Hidden population substructures in an apparently homogeneous population bias association studies - PubMed

Comparative Study

Hidden population substructures in an apparently homogeneous population bias association studies

Mario Berger et al. Eur J Hum Genet. 2006 Feb.

Abstract

Linkage- and association-based approaches have been applied to attempt to unravel the genetic predisposition for complex diseases. However, studies often report contradictory results even when similar population backgrounds are investigated. Unrecognized population substructures could possibly explain these inconsistencies. In an apparently homogeneous German sample of 612 patients with type 2 diabetic and end-stage diabetic nephropathy and 214 healthy controls, we tested for hidden population substructures and their possible effects on association. Using a genetic vector space analysis of genotypes of 20 microsatellite markers, we identified four distinct subsets of cases and controls. The significance of these substructures was demonstrated by subsequent association analyses, using three genetic markers (UCSNP-43,-19,-63; intron 3 of the calpain-10 gene). In the undivided sample, we found no association between individual SNPs or any haplogenotypes (ie the genotype combination of two multilocus haplotypes) and type 2 diabetes. In contrast, when analyzing the four groups separately, we found that there was evidence for association of the common C allele of UCSNP-63 with the trait in the largest group (n=547 cases/101 controls; P=0.002). In this subset haplotype 112 was more frequent in controls than in cases (P=0.006; haplogenotype 112/121: odds ratio (OR)=0.27, 95% confidence intervals (CI)=0.13-0.57), indicating a protective effect against the development of type 2 diabetes. Our study demonstrates that unconsidered population substructures (ethnicity-dependent factors) can severely bias association studies.

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