Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, Canada.
Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada.
Genet Epidemiol. 2024 Oct;48(7):324-343. doi: 10.1002/gepi.22579. Epub 2024 Jun 28.
Family-based sequencing studies are increasingly used to find rare genetic variants of high risk for disease traits with familial clustering. In some studies, families with multiple disease subtypes are collected and the exomes of affected relatives are sequenced for shared rare variants (RVs). Since different families can harbor different causal variants and each family harbors many RVs, tests to detect causal variants can have low power in this study design. Our goal is rather to prioritize shared variants for further investigation by, for example, pathway analyses or functional studies. The transmission-disequilibrium test prioritizes variants based on departures from Mendelian transmission in parent-child trios. Extending this idea to families, we propose methods to prioritize RVs shared in affected relatives with two disease subtypes, with one subtype more heritable than the other. Global approaches condition on a variant being observed in the study and assume a known probability of carrying a causal variant. In contrast, local approaches condition on a variant being observed in specific families to eliminate the carrier probability. Our simulation results indicate that global approaches are robust to misspecification of the carrier probability and prioritize more effectively than local approaches even when the carrier probability is misspecified.
基于家系的测序研究越来越多地用于发现具有家族聚集性疾病特征的高风险罕见遗传变异。在一些研究中,收集了具有多种疾病亚型的家系,并对受影响亲属的外显子组进行测序以寻找共同的罕见变异(RVs)。由于不同的家系可能携带不同的因果变异,并且每个家系都携带许多 RVs,因此在这种研究设计中,检测因果变异的测试可能效果不佳。我们的目标是通过例如途径分析或功能研究,优先考虑共享变体进行进一步研究。传递不平衡测试根据亲子三胞胎中孟德尔传递的偏差对变体进行优先级排序。将这个想法扩展到家庭中,我们提出了在具有两种疾病亚型的受影响亲属中共享 RV 的方法,其中一种亚型比另一种更具遗传性。全局方法在研究中观察到一个变体的条件下进行,并假设携带因果变体的概率已知。相比之下,局部方法在特定的家庭中观察到一个变体的条件下进行,以消除携带概率。我们的模拟结果表明,全局方法对携带概率的指定不准确具有鲁棒性,并且即使在携带概率指定不准确的情况下,也比局部方法更有效地进行优先级排序。