Growth differentiation factor-15 (GDF-15) is a stress responsive cytokine. It is highly expressed in cardiomyocytes, adipocytes, macrophages, endothelial cells, and vascular smooth muscle cells in normal and pathological condition. GDF-15 increases during tissue injury and inflammatory states and is associated with cardiometabolic risk. Increased GDF-15 levels are associated with cardiovascular diseases such as hypertrophy, heart failure, atherosclerosis, endothelial dysfunction, obesity, insulin resistance, diabetes, and chronic kidney diseases in diabetes. Increased GDF-15 level is linked with the progression and prognosis of the disease condition. Age, smoking, and environmental factors are other risk factors that may increase GDF-15 level. Most of the scientific studies reported that GDF-15 plays a protective role in different tissues. However, few reports show that the deficiency of GDF-15 is beneficial against vascular injury and inflammation. GDF-15 protects heart, adipose tissue, and endothelial cells by inhibiting JNK (c-Jun N-terminal kinase), Bad (Bcl-2-associated death promoter), and EGFR (epidermal growth factor receptor) and activating Smad, eNOS, PI3K, and AKT signaling pathways. The present review describes the different animal and clinical studies and patent updates of GDF-15 in diabetes and cardiovascular diseases. It is a challenge for the scientific community to use GDF-15 information for patient monitoring, clinical decision-making, and replacement of current treatment strategies for diabetic and cardiovascular diseases.

BackgroundWe have previously reported that increased glucose levels were associated with higher serum nitric oxide (NO) levels in fructose-fed insulin resistant rats. However, the relationship between hyperglycemia and serum NO level was not clear. Therefore, the present study was designed to find the association between hyperglycemia and serum NO levels in Type 2 diabetic (T2DM) patients and T2DM with cardiovascular complication.MethodsEndothelial cells (HUVEC) were treated with of D-glucose (10-100mM), and NO levels and NOS gene expression was measured. Hyperglycaemia was induced in Sprague-Dawley rats, and serum NO levels were measured after 8 weeks. For clinical evaluation, five groups of patients were recruited: Control (CT, n=48), Type 2 diabetes (T2DM, n=26), T2DM with hypertension (DMHT, n=46), Coronary artery diseases (CAD, n=29) and T2DM with coronary artery diseases (DMCD, n=38). NO (nitrite + nitrate) levels were measured from human serum.ResultsWe found a significant (p<0.05) and dose-dependent increase in NO levels in HUVEC cells after 4 hours of high glucose exposure. eNOS and iNOS gene expression was increased in HUVEC cells after different concentrations and time periods of glucose treatment. We also observed significant (149.1±25μM, p<0.01) increase in serum NO levels in hyperglycaemic rats compared to control (76.6±13.2μM). Serum NO level was significantly higher in T2DM (111.8 μM (81.7-122.4), p<0.001) and DMCD patients ((129.4 μM (121.2-143.5), p <0.001) but not in CAD patients (76.4 μM (70.5-87)), as compared to control (68.2 μM (56.4-82.3)). We found significantly lower NO levels (83.5 μM (60.5-122.9)) in subjects suffering from diabetes since more than 5 years, compared to subjects (115.3 μM (75.2-127.1), p<0.001) with less than 5 years.ConclusionIn conclusion, high NO levels were observed in South Indian diabetic patients. Higher glucose levels in serum might be responsible for activation of endothelial cells to enhance NO levels.

The study was aimed at finding the effect of garlic and resveratrol on loss of β-cells and diabetic complication in streptozotocin (STZ)-induced Type-I diabetic rats. Rats were injected with single dose STZ (50 mg/kg, i.p.) for induction of type 1 diabetes (Dia) and compared with control group. Rats from third (Dia+Gar), fourth (Dia+Resv), and fifth (Dia+Met) groups were fed raw garlic homogenate (250 mg/kg/day), resveratrol (25 mg/kg/day), and metformin (500 mg/kg/day) orally, respectively, for a period of 4 weeks. Diabetic group had decreased serum insulin and hydrogen sulfide levels along with increased blood glucose and glycated hemoglobin, triglyceride, uric acid, and nitric oxide levels. Significant (p < 0.05) increase in pancreatic and hepatic TBARS, conjugated dienes, nitric oxide, and AGE level and significant (p < 0.05) decrease in SOD, catalase, H2S, GSH level were observed in diabetic group. Administration of garlic, resveratrol, and metformin significantly (p < 0.05) normalized most of the altered metabolic and oxidative stress parameters as well as histopathological changes. Administration of garlic, resveratrol, and metformin in diabetic rat decreases pancreatic β-cell damage and hepatic injury. Our data concluded that administration of garlic showed more promising effect in terms of reducing oxidative stress and pathological changes when compared to resveratrol and metformin groups.

BackgroundCoronary artery disease (CAD) is the leading cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). The purpose of the present study was to discriminate the Indian CAD patients with or without T2DM by using multiple pathophysiological biomarkers.MethodsUsing sensitive multiplex protein assays, we assessed 46 protein markers including cytokines/chemokines, metabolic hormones, adipokines and apolipoproteins for evaluating different pathophysiological conditions of control, T2DM, CAD and T2DM with CAD patients (T2DM_CAD). Network analysis was performed to create protein-protein interaction networks by using significantly (p < 0.05) altered protein markers in each disease using STRING 10.5 database. We used two supervised analysis methods i.e., between class analysis (BCA) and principal component analysis (PCA) to reveals distinct biomarkers profiles. Further, random forest classification (RF) was used to classify the diseases by the panel of markers.ResultsOur two supervised analysis methods BCA and PCA revealed a distinct biomarker profiles and high degree of variability in the marker profiles for T2DM_CAD and CAD. Thereafter, the present study identified multiple potential biomarkers to differentiate T2DM, CAD, and T2DM_CAD patients based on their relative abundance in serum. RF classified T2DM based on the abundance patterns of nine markers i.e., IL-1β, GM-CSF, glucagon, PAI-I, rantes, IP-10, resistin, GIP and Apo-B; CAD by 14 markers i.e., resistin, PDGF-BB, PAI-1, lipocalin-2, leptin, IL-13, eotaxin, GM-CSF, Apo-E, ghrelin, adipsin, GIP, Apo-CII and IP-10; and T2DM _CAD by 12 markers i.e., insulin, resistin, PAI-1, adiponectin, lipocalin-2, GM-CSF, adipsin, leptin, Apo-AII, rantes, IL-6 and ghrelin with respect to the control subjects. Using network analysis, we have identified several cellular network proteins like PTPN1, AKT1, INSR, LEPR, IRS1, IRS2, IL1R2, IL6R, PCSK9 and MYD88, which are responsible for regulating inflammation, insulin resistance, and atherosclerosis.ConclusionWe have identified three distinct sets of serum markers for diabetes, CAD and diabetes associated with CAD in Indian patients using nonparametric-based machine learning approach. These multiple marker classifiers may be useful for monitoring progression from a healthy person to T2DM and T2DM to T2DM_CAD. However, these findings need to be further confirmed in the future studies with large number of samples.Electronic supplementary materialThe online version of this article (10.1186/s12967-018-1755-5) contains supplementary material, which is available to authorized users.