Freedman Matthew L, Reich David, Penney Kathryn L, McDonald Gavin J, Mignault Andre A, Patterson Nick, Gabriel Stacey B, Topol Eric J, Smoller Jordan W, Pato Carlos N, Pato Michele T, Petryshen Tracey L, Kolonel Laurence N, Lander Eric S, Sklar Pamela, Henderson Brian, Hirschhorn Joel N, Altshuler David
Department of Medicine and Molecular Biology, Massachusetts General Hospital, Boston, and Program in Medical and Population Genetics, Broad Institute, Cambridge, USA.
Nat Genet. 2004 Apr;36(4):388-93. doi: 10.1038/ng1333. Epub 2004 Mar 28.
Population stratification refers to differences in allele frequencies between cases and controls due to systematic differences in ancestry rather than association of genes with disease. It has been proposed that false positive associations due to stratification can be controlled by genotyping a few dozen unlinked genetic markers. To assess stratification empirically, we analyzed data from 11 case-control and case-cohort association studies. We did not detect statistically significant evidence for stratification but did observe that assessments based on a few dozen markers lack power to rule out moderate levels of stratification that could cause false positive associations in studies designed to detect modest genetic risk factors. After increasing the number of markers and samples in a case-cohort study (the design most immune to stratification), we found that stratification was in fact present. Our results suggest that modest amounts of stratification can exist even in well designed studies.
群体分层是指病例组和对照组之间等位基因频率的差异，这是由于祖先的系统差异而非基因与疾病的关联所致。有人提出，通过对几十种不连锁的遗传标记进行基因分型，可以控制分层导致的假阳性关联。为了实证评估分层情况，我们分析了11项病例对照和病例队列关联研究的数据。我们没有检测到具有统计学意义的分层证据，但确实观察到，基于几十种标记的评估缺乏排除中等程度分层的能力，而这种分层可能会在旨在检测适度遗传风险因素的研究中导致假阳性关联。在增加病例队列研究（对分层最具抗性的设计）中的标记数量和样本量后，我们发现实际上存在分层现象。我们的结果表明，即使在设计良好的研究中也可能存在适度的分层。
