oa Quantitative serum proteomics facilitates diabetes biomarker discovery and validation in a Qatari population

Background: The incidence and prevalence of type 2 diabetes mellitus (T2DM) is on the rise in Qatar. The pathogenesis of T2DM is complex owing to molecular heterogeneity in the afflicted population. Current diagnostic methods rely on blood glucose measurements, which are non-informative with respect to progression of the disease to other associated pathologies. Thus predicting the risk and development of T2DM-related complications like cardiovascular disease remains a major challenge. Methods: We have used a combination of quantitative methods for characterization of circulating serum biomarkers of T2DM using a cohort of non-diabetic control subjects (n=76) and patients diagnosed with T2DM (n=106). In this case-control study, the samples were randomly divided as training and validation data sets. In the first step iTRAQ (isobaric tagging for relative and absolute quantification) based protein expression profiling was performed for identification of proteins displaying a significant differential expression in the two study groups. Five of these protein markers were selected for validation using multiple reaction-monitoring mass spectrometry (MRM-MS) and further confirmed with Western Blot and QRTPCR analysis. Results: We report the identification and verification of several biomarker candidates that can be potentially used for subset stratification of T2DM cohort. We identified a total of 227 high confidence proteins corresponding to 1393 peptides with greater than 95% confidence representing >40% sequence coverage. GO analysis predicted the differentially expressed proteins to be involved in a wide variety of cellular and metabolic processes. A total of 124 proteins showed a fold change of 2 or more between the control and T2DM serum samples. We report a set of five proteins viz. apolipoprotein-A-1, vitamin D binding protein, fibronectin, afamin and transthyretin as potent biomarkers, which are significantly up-regulated in diabetics. Conclusion: Our study revealed that many distinct molecular networks and metabolic pathways were activated in T2DM. It is hoped that future studies with larger cohorts as well those that focus on dissecting mechanistic roles will enhance our understanding of pathogenesis of T2DM and contribute to the development of targeted therapeutics in accordance with the personalized medicine paradigm.