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Genetic Diversity and Association Studies in US Hispanic/Latino Populations: Applications in the Hispanic Community Health Study/Study of Latinos.

TitleGenetic Diversity and Association Studies in US Hispanic/Latino Populations: Applications in the Hispanic Community Health Study/Study of Latinos.
Publication TypePublication
Year2016
AuthorsConomos MP, Laurie CA, Stilp AM, Gogarten SM, McHugh CP, Nelson SC, Sofer T, Fernández-Rhodes L, Justice AE, Graff M, Young KL, Seyerle AA, Avery CL, Taylor KD, Rotter JI, Talavera GA, Daviglus ML, Wassertheil-Smoller S, Schneiderman N, Heiss G, Kaplan RC, Franceschini N, Reiner AP, Shaffer JR, R Barr G, Kerr KF, Browning SR, Browning BL, Weir BS, M Avilés-Santa L, Papanicolaou GJ, Lumley T, Szpiro AA, North KE, Rice K, Thornton TA, Laurie CC
JournalAm J Hum Genet
Volume98
Issue1
Pagination165-84
Date Published2016 Jan 07
ISSN1537-6605
KeywordsGenetic Variation, genome-wide association study, Hispanic Americans, Humans, United States
Abstract

US Hispanic/Latino individuals are diverse in genetic ancestry, culture, and environmental exposures. Here, we characterized and controlled for this diversity in genome-wide association studies (GWASs) for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We simultaneously estimated population-structure principal components (PCs) robust to familial relatedness and pairwise kinship coefficients (KCs) robust to population structure, admixture, and Hardy-Weinberg departures. The PCs revealed substantial genetic differentiation within and among six self-identified background groups (Cuban, Dominican, Puerto Rican, Mexican, and Central and South American). To control for variation among groups, we developed a multi-dimensional clustering method to define a "genetic-analysis group" variable that retains many properties of self-identified background while achieving substantially greater genetic homogeneity within groups and including participants with non-specific self-identification. In GWASs of 22 biomedical traits, we used a linear mixed model (LMM) including pairwise empirical KCs to account for familial relatedness, PCs for ancestry, and genetic-analysis groups for additional group-associated effects. Including the genetic-analysis group as a covariate accounted for significant trait variation in 8 of 22 traits, even after we fit 20 PCs. Additionally, genetic-analysis groups had significant heterogeneity of residual variance for 20 of 22 traits, and modeling this heteroscedasticity within the LMM reduced genomic inflation for 19 traits. Furthermore, fitting an LMM that utilized a genetic-analysis group rather than a self-identified background group achieved higher power to detect previously reported associations. We expect that the methods applied here will be useful in other studies with multiple ethnic groups, admixture, and relatedness.

DOI10.1016/j.ajhg.2015.12.001
Alternate JournalAm J Hum Genet
PubMed ID26748518
PubMed Central IDPMC4716704
Grant ListHHSN268201300005C / HL / NHLBI NIH HHS / United States
UL1TR000124 / TR / NCATS NIH HHS / United States
P01 GM099568 / GM / NIGMS NIH HHS / United States
KL2 TR001109 / TR / NCATS NIH HHS / United States
N01HC65236 / HL / NHLBI NIH HHS / United States
N01HC65235 / HL / NHLBI NIH HHS / United States
N01 HC65235 / HC / NHLBI NIH HHS / United States
N01-HC65237 / HC / NHLBI NIH HHS / United States
UL1 TR000124 / TR / NCATS NIH HHS / United States
N01HC65234 / HL / NHLBI NIH HHS / United States
P30 DK063491 / DK / NIDDK NIH HHS / United States
N01HC65233 / HL / NHLBI NIH HHS / United States
R01 DK101855 / DK / NIDDK NIH HHS / United States
N01HC65237 / HL / NHLBI NIH HHS / United States
N01-HC65233 / HC / NHLBI NIH HHS / United States
P30 DK020541 / DK / NIDDK NIH HHS / United States
N01-HC65234 / HC / NHLBI NIH HHS / United States
N01-HC65236 / HC / NHLBI NIH HHS / United States
1R01DK101855-01 / DK / NIDDK NIH HHS / United States
K01 CA148958 / CA / NCI NIH HHS / United States
DK063491 / DK / NIDDK NIH HHS / United States
T32 GM081062 / GM / NIGMS NIH HHS / United States
P2C HD050924 / HD / NICHD NIH HHS / United States
T32 HL007055 / HL / NHLBI NIH HHS / United States
MS#: 
0284
Manuscript Lead/Corresponding Author Affiliation: 
HCHS/SOL Genetic Analysis Center - University of Washington, Seattle
ECI: 
Manuscript Status: 
Published