Evidence map›Paper›PMID 34673571›Full record

ArticleThe Journal of clinical investigation2021

Will GWAS eventually allow the identification of genomic biomarkers for COVID-19 severity and mortality?

Vito Luigi Colona, Michela Biancolella, Antonio Novelli, Giuseppe Novelli

Abstract readComment
In one paragraph

Article in The Journal of clinical investigation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Review
  2. Article
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  5. Article
  6. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Vito Luigi ColonaDepartment of Biomedicine and Prevention and.
Michela BiancolellaDepartment of Biology, Tor Vergata University of Rome, Rome, Italy.
Antonio NovelliLaboratory of Medical Genetics, IRCCS Bambino Gesù Children's Hospital, Rome, Italy.
Giuseppe NovelliDepartment of Biomedicine and Prevention and.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

GWAS involve testing genetic variants across the genomes of many individuals to identify genotype-phenotype associations. GWAS have enabled the identification of numerous genomic biomarkers in various complex human diseases, including infectious ones. However, few of these studies are relevant for clinical practice or at the bedside. In this issue of the JCI, Nakanishi et al. characterized the clinical implications of a major genetic risk factor for COVID-19 severity and its age-dependent effect, using individual-level data in a large international multicenter consortium. This study indicates that a common COVID-19 genetic risk factor (rs10490770) associates with increased risks of morbidity and mortality, suggesting potential implications for future clinical risk management. How can the genomic biomarkers identified by GWAS be associated with the clinical outcomes of an infectious disease? In this Commentary, we evaluate the advantages and limitations of this approach.

Indexed as

COVID-19Genome-Wide Association StudyBiomarkers, TumorGenomicsHumansSARS-CoV-2Biomarkers, Tumor

Identifiers

PMID34673571
PMCPMC8631589

What OpenQuestion holds

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Registered trials

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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.