Wittke-Thompson Jacqueline K, Pluzhnikov Anna, Cox Nancy J
Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA.
Am J Hum Genet. 2005 Jun;76(6):967-86. doi: 10.1086/430507. Epub 2005 Apr 15.
Previous studies have explored the use of departure from Hardy-Weinberg equilibrium (DHW) for fine mapping Mendelian disorders and for general fine mapping. Other studies have used Hardy-Weinberg tests for genotyping quality control. To enable investigators to make rational decisions about whether DHW is due to genotyping error or to underlying biology, we developed an analytic framework and software to determine the parameter values for which DHW might be expected for common diseases. We show analytically that, for a general disease model, the difference between population and Hardy-Weinberg expected genotypic frequencies (delta) at the susceptibility locus is a function of the susceptibility-allele frequency (q), heterozygote relative risk (beta), and homozygote relative risk (gamma). For unaffected control samples, is a function of risk in nonsusceptible homozygotes (alpha), the population prevalence of disease (KP), q, beta, and gamma. We used these analytic functions to calculate and the number of cases or controls needed to detect DHW for a range of genetic models consistent with common diseases (1.1 < or = gamma < or = 10 and 0.005 < or = KP < or = 0.2). Results suggest that significant DHW can be expected in relatively small samples of patients over a range of genetic models. We also propose a goodness-of-fit test to aid investigators in determining whether a DHW observed in the context of a case-control study is consistent with a genetic disease model. We illustrate how the analytic framework and software can be used to help investigators interpret DHW in the context of association studies of common diseases.
以往研究探讨了利用偏离哈迪-温伯格平衡(DHW)进行孟德尔疾病精细定位以及一般精细定位。其他研究则将哈迪-温伯格检验用于基因分型质量控制。为使研究人员能够就是否因基因分型错误或潜在生物学因素导致DHW做出合理决策,我们开发了一个分析框架和软件,以确定常见疾病可能出现DHW的参数值。我们通过分析表明,对于一般疾病模型,易感位点处群体基因型频率与哈迪-温伯格预期基因型频率之差(δ)是易感等位基因频率(q)、杂合子相对风险(β)和纯合子相对风险(γ)的函数。对于未受影响的对照样本,是不易感纯合子风险(α)、疾病群体患病率(KP)、q、β和γ的函数。我们使用这些分析函数来计算以及检测一系列与常见疾病一致的遗传模型(1.1≤γ≤10且0.005≤KP≤0.2)中DHW所需的病例数或对照数。结果表明,在一系列遗传模型下,相对较小的患者样本中可能会出现显著的DHW。我们还提出了一种拟合优度检验,以帮助研究人员确定在病例对照研究背景下观察到的DHW是否与遗传疾病模型一致。我们举例说明了如何使用分析框架和软件来帮助研究人员在常见疾病关联研究背景下解释DHW。