ABSTRACT
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). 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 druggable target using cyclosporine. Other highly-ranked genes included proposed prognostic factors (CXCL10, CD4, CD3E) and investigational therapeutic targets (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. Researchers can search and review the gene rankings and the contribution of different experimental methods to gene rank at https://baillielab.net/maic/covid19 . As new data are published we will regularly update the list of genes as a resource to inform and prioritise future studies.
Subject(s)
COVID-19/epidemiology , COVID-19/genetics , Algorithms , CD3 Complex/genetics , CD4 Antigens/genetics , Chemokine CXCL10/genetics , Computational Biology , Cyclophilin A/genetics , Cyclosporine/pharmacology , Databases, Genetic , Genome-Wide Association Study , Genomics , Humans , Immune System , Immunogenetics , Inflammation , Interleukin-1alpha/genetics , Microtubule-Associated Proteins/genetics , ProteomicsABSTRACT
BACKGROUND: We observe changes of the main lymphocyte subsets (CD16+CD56ãCD19ãCD3ãCD4ãand CD8) in COVID-19-infected patients and explore whether the changes are associated with disease severity. METHODS: One-hundred and fifty-four cases of COVID-19-infected patients were selected and divided into 3 groups (moderate group, severe group and critical group). The flow cytometry assay was performed to examine the numbers of lymphocyte subsets. RESULTS: CD3+, CD4+ and CD8 + T lymphocyte subsets were decreased in COVID-19-infected patients. Compared with the moderate group and the sever group, CD3+, CD4+ and CD8+ T cells in the critical group decreased greatly (P < 0.001, P = 0.005 or P = 0.001). CONCLUSIONS: Reduced CD3+, CD4+, CD8+ T lymphocyte counts may reflect the severity of the COVID-19. Monitoring T cell changes has important implications for the diagnosis and treatment of severe patients who may become critically ill.