Objective: This study aimed to analyze the PITX2 gene using two exons, 4 and 5, in individuals with atrial fibrillation (AF) in order to assess, through in silico prediction, the potential impact of the mutations identified.

Methods: Forty-six (46) patients with AF and twenty (20) controls were included. Sequencing of the PITX2 gene identified several variants. These were evaluated using bioinformatic functional prediction tools to determine their likely consequences on the structure and activity of the PITX2 protein.

Results: The variants identified are not classified as pathogenic according to reference databases and current classification criteria. However, most of the mutations were found to affect protein function and DNA binding, suggesting a possible role in modulating the molecular mechanisms involved in FA.

Conclusion: Although the identified mutations are not associated with known pathogenicity, their functional effects on PITX2 could contribute to individual susceptibility to atrial fibrillation. These results highlight the value of in silico prediction approaches for exploring the functional variability of candidate genes and better understanding the genetic complexity of AF.