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Systematic review and meta-analysis identifies potential host therapeutic targets in COVID-19.
Preprint
em En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-20182238
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). 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 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. As new data are published we will regularly update list of genes as a resource to inform and prioritise future studies.
cc_by_nc_nd
Texto completo:
1
Coleções:
09-preprints
Base de dados:
PREPRINT-MEDRXIV
Tipo de estudo:
Experimental_studies
/
Prognostic_studies
/
Review
/
Systematic_reviews
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Preprint