Biological Psychiatry最新文献

Background: Bipolar disorder typically features episodes of mania and depression, frequently accompanied by psychosis. While progress has been made in understanding the genetics of depression and psychosis, mania remains underexplored, limiting opportunities for targeted interventions and a fuller understanding of bipolar disorder's heterogeneity.

Methods: We used genomic structural equation modeling to subtract the genetic effects of major depressive disorder (MDD) from bipolar disorder, allowing us to isolate a genetic component specific to mania. This approach used genome-wide association study (GWAS) summary statistics from large-scale studies of European ancestry, including 576,327 effective samples for MDD and 27,196 cases with 43,792 controls for bipolar disorder.

Results: The structural equation model revealed significant loadings for "mania" (0.90, p < .001) and "depression" (0.43, p < .001) factors, with mania and MDD explaining 81.5% and 18.5% of the variance in bipolar disorder, respectively. Seventy-one independent significant single nucleotide polymorphisms associated with mania were identified, spread in 37 genomic loci. Mania exhibited distinct genetic correlations compared with bipolar disorder, including significantly different correlations with psychiatric phenotypes, tiredness (r_g = -0.13 vs. -0.17), subjective well-being (r_g = 0.08 vs. -0.13), and educational attainment (r_g = 0.26 vs. 0.14). Pathway analysis highlighted a significant enrichment in the voltage-gated calcium channel activity pathway.

Conclusions: These findings enhance understanding of bipolar disorder's genetic architecture, offering a more bipolar disorder-specific GWAS. Identifying mania-specific loci may inform earlier diagnosis, personalized treatment approaches, and the development of targeted therapies.

Background: Negative reactivity (NR) and behavioral inhibition (BI), temperamental traits characterized by novelty-evoked distress and avoidance respectively, represent risk markers for anxiety. However, not all infants with NR and BI develop anxiety. Pathways from infant temperament to anxiety remain underspecified. This study tests the hypothesis that heightened neural sensitivity to unexpected sensory stimuli in infancy moderates risk for anxiety.

Methods: Data from the Temperament Over Time Study (N=291) were utilized. Infants completed laboratory-based assessments of NR at 4 months (M) and BI at 2-3 years. BI was also assessed using parent-report. At 9 and 36M, electroencephalography was collected during a passive three-stimulus auditory oddball task, and the mismatch response (MMR) and novelty P3 were quantified. Adolescent anxiety was measured using parent- and self-reports, and clinical interviews at 13 and 15 years. Structural equational modeling analyses were applied to examine whether infants' MMR or novelty P3 at 9 and 36M modulate relations between NR, BI, and adolescent anxiety.

Results: The MMR at 9M moderated the relation between NR and BI, and the MMR at 36M moderated the relation between BI and 13-year anxiety. In both cases, a more negative MMR was associated with elevated risk. This association was not present for attention problems or externalizing outcomes. Additional exploratory analyses showed that the novelty P3 mediated pathways from NR to social anxiety.

Conclusions: Individual differences in the infant's neural response to unexpected stimuli relate to temperamental risk for anxiety.

Family history (FH) of major depression is a well-replicated risk factor for developing the disorder. Studying individuals who may be at high familial risk but are symptom free may allow us to better distinguish mechanisms predisposing individuals to depression from those that arise from having the disorder. Neuroimaging studies, employing such high-risk designs, have suggested several cortical and subcortical regions that may contribute to depression susceptibility; however, specificity, timing of mechanisms, and long-term clinical implications remain unclear. As developing de novo cohorts to address these questions would be resource demanding, we sought to identify existing, longitudinal cohorts that could be used to examine the effects of family history on brain imaging outcomes rigorously and cost-effectively; to determine how family history was assessed in these cohorts; and to summarize their major findings published to date. A structured PUBMED search identified 25 longitudinal cohorts (13 countries), each containing ≥1,000 participants, direct- or informant-based family history, psychiatric measures, and ≥1 MRI collection. Across publications from these cohorts, subcortical (particularly striatum, amygdala) and cortical (anterior cingulate, prefrontal) regions most frequently showed alterations in association with familial risk. However, current evidence for whether these regions predicted psychopathology was limited and should be examined in future studies as offspring in these cohorts age. This comprehensive review should also serve as a resource for further analyses of existing data from cohorts with family history and neuroimaging data in the context of depression and other disorders.