The Role of the 5-HTTLPR Gene Variation of the SLC6A4 Serotonergic System in the Development of Addictive Disorders: A Narrative Review.

BACKGROUND

Addictive disorders remain a global problem, affecting health, society and the economy. The etiopathogenesis of addictions, which have a multifactorial nature, is poorly understood, making it difficult to develop personalized treatment approaches. Of particular interest is the gene, which regulates serotonergic transmission. The 5-HTTLPR variation of this gene is associated with the risk of addictions, but the data are contradictory due to the heterogeneity of clinical manifestations and pleiotropic effects of the gene. Integration of genetic, environmental and neurobiological factors into multidimensional models is becoming relevant.

AIM

The aim of this study is to assess the role of 5-HTTLPR variations in the gene of the serotonergic system in the development of addictive disorders.

METHODS

The manuscripts were searched in the MEDLINE and eLIBRARY.RU databases using the keywords in Russian and English: "SLC6A4", "5-HTTLPR", "addictive disorders", "pharmacogenetics", "serotonin", "antidepressants", "ethnic differences". After eliminating duplicates and a two-stage screening (by titles/annotations and full-text analysis) of the 1,561 discovered papers, the final review included 41 publications that meet the stated inclusion criteria.

RESULTS

The S-allele of 5-HTTLPR is associated with an increased risk of addictions and comorbid affective disorders, but its role is ambiguous due to the heterogeneity of symptoms. Ethnic differences have been identified: the S-allele predominates (70.6-80.9%) in Asian populations, the L-allele in Europeans (38.5-66.7%). Unique neurobiological markers for S-allele carriers have not been established, and the pleiotropic effects of are also observed in other mental disorders, which reduces its specificity for addictions.

CONCLUSION

The inconsistency of the data on 5-HTTLPR highlights the need to take into account ethnic specificity and develop multivariate models that integrate genetic, environmental and clinical factors. This will improve risk prediction (development of addictions), personalization of therapy and the effectiveness of pharmacogenetic approaches, reducing the likelihood of adverse reactions.