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 ranked genes 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 list of genes as a resource to inform and prioritise future
studies.
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 ranked genes 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 list of genes as a resource to inform and prioritise future
studies.
| Original language | English |
|---|---|
| Journal | Scientific Reports |
| Volume | 10 |
| Issue number | 1 |
| Early online date | 18 Dec 2020 |
| DOIs | |
| Publication status | E-pub ahead of print - 18 Dec 2020 |
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Profiles
-
Andy Law
- Royal (Dick) School of Veterinary Studies - Group Leader/Senior Research Fellow
Person: Academic: Research Active