Epigenetics of suicidal behavior

Suicide is the second leading cause of death among young people and therefore being a serious global problem worldwide. The study of genetic and epigenetic factors in the development of suicidal behavior plays an important role in the development of advanced methods of diagnosis and treatment of this pathology. The role of hereditary factors in the development of suicidal behavior is estimated at 30–55 %, with a pronounced comorbidity with other psychopathologies. The study of genetic liability to suicidal behavior is based on molecular-genetic methods including association and linkage analyses, chip gene expression arrays, and genome-wide association studies. Published data identified multiple genes including those involved in the functioning of serotonergic (SLC6A4, TPH, 5-HT1A), hypothalamic-pituitary-adrenal systems (FKBP5) and polyamines (SAT and OATL1) associated with suicidal behavior. However, the diversity of interacting genetic loci complicates the interpretation of the development of a complex phenotype of pathology and prevents the association from being detected. To solve this problem and interpret the missing relationship between the environment and the genome, promising results were obtained from a study of epigenetic factors, which affected the expression of a number of candidate genes involved in brain functioning in suicidal behavior. The analysis of a brain obtained from suicide victims, representing a unique tool for the analysis of modified genomic processes, revealed a wide range of reprogramming patterns of DNA methylation in promoters of the genes of polyamine (OAZ1, OAZ2, AMD1, ARG2, SKA2), serotonergic (SLC6A4) and GABAergic (GABRA1) systems, HPA-axis (GR, NR3C1), tyrosine kinase (TrkB) receptors, brain-derived neurotrophic factor (BDNF). The role of histone modifications in distinct genes (Cx30, Cx43, TrkB.T1) and the expression of specific long noncoding RNAs and microRNAs in the development of suicidal behavior, which is promising for the development of diagnostic algorithms and target therapy, is discussed