TY - JOUR
T1 - Determining population stratification and subgroup effects in association studies of rare genetic variants for nicotine dependence
AU - Hsieh, Ai Ru
AU - Chen, Li Shiun
AU - Li, Ying Ju
AU - Fann, Cathy S.J.
N1 - Publisher Copyright:
© 2019 Lippincott Williams and Wilkins. All rights reserved.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - Background Rare variants (minor allele frequency < 1% or 5 %) can help researchers to deal with the confounding issue of 'missing heritability' and have a proven role in dissecting the etiology for human diseases and complex traits. Methods We extended the combined multivariate and collapsing (CMC) and weighted sum statistic (WSS) methods and accounted for the effects of population stratification and subgroup effects using stratified analyses by the principal component analysis, named here as 'str-CMC' and 'str-WSS'. To evaluate the validity of the extended methods, we analyzed the Genetic Architecture of Smoking and Smoking Cessation database, which includes African Americans and European Americans genotyped on Illumina Human Omni2.5, and we compared the results with those obtained with the sequence kernel association test (SKAT) and its modification, SKAT-O that included population stratification and subgroup effect as covariates. We utilized the Cochran-Mantel-Haenszel test to check for possible differences in single nucleotide polymorphism allele frequency between subgroups within a gene. We aimed to detect rare variants and considered population stratification and subgroup effects in the genomic region containing 39 acetylcholine receptor-related genes. Results The Cochran-Mantel-Haenszel test as applied to GABRG2 (P = 0.001) was significant. However, GABRG2 was detected both by str-CMC (P= 8.04E-06) and str-WSS (P= 0.046) in African Americans but not by SKAT or SKAT-O. Conclusions Our results imply that if associated rare variants are only specific to a subgroup, a stratified analysis might be a better approach than a combined analysis.
AB - Background Rare variants (minor allele frequency < 1% or 5 %) can help researchers to deal with the confounding issue of 'missing heritability' and have a proven role in dissecting the etiology for human diseases and complex traits. Methods We extended the combined multivariate and collapsing (CMC) and weighted sum statistic (WSS) methods and accounted for the effects of population stratification and subgroup effects using stratified analyses by the principal component analysis, named here as 'str-CMC' and 'str-WSS'. To evaluate the validity of the extended methods, we analyzed the Genetic Architecture of Smoking and Smoking Cessation database, which includes African Americans and European Americans genotyped on Illumina Human Omni2.5, and we compared the results with those obtained with the sequence kernel association test (SKAT) and its modification, SKAT-O that included population stratification and subgroup effect as covariates. We utilized the Cochran-Mantel-Haenszel test to check for possible differences in single nucleotide polymorphism allele frequency between subgroups within a gene. We aimed to detect rare variants and considered population stratification and subgroup effects in the genomic region containing 39 acetylcholine receptor-related genes. Results The Cochran-Mantel-Haenszel test as applied to GABRG2 (P = 0.001) was significant. However, GABRG2 was detected both by str-CMC (P= 8.04E-06) and str-WSS (P= 0.046) in African Americans but not by SKAT or SKAT-O. Conclusions Our results imply that if associated rare variants are only specific to a subgroup, a stratified analysis might be a better approach than a combined analysis.
KW - acetylcholine receptor-related genes
KW - nicotine dependence
KW - population stratification
KW - principal component analysis
KW - rare variant
KW - subgroup effects
UR - http://www.scopus.com/inward/record.url?scp=85069236386&partnerID=8YFLogxK
U2 - 10.1097/YPG.0000000000000227
DO - 10.1097/YPG.0000000000000227
M3 - Article
C2 - 31033776
AN - SCOPUS:85069236386
SN - 0955-8829
VL - 29
SP - 111
EP - 119
JO - Psychiatric genetics
JF - Psychiatric genetics
IS - 4
ER -