taylor, Kent D %A Durda, Peter %A Johnson, W Craig %A Cornell, Elaine %A Guo, Xiuqing %A Liu, Yongmei %A Tracy, Russell P %A Ardlie, Kristin G %A Aguet, Francois %A VanDenBerg, David J %A Papanicolaou, George J %A Rotter, Jerome I %A Barnes, Kathleen C %A Jain, Deepti %A Nickerson, Deborah A %A Muzny, Donna M %A Metcalf, Ginger A %A Doddapaneni, Harshavardhan %A Dugan-Perez, Shannon %A Gupta, Namrata %A Gabriel, Stacey %A Rich, Stephen S %A O'Connor, George T %A Redline, Susan %A Reed, Robert M %A Laurie, Cathy C %A Daviglus, Martha L %A Preudhomme, Liana K %A Burkart, Kristin M %A Kaplan, Robert C %A Wain, Louise V %A Tobin, Martin D %A London, Stephanie J %A Lappalainen, Tuuli %A Oelsner, Elizabeth C %A Abecasis, Goncalo R %A Silverman, Edwin K %A Barr, R Graham %A Cho, Michael H %A Manichaikul, Ani %K Adult %K African Americans %K Aged %K Aged, 80 and over %K Alpha-Ketoglutarate-Dependent Dioxygenase FTO %K Calcium-Binding Proteins %K Feasibility Studies %K Female %K Follow-Up Studies %K Genetic Loci %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Intracellular Signaling Peptides and Proteins %K Lung %K Male %K Middle Aged %K Polymorphism, Single Nucleotide %K Protein Inhibitors of Activated STAT %K Pulmonary Disease, Chronic Obstructive %K Respiratory Physiological Phenomena %K Small Ubiquitin-Related Modifier Proteins %K Whole Genome Sequencing %X

Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry.

%B Nat Commun %V 11 %P 5182 %8 2020 10 14 %G eng %N 1 %R 10.1038/s41467-020-18334-7 %0 Journal Article %J Nat Commun %D 2021 %T Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes. %A Goodrich, Julia K %A Singer-Berk, Moriel %A Son, Rachel %A Sveden, Abigail %A Wood, Jordan %A England, Eleina %A Cole, Joanne B %A Weisburd, Ben %A Watts, Nick %A Caulkins, Lizz %A Dornbos, Peter %A Koesterer, Ryan %A Zappala, Zachary %A Zhang, Haichen %A Maloney, Kristin A %A Dahl, Andy %A Aguilar-Salinas, Carlos A %A Atzmon, Gil %A Barajas-Olmos, Francisco %A Barzilai, Nir %A Blangero, John %A Boerwinkle, Eric %A Bonnycastle, Lori L %A Bottinger, Erwin %A Bowden, Donald W %A Centeno-Cruz, Federico %A Chambers, John C %A Chami, Nathalie %A Chan, Edmund %A Chan, Juliana %A Cheng, Ching-Yu %A Cho, Yoon Shin %A Contreras-Cubas, Cecilia %A Córdova, Emilio %A Correa, Adolfo %A DeFronzo, Ralph A %A Duggirala, Ravindranath %A Dupuis, Josée %A Garay-Sevilla, Ma Eugenia %A García-Ortiz, Humberto %A Gieger, Christian %A Glaser, Benjamin %A González-Villalpando, Clicerio %A Gonzalez, Ma Elena %A Grarup, Niels %A Groop, Leif %A Gross, Myron %A Haiman, Christopher %A Han, Sohee %A Hanis, Craig L %A Hansen, Torben %A Heard-Costa, Nancy L %A Henderson, Brian E %A Hernandez, Juan Manuel Malacara %A Hwang, Mi Yeong %A Islas-Andrade, Sergio %A Jørgensen, Marit E %A Kang, Hyun Min %A Kim, Bong-Jo %A Kim, Young Jin %A Koistinen, Heikki A %A Kooner, Jaspal Singh %A Kuusisto, Johanna %A Kwak, Soo-Heon %A Laakso, Markku %A Lange, Leslie %A Lee, Jong-Young %A Lee, Juyoung %A Lehman, Donna M %A Linneberg, Allan %A Liu, Jianjun %A Loos, Ruth J F %A Lyssenko, Valeriya %A Ma, Ronald C W %A Martínez-Hernández, Angélica %A Meigs, James B %A Meitinger, Thomas %A Mendoza-Caamal, Elvia %A Mohlke, Karen L %A Morris, Andrew D %A Morrison, Alanna C %A Ng, Maggie C Y %A Nilsson, Peter M %A O'Donnell, Christopher J %A Orozco, Lorena %A Palmer, Colin N A %A Park, Kyong Soo %A Post, Wendy S %A Pedersen, Oluf %A Preuss, Michael %A Psaty, Bruce M %A Reiner, Alexander P %A Revilla-Monsalve, Cristina %A Rich, Stephen S %A Rotter, Jerome I %A Saleheen, Danish %A Schurmann, Claudia %A Sim, Xueling %A Sladek, Rob %A Small, Kerrin S %A So, Wing Yee %A Spector, Timothy D %A Strauch, Konstantin %A Strom, Tim M %A Tai, E Shyong %A Tam, Claudia H T %A Teo, Yik Ying %A Thameem, Farook %A Tomlinson, Brian %A Tracy, Russell P %A Tuomi, Tiinamaija %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A van Dam, Rob M %A Vasan, Ramachandran S %A Wilson, James G %A Witte, Daniel R %A Wong, Tien-Yin %A Burtt, Noel P %A Zaitlen, Noah %A McCarthy, Mark I %A Boehnke, Michael %A Pollin, Toni I %A Flannick, Jason %A Mercader, Josep M %A O'Donnell-Luria, Anne %A Baxter, Samantha %A Florez, Jose C %A MacArthur, Daniel G %A Udler, Miriam S %K Adult %K Biological Variation, Population %K Biomarkers %K Diabetes Mellitus, Type 2 %K Dyslipidemias %K Exome %K Genetic Predisposition to Disease %K Genotype %K Humans %K Multifactorial Inheritance %K Penetrance %K Risk Assessment %X

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.

%B Nat Commun %V 12 %P 3505 %8 2021 06 09 %G eng %N 1 %R 10.1038/s41467-021-23556-4 %0 Journal Article %J Circ Genom Precis Med %D 2021 %T Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations. %A Haslam, Danielle E %A Peloso, Gina M %A Guirette, Melanie %A Imamura, Fumiaki %A Bartz, Traci M %A Pitsillides, Achilleas N %A Wang, Carol A %A Li-Gao, Ruifang %A Westra, Jason M %A Pitkänen, Niina %A Young, Kristin L %A Graff, Mariaelisa %A Wood, Alexis C %A Braun, Kim V E %A Luan, Jian'an %A Kähönen, Mika %A Kiefte-de Jong, Jessica C %A Ghanbari, Mohsen %A Tintle, Nathan %A Lemaitre, Rozenn N %A Mook-Kanamori, Dennis O %A North, Kari %A Helminen, Mika %A Mossavar-Rahmani, Yasmin %A Snetselaar, Linda %A Martin, Lisa W %A Viikari, Jorma S %A Oddy, Wendy H %A Pennell, Craig E %A Rosendall, Frits R %A Ikram, M Arfan %A Uitterlinden, André G %A Psaty, Bruce M %A Mozaffarian, Dariush %A Rotter, Jerome I %A Taylor, Kent D %A Lehtimäki, Terho %A Raitakari, Olli T %A Livingston, Kara A %A Voortman, Trudy %A Forouhi, Nita G %A Wareham, Nick J %A de Mutsert, Renée %A Rich, Steven S %A Manson, JoAnn E %A Mora, Samia %A Ridker, Paul M %A Merino, Jordi %A Meigs, James B %A Dashti, Hassan S %A Chasman, Daniel I %A Lichtenstein, Alice H %A Smith, Caren E %A Dupuis, Josée %A Herman, Mark A %A McKeown, Nicola M %X

BACKGROUND: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the locus and dyslipidemia.

METHODS: Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake.

RESULTS: In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; <0.0001), but not significantly among the lowest SSB consumers (=0.81; <0.0001). Similar results were observed for 2 additional variants (rs35709627 and rs71556736). For triglyceride, rs55673514 was positively associated with triglyceride concentrations only among the highest SSB consumers (β, 0.06 [95% CI, 0.02-0.09] ln-mg/dL per allele, =0.001) but not the lowest SSB consumers (=0.84; =0.0005).

CONCLUSIONS: Our results identified genetic variants in the locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in triglyceride concentrations. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00005133, NCT00005121, NCT00005487, and NCT00000479.

%B Circ Genom Precis Med %V 14 %P e003288 %8 2021 Aug %G eng %N 4 %R 10.1161/CIRCGEN.120.003288 %0 Journal Article %J Nat Genet %D 2022 %T Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. %A Mahajan, Anubha %A Spracklen, Cassandra N %A Zhang, Weihua %A Ng, Maggie C Y %A Petty, Lauren E %A Kitajima, Hidetoshi %A Yu, Grace Z %A Rüeger, Sina %A Speidel, Leo %A Kim, Young Jin %A Horikoshi, Momoko %A Mercader, Josep M %A Taliun, Daniel %A Moon, Sanghoon %A Kwak, Soo-Heon %A Robertson, Neil R %A Rayner, Nigel W %A Loh, Marie %A Kim, Bong-Jo %A Chiou, Joshua %A Miguel-Escalada, Irene %A Della Briotta Parolo, Pietro %A Lin, Kuang %A Bragg, Fiona %A Preuss, Michael H %A Takeuchi, Fumihiko %A Nano, Jana %A Guo, Xiuqing %A Lamri, Amel %A Nakatochi, Masahiro %A Scott, Robert A %A Lee, Jung-Jin %A Huerta-Chagoya, Alicia %A Graff, Mariaelisa %A Chai, Jin-Fang %A Parra, Esteban J %A Yao, Jie %A Bielak, Lawrence F %A Tabara, Yasuharu %A Hai, Yang %A Steinthorsdottir, Valgerdur %A Cook, James P %A Kals, Mart %A Grarup, Niels %A Schmidt, Ellen M %A Pan, Ian %A Sofer, Tamar %A Wuttke, Matthias %A Sarnowski, Chloe %A Gieger, Christian %A Nousome, Darryl %A Trompet, Stella %A Long, Jirong %A Sun, Meng %A Tong, Lin %A Chen, Wei-Min %A Ahmad, Meraj %A Noordam, Raymond %A Lim, Victor J Y %A Tam, Claudia H T %A Joo, Yoonjung Yoonie %A Chen, Chien-Hsiun %A Raffield, Laura M %A Lecoeur, Cécile %A Prins, Bram Peter %A Nicolas, Aude %A Yanek, Lisa R %A Chen, Guanjie %A Jensen, Richard A %A Tajuddin, Salman %A Kabagambe, Edmond K %A An, Ping %A Xiang, Anny H %A Choi, Hyeok Sun %A Cade, Brian E %A Tan, Jingyi %A Flanagan, Jack %A Abaitua, Fernando %A Adair, Linda S %A Adeyemo, Adebowale %A Aguilar-Salinas, Carlos A %A Akiyama, Masato %A Anand, Sonia S %A Bertoni, Alain %A Bian, Zheng %A Bork-Jensen, Jette %A Brandslund, Ivan %A Brody, Jennifer A %A Brummett, Chad M %A Buchanan, Thomas A %A Canouil, Mickaël %A Chan, Juliana C N %A Chang, Li-Ching %A Chee, Miao-Li %A Chen, Ji %A Chen, Shyh-Huei %A Chen, Yuan-Tsong %A Chen, Zhengming %A Chuang, Lee-Ming %A Cushman, Mary %A Das, Swapan K %A de Silva, H Janaka %A Dedoussis, George %A Dimitrov, Latchezar %A Doumatey, Ayo P %A Du, Shufa %A Duan, Qing %A Eckardt, Kai-Uwe %A Emery, Leslie S %A Evans, Daniel S %A Evans, Michele K %A Fischer, Krista %A Floyd, James S %A Ford, Ian %A Fornage, Myriam %A Franco, Oscar H %A Frayling, Timothy M %A Freedman, Barry I %A Fuchsberger, Christian %A Genter, Pauline %A Gerstein, Hertzel C %A Giedraitis, Vilmantas %A González-Villalpando, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Goodarzi, Mark O %A Gordon-Larsen, Penny %A Gorkin, David %A Gross, Myron %A Guo, Yu %A Hackinger, Sophie %A Han, Sohee %A Hattersley, Andrew T %A Herder, Christian %A Howard, Annie-Green %A Hsueh, Willa %A Huang, Mengna %A Huang, Wei %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Hwu, Chii-Min %A Ichihara, Sahoko %A Ikram, Mohammad Arfan %A Ingelsson, Martin %A Islam, Md Tariqul %A Isono, Masato %A Jang, Hye-Mi %A Jasmine, Farzana %A Jiang, Guozhi %A Jonas, Jost B %A Jørgensen, Marit E %A Jørgensen, Torben %A Kamatani, Yoichiro %A Kandeel, Fouad R %A Kasturiratne, Anuradhani %A Katsuya, Tomohiro %A Kaur, Varinderpal %A Kawaguchi, Takahisa %A Keaton, Jacob M %A Kho, Abel N %A Khor, Chiea-Chuen %A Kibriya, Muhammad G %A Kim, Duk-Hwan %A Kohara, Katsuhiko %A Kriebel, Jennifer %A Kronenberg, Florian %A Kuusisto, Johanna %A Läll, Kristi %A Lange, Leslie A %A Lee, Myung-Shik %A Lee, Nanette R %A Leong, Aaron %A Li, Liming %A Li, Yun %A Li-Gao, Ruifang %A Ligthart, Symen %A Lindgren, Cecilia M %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Locke, Adam E %A Louie, Tin %A Luan, Jian'an %A Luk, Andrea O %A Luo, Xi %A Lv, Jun %A Lyssenko, Valeriya %A Mamakou, Vasiliki %A Mani, K Radha %A Meitinger, Thomas %A Metspalu, Andres %A Morris, Andrew D %A Nadkarni, Girish N %A Nadler, Jerry L %A Nalls, Michael A %A Nayak, Uma %A Nongmaithem, Suraj S %A Ntalla, Ioanna %A Okada, Yukinori %A Orozco, Lorena %A Patel, Sanjay R %A Pereira, Mark A %A Peters, Annette %A Pirie, Fraser J %A Porneala, Bianca %A Prasad, Gauri %A Preissl, Sebastian %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Roden, Michael %A Rohde, Rebecca %A Roll, Kathryn %A Sabanayagam, Charumathi %A Sander, Maike %A Sandow, Kevin %A Sattar, Naveed %A Schönherr, Sebastian %A Schurmann, Claudia %A Shahriar, Mohammad %A Shi, Jinxiu %A Shin, Dong Mun %A Shriner, Daniel %A Smith, Jennifer A %A So, Wing Yee %A Stančáková, Alena %A Stilp, Adrienne M %A Strauch, Konstantin %A Suzuki, Ken %A Takahashi, Atsushi %A Taylor, Kent D %A Thorand, Barbara %A Thorleifsson, Gudmar %A Thorsteinsdottir, Unnur %A Tomlinson, Brian %A Torres, Jason M %A Tsai, Fuu-Jen %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A Valladares-Salgado, Adan %A van Dam, Rob M %A van Klinken, Jan B %A Varma, Rohit %A Vujkovic, Marijana %A Wacher-Rodarte, Niels %A Wheeler, Eleanor %A Whitsel, Eric A %A Wickremasinghe, Ananda R %A van Dijk, Ko Willems %A Witte, Daniel R %A Yajnik, Chittaranjan S %A Yamamoto, Ken %A Yamauchi, Toshimasa %A Yengo, Loic %A Yoon, Kyungheon %A Yu, Canqing %A Yuan, Jian-Min %A Yusuf, Salim %A Zhang, Liang %A Zheng, Wei %A Raffel, Leslie J %A Igase, Michiya %A Ipp, Eli %A Redline, Susan %A Cho, Yoon Shin %A Lind, Lars %A Province, Michael A %A Hanis, Craig L %A Peyser, Patricia A %A Ingelsson, Erik %A Zonderman, Alan B %A Psaty, Bruce M %A Wang, Ya-Xing %A Rotimi, Charles N %A Becker, Diane M %A Matsuda, Fumihiko %A Liu, Yongmei %A Zeggini, Eleftheria %A Yokota, Mitsuhiro %A Rich, Stephen S %A Kooperberg, Charles %A Pankow, James S %A Engert, James C %A Chen, Yii-Der Ida %A Froguel, Philippe %A Wilson, James G %A Sheu, Wayne H H %A Kardia, Sharon L R %A Wu, Jer-Yuarn %A Hayes, M Geoffrey %A Ma, Ronald C W %A Wong, Tien-Yin %A Groop, Leif %A Mook-Kanamori, Dennis O %A Chandak, Giriraj R %A Collins, Francis S %A Bharadwaj, Dwaipayan %A Paré, Guillaume %A Sale, Michèle M %A Ahsan, Habibul %A Motala, Ayesha A %A Shu, Xiao-Ou %A Park, Kyong-Soo %A Jukema, J Wouter %A Cruz, Miguel %A McKean-Cowdin, Roberta %A Grallert, Harald %A Cheng, Ching-Yu %A Bottinger, Erwin P %A Dehghan, Abbas %A Tai, E-Shyong %A Dupuis, Josée %A Kato, Norihiro %A Laakso, Markku %A Köttgen, Anna %A Koh, Woon-Puay %A Palmer, Colin N A %A Liu, Simin %A Abecasis, Goncalo %A Kooner, Jaspal S %A Loos, Ruth J F %A North, Kari E %A Haiman, Christopher A %A Florez, Jose C %A Saleheen, Danish %A Hansen, Torben %A Pedersen, Oluf %A Mägi, Reedik %A Langenberg, Claudia %A Wareham, Nicholas J %A Maeda, Shiro %A Kadowaki, Takashi %A Lee, Juyoung %A Millwood, Iona Y %A Walters, Robin G %A Stefansson, Kari %A Myers, Simon R %A Ferrer, Jorge %A Gaulton, Kyle J %A Meigs, James B %A Mohlke, Karen L %A Gloyn, Anna L %A Bowden, Donald W %A Below, Jennifer E %A Chambers, John C %A Sim, Xueling %A Boehnke, Michael %A Rotter, Jerome I %A McCarthy, Mark I %A Morris, Andrew P %K Diabetes Mellitus, Type 2 %K Ethnicity %K Genetic Predisposition to Disease %K Genome-Wide Association Study %K Humans %K Polymorphism, Single Nucleotide %K Risk Factors %X

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

%B Nat Genet %V 54 %P 560-572 %8 2022 May %G eng %N 5 %R 10.1038/s41588-022-01058-3 %0 Journal Article %J Am J Hum Genet %D 2022 %T Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program. %A Hu, Xiaowei %A Qiao, Dandi %A Kim, Wonji %A Moll, Matthew %A Balte, Pallavi P %A Lange, Leslie A %A Bartz, Traci M %A Kumar, Rajesh %A Li, Xingnan %A Yu, Bing %A Cade, Brian E %A Laurie, Cecelia A %A Sofer, Tamar %A Ruczinski, Ingo %A Nickerson, Deborah A %A Muzny, Donna M %A Metcalf, Ginger A %A Doddapaneni, Harshavardhan %A Gabriel, Stacy %A Gupta, Namrata %A Dugan-Perez, Shannon %A Cupples, L Adrienne %A Loehr, Laura R %A Jain, Deepti %A Rotter, Jerome I %A Wilson, James G %A Psaty, Bruce M %A Fornage, Myriam %A Morrison, Alanna C %A Vasan, Ramachandran S %A Washko, George %A Rich, Stephen S %A O'Connor, George T %A Bleecker, Eugene %A Kaplan, Robert C %A Kalhan, Ravi %A Redline, Susan %A Gharib, Sina A %A Meyers, Deborah %A Ortega, Victor %A Dupuis, Josée %A London, Stephanie J %A Lappalainen, Tuuli %A Oelsner, Elizabeth C %A Silverman, Edwin K %A Barr, R Graham %A Thornton, Timothy A %A Wheeler, Heather E %A Cho, Michael H %A Im, Hae Kyung %A Manichaikul, Ani %X

While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV] and its ratio to forced vital capacity [FEV/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV and FEV/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08-1.43] for PTRS versus 1.10 [0.96-1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p < 2.2 × 10 with portability gains ranging from 5% to 28%) for both dichotomous COPD traits and across all smoking strata. Our study demonstrates the value of PTRS for improved cross-ethnic portability compared to PRS in predicting COPD risk.

%B Am J Hum Genet %8 2022 Mar 31 %G eng %R 10.1016/j.ajhg.2022.03.007 %0 Journal Article %J Commun Biol %D 2022 %T Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program. %A DiCorpo, Daniel %A Gaynor, Sheila M %A Russell, Emily M %A Westerman, Kenneth E %A Raffield, Laura M %A Majarian, Timothy D %A Wu, Peitao %A Sarnowski, Chloe %A Highland, Heather M %A Jackson, Anne %A Hasbani, Natalie R %A de Vries, Paul S %A Brody, Jennifer A %A Hidalgo, Bertha %A Guo, Xiuqing %A Perry, James A %A O'Connell, Jeffrey R %A Lent, Samantha %A Montasser, May E %A Cade, Brian E %A Jain, Deepti %A Wang, Heming %A D'Oliveira Albanus, Ricardo %A Varshney, Arushi %A Yanek, Lisa R %A Lange, Leslie %A Palmer, Nicholette D %A Almeida, Marcio %A Peralta, Juan M %A Aslibekyan, Stella %A Baldridge, Abigail S %A Bertoni, Alain G %A Bielak, Lawrence F %A Chen, Chung-Shiuan %A Chen, Yii-Der Ida %A Choi, Won Jung %A Goodarzi, Mark O %A Floyd, James S %A Irvin, Marguerite R %A Kalyani, Rita R %A Kelly, Tanika N %A Lee, Seonwook %A Liu, Ching-Ti %A Loesch, Douglas %A Manson, JoAnn E %A Minster, Ryan L %A Naseri, Take %A Pankow, James S %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Reupena, Muagututi'a Sefuiva %A Selvin, Elizabeth %A Smith, Jennifer A %A Weeks, Daniel E %A Xu, Huichun %A Yao, Jie %A Zhao, Wei %A Parker, Stephen %A Alonso, Alvaro %A Arnett, Donna K %A Blangero, John %A Boerwinkle, Eric %A Correa, Adolfo %A Cupples, L Adrienne %A Curran, Joanne E %A Duggirala, Ravindranath %A He, Jiang %A Heckbert, Susan R %A Kardia, Sharon L R %A Kim, Ryan W %A Kooperberg, Charles %A Liu, Simin %A Mathias, Rasika A %A McGarvey, Stephen T %A Mitchell, Braxton D %A Morrison, Alanna C %A Peyser, Patricia A %A Psaty, Bruce M %A Redline, Susan %A Shuldiner, Alan R %A Taylor, Kent D %A Vasan, Ramachandran S %A Viaud-Martinez, Karine A %A Florez, Jose C %A Wilson, James G %A Sladek, Robert %A Rich, Stephen S %A Rotter, Jerome I %A Lin, Xihong %A Dupuis, Josée %A Meigs, James B %A Wessel, Jennifer %A Manning, Alisa K %K Diabetes Mellitus, Type 2 %K Fasting %K Glucose %K Humans %K Insulin %K National Heart, Lung, and Blood Institute (U.S.) %K Nerve Tissue Proteins %K Polymorphism, Single Nucleotide %K Precision Medicine %K Receptors, Immunologic %K United States %X

The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.

%B Commun Biol %V 5 %P 756 %8 2022 07 28 %G eng %N 1 %R 10.1038/s42003-022-03702-4 %0 Journal Article %J J Am Heart Assoc %D 2023 %T Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk. %A Liu, Xue %A Sun, Xianbang %A Zhang, Yuankai %A Jiang, Wenqing %A Lai, Meng %A Wiggins, Kerri L %A Raffield, Laura M %A Bielak, Lawrence F %A Zhao, Wei %A Pitsillides, Achilleas %A Haessler, Jeffrey %A Zheng, Yinan %A Blackwell, Thomas W %A Yao, Jie %A Guo, Xiuqing %A Qian, Yong %A Thyagarajan, Bharat %A Pankratz, Nathan %A Rich, Stephen S %A Taylor, Kent D %A Peyser, Patricia A %A Heckbert, Susan R %A Seshadri, Sudha %A Boerwinkle, Eric %A Grove, Megan L %A Larson, Nicholas B %A Smith, Jennifer A %A Vasan, Ramachandran S %A Fitzpatrick, Annette L %A Fornage, Myriam %A Ding, Jun %A Carson, April P %A Abecasis, Goncalo %A Dupuis, Josée %A Reiner, Alexander %A Kooperberg, Charles %A Hou, Lifang %A Psaty, Bruce M %A Wilson, James G %A Levy, Daniel %A Rotter, Jerome I %A Bis, Joshua C %A Satizabal, Claudia L %A Arking, Dan E %A Liu, Chunyu %X

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). <0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1-SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04-1.12; <0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; =0.11) or in the reverse direction (β=-0.012; =0.076). Additional bidirectional Mendelian randomization analyses revealed that low-density lipoprotein cholesterol had a causal effect on mtDNA CN (β=-0.084; <0.001), but the reverse direction was not significant (=0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low-density lipoprotein cholesterol level (=0.52), whereas there was a strong direct causal effect of higher low-density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=-0.092; <0.001). Conclusions Our findings indicate that high low-density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.

%B J Am Heart Assoc %P e029090 %8 2023 Oct 07 %G eng %R 10.1161/JAHA.122.029090 %0 Journal Article %J Diabetes Care %D 2023 %T Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk. %A Tobias, Deirdre K %A Manning, Alisa K %A Wessel, Jennifer %A Raghavan, Sridharan %A Westerman, Kenneth E %A Bick, Alexander G %A DiCorpo, Daniel %A Whitsel, Eric A %A Collins, Jason %A Correa, Adolfo %A Cupples, L Adrienne %A Dupuis, Josée %A Goodarzi, Mark O %A Guo, Xiuqing %A Howard, Barbara %A Lange, Leslie A %A Liu, Simin %A Raffield, Laura M %A Reiner, Alex P %A Rich, Stephen S %A Taylor, Kent D %A Tinker, Lesley %A Wilson, James G %A Wu, Peitao %A Carson, April P %A Vasan, Ramachandran S %A Fornage, Myriam %A Psaty, Bruce M %A Kooperberg, Charles %A Rotter, Jerome I %A Meigs, James %A Manson, JoAnn E %X

OBJECTIVE: Clonal hematopoiesis of indeterminate potential (CHIP) is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in atherosclerotic coronary heart disease (CHD) and all-cause mortality, but its association with incident type 2 diabetes (T2D) is unknown. We hypothesized that CHIP is associated with elevated risk of T2D.

RESEARCH DESIGN AND METHODS: CHIP was derived from whole-genome sequencing of blood DNA in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) prospective cohorts. We performed analysis for 17,637 participants from six cohorts, without prior T2D, cardiovascular disease, or cancer. We evaluated baseline CHIP versus no CHIP prevalence with incident T2D, including associations with DNMT3A, TET2, ASXL1, JAK2, and TP53 variants. We estimated multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) with adjustment for age, sex, BMI, smoking, alcohol, education, self-reported race/ethnicity, and combined cohorts' estimates via fixed-effects meta-analysis.

RESULTS: Mean (SD) age was 63.4 (11.5) years, 76% were female, and CHIP prevalence was 6.0% (n = 1,055) at baseline. T2D was diagnosed in n = 2,467 over mean follow-up of 9.8 years. Participants with CHIP had 23% (CI = 1.04, 1.45) higher risk of T2D than those with no CHIP. Specifically, higher risk was for TET2 (HR 1.48; CI = 1.05, 2.08) and ASXL1 (HR 1.76; CI = 1.03, 2.99) mutations; DNMT3A was nonsignificant (HR 1.15; CI = 0.93, 1.43). Statistical power was limited for JAK2 and TP53 analyses.

CONCLUSIONS: CHIP was associated with higher incidence of T2D. CHIP mutations located on genes implicated in CHD and mortality were also related to T2D, suggesting shared aging-related pathology.

%B Diabetes Care %8 2023 Sep 27 %G eng %R 10.2337/dc23-0805 %0 Journal Article %J medRxiv %D 2023 %T Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications. %A Suzuki, Ken %A Hatzikotoulas, Konstantinos %A Southam, Lorraine %A Taylor, Henry J %A Yin, Xianyong %A Lorenz, Kim M %A Mandla, Ravi %A Huerta-Chagoya, Alicia %A Rayner, Nigel W %A Bocher, Ozvan %A Ana Luiza de, S V Arruda %A Sonehara, Kyuto %A Namba, Shinichi %A Lee, Simon S K %A Preuss, Michael H %A Petty, Lauren E %A Schroeder, Philip %A Vanderwerff, Brett %A Kals, Mart %A Bragg, Fiona %A Lin, Kuang %A Guo, Xiuqing %A Zhang, Weihua %A Yao, Jie %A Kim, Young Jin %A Graff, Mariaelisa %A Takeuchi, Fumihiko %A Nano, Jana %A Lamri, Amel %A Nakatochi, Masahiro %A Moon, Sanghoon %A Scott, Robert A %A Cook, James P %A Lee, Jung-Jin %A Pan, Ian %A Taliun, Daniel %A Parra, Esteban J %A Chai, Jin-Fang %A Bielak, Lawrence F %A Tabara, Yasuharu %A Hai, Yang %A Thorleifsson, Gudmar %A Grarup, Niels %A Sofer, Tamar %A Wuttke, Matthias %A Sarnowski, Chloe %A Gieger, Christian %A Nousome, Darryl %A Trompet, Stella %A Kwak, Soo-Heon %A Long, Jirong %A Sun, Meng %A Tong, Lin %A Chen, Wei-Min %A Nongmaithem, Suraj S %A Noordam, Raymond %A Lim, Victor J Y %A Tam, Claudia H T %A Joo, Yoonjung Yoonie %A Chen, Chien-Hsiun %A Raffield, Laura M %A Prins, Bram Peter %A Nicolas, Aude %A Yanek, Lisa R %A Chen, Guanjie %A Brody, Jennifer A %A Kabagambe, Edmond %A An, Ping %A Xiang, Anny H %A Choi, Hyeok Sun %A Cade, Brian E %A Tan, Jingyi %A Alaine Broadaway, K %A Williamson, Alice %A Kamali, Zoha %A Cui, Jinrui %A Adair, Linda S %A Adeyemo, Adebowale %A Aguilar-Salinas, Carlos A %A Ahluwalia, Tarunveer S %A Anand, Sonia S %A Bertoni, Alain %A Bork-Jensen, Jette %A Brandslund, Ivan %A Buchanan, Thomas A %A Burant, Charles F %A Butterworth, Adam S %A Canouil, Mickaël %A Chan, Juliana C N %A Chang, Li-Ching %A Chee, Miao-Li %A Chen, Ji %A Chen, Shyh-Huei %A Chen, Yuan-Tsong %A Chen, Zhengming %A Chuang, Lee-Ming %A Cushman, Mary %A Danesh, John %A Das, Swapan K %A Janaka de Silva, H %A Dedoussis, George %A Dimitrov, Latchezar %A Doumatey, Ayo P %A Du, Shufa %A Duan, Qing %A Eckardt, Kai-Uwe %A Emery, Leslie S %A Evans, Daniel S %A Evans, Michele K %A Fischer, Krista %A Floyd, James S %A Ford, Ian %A Franco, Oscar H %A Frayling, Timothy M %A Freedman, Barry I %A Genter, Pauline %A Gerstein, Hertzel C %A Giedraitis, Vilmantas %A González-Villalpando, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Gordon-Larsen, Penny %A Gross, Myron %A Guare, Lindsay A %A Hackinger, Sophie %A Han, Sohee %A Hattersley, Andrew T %A Herder, Christian %A Horikoshi, Momoko %A Howard, Annie-Green %A Hsueh, Willa %A Huang, Mengna %A Huang, Wei %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Hwu, Chii-Min %A Ichihara, Sahoko %A Ikram, Mohammad Arfan %A Ingelsson, Martin %A Islam, Md Tariqul %A Isono, Masato %A Jang, Hye-Mi %A Jasmine, Farzana %A Jiang, Guozhi %A Jonas, Jost B %A Jørgensen, Torben %A Kandeel, Fouad R %A Kasturiratne, Anuradhani %A Katsuya, Tomohiro %A Kaur, Varinderpal %A Kawaguchi, Takahisa %A Keaton, Jacob M %A Kho, Abel N %A Khor, Chiea-Chuen %A Kibriya, Muhammad G %A Kim, Duk-Hwan %A Kronenberg, Florian %A Kuusisto, Johanna %A Läll, Kristi %A Lange, Leslie A %A Lee, Kyung Min %A Lee, Myung-Shik %A Lee, Nanette R %A Leong, Aaron %A Li, Liming %A Li, Yun %A Li-Gao, Ruifang %A Lithgart, Symen %A Lindgren, Cecilia M %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Locke, Adam E %A Louie, Tin %A Luan, Jian'an %A Luk, Andrea O %A Luo, Xi %A Lv, Jun %A Lynch, Julie A %A Lyssenko, Valeriya %A Maeda, Shiro %A Mamakou, Vasiliki %A Mansuri, Sohail Rafik %A Matsuda, Koichi %A Meitinger, Thomas %A Metspalu, Andres %A Mo, Huan %A Morris, Andrew D %A Nadler, Jerry L %A Nalls, Michael A %A Nayak, Uma %A Ntalla, Ioanna %A Okada, Yukinori %A Orozco, Lorena %A Patel, Sanjay R %A Patil, Snehal %A Pei, Pei %A Pereira, Mark A %A Peters, Annette %A Pirie, Fraser J %A Polikowsky, Hannah G %A Porneala, Bianca %A Prasad, Gauri %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Roden, Michael %A Rohde, Rebecca %A Roll, Katheryn %A Sabanayagam, Charumathi %A Sandow, Kevin %A Sankareswaran, Alagu %A Sattar, Naveed %A Schönherr, Sebastian %A Shahriar, Mohammad %A Shen, Botong %A Shi, Jinxiu %A Shin, Dong Mun %A Shojima, Nobuhiro %A Smith, Jennifer A %A So, Wing Yee %A Stančáková, Alena %A Steinthorsdottir, Valgerdur %A Stilp, Adrienne M %A Strauch, Konstantin %A Taylor, Kent D %A Thorand, Barbara %A Thorsteinsdottir, Unnur %A Tomlinson, Brian %A Tran, Tam C %A Tsai, Fuu-Jen %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A Valladares-Salgado, Adan %A van Dam, Rob M %A van Klinken, Jan B %A Varma, Rohit %A Wacher-Rodarte, Niels %A Wheeler, Eleanor %A Wickremasinghe, Ananda R %A van Dijk, Ko Willems %A Witte, Daniel R %A Yajnik, Chittaranjan S %A Yamamoto, Ken %A Yamamoto, Kenichi %A Yoon, Kyungheon %A Yu, Canqing %A Yuan, Jian-Min %A Yusuf, Salim %A Zawistowski, Matthew %A Zhang, Liang %A Zheng, Wei %A Project, Biobank Japan %A BioBank, Penn Medicine %A Center, Regeneron Genetics %A Consortium, eMERGE %A Raffel, Leslie J %A Igase, Michiya %A Ipp, Eli %A Redline, Susan %A Cho, Yoon Shin %A Lind, Lars %A Province, Michael A %A Fornage, Myriam %A Hanis, Craig L %A Ingelsson, Erik %A Zonderman, Alan B %A Psaty, Bruce M %A Wang, Ya-Xing %A Rotimi, Charles N %A Becker, Diane M %A Matsuda, Fumihiko %A Liu, Yongmei %A Yokota, Mitsuhiro %A Kardia, Sharon L R %A Peyser, Patricia A %A Pankow, James S %A Engert, James C %A Bonnefond, Amélie %A Froguel, Philippe %A Wilson, James G %A Sheu, Wayne H H %A Wu, Jer-Yuarn %A Geoffrey Hayes, M %A Ma, Ronald C W %A Wong, Tien-Yin %A Mook-Kanamori, Dennis O %A Tuomi, Tiinamaija %A Chandak, Giriraj R %A Collins, Francis S %A Bharadwaj, Dwaipayan %A Paré, Guillaume %A Sale, Michèle M %A Ahsan, Habibul %A Motala, Ayesha A %A Shu, Xiao-Ou %A Park, Kyong-Soo %A Jukema, J Wouter %A Cruz, Miguel %A Chen, Yii-Der Ida %A Rich, Stephen S %A McKean-Cowdin, Roberta %A Grallert, Harald %A Cheng, Ching-Yu %A Ghanbari, Mohsen %A Tai, E-Shyong %A Dupuis, Josée %A Kato, Norihiro %A Laakso, Markku %A Köttgen, Anna %A Koh, Woon-Puay %A Bowden, Donald W %A Palmer, Colin N A %A Kooner, Jaspal S %A Kooperberg, Charles %A Liu, Simin %A North, Kari E %A Saleheen, Danish %A Hansen, Torben %A Pedersen, Oluf %A Wareham, Nicholas J %A Lee, Juyoung %A Kim, Bong-Jo %A Millwood, Iona Y %A Walters, Robin G %A Stefansson, Kari %A Goodarzi, Mark O %A Mohlke, Karen L %A Langenberg, Claudia %A Haiman, Christopher A %A Loos, Ruth J F %A Florez, Jose C %A Rader, Daniel J %A Ritchie, Marylyn D %A Zöllner, Sebastian %A Mägi, Reedik %A Denny, Joshua C %A Yamauchi, Toshimasa %A Kadowaki, Takashi %A Chambers, John C %A Ng, Maggie C Y %A Sim, Xueling %A Below, Jennifer E %A Tsao, Philip S %A Chang, Kyong-Mi %A McCarthy, Mark I %A Meigs, James B %A Mahajan, Anubha %A Spracklen, Cassandra N %A Mercader, Josep M %A Boehnke, Michael %A Rotter, Jerome I %A Vujkovic, Marijana %A Voight, Benjamin F %A Morris, Andrew P %A Zeggini, Eleftheria %X

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10 ) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.

%B medRxiv %8 2023 Mar 31 %G eng %R 10.1101/2023.03.31.23287839 %0 Journal Article %J medRxiv %D 2023 %T Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus. %A Kwak, Soo Heon %A Hernandez-Cancela, Ryan B %A DiCorpo, Daniel A %A Condon, David E %A Merino, Jordi %A Wu, Peitao %A Brody, Jennifer A %A Yao, Jie %A Guo, Xiuqing %A Ahmadizar, Fariba %A Meyer, Mariah %A Sincan, Murat %A Mercader, Josep M %A Lee, Sujin %A Haessler, Jeffrey %A Vy, Ha My T %A Lin, Zhaotong %A Armstrong, Nicole D %A Gu, Shaopeng %A Tsao, Noah L %A Lange, Leslie A %A Wang, Ningyuan %A Wiggins, Kerri L %A Trompet, Stella %A Liu, Simin %A Loos, Ruth J F %A Judy, Renae %A Schroeder, Philip H %A Hasbani, Natalie R %A Bos, Maxime M %A Morrison, Alanna C %A Jackson, Rebecca D %A Reiner, Alexander P %A Manson, JoAnn E %A Chaudhary, Ninad S %A Carmichael, Lynn K %A Chen, Yii-Der Ida %A Taylor, Kent D %A Ghanbari, Mohsen %A van Meurs, Joyce %A Pitsillides, Achilleas N %A Psaty, Bruce M %A Noordam, Raymond %A Do, Ron %A Park, Kyong Soo %A Jukema, J Wouter %A Kavousi, Maryam %A Correa, Adolfo %A Rich, Stephen S %A Damrauer, Scott M %A Hajek, Catherine %A Cho, Nam H %A Irvin, Marguerite R %A Pankow, James S %A Nadkarni, Girish N %A Sladek, Robert %A Goodarzi, Mark O %A Florez, Jose C %A Chasman, Daniel I %A Heckbert, Susan R %A Kooperberg, Charles %A Dupuis, Josée %A Malhotra, Rajeev %A de Vries, Paul S %A Liu, Ching-Ti %A Rotter, Jerome I %A Meigs, James B %X

BACKGROUND: Type 2 diabetes mellitus (T2D) confers a two- to three-fold increased risk of cardiovascular disease (CVD). However, the mechanisms underlying increased CVD risk among people with T2D are only partially understood. We hypothesized that a genetic association study among people with T2D at risk for developing incident cardiovascular complications could provide insights into molecular genetic aspects underlying CVD.

METHODS: From 16 studies of the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) Consortium, we conducted a multi-ancestry time-to-event genome-wide association study (GWAS) for incident CVD among people with T2D using Cox proportional hazards models. Incident CVD was defined based on a composite of coronary artery disease (CAD), stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. Cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. We also tested 204 known CAD variants for association with incident CVD among patients with T2D.

RESULTS: A total of 49,230 participants with T2D were included in the analyses (31,118 European ancestries and 18,112 non-European ancestries) which consisted of 8,956 incident CVD cases over a range of mean follow-up duration between 3.2 and 33.7 years (event rate 18.2%). We identified three novel, distinct genetic loci for incident CVD among individuals with T2D that reached the threshold for genome-wide significance ( <5.0×10 ): rs147138607 (intergenic variant between and ) with a hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.15 - 1.32, =3.6×10 , rs11444867 (intergenic variant near ) with HR 1.89, 95% CI 1.52 - 2.35, =9.9×10 , and rs335407 (intergenic variant between and ) HR 1.25, 95% CI 1.16 - 1.35, =1.5×10 . Among 204 known CAD loci, 32 were associated with incident CVD in people with T2D with <0.05, and 5 were significant after Bonferroni correction ( <0.00024, 0.05/204). A polygenic score of these 204 variants was significantly associated with incident CVD with HR 1.14 (95% CI 1.12 - 1.16) per 1 standard deviation increase ( =1.0×10 ).

CONCLUSIONS: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.

CLINICAL PERSPECTIVE: We conducted a large-scale multi-ancestry time-to-event GWAS to identify genetic variants associated with CVD among people with T2D. Three variants were significantly associated with incident CVD in people with T2D: rs147138607 (intergenic variant between and ), rs11444867 (intergenic variant near ), and rs335407 (intergenic variant between and ). A polygenic score composed of known CAD variants identified in the general population was significantly associated with the risk of CVD in people with T2D. There are genetic risk factors specific to T2D that could at least partially explain the excess risk of CVD in people with T2D.In addition, we show that people with T2D have enrichment of known CAD association signals which could also explain the excess risk of CVD.

%B medRxiv %8 2023 Jul 28 %G eng %R 10.1101/2023.07.25.23293180 %0 Journal Article %J J Endocr Soc %D 2023 %T A Type 1 Diabetes Polygenic Score Is Not Associated With Prevalent Type 2 Diabetes in Large Population Studies. %A Srinivasan, Shylaja %A Wu, Peitao %A Mercader, Josep M %A Udler, Miriam S %A Porneala, Bianca C %A Bartz, Traci M %A Floyd, James S %A Sitlani, Colleen %A Guo, Xiquing %A Haessler, Jeffrey %A Kooperberg, Charles %A Liu, Jun %A Ahmad, Shahzad %A van Duijn, Cornelia %A Liu, Ching-Ti %A Goodarzi, Mark O %A Florez, Jose C %A Meigs, James B %A Rotter, Jerome I %A Rich, Stephen S %A Dupuis, Josée %A Leong, Aaron %X

CONTEXT: Both type 1 diabetes (T1D) and type 2 diabetes (T2D) have significant genetic contributions to risk and understanding their overlap can offer clinical insight.

OBJECTIVE: We examined whether a T1D polygenic score (PS) was associated with a diagnosis of T2D in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.

METHODS: We constructed a T1D PS using 79 known single nucleotide polymorphisms associated with T1D risk. We analyzed 13 792 T2D cases and 14 169 controls from CHARGE cohorts to determine the association between the T1D PS and T2D prevalence. We validated findings in an independent sample of 2256 T2D cases and 27 052 controls from the Mass General Brigham Biobank (MGB Biobank). As secondary analyses in 5228 T2D cases from CHARGE, we used multivariable regression models to assess the association of the T1D PS with clinical outcomes associated with T1D.

RESULTS: The T1D PS was not associated with T2D both in CHARGE ( = .15) and in the MGB Biobank ( = .87). The partitioned human leukocyte antigens only PS was associated with T2D in CHARGE (OR 1.02 per 1 SD increase in PS, 95% CI 1.01-1.03, = .006) but not in the MGB Biobank. The T1D PS was weakly associated with insulin use (OR 1.007, 95% CI 1.001-1.012, = .03) in CHARGE T2D cases but not with other outcomes.

CONCLUSION: In large biobank samples, a common variant PS for T1D was not consistently associated with prevalent T2D. However, possible heterogeneity in T2D cannot be ruled out and future studies are needed do subphenotyping.

%B J Endocr Soc %V 7 %P bvad123 %8 2023 Oct 09 %G eng %N 11 %R 10.1210/jendso/bvad123 %0 Journal Article %J bioRxiv %D 2023 %T Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium. %A Jiang, Min-Zhi %A Gaynor, Sheila M %A Li, Xihao %A Van Buren, Eric %A Stilp, Adrienne %A Buth, Erin %A Wang, Fei Fei %A Manansala, Regina %A Gogarten, Stephanie M %A Li, Zilin %A Polfus, Linda M %A Salimi, Shabnam %A Bis, Joshua C %A Pankratz, Nathan %A Yanek, Lisa R %A Durda, Peter %A Tracy, Russell P %A Rich, Stephen S %A Rotter, Jerome I %A Mitchell, Braxton D %A Lewis, Joshua P %A Psaty, Bruce M %A Pratte, Katherine A %A Silverman, Edwin K %A Kaplan, Robert C %A Avery, Christy %A North, Kari %A Mathias, Rasika A %A Faraday, Nauder %A Lin, Honghuang %A Wang, Biqi %A Carson, April P %A Norwood, Arnita F %A Gibbs, Richard A %A Kooperberg, Charles %A Lundin, Jessica %A Peters, Ulrike %A Dupuis, Josée %A Hou, Lifang %A Fornage, Myriam %A Benjamin, Emelia J %A Reiner, Alexander P %A Bowler, Russell P %A Lin, Xihong %A Auer, Paul L %A Raffield, Laura M %X

Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.

%B bioRxiv %8 2023 Sep 12 %G eng %R 10.1101/2023.09.10.555215 %0 Journal Article %J Nature %D 2024 %T Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. %A Suzuki, Ken %A Hatzikotoulas, Konstantinos %A Southam, Lorraine %A Taylor, Henry J %A Yin, Xianyong %A Lorenz, Kim M %A Mandla, Ravi %A Huerta-Chagoya, Alicia %A Melloni, Giorgio E M %A Kanoni, Stavroula %A Rayner, Nigel W %A Bocher, Ozvan %A Arruda, Ana Luiza %A Sonehara, Kyuto %A Namba, Shinichi %A Lee, Simon S K %A Preuss, Michael H %A Petty, Lauren E %A Schroeder, Philip %A Vanderwerff, Brett %A Kals, Mart %A Bragg, Fiona %A Lin, Kuang %A Guo, Xiuqing %A Zhang, Weihua %A Yao, Jie %A Kim, Young Jin %A Graff, Mariaelisa %A Takeuchi, Fumihiko %A Nano, Jana %A Lamri, Amel %A Nakatochi, Masahiro %A Moon, Sanghoon %A Scott, Robert A %A Cook, James P %A Lee, Jung-Jin %A Pan, Ian %A Taliun, Daniel %A Parra, Esteban J %A Chai, Jin-Fang %A Bielak, Lawrence F %A Tabara, Yasuharu %A Hai, Yang %A Thorleifsson, Gudmar %A Grarup, Niels %A Sofer, Tamar %A Wuttke, Matthias %A Sarnowski, Chloe %A Gieger, Christian %A Nousome, Darryl %A Trompet, Stella %A Kwak, Soo-Heon %A Long, Jirong %A Sun, Meng %A Tong, Lin %A Chen, Wei-Min %A Nongmaithem, Suraj S %A Noordam, Raymond %A Lim, Victor J Y %A Tam, Claudia H T %A Joo, Yoonjung Yoonie %A Chen, Chien-Hsiun %A Raffield, Laura M %A Prins, Bram Peter %A Nicolas, Aude %A Yanek, Lisa R %A Chen, Guanjie %A Brody, Jennifer A %A Kabagambe, Edmond %A An, Ping %A Xiang, Anny H %A Choi, Hyeok Sun %A Cade, Brian E %A Tan, Jingyi %A Broadaway, K Alaine %A Williamson, Alice %A Kamali, Zoha %A Cui, Jinrui %A Thangam, Manonanthini %A Adair, Linda S %A Adeyemo, Adebowale %A Aguilar-Salinas, Carlos A %A Ahluwalia, Tarunveer S %A Anand, Sonia S %A Bertoni, Alain %A Bork-Jensen, Jette %A Brandslund, Ivan %A Buchanan, Thomas A %A Burant, Charles F %A Butterworth, Adam S %A Canouil, Mickaël %A Chan, Juliana C N %A Chang, Li-Ching %A Chee, Miao-Li %A Chen, Ji %A Chen, Shyh-Huei %A Chen, Yuan-Tsong %A Chen, Zhengming %A Chuang, Lee-Ming %A Cushman, Mary %A Danesh, John %A Das, Swapan K %A de Silva, H Janaka %A Dedoussis, George %A Dimitrov, Latchezar %A Doumatey, Ayo P %A Du, Shufa %A Duan, Qing %A Eckardt, Kai-Uwe %A Emery, Leslie S %A Evans, Daniel S %A Evans, Michele K %A Fischer, Krista %A Floyd, James S %A Ford, Ian %A Franco, Oscar H %A Frayling, Timothy M %A Freedman, Barry I %A Genter, Pauline %A Gerstein, Hertzel C %A Giedraitis, Vilmantas %A González-Villalpando, Clicerio %A Gonzalez-Villalpando, Maria Elena %A Gordon-Larsen, Penny %A Gross, Myron %A Guare, Lindsay A %A Hackinger, Sophie %A Hakaste, Liisa %A Han, Sohee %A Hattersley, Andrew T %A Herder, Christian %A Horikoshi, Momoko %A Howard, Annie-Green %A Hsueh, Willa %A Huang, Mengna %A Huang, Wei %A Hung, Yi-Jen %A Hwang, Mi Yeong %A Hwu, Chii-Min %A Ichihara, Sahoko %A Ikram, Mohammad Arfan %A Ingelsson, Martin %A Islam, Md Tariqul %A Isono, Masato %A Jang, Hye-Mi %A Jasmine, Farzana %A Jiang, Guozhi %A Jonas, Jost B %A Jørgensen, Torben %A Kamanu, Frederick K %A Kandeel, Fouad R %A Kasturiratne, Anuradhani %A Katsuya, Tomohiro %A Kaur, Varinderpal %A Kawaguchi, Takahisa %A Keaton, Jacob M %A Kho, Abel N %A Khor, Chiea-Chuen %A Kibriya, Muhammad G %A Kim, Duk-Hwan %A Kronenberg, Florian %A Kuusisto, Johanna %A Läll, Kristi %A Lange, Leslie A %A Lee, Kyung Min %A Lee, Myung-Shik %A Lee, Nanette R %A Leong, Aaron %A Li, Liming %A Li, Yun %A Li-Gao, Ruifang %A Ligthart, Symen %A Lindgren, Cecilia M %A Linneberg, Allan %A Liu, Ching-Ti %A Liu, Jianjun %A Locke, Adam E %A Louie, Tin %A Luan, Jian'an %A Luk, Andrea O %A Luo, Xi %A Lv, Jun %A Lynch, Julie A %A Lyssenko, Valeriya %A Maeda, Shiro %A Mamakou, Vasiliki %A Mansuri, Sohail Rafik %A Matsuda, Koichi %A Meitinger, Thomas %A Melander, Olle %A Metspalu, Andres %A Mo, Huan %A Morris, Andrew D %A Moura, Filipe A %A Nadler, Jerry L %A Nalls, Michael A %A Nayak, Uma %A Ntalla, Ioanna %A Okada, Yukinori %A Orozco, Lorena %A Patel, Sanjay R %A Patil, Snehal %A Pei, Pei %A Pereira, Mark A %A Peters, Annette %A Pirie, Fraser J %A Polikowsky, Hannah G %A Porneala, Bianca %A Prasad, Gauri %A Rasmussen-Torvik, Laura J %A Reiner, Alexander P %A Roden, Michael %A Rohde, Rebecca %A Roll, Katheryn %A Sabanayagam, Charumathi %A Sandow, Kevin %A Sankareswaran, Alagu %A Sattar, Naveed %A Schönherr, Sebastian %A Shahriar, Mohammad %A Shen, Botong %A Shi, Jinxiu %A Shin, Dong Mun %A Shojima, Nobuhiro %A Smith, Jennifer A %A So, Wing Yee %A Stančáková, Alena %A Steinthorsdottir, Valgerdur %A Stilp, Adrienne M %A Strauch, Konstantin %A Taylor, Kent D %A Thorand, Barbara %A Thorsteinsdottir, Unnur %A Tomlinson, Brian %A Tran, Tam C %A Tsai, Fuu-Jen %A Tuomilehto, Jaakko %A Tusié-Luna, Teresa %A Udler, Miriam S %A Valladares-Salgado, Adan %A van Dam, Rob M %A van Klinken, Jan B %A Varma, Rohit %A Wacher-Rodarte, Niels %A Wheeler, Eleanor %A Wickremasinghe, Ananda R %A van Dijk, Ko Willems %A Witte, Daniel R %A Yajnik, Chittaranjan S %A Yamamoto, Ken %A Yamamoto, Kenichi %A Yoon, Kyungheon %A Yu, Canqing %A Yuan, Jian-Min %A Yusuf, Salim %A Zawistowski, Matthew %A Zhang, Liang %A Zheng, Wei %A Raffel, Leslie J %A Igase, Michiya %A Ipp, Eli %A Redline, Susan %A Cho, Yoon Shin %A Lind, Lars %A Province, Michael A %A Fornage, Myriam %A Hanis, Craig L %A Ingelsson, Erik %A Zonderman, Alan B %A Psaty, Bruce M %A Wang, Ya-Xing %A Rotimi, Charles N %A Becker, Diane M %A Matsuda, Fumihiko %A Liu, Yongmei %A Yokota, Mitsuhiro %A Kardia, Sharon L R %A Peyser, Patricia A %A Pankow, James S %A Engert, James C %A Bonnefond, Amélie %A Froguel, Philippe %A Wilson, James G %A Sheu, Wayne H H %A Wu, Jer-Yuarn %A Hayes, M Geoffrey %A Ma, Ronald C W %A Wong, Tien-Yin %A Mook-Kanamori, Dennis O %A Tuomi, Tiinamaija %A Chandak, Giriraj R %A Collins, Francis S %A Bharadwaj, Dwaipayan %A Paré, Guillaume %A Sale, Michèle M %A Ahsan, Habibul %A Motala, Ayesha A %A Shu, Xiao-Ou %A Park, Kyong-Soo %A Jukema, J Wouter %A Cruz, Miguel %A Chen, Yii-Der Ida %A Rich, Stephen S %A McKean-Cowdin, Roberta %A Grallert, Harald %A Cheng, Ching-Yu %A Ghanbari, Mohsen %A Tai, E-Shyong %A Dupuis, Josée %A Kato, Norihiro %A Laakso, Markku %A Köttgen, Anna %A Koh, Woon-Puay %A Bowden, Donald W %A Palmer, Colin N A %A Kooner, Jaspal S %A Kooperberg, Charles %A Liu, Simin %A North, Kari E %A Saleheen, Danish %A Hansen, Torben %A Pedersen, Oluf %A Wareham, Nicholas J %A Lee, Juyoung %A Kim, Bong-Jo %A Millwood, Iona Y %A Walters, Robin G %A Stefansson, Kari %A Ahlqvist, Emma %A Goodarzi, Mark O %A Mohlke, Karen L %A Langenberg, Claudia %A Haiman, Christopher A %A Loos, Ruth J F %A Florez, Jose C %A Rader, Daniel J %A Ritchie, Marylyn D %A Zöllner, Sebastian %A Mägi, Reedik %A Marston, Nicholas A %A Ruff, Christian T %A van Heel, David A %A Finer, Sarah %A Denny, Joshua C %A Yamauchi, Toshimasa %A Kadowaki, Takashi %A Chambers, John C %A Ng, Maggie C Y %A Sim, Xueling %A Below, Jennifer E %A Tsao, Philip S %A Chang, Kyong-Mi %A McCarthy, Mark I %A Meigs, James B %A Mahajan, Anubha %A Spracklen, Cassandra N %A Mercader, Josep M %A Boehnke, Michael %A Rotter, Jerome I %A Vujkovic, Marijana %A Voight, Benjamin F %A Morris, Andrew P %A Zeggini, Eleftheria %X

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

%B Nature %8 2024 Feb 19 %G eng %R 10.1038/s41586-024-07019-6