| Multiomics Integration of Epigenetics, Proteomics, and Metabolomics Identifies Putative Drug Targets and Improves Early Prediction for Diabetes |
| 論文作者 |
Li, WR; Cheng, YY; Cui, AY; Huang, MY; Huang, QX; Wang, Q; Xia, MF; Qiu, JE; Peng, QQ; Li, JR; Li, HT; Wang, Y; Zong, G; Zheng, Y; Wang, JC; Gao, X; Ding, C; Tang, HR; Jiang, BH; Jin, L; Li, Y; Wang, SJ |
| 期刊/會(huì)議名稱 |
DIABETES |
| 論文年度 |
2025 |
| 論文類別 |
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| 摘要 |
Diabetes holds significant social importance due to its high incidence rate and multitude of associated complications. The identification of diabetes biomarkers and the understanding of the intricate biological mechanisms underlying diabetes are crucial for the early diagnosis and treatment of diabetes. In this study, we conducted comprehensive omics profiling of CpGs, plasma proteins, and serum metabolites in an National Survey of Physical Traits (NSPT) cohort of 3,451 individuals, among whom 293 were patients with diabetes. Global association analysis identified 175 CpGs, 29 proteins, and 93 metabolites significantly linked to diabetes, among which 43 CpGs and 25 metabolites were validated in an independent cohort comprising 532 individuals. Mendelian randomization and mediation analysis identified 20 causal biomarkers and 190 signaling pathways linking biomarkers from different layers. By integrating the cross-omics evidence, we provide a list of putative causal biomarkers of diabetes to serve as a valuable resource for the diabetes community. Cross-omics integration prioritized biomarkers for therapeutic targeting, highlighting COLEC11 as an example of a potential target and whose function was further validated in vitro. The early-prediction model using the prioritized biomarkers improved the area under the receiver operating characteristic curve by 27.5% compared with the baseline model, using clinical features alone. Our findings provide a comprehensive list of prioritized multiomics biomarkers and elucidate specific signaling pathways in diabetes, contributing significantly to the selection of therapeutic target and the understanding of diabetes pathophysiology.Article Highlights A total of 175 CpGs, 29 proteins, and 93 metabolites were identified as associated with diabetes, among which 43 CpGs and 25 metabolites were validated in an independent cohort. Causal and mediation analyses revealed 20 biomarkers and 190 signaling pathways involved in diabetes development. The integrative multiomics prioritization provides the community with an ordered list of diabetes biomarkers. We experimentally validated one of the prioritized proteins, COLEC11, and demonstrated its involvement in lipid metabolism. Our findings prioritize potential therapeutic targets and demonstrate that integrating multiomics biomarkers improves diabetes risk prediction beyond traditional clinical models. |
| 卷 |
74 |
| 影響因子 |
7.5 |
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