ASSESSING THE IMPACT OF GLOBAL VERSUS LOCAL ANCESTRY IN ASSOCIATION STUDIES

Case Western Reserve University, Cleveland OH

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Abstract

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. To account for population stratification, principal components analysis is often performed using single nucleotide polymorphisms (SNPs) across the genome. We used Framingham GAW16 data to compare the performance of local ancestry, measured by principal components (PCs) estimated from SNPs in a local chromosomal region, with global ancestry, measured by PCs estimated from genome-wide SNPs, to address underlying population stratification. Standardized height residuals from unrelated adults from the Framingham Offspring Cohort were averaged from longitudinal data. PCs of SNP genotype data were calculated to represent individual's ancestry either 1) globally using all SNPs across the genome or 2) locally using SNPs in adjacent 20 Mbp regions within each chromosome. We assessed the extent to which there are differences in association studies of height depending on whether PCs for global, local or both are included as covariates.The correlations between local and global PCs were low (r <0.12), suggesting variability between local and global ancestry estimates. Q-Q plots of the p values from genome-wide association tests indicate inflated type I error rate without adjusting for ancestry, but can be reasonably controlled by adjusting for local ancestry, global ancestry, or both. Spurious associations are observable in this European-American population and the effect of population stratification in association analysis can be controlled by adjustment with local or global ancestry PCs. Population stratification is a potential source of bias in this seemingly homogenous Framingham population. However, local and global PCs derived from SNPs appear to provide adequate information about ancestry.