Evidence map›Paper›PMID 37378764›Full record

ReviewAdvances in experimental medicine and biology2023

Genetic Associations with Coronavirus Susceptibility and Disease Severity.

Fatima Barmania, Juanita Mellet, Megan A Holborn, Michael S Pepper

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
3.5field-weighted citation impact, top 9% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 1 institution in 1 country.

Fatima BarmaniaInstitute for Cellular and Molecular Medicine, Department of Immunology, SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa.
Juanita MelletInstitute for Cellular and Molecular Medicine, Department of Immunology, SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa.
Megan A HolbornInstitute for Cellular and Molecular Medicine, Department of Immunology, SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa.
Michael S PepperInstitute for Cellular and Molecular Medicine, Department of Immunology, SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa. michael.pepper@up.ac.za.
University of Pretoria · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for the coronavirus disease 2019 (COVID-19) global public health emergency, and the disease it causes is highly variable in its clinical presentation. Host genetic factors are increasingly recognised as a determinant of infection susceptibility and disease severity. Several initiatives and groups have been established to analyse and review host genetic epidemiology associated with COVID-19 outcomes. Here, we review the genetic loci associated with COVID-19 susceptibility and severity focusing on the common variants identified in genome-wide association studies.

Indexed as

COVID-19Middle East Respiratory Syndrome CoronavirusGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansPatient AcuitySARS-CoV-2Candidate geneCovid-19GWASHost geneticsSARS-CoV-2SeveritySusceptibilityVariants

Identifiers

PMID37378764
OpenAlexW4382344057

What OpenQuestion holds

Textmetadata
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.