Influence of population stratification on population-based marker-disease association analysis.
Population-based genetic association analysis may suffer from the failure to control for confounders such as population stratification (PS). There has been extensive study on the influence of PS on candidate gene-disease association analysis, but much less attention has been paid to its influence on marker-disease association analysis. In this paper, we focus on the Pearson chi(2) test and the trend test for marker-disease association analysis. The mean and variance of the test statistics are derived under presence of PS, so that the power and inflated type I error rate can be evaluated. It is shown that the bias and the variance distortion are not zero in the presence of both PS and penetrance heterogeneity (PH). Unlike candidate gene-disease association analysis, when PS is present, the bias is not zero no matter whether PH is present or not. This work generalises the published results, where only the fully recessive penetrance model is considered and only the bias is calculated. It is shown that candidate gene-disease association analysis can be treated as a special case of marker-disease association analysis. Consequently, our results extend previous studies on candidate gene-disease association analysis. A simulation study confirms the theoretical findings.
Department of Mathematics, Fudan University, 220 Handan Road, Shanghai 200433, PR China.
Tengfei
T
Li
Zhaohai
Z
Li
Zhiliang
Z
Ying
Hong
H
Zhang
D015982:Bias; D015986:Confounding Factors, Epidemiologic; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D005828:Genetics, Population / Q000379:methods*; D055106:Genome-Wide Association Study; D006801:Humans; D015233:Models, Statistical; D019683:Penetrance; D013223:Statistics as Topic
D005819:Genetic Markers