Molecular Psychiatry最新文献

Patients with borderline personality disorder (BPD) are over-represented in psychiatric services, and their suicide mortality is markedly higher than that of the general population. This network meta-analysis evaluated and compared the efficacy and safety of pharmacological treatments for symptoms of BPD. A systematic search of Medline®, Web of Science®, and Google Scholar® identified randomised clinical trials comparing active drugs with placebo or another agent between 15 January and 12 February 2024. Standardised mean differences were estimated using random-effects pairwise and network meta-analyses. The level of evidence (LoE) for significant drug-placebo comparisons was rated using GRADE NMA guidance. Thirty-five trials including 2551 participants assessed 26 treatments against placebo: 18 had low, five moderate, and 12 high risk of bias. Topiramate (200-250 mg/day, 8-10 weeks), lamotrigine (50-200 mg/day, 8 weeks), and aripiprazole (15 mg/day, 8 weeks) most effectively reduced hostility, aggressiveness, and anger, and improved anger control. Carbamazepine (200-1200 mg/ day, 6 weeks) and asenapine (5-10 mg/day, 12 weeks) improved impulsivity and emotional dysregulation, respectively. Topiramate, lamotrigine, and aripiprazole demonstrated high, moderate, and moderate LoE for hostility and anger reduction. Carbamazepine and asenapine demonstrated low and very low LoE for impulsivity and emotional dysregulation. Conversely, alprazolam, methylphenidate, haloperidol, and valproate had only low-certainty evidence in unselected BPD samples and should not be prioritised. Prescription should be limited to specific, individualised indications, such as panic, comorbid ADHD, or transient psychotic features, following cautious clinical appraisal.

Post-traumatic stress disorder (PTSD) persists when stress biases memory systems-broadening threat engrams, weakening context-appropriate inhibition, and rendering extinction fragile. Integrating preclinical and human evidence, we argue that these liabilities are tractable within a circuit-informed framework that aligns behavioral procedures with the biology of fear memory. Extinction can be stabilized by preferentially engaging hippocampal-prefrontal-amygdala pathways and their thalamic coordinators; targeted training and sleep-based reactivation strengthen top-down control over intrusions and sharpen discrimination between safety and threat. Brief, prediction-error-rich retrieval opens a reconsolidation window through which maladaptive content can be updated; pairing this window with state-aligned neuromodulation or phase-specific psychedelic pharmacology biases plasticity toward safety without relying on nonspecific anxiolysis. Framed this way, integrating extinction reinforcement with voluntary memory control and reconsolidation editing offers a coherent route to more durable relief from traumatic memories in PTSD.

Interleukin-17 (IL-17) is a pleiotropic cytokine produced mainly by peripheral T helper 17 cells. Yet, the brain functions of IL-17 derived from central nervous cells remain poorly understood. Here, we find an aberrant IL-17A signaling in the cerebellum of Fmr1-KO mice, a well-established genetic model for autism spectrum disorder (ASD). Cerebellar IL-17A, derived exclusively from microglia, is essential for the regulation of social behaviors by maintaining neuronal excitability and selectively suppressing inhibitory neurotransmission of Purkinje cells (PCs) in the cerebellar Crus I, a brain region critically involved in social cognition. Specific downregulation of IL-17 receptor-mediated signaling in cerebellar PCs recapitulates ASD-like social deficits and repetitive behaviors. Notably, both direct administration of IL-17A and induction of IL-17A release from cerebellar microglia by poly(I:C) effectively restore PC excitability and ameliorate ASD-like symptoms. The findings uncover an indispensable role of microglia-derived IL-17A for cerebellar social processing and suggest potential therapeutic strategies targeting IL-17A signaling for ASD.

While modern diagnostic classification systems aim to nosologically structure psychiatric disorders, they poorly align with the genetic, neurobiological, and environmental heterogeneity observed in these disorders. This limitation has complicated the search for clinically useful biomarkers for diagnosis and treatment. Recent work on genetic and environmental contributions to mental health indicates that this heterogeneity stems from differential involvement of diverse biological pathways within and across diagnostic clusters. This complex interplay presents a many-to-many mapping problem in psychiatry, where distinct pathophysiological processes can lead to similar clinical symptoms. Here, we argue that disentangling these biological mechanisms requires development of process-specific biomarkers that could replace non-specific neuroimaging markers widely used in neuropsychiatric research. We further propose a framework for biomarker research that adopts a biologically informed perspective integrating the interactions between genes and the environment to address this problem. Such a multidimensional framework holds promise for developing biology-driven models of psychiatric disorders, enabling treatment strategies tailored to individual pathophysiology.

While a growing number of studies have highlighted the relevance of core and bridge symptoms as potential intervention targets by following the network approach to  psychopathology, their findings have remained primarily descriptive or retrospective. To date, no study has prospectively tested whether interventions tailored to person-specific symptom networks can improve clinical outcomes compared to standard interventions. To address this gap, we conducted an exploratory investigation to examine whether a network-driven, person-specific sequencing of modules yields signals of added benefit compared with a standardized sequence. Accordingly, this proof-of-concept pilot randomized controlled trial recruited participants aged 18-29 years with depressive symptoms, and the Mini International Neuropsychiatric Interview was administered in person to screen for psychiatric conditions. The study compared a digital intervention program, consisting of up to 9 sessions plus one psychoeducation session, sequenced according to core symptoms identified through network analysis using 10-day ecological momentary assessment (EMA) collected beforehand, with a standardized fixed-sequence intervention. Depressive symptoms were measured using the, which includes one item assessing thoughts of self-harm or suicide, at post-intervention, and at 1- and 3-months follow-up. In total, 62 participants were randomly assigned to one of two intervention groups in a 1:1 ratio, with 31 participants in each group. An intent-to-treat analysis revealed significant improvements in depressive symptoms over time in both groups (p_fdr < 0.01). Both groups showed substantial reductions in depression scores from baseline to post-intervention, with large effect sizes (d = 1.24 for the personalized group and d = 1.15 for the standardized group). These improvements were maintained at the 1-month follow-up (d = 0.86 for the personalized group and d = 1.09 for the standardized group) and the 3-month follow-up (d = 1.05 for the personalized group and d = 0.89 for the standardized group). However, the group × time interaction was near zero and imprecisely estimated (β = -0.01, 95% CI - 0.96-0.94; p = 0.987), indicating that, in this pilot, between-arm differences were small and statistically non-significant. Non-significant results are interpreted as inconclusive rather than evidencing equivalence. These findings underscore the need for further trials to identify the specific conditions under which personalized, network-informed approaches might yield advantages over standard interventions. TRIAL REGISTRATION: The study was pre-registered with the Chinese Clinical Trial Registry (ChiCTR2300078568).

Observational studies have reported alteration of circulating metabolites across several psychiatric conditions, but these studies cannot resolve causal relationships. Emerging evidence suggests a genetic relationship exists between these traits requiring further investigation to identify clinically actionable biology. Here, we used the largest genome-wide association studies available to investigate genetic correlation and causal relationships between 10 psychiatric conditions and 249 circulating metabolites. This revealed 1,100 significantly correlated trait pairings, involving fatty acids, lipoproteins and other metabolites, with evidence for causal effects on the liability for major depressive disorder, post-traumatic stress disorder and anorexia nervosa. Notably, the most robust association was a putative causal effect of high-density lipoprotein properties on anorexia nervosa. We also observed significant relationships between metabolic traits and cortical thickness and surface area, as well as evidence of shared gene-level common variant associations amongst 23 metabolite-psychiatric pairings, converging in pathways with metabolic and neuronal function. These findings highlight specific metabolites as potential biomarkers and therapeutic targets in the clinical management of psychiatric disorders.

Angelman syndrome (AS) is a neurodevelopmental disorder caused by UBE3A loss. In humans, UBE3A generates three isoforms that localize to distinct subcellular compartments-one mainly nuclear and two cytoplasmic. The nuclear and most highly expressed cytoplasmic UBE3A isoform are highly conserved in mice, whereas the cytoplasmic human isoform accounting for just ~1% of total UBE3A has no mouse counterpart. Loss of the nuclear-enriched UBE3A isoform causes AS and behavioral deficits in mice; no specific contribution of the predominant cytoplasmic UBE3A isoform has yet been identified. Because the nuclear-enriched isoform constitutes ~80% of total UBE3A protein, it is unclear if its outsized phenotypic impact upon deletion is due to a loss of nuclear UBE3A function or simply a dramatic reduction in overall UBE3A levels. If the former, overexpression of the cytoplasmic UBE3A isoform would be unable to rescue AS phenotypes. To test this, we developed a mouse model that overexpresses the cytoplasmic UBE3A isoform (mIso2-OE) and crossed it with an AS mouse model to yield wildtype (WT), mIso2-OE, AS, and AS/mIso2-OE mice, the latter of which lacked the endogenous nuclear UBE3A isoform (mIso3) in neurons. Unexpectedly, we found that overexpression of the cytoplasmic UBE3A isoform alone rescued most tested AS-related behavioral deficits, except for kindling-induced epileptogenesis or seizure-linked perineuronal net (PNN) accumulation in AS mice. Thus, while many AS phenotypes may be caused by isoform non-selective reductions in UBE3A levels, AS-associated epilepsies appear linked to isoform-selective nuclear UBE3A loss. This information is expected to inform AS gene therapy studies.