Multi-omics reveals regulatory networks and critical early-warning factors for severe disease progression in diabetic patients infected with SARS-CoV-2

Background Diabetic patients face elevated risks of severe COVID-19, yet the molecular underpinnings of disease progression, particularly for Omicron subvariants, which have predominated since late 2021, remain poorly defined. This observational study leverages a cohort recruited during China’s Omicron peak (December 2022–February 2023) to delineate multi-omic signatures underlying severe diabetic COVID-19. Methods We enrolled 55 patients across five clinical strata: non-diabetic mild/severe, diabetic mild/severe/fatal. Integrated 4D-DIA proteomics and LC/GC-MS metabolomics were applied, adjusting for confounders while retaining secondary infections as integral disease features. Results Diabetic patients exhibited immune exhaustion with elevated IL-6/IL-10, blunted antiviral responses, and high secondary infection rates. We identified 62 diabetes-unique molecules associated with coordinated dysregulation across six pathways: oxidative stress, ferroptosis, glycolytic dysfunction, lipid remodeling, insulin signaling, and endothelial injury. A graded molecular signature tracked clinical deterioration: progressive depletion of GP1BB and PRG3, coupled with stepwise elevation of MMP-3/LOXL1 and Dl-Xylose. Fatal cases further revealed a metabolic substrate misalignment, glycolytic flux adduct accumulation paradoxically coexisting with glucose, lactate, ornithine depletion, suggesting terminal fuel utilization failure. Stage-dependent shifts of stress mediators (e.g., GSK3B, ALDH9A1) distinguished severe from fatal outcomes, implying transition from compensatory adaptation to homeostatic exhaustion. Conclusions Severe diabetic COVID-19 is characterized by progressive immune-metabolic collapse. GP1BB, MMP-3, and Dl-Xylose warrant evaluation as early-warning biomarkers, while ornithine and PC(18:2) may track homeostatic reserve depletion in terminal disease. Together, these findings identify candidate biomarkers and pathway nodes that, with further validation, could contribute to risk-stratification and therapeutic strategies for diabetic patients with severe viral infections.