Impact of fat mass and obesity-associated (FTO) gene variants on adult obesity and overweight: a comprehensive meta-analysis

Obesity has become one of the most common disorders in the world and causes a significant public health challenge. Genome-wide association studies (GWAS) have identified variants within the FTO gene as an important genetic risk factor for obesity. This study evaluates the associations between FTO gene variants and the risk of obesity in adults. In this study, we conducted a comprehensive search across PubMed, Scopus, and Web of Science, covering literature up to January 2025. Subsequently, a meta-analysis was conducted to calculate pooled genotype and allelic frequencies, using a random‑effects model to assess outcomes among three groups: obesity, overweight, and both obesity and overweight. Additionally, we analyzed FTO polymorphisms across different geographic regions. A total of 41 eligible studies were evaluated in this meta-analysis, comprising 34,206 participants from 27 countries. The analysis included 11 polymorphisms: rs1121980, rs1421085, rs1558902, rs17817449, rs3751812, rs7204609, rs8050136, rs9926289, rs9930506, rs9939609, and rs9939973. In the obesity group, the rs1421085 exhibited the strongest effect, with an odds ratio (OR) of 2.16 (95% CI: 1.58–2.95). In the investigation of both obesity and overweight, the rs9939609 showed a significant association, with an OR of 1.67 (95% CI: 1.41; 1.99) in the Homozygous model. Furthermore, in the evaluation of the FTO variant across different geographic regions, the rs1421085 demonstrated a consistent association in all genetic models, particularly in Asians, while the rs17817449 exhibited a strong effect within the American population. This meta-analysis provides strong evidence that FTO polymorphisms, particularly rs1421085 and rs9939609, are significantly associated with increased susceptibility to obesity in adults, while their impact on overweight is comparatively weaker. Moreover, the association between the FTO gene variants and obesity risk is stronger in certain genetic models. This review shed light on the importance of selecting a personalized strategy for obesity prevention and treatment, considering both individual genotypic variability and population specific differences. Such tailored approaches may enhance the effectiveness of efforts to reduce the global impact of obesity and its associated health complications. Not applicable.