Is it reasonable to account for population structure in genome-wide association studies?

Population structure is widely perceived as a noise factor that undermines the quality of association between an SNP variable and a phenotypic variable in genome-wide association studies (GWAS). The linear model for GWAS generally accounts for population-structure variables to obtain the adjusted phenotype which has less noise. Its result is known to amplify the contrast between significant SNPs and insignificant SNPs in a resultant Manhattan plot. In fact, however, conventional GWAS practice often implements the linear model in an unusual way in that the population-structure variables are incorporated into the linear model in the form of continuous variables rather than factor variables. If the coefficients for population-structure variables change across all SNPs, then each SNP variable will be regressed against a differently adjusted phenotypic variable, making the GWAS process unreliable. Focusing on this concern, this study investigated whether accounting for population-structure variables in the linear model for GWAS can assure the adjusted phenotypes to be consistent across all SNPs. The result showed that the adjusted phenotypes resulting across all SNPs were not consistent, which is alarming considering conventional GWAS practice that accounts for population structure.