Drug induced liver toxicity is a serious health complication leading to high mortality rates and post marketing withdrawal of drugs. Although considered to be the gold standard biomarkers; aspartate aminotransferase, alanine aminotransferase, total bilirubin and alkaline phosphatase have been found to have specificities beyond liver, therefore more specific and predictive markers for the detection of antitubercular drug mediated liver damage are required. Unfortunately, the effectiveness of currently used first line antitubercular drugs namely isoniazid, rifampicin, pyrazinamide is often accompanied with liver injury, impeding the cure of patients. Keeping in view, the prognostic and diagnostic applications of microRNAs in various diseases, we tried to assess the importance of microRNAs 122 and 192 in antitubercular drug associated liver injuries. The study included subjects having tuberculosis of any type with antitubercular drug induced liver injury; naïve or newly diagnosed tuberculosis patients, tuberculosis patients on drugs not having toxicity and healthy controls. Observations from this study revealed that expression levels of miR-122 and miR-192 were significantly decreased in the serum of antitubercular drug induced liver injury patients only. Therefore, these microRNAs or the pathways associated with them can be used as a tool to predict or cure antitubercular drug associated liver injury in future.
Background Diabetes is an important risk factor for developing tuberculosis. This association leads to exacerbation of tuberculosis symptoms and delayed treatment of both the diseases. Molecular mechanism and biomarkers/drug targets related to copathogenesis of tuberculosis and diabetes are still poorly understood. In this study, proteomics based 2D-MALDI/MS approach was employed to identify host signature proteins which are altered during copathogenesis of tuberculosis and diabetes. Methods Comparative proteome of human peripheral blood mononuclear cells (PBMCs) from healthy controls, tuberculosis and diabetes patients in comparison to comorbid diabetes and tuberculosis patients was analyzed. Gel based proteomics approach followed by in gel trypsin digestion and peptide identification by mass spectrometry was used for signature protein identification. Results Total of 18 protein spots with differential expression in tuberculosis and diabetes copathogenesis (TBDM) patients in comparison to other groups were identified. These proteins belonged to four functional categories i.e. structural, cell cycle/growth regulation, signaling and intermediary metabolism. These include Vimentin, tubulin beta chain protein, Actin related protein 2/3 complex subunit 2, coffilin 1 (Structural), PDZ LIM domain protein, Rho-GDP dissociation inhibitor, Ras related protein Rab (signaling), superoxide dismutase, dCTPpyrophosphatase 1, Transcription initiation factor TFIID subunit 12, three isoforms of Peptidylprolylcis-trans isomerase A, SH3 domain containing protein (metabolism), three isoforms of Protein S100A9 and S100A8 (cell cycle progression/growth regulation). Conclusion Proteins identified to be differentially expressed in TBDM patient can act as potent biomarkers and as predictors for copathogenesis of tuberculosis and diabetes.
18Background: Diabetes is an important risk factor for developing tuberculosis. This association 19 leads to exacerbation of tuberculosis symptoms and delayed treatment of both the diseases. 20 Molecular mechanism and biomarkers/drug targets related to copathogenesis of tuberculosis and 2 21 diabetes, however, still remains to be poorly understood. In this study, proteomics based 2D-22 MALDI/MS approach was employed to identify host signature proteins which are altered during 23 copathogenesis of tuberculosis and diabetes. 24 Methods: Comparative proteome of human peripheral blood mononuclear cells (PBMCs) from 25 healthy controls, tuberculosis and diabetes patients in comparison to comorbid diabetes and 26 tuberculosis patients was analyzed. Gel based proteomics approach followed by in gel trypsin 27 digestion and peptide identification by mass spectrometry was used for signature protein 28 identification. 29 Results: Total of 18 protein spots with differential expression in TBDM patients in comparison 30 to other groups were identified. These include Vimentin, tubulin beta chain protein, superoxide 31 dismutase, Actin related protein 2/3 complex subunit 2, PDZ LIM domain protein, Rho-GDP 32 dissociation inhibitor, Ras related protein Rab, dCTPpyrophosphatase 1, Transcription initiation 33 factor TFIID subunit 12, coffilin 1, three isoforms of Peptidylprolylcis-trans isomerase A, three 34 isoforms of Protein S100A9, Protein S100A8 and SH3 domain containing protein. These 35 proteins belonged to four functional categories i.e. structural, cell cycle/growth regulation, 36 signaling and intermediary metabolism.40 42 10million fresh TB cases has been reported worldwide (1). Despite extensive research on the 3 43 biology of M. tuberculosis, exact mechanism of infection and immune evasion still remains 44 elusive. Copathogenesis with HIV and diabetes further complicates the tuberculosis control 45 measures. Although HIV infection is the topmost risk factor for development of active 46 tuberculosis but population attributable risk of diabetes is more than that of HIV infection (2, 3) 47 as diabetes is known to triple the risk of developing active tuberculosis (4). As diabetes is 48 associated with various immunological dysfunctions, diabetic patients fall prey to other co-49 infections like tuberculosis, melioidosis and other conventional hyperglycemia related 50 complications like various cardiovascular disorders, retinopathy, nephropathy and many more. 51 Diabetes mellitus affected 425 million individuals worldwide in 2017 and is predicted to reach 52 629 million by 2045, the time at which 80% of diabetics will be residents of economically 53 challenged countries where active tuberculosis (TB) prevails (5, 6). Countries with highest 54 burden of diabetes are also in the list of WHO's tuberculosis high burden countries and India and 55China for example, have first two positions for the copathogenesis of TB and diabetes (7, 8). The 56 epidemiological data for association between TB and DM is increasing significantly...
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