Evidence map›Paper›PMID 33339864›Full record

SynthesisScientific reports2020

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

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 and 1 more

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 5 pooled it
0.9field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 5 syntheses or guidelines pooled it, 50 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 2 countries.

Nicholas ParkinsonRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
Natasha RodgersRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
Max Head FourmanRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
Bo WangRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
Marie ZechnerRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
Maaike C SwetsRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
Jonathan E MillarRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
Andy LawRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
Clark D RussellRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.
J Kenneth BaillieRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK. j.k.baillie@ed.ac.uk.
Sara ClohiseyRoslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK. sara.clohisey@roslin.ed.ac.uk.
Roslin Institute · GBUniversity of Edinburgh · GB

Funding

Medical Research Council MC_PC_19025Medical Research Council MC_PC_19059
6 · The paper itself

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.

Indexed as

AlgorithmsCD3 ComplexCD4 AntigensChemokine CXCL10Computational BiologyCOVID-19Cyclophilin ACyclosporineDatabases, GeneticGenome-Wide Association StudyGenomicsHumansImmune SystemImmunogeneticsInflammationInterleukin-1alphaCD3 ComplexCD3E protein, humanCD4 AntigensChemokine CXCL10CXCL10 protein, humanCyclophilin ACyclosporineFYCO1 protein, humanIL1A protein, humanInterleukin-1alphaMicrotubule-Associated Proteins

Identifiers

PMID33339864
PMCPMC7749145
OpenAlexW3116963543

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.