Browsing by Author "Liu, Ching-Ti"

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    A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation
    (Springer Nature, 2022) Vujkovic, Marijana; Ramdas, Shweta; Lorenz, Kim M.; Guo, Xiuqing; Darlay, Rebecca; Cordell, Heather J.; He, Jing; Gindin, Yevgeniy; Chung, Chuhan; Myers, Robert P.; Schneider, Carolin V.; Park, Joseph; Lee, Kyung Min; Serper, Marina; Carr, Rotonya M.; Kaplan, David E.; Haas, Mary E.; MacLean, Matthew T.; Witschey, Walter R.; Zhu, Xiang; Tcheandjieu, Catherine; Kember, Rachel L.; Kranzler, Henry R.; Verma, Anurag; Giri, Ayush; Klarin, Derek M.; Sun, Yan V.; Huang, Jie; Huffman, Jennifer E.; Townsend Creasy, Kate; Hand, Nicholas J.; Liu, Ching-Ti; Long, Michelle T.; Yao, Jie; Budoff, Matthew; Tan, Jingyi; Li, Xiaohui; Lin, Henry J.; Chen, Yii-Der Ida; Taylor, Kent D.; Chang, Ruey-Kang; Krauss, Ronald M.; Vilarinho, Silvia; Brancale, Joseph; Nielsen, Jonas B.; Locke, Adam E.; Jones, Marcus B.; Verweij, Niek; Baras, Aris; Reddy, K. Rajender; Neuschwander-Tetri, Brent A.; Schwimmer, Jeffrey B.; Sanyal, Arun J.; Chalasani, Naga; Ryan, Kathleen A.; Mitchell, Braxton D.; Gill, Dipender; Wells, Andrew D.; Manduchi, Elisabetta; Saiman, Yedidya; Mahmud, Nadim; Miller, Donald R.; Reaven, Peter D.; Phillips, Lawrence S.; Muralidhar, Sumitra; DuVall, Scott L.; Lee, Jennifer S.; Assimes, Themistocles L.; Pyarajan, Saiju; Cho, Kelly; Edwards, Todd L.; Damrauer, Scott M.; Wilson, Peter W.; Gaziano, J. Michael; O'Donnell, Christopher J.; Khera, Amit V.; Grant, Struan F. A.; Brown, Christopher D.; Tsao, Philip S.; Saleheen, Danish; Lotta, Luca A.; Bastarache, Lisa; Anstee, Quentin M.; Daly, Ann K.; Meigs, James B.; Rotter, Jerome I.; Lynch, Julie A.; Regeneron Genetics Center; Geisinger-Regeneron DiscovEHR Collaboration; EPoS Consortium; VA Million Veteran Program; Rader, Daniel J.; Voight, Benjamin F.; Chang, Kyong-Mi; Medicine, School of Medicine
    Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic elevation of alanine aminotransferase (cALT) levels without other liver diseases, we performed a multiancestry genome-wide association study (GWAS) in the Million Veteran Program (MVP) including 90,408 cALT cases and 128,187 controls. Seventy-seven loci exceeded genome-wide significance, including 25 without prior NAFLD or alanine aminotransferase associations, with one additional locus identified in European American-only and two in African American-only analyses (P < 5 × 10-8). External replication in histology-defined NAFLD cohorts (7,397 cases and 56,785 controls) or radiologic imaging cohorts (n = 44,289) replicated 17 single-nucleotide polymorphisms (SNPs) (P < 6.5 × 10-4), of which 9 were new (TRIB1, PPARG, MTTP, SERPINA1, FTO, IL1RN, COBLL1, APOH and IFI30). Pleiotropy analysis showed that 61 of 77 multiancestry and all 17 replicated SNPs were jointly associated with metabolic and/or inflammatory traits, revealing a complex model of genetic architecture. Our approach integrating cALT, histology and imaging reveals new insights into genetic liability to NAFLD.
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    Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels
    (Nature Publishing Group, 2018-01-17) Jiang, Xia; O’Reilly, Paul F.; Aschard, Hugues; Hsu, Yi-Hsiang; Richards, J. Brent; Dupuis, Josée; Ingelsson, Erik; Karasik, David; Pilz, Stefan; Berry, Diane; Kestenbaum, Bryan; Zheng, Jusheng; Luan, Jianan; Sofianopoulou, Eleni; Streeten, Elizabeth A.; Albanes, Demetrius; Lutsey, Pamela L.; Yao, Lu; Tang, Weihong; Econs, Michael J.; Wallaschofski, Henri; Völzke, Henry; Zhou, Ang; Power, Chris; McCarthy, Mark I.; Michos, Erin D.; Boerwinkle, Eric; Weinstein, Stephanie J.; Freedman, Neal D.; Huang, Wen-Yi; Van Schoor, Natasja M.; Velde, Nathalie van der; de Groot, Lisette C. P. G. M.; Enneman, Anke; Cupples, L. Adrienne; Booth, Sarah L.; Vasan, Ramachandran S.; Liu, Ching-Ti; Zhou, Yanhua; Ripatti, Samuli; Ohlsson, Claes; Vandenput, Liesbeth; Lorentzon, Mattias; Eriksson, Johan G.; Shea, M. Kyla; Houston, Denise K.; Kritchevsky, Stephen B.; Liu, Yongmei; Lohman, Kurt K.; Ferrucci, Luigi; Peacock, Munro; Gieger, Christian; Beekman, Marian; Slagboom, Eline; Deelen, Joris; Heemst, Diana van; Kleber, Marcus E.; März, Winfried; de Boer, Ian H.; Wood, Alexis C.; Rotter, Jerome I.; Rich, Stephen S.; Robinson-Cohen, Cassianne; Heijer, Martin den; Jarvelin, Marjo-Riitta; Cavadino, Alana; Joshi, Peter K.; Wilson, James F.; Hayward, Caroline; Lind, Lars; Michaëlsson, Karl; Trompet, Stella; Zillikens, M. Carola; Uitterlinden, Andre G.; Rivadeneira, Fernando; Broer, Linda; Zgaga, Lina; Campbell, Harry; Theodoratou, Evropi; Farrington, Susan M.; Timofeeva, Maria; Dunlop, Malcolm G.; Valdes, Ana M.; Tikkanen, Emmi; Lehtimäki, Terho; Lyytikäinen, Leo-Pekka; Kähönen, Mika; Raitakari, Olli T.; Mikkilä, Vera; Ikram, M. Arfan; Sattar, Naveed; Jukema, J. Wouter; Wareham, Nicholas J.; Langenberg, Claudia; Forouhi, Nita G.; Gundersen, Thomas E.; Khaw, Kay-Tee; Butterworth, Adam S.; Danesh, John; Spector, Timothy; Wang, Thomas J.; Hyppönen, Elina; Kraft, Peter; Kiel, Douglas P.; Medicine, School of Medicine
    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 = 4.7×10-9 at rs8018720 in SEC23A, and P = 1.9×10-14 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
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    Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program
    (Elsevier, 2019-09-26) Sarnowski, Chloé; Leong, Aaron; Raffield, Laura M.; Wu, Peitao; de Vries, Paul S.; DiCorpo, Daniel; Guo, Xiuqing; Xu, Huichun; Liu, Yongmei; Zheng, Xiuwen; Hu, Yao; Brody, Jennifer A.; Goodarzi, Mark O.; Hidalgo, Bertha A.; Highland, Heather M.; Jain, Deepti; Liu, Ching-Ti; Naik, Rakhi P.; O’Connell, Jeffrey R.; Perry, James A.; Porneala, Bianca C.; Selvin, Elizabeth; Wessel, Jennifer; Psaty, Bruce M.; Curran, Joanne E.; Peralta, Juan M.; Blangero, John; Kooperberg, Charles; Mathias, Rasika; Johnson, Andrew D.; Reiner, Alexander P.; Mitchell, Braxton D.; Cupples, L. Adrienne; Vasan, Ramachandran S.; Correa, Adolfo; Morrison, Alanna C.; Boerwinkle, Eric; Rotter, Jerome I.; Rich, Stephen S.; Manning, Alisa K.; Dupuis, Josée; Meigs, James B.; TOPMed Diabetes Working Group; TOPMed Hematology Working Group; TOPMed Hemostasis Working Group; National Heart, Lung, and Blood Institute TOPMed Consortium; Epidemiology, School of Public Health
    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.
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    Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits
    (American Diabetes Association, 2023) Westerman, Kenneth E.; Walker, Maura E.; Gaynor, Sheila M.; Wessel, Jennifer; DiCorpo, Daniel; Ma, Jiantao; Alonso, Alvaro; Aslibekyan, Stella; Baldridge, Abigail S.; Bertoni, Alain G.; Biggs, Mary L.; Brody, Jennifer A.; Chen, Yii-Der Ida; Dupuis, Joseé; Goodarzi, Mark O.; Guo, Xiuqing; Hasbani, Natalie R.; Heath, Adam; Hidalgo, Bertha; Irvin, Marguerite R.; Johnson, W. Craig; Kalyani, Rita R.; Lange, Leslie; Lemaitre, Rozenn N.; Liu, Ching-Ti; Liu, Simin; Moon, Jee-Young; Nassir, Rami; Pankow, James S.; Pettinger, Mary; Raffield, Laura M.; Rasmussen-Torvik, Laura J.; Selvin, Elizabeth; Senn, Mackenzie K.; Shadyab, Aladdin H.; Smith, Albert V.; Smith, Nicholas L.; Steffen, Lyn; Talegakwar, Sameera; Taylor, Kent D.; de Vries, Paul S.; Wilson, James G.; Wood, Alexis C.; Yanek, Lisa R.; Yao, Jie; Zheng, Yinan; Boerwinkle, Eric; Morrison, Alanna C.; Fornage, Miriam; Russell, Tracy P.; Psaty, Bruce M.; Levy, Daniel; Heard-Costa, Nancy L.; Ramachandran, Vasan S.; Mathias, Rasika A.; Arnett, Donna K.; Kaplan, Robert; North, Kari E.; Correa, Adolfo; Carson, April; Rotter, Jerome I.; Rich, Stephen S.; Manson, JoAnn E.; Reiner, Alexander P.; Kooperberg, Charles; Florez, Jose C.; Meigs, James B.; Merino, Jordi; Tobias, Deirdre K.; Chen, Han; Manning, Alisa K.; Epidemiology, Richard M. Fairbanks School of Public Health
    Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry. Article highlights: We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.
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    Meta-analysis of genome-wide studies identifies WNT16 and ESR1 SNPs associated with bone mineral density in premenopausal women
    (Oxford University Press, 2013) Koller, Daniel L.; Zheng, Hou-Feng; Karasik, David; Yerges-Armstrong, Laura; Liu, Ching-Ti; McGuigan, Fiona; Kemp, John P.; Giroux, Sylvie; Lai, Dongbing; Edenberg, Howard J.; Peacock, Munro; Czerwinski, Stefan A.; Choh, Audrey C.; McMahon, George; St. Pourcain, Beate; Timpson, Nicholas J.; Lawlor, Debbie A.; Evans, David M.; Towne, Bradford; Blangero, John; Carless, Melanie A.; Kammerer, Candace; Goltzman, David; Kovacs, Christopher S.; Prior, Jerilynn C.; Spector, Tim D.; Rousseau, Francois; Tobias, Jon H.; Akesson, Kristina; Econs, Michael J.; Mitchell, Braxton D.; Richards, J. Brent; Kiel, Douglas P.; Foroud, Tatiana; Medical and Molecular Genetics, School of Medicine
    Previous genome-wide association studies (GWAS) have identified common variants in genes associated with variation in bone mineral density (BMD), although most have been carried out in combined samples of older women and men. Meta-analyses of these results have identified numerous single-nucleotide polymorphisms (SNPs) of modest effect at genome-wide significance levels in genes involved in both bone formation and resorption, as well as other pathways. We performed a meta-analysis restricted to premenopausal white women from four cohorts (n = 4061 women, aged 20 to 45 years) to identify genes influencing peak bone mass at the lumbar spine and femoral neck. After imputation, age- and weight-adjusted bone-mineral density (BMD) values were tested for association with each SNP. Association of an SNP in the WNT16 gene (rs3801387; p = 1.7 × 10(-9) ) and multiple SNPs in the ESR1/C6orf97 region (rs4870044; p = 1.3 × 10(-8) ) achieved genome-wide significance levels for lumbar spine BMD. These SNPs, along with others demonstrating suggestive evidence of association, were then tested for association in seven replication cohorts that included premenopausal women of European, Hispanic-American, and African-American descent (combined n = 5597 for femoral neck; n = 4744 for lumbar spine). When the data from the discovery and replication cohorts were analyzed jointly, the evidence was more significant (WNT16 joint p = 1.3 × 10(-11) ; ESR1/C6orf97 joint p = 1.4 × 10(-10) ). Multiple independent association signals were observed with spine BMD at the ESR1 region after conditioning on the primary signal. Analyses of femoral neck BMD also supported association with SNPs in WNT16 and ESR1/C6orf97 (p < 1 × 10(-5) ). Our results confirm that several of the genes contributing to BMD variation across a broad age range in both sexes have effects of similar magnitude on BMD of the spine in premenopausal women. These data support the hypothesis that variants in these genes of known skeletal function also affect BMD during the premenopausal period.
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    Whole Genome Sequence Association Analysis of Fasting Glucose and Fasting Insulin Levels in Diverse Cohorts from the NHLBI TOPMed Program
    (Springer Nature, 2022-07-28) DiCorpo, Daniel; Gaynor, Sheila M.; Russell, Emily M.; Westerman, Kenneth E.; Raffield, Laura M.; Majarian, Timothy D.; Wu, Peitao; Sarnowski, Chloé; Highland, Heather M.; Jackson, Anne; Hasbani, Natalie R.; de Vries, Paul S.; Brody, Jennifer A.; Hidalgo, Bertha; Guo, Xiuqing; Perry, James A.; O’Connell, Jeffrey R.; Lent, Samantha; Montasser, May E.; Cade, Brian E.; Jain, Deepti; Wang, Heming; D’Oliveira Albanus, Ricardo; Varshney, Arushi; Yanek, Lisa R.; Lange, Leslie; Palmer, Nicholette D.; Almeida, Marcio; Peralta, Juan M.; Aslibekyan, Stella; Baldridge, Abigail S.; Bertoni, Alain G.; Bielak, Lawrence F.; Chen, Chung-Shiuan; Chen, Yii-Der Ida; Choi, Won Jung; Goodarzi, Mark O.; Floyd, James S.; Irvin, Marguerite R.; Kalyani, Rita R.; Kelly, Tanika N.; Lee, Seonwook; Liu, Ching-Ti; Loesch, Douglas; Manson, JoAnn E.; Minster, Ryan L.; Naseri, Take; Pankow, James S.; Rasmussen-Torvik, Laura J.; Reiner, Alexander P.; Reupena, Muagututi’a Sefuiva; Selvin, Elizabeth; Smith, Jennifer A.; Weeks, Daniel E.; Xu, Huichun; Yao, Jie; Zhao, Wei; Parker, Stephen; Alonso, Alvaro; Arnett, Donna K.; Blangero, John; Boerwinkle, Eric; Correa, Adolfo; Cupples, L. Adrienne; Curran, Joanne E.; Duggirala, Ravindranath; He, Jiang; Heckbert, Susan R.; Kardia, Sharon L.R.; Kim, Ryan W.; Kooperberg, Charles; Liu, Simin; Mathias, Rasika A.; McGarvey, Stephen T.; Mitchell, Braxton D.; Morrison, Alanna C.; Peyser, Patricia A.; Psaty, Bruce M.; Redline, Susan; Shuldiner, Alan R.; Taylor, Kent D.; Vasan, Ramachandran S.; Viaud-Martinez, Karine A.; Florez, Jose C.; Wilson, James G.; Sladek, Robert; Rich, Stephen S.; Rotter, Jerome I.; Lin, Xihong; Dupuis, Josée; Meigs, James B.; Wessel, Jennifer; Manning, Alisa K.; Epidemiology, School of Public Health
    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.
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    Whole Genome Sequencing Analysis of Body Mass Index Identifies Novel African Ancestry-Specific Risk Allele
    (medRxiv, 2023-08-22) Zhang, Xinruo; Brody, Jennifer A.; Graff, Mariaelisa; Highland, Heather M.; Chami, Nathalie; Xu, Hanfei; Wang, Zhe; Ferrier, Kendra; Chittoor, Geetha; Josyula, Navya S.; Li, Xihao; Li, Zilin; Allison, Matthew A.; Becker, Diane M.; Bielak, Lawrence F.; Bis, Joshua C.; Boorgula, Meher Preethi; Bowden, Donald W.; Broome, Jai G.; Buth, Erin J.; Carlson, Christopher S.; Chang, Kyong-Mi; Chavan, Sameer; Chiu, Yen-Feng; Chuang, Lee-Ming; Conomos, Matthew P.; DeMeo, Dawn L.; Du, Margaret; Duggirala, Ravindranath; Eng, Celeste; Fohner, Alison E.; Freedman, Barry I.; Garrett, Melanie E.; Guo, Xiuqing; Haiman, Chris; Heavner, Benjamin D.; Hidalgo, Bertha; Hixson, James E.; Ho, Yuk-Lam; Hobbs, Brian D.; Hu, Donglei; Hui, Qin; Hwu, Chii-Min; Jackson, Rebecca D.; Jain, Deepti; Kalyani, Rita R.; Kardia, Sharon L. R.; Kelly, Tanika N.; Lange, Ethan M.; LeNoir, Michael; Li, Changwei; Marchand, Loic Le; McDonald, Merry-Lynn N.; McHugh, Caitlin P.; Morrison, Alanna C.; Naseri, Take; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; O'Connell, Jeffrey; O'Donnell, Christopher J.; Palmer, Nicholette D.; Pankow, James S.; Perry, James A.; Peters, Ulrike; Preuss, Michael H.; Rao, D. C.; Regan, Elizabeth A.; Reupena, Sefuiva M.; Roden, Dan M.; Rodriguez-Santana, Jose; Sitlani, Colleen M.; Smith, Jennifer A.; Tiwari, Hemant K.; Vasan, Ramachandran S.; Wang, Zeyuan; Weeks, Daniel E.; Wessel, Jennifer; Wiggins, Kerri L.; Wilkens, Lynne R.; Wilson, Peter W. F.; Yanek, Lisa R.; Yoneda, Zachary T.; Zhao, Wei; Zöllner, Sebastian; Arnett, Donna K.; Ashley-Koch, Allison E.; Barnes, Kathleen C.; Blangero, John; Boerwinkle, Eric; Burchard, Esteban G.; Carson, April P.; Chasman, Daniel I.; Chen, Yii-Der Ida; Curran, Joanne E.; Fornage, Myriam; Gordeuk, Victor R.; He, Jiang; Heckbert, Susan R.; Hou, Lifang; Irvin, Marguerite R.; Kooperberg, Charles; Minster, Ryan L.; Mitchell, Braxton D.; Nouraie, Mehdi; Psaty, Bruce M.; Raffield, Laura M.; Reiner, Alexander P.; Rich, Stephen S.; Rotter, Jerome I.; Shoemaker, M. Benjamin; Smith, Nicholas L.; Taylor, Kent D.; Telen, Marilyn J.; Weiss, Scott T.; Zhang, Yingze; Heard-Costa, Nancy; Sun, Yan V.; Lin, Xihong; Cupples, L. Adrienne; Lange, Leslie A.; Liu, Ching-Ti; Loos, Ruth J. F.; North, Kari E.; Justice, Anne E.; Biostatistics and Health Data Science, School of Medicine
    Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10−9). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.