Evidence map›Paper›PMID 35987511›Full record

SynthesisGene2022

Systematic review and meta-analysis of human genetic variants contributing to COVID-19 susceptibility and severity.

Kajal Gupta, Gaganpreet Kaur, Tejal Pathak, Indranil Banerjee

Open access · greenAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Gene, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
6.5field-weighted citation impact, top 2% 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

34 citing papers in PubMed, 66 citations in OpenAlex.

  1. Article
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  6. The I/D variant of theFuture science OA · 2025
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  7. Article
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  14. Association between FTO polymorphism and COVID-19 mortality among older adults: A population-based cohort study.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2024
    Article
  15. Article
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  17. Association ofHeliyon · 2024
    Article
  18. Article
  19. Review
  20. Predictive Factors andInternational journal of molecular sciences · 2023
    Article
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.

Kajal GuptaCellular Virology Lab, Department of Biological Sciences, Indian Institute of Science Education and Research, Mohali (IISER Mohali), Sector 81, S.A.S Nagar, Mohali 140306, India.
Gaganpreet KaurCellular Virology Lab, Department of Biological Sciences, Indian Institute of Science Education and Research, Mohali (IISER Mohali), Sector 81, S.A.S Nagar, Mohali 140306, India.
Tejal PathakCellular Virology Lab, Department of Biological Sciences, Indian Institute of Science Education and Research, Mohali (IISER Mohali), Sector 81, S.A.S Nagar, Mohali 140306, India.
Indranil BanerjeeCellular Virology Lab, Department of Biological Sciences, Indian Institute of Science Education and Research, Mohali (IISER Mohali), Sector 81, S.A.S Nagar, Mohali 140306, India. Electronic address: indranil@iisermohali.ac.in.
Indian Institute of Science Education and Research Mohali · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has spawned global health crisis of unprecedented magnitude, claiming millions of lives and pushing healthcare systems in many countries to the brink. Among several factors that contribute to an increased risk of COVID-19 and progression to exacerbated manifestations, host genetic landscape is increasingly being recognized as a critical determinant of susceptibility/resistance to infection and a prognosticator of clinical outcomes in infected individuals. Recently, several case-control association studies investigated the influence of human gene variants on COVID-19 susceptibility and severity to identify the culpable mutations. However, a comprehensive synthesis of the recent advances in COVID-19 host genetics research was lacking, and the inconsistent findings of the association studies required reliable evaluation of the strength of association with greater statistical power. In this study, we embarked on a systematic search of all possible reports of genetic association with COVID-19 till April 07, 2022, and performed meta-analyses of all the genetic polymorphisms that were examined in at least three studies. After identifying a total of 84 studies that investigated the association of 130 polymorphisms in 61 genes, we performed meta-analyses of all the eligible studies. Seven genetic polymorphisms involving 15,550 cases and 444,007 controls were explored for association with COVID-19 susceptibility, of which, ACE1 I/D rs4646994/rs1799752, APOE rs429358, CCR5 rs333, and IFITM3 rs12252 showed increased risk of infection. Meta-analyses of 11 gene variants involving 6702 patients with severe COVID-19 and 8640 infected individuals with non-severe manifestations revealed statistically significant association of ACE2 rs2285666, ACE2 rs2106809, ACE2 rs2074192, AGTR1 rs5186, and TNFA rs1800629 with COVID-19 severity. Overall, our study presents a synthesis of evidence on all the genetic determinants implicated in COVID-19 to date, and provides evidence of correlation between the above polymorphisms with COVID-19 susceptibility and severity.

Indexed as

COVID-19Angiotensin-Converting Enzyme 2Genetic Predisposition to DiseaseHuman GeneticsHumansMembrane ProteinsPandemicsRNA-Binding ProteinsSARS-CoV-2Angiotensin-Converting Enzyme 2IFITM3 protein, humanMembrane ProteinsRNA-Binding ProteinsAssociationCOVID-19Meta-analysisPolymorphismSARS-CoV-2Systematic review

Identifiers

PMID35987511
PMCPMC9384365
OpenAlexW4292133274

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.