Laboratory of Biomedicine Research Unit, Faculty of Higher Studies Iztacala, National Autonomous University of Mexico, Mexico City, Mexico.
Laboratory of Molecular Oncology and Oxidative Stress, Section of Research & Graduate Studies, Superior School of Medicine, National Polytechnic Institute, Mexico City, Mexico.
Indian J Med Res. 2019 May;149(5):616-626. doi: 10.4103/ijmr.IJMR_1165_17.
BACKGROUND & OBJECTIVES: Obesity is a health problem that requires substantial efforts to understand the physiopathology of its various types and to determine therapeutic strategies for its treatment. The objective of this study was to characterize differences in the global gene expression profiles of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) between control patients (normal weight) and patients with obesity (IMC≥30) using microarrays.
Employing RNA isolated from SAT and VAT samples obtained from eight control and eight class I, II and III patients with obesity, the gene expression profiles were compared between SAT and VAT using microarrays and the findings were validated via real-time quantitative polymerase chain reaction.
A total of 327 and 488 genes were found to be differentially expressed in SAT and VAT, respectively (P≤0.05). Upregulation of PPAP2C, CYP4A11 and CYP17A1 genes was seen in the VAT of obese individuals.
INTERPRETATION & CONCLUSIONS: SAT and VAT exhibited significant differences in terms of the expression of specific genes. These genes might be related to obesity. These findings may be used to improve the clinical diagnosis of obesity and could be a tool leading to the proposal of new therapeutic strategies for the treatment of obesity.
肥胖是一个健康问题，需要大量的努力来理解其各种类型的病理生理学，并确定治疗肥胖的治疗策略。本研究的目的是使用微阵列来描述控制患者（正常体重）和肥胖患者（BMI≥30）的皮下脂肪组织（SAT）和内脏脂肪组织（VAT）之间的全球基因表达谱的差异。
采用从 8 名对照和 8 名 I 、 II 和 III 类肥胖患者的 SAT 和 VAT 样本中分离的 RNA ，使用微阵列比较 SAT 和 VAT 之间的基因表达谱，并通过实时定量聚合酶链反应验证发现。
在 SAT 和 VAT 中分别发现了 327 和 488 个差异表达的基因（P≤0.05）。在肥胖个体的 VAT 中观察到 PPAP2C、CYP4A11 和 CYP17A1 基因的上调。
SAT 和 VAT 在特定基因表达方面表现出显著差异。这些基因可能与肥胖有关。这些发现可用于改善肥胖的临床诊断，并可能成为提出治疗肥胖新治疗策略的工具。
