Genetic Diversity and Association Studies in US Hispanic/Latino Populations

Applications in the Hispanic Community Health Study/Study of Latinos

Matthew P. Conomos, Cecelia A. Laurie, Adrienne M. Stilp, Stephanie M. Gogarten, Caitlin P. McHugh, Sarah C. Nelson, Tamar Sofer, Lindsay Fernandez-Rhodes, Anne E. Justice, Mariaelisa Graff, Kristin L. Young, Amanda A. Seyerle, Christy L. Avery, Kent D. Taylor, Jerome I. Rotter, Gregory A. Talavera, Martha L. Daviglus, Sylvia Wassertheil-Smoller, Neil Schneiderman, Gerardo Heiss & 17 others Robert C. Kaplan, Nora Franceschini, Alex P. Reiner, John R. Shaffer, R. Graham Barr, Kathleen F. Kerr, Sharon R. Browning, Brian L. Browning, Bruce S. Weir, M. Larissa Avilés-Santa, George J. Papanicolaou, Thomas Lumley, Adam A. Szpiro, Kari E. North, Ken Rice, Timothy A. Thornton, Cathy C. Laurie

Research output: Contribution to journalArticle

88 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)165-184
Number of pages20
JournalAmerican Journal of Human Genetics
Volume98
Issue number1
DOIs
StatePublished - Jan 7 2016

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Genetic Association Studies
Hispanic Americans
Linear Models
Genome-Wide Association Study
Health
Population
Environmental Exposure
Economic Inflation
Ethnic Groups
Cluster Analysis

All Science Journal Classification (ASJC) codes

  • Genetics
  • Genetics(clinical)

Cite this

Conomos, Matthew P. ; Laurie, Cecelia A. ; Stilp, Adrienne M. ; Gogarten, Stephanie M. ; McHugh, Caitlin P. ; Nelson, Sarah C. ; Sofer, Tamar ; Fernandez-Rhodes, Lindsay ; Justice, Anne E. ; Graff, Mariaelisa ; Young, Kristin L. ; Seyerle, Amanda A. ; Avery, Christy L. ; Taylor, Kent D. ; Rotter, Jerome I. ; Talavera, Gregory A. ; Daviglus, Martha L. ; Wassertheil-Smoller, Sylvia ; Schneiderman, Neil ; Heiss, Gerardo ; Kaplan, Robert C. ; Franceschini, Nora ; Reiner, Alex P. ; Shaffer, John R. ; Barr, R. Graham ; Kerr, Kathleen F. ; Browning, Sharon R. ; Browning, Brian L. ; Weir, Bruce S. ; Avilés-Santa, M. Larissa ; Papanicolaou, George J. ; Lumley, Thomas ; Szpiro, Adam A. ; North, Kari E. ; Rice, Ken ; Thornton, Timothy A. ; Laurie, Cathy C. / Genetic Diversity and Association Studies in US Hispanic/Latino Populations : Applications in the Hispanic Community Health Study/Study of Latinos. In: American Journal of Human Genetics. 2016 ; Vol. 98, No. 1. pp. 165-184.
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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.",
author = "Conomos, {Matthew P.} and Laurie, {Cecelia A.} and Stilp, {Adrienne M.} and Gogarten, {Stephanie M.} and McHugh, {Caitlin P.} and Nelson, {Sarah C.} and Tamar Sofer and Lindsay Fernandez-Rhodes and Justice, {Anne E.} and Mariaelisa Graff and Young, {Kristin L.} and Seyerle, {Amanda A.} and Avery, {Christy L.} and Taylor, {Kent D.} and Rotter, {Jerome I.} and Talavera, {Gregory A.} and Daviglus, {Martha L.} and Sylvia Wassertheil-Smoller and Neil Schneiderman and Gerardo Heiss and Kaplan, {Robert C.} and Nora Franceschini and Reiner, {Alex P.} and Shaffer, {John R.} and Barr, {R. Graham} and Kerr, {Kathleen F.} and Browning, {Sharon R.} and Browning, {Brian L.} and Weir, {Bruce S.} and Avil{\'e}s-Santa, {M. Larissa} and Papanicolaou, {George J.} and Thomas Lumley and Szpiro, {Adam A.} and North, {Kari E.} and Ken Rice and Thornton, {Timothy A.} and Laurie, {Cathy C.}",
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Conomos, MP, Laurie, CA, Stilp, AM, Gogarten, SM, McHugh, CP, Nelson, SC, Sofer, T, Fernandez-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, Barr, RG, Kerr, KF, Browning, SR, Browning, BL, Weir, BS, Avilés-Santa, ML, Papanicolaou, GJ, Lumley, T, Szpiro, AA, North, KE, Rice, K, Thornton, TA & Laurie, CC 2016, 'Genetic Diversity and Association Studies in US Hispanic/Latino Populations: Applications in the Hispanic Community Health Study/Study of Latinos', American Journal of Human Genetics, vol. 98, no. 1, pp. 165-184. https://doi.org/10.1016/j.ajhg.2015.12.001

Genetic Diversity and Association Studies in US Hispanic/Latino Populations : Applications in the Hispanic Community Health Study/Study of Latinos. / Conomos, Matthew P.; Laurie, Cecelia A.; Stilp, Adrienne M.; Gogarten, Stephanie M.; McHugh, Caitlin P.; Nelson, Sarah C.; Sofer, Tamar; Fernandez-Rhodes, Lindsay; Justice, Anne E.; Graff, Mariaelisa; Young, Kristin L.; Seyerle, Amanda A.; Avery, Christy L.; Taylor, Kent D.; Rotter, Jerome I.; Talavera, Gregory A.; Daviglus, Martha L.; Wassertheil-Smoller, Sylvia; Schneiderman, Neil; Heiss, Gerardo; Kaplan, Robert C.; Franceschini, Nora; Reiner, Alex P.; Shaffer, John R.; Barr, R. Graham; Kerr, Kathleen F.; Browning, Sharon R.; Browning, Brian L.; Weir, Bruce S.; Avilés-Santa, M. Larissa; Papanicolaou, George J.; Lumley, Thomas; Szpiro, Adam A.; North, Kari E.; Rice, Ken; Thornton, Timothy A.; Laurie, Cathy C.

In: American Journal of Human Genetics, Vol. 98, No. 1, 07.01.2016, p. 165-184.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Genetic Diversity and Association Studies in US Hispanic/Latino Populations

T2 - Applications in the Hispanic Community Health Study/Study of Latinos

AU - Conomos, Matthew P.

AU - Laurie, Cecelia A.

AU - Stilp, Adrienne M.

AU - Gogarten, Stephanie M.

AU - McHugh, Caitlin P.

AU - Nelson, Sarah C.

AU - Sofer, Tamar

AU - Fernandez-Rhodes, Lindsay

AU - Justice, Anne E.

AU - Graff, Mariaelisa

AU - Young, Kristin L.

AU - Seyerle, Amanda A.

AU - Avery, Christy L.

AU - Taylor, Kent D.

AU - Rotter, Jerome I.

AU - Talavera, Gregory A.

AU - Daviglus, Martha L.

AU - Wassertheil-Smoller, Sylvia

AU - Schneiderman, Neil

AU - Heiss, Gerardo

AU - Kaplan, Robert C.

AU - Franceschini, Nora

AU - Reiner, Alex P.

AU - Shaffer, John R.

AU - Barr, R. Graham

AU - Kerr, Kathleen F.

AU - Browning, Sharon R.

AU - Browning, Brian L.

AU - Weir, Bruce S.

AU - Avilés-Santa, M. Larissa

AU - Papanicolaou, George J.

AU - Lumley, Thomas

AU - Szpiro, Adam A.

AU - North, Kari E.

AU - Rice, Ken

AU - Thornton, Timothy A.

AU - Laurie, Cathy C.

PY - 2016/1/7

Y1 - 2016/1/7

N2 - 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.

AB - 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.

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