Type 2 diabetes (T2D) is a complex disease with an elusive link between its molecular aetiology and clinical presentation. Although, the role of visceral adipose tissue in insulin-resistance and T2D is known, limited information is available on the role of peripheral-subcutaneous adipose tissue especially in Asian Indians. In this microarray-based study of diabetic and normal glucose tolerant Asian Indians, we generated the transcriptome of their thigh adipose tissue and analyzed differentially expressed genes (DEGs) using weighted gene co-expression network analysis; further we identified perturbed pathways implicated by these DEGs in relevant co-expression modules. We also attempted to link these pathways with known aspects of T2D pathophysiology in terms of their association with some of their intermediate traits, namely; adipocyte size, HOMA-B, HOMA-R, Hb1Ac, insulin, glucose-level, TNF-α, IL-6, VLDLs, LDLs, HDLs, and NEFAs. It was observed that several modules of co-expressed genes show an association with diabetes and some of its intermediate phenotypic traits mentioned above. Therefore, these findings suggest a role of peripheral subcutaneous adipose tissue in the pathophsiology of T2D in Asian Indians. Additionally, our study indicated that the peripheral subcutaneous adipose tissue in diabetics shows pathologic changes characterized by adipocyte hypertrophy and up-regulation of inflammation-related pathways.

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Background: Mycobacterium ulcerans is the fundamental agent of the third most common Mycobacterial disease known as Buruli Ulcer (BU). It is an infection of the skin and soft tissue affecting the human population worldwide. Presently, the vaccine is not available against BU. Objective: This study aimed to investigate the vaccine potential of virulence proteins of M. ulcerans computationally. Methods: Chromosome encoded virulence proteins of Mycobacterium ulcerans strain Agy99 were selected, which were available at the VFDB database. These proteins were analyzed for their subcellular localization, antigenicity, and human non-homology analysis. Ten virulence factors were finally chosen and analyzed for further study. Three-dimensional structures for selected proteins were predicted using Phyre2. B cell and T cell epitope analysis was done using methods available at Immune Epitope Database and Analysis Resource. Antigenicity, allergenicity, and toxicity analysis were also done to predict epitopes. Molecular docking analysis was done for T cell epitopes, those showing overlap with B cell epitopes. Results: Selected virulence proteins were predicted with B cell and T cell epitopes. Some of the selected proteins were found to be already reported as antigenic in other mycobacteria. Some of the predicted epitopes also had similarities with experimentally identified epitopes of M. ulcerans and M. tuberculosis which further supported our predictions. Conclusion : In-silico approach used for the vaccine candidate identification predicted some virulence proteins that could be proved important in future vaccination strategies against this chronic disease. Predicted epitopes require further experimental validation for their potential use as peptide vaccines.

The prevalence of Type 2 Diabetes has reached an epidemic proportion particularly in south Asian countries. We have earlier shown that the anatomical fat distribution, termed ‘thin fat phenotype’ in this population indeed plays a major role for their T2D-predisposition it is indeed the sick fat or adiposopathy, which is the root cause of metabolic syndrome and diabetes and affects both—peripheral, as well as visceral adipose tissue compartments. In present study, we have attempted to unravel the altered regulatory mechanisms at the level of transcription factors, and miRNAs those may likely accounts to T2D pathophysiology in femoral subcutaneous adipose tissue. We prioritized transcription factors and protein kinases as likely upstream regulators of obtained differentially expressed genes in this RNA-seq study. An inferred network of these upstream regulators was then derived and the role of TFs and miRNAs in T2D pathophysiology was explored. In conclusions, this RNS-Seq study finds that peripheral subcutaneous adipose tissue among Asian Indians show pathology characterized by altered lipid, glucose and protein metabolism, adipogenesis defect and inflammation. A network of regulatory transcription factors, protein kinases and microRNAs have been imputed which converge on the process of adipogenesis. As the majority of these genes also showed altered expression in diabetics and some of them are also circulatory, therefore they deserve further investigation for potential clinical diagnostic and therapeutic applications.

We performed a systematic analysis of genes implicated in thigh subcutaneous adipose tissue of Asian Indian Type 2 Diabetes Mellitus (AIT2DM) and created a phenome-interactome network. This analysis was performed on 60 subjects specific to limb thigh fat by integrating phenotypic traits and similarity scores associated with AIT2DM. Using a phenotypic attribute, a contextual neighbor was identified across all the traits, viz. body mass index (BMI) statistics, adipocyte size, lipid parameters, homeostatic model assessment- insulin resistance (HOMA-IR), HOMA-ß. In this work, we have attempted to characterize transcription signatures using the phenome-interactome maps where each of the traits under study including the intermediary phenotypes has a distinct set of genes forming the hubs. Furthermore, we have identified various clinical, biochemical, and radiological parameters which show significant correlation with distinct hubs. We observed a number of novel pathways and genes including those that are non-coding RNAs implicated in AIT2DM.We showed that they appear to be associated with pathways, viz. tyrosine kinase JAK2, NOTCH thereby recruiting signaling molecules such as STAT5 and Src family kinases on the cell surface regulated them and our analyses comprising significant hubs suggest that thigh subcutaneous adipose tissue plays a role in pathophysiology of AIT2DM.