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Polymorphism of -308 G/A TNF- gene correlated with the concentration of TNF- and lipid profile in obese subject of Javanese population
Author(s) -
Hastuti Pramudji,
Chornelia Martantiningtyas Demes,
Karina Pharamita Dewi,
Tasmini,
Hamim Sadewa Ahmad
Publication year - 2017
Publication title -
african journal of biotechnology
Language(s) - English
Resource type - Journals
ISSN - 1684-5315
DOI - 10.5897/ajb2017.16150
Subject(s) - genotype , medicine , endocrinology , triglyceride , obesity , lipid profile , population , body mass index , odds ratio , biology , cholesterol , genetics , gene , environmental health
Tumor necrosis factor-α (TNF-α) is an adipokine produced in adipocytes which acts as a marker of inflammation. Increased levels of TNF-α have been associated with obesity and abnormal lipid profile. This study aimed to examine the relationship between polymorphism in -308 G/A TNF-α with concentrations of TNF-α, lipid profile and obesity in a Javanese population. The study consisted of 200 participants (98 controls and 102 obese) from a Javanese sample population. All subjects were measured for anthropometry, high-density lipoprotein (HDL)-C, low-density lipoprotein (LDL)-C, triglyceride, cholesterol, and TNF-α levels. Lipid profile were measured using the enzymatic colorimetric method, TNF-α level was measured with enzyme-linked immunosorbent assay (ELISA) and -308 G/A TNF-α polymorphism was detected using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP). Results showed that the GA genotype have LDL-C, triglyceride, cholesterol and TNF-α levels higher than the GG genotype. The findings demonstrate that 308 G/A TNF-α gene polymorphism plays a role in increasing the risk of obesity with odds ratio for A to G allele 1.96 (95% CI = 1.60-2.40) and odds ratio for GA to GG genotype 3.52 (95% CI = 2.84-4.36). TNF-α polymorphism (-308G/A) contributed to increased body mass index and elevated levels of LDL, triglyceride, cholesterol and TNF-α in obese Javanese population. This polymorphism may be used as a marker in the development of metabolic diseases and the identification of risk of obesity. Multifactorial analysis in the future may reveal basic genotypic differences between ethnic groups and demonstrate evidence for other environmental factors. Key words: Adipokines, lipid profile, obese, polymorphism, populations, tumor necrosis factor-α (TNF-α).

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