Dalla Lana School of Public Health, University of Toronto, Room 500, 155 College St, Toronto, ON, M5T3M7, Canada.
Program in Genetics and Genome Biology, The Hospital for Sick Children, Room 12.9801, 686 Bay Street, Toronto, ON, M5G0A4, Canada.
Genome Med. 2020 Dec 28;12(1):115. doi: 10.1186/s13073-020-00818-2.
The identification of genetic variation that directly impacts infection susceptibility to SARS-CoV-2 and disease severity of COVID-19 is an important step towards risk stratification, personalized treatment plans, therapeutic, and vaccine development and deployment. Given the importance of study design in infectious disease genetic epidemiology, we use simulation and draw on current estimates of exposure, infectivity, and test accuracy of COVID-19 to demonstrate the feasibility of detecting host genetic factors associated with susceptibility and severity in published COVID-19 study designs. We demonstrate that limited phenotypic data and exposure/infection information in the early stages of the pandemic significantly impact the ability to detect most genetic variants with moderate effect sizes, especially when studying susceptibility to SARS-CoV-2 infection. Our insights can aid in the interpretation of genetic findings emerging in the literature and guide the design of future host genetic studies.
鉴定直接影响 SARS-CoV-2 感染易感性和 COVID-19 疾病严重程度的遗传变异是风险分层、个性化治疗计划、治疗和疫苗开发和部署的重要步骤。鉴于传染病遗传流行病学研究设计的重要性，我们使用模拟并借鉴 COVID-19 的当前暴露、传染性和检测准确性估计，来证明在已发表的 COVID-19 研究设计中检测与易感性和严重程度相关的宿主遗传因素的可行性。我们表明，在大流行的早期阶段，有限的表型数据和暴露/感染信息会显著影响检测大多数中等效应大小的遗传变异的能力，尤其是在研究对 SARS-CoV-2 感染的易感性时。我们的见解可以帮助解释文献中出现的遗传发现，并指导未来宿主遗传研究的设计。
