The pathogenesis of Type 2 diabetes mellitus (T2DM) is complex owing to molecular heterogeneity in the afflicted population. Current diagnostic methods rely on blood glucose measurements, which are noninformative with respect to progression of the disease to other associated pathologies. Thus, predicting the risk and development of T2DM-related complications, such as cardiovascular disease, remains a major challenge. We have used a combination of quantitative methods for characterization of circulating serum biomarkers of T2DM using a cohort of nondiabetic 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 QPCR analysis. Functional pathway analysis identified perturbations in lipid and small molecule metabolism as well as pathways that lead to disruption of glucose homeostasis and blood coagulation. These putative biomarkers may be clinically useful for subset stratification of T2DM patients as well as for the development of novel therapeutics targeting the specific pathology.

Type 2 diabetes (T2DM) is a multi-factorial disease with a complex pathogenic mechanism; however a complete understanding of precise biochemical alterations accompanying the onset and progression of T2DM is lacking. Using a combination of untargeted and targeted metabolomic profiling approach we were able to delineate significantly altered metabolites in the diabetic (T2DM) group. Our results indicate significant perturbations in amino acid metabolism, TCA cycle and glycerol-phospholipid metabolism possibly impacting the overall glucose homeostasis in T2DM. A systems approach offers promise towards identification of clinically relevant markers of T2DM and novel molecular targets to foster drug discovery for effective therapeutic development for diabetes.

BackgroundMetabolic abnormalities are common in patients maintained on antipsychotics. These abnormalities increase the risk of cardiovascular diseases and mortality in this population. The aim of this study is to assess the prevalence of metabolic syndrome (MetS) in subjects maintained on antipsychotics relative to controls in Qatar, and to assess the factors contributing to the development of MetS.MethodsA cross sectional design was used to collect data and fasting blood samples from subjects maintained on antipsychotics for at least six months (n = 112) and from a control group (n = 114). The groups were compared in regard to prevalence of MetS, and multiple regression analysis was used to determine the risk factors in each group.ResultsThe two groups (antipsychotics vs. control) were similar in regard to age (35.73 ± 10.28 vs. 35.73 ± 8.16 years) and gender ratio. The MetS was higher among the subjects on antipsychotics, but this difference did not reach statistical significance. Blood pressure (BP) was significantly higher in the antipsychotics group and BMI was the major risk factor to develop MetS in this group.ConclusionsThe prevalence of MetS in both groups is high and mostly attributed to obesity and high BP. Public health interventions are needed to address this major health problem overall. Larger studies are needed to further assess the impact of antipsychotics and mental illness on the development of MetS.

Background. Several polymorphisms of a locus on chromosome 1p13.3 have a significant effect on low-density lipoprotein cholesterol (LDL-C), atherosclerosis, and acute coronary syndrome (ACS). Methods. We aimed to investigate the association between rs599839, rs646776, and rs4970834 of locus 1p13.3 and serum LDL-C and severity of coronary artery stenosis in ACS patients. Genotyping of the rs599839, rs646776, and rs4970834 polymorphisms was performed on Arab patients undergoing coronary angiography for ACS. Patients were divided into group A (ACS with insignificant stenosis (<50%)) and group B (with significant stenosis (≥50%)). Results. Patients carrying the minor G allele in rs599839 had significantly lower mean of LDL-C (2.58 versus 3.44 mM, P = 0.026) than homozygous A allele carriers (GG versus AA). Carriers of minor C allele in rs64776 had significantly higher mean of HDL-C (2.16 versus 1.36 mM, P = 0.004) than carriers of the T alleles (AA versus GG). The odd ratio and 95% confidence interval for dominant model for G allele carriers of rs599839 were 0.51 (0.30–0.92), P = 0.038, among patients with significant stenosis. Conclusions. Polymorphisms rs646776 and rs599839 of locus 1p13.3 were significantly associated with LDL-C and other lipid parameters. In addition, the G-allele carriers of variant rs599839 had a significant protective effect against the atherosclerosis.

The objective of the current study is to accomplish a relative exploration of the biological roles of differentially dysregulated genes (DRGs) in type 2 diabetes mellitus (T2DM). The study aimed to determine the impact of these DRGs on the biological pathways and networks that are related to the associated disorders and complications in T2DM and to predict its role as prospective biomarkers. Methods: Datasets obtained from metabolomic and proteomic profiling were used for investigation of the differential expression of the genes. A subset of DRGs was integrated into IPA software to explore its biological pathways, related diseases, and their regulation in T2DM. Upon entry into the IPA, only 94 of the DRGs were recognizable, mapped, and matched within the database. Results: The study identified networks that explore the dysregulation of several functions; cell components such as degranulation of cells; molecular transport process and metabolism of cellular proteins; and inflammatory responses. Top disorders associated with DRGs in T2DM are related to organ injuries such as renal damage, connective tissue disorders, and acute inflammatory disorders. Upstream regulator analysis predicted the role of several transcription factors of interest, such as STAT3 and HIF alpha, as well as many kinases such as JAK kinases, which affects the gene expression of the dataset in T2DM. Interleukin 6 (IL6) is the top regulator of the DRGs, followed by leptin (LEP). Monitoring the dysregulation of the coupled expression of the following biomarkers (TNF, IL6, LEP, AGT, APOE, F2, SPP1, and INS) highlights that they could be used as potential prognostic biomarkers. Conclusion: The integration of data obtained by advanced metabolomic and proteomic technologies has made it probable to advantage in understanding the role of these biomarkers in the identification of significant biological processes, pathways, and regulators that are associated with T2DM and its comorbidities.