Translational Psychiatry

Background: The Neuro-Immune-Metabolic-Oxidative Stress (NIMETOX) theory identified systemic dysregulation in Major Depressive Disorder (MDD), yet the precise gut-derived metabolic triggers initiating this cascade remain elusive. This study investigated the interplay between fecal short-chain fatty acids (SCFAs), systemic immune activation, and clinical phenotypes to identify a potential gut-immune biotype for MDD. Methods: Fecal SCFA profiles and serum immune-inflammatory markers were quantified in 102 patients with MDD and 38 matched healthy controls. A multistage statistical approach was employed: binary logistic regression and 10-fold cross-validated linear discriminant analysis (LDA) were utilized to evaluate diagnostic accuracy, while multivariable regression models were applied to identify robust predictors of clinical phenotypes, including the overall severity of depression (OSOD), physiosomatic symptoms, and recurrence of illness (ROI). Results: MDD patients exhibited a significant depletion of protective straight-chain SCFAs (acetate, propionate, butyrate) and an elevation in branched-chain SCFAs (BSCFAs), indicating a pathological shift from saccharolytic to proteolytic fermentation. This metabolic shift correlated with elevated acute phase-inflammatory index (API) and epidermal growth factor (EGF). A multidimensional model combining BSCFAs, acetate, API, EGF, and T helper 2 discriminated MDD from controls with adequate accuracy (AUC = 0.874). Furthermore, elevated BSCFAs and decreased protective SCFAs strongly predicted higher OSOD, more severe physiosomatic symptoms, and increased ROI. Notably, 5-Hydroxytryptamine receptor 1A agonists were independently associated with elevated BSCFAs. Conclusion: MDD is characterized by a distinct gut-immune biotype tightly linked to toxic proteolytic gut fermentation. This metabolic-immune fingerprint offers an objective diagnostic tool and highlights the need for microbiome-targeted interventions in precision psychiatry.

Background: Aberrations in neuro-immune, metabolic, and oxidative stress (NIMETOX) pathways are implicated in major depressive disorder (MDD). First-episode simple dysmood disorder (FE-SDMD) without metabolic syndrome offers a unique model to investigate early lipid alterations underlying NIMETOX pathophysiology. Methods: Plasma samples were collected from 88 university students (44 FE-SDMD, 44 healthy controls). Participants underwent comprehensive psychiatric and psychological assessments, including adverse childhood experiences (ACEs), negative life events (NLEs), depression, anxiety, suicidal behaviors, and insomnia. Untargeted lipid profiling was performed using LC-QTOF-MS, while indices of oxidative and nitrosative stress (ONS) and lecithin-cholesterol acyltransferase (LCAT) activity were assessed. Data was analyzed using machine learning approaches with recursive feature elimination and cross-validation. Results: FE-SDMD was characterized by increased ceramides (CER), diacylglycerides (DAG), triacylglycerides (TG), sphingomyelins (SM), bis-monoacylglycerol phosphates (BMP), cholestone, and fatty-acyl amino acids (FAAA). DAG, CER, and BMP were the strongest predictors of depression severity and physiosomatic symptoms, whereas cholestone, CER, and SM predicted suicidal behaviors. These lipid modules, together with lowered LCAT and increased ONS, explained substantial variance in depression severity (46.4%), physiosomatic symptoms (42.4%), cognitive-affective symptoms (37.9%), suicidal behaviors (30.1%), insomnia (32%), and anxiety (19.5%). ACEs and NLEs were strongly associated with CER (p<0.001), DAG (p<0.01), and cholestone (p<0.01). Conclusion: Early-stage MDD is characterized by distinct lipid dysregulations linked to psychosocial stress exposure, oxidative and nitrosative stress, and an indicant of impaired reverse cholesterol transport. These lipid modules may serve as early biomarkers and therapeutic targets in vulnerable populations.

Suicidal ideation in obsessive-compulsive disorder (OCD) is common and clinically significant, yet much of the existing literature conceptualizes suicide risk through the lens of comorbid depressive symptomatology. The present study examined whether other clinical features can identify clinically meaningful patterns associated with SI. Participants included 231 individuals with clinically significant OCD symptoms. SI was operationalized using Item 9 of the Beck Depression Inventory-II and binarized to reflect the presence or absence of suicidal thoughts. Depression severity scores were intentionally excluded from the predictive feature set, and three machine learning models (ElasticNet, Random Forest, and Explainable Boosting Machines) were evaluated using repeated nested cross-validation. All three algorithms showed comparable predictive performance. Given this overlap, the EBM was selected for interpretation due to its ability to model nonlinear relationships and interaction effects transparently. The model identified quality of life, obsessive-compulsive trait severity, somatic burden, and conscientiousness as prominent predictors of SI. Risk functions suggested nonlinear increases in estimated suicide risk at elevated levels of obsessive-compulsive traits and reduced quality of life. Additionally, interaction analyses indicated that severe obsessive-compulsive traits combined with elevated somatic burden were associated with higher estimated suicide risk than either factor alone. These findings suggest that interpretable machine learning can support clinically relevant phenotypic hypothesis generation. They also highlight somatic burden, functional impairment, obsessive-compulsive trait severity, and conscientiousness as potentially underappreciated targets for SI risk assessment in OCD, beyond the traditional focus on depressive comorbidity.

Major depressive disorder (MDD) is a highly prevalent neuropsychiatric disorder characterized by depressed mood, feelings of sadness, loss of interest, and reduced pleasure related to daily activities. The clinical etiology of depression has been extensively studied, with research indicating biological, social, and psychological factors related to onset of depressive symptoms. Despite increased knowledge related to MDD, there is no tangible biomarker developed for MDD. Neuroimaging modalities such as single photon emission computed tomography (SPECT) have been utilized to characterize regional cerebral perfusion (rCBF). Functional dysconnectivity in depressed patients have been examined, with depressed individuals showing elevated depression scores and decreased rCBF in cognition and executive functioning networks. While SPECT can be utilized to monitor rCBF changes with respect to symptom severity, it alone cannot be utilized to develop a potent biomarker. Advanced multivariate methods such as independent component analysis (ICA) have been used to visualize disconnected functional patterns across disorders including depression and schizophrenia. Given no current SPECT studies examine transdiagnostic clinical profiles, the current study aims to bridge this gap. We utilized the 68 NeuroMark SPECT template across six patient groups. Factor scores investigating three key symptoms of depression: worry/rumination, moodiness, and social disinterest, and measured the loading parameter strength (i.e. component expression for each NeuroMark domain/subdomain) across the 68 components were examined. We identified significant relationships between symptoms and frontal, triple network, sensorimotor, and visual components across the three symptom profiles. Future studies should examine these trends across larger sample sizes, and increased clinical samples.

Polygenic risk scores (PRS) have shown increasing utility for risk stratification across complex diseases, but for psychiatric disorders such as bipolar disorder (BD), current PRS explain only a fraction of disorder liability (~1-9%), with predictive performance further diminished in non-European populations and real-world clinical cohorts. To explore the potential of integrating social and environmental risk factors alongside genetic liability to improve risk prediction, we evaluated the relationship between a PRS for BD (PRSBD) and six social risk measures - perceived stress, discrimination in medical settings, neighborhood social cohesion, perceived neighborhood disorder, cost-related medication nonadherence, and adverse childhood experiences - to BD case status in 115,275 participants (7,000 cases; 108,275 controls) from the All of Us Research Program. PRSBD was associated with BD case status across ancestry groups, though liability-scale variance explained was attenuated relative to what has been reported for curated research cohorts (R2 = 1.86% in European, 0.60% in African, 1.65% in Latino/Admixed American ancestries). Each social risk factor tested exhibited a larger effect size than PRSBD, with perceived stress (OR = 2.05 per SD) and adverse childhood experiences (OR = 2.68 for [&ge;]4 ACEs) demonstrating the strongest associations. Individuals in the lowest genetic risk decile with high social burden exhibited BD prevalence comparable to or exceeding those in the highest genetic risk decile with low social burden. These findings demonstrate the substantial explanatory power of social risk factors and support the development of integrated genetic-social risk frameworks for more accurate and equitable psychiatric risk prediction.

Problematic Sexual Behaviour (PSB) is defined as difficult to control recurrent sexual behaviours that continue despite adverse consequences, leading to social and functional impairment. There is debate whether PSB is a disorder of compulsion or addiction; PSB often co-occurs with neuropsychiatric disorders, but further elucidation regarding underlying biology is required. A deficiency in reward neurotransmitter systems (reward deficiency syndrome: RDS) may underlie a shared vulnerability to addiction. We conducted the first case-control genome wide association study (GWAS) of PSB in patients (n=448), and comparison participants with (n=196) and without PSB (n=1488). We used polygenic risk scores (PRS) to test genetic overlap with related psychiatric, behavioural and personality phenotypes. Three models were used: 1) All-PSB (patient + comparison) vs. controls, 2) Patient-PSB vs controls, and 3) RDS (yes/no). Results suggested genetic overlap of PSB with psychiatric conditions, with PRS for major depression, substance use, and others predicting PSB status. PRS for related behavioural phenotypes (e.g., externalizing, age at first sex, number of lifetime sexual partners) and personality traits also predicted PSB. The patient model showed stronger associations than the All-PSB model, and RDS had both shared and distinct genetics with PSB. As expected with the sample size, only suggestive hits were observed with single variant and gene-based tests. PSB may share genetic mechanisms with various conditions. Further research in larger cohorts is needed to better understand the underlying genetics and environmental factors involved, and to improve diagnostic classification, intervention and treatment prospects.

Major depressive disorder (MDD) is a common psychiatric illness with a high proportion of patients being nonresponsive to therapy. Selective serotonin reuptake inhibitors (SSRI) are widely prescribed for treating depression. Chronic SSRI administration is needed for therapeutic effects, a process implicating in part, increased neurogenesis in the hippocampus. Recent genome wide association studies (GWAS) identified the DrD2 locus, which encodes the dopamine D2 receptor (D2R) as a major risk factor in MDD. Here we demonstrate that behavioural effects associated with chronic administration of the SSRI drug fluoxetine and its accompanying neurogenic effects require D2R. Administration of fluoxetine to congenital D2R-knockout mice, or co-administration of the antidepressant with the antipsychotic D2R antagonist drug haloperidol prevented the neurogenic effects of fluoxetine. Furthermore, while acute behavioural responses to fluoxetine did not require D2R, this receptor was essential for the behavioural effects of chronic fluoxetine. The neurogenic impact of chronic fluoxetine was further associated with beta-arrestin 2-mediated signalling and the hippocampal regulation of the pro-neurogenic factor BDNF. These results support a role of D2R in regulating the therapeutically relevant chronic effects of fluoxetine on mood, BDNF signalling, and associated hippocampal neurogenesis. Furthermore, our findings suggest an unappreciated interaction between genetic risk for MDD and treatment responsiveness as well as a negative interaction between SSRIs and antipsychotic drugs in the regulation of hippocampal neurogenesis.

Psychiatric disorders, such as attention-deficit/hyperactivity disorder, autism spectrum disorder, and schizophrenia, are clinically heterogeneous and lack objective biomarkers for reliable diagnosis. Although blood transcriptomic data have been proposed as a potential source of diagnostic information, their generalizability across independent cohorts remains unclear. This study aimed to assess whether biologically informed measures of dynamic instability enhance the reproducibility and generalizability of psychiatric classifications based on peripheral blood data by integrating publicly available blood transcriptomic datasets from multiple cohorts and evaluating classification performance using individual-level cross-validation and study-level holdout validation. To investigate the underlying biological structure, we applied a dynamic systems framework, including pseudotime-based vector field inference and attractor analysis. Additionally, we introduced temporal entropy as a measure of dynamic instability in the inferred transcriptomic trajectories. High classification performance was observed in individual-level cross-validation (area under the receiver operating characteristic [AUROC] > 0.8 across several comparisons); however, performance decreased substantially in study-level validation (AUROC {approx} 0.5-0.7), indicating limited generalizability. Attractor analysis revealed that transcriptomic states formed continuous and overlapping structures rather than distinct diagnostic clusters. Stratification based on temporal entropy identified a subset of individuals with unstable transcriptomic dynamics, and excluding these individuals improved the classification performance across most diagnostic pairs (AUROC > 0.7). These findings suggest that transcriptomic variability and dynamic instability contribute to the limited reproducibility of psychiatric classifications. Incorporating temporal entropy as a measure of system-level instability may enhance the robustness and interpretability of biomarker-based models and provide a new perspective on psychiatric disorders as dynamic systems.

GABAergic deficit is associated with key neuropsychiatric disorders, such as major depressive disorder (MDD), anxiety, schizophrenia, and autism spectrum disorder (ASD). However, it is not known whether these disorders are causal to or a result of GABAergic dysfunction. We previously showed that the Solute carrier 38 member 1 (Slc38a1) accumulates glutamine in subpopulations of GABAergic neurons and sustains neurotransmitter GABA synthesis. Genetic inactivation of Slc38a1 in mice caused lowered GABA levels, altered synaptic vesicle morphology, slowed {gamma}-oscillations, and reduced cortical processing and plasticity, selectively at GABAergic synapses. We now demonstrate a significant reduction in learning and memory performance in the Morris water maze and increased signs of despair in the forced swim test in Slc38a1-/- mice compared to Slc38a1+/+ mice, implicating cognitive impairments and depressive-like behavior. Examination in the open field maze also indicates anxiety and/or reduced interest in exploration. There are no signs of impaired sociability or recognition of social novelty in the three-chambered test, speaking against involvement in schizophrenia- or ASD-like disorders. Metabolic phenotyping and measurement of the locomotion do not segregate the Slc38a1 genotypes, suggesting that the cognitive impairments, depressive-like behavior and anxiety are brain-dependent. Our data is further supported by a pathologic variant of Slc38a1 in a family with depression and suicidal behavior. Altogether, we demonstrate that dysfunction of Slc38a1-dependent GABA synthesis and the ensuing impaired {gamma}-oscillations underpin the pathogenesis of neurocognitive deficits, anxiety and depression.

Impaired learning that both novel and previously dangerous stimuli are safe (safety and extinction learning, respectively) are long standing, robust, and heritable features of anxiety disorders, representing potential endophenotypes. The computational mechanisms underpinning them have demonstrated associations with anxiety severity in recent studies. We undertook a pre-registered replication in a tenfold larger independent sample of twins (n = 925). Extinction learning rates were associated with anxiety severity ({rho}replication = -0.14, BFr0 = 1189. 67) but safety learning rates were not. Conversely, although safety learning rates showed modest heritability (h2safety = 0.16), extinction learning rates were not heritable. Accordingly, we were unable to identify genetic overlap between anxiety and either learning rate. Although this suggests neither learning rate is an anxiety endophenotype, we confirmed a cognitive-behavioral mechanism underpinning a robust marker of anxiety severity. Furthermore, we demonstrated heritability of a computationally modelled learning parameter, a key step towards establishing its biological basis.

Background: Major depressive disorder (MDD) is clinically heterogeneous, hindering identification of reproducible biomarkers. Using a semi-supervised machine learning approach, HYDRA, we previously identified two neuroanatomical dimensions from structural MRI in medication-free MDD from COORDINATE-MDD consortium. These dimensions (D1, D2) showed differential responses to selective serotonin reuptake inhibitor (SSRI) antidepressants and placebo. External replication in UK Biobank linked D2, characterized by widespread subtle neuroanatomical reductions, to an immuno-metabolic profile. Here, we examined whether these dimensions are detectable early in the course of illness. Methods: We applied the pre-trained model to structural MRI data from the multisite PRONIA cohort, comprising individuals with recent-onset depression (ROD; n = 377; mean age 25.8 years, SD 6.0; 51.3% female) and healthy controls (n = 267; mean age 25.5 years, SD 6.4; 61.0% female). Participants were assigned to clusters (C1, C2) corresponding to the previously identified dimensions (D1, D2). Clusters were compared on clinical symptom profiles, peripheral inflammatory markers, and in a subset (n = 107), proteomic ageing indices. Results: Two neuroanatomical clusters were identified in PRONIA. C1 (n = 265) showed higher negative symptom severity and elevated interleukin-2 levels. C2 (n = 140) was associated with higher residual proteomic age. Overall depressive symptom severity did not differ significantly between clusters. Conclusions: Neuroanatomical dimensions of MDD are reproducible and detectable at illness onset. Associations with negative symptom severity, inflammatory signalling, and proteomic ageing suggest these dimensions capture biologically meaningful heterogeneity early in depression. These findings support a biologically informed framework for stratified treatment approaches in MDD.

Background: Hydrogen sulfide (H2S) is an endogenous gasotransmitter synthesised in the central nervous system (CNS) primarily by cystathionine {beta}-synthase (CBS) and cystathionine {gamma}-lyase (CSE). Pre-clinical studies consistently implicates H2S deficiency in the pathophysiology of depression through disruption of synaptic plasticity, neuroinflammation, oxidative stress, and brain-derived neurotrophic factor (BDNF) signalling. Yet, we still lack direct clinical evidence quantifying circulating H2S in patients with Major Depressive Disorder (MDD), particularly from South Asian populations. In this study, we measured serum H2S levels in drug-naive patients with MDD and compared them with healthy controls at a tertiary care center in eastern India. We examined the associations between serum H2S and depression severity as assessed by the 17-item Hamilton Depression Rating Scale (HAM-D-17). This institution-based, cross-sectional analytical study was conducted at North Bengal Medical College and Hospital (NBMCH), West Bengal, India, over 12 months. Fifty drug-naive patients fulfilling DSM-5 criteria for MDD and fifty age- and sex-matched healthy controls were enrolled by consecutive sampling. We quantified serum H2S using the spectrophotometric methylene blue method and depression severity was assessed using HAM-D-17. Statistical analyses included independent-samples t-test, chi-square test, and linear regression. Serum H2S was markedly and significantly lower in MDD patients (0.068 {+/-} 0.044 {micro}mol/L) compared with healthy controls (0.524 {+/-} 0.272 {micro}mol/L; p < 0.001), representing an approximately 7.7-fold reduction. HAM-D-17 scores were significantly higher in MDD patients (28.94 {+/-} 12.78) than in controls (3.96 {+/-} 2.31; p < 0.001). Linear regression across the combined cohort revealed a significant negative association between serum H2S and HAM-D score (R{superscript 2} = 0.287; y = 24.64 - 26.84x; p < 0.001), indicating that higher serum H2S was associated with lower depression severity. Within the MDD group alone, the regression was weak (R{superscript 2} = 0.061), consistent with a floor effect. Within the control group alone, the regression was strong (R{superscript 2} = 0.772). No significant associations were found between serum H2S and any sociodemographic variable in either group. Drug-naive MDD patients exhibited substantially reduced serum H2S levels compared with healthy controls, and lower H2S was associated with greater depression severity. These findings provide direct clinical evidence from an Indian population supporting the H2S deficiency hypothesis of depression and suggest that the CBS/CSE-H2S axis may represent a novel biomarker and therapeutic target in MDD. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/26352330v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1ce64f6org.highwire.dtl.DTLVardef@1465ca2org.highwire.dtl.DTLVardef@6bba64org.highwire.dtl.DTLVardef@9a1411_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background: Schizophrenia, bipolar disorder, and depression share substantial genetic liability. However, the molecular mechanisms underlying this shared architecture remain poorly characterized. In particular, the role of circulating proteins as potential mediators and therapeutic targets is not well understood. Methods: Based on large-scale genome-wide association studies, we constructed a latent psychiatric common factor using genomic structural equation modeling. We then performed proteome-wide Mendelian randomization to estimate the associations between circulating proteins and this shared liability, based on four independent proteomic cohorts. Protein-psychiatric common factor associations were prioritized through comprehensive sensitivity analyses and colocalization. We additionally performed tissue- and single-cell expression enrichment analyses and a systematic druggability assessment. Results: We identified 36 circulating proteins with evidence of association with the psychiatric common factor that withstood multiple sensitivity analyses. Several proteins showed distinct tissue-specific expression patterns, with enrichment in brain, immune, or liver tissues, highlighting convergent neuroimmune and systemic pathways. For instance, genetically predicted higher levels of MAPK3, FES, MRE11A, HS6ST3, OLFM1, BTN3A1, BTN3A2 and BTN3A3 were associated with increased psychiatric risk, whereas higher levels of CD40, ITIH3, and ITIH4 were associated with decreased risk. Druggability assessment identified CD40, MAPK3, FES, MRE11A and BTN3A1 as established or potential therapeutic targets. Conclusions: By integrating genetic, proteomic, and transcriptomic data, this study identifies circulating proteins that associated with the shared genetic effects on three major psychiatric disorders. These findings provide biologically grounded candidates for therapeutic targeting and offer insights into shared disease mechanisms.

Abstract Schizophrenia (SCZ) and bipolar disorder (BPD) are highly heritable psychiatric disorders with complex polygenic architectures. Genome-wide association studies (GWASs) have identified numerous common variant associations, but rarer variants detectable through whole-genome sequencing (WGS) remain underexplored. We conducted rare variant association analysis using WGS data from the Portuguese Island Collection (PIC), including 28 families with SCZ (n = 53) and 41 families with BPD (n = 83) cases, and population controls (n = 62). Following ANNOVAR and CADD annotation, burden analysis of deleterious variants showed that both affected and unaffected family members from SCZ and BPD pedigrees had significantly higher burdens of rare deleterious variants compared to controls (p < 0.0001), with no significant differences observed between affected and unaffected relatives, consistent with shared familial genetic liability. Polygenic Risk Score (PRS) analysis confirmed significant genetic contributions to both disorders within PIC. Association analyses were subsequently performed using SAIGE-GENE+ identifying 483 and 583 nominally significant (suggestive associations) gene sets (p-value [&le;] 0.05; FDR > 0.05) for SCZ and BPD, respectively, including gene sets related to neurotransmission, synaptic function and structure, neurodevelopment, and neuroinflammation as well as major signaling pathways. Cross disorder overlaps also identified shared suggestive enrichment of GABA and glutamate signaling, synaptic signaling, and Wnt signaling gene sets in both SCZ and BPD. These findings support shared rare variant burden within multiplex psychiatric families and highlight the role of gene-set based rare variant analysis in identifying neurobiological pathways relevant to SCZ and BPD. Keywords: WGS, Rare Variants, Schizophrenia, Bipolar Disorder

Nicotine use disorder shows heterogeneity in treatment response, potentially reflecting differences in underlying neural circuitry, particularly in the presence of depression. We examined real-time neural dynamics during nicotine inhalation in two chronic users - one with depression and one without - using simultaneous hippocampal recordings from responsive neurostimulation (RNS) electrodes and scalp EEG. Oscillatory activity and hippocampal-cortical connectivity were analyzed in relation to mood and craving. Oscillatory activity tracked mood in the non-depressed individual but was attenuated or reversed in the depressed individual, suggesting reduced reward-related neural responsiveness. In contrast, both participants showed reduced alpha hippocampal-cortical connectivity following nicotine use, suggesting a shift from reward-seeking to reward and relief processing. These findings support a network-based framework of nicotine-driven neural dynamics and provide preliminary evidence that depressive status may modulate these processes. Although limited to two cases, this work highlights the potential for identifying neurophysiological subtypes of nicotine users and informs future efforts toward personalized treatment approaches.

Negative cognitive biases in depression are more pronounced in females than in males. This sex difference emerges during adolescence, a sensitive developmental stage when chronic stress exposure increases the risk of depression in adulthood. The neurobiology linking adolescent stress to sex-specific cognitive bias and resting-state network reorganization in adults remain poorly understood. The study aimed to investigate the longitudinal effects of chronic restraint stress (CRS) during adolescence on cognitive bias and functional connectome in emerging adulthood. 28 Wistar rats (sex-balanced; aged five weeks on arrival) were trained on a judgment bias task with distinct tactile cues signalling differential rewards. Cognitive bias was quantified from responses to ambiguous probe trials. Following training, animals were randomly and equally assigned to CRS or control groups (sex-balanced). Offline resting-state functional MRI scans were conducted at adolescent baseline (pre-CRS) and again in adulthood (post-CRS), followed by probe trials to assess neural and behavioural changes. Following CRS, females showed a greater tendency to shift toward negative bias than males (ratio of odds ratio=3.67). Furthermore, CRS significantly reduced functional connectivity between the left cerebellar-auditory and hypothalamic-thalamic networks only in females. Repeated-measures correlation between cognitive bias and network connectivity were not statistically significant across sex-by-group strata, potentially due to offline imaging and small sample size. However, intra-individual association revealed sex-specific trends, with CRS females showing moderately positive correlations and CRS males exhibiting a weak negative association. The results could inform stratified connectome-based interventions targeting adolescent stress exposures to potentially reduce the risk of adult depression. Six keywords: Resting-State Functional MRI, Chronic Restraint Stress, Judgement Bias, Open Field Test, Sex Differences

The ability to adjust to changing environments (cognitive flexibility) and optimal decision-making are pivotal brain functions that govern successful human behavior. Anxiety and depressive disorders are strongly pervasive psychiatric conditions across the lifespan that profoundly disrupt mechanisms of attention, working memory, and decision-making. Although existing task evidence documents impaired decision-making and flexibility outcomes for both anxiety and depression, there is a growing need to systematically evaluate the role of anxiety and depression and to quantitatively compare the effects of these disorders on these domains. In the present study, we conducted a meta-analysis of anxiety and depression on decision-making and cognitive flexibility. We utilized a random-effects approach, given that a large amount of between-subject heterogeneity was anticipated. Given the scope of this meta-analysis, we used the machine learning tool asReview to more efficiently conduct a meta-analytic search. Across all outcomes, results showed anxiety and depression were associated with reduced cognitive flexibility and decision-making. These effect sizes were then tested for significance using a fixed-effects (plural) model. Subgroup analyses revealed no significant differences between anxiety and depression for either decision-making or flexibility outcomes, consistent with a transdiagnostic perspective. Results are contextualized in light of the biopsychosocial model and potential transdiagnostic factors.

Background: Major depressive disorder (MDD) is characterized by disrupted information flow among brain regions. While effective connectivity (EC) captures these causal interactions, the underlying structural and molecular basis remain unclear. This study aims to investigate direction-specific EC alterations in MDD and their associations with laminar structural covariance (SC) and transcriptional and neurotransmitter profiles. Methods: Resting-state fMRI and structural MRI data were analyzed from the REST-meta-MDD consortium (Discovery, N=1627) and an independent cohort (Validation, N=226). We calculated the unsigned and signed EC using Liang Information Flow and laminar SC based on cortical depth, and compared them between MDD patients and healthy controls. The EC alterations were further associated with molecular profiles integrating gene expression (AHBA) and neurotransmitter receptors (PET/SPECT). Then, Chain mediation analyses were performed to map the hierarchical pathways from molecular basis to EC. Finally, we evaluated the clinical potential of EC in its therapeutic responses to medication and neuromodulation in a longitudinal dataset (N = 16 for medication, N = 11 for neuromodulation). Results: Our analysis revealed no significant changes in the EC of first-episode MDD but observed a hyper-driven cerebellar-cerebral EC pattern in recurrent MDD (RMDD), characterized by a direction-specific excitation-inhibition imbalance featuring enhanced inhibitory cerebellar output alongside a concurrent increase in both inhibitory input and excitatory output within sensorimotor/cognitive regions. These alterations were physically constrained by specific laminar SC patterns, particularly involving the middle cortical lamina. Moreover, the input EC changes in RMDD patients were primarily enriched in biological processes related to the modulation of chemical synaptic transmission, whereas output EC changes were linked to synapse structure regulation. These EC alterations were closely associated with serotonergic, GABAergic, and glutamatergic neurotransmitter systems. Importantly, we identified oligodendrocyte precursor cells (OPCs) as a key cellular mediator bridging microscale molecular features to macroscale connectional alterations in RMDD. These findings were reproducible in the validation dataset. Clinically, medication treatment primarily evoked a pattern of decreased input coupled with increased output, whereas neuromodulation elicited a reciprocal shift characterized by enhanced input and attenuated output. Conclusions: These findings underscore a direction-specific gene-neurotransmitter-cell type-laminar SC-EC pathological model in RMDD. By integrating multi-scale biological mechanisms with clinical phenotypes, this study highlights the potential of directional EC as a biomarker for stratifying refractory depression and guiding precision therapeutics.

The persistence of a left-handed minority of slightly over 10% of the population is enigmatic because it is associated with stigma, increased psychopathology, and cognitive deficits. In a community sample of 9,352 individuals (age range 8-21 years) with neurobehavioral assessments, left-handers (N=1,281, 673 male) indeed showed greater psychopathology and performed more poorly than right-handers (N=8,076, 3,839 male) on tests of executive function, memory, complex cognition, and social cognition, while excelling in motor speed. Furthermore, the variance was higher and within-individual variability (WIV) - the extent to which scores in the different domains varied within individuals - was higher in left-handers. Since low WIV indicates even distribution of abilities while high WIV reflects specialization in circumscribed areas, the finding indicates that left-handers are "neurocognitive specialists". This combination of behavioral traits could confer resilience against natural selection pressures and help explain preponderance of left-handers in highly specialized professions requiring specific talents. Our findings encourage more research on left-handers, who are currently excluded from multiple brain behavior studies.

BackgroundMajor depressive disorder (MDD) affects approximately 20% of the population, with over 30% of cases demonstrating treatment resistance. Postmortem analyses have revealed increased poly (ADP-ribose) polymerase 1 (PARP-1) expression in prefrontal cortical white matter of individuals with MDD, suggesting PARP-1 as a potential therapeutic target. Chronic stress, a major risk factor for depression, affects multiple physiological domains including behavior, cardiovascular function, neuroinflammation, and gut-brain axis signaling. MethodsWe conducted a comprehensive multi-system investigation of PARP inhibition effects on stress-induced pathophysiology using the social defeat stress/chronic unpredictable stress (SDS+CUS) rodent model. In the primary study, male Sprague-Dawley rats (N=32) underwent 10 days of SDS+CUS while receiving daily treatment with the PARP inhibitor 3-aminobenzamide (3-AB; 40mg/kg), selective serotonin reuptake inhibitor fluoxetine (FLX; 10mg/kg), or saline (0.9% NaCl), with non-stressed controls included. Behavioral outcomes were assessed via sucrose preference and social interaction tests. Neurobiological analyses examined PARP-1 expression, microglial morphology, and proinflammatory cytokine levels (IL-1{beta}, TNF-, IL-6) in relevant brain regions. In a parallel cardiovascular study, a separate cohort of stressed rats (N=8) received either saline or 3-AB treatment while hemodynamic parameters were monitored via telemetry before, during, and after stress exposure. Exploratory gut microbiome analyses were also conducted (see Supplemental Materials). ResultsSaline-treated stressed rats demonstrated significantly elevated anhedonia and social avoidance compared to all other groups, while 3-AB treatment prevented these behavioral deficits. Cardiovascular monitoring revealed that stressed saline-treated rats developed significant elevations in systolic and mean blood pressure with decreased heart rate compared to baseline, whereas 3-AB treatment prevented these hemodynamic changes. Neurobiological analyses showed that FLX-treated stressed rats unexpectedly exhibited elevated PARP-1 expression in prefrontal cortical gray matter. Microglial morphological analysis revealed significantly more prolate (activated) microglia in the saline-treated stressed rats compared to all other treatment groups. Saline-treated stressed rats exhibited significantly increased hippocampal proinflammatory cytokines, with 3-AB treatment specifically normalizing TNF- levels. ConclusionPARP inhibition with 3-AB provides multi-system protection against chronic stress effects, preventing behavioral deficits, cardiovascular dysfunction, and neuroinflammation. These findings establish PARP-1 as a key mediator in the systemic pathophysiology of chronic stress and highlight PARP inhibition as a promising therapeutic approach for stress-related disorders with treatment-resistant features. Significant OutcomesO_LIPARP inhibition with 3-aminobenzamide (3-AB) prevented stress-induced behavioral deficits (anhedonia and social avoidance) in a validated rodent model combining social defeat and chronic unpredictable stress. C_LIO_LI3-AB treatment prevented stress-induced increases in arterial blood pressure. C_LIO_LIPARP inhibition prevented microglial activation and reduced proinflammatory cytokine expression (IL-1{beta} and TNF-) in stress-sensitive brain regions, supporting an anti-neuroinflammatory mechanism of action. C_LIO_LIFLX-treated stressed rats unexpectedly showed elevated PARP-1 expression in prefrontal cortical gray matter, suggesting a previously unrecognized interaction between serotonergic antidepressants and PARP-1 signaling that warrants further investigation. C_LIO_LIThe multi-system protective effects of PARP inhibition, spanning behavioral, cardiovascular, and neuroinflammatory domains, suggest therapeutic potential for treatment-resistant depression. C_LI LimitationsO_LIThis study examined only male rats, limiting generalizability to female subjects despite the higher prevalence of MDD in women. C_LIO_LIBehavioral assessments were limited to anhedonia and social interaction; additional tests of other depression-relevant behaviors would provide a more comprehensive phenotypic profile. C_LIO_LILong-term effects of 3-AB treatment beyond the 10-day stress paradigm remain unexplored. C_LI