Exploring Sex Differences in Type 2 Diabetes via a Male-Dominant Beta-Cell Cluster from Single-Cell Pancreatic Sequencing of Public Datasets.

Background: Type 2 diabetes is a complex metabolic disorder characterized by insulin resistance and progressive beta-cell dysfunction. Although sex differences in type 2 diabetes prevalence, progression, and complications have been reported, the molecular mechanisms underlying these differences remain largely unknown. We aimed to utilize single-cell RNA sequencing to identify a beta-cell cluster that is more prevalent in males than in females and exhibits distinct gene expression patterns, gene set enrichment profiles, and cell-cell communication compared to other clusters.

Methods: FASTQ files from four public datasets were preprocessed, aligned to the human genome (GRCh38), and integrated into a high-quality matrix to mitigate batch effects. We focused on beta-cells from type 2 diabetes patients, performed trajectory inference to identify clusters, and conducted differential gene expression and gene set enrichment analyses. These findings were validated using bulk RNA-seq datasets. Additionally, cell-cell communication analysis was performed to identify ligand-receptor interactions, followed by a sensitivity analysis to assess sex-specific differences.

Results: We identified a male-dominant beta-cell cluster (adjusted P value=4.2×10-6) that displayed unique gene expression patterns and downregulation of pathways associated with protein metabolism and insulin synthesis. Differentially expressed genes (e.g., interleukin 24 [IL24], regulator of G protein signaling like 1 [RGSL1]) were confirmed through bulk analysis. Moreover, the cluster demonstrated distinct communication patterns with other cell types, underscoring sex-specific differences.

Conclusion: We have identified a male-dominant beta-cell cluster characterized by distinct gene expression, signaling pathways, and cell interactions. These findings provide insights into the pathophysiology of type 2 diabetes and may inform the development of more effective, sex-specific therapeutic strategies in the future.