Identifying the shared genetic architecture among severe COVID-19, type 2 diabetes, and obesity using cross-trait meta-analysis

This study explores the shared genetic architecture between severe COVID-19 and metabolic traits such as type 2 diabetes (T2D), body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR). While chronic conditions such as T2D and obesity are known to increase the risk of severe COVID-19, the genetic mechanisms underlying these associations remain unclear. To address this gap, we performed cross-trait meta-analyses using genome-wide association study (GWAS) data and identified significant genetic correlations between severe COVID-19 and metabolic traits. Subsequent analyses revealed shared genetic loci, indicating potential pleiotropic effects. To assess the functional relevance of these findings, we conducted transcriptome-wide association studies (TWAS) across multiple tissues. The TWAS analyses identified key genes significantly associated with metabolically relevant tissues, including adipose, cardiovascular, and immune-related tissues. Pathway enrichment analyses using the KEGG pathway database, GWAS Catalog, and DisGeNET further revealed substantial genetic overlap between severe COVID-19 and metabolic traits. These findings suggest that metabolic dysregulation may exacerbate severe COVID-19 through shared immune-metabolic pathways and highlight candidate genes and mechanisms that link metabolic health to COVID-19 outcomes.

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Publication Details

Journal
Scientific Reports
Published
2026-07-23
DOI
https://doi.org/10.1038/s41598-026-63056-3
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00

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article

Identifying the shared genetic architecture among severe COVID-19, type 2 diabetes, and obesity using cross-trait meta-analysis

Wonil Chung, Jieun Seo, Taesung Park, Seunghwan Park
Scientific Reports
Genetic Associations and Epidemiology
article

Identifying the shared genetic architecture among severe COVID-19, type 2 diabetes, and obesity using cross-trait meta-analysis

Wonil Chung, Jieun Seo, Taesung Park, Seunghwan Park
article en

Abstract

This study explores the shared genetic architecture between severe COVID-19 and metabolic traits such as type 2 diabetes (T2D), body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR). While chronic conditions such as T2D and obesity are known to increase the risk of severe COVID-19, the genetic mechanisms underlying these associations remain unclear. To address this gap, we performed cross-trait meta-analyses using genome-wide association study (GWAS) data and identified significant genetic correlations between severe COVID-19 and metabolic traits. Subsequent analyses revealed shared genetic loci, indicating potential pleiotropic effects. To assess the functional relevance of these findings, we conducted transcriptome-wide association studies (TWAS) across multiple tissues. The TWAS analyses identified key genes significantly associated with metabolically relevant tissues, including adipose, cardiovascular, and immune-related tissues. Pathway enrichment analyses using the KEGG pathway database, GWAS Catalog, and DisGeNET further revealed substantial genetic overlap between severe COVID-19 and metabolic traits. These findings suggest that metabolic dysregulation may exacerbate severe COVID-19 through shared immune-metabolic pathways and highlight candidate genes and mechanisms that link metabolic health to COVID-19 outcomes.

Scientific Reports
Harvard University (US), Seoul National University (KR), Soongsil University (KR)
National Research Foundation, National Research Foundation of Korea
Zero hunger
Openalex Percentile: Top 9%
Genetic Associations and Epidemiology
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Identifying the shared genetic architecture among severe COVID-19, type 2 diabetes, and obesity using cross-trait meta-analysis — Wonil Chung, Jieun Seo, et al. · Scientific Reports (2026) | TGRS Research Map | TGRS