Molecular Psychiatry最新文献

Genome-wide association studies (GWASs) of major depressive disorder (MDD) have recently achieved extremely large sample sizes and yielded substantial numbers of genome-wide significant loci. Because of the approach to ascertainment and assessment in many of these studies, some of these loci appear to be associated with dysphoria rather than with MDD, potentially decreasing the clinical relevance of the findings. An alternative approach to MDD GWAS is to focus on the most severe forms of MDD, with the hope that this will enrich for loci of larger effect, rendering their identification plausible, and providing potentially more clinically actionable findings. Here we review the genetics of severe depression by using clinical markers of severity including: age of onset, recurrence, degree of impairment, and treatment with ECT. There is evidence for increased family-based and Single Nucleotide Polymorphism (SNP)-based estimates of heritability in recurrent and early-onset illness as well as severe functional impariment. GWAS have been performed looking at severe forms of MDD and a few genome-wide loci have been identified. Several whole exome sequencing studies have also been performed, identifying associated rare variants. Although these findings have not yet been rigorously replicated, the elevated heritability seen in severe MDD phenotypes suggests the value of pursuing additional genome-wide interrogation of samples from this population. The challenge now is generating a cohort of adequate size with consistent phenotyping that will allow for careful and robust classifications and distinctions to be made. We are currently pursuing such a strategy in our 50-site worldwide Gen-ECT-ics consortium.

Background

Neuroimaging studies have provided valuable insights into the macroscale impacts of antidepressants on brain functions in patients with major depressive disorder. However, the findings of individual studies are inconsistent. Here, we aimed to provide a quantitative synthesis of the literature to identify convergence of the reported findings at both regional and network levels and to examine their associations with neurotransmitter systems.

Methods

Through a comprehensive search in PubMed and Scopus databases, we reviewed 5258 abstracts and identified 36 eligible functional neuroimaging studies on antidepressant effects in major depressive disorder. Activation likelihood estimation was used to investigate regional convergence of the reported foci of antidepressant effects, followed by functional decoding and connectivity mapping of the convergent clusters. Additionally, utilizing group-averaged data from the Human Connectome Project, we assessed convergent resting-state functional connectivity patterns of the reported foci. Next, we compared the convergent circuit with the circuits targeted by transcranial magnetic stimulation therapy. Last, we studied the association of regional and network-level convergence maps with selected neurotransmitter receptors/transporters maps.

Results

No regional convergence was found across foci of treatment-associated alterations in functional imaging. Subgroup analysis in the Treated > Untreated contrast revealed a convergent cluster in the left dorsolateral prefrontal cortex, which was associated with working memory and attention behavioral domains. Moreover, we found network-level convergence of the treatment-associated alterations in a circuit more prominent in the frontoparietal areas. This circuit was co-aligned with circuits targeted by “anti-subgenual” and “Beam F3” transcranial magnetic stimulation therapy. We observed no significant correlations between our meta-analytic findings with the maps of neurotransmitter receptors/transporters.

Conclusion

Our findings highlight the importance of the frontoparietal network and the left dorsolateral prefrontal cortex in the therapeutic effects of antidepressants, which may relate to their role in improving executive functions and emotional processing.

Understanding how sleep affects the glymphatic system and human brain networks is crucial for elucidating the neurophysiological mechanism underpinning aging-related memory declines. We analyzed a multimodal dataset collected through magnetic resonance imaging (MRI) and polysomnographic recording from 72 older adults. A proxy of the glymphatic functioning was obtained from the Diffusion Tensor Image Analysis along the Perivascular Space (DTI-ALPS) index. Structural and functional brain networks were constructed based on MRI data, and coupling between the two networks (SC-FC coupling) was also calculated. Correlation analyses revealed that DTI-ALPS was negatively correlated with sleep quality measures [e.g., Pittsburgh Sleep Quality Index (PSQI) and apnea-hypopnea index]. Regarding human brain networks, DTI-ALPS was associated with the strength of both functional connectivity (FC) and structural connectivity (SC) involving regions such as the middle temporal gyrus and parahippocampal gyrus, as well as with the SC-FC coupling of rich-club connections. Furthermore, we found that DTI-ALPS positively mediated the association between sleep quality and rich-club SC-FC coupling. The rich-club SC-FC coupling further mediated the association between DTI-ALPS and memory function in good sleepers but not in poor sleepers. The results suggest a disrupted glymphatic-brain relationship in poor sleepers, which underlies memory decline. Our findings add important evidence that sleep quality affects cognitive health through the underlying neural relationships and the interplay between the glymphatic system and multimodal brain networks.

Excessive alcohol consumption is a leading cause of preventable death worldwide. To improve understanding of neurobiological mechanisms associated with alcohol use disorder (AUD) in humans, we compared gene expression data from deceased individuals with and without AUD across two addiction-relevant brain regions: the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC). Bulk RNA-seq data from NAc and DLPFC (N ≥50 with AUD, ≥46 non-AUD) were analyzed for differential gene expression using modified negative binomial regression adjusting for technical and biological covariates. The region-level results were meta-analyzed with those from an independent dataset (N_NAc = 28 AUD, 29 non-AUD; N_PFC = 66 AUD, 77 non-AUD). We further tested for heritability enrichment of AUD-related phenotypes, gene co-expression networks, gene ontology enrichment, and drug repurposing. We identified 176 differentially expressed genes (DEGs; 12 in both regions, 78 in NAc only, 86 in DLPFC only) for AUD in our new dataset. After meta-analyzing with published data, we identified 476 AUD DEGs (25 in both regions, 29 in NAc only, 422 in PFC only). Of these DEGs, 17 were significant when looked up in GWAS of problematic alcohol use or drinks per week. Gene co-expression analysis showed both concordant and unique gene networks across brain regions. We also identified 29 and 436 drug compounds that target DEGs from our meta-analysis in NAc and PFC, respectively. This study identified robust AUD-associated DEGs, contributing novel neurobiological insights into AUD and highlighting genes targeted by known drug compounds, generating opportunity for drug repurposing to treat AUD.

Emerging evidence supports the therapeutic potential of cannabinoids in Alzheimer’s disease (AD), but the underlying mechanism upon how cannabinoids impact brain cognition and AD pathology remains unclear. Here we show that chronic cannabidiol (CBD) administration significantly mitigates cognitive deficiency and hippocampal β-amyloid (Aβ) pathology in 5×FAD mouse model of AD. CBD achieves its curative effect mainly through potentiating the function of inhibitory extrasynaptic glycine receptor (GlyR) in hippocampal dentate gyrus (DG). Based on the in vitro and in vivo electrophysiological recording and calcium imaging, CBD mediated anti-AD effects via GlyR are mainly accomplished by decreasing neuronal hyperactivity of granule cells in the DG of AD mice. Furthermore, the AAV-mediated ablation of DG GlyRα1, or the GlyRα1^S296A mutation that exclusively disrupts CBD binding, significantly intercepts the anti-AD effect of CBD. These findings suggest a GlyR dependent mechanism underlying the therapeutic potential of CBD in the treatment of AD.

Antidepressants are among the most extensively prescribed psychotropic drugs worldwide. Discontinuation induced withdrawal symptoms have been reported for almost all antidepressants. The incidence of antidepressant withdrawal syndrome (AWS) and other characteristics remain unknown. We searched the PubMed, Embase, PsycINFO, MEDLINE, CINAHL, and Cochrane Central Register of Controlled Trials databases from inception to December 31, 2023. Randomized double-blinded trials, longitudinal or cross-sectional studies that reported the incidence and other characteristics of antidepressant withdrawal symptoms were included. The pooled incidence of AWS was calculated by a random effects model. We included 35 studies, of which 2 studies just provided incidence of specific withdrawal symptoms, and 4 studies only described other characteristics. The pooled incidence of AWS from all available studies was 42.9%, from 11 RCTs was 44.4%, in studies in which the treatment duration was mostly 8-12 weeks, which usually appear within 2 weeks, and were generally measured for <4 weeks. The incidence in selective serotonin-norepinephrine reuptake inhibitors was the lowest (29.7%), followed by selective serotonin reuptake inhibitors (45.6%) and tricyclic antidepressants (59.7%), without significant differences (p = 0.221). Treatment duration showed a dose-response to the incidence of AWS (6-12 W: 35.1%, 12-24 W: 42.7%, >24 W: 51.4%). The half-life did not show such a simple dose-dependent relationship. The pooled estimate was robust regardless whether withdrawal symptoms were measured in RCTs or observational studies (including face-to-face and online survey studies). Tapering the dose reduced the incidence of AWS compared with abrupt stoppage (34.5% vs 42.5%), without a significant difference (p = 0.484). Risk factors for withdrawal symptoms included being female, younger, experiencing adverse effects early in treatment, taking higher doses or longer duration of medication, abrupt cessation of drugs, and those with a lower clearance of drugs or with serotonin 1A receptor gene variation. The findings suggest the incidence of AWS are common and some clinical characteristics and risk factors which can help clinicians identify who is at greater risk of experiencing AWS. Discontinuation studies on long-term antidepressant users with long follow-up periods are required in the future.

Obsessive compulsive disorder (OCD) is a highly prevalent disorder that causes serious disability. Available treatments leave 40% or more of people with OCD significantly symptomatic. There is an urgent need for novel therapeutic approaches. Mice that carry a homozygous deletion of the SAPAP3 gene (SAPAP3 KO) manifest a phenotype of excessive self-grooming, tic-like head-body twitches and anxiety. These behaviors closely resemble pathological self-grooming behaviors observed in humans in conditions that overlap with OCD. Following a preliminary report that the tryptaminergic psychedelic, psilocybin, may reduce symptoms in patients with OCD, we undertook a randomized controlled trial of psilocybin in 50 SAPAP3 KO mice (28 male, 22 female). Mice that fulfilled inclusion criteria were randomly assigned to a single intraperitoneal injection of psilocybin (4.4 mg/kg), psychedelic mushroom extract (encompassing the same psilocybin dose) or vehicle control and were evaluated after 2, 12, and 21 days by a rater blind to treatment allocation for grooming characteristics, head-body twitches, anxiety, and other behavioral features. Mice treated with vehicle (n = 18) manifested a 118.71 ± 95.96% increase in total self-grooming (the primary outcome measure) over the 21-day observation period. In contrast, total self-grooming decreased by 14.60 ± 17.90% in mice treated with psilocybin (n = 16) and by 19.20 ± 20.05% in mice treated with psychedelic mushroom extract (n = 16) (p = 0.001 for effect of time; p = 0.0001 for time × treatment interaction). Five mice were dropped from the vehicle group because they developed skin lesions; 4 from the psilocybin group and none from the psychedelic mushroom extract group. Secondary outcome measures such as head-body twitches and anxiety all showed a significant improvement over 21 days. Notably, in mice that responded to psilocybin (n = 12) and psychedelic mushroom extract (n = 13), the beneficial effect of a single treatment persisted up to 7 weeks. Mice initially treated with vehicle and non-responsive, showed a clear and lasting therapeutic response when treated with a single dose of psilocybin or psychedelic mushroom extract and followed for a further 3 weeks. While equivalent to psilocybin in overall effect on self-grooming, psychedelic mushroom extract showed superior effects in alleviating head-body twitches and anxiety. These findings strongly justify clinical trials of psilocybin in the treatment of OCD and further studies aimed at elucidating mechanisms that underlie the long-term effects to alleviate excessive self-grooming observed in this study. Prepared with BioRender ( https://www.biorender.com/ ).

Aberrant salience processing has been proposed as a pathophysiological mechanism underlying psychiatric symptoms in patients with schizophrenia. The gaze trajectories of individuals with schizophrenia have been reported to be abnormal when viewing an image, suggesting anomalous visual salience as one possible pathophysiological mechanism associated with psychiatric diseases. This study was designed to determine whether visual salience is affected in individuals with schizophrenia, and whether this abnormality is unique to patients with schizophrenia. We examined the gaze behaviors of 1012 participants recruited from seven institutes (550 healthy individuals and 238, 41, 50 and 133 individuals with schizophrenia, bipolar disorder, major depressive disorder and autism spectrum disorder, respectively) when they looked at stationary images as they liked, i.e., free-viewing condition. We used an established computational model of salience maps derived from low-level visual features to measure the degree to which the gaze trajectories of individuals were guided by visual salience. The analysis revealed that the saliency at the gaze of individuals with schizophrenia were higher than healthy individuals, suggesting that patients' gazes were guided more by low-level image salience. Among the low-level image features, orientation salience was most affected. Furthermore, a general linear model analysis of the data for the four psychiatric disorders revealed a significant effect of disease. This abnormal salience processing depended on the disease and was strongest in patients with schizophrenia, followed by patients with bipolar disorder, major depressive disorder, and autism spectrum disorder, suggesting a link between abnormalities in salience processing and strength/frequency for psychosis of these disorders.

Despite perinatal damage to the cerebellum being one of the highest risk factors for later being diagnosed with autism spectrum disorder (ASD), it is not yet clear how the cerebellum might influence the development of cerebral cortex and whether this co-developmental process is distinct between neurotypical and ASD children. Leveraging a large structural brain MRI dataset of neurotypical children and those diagnosed with ASD, we examined whether structural variation in cerebellar tissue across individuals was correlated with neocortical variation during development, including the thalamus as a coupling factor. We found that the thalamus plays a distinct role in moderating cerebro-cerebellar structural coordination in ASD. Notably, structural coupling between cerebellum, thalamus, and neocortex was strongest in younger childhood and waned by early adolescence, mirroring a previously undescribed trajectory of behavioral development between ASD and neurotypical children. Complementary functional connectivity analyses likewise revealed atypical connectivity between cerebellum and neocortex in ASD. This relationship was particularly prominent in a model of cerebellar structure predicting functional connectivity, where ASD and neurotypical children showed divergent patterns. Interestingly, these functional-structural relationships became more prominent with age, while structural effects were most prominent earlier in childhood, and showed significant lateralization. This pattern may suggest a developmental sequence where early uncoordinated structural growth amongst regions is followed by increasingly atypical functional synchronization. These findings provide multimodal evidence in the living brain for a cerebellar diaschisis model of autism, where both increased cerebellar-cerebral structural coupling and altered functional connectivity in cerebro-cerebellar pathways contribute to the ontogeny of this neurodevelopmental disorder.

Over 90% of drug candidates fail in clinical trials, while it takes 10-15 years and one billion US dollars to develop a single successful drug. Drug development is more challenging for psychiatric disorders, where disease comorbidity and complex symptom profiles obscure the identification of causal mechanisms for therapeutic intervention. One promising approach for determining more suitable drug candidates in clinical trials is integrating human genetic data into the selection process. Genome-wide association studies have identified thousands of replicable risk loci for psychiatric disorders, and sophisticated statistical tools are increasingly effective at using these data to pinpoint likely causal genes. These studies have also uncovered shared or pleiotropic genetic risk factors underlying comorbid psychiatric disorders. In this article, we argue that leveraging pleiotropic effects will provide opportunities to discover novel drug targets and identify more effective treatments for psychiatric disorders by targeting a common mechanism rather than treating each disease separately.