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Peer-reviewedCC BYScientific Reports

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

  • Seunghwan Park1
  • Jieun Seo1
  • Taesung Park2
  • Wonil Chung1
  1. 1Department of Statistics and Actuarial Science, Soongsil University
  2. 2Department of Statistics, Seoul National University
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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.

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Cite

BibTeXRIS
BibTeX
@article{park2026identifying,
  title = {{Identifying the shared genetic architecture among severe COVID-19, type 2 diabetes, and obesity using cross-trait meta-analysis}},
  author = {Seunghwan Park and Jieun Seo and Taesung Park and Wonil Chung},
  journal = {Scientific Reports},
  year = {2026},
  month = jul,
  doi = {10.1038/s41598-026-63056-3},
  url = {https://doi.org/10.1038/s41598-026-63056-3},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Identifying the shared genetic architecture among severe COVID-19, type 2 diabetes, and obesity using cross-trait meta-analysis
AU  - Seunghwan Park
AU  - Jieun Seo
AU  - Taesung Park
AU  - Wonil Chung
PY  - 2026
DA  - 2026/07/01
JO  - Scientific Reports
DO  - 10.1038/s41598-026-63056-3
UR  - https://doi.org/10.1038/s41598-026-63056-3
AB  - 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.
SN  - 2045-2322
ER  -