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DOI 10.3760/cma.j.cn112338-20250407-00217

Медицинская библиотека · Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi · 2025

[Exploring potential molecular biomarkers of gestational diabetes mellitus through multi-omics data integration].

Mu Y, Wen Y, Li J H, Deng Y Y, Hu Z C, Zhao J, Gao X

Аннотация на английскомСтатьяПеревод в очереди

Аннотация

Objective

To explore protein molecular markers and therapeutic targets for gestational diabetes mellitus (GDM).

Methods

Based on transcriptomic, proteomic, and genomic data, we performed Mendelian randomization and colocalization analyses to preliminarily identify candidate proteins whose expression levels are associated with GDM risk and to evaluate whether the same causal variants drive protein levels and GDM. Protein-protein interaction (PPI) network analysis was then applied to elucidate interactions among these proteins, and gene ontology (GO) enrichment analysis was conducted to summarize their features in terms of biological processes, cellular components, and molecular functions. Finally, integrating our findings with existing evidence, we graded proteins significantly associated with GDM risk at the expression level according to established criteria for prioritizing potential protein targets.

Results

GCKR (OR=3.55, 95%CI: 2.60-4.84) was classified as first-tier evidence. Proteins with second-tier evidence included PARP1 (OR=0.53, 95%CI: 0.39-0.81), NUDT2 (OR=1.13, 95%CI: 1.07-1.20), and NRBP1 (OR=0.18, 95%CI: 0.10-0.31). Third-tier evidence encompassed SV2A (OR=1.30, 95%CI: 1.12-1.52), PINLYP (OR=0.92, 95%CI: 0.89-0.94), PILRA (OR=0.96, 95%CI: 0.95-0.98), LYPLAL1 (OR=1.68, 95%CI: 1.33-2.13), BOLA1 (OR=1.56, 95%CI: 1.18-2.07), TYRO3 (OR=1.08, 95%CI: 1.04-1.11) and SF3B4 (OR=2.89, 95%CI: 1.51-5.51). PPI network analysis revealed an interaction between GCKR and LYPLAL1, and GO enrichment analysis indicated that the 11 proteins were involved in pathways such as the regulation of small-molecule metabolic processes and responses to fructose.

Conclusions

Through the development of a multi-omics integrative genetic framework, we identified 11 proteins whose circulating levels are significantly associated with the risk of GDM. These findings offer multidimensional molecular insights into the pathogenesis of GDM, providing multidimensional molecular mechanism evidence for the exploration of potential biomarkers and targeted therapeutic research in GDM.

Для цитирования: Mu Y, Wen Y, Li J H, Deng Y Y, Hu Z C, Zhao J, Gao X. [Exploring potential molecular biomarkers of gestational diabetes mellitus through multi-omics data integration].. Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi. 2025. DOI: 10.3760/cma.j.cn112338-20250407-00217.

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