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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
Published on: March 14, 2013
Untargeted LC-MS/MS profiling identifies ST18 as a novel serum marker for T2DM-associated depression
Jiya Singh1, Sabyasachi Bandyopadhyay2, Atanu Sen1
1Department of Biochemistry, All India Institute of Medical Sciences, Rishikesh, India.
Abstract:
Depression is a prevalent but underdiagnosed comorbidity in type 2 diabetes mellitus (T2DM), intensifying disease burden and complicating metabolic management. Reliable biomarkers for early detection remain limited. This study aimed to identify serum protein signatures associated with depression in individuals with T2DM using an untargeted proteomic approach. Methods Serum samples from healthy controls, T2DM patients, and T2DM patients with comorbid depression (n = 6 per group) were analyzed using LC-MS/MS-based untargeted proteomics (total n = 18). Differential protein abundance was assessed using MetaboAnalyst 6.0. Protein-protein interaction networks and pathway enrichment analyses were conducted using the STRING database. Candidate markers were further validated by ELISA in an independent cohort of healthy controls (n = 30), T2DM (n = 30), and T2DM with depression (n = 30). Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves. Results LC-MS/MS identified 242 serum proteins, of which 12 were significantly dysregulated among the groups. Nine proteins showed unique alterations in the T2DM-depression group. STRING analysis highlighted ST18 as a central regulatory protein. ELISA validation confirmed significant elevation of LRG1, APOC2, and ST18 in T2DM with depression compared to controls and T2DM without depression. Among these, ST18 demonstrated the highest diagnostic accuracy, yielding the greatest area under the ROC curve. Conclusion Untargeted proteomic profiling revealed distinct serum protein alterations in T2DM patients with comorbid depression. ST18 emerged as a robust and specific biomarker, suggesting its potential involvement in the molecular interplay between metabolic dysregulation and depressive pathology. Larger, longitudinal studies are required to validate its predictive utility and clarify its role in T2DM-associated depression.