| Title: | Identifying the shared genetic architecture among severe COVID-19, type 2 diabetes, and obesity using cross-trait meta-analysis |
| Journal: | Scientific Reports |
| Published: | 23 Jul 2026 |
| DOI: | https://doi.org/10.1038/s41598-026-63056-3 |
| URL: | https://www.nature.com/articles/s41598-026-63056-3_reference.pdf |
Publication 21376
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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.</p>
4 Authors
- Seunghwan Park
- Jieun Seo
- Taesung Park
- Wonil Chung
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