Trans-ethnic fine-mapping of genetic loci for body mass index in the diverse ancestral populations of the Population Architecture using Genomics and Epidemiology (PAGE) Study reveals evidence for multiple signals at established loci

Lindsay Fernández-Rhodes, Jian Gong, Jeffrey Haessler, Nora Franceschini, Mariaelisa Graff, Katherine K. Nishimura, Yujie Wang, Heather M. Highland, Sachiko Yoneyama, William S. Bush, Robert Goodloe, Marylyn D. Ritchie, Dana Crawford, Myron Gross, Myriam Fornage, Petra Buzkova, Ran Tao, Carmen Isasi, Larissa Avilés-Santa, Martha DaviglusRachel H. Mackey, Denise Houston, C. Charles Gu, Georg Ehret, Khanh Dung H. Nguyen, Cora E. Lewis, Mark Leppert, Marguerite R. Irvin, Unhee Lim, Christopher A. Haiman, Loic Le Marchand, Fredrick Schumacher, Lynne Wilkens, Yingchang Lu, Erwin P. Bottinger, Ruth J.L. Loos, Wayne H.H. Sheu, Xiuqing Guo, Wen Jane Lee, Yang Hai, Yi Jen Hung, Devin Absher, I. Chien Wu, Kent D. Taylor, I. Te Lee, Yeheng Liu, Tzung Dau Wang, Thomas Quertermous, Jyh Ming J. Juang, Jerome I. Rotter, Themistocles Assimes, Chao A. Hsiung, Yii Der Ida Chen, Ross Prentice, Lewis H. Kuller, Jo Ann E. Manson, Charles Kooperberg, Paul Smokowski, Whitney R. Robinson, Penny Gordon-Larsen, Rongling Li, Lucia Hindorff, Steven Buyske, Tara C. Matise, Ulrike Peters, Kari E. North

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Most body mass index (BMI) genetic loci have been identified in studies of primarily European ancestries. The effect of these loci in other racial/ethnic groups is less clear. Thus, we aimed to characterize the generalizability of 170 established BMI variants, or their proxies, to diverse US populations and trans-ethnically fine-map 36 BMI loci using a sample of >102,000 adults of African, Hispanic/Latino, Asian, European and American Indian/Alaskan Native descent from the Population Architecture using Genomics and Epidemiology Study. We performed linear regression of the natural log of BMI (18.5–70 kg/m2) on the additive single nucleotide polymorphisms (SNPs) at BMI loci on the MetaboChip (Illumina, Inc.), adjusting for age, sex, population stratification, study site, or relatedness. We then performed fixed-effect meta-analyses and a Bayesian trans-ethnic meta-analysis to empirically cluster by allele frequency differences. Finally, we approximated conditional and joint associations to test for the presence of secondary signals. We noted directional consistency with the previously reported risk alleles beyond what would have been expected by chance (binomial p < 0.05). Nearly, a quarter of the previously described BMI index SNPs and 29 of 36 densely-genotyped BMI loci on the MetaboChip replicated/generalized in trans-ethnic analyses. We observed multiple signals at nine loci, including the description of seven loci with novel multiple signals. This study supports the generalization of most common genetic loci to diverse ancestral populations and emphasizes the importance of dense multiethnic genomic data in refining the functional variation at genetic loci of interest and describing several loci with multiple underlying genetic variants.

Original languageEnglish (US)
Pages (from-to)771-800
Number of pages30
JournalHuman Genetics
Volume136
Issue number6
DOIs
StatePublished - Jun 1 2017

Bibliographical note

Funding Information:
LFR was supported by the Cardiovascular Disease Epidemiology Training Grant from the National Heart, Lung, and Blood Institute (T32HL007055) and the American Heart Association (AHA) predoctoral Grant (13PRE16100015). LFR also received support from the Population Research Infrastructure Program (P2C HD050924). KKN was supported by a National Cancer Institute training grant: Cancer Prevention Training in Nutrition, Exercise and Genetics (R25CA094880). RHM was supported by the Women’s Health Initiative Regional Field Center Program (HHSN268201100002C). KEN was supported by R01-DK089256; 2R01HD057194; U01HG007416; R01DK101855, and AHA Grant 13GRNT16490017. PG-L was supported by the National Institute of Child Health and Human Development (R01HD05719). The Population Architecture Using Genomics and Epidemiology (PAGE) program was funded by the National Human Genome Research Institute (NHGRI), supported by U01HG004803 (CALiCo), U01HG004798 (EAGLE), U01HG004802 (MEC), U01HG004790 (WHI), and U01HG004801 (Coordinating Center), and their respective NHGRI ARRA supplements. The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. The complete list of PAGE members can be found at PAGE website ( http://www.pagestudy.org ). The data and materials included in this report result from a collaboration between the following studies: The “Epidemiologic Architecture for Genes Linked to Environment (EAGLE)” was funded through the NHGRI PAGE program (U01HG004798 and its NHGRI ARRA supplement). The data set(s) used for the analyses described were obtained from Vanderbilt University Medical Center’s BioVU which was supported by institutional funding and by the Vanderbilt CTSA Grant UL1 TR000445 from NCATS/NIH. The Vanderbilt University Center for Human Genetics Research, Computational Genomics Core provided computational and/or analytical support for this work. The Multiethnic Cohort study (MEC) characterization of epidemiological architecture was funded through NHGRI (HG004802 and HG007397) and the NHGRI PAGE program (U01HG004802 and its NHGRI ARRA supplement). The MEC study was funded through the National Cancer Institute (CA164973, R37CA54281, R01 CA 063464, P01CA33619, U01CA136792, and U01CA98758). Funding support for the “Epidemiology of putative genetic variants: The Women’s Health Initiative” study was provided through the NHGRI PAGE program (U01HG004790 and its NHGRI ARRA supplement). The WHI program was funded by the National Heart, Lung, and Blood Institute; NIH; and U.S. Department of Health and Human Services through contracts N01WH22110, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, and 44221. The authors thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A full listing of WHI investigators can be found at: http://www.whiscience.org/publications/ WHI_investigators_shortlist.pdf. Funding support for the Genetic Epidemiology of Causal Variants Across the Life Course (CALiCo) program was provided through the NHGRI PAGE program (U01HG004803 and its NHGRI ARRA supplement). The following studies contributed to this manuscript and were funded by the following agencies: The Atherosclerosis Risk in Communities Study (ARIC) was carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL087641, R01HL59367, and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. The Coronary Artery Risk Development in Young Adults (CARDIA) study was supported by the following National Institutes of Health, National Heart, Lung and Blood Institute contracts: N01-HC-95095; N01-HC-48047; N01-HC-48048; N01-HC-48049; N01-HC-48050; N01-HC-45134; N01-HC-05187; and N01-HC-45205. The Cardiovascular Health Study (CHS) was supported by contracts HHSN268201200036C, N01-HC-85239, and N01-HC-85079 through N01-HC-85086, N01-HC-35129, N01 HC-15103, N01 HC-55222, N01-HC-75150, and N01-HC-45133, and Grant HL080295 from the National Heart, Lung, and Blood Institute (NHLBI), with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG-023629, AG-15928, AG-20098, and AG-027058 from the National Institute on Aging (NIA). The Hispanic Community Health Study/Study of Latinos (SOL) was carried out as a collaborative study supported by contracts from the National Heart, Lung, and Blood Institute (NHLBI) to the University of North Carolina (N01-HC65233), University of Miami (N01-HC65234), Albert Einstein College of Medicine (N01-HC65235), Northwestern University (N01-HC65236), and San Diego State University (N01-HC65237). Additional support was provided by 1R01DK101855-01 and 13GRNT16490017. The following Institutes/Centers/Offices contributed to the HCHS/SOL through a transfer of funds to the NHLBI: National Center on Minority Health and Health Disparities, the National Institute of Deafness and Other Communications Disorders, the National Institute of Dental and Craniofacial Research, the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Neurological Disorders and Stroke, and the Office of Dietary Supplements. GenNet was one of four networks in the Family Blood Pressure Program, established in 1995 and supported by a series of agreements with the NIH National Heart, Lung and Blood Institute. The Mount Sinai BioMe Biobank was supported by The Andrea and Charles Bronfman Philanthropies. The studies of the TaiChi Consortium were supported by the National Health Research Institutes, Taiwan (PH-100-SP-01, BS-094-PP-01, and PH-100-PP-03), the National Science Council, Taiwan (Grant Nos NSC 98-2314-B-075A-002-MY3, NSC 96-2314-B-002-151, NSC 96-2314-B-002-152, NSC 98-2314-B-002-122-MY2, NSC 100-2314-B-002-115, NSC 101-2325-002-078, and 101-2314-B-075A-006-MY3), the National Taiwan University Hospital, Taiwan (NTUH 98-N1266, NTUH 100-N1775, NTUH 101-N2010, NTUH 101-N, VN101-04, and NTUH 101-S1784). The Hypertension Genetic Epidemiology Network (HyperGEN) study was supported by National Heart, Lung, and Blood Institute contracts HL086694 and HL055673. Assistance with phenotype harmonization, SNP selection and annotation, data cleaning, data management, integration and dissemination, and general study coordination was provided by the PAGE Coordinating Center (U01HG004801-01 and its NHGRI ARRA supplement). The National Institutes of Mental Health also contributed support for the Coordinating Center. The authors gratefully acknowledge Dr. Ben Voight for sharing the Metabochip SNP linkage disequilibrium and minor allele frequency statistics estimated in the Malmö Diet and Cancer Study. The PAGE Study thanks the staff and participants of all PAGE studies for their important contributions.

Publisher Copyright:
© 2017, Springer-Verlag Berlin Heidelberg.

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