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ObjectiveChronic hyperglycemia induces pathogenic changes in the vascular endothelium and leads to the development of microvascular complications in patients with type 2 diabetes mellitus. Early identification of markers of diabetes complications may help to minimize the risk of the development and progression of microvascular complications.MethodsThis follow-up study was conducted in type 2 diabetic cohort aged between 30-70 years. Out of 160 eligible participants, 70 of them completed follow-up. Levels of cell adhesion molecules and selectins (VCAM-1, ICAM-1, E-selectin, L-selectin and P-selectin) at baseline and follow-up were measured using Randox Evidence biochip analyzer (UK). Development of microvascular complications (diabetic neuropathy, retinopathy and nephropathy) was evaluated.ResultsDuring the follow-up (2 years, median), 31 (44.3%) developed diabetic neuropathy, 10 (14.3%) developed diabetic retinopathy and, 27 (38.6%) developed diabetic nephropathy. A significant difference in levels of cell adhesion molecules and selectins were found in type 2 diabetic patients with and without microvascular complications. Multiple logistic regression analysis reveals that baseline level of VCAM-1 is significantly associated with microvascular complications; diabetic neuropathy(p=0.028), retinopathy (p=0.007) and nephropathy(p=ConclusionCell adhesion molecules and selectins are indicators of microvascular complication among patients with type 2 diabetes (T2D). Association of these markers with the development of microvascular complications may provide additive information for developing strategies for diabetes management and prediction of microvascular complications.

BackgroundChronic kidney disease (CKD) in patients with type 2 diabetes mellitus (T2DM) is the major cause of end stage renal disease, characterized by proteinuria with a subsequent decline in glomerular filtration rate. Although hyperglycemia is the major risk factor for the development and progression of kidney disease among diabetic patients, many other risk factors also contribute to structural and functional changes in the kidneys. As recommended by Kidney Disease Improving Global Outcomes (KDIGO), CKD classification based on cause and severity, links to risk of adverse outcomes including mortality and kidney outcomes.ObjectiveThe aim of this study is to investigate the involvement of risk factors associated with the severity of CKD among participants with longer duration of diabetes. This study also aims to find whether number of risk factors vary among risk of CKD progression categories based on KDIGO classification.Material and methodsThis cross-sectional study retrospectively selected 424 participants from type 2 diabetic cohort and categorized them based on the classifications for the diagnosis of kidney diseases in patients with diabetes, according to the KDIGO guidelines. Odds ratios and 95% CI of each risk factors according to severity of renal disease were determined.ResultsBased on KDIGO classification, participants with type 2 diabetes (T2D) were categorized in to low risk (n=174); moderately increased risk (n=98); and high/very high risk (n=152). Type 2 diabetic participants with risk factors such as, hyperlipidemia, hypertension, DM duration ≥15 years and diabetic retinopathy showed a high/very high risk of CKD progression when compared with low-risk category. While T2D participants with risk factors such as, lack of exercise, hypertension, and diabetic retinopathy showed a moderately increased risk of CKD progression. In addition, participants with highest number of risk factors were significantly distributed among high/very high risk of CKD progression category.ConclusionThis study findings conclude that patients with T2DM and duration of ≥15 years, hyperlipidemia, hypertension and diabetic retinopathy have an increased prevalence of advanced CKD. In addition to this, increased number of risk factors could be an indicator of the severity of CKD in T2D.

BackgroundHyperthyroidism is characterized by increased thyroid hormone production, which impacts various processes, including metabolism and energy expenditure. Yet, the underlying mechanism and subsequent influence of these changes are unknown. Metabolomics is a broad analytical method that enables qualitative and quantitative examination of metabolite level changes in biological systems in response to various stimuli, pathologies, or treatments.ObjectivesThis study uses untargeted metabolomics to explore the potential pathways and metabolic patterns associated with hyperthyroidism treatment.MethodsThe study consisted of 20 patients newly diagnosed with hyperthyroidism who were assessed at baseline and followed up after starting antithyroid treatment. Two blood samples were taken from each patient, pre (hyperthyroid state) and post-treatment (euthyroid state). Hyperthyroid and euthyroid states were identified based on thyroxine and thyroid-stimulating hormone levels. The metabolic alteration associated with antithyroid therapy was investigated using liquid chromatography- high-resolution mass spectrometry. The untargeted metabolomics data was analyzed using both univariate and multivariate analyses using MetaboAnalyst v5.0. The significant metabolic pattern was identified using the lab standard pipeline, which included molecular annotation in the Human Metabolome Database, LipidMap, LipidBlast, and METLIN. The identified metabolites were examined using pathway and network analyses and linked to cellular metabolism.ResultsThe results revealed a strong group separation between the pre- and post-hyperthyroidism treatment (Q2 = 0.573, R2 = 0.995), indicating significant differences in the plasma metabolome after treatment. Eighty-three mass ions were significantly dysregulated, of which 53 and 30 characteristics were up and down-regulated in the post-treatment compared to the pre-treatment group, respectively. The medium-chain acylcarnitines, octanoylcarnitine, and decanoylcarnitine, previously found to rise in hyperthyroid patients, were among the down-regulated metabolites, suggesting that their reduction could be a possible biomarker for monitoring euthyroid restoration. Kynurenine is a downregulated tryptophan metabolite, indicating that the enzyme kynurenine 3-hydroxylase, inhibited in hyperthyroidism, is back functioning. L-cystine, a cysteine dimer produced from cysteine oxidation, was among the down-regulated metabolites, and its accumulation is considered a sign of oxidative stress, which was reported to accompany hyperthyroidism; L-cystine levels dropped, this suggests that the plasma level of L-cystine can be used to monitor the progress of euthyroid state restoration.ConclusionThe plasma metabolome of patients with hyperthyroidism before and after treatments revealed differences in the abundance of several small metabolites. Our findings add to our understanding of hyperthyroidism’s altered metabolome and associated metabolic processes and shed light on acylcarnitines as a new biomarker for treatment monitoring in conjunction with thyroxine and thyroid-stimulating hormone.

Goiter is a term to describe the enlargement of the thyroid gland. The pathophysiology and molecular changes behind development of diffuse benign goiter remains unclear. The present study targeted to identify and describe the alterations in the thyroid tissue proteome from patients (obese euthyroid) with benign diffuse goiter (BDG) using proteomics approach. Thyroid tissue samples, from 7 age and sex matched, patients with BDG and 7 controls were obtained at the time of surgery. An untargeted proteomic analysis of the thyroid tissue was performed out utilizing two-dimensional difference (2D-DIGE) in gel electrophoresis followed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for identification of the proteins. Progenesis software was used to identify changes in expression of tissue proteins and found statistically significant differences in abundance in a total of 90 proteins, 46 up and 44 down (1.5-fold change, ANOVA, p ≤ 0.05) in BDG compared to the control group. Bioinformatic analysis using Ingenuity Pathway Analysis (IPA) identified dysregulation of signalling pathways linked to ERK1/2, Glutathione peroxidase and NADPH oxidase associated to organismal injury and abnormalities, endocrine system disorders and cancer. The thyroid tissue proteome in patients with BDG revealed a significant decrease in thyroglobulin along with dysregulation of glycolysis and an increase in prooxidant peroxidase enzymes. Dysregulation of metabolic pathways related to glycolysis, redox proteins, and the proteins associated with maintaining the cytoskeletal structure of the thyrocytes was also identified.