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Epigenetic Analysis of the Dopamine Transporter Gene DAT1 with a Focus on Personality Traits in Athletes.

Kinga Humińska-LisowskaKrzysztof ChmielowiecAleksandra StrońskaJolanta ChmielowiecAleksandra SuchaneckaJolanta MasiakMonika Michałowska-SawczynAgnieszka BorońPaweł CieszczykAnna Grzywacz
Published in: International journal of molecular sciences (2023)
Human phenotypes (traits) are determined by the selective use of a person's unique genotype (DNA sequence), following exposure to environmental stimuli, such as exercise. Inducing profound changes in epigenetics may be an underlying factor of the beneficial effects of exercise. This study aimed to investigate the association between methylation in the promoter region of the DAT1 gene and personality traits measured by the NEO-FFI questionnaire in a group of athletes. The study group included 163 athletes, and the control group consisted of 232 non-athletes. The obtained results show several significant differences between the studied groups of subjects. The Extraversion scale and the Conscientiousness scale results of the NEO-FFI are significantly higher in the group of athletes compared to controls. The total methylation and the number of methylated islands in the promoter region of the DAT1 gene are higher in the study group. Pearson's linear correlation between the total methylation, the number of methylated islands and the NEO-FFI shows significant results for the Extraversion and Agreeability scales. The total methylation and the number of methylated islands in the promoter region of the DAT1 gene are higher in the study group. Pearson's linear correlation between the total methylation, the number of methylated islands and the NEO-FFI shows significant results for the Extraversion and Agreeability scales. Our analysis of the methylation status of individual CpG sites revealed a new direction of research into the biological aspects of regulating dopamine release and personality traits in people practicing sports.
Keyphrases
  • dna methylation
  • genome wide
  • gene expression
  • transcription factor
  • risk assessment
  • endothelial cells
  • high intensity
  • single cell
  • resistance training
  • cross sectional
  • neural network