04476nas a2200937 4500008004100000022001400041245014100055210006900196260001300265300001300278490000600291520177500297653002202072653001502094653002102109653002302130653002102153653003002174653001102204653001902215653002202234653002502256653001802281653003402299653001302333653001102346653002702357653000902384653001502393653001402408653003602422653003302458653004702491653001302538100002102551700001802572700002202590700001802612700001702630700002002647700002002667700002002687700002402707700001802731700001702749700002102766700002502787700001602812700002502828700002302853700001902876700002102895700001602916700002802932700002402960700002802984700002003012700002203032700001503054700002003069700002303089700002103112700002203133700001903155700002203174700002403196700002203220700002803242700002303270700001903293700002003312700002403332700002403356700001703380700002703397700001703424700002003441700002103461700002003482856003603502 2011 eng d a1553-740400aEnhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.0 aEnhanced statistical tests for GWAS in admixed populations asses c2011 Apr ae10013710 v73 a
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.
10aAfrican Americans10aAlgorithms10aBreast Neoplasms10aChromosome Mapping10aCoronary Disease10aDiabetes Mellitus, Type 210aFemale10aGene Frequency10aGenetic Variation10aGenetics, Population10aGenome, Human10aGenome-Wide Association Study10aGenotype10aHumans10aLinkage Disequilibrium10aMale10aOdds Ratio10aPhenotype10aPolymorphism, Single Nucleotide10aPrincipal Component Analysis10aReceptor, Fibroblast Growth Factor, Type 210aSoftware1 aPasaniuc, Bogdan1 aZaitlen, Noah1 aLettre, Guillaume1 aChen, Gary, K1 aTandon, Arti1 aKao, Linda, W H1 aRuczinski, Ingo1 aFornage, Myriam1 aSiscovick, David, S1 aZhu, Xiaofeng1 aLarkin, Emma1 aLange, Leslie, A1 aCupples, Adrienne, L1 aYang, Qiong1 aAkylbekova, Ermeg, L1 aMusani, Solomon, K1 aDivers, Jasmin1 aMychaleckyj, Joe1 aLi, Mingyao1 aPapanicolaou, George, J1 aMillikan, Robert, C1 aAmbrosone, Christine, B1 aJohn, Esther, M1 aBernstein, Leslie1 aZheng, Wei1 aHu, Jennifer, J1 aZiegler, Regina, G1 aNyante, Sarah, J1 aBandera, Elisa, V1 aIngles, Sue, A1 aPress, Michael, F1 aChanock, Stephen, J1 aDeming, Sandra, L1 aRodriguez-Gil, Jorge, L1 aPalmer, Cameron, D1 aBuxbaum, Sarah1 aEkunwe, Lynette1 aHirschhorn, Joel, N1 aHenderson, Brian, E1 aMyers, Simon1 aHaiman, Christopher, A1 aReich, David1 aPatterson, Nick1 aWilson, James, G1 aPrice, Alkes, L uhttps://chs-nhlbi.org/node/1288