Dynamic data-driven meta-analysis for prioritisation of host genes implicated in COVID-19

Sci Rep. 2020 Dec 18;10(1):22303. doi: 10.1038/s41598-020-79033-3.


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.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't
  • Systematic Review

MeSH terms

  • Algorithms
  • CD3 Complex / genetics
  • CD4 Antigens / genetics
  • COVID-19 / epidemiology*
  • COVID-19 / 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
  • Proteomics


  • CD3 Complex
  • CD3E protein, human
  • CD4 Antigens
  • CXCL10 protein, human
  • Chemokine CXCL10
  • FYCO1 protein, human
  • IL1A protein, human
  • Interleukin-1alpha
  • Microtubule-Associated Proteins
  • Cyclosporine
  • Cyclophilin A