Department of Health Sciences, University of Genova, Genova, Italy.
Unit of Medical Genetics, Galliera Hospital, Genova, Italy.
Hum Genomics. 2020 Sep 11;14(1):30. doi: 10.1186/s40246-020-00280-6.
The COVID-19 pandemic has strengthened the interest in the biological mechanisms underlying the complex interplay between infectious agents and the human host. The spectrum of phenotypes associated with the SARS-CoV-2 infection, ranging from the absence of symptoms to severe systemic complications, raised the question as to what extent the variable response to coronaviruses (CoVs) is influenced by the variability of the hosts' genetic background.To explore the current knowledge about this question, we designed a systematic review encompassing the scientific literature published from Jan. 2003 to June 2020, to include studies on the contemporary outbreaks caused by SARS-CoV-1, MERS-CoV and SARS-CoV-2 (namely SARS, MERS and COVID-19 diseases). Studies were eligible if human genetic variants were tested as predictors of clinical phenotypes.An ad hoc protocol for the rapid review process was designed according to the PRISMA paradigm and registered at the PROSPERO database (ID: CRD42020180860). The systematic workflow provided 32 articles eligible for data abstraction (28 on SARS, 1 on MERS, 3 on COVID-19) reporting data on 26 discovery cohorts. Most studies considered the definite clinical diagnosis as the primary outcome, variably coupled with other outcomes (severity was the most frequently analysed). Ten studies analysed HLA haplotypes (1 in patients with COVID-19) and did not provide consistent signals of association with disease-associated phenotypes. Out of 22 eligible articles that investigated candidate genes (2 as associated with COVID-19), the top-ranked genes in the number of studies were ACE2, CLEC4M (L-SIGN), MBL, MxA (n = 3), ACE, CD209, FCER2, OAS-1, TLR4, TNF-α (n = 2). Only variants in MBL and MxA were found as possibly implicated in CoV-associated phenotypes in at least two studies. The number of studies for each predictor was insufficient to conduct meta-analyses.Studies collecting large cohorts from different ancestries are needed to further elucidate the role of host genetic variants in determining the response to CoVs infection. Rigorous design and robust statistical methods are warranted.
COVID-19 大流行加强了人们对传染性病原体与人类宿主之间复杂相互作用的生物学机制的兴趣。SARS-CoV-2 感染相关表型的范围从无症状到严重全身并发症不等，这引发了一个问题，即宿主遗传背景的变异性在多大程度上影响了对冠状病毒（CoV）的可变反应。为了探讨这个问题的现有知识，我们设计了一个系统综述，其中包括 2003 年 1 月至 2020 年 6 月发表的科学文献，以包括对 SARS-CoV-1、MERS-CoV 和 SARS-CoV-2（即 SARS、MERS 和 COVID-19 疾病）引起的当代暴发的研究。如果人类遗传变异被测试为临床表型的预测因子，则研究符合条件。根据 PRISMA 范例设计了一个专门用于快速审查过程的方案，并在 PROSPERO 数据库中注册（ID：CRD42020180860）。系统工作流程提供了 32 篇符合数据抽象条件的文章（28 篇关于 SARS，1 篇关于 MERS，3 篇关于 COVID-19），报告了 26 个发现队列的数据。大多数研究将明确的临床诊断作为主要结局，不同程度地与其他结局相关联（严重程度是最常分析的）。有 10 项研究分析了 HLA 单倍型（1 项涉及 COVID-19 患者），但没有提供与疾病相关表型相关联的一致信号。在 22 篇符合条件的研究候选基因（2 项与 COVID-19 相关）中，在研究数量中排名最高的基因是 ACE2、CLEC4M（L-SIGN）、MBL、MxA（n = 3）、ACE、CD209、FCER2、OAS-1、TLR4、TNF-α（n = 2）。只有 MBL 和 MxA 中的变异被认为至少在两项研究中与 CoV 相关表型有关。每个预测因子的研究数量都不足以进行荟萃分析。需要收集来自不同种族的大样本队列的研究，以进一步阐明宿主遗传变异在决定对 CoV 感染的反应中的作用。需要严格的设计和稳健的统计方法。
