Single-Cell Multi-Omics in Type 2 Diabetes Mellitus: Revealing Cellular Heterogeneity and Mechanistic Insights

Type 2 diabetes mellitus (T2DM) is a prevalent and complex metabolic disorder characterized by insulin resistance, progressive β-cell dysfunction, and severe systemic complications. Advances in single-cell multi-omics-transcriptomics, chromatin accessibility profiling, and integrative analyses-have offered unprecedented insights into the cellular heterogeneity and regulatory networks of pancreatic islets. We highlight recent discoveries in islet cell heterogeneity and β-cell pathophysiology, with a particular focus on dysfunction and dedifferentiation. We further underscore the computational frameworks that enable these discoveries, spanning data preprocessing, multi-omics integration, and machine learning-driven analyses, which collectively enable the dissection of disease-relevant cell subpopulations and the reconstruction of developmental and regulatory trajectories. We also examine how impaired signaling within islets and chronic adipose inflammation contribute to T2DM pathogenesis. Finally, we discuss key challenges in clinical translation-including limited population diversity in single-cell atlases and the interpretability of computational models-and propose future directions toward precision diagnostics and therapeutic innovation in T2DM.