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Systematic review and meta-analysis identifies potential host therapeutic targets in COVID-19.
medRxiv - Genetic and Genomic Medicine Pub Date : 2020-09-27 , DOI: 10.1101/2020.08.27.20182238
Nicholas Parkinson , Natasha Rodgers , Max Head Fourman , Bo Wang , Marie Zechner , Maaike C. Swets , Jonathan E. Millar , Andy Law , Clark D. Russell , J. Kenneth Baillie , Sara Clohisey

The increasing body of literature describing the role of host factors in COVID- 19 pathogenesis demonstrates the need to combine diverse, multi-omic data to evaluate and substantiate the most robust evidence and inform development of therapies. Here we present a dynamic ranking of host genes implicated in human betacoronavirus infection (SARS-CoV-2, SARS-CoV, MERS-CoV, seasonal coronaviruses). Researchers can search and review the ranked genes and the contribution of different experimental methods to gene rank at https://baillielab.net/maic/covid19. We conducted an extensive systematic review of experiments identifying potential host factors. Gene lists from diverse sources were integrated using Meta- Analysis by Information Content (MAIC). This previously described algorithm uses data-driven gene list weightings to produce a comprehensive ranked list of implicated host genes. From 32 datasets, the top ranked gene was PPIA, encoding cyclophilin A, a drug- gable target using cyclosporine.Other highly-ranked genes included proposed prognostic factors (CXCL10, CD4, CD3E) and investigational therapeutic tar- gets (IL1A) for COVID-19. Gene rankings also inform the interpretation of COVID-19 GWAS results, implicating FYCO1 over other nearby genes in a disease-associated locus on chromosome 3. As new data are published we will regularly update list of genes as a resource to inform and prioritise future studies.

中文翻译:

系统评价和荟萃分析确定了COVID-19中潜在的宿主治疗靶标。

描述宿主因素在COVID-19发病机理中作用的文献越来越多,这表明需要结合多种多样的全基因组数据来评估和证实最有力的证据,并为治疗的发展提供信息。在这里,我们介绍与人类β冠状病毒感染(SARS-CoV-2,SARS-CoV,MERS-CoV,季节性冠状病毒)有关的宿主基因的动态排名。研究人员可以在https://baillielab.net/maic/covid19上搜索和审查排名的基因以及不同实验方法对基因排名的贡献。我们对确定潜在宿主因素的实验进行了广泛的系统综述。使用信息内容的元分析(MAIC)对来自不同来源的基因列表进行整合。先前描述的算法使用数据驱动的基因列表加权来生成牵连的宿主基因的综合排名列表。在32个数据集中,排名最高的基因是PPIA,编码使用环孢菌素的药物靶点亲环蛋白A。其他排名较高的基因包括拟议的预后因素(CXCL10,CD4,CD3E)和COVID的治疗靶标(IL1A)。 -19。基因排名还可以解释COVID-19 GWAS结果,在染色体3上与疾病相关的基因座中,FYCO1比其他邻近基因有影响。随着新数据的发布,我们将定期更新基因列表,以作为对未来研究进行宣传和优先考虑的资源。 。其他排名较高的基因包括拟议的预后因素(CXCL10,CD4,CD3E)和COVID-19的研究治疗靶标(IL1A)。基因排名还可以解释COVID-19 GWAS结果,在染色体3上与疾病相关的基因座中,FYCO1比其他邻近基因有影响。随着新数据的发布,我们将定期更新基因列表,以作为对未来研究进行宣传和优先考虑的资源。 。其他排名较高的基因包括拟议的预后因素(CXCL10,CD4,CD3E)和COVID-19的研究治疗靶标(IL1A)。基因排名还可以解释COVID-19 GWAS结果,在染色体3上与疾病相关的基因座中,FYCO1比其他邻近基因有影响。随着新数据的发布,我们将定期更新基因列表,以作为对未来研究进行宣传和优先考虑的资源。 。
更新日期:2020-09-28
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