RESUMO
Evidence suggests a remarkable shared genetic susceptibility between psychiatric disorders. However, sex-dependent differences have been less studied. We explored the contribution of schizophrenia (SCZ), bipolar disorder (BD) and major depressive disorder (MDD) polygenic scores (PGSs) on the risk for psychotic disorders and whether sex-dependent differences exist (CIBERSAM sample: 1826 patients and 1372 controls). All PGSs were significantly associated with psychosis. Sex-stratified analyses showed that the variance explained in psychotic disorders risk was significantly higher in males than in females for all PGSs. Our results confirm the shared genetic architecture across psychotic disorders and demonstrate sex-dependent differences in the vulnerability to psychotic disorders.
Assuntos
Transtorno Bipolar , Transtorno Depressivo Maior , Predisposição Genética para Doença , Herança Multifatorial , Transtornos Psicóticos , Esquizofrenia , Caracteres Sexuais , Humanos , Masculino , Feminino , Herança Multifatorial/genética , Transtornos Psicóticos/genética , Transtornos Psicóticos/epidemiologia , Predisposição Genética para Doença/genética , Adulto , Transtorno Bipolar/genética , Esquizofrenia/genética , Esquizofrenia/epidemiologia , Transtorno Depressivo Maior/genética , Transtorno Depressivo Maior/epidemiologia , Pessoa de Meia-IdadeRESUMO
Lithium (Li) is the first-line treatment for bipolar disorder (BD) even though only 30 % of BD patients are considered excellent responders. The mechanisms by which Li exerts its action are not clearly understood, but it has been suggested that specific epigenetic mechanisms, such as methylation processes, may play a role. In this regard, DNA methylation patterns can be used to estimate epigenetic age (EpiAge), which is accelerated in BD patients and reversed by Li treatment. Our first aim was to compare the DNA methylation profile in peripheral blood between BD patients categorized as excellent responders to Li (Ex-Rp) and non-responders (N-Rp). Secondly, EpiAge was estimated to detect differential age acceleration between the two groups. A total of 130 differentially methylated positions (DMPs) and 16 differentially methylated regions (DMRs) between Ex-Rp (n = 26) and N-Rp (n = 37) were identified (FDR adjusted p-value < 0.05). We found 122 genes mapping the DMPs and DMRs, nine of which (HOXB6, HOXB3, HOXB-AS3, TENM2, CACNA1B, ANK3, EEF2K, CYP1A1, and SORCS2) had previously been linked to Li response. We found genes related to the GSK3ß pathway to be highly represented. Using FUMA, we found enrichment in Gene Ontology Cell Component for the synapse. Gene network analysis highlighted functions related to the cell cycle, nervous system development and function, and gene expression. No significant differences in age acceleration were found between Ex-Rp and N-Rp for any of the epigenetic clocks analysed. Our findings indicate that a specific methylation pattern could determine the response to Li in BD patients. We also found that a significant portion of the differentially methylated genes are closely associated with the GSK3ß pathway, reinforcing the role of this system in Li response. Future longitudinal studies with larger samples will help to elucidate the epigenetic mechanisms underlying Li response.