Document Type : Original Article
Authors
1
Environmental and Occupational Department, National Research Centre, Egypt.
2
Biochemistry department, faculty of science, Ain Shams university, Egypt.
3
Environmental and Occupational department, National Research Centre, Egypt.
4
Biochemistry department, National Research Centre, Egypt.
5
Biochemistry department,faculty of science , Ain shams university, Egypt.
Abstract
Obesity is a metabolic condition caused by a chronic disruption in energy balance, leading to the accumulation of excess body fat with subsequent detrimental health consequences. The global epidemic of obesity emphasizes the necessity of understanding the molecular mechanisms of energy regulation. This study aimed to evaluate the expression levels of energy metabolism-related genes, including SREBP-1c, AMPK, UCP-2, and FASN, in the adipose tissue of individuals with different grades of obesity and determine their potential as obesity biomarkers. Subcutaneous adipose tissue samples were collected from 20 non-obese controls and 70 obese individuals, categorised as obese class I (BMI = 30–34.9 kg/m2), obese class II (BMI = 35–39.9 kg/m2), and obese class III (BMI ≥ 40 kg/m2). mRNA was extracted from those samples, and the expression levels were measured using a real-time quantitative polymerase reaction. The study found that obese individuals have higher levels of FASN, SREBP-1c, UCP-2, and AMPK gene expression compared to non-obese individuals. These genes were expressed more in obese class II than in obese class I, but less in obese class III. Additionally, BMI and serum levels of total cholesterol, triglycerides, and LDL cholesterol were found to have a positive correlation with the expression of the studied genes, while HDL cholesterol showed a negative correlation. The investigated genes demonstrated excellent accuracy in discriminating between obese and non-obese individuals. The study's findings indicate that the genes examined may play a significant role in obesity and could be used as early predictors of obesity risk in humans. These results could be a step towards improving the clinical diagnosis of obesity and the development of new treatment strategies.
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