Molecular Psychiatry最新文献

Glycine is an obligatory co-agonist at excitatory NMDA receptors in the brain, especially in the dentate gyrus, which has been postulated to be crucial for the development of psychotic associations and memories with psychotic content. Drugs modulating glycine levels are in clinical development for improving cognition in schizophrenia. However, the functional relevance of the regulation of glycine metabolism by endogenous enzymes is unclear. Using a chromosome-engineered allelic series in mice, we report that a triplication of the gene encoding the glycine-catabolizing enzyme glycine decarboxylase (GLDC) - as found on a small supernumerary marker chromosome in patients with psychosis - reduces extracellular glycine levels as determined by optical fluorescence resonance energy transfer (FRET) in dentate gyrus (DG) and suppresses long-term potentiation (LTP) in mPP-DG synapses but not in CA3-CA1 synapses, reduces the activity of biochemical pathways implicated in schizophrenia and mitochondrial bioenergetics, and displays deficits in schizophrenia-like behaviors which are in part known to be dependent on the activity of the dentate gyrus, e.g., prepulse inhibition, startle habituation, latent inhibition, working memory, sociability and social preference. Our results demonstrate that Gldc negatively regulates long-term synaptic plasticity in the dentate gyrus in mice, suggesting that an increase in GLDC copy number possibly contributes to the development of psychosis in humans.

The role of genetic testing in the domain of neurodevelopmental and psychiatric disorders (NPDs) is gradually changing from providing etiological explanation for the presence of NPD phenotypes to also identifying young individuals at high risk of developing NPDs before their clinical manifestation. In clinical practice, the latter implies a shift towards the availability of individual genetic information predicting a certain liability to develop an NPD (e.g., autism, intellectual disability, psychosis etc.). The shift from mostly a posteriori explanation to increasingly a priori risk prediction is the by-product of the systematic implementation of whole exome or genome sequencing as part of routine diagnostic work-ups during the neonatal and prenatal periods. This rapid uptake of genetic testing early in development has far-reaching consequences for psychiatry: Whereas until recently individuals would come to medical attention because of signs of abnormal developmental and/or behavioral symptoms, increasingly, individuals are presented based on genetic liability for NPD outcomes before NPD symptoms emerge. This novel clinical scenario, while challenging, also creates opportunities for research on prevention interventions and precision medicine approaches. Here, we review why optimization of individual risk prediction is a key prerequisite for precision medicine in the sphere of NPDs, as well as the technological and statistical methods required to achieve this ambition.

Objective markers of pathophysiological processes underlying lifetime depression and mania/hypomania risk can provide biologically informed targets for novel interventions to help prevent the onset of affective disorders in individuals with subsyndromal symptoms. Greater activity within and functional connectivity (FC) between the central executive network (CEN), supporting emotional regulation (ER) subcomponent processes such as working memory (WM), the default mode network (DMN), supporting self-related information processing, and the salience network (SN), is thought to interfere with cognitive functioning and predispose to depressive disorders. Using an emotional n-back paradigm designed to examine WM and ER capacity, we examined in young adults: (1) relationships among activity and FC in these networks and lifetime depression and mania/hypomania risk; (2) the extent to which these relationships were specific to lifetime depression risk versus lifetime mania/hypomania risk; (3) whether findings in a first, Discovery sample n = 101, 63 female, age = 23.85 (2.9) could be replicated in a two independent Test samples of young adults: Test sample 1: n = 90, 60 female, age = 21.7 (2.0); Test sample 2: n = 96, 65 female, age = 21.6 (2.1). The Mood Spectrum Self-Report (MOODS-SR-L) assessed lifetime mania/hypomania risk and depression risk. We showed significant clusters of activity to each contrast in similar locations in the anatomic mask in each Test sample as in the Discovery sample, and, using extracted mean BOLD signal from these clusters as IVs, we showed similar patterns of IV-DV relationships in each Test sample as in the Discovery sample. Specifically, in the Discovery sample, greater DMN activity during WM was associated with greater lifetime depression risk. This finding was specific to depression and replicated in both independent samples (all ps<0.05 qFDR). Greater CEN activity during ER was associated with increased lifetime depression risk and lifetime mania/hypomania risk in all three samples (all ps< 0.05 qFDR). These replicated findings provide promising objective, neural markers to better identify, and guide and monitor early interventions for, depression and mania/hypomania risk in young adults.

Effortful tasks are generally experienced as costly, but the value of work varies greatly across individuals and populations. While most mental health conditions are characterized by amotivation and effort avoidance, individuals with anorexia nervosa (AN) persistently engage in effortful behaviors that most people find unrewarding (food restriction, excessive exercise). Current models of AN differentially attribute such extreme weight-control behavior to altered reward responding and exaggerated cognitive control. In a novel test of these theoretical accounts, we employed an established cognitive effort discounting paradigm in combination with fMRI in young acutely underweight female patients with AN (n = 48) and age-matched healthy controls (HC; n = 48). Contrary to the hypothesis that individuals with AN would experience cognitive effort (operationalized as N-back task performance) as less costly than HC participants, groups did not differ in the subjective value (SV) of discounted rewards or in SV-related activation of brain regions involved in reward valuation. Rather, all group differences in both behavior (superior N-back performance in AN and associated effort ratings) and fMRI activation (increased SV-related frontoparietal activation during decision-making in AN even for easier choices) were more indicative of increased control. These findings suggest that while effort discounting may be relatively intact in AN, effort investment is high both when performing demanding tasks and during effort-based decision-making; highlighting cognitive overcontrol as an important therapeutic target. Future research should establish whether exaggerated control during effort-based decision-making persists after weight-recovery and explore learning the value of effort in AN with tasks involving disorder-relevant effort demands and rewards.

Melancholia has been proposed as a qualitatively distinct depressive subtype associated with a characteristic symptom profile (psychomotor retardation, profound anhedonia) and a better response to biological therapies. Existing work has suggested that individuals with melancholia are blunted in their display of positive emotions and differ in their neural response to emotionally evocative stimuli. Here, we unify these brain and behavioural findings amongst a carefully phenotyped group of seventy depressed participants, drawn from an established Australian database (the Australian Genetics of Depression Study) and further enriched for melancholia (high ratings of psychomotor retardation and anhedonia). Melancholic (n = 30) or non-melancholic status (n = 40) was defined using a semi-structured interview (the Sydney Melancholia Prototype Index). Complex facial expressions were captured whilst participants watched a movie clip of a comedian and classified using a machine learning algorithm. Subsequently, the dynamics of sequential changes in brain activity were modelled during the viewing of an emotionally evocative movie in the MRI scanner. We found a quantitative reduction in positive facial expressivity amongst participants with melancholia, combined with differences in the synchronous expression of brain states during positive epochs of the movie. In non-melancholic depression, the display of positive affect was inversely related to the activity of cerebellar regions implicated in the processing of affect. However, this relationship was reduced in those with a melancholic phenotype. Our multimodal findings show differences in evaluative and motoric domains between melancholic and non-melancholic depression through engagement in ecologically valid tasks that evoke positive emotion. These findings provide new markers to stratify depression and an opportunity to support the development of targeted interventions.

The aim of this study was to provide evidence-based recommendations regarding the efficacy, safety, and tolerability of currently used pharmacological treatments for adults with acute bipolar mania. To achieve this, we conducted a systematic review and network meta-analysis (NMA) using R software and related packages. We searched primary clinical databases until February 2023 for reports of randomized controlled trials of drug treatments and adjunctive therapies for adults with acute bipolar mania, with outcomes including efficacy (mean change from baseline to endpoint in mania rating scores), safety (clinically significant adverse events from baseline to end of treatment), and tolerability (the proportion of patients who completed the whole trial to the planned endpoint). A total of 113 studies were included in our analysis, in which 23,491 participants (50.38% males; mean age = 38.6 years; mean study duration = 3.39 weeks; mean manic baseline score = 29.37) were randomly allocated to one of 51 monotherapies, adjunctive treatments, or placebo. Our results showed that tamoxifen (mean difference, -22.31 [-25.97, -18.63], N = 2, n1 = 43, n2 = 39) and tamoxifen+ lithium or valproate (LIT/VAL) (-16.37 [-22.55, -10.25], N = 1, n1 = 20, n2 = 20) had the best and second-best clinical efficacy in adults with acute bipolar mania over the placebo. Furthermore, olanzapine, paliperidone, quetiapine, ziprasidone, risperidone, divalproex, and haloperidol were significantly better tolerated than placebo. Combination therapies of antipsychotics and LIT/VAL appeared to be more effective than their corresponding monotherapies. While pharmacotherapies were associated with specific common adverse events, we found no evidence of increased incidence of headache or depression events compared to the placebo. Overall, our NMAs provided important insights into the effectiveness, safety, and tolerability of pharmacological treatments for acute bipolar mania and can help guide treatment decisions for clinicians.

Recent studies have provided promising evidence that neuroimaging data can predict treatment outcomes for patients with major depressive disorder (MDD). As most of these studies had small sample sizes, a meta-analysis is warranted to identify the most robust findings and imaging modalities, and to compare predictive outcomes obtained in magnetic resonance imaging (MRI) and studies using clinical and demographic features. We conducted a literature search from database inception to July 22, 2023, to identify studies using pretreatment clinical or brain MRI features to predict treatment outcomes in patients with MDD. Two meta-analyses were conducted on clinical and MRI studies, respectively. The meta-regression was employed to explore the effects of covariates and compare the predictive performance between clinical and MRI groups, as well as across MRI modalities and intervention subgroups. Meta-analysis of 13 clinical studies yielded an area under the curve (AUC) of 0.73, while in 44 MRI studies, the AUC was 0.89. MRI studies showed a higher sensitivity than clinical studies (0.78 vs. 0.62, Z = 3.42, P = 0.001). In MRI studies, resting-state functional MRI (rsfMRI) exhibited a higher specificity than task-based fMRI (tbfMRI) (0.79 vs. 0.69, Z = -2.86, P = 0.004). No significant differences in predictive performance were found between structural and functional MRI, nor between different interventions. Of note, predictive MRI features for treatment outcomes in studies using antidepressants were predominantly located in the limbic and default mode networks, while studies of electroconvulsive therapy (ECT) were restricted mainly to the limbic network. Our findings suggest a promise for pretreatment brain MRI features to predict MDD treatment outcomes, outperforming clinical features. While tasks in tbfMRI studies differed, those studies overall had less predictive utility than rsfMRI data. Overlapping but distinct network-level measures predicted antidepressants and ECT outcomes. Future studies are needed to predict outcomes using multiple MRI features, and to clarify whether imaging features predict outcomes generally or differ depending on treatments.

Emerging fMRI methods quantifying brain dynamics present an opportunity to capture how fluctuations in brain responses give rise to individual variations in affective and motivation states. Although the experience and regulation of affective states affect psychopathology, their underlying time-varying brain responses remain unclear. Here, we present a novel framework to identify network states matched to an affective experience and examine how the dynamic engagement of these network states contributes to this experience. We apply this framework to investigate network state dynamics underlying basal craving, an affective experience with important clinical implications. In a transdiagnostic sample of healthy controls and individuals diagnosed with or at risk for craving-related disorders (total N = 252), we utilized connectome-based predictive modeling (CPM) to identify brain networks predictive of basal craving. An edge-centric timeseries approach was leveraged to quantify the moment-to-moment engagement of the craving-positive and craving-negative subnetworks during independent scan runs. We found that dynamic markers of network engagement, namely more persistence in a craving-positive network state and less dwelling in a craving-negative network state, characterized individuals with higher craving. We replicated the latter results in a separate dataset, incorporating distinct participants (N = 173) and experimental stimuli. The associations between basal craving and network state dynamics were consistently observed even when craving-predictive networks were defined in the replication dataset. These robust findings suggest that network state dynamics underpin individual differences in basal craving. Our framework additionally presents a new avenue to explore how the moment-to-moment engagement of behaviorally meaningful network states supports our affective experiences.

Genomic correlates of impulsivity have been identified in several genome-wide association studies (GWAS) using cross-sectional designs, but no studies have investigated the molecular genetic correlates of impulsivity phenotypes using longitudinally constructed traits. In 3860 unrelated European participants in the Avon Longitudinal Study of Parents and Children (ALSPAC), we constructed longitudinal phenotypes for delay discounting and impulsive personality traits (as measured by the UPPS-P impulsive behavior scales) via assessment at ages 24, 26, and 28. We conducted GWASs of impulsivity using both cross-sectional and longitudinal phenotypes, estimated heritability and their phenotypic and genetic correlations, and evaluated their association with recently-developed polygenic risk scores (PRSs) for the impulsivity indicators themselves and also related psychiatric conditions. Latent growth curve modeling revealed a stable intercept over time for all impulsivity phenotypes. High genetic correlation of cross-sectional measures over time suggested a stable genetic component for delay discounting (r_g = 0.53–0.99) and sensation seeking (r_g = 0.99). Heritability estimates of the stable longitudinal phenotypes substantively improved as compared to their cross-sectional counterparts, revealing a significant SNP-heritability for delay discounting (0.22; p = 0.03) and sensation seeking (0.35; p = 0.0007). Consistent with previous reports, GWAS and gene-based analyses revealed associations between specific longitudinal impulsivity indicators and CADM2 and NCAM1 genes. The PRSs for the impulsivity indicators and disorders related to self-regulation were also significantly associated with longitudinal impulsivity traits. Finally, we validated the associations between longitudinal impulsivity phenotypes and their PRSs in an independent 13-wave longitudinal study (n = 1019) and the benefit of longitudinal phenotypes in simulation studies. In this first longitudinal genetic study of impulsivity traits, the results revealed stable genomic correlates of delay discounting and sensation seeking over time and further validated the utility of recently-developed PRSs, both in relation to the observed traits and in connecting them to psychiatric disorders. More generally, these findings support using latent intercepts as novel longitudinal phenotypes to boost signal for heritability and genomic correlates of mechanisms contributing to psychiatric disease liability.