Intronic Polymorphisms of the Fat Mass and Obesity-Associated (FTO) Gene in Association with Morbid Obesity in Southern Iran

Considering the important role of the genetic factors in the etiology of obesity, the genetic knowledge-based approach can be helpful to find individuals with the potential risk of obesity and obesity-related diseases. Evidence suggests the fat mass and obesity-associated (FTO) gene as the most important contributor to polygenic obesity. Although, different studies on various populations indicated the association of the FTO genetic variations (rs1421085 and rs17817449) and morbid obesity, to our knowledge, there is still no such study in the Iranian population.

The aim of this study was to evaluate and compare two FTO single nucleotide polymorphisms (SNPs) (rs1421085 and rs17817449) in morbidly obese patients and healthy normal controls in southern Iran. The potential association between these genetic variations and some demographic and clinical characteristics of obese patients were also investigated.

A total of 90 morbidly obese patients and 90 healthy normal controls were included in this study. Genotyping of blood samples was performed using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. SPSS software was applied for statistical analysis of data.

Both mentioned SNPs were significantly associated with an increased risk of obesity. No significant association was found between these two FTO genetic variations and demographic and clinical characteristics of obese patients including sex, age, family history of obesity, BMI, type 2 diabetes, hypothyroidism, physical activity, amount of stress, consumption of fatty/frying foods, sweetmeat, fruit and vegetables, cigarette and hookah smoking, alcohol consumption, fasting blood glucose (FBS), triglyceride (TG), total cholesterol, HDL, and LDL.

It seems that FTOSNPs (rs1421085, rs17817449)may increase the risk of morbid obesity in southern Iran. Further investigations in the different populations with larger sample sizes are required to consider these genetic variations as potential biomarkers for obesity