Epidemiology and Biostatistics, Department of Public Health, University of Southern Denmark, Odense, Denmark.
Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark.
Eur J Hum Genet. 2019 Apr;27(4):631-636. doi: 10.1038/s41431-018-0320-2. Epub 2019 Jan 18.
Genetic interaction is a crucial issue in the understanding of functional pathways underlying complex diseases. However, detecting such interaction effects is challenging in terms of both methodology and statistical power. We address this issue by introducing a disease-concordant twin-case-only design, which applies to both monozygotic and dizygotic twins. To investigate the power, we conducted a computer simulation study by setting a series of parameter schemes with different minor allele frequencies and relative risks. Results from the simulation study reveals that the disease-concordant twin-case-only design largely reduces sample size required for sufficient power compared to the ordinary case-only design for detecting gene-gene interaction using unrelated individuals. Sample sizes for dizygotic and monozygotic twins were roughly 1/2 and 1/4 of sample sizes in the ordinary case-only design. Since dizygotic twins are genetically similar as siblings, the enriched power for dizygotic twins also applies to affected siblings, which could help to largely extend the application of the powerful twin-case-only design. In summary, our simulation reveals high value of disease-concordant twins and siblings in efficiently detecting gene-by-gene interactions.
遗传相互作用是理解复杂疾病功能途径的关键问题。然而，从方法和统计功效的角度来看，检测这种相互作用效应具有挑战性。我们通过引入一种疾病一致的双胞胎病例对照设计来解决这个问题，这种设计适用于同卵双胞胎和异卵双胞胎。为了研究功效，我们通过设置一系列具有不同次要等位基因频率和相对风险的参数方案进行了计算机模拟研究。模拟研究的结果表明，与使用无关个体检测基因-基因相互作用的普通病例对照设计相比，疾病一致的双胞胎病例对照设计大大减少了检测所需的样本量。与普通病例对照设计相比，异卵双胞胎和同卵双胞胎的样本量分别约为 1/2 和 1/4。由于异卵双胞胎在遗传上与兄弟姐妹相似，因此异卵双胞胎的富集功效也适用于受影响的兄弟姐妹，这有助于大大扩展强大的双胞胎病例对照设计的应用。总之，我们的模拟揭示了疾病一致的双胞胎和兄弟姐妹在有效检测基因-基因相互作用方面的高价值。
