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Genetic Variants Allegedly Linked to Antisocial Behaviour Are Equally Distributed Across Different Populations.

Stefania ZampattiMichele RagazzoCarlo FabrizioAndrea TermineGiulia CampoliValerio CaputoClaudia StrafellaRaffaella CascellaCarlo CaltagironeEmiliano Giardina
Published in: Journal of personalized medicine (2021)
Human behaviour is determined by a complex interaction of genetic and environmental factors. Several studies have demonstrated different associations between human behaviour and numerous genetic variants. In particular, allelic variants in SLC6A4, MAOA, DRD4, and DRD2 showed statistical associations with major depressive disorder, antisocial behaviour, schizophrenia, and bipolar disorder; BDNF polymorphic variants were associated with depressive, bipolar, and schizophrenia diseases, and TPH2 variants were found both in people with unipolar depression and in children with attention deficit-hyperactivity disorder (ADHD). Independent studies have failed to confirm polymorphic variants associated with criminal and aggressive behaviour. In the present study, a set of genetic variants involved in serotoninergic, dopaminergic, and neurobiological pathways were selected from those previously associated with criminal behaviour. The distribution of these genetic variants was compared across worldwide populations. While data on single polymorphic variants showed differential distribution across populations, these differences failed to be significant when a comprehensive analysis was conducted on the total number of published variants. The lack of reproducibility of the genetic association data published to date, the weakness of statistical associations, the heterogeneity of the phenotype, and the massive influence of the environment on human behaviour do not allow us to consider these genetic variants as undoubtedly associated with antisocial behaviour. Moreover, these data confirm the absence of ethnic predisposition to aggressive and criminal behaviour.
Keyphrases
  • bipolar disorder
  • major depressive disorder
  • copy number
  • endothelial cells
  • big data
  • gene expression
  • attention deficit hyperactivity disorder
  • dna methylation
  • machine learning
  • stress induced