Background The COVID-19 pandemic has led to over 820,000 deaths for almost 24 million confirmed cases worldwide, as of August 27th, 2020, per WHO report. Risk factors include pre-existing conditions such as cancer, cardiovascular disease, diabetes, obesity, and cancer. There are currently no effective treatments. Our objective was to complete a meta-analysis to identify comorbidity-associated single nucleotide polymorphisms (SNPs), potentially conferring increased susceptibility to SARS-CoV-2 infection using a computational approach. Results SNP datasets were downloaded from publicly available GWAS catalog for 141 of 258 candidate COVID-19 comorbidities. Gene-level SNP analysis was performed to identify significant pathways by using MAGMA program. SNP annotation program was used to analyze MAGMA-identified genes. COVID-19 comorbidities from six disease categories were found to have significant associated pathways, which were validated by Q-Q plots (p<0.05). The top 250 human mRNA gene expressions for SNP-affected pathways, extracted from publicly accessible gene expression profiles, were evaluated for significant pathways. Protein-protein interactions of identified differentially expressed genes, visualized with STRING program, were significant (p<0.05). Gene interaction networks were found to be relevant to SARS and influenza pathogenesis. Conclusion Pathways potentially affected by or affecting SARS-CoV-2 infection were identified in underlying medical conditions likely to confer susceptibility and/or severity to COVID-19. Our findings have implications in COVID-19 treatment development. Keywords: SARS-CoV-2, COVID-19, comorbidity, susceptibility, severity

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合并症和COVID-19的易感性：通用基因组Meta分析方法

背景资料根据世界卫生组织的报告，截至2020年8月27日，COVID-19大流行已导致全球近2400万确诊病例的82万多人死亡。风险因素包括癌症，心血管疾病，糖尿病，肥胖和癌症等既往疾病。目前尚无有效的治疗方法。我们的目标是完成一项荟萃分析，以鉴定合并症相关的单核苷酸多态性（SNP），并可能通过计算方法提高对SARS-CoV-2感染的易感性。结果从258个候选COVID-19合并症中的141个公开下载的GWAS目录中下载了SNP数据集。使用MAGMA程序进行了基因水平的SNP分析，以鉴定重要的途径。SNP注释程序用于分析MAGMA鉴定的基因。发现来自六个疾病类别的COVID-19合并症具有显着的相关途径，这已通过QQ图进行了验证（p <0.05）。从公众可访问的基因表达谱中提取了SNP影响途径的前250条人类mRNA基因表达，评估了其重要途径。通过STRING程序显示，已鉴定的差异表达基因的蛋白质-蛋白质相互作用显着（p <0.05）。发现基因相互作用网络与SARS和流感发病机理有关。结论在潜在的可能导致COVID-19易感性和/或严重性的医学状况下，确定了可能受SARS-CoV-2感染影响或影响的途径。我们的发现对COVID-19治疗的发展有影响。关键字：SARS-CoV-2，COVID-19，合并症，药敏性，