Evidence map›Paper›PMID 40034745›Full record

ArticleFrontiers in genetics2025

Exploring genetic loci linked to COVID-19 severity and immune response through multi-trait GWAS analyses.

Ziang Meng, Chumeng Zhang, Shuai Liu, Wen Li, Yue Wang, Qingyi Zhang, Bichen Peng, Weiyi Ye, Yue Jiang, Yingchao Song and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

13 authors.

Ziang Meng *Department of Infectious Disease, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
Chumeng Zhang *The Second School of Clinical Medicine of Shandong First Medical University, Tai'an, Shandong, China.
Shuai LiuAgricultural Products Quality and Safety Center of Jinan, Jinan, Shandong, China.
Wen LiCollege of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, Shandong, China.
Yue WangCollege of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, Shandong, China.
Qingyi ZhangCollege of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, Shandong, China.
Bichen PengCollege of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, Shandong, China.
Weiyi YeCollege of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, Shandong, China.
Yue JiangCollege of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, Shandong, China.
Yingchao SongCollege of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, Shandong, China.
Miao GuoSchool of Life Sciences, Shandong First Medical University, Shandong, China.
Xiao ChangCollege of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, Shandong, China.
Lei ShaoDepartment of Infectious Disease, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: COVID-19 severity has been linked to immune factors, with excessive immune responses like cytokine storms contributing to mortality. However, the genetic basis of these immune responses is not well understood. This study aimed to explore the genetic connection between COVID-19 severity and blood cell traits, given their close relationship with immunity. Materials and methods: GWAS summary statistics for COVID-19 and blood cell counts were analyzed using Linkage Disequilibrium Score Regression (LDSC) to estimate genetic correlations and heritabilities. For traits with significant correlations, a Multi-Trait GWAS Analysis (MTAG) was performed to identify pleiotropic loci shared between COVID-19 and blood cell counts. Results: Our MTAG analysis identified four pleiotropic loci associated with COVID-19 severity, five loci linked to hospitalized cases, and one locus related to general patients. Among these, two novel loci were identified in the high-risk population, with rs55779981 located near Conclusion: Our study offers insights into the genetic overlap between COVID-19 and immune factors, suggesting potential directions for future research and clinical exploration.

Indexed as

COVID-19genome-wide cross-trait analysisimmune responselymphocytetranscriptome-wide association studies

Identifiers

PMID40034745
PMCPMC11873281

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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.