DOI: 10.3390/biomedicines14112481 ISSN: 2227-9059

A Senescence-Associated Transcriptional Signature in PBMC for Molecular Characterization and Diagnosis of Type 2 Diabetes Mellitus

Shangrong Wu, Changqing Yin, Xiaolan He, Lu Xiong, Yuexi Zhou, Yajun Hu, Haiqiang Ke

Background/Objectives: Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder associated with substantial morbidity and mortality. Peripheral blood mononuclear cells (PBMCs) represent an accessible cellular source for investigating systemic molecular alterations in T2DM. This study aimed to characterize senescence-associated transcriptional alterations in PBMCs and to evaluate their potential relevance to the molecular characterization and diagnosis of T2DM. Methods: Publicly available PBMC RNA-sequencing datasets were integrated following normalization and batch-effect correction. Differentially expressed genes were intersected with curated senescence-associated gene sets and subjected to functional enrichment analyses. Weighted gene co-expression network analysis was used to identify T2DM-associated gene modules, and immune deconvolution was performed to characterize alterations in immune-cell composition. LASSO regression, random forest, and support vector machine analyses were integrated to identify candidate diagnostic genes. The resulting gene signature was evaluated in independent cohorts and further validated by RT-qPCR in clinical PBMC samples. Consensus clustering was additionally performed to investigate molecular heterogeneity among patients with T2DM. Results: Senescence-associated transcriptional alterations were enriched in pathways related to RNA processing, cell-cycle regulation, and metabolism. A three-gene signature comprising ICE2, NHLRC2, and RPS24 was identified and showed reproducible diagnostic performance across independent cohorts. A nomogram incorporating these genes achieved an area under the receiver operating characteristic curve of 0.882. RT-qPCR analysis of clinical PBMC samples confirmed expression patterns consistent with the transcriptomic analyses. Furthermore, consensus clustering identified distinct T2DM molecular subtypes characterized by differential immune and inflammatory profiles. Conclusions: These findings identify a senescence-associated PBMC transcriptional signature with potential diagnostic relevance in T2DM and reveal molecular heterogeneity associated with distinct immune and inflammatory features. The results provide a transcriptomic framework for further investigation of senescence-related immune–metabolic alterations in T2DM.

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