Antisocial behaviour in youth has serious consequences at individual and societal level. Adolescence is also a critical period for the emergence of prodromal psychosis symptoms. Their co-occurrence may aggravate aggression and lead to severe adverse outcomes. Common genetic risk for psychosis, antisocial behaviour, and substance use has been suggested, but the putatively shared genetic architecture is unknown, and evidence in youth is limited. Here we examined whether common genetic liability indexed by polygenic risk scores (PRSs) relates to these complex traits in the Norwegian Mother, Father and Child Cohort Study (MoBa; n = 18960). Antisocial psychopathology was operationalised as three complementary dimensions: conduct-disorder (CD) traits, oppositional-defiant disorder (ODD) traits, and psychopathy traits. We first quantified phenotypic correlations between psychotic-like experiences (PLEs) and the antisocial dimensions. We then evaluated PRS-phenotype associations (single-PRS and joint multivariable models) using PRSs for antisocial behaviour (PRSASB) and schizophrenia (PRSSCZ), in addition to PRS for alcohol use disorder (PRSAUD). We found phenotypic correlations between antisocial traits and PLEs (rs=0.13-0.34, p < 0.0001). This overlap was reflected at the genetic level, as we found associations between PRSASB and PLEs (p = 0.0004). The associations between PRSSCZ and antisocial traits were present for CD (p = 0.005) and ODD (p = 0.003) traits. Both PLEs and antisocial traits were associated with PRSAUD. Patterns persisted in mutually adjusted models. These findings indicate cross-trait associations between polygenic liability for SCZ, ASB, AUD and adolescent PLEs and antisocial dimensions in the general youth population, consistent with partially shared common genetic influences. Future studies should further delineate underlying biological mechanisms.
N. Tesli, P. Jahołkowski, J. Rokicki et al.· European Child and Adolescen...· 0 citations
Background Premenstrual disorder (PMD) and postpartum depression (PPD) have a strong phenotypic link and echo women’s hormone fluctuations. Yet, the extent to which they may be cross-inherited remains poorly understood. Methods Using the nationwide cohort of 907,841 women who born 1950-2007 and gave birth during 2001-2021 in Sweden, we estimated the cumulative incidence functions-based heritability and genetic correlation for PMD and PPD. We also analyzed genome-wide association study (GWAS) summary statistics from the largest European-ancestry cohorts for PMD (17,511 cases and 54,786 controls) and PPD (16,145 cases and 46,609 controls) using linkage disequilibrium score regression (LDSC). Fixed-effect cross-trait meta-analysis and imputed transcriptome-wide association analyses (TWAS) were conducted to identify shared loci and gene-tissue associations. Results The register-based heritability was 0.35 (95% CI: 0.29-0.41) for PMD and 0.31 (95% CI: 0.23-0.37) for PPD, with a positive genetic correlation between these disorders (rg = 0.47, 95% CI: 0.25–0.69). LDSC also showed a positive genetic correlation between PMD and PPD (rg = 0.66, SE = 0.10, P = 1.014×10−10), indicating sizable shared heritable influences. Cross-trait meta-analysis identified two novel genome-wide significant loci jointly associated with PMD and PPD, mapping to an intronic region of PCDH9 and the 3’ untranslated region of KCTD16. The KCTD16 locus implicates GABAB–mediated inhibitory signaling in both disorders. Consistent with this, TWAS revealed a hippocampus regulatory signal for KCTD16, with no detectable trend effects in other brain regions or peripheral tissues. Beyond the lead loci, TWAS suggested that the shared risk variants may partially act through genetically regulated gene expression across brain, endocrine and immune-related tissues. Conclusions Together, these findings provide the first evidence for sizable genetic overlap between PMD and PPD and highlight novel and convergent biological mechanisms underlying the abnormal brain response of some women to gonadal hormone fluctuations.
Susu Qu, Kejia Hu, J. Guintivano et al.· Research Square· 0 citations
