As a leading cause of adolescent death, suicidal and self-injurious related behaviors (SSIRBs) is a devastating global health problem, particularly among patients with psychiatric disorders (PDs). Previous studies have shown that multiple interventions can alleviate symptoms and reduce risks. This review aimed to provide a systematic summary of interventions (i.e., medication, physical therapy, psychosocial therapy) for the treatment of SSIRBs among Chinese adolescents with PDs. From inception to September 17, 2023, twelve databases (PubMed, CINAHL, ScienceDirect, PsycINFO, EMBASE, Cochrane Library, Clinical Trial, Web of Science, CEPS, SinoMed, Wanfang and CNKI) were searched. We qualitatively and quantitatively synthesized the included studies. Standardized mean differences (SMDs), risk ratios and their 95% confidence intervals (CIs) used the Der Simonian and Laird random-effects model. Fifty-two studies covering 3709 eligible participants were included. Overall, the commonly used interventions targeting SSIRBs and negative feelings in PDs adolescents with SSIRBs included psychosocial therapy (e.g., cognitive behavioral therapy), medication (e.g., antidepressants), and physiotherapy (e.g., repetitive transcranial magnetic stimulation). Importantly, quetiapine fumarate in combination with sodium valproate (SV) had positive effects on reducing self-injury behaviors score [SMD: -2.466 (95% CI: -3.305, -1.628), I = 88.36%], depression [SMD: -1.587 (95% CI: -2.505, -0.670), I = 90.45%], anxiety [SMD: -1.925 (95% CI: -2.700, -1.150), I = 85.23%], impulsivity [SMD: -2.439 (95% CI: -2.748, -2.094), I = 0%], as well as its safety in comparison with SV alone. No significant difference of adverse reactions was found by low-dose QF (P > 0.05). This review systematically outlined the primary characteristics, safety and effectiveness of interventions for Chinese PDs adolescents with SSIRBs, which could serve as valuable evidence for guidelines aiming to formulate recommendations.

The heterogeneity of Major Depressive Disorder (MDD) has been increasingly recognized, challenging traditional symptom-based diagnostics and the development of mechanism-targeted therapies. This study aims to identify neuroimaging-based MDD subtypes and dissect their predominant biological characteristics using multi-omics data. A total of 807 participants were included in this study, comprising 327 individuals with MDD and 480 healthy controls (HC). The amplitude of low-frequency fluctuations (ALFF), a functional neuroimaging feature, was extracted for each participant and used to identify MDD subtypes through machine learning clustering. Multi-omics data, including profiles of genetic, epigenetics, metabolomics, and pro-inflammatory cytokines, were obtained. Comparative analyses of multi-omics data were conducted between each MDD subtype and HC to explore the molecular underpinnings involved in each subtype. We identified three neuroimaging-based MDD subtypes, each characterized by unique ALFF pattern alterations compared to HC. Multi-omics analysis showed a strong genetic predisposition for Subtype 1, primarily enriched in neuronal development and synaptic regulation pathways. This subtype also exhibited the most severe depressive symptoms and cognitive decline compared to the other subtypes. Subtype 2 is characterized by immuno-inflammation dysregulation, supported by elevated IL-1 beta levels, altered epigenetic inflammatory measures, and differential metabolites correlated with IL-1 beta levels. No significant biological markers were identified for Subtype 3. Our results identify neuroimaging-based MDD subtypes and delineate the distinct biological features of each subtype. This provides a proof of concept for mechanism-targeted therapy in MDD, highlighting the importance of personalized treatment approaches based on neurobiological and molecular profiles.

Associations between birth weight and cortical structural phenotypes have been detected; however, the understanding is incomprehensive, and the potential biological bases are not well defined. Leveraging data from genome-wide association studies, we investigated the associations and the shared transcriptomic, proteomic and cellular bases of birth weight and 13 cortical structural phenotypes. Mendelian randomization analyses were performed to examine associations between birth weight and cortical structure. Downstream transcriptome-wide association study (TWAS), proteome-wide association study (PWAS) and summary-based Mendelian randomization (SMR) analyses were utilized to identify the shared cis-regulated gene expressions and proteins. Finally, cell-type expression-specific integration for complex traits (CELLECT) analyses were conducted to explore the enriched cell types. The Mendelian randomization analyses found positive associations between birth weight and global cortical folding index, intrinsic curvature index, local gyrification index, surface area and volume. Downstream transcriptomic-level TWAS and SMR identified three gene expressions both linked to birth weight and at least one cortical structural phenotype (CNNM2, RABGAP1 and CENPW). Parallel PWAS and SMR analyses at the proteomic level identified four proteins linked to both phenotypes (CNNM2, RAB7L1, RAB5B and PPA2), of which CNNM2 was replicated. CELLECT analyses revealed brain cell types enriched in birth weight, including pericytes, inhibitory GABAergic neurons and cerebrovascular cells. These findings support the importance of early life growth to cortical structure, and suggest underlying transcriptomic, proteomic and cellular bases. These results provide intriguing targets for further research into the mechanisms of cortical development.

Sensory symptoms are highly prevalent amongst autistic individuals and are now considered in the diagnostic criteria. Whilst evidence suggests a genetic relationship between autism and sensory symptoms, sensory symptoms are neither universal within autism nor unique to autism. One explanation for the heterogeneity within autism and commonality across conditions with respect to sensory symptoms, is that it is alexithymia (a condition associated with difficulties identifying and describing one's own emotions) that has a genetic relationship with sensory symptoms, and that alexithymia commonly co-occurs with autism and with several other conditions. Using parent-reports of symptoms in a sample of adolescent twins, we sought to examine the genetic association between autism, alexithymia and sensory symptoms. Results showed that the genetic correlation between autism and sensory symptoms was not significant after controlling for alexithymia. In contrast, after controlling for variance in alexithymia explained by autism, the genetic correlation between alexithymia and sensory symptoms was significant (and the proportion of variance explained by genetic factors remained consistent after controlling for autism). These results suggest that 1) alexithymia and sensory symptoms share aetiology that is not accounted for by their association with autism and 2) that the genetic association between sensory symptoms and autism may be, in part or wholly, a product of alexithymia. Future research should seek to examine the contribution of alexithymia to sensory symptoms across other conditions.

Impaired social interaction and repetitive behavior are key features observed in individuals with autism spectrum disorder (ASD). SHANK3 is a high-confidence ASD risk gene that encodes an abundant scaffolding protein in the postsynaptic density. In wild-type (WT) domestic dogs, maternal behaviors such as licking and nursing (largely milk feeding) of puppies are most commonly observed. To address whether SHANK3 plays a role in social behaviors especially maternal behaviors, we analyzed Shank3 mutant dogs generated by CRISPR/Cas9 methodology. We found that Shank3 mutant dams exhibited a fewer and shorter licking behavior, as well as reduced nursing frequency when compared with WT dams. Additionally, a significant decrease in blood oxytocin (OXT) concentration was detected in Shank3 mutant dams. We thus conducted a vehicle-controlled experiment to examine whether a two-week intranasal OXT treatment, initiated on the 8 postpartum day, could rescue the maternal licking deficits in Shank3 mutant dams. We found that the decreased licking behavior in Shank3 mutant dams was significantly attenuated both acutely and chronically by OXT treatment. The rescue effect of OXT implicates an oxytocinergic contribution to the maternal defects in Shank3 mutant dams, suggesting a potential therapeutic strategy for SHANK3-associated ASD.

Loss of glutamatergic terminals is hypothesised to contribute to excitation-inhibition imbalance in schizophrenia, supported by evidence that the normal positive association between glutamate concentrations and synaptic terminal density is not found in patients with chronic schizophrenia. However, it is unknown whether the relationship between synaptic terminal density and glutamate levels is altered early in the course of illness. To address this, we investigated [C]UCB-J distribution volume ratio (DVR) and glutamatergic markers in healthy volunteers (HV) and in antipsychotic-naïve/free patients with schizophrenia (SCZ) recruited from first-episode psychosis services. Forty volunteers (HV n = 19, SCZ n = 21) underwent [C]UCB-J positron emission tomography and proton magnetic resonance spectroscopy (H-MRS) imaging in the anterior cingulate cortex (ACC) and left hippocampus to index [C]UCB-J DVR and creatine-scaled glutamate (Glu/Cr) and glutamate in combination with glutamine (Glx/Cr). In the HV but not SCZ group, [C]UCB-J DVR was significantly positively associated with Glu/Cr (Spearman's rho = 0.55, p = 0.02) and Glx/Cr (Spearman's rho = 0.73, p = 0.0004) in the ACC, and with Glu/Cr in the left hippocampus (Spearman's rho = 0.77, p = 0.0001). DVR was significantly lower in the ACC in the SCZ group compared to the HV group (Kolmogorov-Smirnov Z = 1.44, p = 0.03). Together, these findings indicate that the normal relationship between levels of a synaptic terminal density marker and levels of glutamate is disrupted early in the course of schizophrenia. This is consistent with the hypothesis that there is loss of glutamatergic terminals at illness onset.

Studies have shown gamma-amino-butyric acid (GABA) and Glx (a combination of glutamate and glutamine) to be altered in major depressive disorder (MDD). Using proton Magnetic Resonance Spectroscopy (H-MRS), this study aimed to determine whether lower pretreatment GABA and Glx levels in the medial frontal cortex, a region implicated in MDD pathophysiology, are associated with better antidepressant treatment response. Participants with MDD (N = 74) were antidepressant naïve or medication-free for at least three weeks before imaging. Two MEGA-PRESS H-MRS acquisitions were collected, interleaved with a water unsuppressed reference scan. GABA and Glx concentrations were quantified from an average difference spectrum, with preprocessing using Gannet and spectral fitting using TARQUIN. Following imaging, participants were randomized to escitalopram or placebo for 8 weeks in a double-blind design. Multivariable logistic regression models were applied with treatment type and age as covariates. Bayes Factor hypothesis testing was used to interpret the strength of the evidence. No significant association was found between pretreatment Glx, GABA, or Glx/GABA and depression remission status or the continuous outcome, percent change in symptom severity. In an exploratory analysis, no significant correlation was found between pretreatment Glx, GABA or Glx/GABA and days to response. Bayes factor analysis showed strong evidence towards the null hypotheses in all cases. To date, there are no replicated biomarkers in psychiatry. To address this, well-powered, placebo-controlled trials need to be undertaken and reported. The present analysis suggests pretreatment GABA, Glx, or their ratio cannot predict antidepressant treatment response. Future direction including examining glutamate and glutamine separately or examining biological subtypes of MDD separately.Trial Name: Advancing Personalized Antidepressant Treatment Using PET/MRI.Registration Number: NCT02623205 URL: https://clinicaltrials.gov/ct2/show/NCT02623205.

Ketamine, a rapid-acting antidepressant, has undesirable psychotomimetic effects, including a dissociative effect. There is currently no effective strategy to suppress these side effects while preserving its antidepressant effect. Here, we investigated the effects of a D2/D3 receptor antagonist and partial agonists on the psychotomimetic and antidepressant effects of ketamine in mice and humans. Aripiprazole, a partial agonist, attenuated the psychotomimetic effect, but maintaining and even enhancing the antidepressant-like effect of ketamine in the forced swim test, whereas raclopride, an antagonist, suppressed both effects in mice. Brain-wide Fos mapping and its network analysis suggested the ventral tegmental area (VTA) as a critical region for distinguishing the effects of aripiprazole and raclopride. In the chronic stress model, local infusion of raclopride into the VTA inhibited ketamine's antidepressant-like effect, accompanied by activation of dopaminergic neurons, suggesting the inhibitory effect of VTA activation on the antidepressant-like effect of ketamine. Consistently, systemic injections of raclopride and brexpiprazole, a partial agonist similar to aripiprazole but closer to an antagonist (lower E), activated dopaminergic neurons in the VTA and suppressed ketamine's antidepressant-like effect in the model when co-administered with ketamine, whereas aripiprazole didn't. In line with these results, in a single-arm, double-blinded clinical study of sequential treatments in depressed patients (N = 9), co-administration of 12 mg of aripiprazole suppressed the dissociative symptoms induced by ketamine while maintaining its antidepressant effects. Together, these findings suggest that fine-tuning dopamine receptor signaling with aripiprazole allows selective suppression of ketamine-induced dissociation preserving its antidepressant effects, and that the combined use of aripiprazole and ketamine may be a preferred therapy for treatment-resistant depression.

We presented a patient with refractory anti-GABA-R encephalitis, and constructed libraries for single-cell sequencing from the patient's peripheral blood mononuclear cells (PBMCs), cerebrospinal fluid cells, as well as four healthy volunteer's PBMCs. A distinct group of monoclonal CD8 T cells and an abnormal JAK-STAT signaling pathway was implicated in the disease. The cross-reactive protein LIM-domain-only protein 5 (LMO5) identified in the patient's thymoma, prompted the activation of the specific CD8 T cells. Furthermore, in vitro analysis revealed the involvement of the JAK-STAT pathway in LMO5-induced CD8T cell activation, a process effectively suppressed by tofacitinib, which improved the patient's clinical outcome.

To investigate the pleiotropic mechanisms linking brain structure and function to alcohol drinking and tobacco smoking, we integrated genome-wide data generated by the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN; up to 805,431 participants) with information related to 3935 brain imaging-derived phenotypes (IDPs) available from UK Biobank (N = 33,224). We observed global genetic correlation of smoking behaviors with white matter hyperintensities, the morphology of the superior longitudinal fasciculus, and the mean thickness of pole-occipital. With respect to the latter brain IDP, we identified a local genetic correlation with age at which the individual began smoking regularly (hg38 chr2:35,895,678-36,640,246: rho = 1, p = 1.01 × 10). This region has been previously associated with smoking initiation, educational attainment, chronotype, and cortical thickness. Our genetically informed causal inference analysis using both latent causal variable approach and Mendelian randomization linked the activity of prefrontal and premotor cortex and that of superior and inferior precentral sulci, and cingulate sulci to the number of alcoholic drinks per week (genetic causality proportion, gcp = 0.38, p = 8.9 × 10, rho = -0.18 ± 0.07; inverse variance weighting, IVW beta = -0.04, 95%CI = -0.07--0.01). This relationship could be related to the role of these brain regions in the modulation of reward-seeking motivation and the processing of social cues. Overall, our brain-wide investigation highlighted that different pleiotropic mechanisms likely contribute to the relationship of brain structure and function with alcohol drinking and tobacco smoking, suggesting decision-making activities and chemosensory processing as modulators of propensity towards alcohol and tobacco consumption.

The primary purpose of this paper is to investigate whether text mining of the outpatient narrative notes for patients with severe and persistent mental illness (SPMI) can strengthen the predictions concerning the probability of an upcoming hospital readmission. A five-year study of all clinical notes for SPMI patients at the outpatient clinic of a tertiary hospital was conducted. The clinical notes were studied using ensemble classification i.e., entity recognition. Confounding variables pertaining to the patient's health status were extracted by text mining. A mixed effects logistic regression model was used for estimating the re-hospitalization risk during a clinic visit. The factors included frequency and continuity of outpatient visits, alterations in medication prescriptions, the usage of long-acting anti-psychotic injections (LAIs), the presence or absence of a legal compulsory treatment order (CTO) and the hospitalizations. The appearance of certain words in the outpatient clinical notes has a statistically significant impact on the risk of an upcoming hospitalization. This study also reconfirms that the risk of a re-hospitalization of an SPMI patient is reduced by the presence of a CTO and the utilization of LAIs, whereas it is increased by the patient dropping out of outpatient care. Our findings pertaining to the risk of re-hospitalization could facilitate preventive interventions for SPMI patients with higher risk.

Post-Traumatic Stress Disorder (PTSD) is a psychiatric disease that may develop after experiencing a traumatic event and it is characterized by resistance to extinction of the traumatic memory. Psychotherapy, which mainly focuses on favoring fear memory extinction, represents the first-line treatment for PTSD. However, this approach is not always successful. Emerging evidence suggests the importance of a social support in alleviating PTSD symptomatology; however, the efficacy of group therapy for PTSD remains controversial. Here, we evaluated the impact of social support on the efficacy of fear extinction sessions in a chronic PTSD-like rat model. We tested the hypothesis that the presence of a social partner during temporally spaced extinction sessions (to mimic the presence of a social support during therapy) or after the extinction sessions in a neutral environment (to mimic the presence of a social support outside of the therapy setting) would ameliorate long-term PTSD-like symptomatology. Extinction sessions were carried out under different conditions: (i) alone; (ii) with a social partner never exposed to the trauma; (iii) with a trauma-exposed partner. In a separate set of experiments, rats were exposed to the extinction sessions alone and, immediately thereafter, paired with a social partner, as indicated above, in a different context. Extinction sessions carried out in the presence of a social partner never exposed to the traumatic experience rescued long-term trauma-induced PTSD-like symptomatology. We provide evidence of beneficial effects of a "healthy" social support during extinction sessions in ameliorating both immediate and persistent over time cognitive and emotional PTSD-like symptoms.

Acylcarnitines (ACs) are involved in bioenergetics processes that may play a role in the pathophysiology of depression. Previous genomic evidence identified four ACs potentially linked to depression risk. We carried forward these ACs and tested the association of their circulating levels with Major Depressive Disorder (MDD) diagnosis, overall depression severity and specific symptom profiles. The sample from the Netherlands Study of Depression and Anxiety included participants with current (n = 1035) or remitted (n = 739) MDD and healthy controls (n = 800). Plasma levels of four ACs (short-chain: acetylcarnitine C2 and propionylcarnitine C3; medium-chain: octanoylcarnitine C8 and decanoylcarnitine C10) were measured. Overall depression severity as well as atypical/energy-related (AES), anhedonic and melancholic symptom profiles were derived from the Inventory of Depressive Symptomatology. As compared to healthy controls, subjects with current or remitted MDD presented similarly lower mean C2 levels (Cohen's d = 0.2, p ≤ 1e-4). Higher overall depression severity was significantly associated with higher C3 levels (ß = 0.06, SE = 0.02, p = 1.21e-3). No associations were found for C8 and C10. Focusing on symptom profiles, only higher AES scores were linked to lower C2 (ß = -0.05, SE = 0.02, p = 1.85e-2) and higher C3 (ß = 0.08, SE = 0.02, p = 3.41e-5) levels. Results were confirmed in analyses pooling data with an additional internal replication sample from the same subjects measured at 6-year follow-up (totaling 4141 observations). Small alterations in levels of short-chain acylcarnitine levels were related to the presence and severity of depression, especially for symptoms reflecting altered energy homeostasis. Cellular metabolic dysfunctions may represent a key pathway in depression pathophysiology potentially accessible through AC metabolism.

Obsessive-compulsive disorder (OCD), a disabling and notoriously treatment-resistant neuropsychiatric disorder, affects 2-3% of the general population and is characterized by recurring, intrusive thoughts (obsessions) and repetitive, ritualistic behaviors (compulsions). Although long associated with dysfunction within the cortico-striato-thalamic-cortical circuits, the thalamic role in OCD pathogenesis remains highly understudied in the literature. Here, we identified a rat thalamic nucleus - the reuniens (NRe) - that mediates persistent, compulsive self-grooming behavior. Optogenetic activation of this nucleus triggers immediate, excessive grooming with strong irresistibility, increases anxiety, and induces negative affective valence. A thalamic-hypothalamic pathway linking NRe to the dorsal premammillary nucleus (PMd) was discovered to mediate excessive self-grooming behavior and render it a defensive coping response to stress, mirroring the compulsions faced by OCD patients. Given the close resemblance between this self-grooming behavior and the clinical manifestations of OCD, the results from this study highlight the role of NRe in mediating OCD-like compulsive behaviors. This can be attributed to NRe's position at the nexus of an extensive frontal-striatal-thalamic network regulating cognition, emotion, and stress-related behaviors, suggesting NRe as a potential novel target for intervention.

This study aimed to explore the clinical characteristics and alteration of orexinergic level in cerebrospinal fluid (CSF) and the volumes of brain grey and white matters, and investigate the roles of orexinergic level on the association between brain atrophy and depression in Alzheimer's disease (AD) patients. The demographic variables of 156 participants were collected. Orexinergic level in CSF and the volumes of brain grey and white matters were evaluated. The correlations of orexinergic level in CSF with depression and brain volume in AD patients were analyzed. The mediating effect of orexinergic level in CSF on the association between brain atrophy and depression in AD patients was investigated. The joint predictive value of orexinergic level in CSF and brain volume for depression in AD patients was established. AD with depression patients showed significantly elevated levels of orexin A and orexin B in CSF; orexin A level in CSF was positively correlated with HAMD score in AD patients. The elevated orexin A level in CSF mediated 49.6% of total association between the decreased grey matter volume of right dorsal medial thalamic nucleus and depression, and 50.3% of total association between the reduced white matter volume of left amygdala and depression. Combinations of above parameters could predict depression in AD patients with a significantly high area under the curve (AUC = 0.841). Therefore, the elevated orexin A level in CSF mediates its effect on the atrophy of the right dorsal medial thalamic nucleus and the white matter of the left amygdala, eventually alleviating depression in AD.

Anorexia nervosa (AN) typically emerges around adolescence and predominantly affects females. Recent progress has been made in identifying biological correlates of AN, but more research is needed to pinpoint the specific mechanisms that lead to its development and maintenance. There is a known phenotypic link between AN, growth and sexual maturation, yet the genetic overlap between these phenotypes remains enigmatic. One may hypothesize that shared factors between AN, energy metabolism and reproductive functions may have been under recent evolutionary selection. Here, we characterize the genetic overlap between AN, BMI and age at menarche, and aimed to reveal recent evolutionary factors that may help explain the origin of AN. We obtained publicly available GWAS summary statistics of AN, BMI and age at menarche and studied the polygenic overlap between them. Next, we used Neandertal Selective Sweep scores to explore recent evolutionary selection. We found 22 loci overlapping between AN and BMI, and 9 loci between AN and age at menarche, with 7 of these not previously associated with AN. We found that loci associated with AN may have been under particular evolutionary dynamic. Chronobiology appeared relevant to the studied genetic overlaps and prone to recent evolutionary selection, offering a promising avenue for future research. Taken together, our findings contribute to the understanding of the genetic underpinning of AN. Ultimately, better knowledge of the biological origins of AN may help to target specific biological processes and facilitate early intervention in individuals who are most at risk.

Depression is a common and severe mental disorder that affects more than 300 million people worldwide. While it is known to have a moderate genetic component, identifying specific genes that contribute to the disorder has been challenging. Previous Genome-wide association studies (GWASs) have identified over 100 genomic loci that are significantly associated with depression. But finding useful therapeutic targets and diagnostic biomarkers from this information has proven difficult. To address this challenge, I conducted a plasma protein proteome-wide association study (PWAS) for depression, using human plasma protein QTL (pQTL) and depression GWAS data. I identified four proteins that were significantly associated with depression: BTN3A3 (P value = 6.41 × 10), PSMB4 (P value = 1.42 × 10), TIMP4 (P value = 3.77 × 10), and ITIH1 (P value = 7.86 × 10). Specifically, I found that BTN3A3 and PSMB4 play a causal role in depression, as confirmed by colocalization and Mendelian Randomization (MR) analysis. Interestingly, I also discovered that PSMB4 was significantly associated with depression in both the brain proteome studies and the plasma PWAS results, which suggests that it may be a particularly promising candidate for further study. Overall, this work has identified 4 new risk proteins for depression and highlights the potential of plasma proteome data for uncovering novel therapeutic targets and diagnostic biomarkers.

Suicidal ideation (SI) and behavior (SB) are major public health concerns, but risk factors for their development and progression are poorly understood. We used ICD codes and a natural language processing algorithm to identify individuals in a hospital biobank with SI-only, SB, and controls without either. We compared the profiles of SB and SI-only patients to controls, and each other, using phenome-wide association studies (PheWAS) and polygenic risk scores (PRS). PheWAS identified many risk factors for SB and SI-only, plus specific psychiatric disorders which may be involved in progression from SI-only to SB. PRS for suicide attempt were only associated with SB, and even after accounting for psychiatric disorder PRS. SI PRS were only associated with SI-only, although not after accounting for psychiatric disorder PRS. These findings advance understanding of distinct genetic and clinical risk factors for SB and SI-only, which will aid in early detection and intervention efforts.

Metabolic syndrome (MetS) is a condition that includes a cluster of risk factors for cardiovascular disease. In this paper, we aimed to evaluate the association between depressive symptoms, antidepressant use, duration of antidepressant use, antidepressant type and MetS. Data from the 2005-2018 National Health and Nutrition Examination Surveys were used in this study. Adults were included if they responded to the depressive symptoms and prescription medications questionnaires and had measures of blood pressure, waist circumference, triglycerides, high-density lipoprotein, and fasting plasma glucose. Participants were categorized by their antidepressant use (yes/no), type, and duration. This study included 14,875 participants (50.45% females), with 3616 (23.45%) meeting the criteria for MetS. Participants with higher depressive symptom scores (aOR = 1.04, 95% CI: 1.02, 1.05, p < 0.001) or those with depressive symptoms (aOR = 1.42, 95% CI: 1.17, 1.73, p = 0.001) had higher odds of MetS. A similar associations was seen among those who were on antidepressants compared to those who were not on antidepressants (aOR = 1.24, 95% CI: 1.03, 1.50, p = 0.025). Duration of antidepressant use was not significantly associated with MetS. Participants on tricyclic antidepressants had greater odds of MetS compared to those not taking any antidepressants (aOR = 2.27, 95% CI: 1.31, 3.93, p = 0.004). Our study provides evidence of the association between depressive symptoms, antidepressant use, and MetS, highlighting the importance of monitoring metabolic and cardiovascular alterations in individuals of depression.

Bipolar disorder (BD) and unipolar depression (UD) are defined as distinct diagnostic categories. However, due to some common clinical and pathophysiological features, it is a clinical challenge to distinguish them, especially in the early stages of BD. This study aimed to explore the common and disease-specific connectivity patterns in BD and UD. This study was constructed over 181 BD, 265 UD and 204 healthy controls. In addition, an independent group of 90 patients initially diagnosed with major depressive disorder at the baseline and then transferred to BD with the episodes of mania/hypomania during follow-up, was identified as initial depressive episode BD (IDE-BD). All participants completed resting-state functional magnetic resonance imaging (R-fMRI) at recruitment. Both network-based analysis and graph theory analysis were applied. Both BD and UD showed decreased functional connectivity (FC) in the whole brain network. The shared aberrant network across groups of patients with depressive episode (BD, IDE-BD and UD) mainly involves the visual network (VN), somatomotor networks (SMN) and default mode network (DMN). Analysis of the topological properties over the three networks showed that decreased clustering coefficient was found in BD, IDE-BD and UD, however, decreased shortest path length and increased global efficiency were only found in BD and IDE-BD but not in UD. The study indicate that VN, SMN, and DMN, which involve stimuli reception and abstraction, emotion processing, and guiding external movements, are common abnormalities in affective disorders. The network separation dysfunction in these networks is shared by BD and UD, however, the network integration dysfunction is specific to BD. The aberrant network integration functions in BD and IDE-BD might be valuable diagnostic biomarkers.

Within precision psychiatry, there is a growing interest in normative models given their ability to parse heterogeneity. While they are intuitive and informative, the technical expertise and resources required to develop normative models may not be accessible to most researchers. Here we present Neurofind, a new freely available tool that bridges this gap by wrapping sound and previously tested methods on data harmonisation and advanced normative models into a web-based platform that requires minimal input from the user. We explain how Neurofind was developed, how to use the Neurofind website in four simple steps ( www.neurofind.ai ), and provide exemplar applications. Neurofind takes as input structural MRI images and outputs two main metrics derived from independent normative models: (1) Outlier Index Score, a deviation score from the normative brain morphology, and (2) Brain Age, the predicted age based on an individual's brain morphometry. The tool was trained on 3362 images of healthy controls aged 20-80 from publicly available datasets. The volume of 101 cortical and subcortical regions was extracted and modelled with an adversarial autoencoder for the Outlier index model and a support vector regression for the Brain age model. To illustrate potential applications, we applied Neurofind to 364 images from three independent datasets of patients diagnosed with Alzheimer's disease and schizophrenia. In Alzheimer's disease, 55.2% of patients had very extreme Outlier Index Scores, mostly driven by larger deviations in temporal-limbic structures and ventricles. Patients were also homogeneous in how they deviated from the norm. Conversely, only 30.1% of schizophrenia patients were extreme outliers, due to deviations in the hippocampus and pallidum, and patients tended to be more heterogeneous than controls. Both groups showed signs of accelerated brain ageing.