alexa Expression Profiling Of Inflammation-related Genes In Type-II Diabetic Individuals | 69065
ISSN: 2332-0737

Current Synthetic and Systems Biology
Open Access

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3rd International Conference on Systems and Synthetic Biology

M Kamran Azim, Humera Inayat and Faiz Muhammad
University of Karachi, Pakistan
Posters & Accepted Abstracts: Curr Synthetic Sys Biol
DOI: 10.4172/2332-0737-C1-009
Abstract
Type-II diabetes has been emerged as a growing health issue that has affected more than 170 million individuals worldwide. According to WHO, number of affected individuals by type-2 diabetes is expected to rise in Pakistan from 4.3 million in 1995 to 14.5 million in 2025, making Pakistan at number four among the top ten countries of the world affected by diabetes. It is well known that diabetes is associated with inflammation and altered immune response; however, the specific cellular and molecular mechanisms involved are not fully resolved. To investigate the mechanism that contributes to the pathology of disease, we performed gene expression profiling of white blood cells in subjects with and without type 2 diabetes mellitus, taking obesity factor into account as well. We categorized subjects according to their HBA1C and BMI level into three groups; subjects with HBA1C level >8.0 were included in group I, 8-10 in group II and >10 in group III. Thirty genes involved in inflammation related pathways including pro- and anti-inflammatory cytokines like CCR1, CCR2, CCR3, CCR4, CCR5, CCL15, CXCL10, CXCL11, CXCL12, TNFα, IL-4, IL-6, IL-10, IL-17A, AKT2 and TNFR1, etc., were profiled for gene expression using Real-Time PCR. Among genes tested, AKT2, CASP1, CASP5, CCR1, CCR2, IL-17A and PPARG genes were found to be upregulated, while CCR4, CXCL12, PPARGC1A and TNFα were downregulated in diabetic individuals in HBA1C-dependent manner. However, obese individuals showed a different pattern of expression than lean individuals. The identification of peripheral inflammatory cytokines associated with type-II diabetes as biomarkers has a potential for better diagnosis, optimized patient care and novel drug research.
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