Genes
Identification of CLOCK and MARK2 as Candidate Blood-Based Biomarkers in Type 2 Diabetes: An Integrated Bulk and Single-Cell Transcriptomic Study
By Yang L, Tang J, Zhang D and 1 others.
Abstract
Background
Type 2 diabetes mellitus (T2DM) is often accompanied by nervous system complications. However, the molecular mechanisms underlying T2DM remain incompletely understood. This study aimed to identify candidate blood-based biomarkers associated with T2DM by screening a neural-related gene set through integrated bulk and single-cell transcriptomic analysis of peripheral blood. The present analysis focused on the systemic expression patterns of the selected genes in peripheral blood as indicators of T2DM-associated immunometabolic dysregulation, rather than on neurological involvement. The neural-related gene set was used only as a predefined screening starting point.
Methods
We employed a three-tier validation framework comprising (1) a training cohort (GSE15932, 8 T2DM patients vs. 8 controls) for biomarker discovery using differential expression analysis and machine learning (XGBoost, random forest, and PPI network topology); (2) an independent validation cohort (GSE184050, 50 T2DM patients vs. 65 controls) for cross-dataset diagnostic performance assessment (ROC analysis); and (3) an experimental validation cohort (5 T2DM patients vs. 5 controls) for independent clinical confirmation by RT-qPCR. Additionally, single-cell RNA sequencing (GSE268210) was used to investigate cell type-specific expression and immune regulatory networks.