Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Alexandroupolis, 68100, Greece.
Clinical Pharmacology & Pharmacogenetics Unit, Academic General Hospital of Alexandroupolis, Alexandroupolis, 68100, Greece.
Pharmacogenomics. 2020 Dec;21(18):1311-1329. doi: 10.2217/pgs-2020-0092. Epub 2020 Nov 27.
There is considerable variation in disease course among individuals infected with SARS-CoV-2. Many of them do not exhibit any symptoms, while some others proceed to develop COVID-19; however, severity of COVID-19 symptoms greatly differs among individuals. Focusing on the early events related to SARS-CoV-2 entry to cells through the ACE2 pathway, we describe how variability in (epi)genetic factors can conceivably explain variability in disease course. We specifically focus on variations in , and genes, as central components for SARS-CoV-2 infection, and on other molecules that modulate their expression such as , , and We propose a genetic classifier for predicting SARS-CoV-2 infectivity potential as a preliminary tool for identifying the at-risk-population. This tool can serve as a dynamic scaffold being updated and adapted to validated (epi)genetic data. Overall, the proposed approach holds potential for better personalization of COVID-19 handling.
在感染 SARS-CoV-2 的个体中，疾病进程存在相当大的差异。他们中的许多人没有表现出任何症状，而另一些人则进展为 COVID-19；然而，COVID-19 症状的严重程度在个体之间有很大的不同。我们专注于与 SARS-CoV-2 通过 ACE2 途径进入细胞相关的早期事件，描述了（表观）遗传因素的变异性如何可以合理地解释疾病进程的变异性。我们特别关注 、 和 基因的变异，因为它们是 SARS-CoV-2 感染的核心组成部分，以及调节它们表达的其他分子，如 、 和 我们提出了一种用于预测 SARS-CoV-2 感染潜力的遗传分类器，作为识别高危人群的初步工具。该工具可以作为一个动态支架，不断更新和适应经过验证的（表观）遗传数据。总的来说，该方法有可能更好地实现 COVID-19 处理的个性化。
