Bioinformatic Insights and XGBoost Identify Shared Genetics in Chronic Obstructive Pulmonary Disease and Type 2 Diabetes
This study identifies key genetic markers shared between COPD and T2DM, providing new insights into their molecular pathways. Our XGBoost model exhibited high predictive accuracy for COPD, highlighting the potential utility of these markers. These findings offer promising biomarkers for early detection and enhance our understanding of the diseases' interplay. Further validation in larger cohorts is recommended.
Authors
- Yaxian Meng (ORCID: https://orcid.org/0009-0006-1514-0470)
- Xiaoliang Chen (ORCID: https://orcid.org/0009-0005-4025-531X)
- Xiaojie Han (ORCID: https://orcid.org/0000-0003-1255-3430)
- Chao Yi (ORCID: https://orcid.org/0000-0001-7445-5030)
- Yiqiang Zhan (ORCID: https://orcid.org/0000-0001-6016-5665)
- Qianqian Ji (ORCID: https://orcid.org/0009-0002-3203-4208)
Institutions
- Sun Yat-sen University (CN)
- Karolinska Institutet (SE)
Publication Details
- Journal
- The Clinical Respiratory Journal
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1111/crj.70057
- Citations
- 1
- Primary Topic
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Type
- article
- Field-Weighted Citation Impact
- 1.52
Funders
- Sun Yat-sen University