Enhanced statistical tests for GWAS in admixed populations: Assessment using african americans from CARe and a breast cancer consortium

Bogdan Pasaniuc, Noah Zaitlen, Guillaume Lettre, Gary K. Chen, Arti Tandon, W. H Linda Kao, Ingo Ruczinski, Myriam Fornage, David S. Siscovick, Xiaofeng Zhu, Emma Larkin, Leslie A. Lange, L. Adrienne Cupples, Qiong Yang, Ermeg L. Akylbekova, Solomon K. Musani, Jasmin Divers, Joe Mychaleckyj, Mingyao Li, George J. PapanicolaouRobert C. Millikan, Christine B. Ambrosone, Esther M. John, Leslie Bernstein, Wei Zheng, Jennifer Hu, Regina G. Ziegler, Sarah J. Nyante, Elisa V. Bandera, Sue A. Ingles, Michael F. Press, Stephen J. Chanock, Sandra L. Deming, Jorge L. Rodriguez-Gil, Cameron D. Palmer, Sarah Buxbaum, Lynette Ekunwe, Joel N. Hirschhorn, Brian E. Henderson, Simon Myers, Christopher A. Haiman, David Reich, Nick Patterson, James G. Wilson, Alkes L. Price

Research output: Contribution to journalArticle

72 Citations (Scopus)

Abstract

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.

Original languageEnglish
Article numbere1001371
JournalPLoS Genetics
Volume7
Issue number4
DOIs
StatePublished - Apr 1 2011

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African American
Genome-Wide Association Study
African Americans
breast neoplasms
cancer
statistical analysis
genome
ancestry
Single Nucleotide Polymorphism
disequilibrium
Breast Neoplasms
Linkage Disequilibrium
linkage disequilibrium
Population
case-control studies
loci
study method
Case-Control Studies
statistics
methodology

ASJC Scopus subject areas

  • Genetics
  • Molecular Biology
  • Ecology, Evolution, Behavior and Systematics
  • Cancer Research
  • Genetics(clinical)

Cite this

Enhanced statistical tests for GWAS in admixed populations : Assessment using african americans from CARe and a breast cancer consortium. / Pasaniuc, Bogdan; Zaitlen, Noah; Lettre, Guillaume; Chen, Gary K.; Tandon, Arti; Kao, W. H Linda; Ruczinski, Ingo; Fornage, Myriam; Siscovick, David S.; Zhu, Xiaofeng; Larkin, Emma; Lange, Leslie A.; Cupples, L. Adrienne; Yang, Qiong; Akylbekova, Ermeg L.; Musani, Solomon K.; Divers, Jasmin; Mychaleckyj, Joe; Li, Mingyao; Papanicolaou, George J.; Millikan, Robert C.; Ambrosone, Christine B.; John, Esther M.; Bernstein, Leslie; Zheng, Wei; Hu, Jennifer; Ziegler, Regina G.; Nyante, Sarah J.; Bandera, Elisa V.; Ingles, Sue A.; Press, Michael F.; Chanock, Stephen J.; Deming, Sandra L.; Rodriguez-Gil, Jorge L.; Palmer, Cameron D.; Buxbaum, Sarah; Ekunwe, Lynette; Hirschhorn, Joel N.; Henderson, Brian E.; Myers, Simon; Haiman, Christopher A.; Reich, David; Patterson, Nick; Wilson, James G.; Price, Alkes L.

In: PLoS Genetics, Vol. 7, No. 4, e1001371, 01.04.2011.

Research output: Contribution to journalArticle

Pasaniuc, B, Zaitlen, N, Lettre, G, Chen, GK, Tandon, A, Kao, WHL, Ruczinski, I, Fornage, M, Siscovick, DS, Zhu, X, Larkin, E, Lange, LA, Cupples, LA, Yang, Q, Akylbekova, EL, Musani, SK, Divers, J, Mychaleckyj, J, Li, M, Papanicolaou, GJ, Millikan, RC, Ambrosone, CB, John, EM, Bernstein, L, Zheng, W, Hu, J, Ziegler, RG, Nyante, SJ, Bandera, EV, Ingles, SA, Press, MF, Chanock, SJ, Deming, SL, Rodriguez-Gil, JL, Palmer, CD, Buxbaum, S, Ekunwe, L, Hirschhorn, JN, Henderson, BE, Myers, S, Haiman, CA, Reich, D, Patterson, N, Wilson, JG & Price, AL 2011, 'Enhanced statistical tests for GWAS in admixed populations: Assessment using african americans from CARe and a breast cancer consortium', PLoS Genetics, vol. 7, no. 4, e1001371. https://doi.org/10.1371/journal.pgen.1001371
Pasaniuc, Bogdan ; Zaitlen, Noah ; Lettre, Guillaume ; Chen, Gary K. ; Tandon, Arti ; Kao, W. H Linda ; Ruczinski, Ingo ; Fornage, Myriam ; Siscovick, David S. ; Zhu, Xiaofeng ; Larkin, Emma ; Lange, Leslie A. ; Cupples, L. Adrienne ; Yang, Qiong ; Akylbekova, Ermeg L. ; Musani, Solomon K. ; Divers, Jasmin ; Mychaleckyj, Joe ; Li, Mingyao ; Papanicolaou, George J. ; Millikan, Robert C. ; Ambrosone, Christine B. ; John, Esther M. ; Bernstein, Leslie ; Zheng, Wei ; Hu, Jennifer ; Ziegler, Regina G. ; Nyante, Sarah J. ; Bandera, Elisa V. ; Ingles, Sue A. ; Press, Michael F. ; Chanock, Stephen J. ; Deming, Sandra L. ; Rodriguez-Gil, Jorge L. ; Palmer, Cameron D. ; Buxbaum, Sarah ; Ekunwe, Lynette ; Hirschhorn, Joel N. ; Henderson, Brian E. ; Myers, Simon ; Haiman, Christopher A. ; Reich, David ; Patterson, Nick ; Wilson, James G. ; Price, Alkes L. / Enhanced statistical tests for GWAS in admixed populations : Assessment using african americans from CARe and a breast cancer consortium. In: PLoS Genetics. 2011 ; Vol. 7, No. 4.
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abstract = "While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8{\%} increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11{\%} increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.",
author = "Bogdan Pasaniuc and Noah Zaitlen and Guillaume Lettre and Chen, {Gary K.} and Arti Tandon and Kao, {W. H Linda} and Ingo Ruczinski and Myriam Fornage and Siscovick, {David S.} and Xiaofeng Zhu and Emma Larkin and Lange, {Leslie A.} and Cupples, {L. Adrienne} and Qiong Yang and Akylbekova, {Ermeg L.} and Musani, {Solomon K.} and Jasmin Divers and Joe Mychaleckyj and Mingyao Li and Papanicolaou, {George J.} and Millikan, {Robert C.} and Ambrosone, {Christine B.} and John, {Esther M.} and Leslie Bernstein and Wei Zheng and Jennifer Hu and Ziegler, {Regina G.} and Nyante, {Sarah J.} and Bandera, {Elisa V.} and Ingles, {Sue A.} and Press, {Michael F.} and Chanock, {Stephen J.} and Deming, {Sandra L.} and Rodriguez-Gil, {Jorge L.} and Palmer, {Cameron D.} and Sarah Buxbaum and Lynette Ekunwe and Hirschhorn, {Joel N.} and Henderson, {Brian E.} and Simon Myers and Haiman, {Christopher A.} and David Reich and Nick Patterson and Wilson, {James G.} and Price, {Alkes L.}",
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T1 - Enhanced statistical tests for GWAS in admixed populations

T2 - Assessment using african americans from CARe and a breast cancer consortium

AU - Pasaniuc, Bogdan

AU - Zaitlen, Noah

AU - Lettre, Guillaume

AU - Chen, Gary K.

AU - Tandon, Arti

AU - Kao, W. H Linda

AU - Ruczinski, Ingo

AU - Fornage, Myriam

AU - Siscovick, David S.

AU - Zhu, Xiaofeng

AU - Larkin, Emma

AU - Lange, Leslie A.

AU - Cupples, L. Adrienne

AU - Yang, Qiong

AU - Akylbekova, Ermeg L.

AU - Musani, Solomon K.

AU - Divers, Jasmin

AU - Mychaleckyj, Joe

AU - Li, Mingyao

AU - Papanicolaou, George J.

AU - Millikan, Robert C.

AU - Ambrosone, Christine B.

AU - John, Esther M.

AU - Bernstein, Leslie

AU - Zheng, Wei

AU - Hu, Jennifer

AU - Ziegler, Regina G.

AU - Nyante, Sarah J.

AU - Bandera, Elisa V.

AU - Ingles, Sue A.

AU - Press, Michael F.

AU - Chanock, Stephen J.

AU - Deming, Sandra L.

AU - Rodriguez-Gil, Jorge L.

AU - Palmer, Cameron D.

AU - Buxbaum, Sarah

AU - Ekunwe, Lynette

AU - Hirschhorn, Joel N.

AU - Henderson, Brian E.

AU - Myers, Simon

AU - Haiman, Christopher A.

AU - Reich, David

AU - Patterson, Nick

AU - Wilson, James G.

AU - Price, Alkes L.

PY - 2011/4/1

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