A Comprehensive Inter-Tissue Crosstalk Analysis Underlying Progression and Control of Obesity and Diabetes.

Obesity is a metabolic state associated with excess of positive energy balance. While adipose tissues are considered the major contributor for complications associated with obesity, they influence a variety of tissues and inflict significant metabolic and inflammatory alterations. Unfortunately, the communication network between different cell-types responsible for such systemic alterations has been largely unexplored. Here we study the inter-tissue crosstalk during progression and cure of obesity using multi-tissue gene expression data generated through microarray analysis. We used gene expression data sets from 10 different tissues from mice fed on high-fat-high-sugar diet (HFHSD) at various stages of disease development and applied a novel analysis algorithm to deduce the tissue crosstalk. We unravel a comprehensive network of inter-tissue crosstalk that emerges during progression of obesity leading to inflammation and insulin resistance. Many of the crosstalk involved interactions between well-known modulators of obesity and associated pathology like inflammation. We then used similar datasets from mice that in addition to HFHSD were also administered with a herbal concoction known to circumvent the effects of HFHSD in the diet induced model of obesity in mice. We propose, the analysis presented here could be applied to understand systemic details of several chronic diseases.

Molecular signatures for obesity and associated disorders identified through partial least square regression models.

BACKGROUND: Obesity is now a worldwide epidemic disease and poses a major risk for diet related diseases like type 2 diabetes, cardiovascular disease, stroke and fatty liver among others. In the present study we employed the murine model of diet-induced obesity to determine the early, tissue-specific, gene expression signatures that characterized progression to obesity and type 2 diabetes. RESULTS: We used the C57BL/6 J mouse which is known as a counterpart for diet-induced human diabetes and obesity model. Our initial experiments involved two groups of mice, one on normal diet (ND) and the other on high-fat and high-sucrose (HFHSD). The later were then further separated into subgroups that either received no additional treatment, or were treated with different doses of the Ayurvedic formulation KAL-1. At different time points (week3, week6, week9, week12, week15 and week18) eight different tissues were isolated from mice being fed on different diet compositions. These tissues were used to extract gene-expression data through microarray experiment. Simultaneously, we also measured different body parameters like body weight, blood Glucose level and cytokines profile (anti-inflammatory & pro-inflammatory) at each time point for all the groups. Using partial least square discriminant analysis (PLS-DA) method we identified gene-expression signatures that predict physiological parameters like blood glucose levels, body weight and the balance of pro- versus anti-inflammatory cytokines. The resulting models successfully predicted diet-induced changes in body weight and blood glucose levels, although the predictive power for cytokines profiles was relatively poor. In the former two instances, however, we could exploit the models to further extract the early gene-expression signatures that accurately predict the onset of diabetes and obesity. These extracted genes allowed definition of the regulatory network involved in progression of disease. CONCLUSION: We identified the early gene-expression signature for the onset of obesity and type 2 diabetes. Further analysis of this data suggests that some of these genes could be used as potential biomarkers for these two disease-states.

Immunomodulatory Role of an Ayurvedic Formulation on Imbalanced Immunometabolics during Inflammatory Responses of Obesity and Prediabetic Disease.

Kal-1 is a polyherbal decoction of seven different natural ingredients, traditionally used in controlling sugar levels, inflammatory conditions particularly regulating metabolic and immunoinflammatory balance which are the major factors involved in obesity and related diseases. In the present study, we aimed to investigate the effect of Kal-1 (an abbreviation derived from the procuring source) on diet-induced obesity and type II diabetes using C57BL/6J mice as a model. The present study was performed with two experimental groups involving obese and prediabetic mice as study animals. In one, the mice were fed on high-fat with increased sucrose diet, and different amounts (5, 20, and 75 µ L) of Kal-1 were administered with monitoring of disease progression over a period of 21 weeks whereas in the second group the mice were first put on the same diet for 21 weeks and then treated with the same amounts of Kal-1. A significant reduction in body weight, fat pads, fasting blood glucose levels, insulin levels, biochemical parameters, immunological parameters, and an array of pro- and anticytokines was observed in obese and diabetic mice plus Kal-1 than control (lean) mice fed on normal diet. In conclusion, Kal-1 has immunomodulatory potential for diet-induced obesity and associated metabolic disorders.

Extracting time-dependent obese-diabetic specific networks in hepatic proteome analysis.

Molecular mechanism governing biological processes leading to dietary obesity and diabetes are largely unknown. Here we study the liver proteome differentially expressed in a long-term high-fat and high-sucrose diet (HFHSD)-induced obesity and diabetes mouse model. Changes in mouse liver proteins were identified using iTRAQ, offline 2D LC (SCX and RP) and MALDI-TOF/TOF MS. A total of 1639 proteins was quantified during 3-15 weeks of disease progression and a pronounced proteome change was captured by incorporating the statistical analysis and network analysis. This underscores the importance of protein expression profiles involved in different biological processes that correlate well with the disease progression. The functionally important modules with key hub proteins such as Egfr, Pklr, Suclg1, and Pcx (Carbohydrate metabolism), Cyp2e1, Fasn, Acat1, and Hmgcs2 (Lipid metabolism and ketogenesis), and Gpx1, Mgst1, and Sod2 (ROS metabolism) can be linked to a physiological state of obesity and T2D. Multiple proteins involved in glucose catabolism and lipogenesis were down-regulated, whereas proteins involved in lipid peroxidation and oxidative phosphorylation were up-regulated. In conclusion, this proteomic study provides targets for future mechanistic and therapeutic studies in relation to development and prevention of obesity and Type 2 Diabetes.