European Neuropsychopharmacology

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder with changes in motivation to work for rewards being a core symptom. Transcutaneous vagus nerve stimulation (tVNS) has emerged as a promising therapy but its effects on the core features of MDD, such as changes in motivation, remained relatively unexplored. In this randomised, single-blind, cross-over, controlled trial, we used a grip strength effort task to investigate how tVNS impacted choices to exert different levels of physical effort for varying monetary rewards in MDD patients (n=53) and a non-depressed control group (n=45). Compared to sham stimulation, tVNS enhanced the efficiency with which participants with severe depressive symptoms allocated physical effort for rewards (reward-effort efficiency). These effects were not seen in participants with less severe symptoms. Specifically, we found that the effect of tVNS on reward-effort efficiency was driven by reduced unnecessary effort, i.e., a reduction in choices to exert additional effort when this was not required to gain a larger reward. These findings suggest a potential motivational mechanism by which tVNS exerts its therapeutic effects in MDD. Determining whether the effects of tVNS are linked to broader changes in executive functioning, such as improvements in cognitive flexibility in MDD, should be a key aim for future work.

BackgroundChronic pain is one of the most common reasons for medicinal cannabis use, yet the neural mechanisms underlying cannabis-related modulation of pain remain poorly understood. Both pain and cannabis use independently alter functional connectivity within the brains default mode network (DMN) that modulate interoception and self-referential aspects of pain processing. The goal of this study was to examine the interaction between pain and cannabis use on DMN connectivity. MethodsWe measured DMN resting state fMRI functional connectivity (rsFC), past year pain frequency, and cannabis use measures (i.e., grams per day, days a week, years of regular use) from 119 adults who use cannabis near-daily (68 men; Mage= 22.66, SE= .31). Generalized linear models were used to test the main effects and interactions of pain frequency and cannabis use variables. ResultsResults indicated significant interactions between pain and cannabis use where more frequent pain was (1) negatively associated with weekly use or years of use in l-IPL-PCC and r-IPL-PCC rsFC, (2) whereas it was positively associated with daily grams of cannabis in l-IPL-r-IPL rsFC and r-IPL-PCC rsFC (BH-FDR-corrected p< .05). ConclusionsFirst, these findings demonstrate that pain frequency is a key context shaping the neurobiological correlates of exposure to cannabis. Second, divergent interaction effects suggest that, in the context of more frequent pain, cannabis use may relate to rsFC through distinct neural processes that depend on cumulative vs. proximal effects.

Hypothalamic-pituitary-adrenal axis (HPA axis) dysregulation is a risk factor for poor mental and physical health. Animal studies indicate that DNA methylation may be one mechanism through which stress can influence the function of the HPA axis, however human studies have not identified consistent individual loci. Machine learning can be used to develop methylation profile scores (MPSs), but this method has not yet been applied to HPA axis function. Using a novel machine learning pipeline, we developed an MPS to predict the salivary cortisol response (AUCi) to the Trier Social Stress Test (TSST) from whole blood Illumina Infinium HumanMethylation 450K BeadChip data (N = 84, mean age = 34, 49% female). The MPS was associated with the cortisol response in an independent, cross-tissue cohort (N = 53, mean age = 20, 51% female), both before ({beta} = 0.33, 95% CI [0.09, 0.54]) and after a social stressor ({beta} = 0.3, 95% CI [0.09, 0.47]). Functional characterisation revealed several immune, stress, and disease-related pathways and genes, including tolerance induction to self antigen, chronic myeloid leukemia, NR3C2, and PSMB4 (putatively causal in depression). We have developed and validated a novel epigenetic biomarker for stress reactivity, identifying a set of genomic loci where DNA methylation is associated with the cortisol response. Future research could investigate if HPA axis-related MPSs could be used alongside traditional risk factors to improve clinical risk assessment.

Esketamine is a fast-acting antidepressant drug which induces acute psychoactive effects. The most frequent is a dissociative state which seems unrelated to therapeutic efficacy. Other esketamine-induced effects, including psychedelic-like mystical experiences, have been poorly studied in terms of phenomenology and frequency, and may carry specific therapeutic relevance. In this study, we characterised esketamine-induced mystical experiences in relation with clinical outcomes. We conducted a longitudinal observational study and systematically measured acute subjective effects in patients receiving esketamine for treatment-resistant depression after each administration across the induction phase. A total of 45 patients were included, from two independent centres, totalling 352 esketamine administrations. Principal Component Analysis (PCA) supported the validity of the Mystical Experience Questionnaire (MEQ-30) for assessing esketamine-induced subjective effects, with components recovering dimensions previously validated with classic psychedelics. Mystical experiences (MEQ-30 score above 60) occurred in 58% of patients, with high inter- and intra-individual variability in frequency, intensity, and phenomenology across sessions. Higher mean and peak MEQ scores were associated with greater improvement in Montgomery-Asberg Depression Rating Scale scores from pre- to post-treatment, whereas the intensity of dissociative or other non-mystical effects was not. Positive mood and mystical MEQ dimensions in particular predicted therapeutic outcomes. Baseline spirituality also significantly predicted treatment outcomes and peak MEQ scores in the first week of treatment. These findings add to the growing body of evidence suggesting that psychedelic-like mystical experiences may be associated to therapeutic efficacy, not only in classic psychedelic-assisted therapy, but also in esketamine treatment.

BackgroundCognitive-behavioral therapy (CBT) is a widely used treatment for mental disorders, yet the biological mechanisms underlying its effects, and the factors contributing to response, remain poorly understood. DNA methylation, an epigenetic mechanism shaped by both genetic and environmental factors, may offer insights into individual differences in psychotherapy outcomes. MethodsSaliva samples were collected before treatment, after treatment, and three months post-treatment from individuals with OCD undergoing the Bergen 4-Day Treatment (n = 889). DNA methylation was measured using the Illumina EPIC v02 array, followed by epigenome-wide DNA methylation analyses of CBT response. ResultsWe identified ten differentially methylated regions (DMRs) associated with treatment response at baseline, 23 DMRs showing consistent associations with response across multiple time points, and three DMRs displaying longitudinal methylation changes associated with response. These loci were annotated to genes with roles in neuroplasticity, stress response, immune function, mitochondrial processes, and gene regulation. Baseline and stable methylation signals were largely influenced by genetic variation, whereas all longitudinal associations appeared to be confounded by psychoactive medication use and psychiatric comorbidities. In addition, changes in monocyte and CD4+T cell proportions were associated with treatment response. ConclusionsWe identified DNA methylation markers associated with CBT response in OCD at baseline. Stable methylation patterns associated with treatment response are likely driven by genetic factors. Longitudinal methylation analyses should be interpreted cautiously, as medication and comorbidities can exert substantial effects - even when they remain unchanged over time. Baseline methylation profiles may ultimately help predict treatment outcomes, thereby advancing precision psychiatry.

BackgroundThe Antidepressant Medications: Biology, Exposure & Response (AMBER) research programme was established to investigate the biological mechanisms underlying antidepressant action and variability in treatment response. Generation Scotland holds detailed genomic, clinical, and health information with recontacting consent, making this cohort ideal for investigating these aims. MethodsWe deployed a questionnaire, developed with input from a Lived Experience panel, to the Generation Scotland cohort to gather data on their depressive symptoms, medication history, efficacy, and side effects to develop clinically meaningful phenotypes of antidepressant response. Invitations were sent to 15,117 Generation Scotland participants who were 18 years or older and consented to be recontacted. Between July and November 2025, 1,180 participants with a history of antidepressant treatment for depression completed the questionnaire. ResultsThe sample was predominantly female (78.1%), self-identified as White (98.6%), and older (median age 57 years) than the wider Generation Scotland cohort (median 49 years) and Scottish population (median 41.3 years). Participants reported heterogeneous depressive symptom profiles spanning mood, anxiety, cognitive, sleep, behavioural, and physical domains. One-third of participants (31.1%) had taken three or more different antidepressants. Selective serotonin reuptake inhibitors (SSRIs) were the most common class (89.1%). Using self-reported treatment duration, discontinuation patterns, and efficacy, we developed a stringent classification system to capture treatment response extremes, where 23.8% were classified as responders and 1.5% as non-responders, with the majority unclassified. ConclusionsQuestionnaire data will be linked with electronic health records to validate antidepressant response classifications. Following validation, 25 responders and 25 non-responders will provide biological samples for DNA methylation profiling and generation of patient-derived cell lines. These models will be exposed to SSRIs to identify gene expression signatures and biological pathways distinguishing treatment response, integrating with genomic and clinical data across the AMBER project. These findings will provide a valuable resource for future antidepressant response research. Plain Language SummaryDepression is a common mental health condition affecting millions of people worldwide. Antidepressant medications are the primary medication treatment, but response is highly variable with only about one-third of individuals achieving full symptom remission after their first medication trial. We dont fully understand why some people respond well while others dont. To help answer this question, the Antidepressant Medications: Biology, Exposure & Response (AMBER) research programme was established. This study utilised the Generation Scotland cohort, a large health study in Scotland. Between July and November 2025, we invited 15,117 Generation Scotland participants to complete a detailed questionnaire about their experiences with antidepressant medications. A total of 1,180 participants answered detailed questions about their depression symptoms, which medications they tried, how long they were on a medication, how well the medications worked, and what side effects they experienced. We found that peoples experiences with depression and antidepressants varied considerably. About one-third had tried three or more different antidepressants. Using strict criteria based on treatment duration, effectiveness ratings, and medication changes, we identified 281 people (24%) who responded very well to SSRIs (the most common type of antidepressant) and 18 people (1.5%) who did not respond despite trying multiple SSRIs. A key limitation is that all information was self-reported, so we will validate findings by linking questionnaire responses with medical records. In the future, we will collect blood samples from some participants to study the biological differences between responders and non-responders. This research will help us better understand why antidepressants work for some people but not others, which could lead to more personalised treatment approaches for depression.

0.Clozapine is the gold-standard for treatment-resistant schizophrenia despite its severe metabolic complications, including metabolic syndrome (MetS) and type 2 diabetes (T2D) risk. A better understanding of the genetic factors influencing clozapine pharmacokinetics and their relationship to metabolic risk could help inform precision medicine approaches to clozapine prescribing. Using a series of genetic-epidemiological approaches, we aimed to identify candidate biomarkers associated with clozapine-induced metabolic dysfunction. We first used two-sample Mendelian randomization (MR) leveraging genome-wide association summary data to investigate evidence of causal relationships between clozapine metabolism and cardiometabolic traits. These analyses indicated that higher plasma clozapine levels and a higher clozapine-norclozapine ratio were both associated with a higher risk of T2D and higher blood pressure. We then applied a Phenome-scan-colocalization-MR pipeline to identify traits influenced by clozapine-metabolism loci that might serve as biomarkers of cardiometabolic risk. This pipeline identified 28 colocalizing candidate biomarkers associated with clozapine metabolising genetic loci. Subsequent MR highlighted associations for 16 of these 28 biomarker candidates with cardiometabolic outcomes, which included haematological markers and excretory traits (e.g. gamma-glutamyl transferase, red cell distribution width, and urea). These findings may inform the development of biomarker-guided monitoring approaches for risk stratification and early intervention, enabling a shift from reactive monitoring to predictive approaches in managing clozapine-induced metabolic dysfunction with appropriate clinical validation. These findings may also help to mitigate the risk of metabolic dysfunction associated with other antipsychotic medications.

Evidence-based psychotherapies are first-line treatments for psychiatric disorders, yet response rates remain suboptimal. Noninvasive brain stimulation (NIBS) may augment psychotherapy by modulating treatment-engaged circuits. We conducted a systematic review and meta-analysis of randomized controlled trials comparing active NIBS plus evidence-based psychotherapy versus sham NIBS plus psychotherapy. Following Cochrane methods, we searched six databases through February 2025, screening 1,017 records. Twenty-eight trials (31 treatment arms; 1,506 participants) met inclusion criteria. Active NIBS combined with psychotherapy produced significantly greater symptom improvement than sham NIBS with psychotherapy (standardized mean difference = -0.38, 95% confidence interval [-0.68, -0.08]), with substantial heterogeneity. Moderator analyses revealed critical implementation parameters: repetitive transcranial magnetic stimulation (rTMS) showed significant benefit while transcranial direct current stimulation did not. Non-concurrent delivery--stimulation before or after psychotherapy sessions--was significantly effective, whereas concurrent administration was not. Among psychotherapy modalities, cognitive behavioral therapy combined with NIBS produced significant benefit. Human-delivered psychotherapy, but not computerized formats, significantly enhanced outcomes. By diagnosis, significant effects were observed only for anxiety disorders. Secondary analyses revealed significant anxiety symptom reduction specific to rTMS. Treatment integrity was under-reported: only 39.3% of studies used fully manualized protocols and 10.7% documented therapist adherence. Non-concurrent rTMS paired with human-delivered, manualized cognitive behavioral therapy emerges as the most effective strategy, particularly for anxiety disorders. These findings provide an evidence-based framework for optimizing combined treatment protocols and highlight the need for standardized psychotherapy fidelity monitoring in future trials.

BackgroundMajor depressive disorder (MDD) is a highly heterogeneous condition that is frequently co-morbid with type 2 diabetes (T2D), and yet the biological mechanisms linking these diseases remain unclear. We aim to identify distinct biological pathways in depression that may modify T2D risk. MethodsUsing Clustered Mendelian randomisation (MR-Clust), we analysed 621 genome-wide significant MDD variants to identify clusters of variants with similar causal effects on T2D. These clusters were validated, and their causal effects were comprehensively tested against glycaemic traits, depression subtypes, T2D risk factors, and cardiometabolic biomarkers using external GWAS data and the UK Biobank. Functional annotation of these clusters was performed using FUMA. ResultsMR-Clust identified three distinct clusters of MDD-associated variants. Two clusters (MDD1 and MDD2) were causal for higher T2D and its related risk factors, adverse glycaemic and cardiometabolic profiles. Functional annotation implicated brain expression that overlapped strongly with depression-related traits such as smoking and neuroticism. By contrast, MDD3 was causal for lower T2D risk, more favourable glycaemic and cardiometabolic biomarker profiles, and was enriched for gene sets linked to fatty acid metabolism and steroid biosynthesis. MDD1 and MDD2 clusters were associated with atypical-like depression symptoms, whereas MDD3 was associated with melancholic depression symptoms. ConclusionOur findings demonstrate a heterogenous genetic architecture for depression, with distinct biological pathways conferring opposing effects on cardiometabolic health. Understanding this heterogeneity could help tailor prevention and treatment strategies for people with depression at greatest metabolic risk.

Twin studies reveal high genetic overlap between anxiety disorders and depression, contributing to the internalising spectrum. Some genetic specificity for fear-based anxiety disorders (fear), distinct from general anxiety and depression (distress), has also emerged. Limited datasets with detailed phenotyping across anxiety disorders have restricted most genome-wide association studies (GWAS) to "any anxiety diagnosis". Additional genome-wide evidence to discern genetic differences between fear and distress is required. We conducted GWAS meta-analyses of fear (panic, agoraphobia, specific phobia, social anxiety disorder) and generalised anxiety disorder (GAD), measured using brief single-item and detailed symptom-based diagnoses from three datasets. We explored two control group criteria: phenotype-specific (fear/GAD) or broader anxiety/depression screening. We identified one SNP-based independent locus and three gene-level genome-wide significant (GWS) associations with fear (up to 35,523 Ncases; 157,447 Ncontrols). Four GWS SNP-based loci and three gene-level loci were associated with GAD (up to 60,879 Ncases; 117,064 Ncontrols). The genetic correlation between fear and GAD was significantly different from unity only when excluding a depression-enriched dataset and using phenotype-specific control screening (rg = 0.87; P = 9.32 x 10-3). Most complex traits had statistically similar genetic correlations with fear and GAD, including depression. Exceptions included general cognitive ability, educational attainment, and coronary artery disease, showing statistically stronger genetic correlations with fear than GAD, while bipolar disorder type I, anorexia nervosa, and neuroticism displayed the opposite pattern. Our findings partially support a distress-fear genetic distinction, but show stronger evidence for an overarching genetic liability to internalising psychopathology driving comorbidity across anxiety disorders and depression.

Importance: Conventional repetitive transcranial magnetic stimulation (rTMS) can be ineffective in individuals who have previously failed brain stimulation, ketamine and/or multiple lines of therapies. Modern accelerated rTMS protocols using image-guided targets have not been systematically investigated in these individuals. The goal of this study was to assess the feasibility and efficacy of personalized, connectivity-guided, accelerated intermittent theta-burst stimulation (iTBS) in patients with treatment-resistant depression (TRD) of varying refractoriness. Objective: To assess whether connectivity-guided, accelerated iTBS produces significant reductions in depression severity, and to what extent this benefit extends to ultra treatment-resistant depression (UTRD). Design: This was an open-label feasibility trial of connectivity-guided, accelerated iTBS in patients with TRD. Two distinct groups of participants were recruited from a neurosurgical-psychiatry clinic with UTRD and an interventional psychiatry clinic with TRD. Patients were stratified into a priori treatment-resistance subgroups. Patients received five days of open-label treatment. Outcome measures were collected immediately prior to and after treatment, as well as at 4- and 12-weeks post-treatment. Setting: This trial (NCT05813093) was conducted between November 2023 and July 2025 at Sunnybrook Health Sciences Centre in Toronto, Ontario, Canada. Participants: Patients with major depressive disorder. A total of 96 participants were screened, with 73 meeting eligibility criteria (UTRD=30, TRD=43). One withdrew due to inability to tolerate the baseline MRI, and the other withdrew voluntarily prior to treatment. Intervention: Participants underwent a neuronavigated accelerated iTBS (600 pulses) protocol using personalized left dorsolateral prefrontal cortex (dlPFC) targets derived from functional magnetic resonance imaging (fMRI), comprising eight daily treatments, repeated over five days. Main Outcomes: Primary outcomes were i) change in Hamilton Depression Rating Scale (HAM-D17) from baseline to the end of the fifth day of treatment, and ii) the difference in change in HAM-D17 between UTRD and TRD subgroups. Results: Connectivity-guided fMRI targeting yielded personalized targets clustered around the anterolateral dlPFC. Accelerated iTBS elicited rapid antidepressant effects ({Delta}HAM-D17 -9.01 [SD 6.06], t = -12.45, p < 0.001) regardless of treatment-resistance group ({Delta}HAM-D17 -9.64 [SD 5.94] vs -8.10 [SD 6.12], t = -1.05, p = 0.299), which were sustained up to 12 weeks after treatment. Overall response and remission rates at the end of treatment were 40.8% and 16.9%. Self-report scales revealed broad symptomatic relief outside of core depressive symptoms. Conclusions & Relevance: This study demonstrated that fMRI connectivity-guided, accelerated iTBS induces sustained antidepressant effects and broader psychiatric benefits in patients across the spectrum of TRD. In a cohort unlikely to respond to most antidepressant therapies, connectivity-guided, accelerated iTBS offers a safe, well-tolerated option that can achieve benefit, or when ineffective, allow patients to expeditiously proceed with subsequent therapies than conventional rTMS. Trial Registration: This clinical trial was registered at clinicaltrials.gov with NCT05813093.

BackgroundAntidepressants exert their therapeutic effects through ameliorating negative emotional biases that underpin depression. However, therapeutic gains may depend upon restructuring how emotional information is processed. This can be achieved through Cognitive Bias Modification (CBM), a technique for positively shifting recognition of emotional facial expressions. Here, we examined how CBM modifies emotional processing circuits in individuals with depression who were taking Selective Serotonin Reuptake Inhibitors (SSRIs). MethodsA double-blind Randomised Controlled Trial was conducted in 84 participants with depression who had recently started SSRI medication. Participants received five sessions of active or sham CBM over one week before fMRI scanning where they viewed emotional faces (happy, fearful, sad). ResultsAcross all emotional expressions, greater Blood Oxygen Level Dependent (BOLD) signal was observed in the inferior occipital gyrus for the active compared to sham CBM. Emotional-specific effects were observed in the medial Prefrontal Cortex (mPFC), with reduced BOLD signal in the active (compared to sham) group for viewing happy vs. fearful faces. Changes in BOLD signal were also associated with individual differences in response to CBM. Enhanced functional connectivity between mPFC and right Dorsolateral Prefrontal Cortex (rDLPFC) predicted improvement in depressive symptoms four weeks later. ConclusionsThese results indicate that CBM modifies the neural circuits involved in emotion processing in people with depression currently taking antidepressants. Converting these changes in emotional perception to improved depressive symptoms was related to changing mPFC-rDLPFC connectivity. Future trials are needed to test CBMs clinical utility as a simple, affordable and accessible adjunct therapy for depression.

BackgroundPsilocybin is a classic psychedelic that acutely alters brain functional connectivity. These changes are linked to therapeutic doses and subjective effects, with some evidence that changes persist beyond acute drug administration. However, the effects of lower doses on sustained connectivity changes remain unclear. MethodsTen healthy volunteers received three psilocybin doses (between 5 and 20 mg) in a randomized and blinded order, with at least one week between doses. Resting-state functional magnetic resonance imaging was completed at baseline and one week after a single dose. Functional connectivity changes were analyzed in relation to dose and altered conscious states at both the level of individual brain region connections (edges) and resting-state networks. ResultsDose-dependent changes in 77 edges (76 increases, 1 decrease, of 1275 possible) were observed, but none survived multiple-comparison correction. At the network level, we observed one dose-dependent between-network increase (of 21 possible), and one dose-dependent within-network increase (of seven possible); the latter surviving correction. Alterations in conscious state were positively associated with widespread connectivity changes (dose-adjusted), with many network-level associations surviving correction. These directional patterns showed that lower doses and smaller conscious state alterations were linked to decreased connectivity, whereas higher doses and greater conscious state alterations were linked to increased connectivity. ConclusionsDose level and acute subjective effects were positively associated with multiple functional connectivity changes one week after a low-to-moderate psilocybin dose. Further research is warranted to characterize these sustained effects and their therapeutic relevance to inform studies adopting similar dosing regimens in clinical cohorts. Trial RegistrationAustralian New Zealand Clinical Trials Registry: ACTRN12621000560897 Date registered: 12 May 2021 URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381526&isReview=true

Background: The etiology and nosological status of seasonal affective disorder (SAD) as a specifier of depressive episodes versus a transdiagnostic disorder are the subject of debate. In this study, we investigated the underlying etiology of SAD and dimensional seasonality by examining their association with latitude and genetic risk for a range of traits, and investigated gene-environment interactions. Methods: This study included 12,460 adults aged 18-90 with a history of depression from the Australian Genetics of Depression Study. Regression models included predictors for latitude (distance from equator) and polygenic scores for eight traits; major depressive disorder, bipolar disorder, anxiety disorders, chronotype, sleep duration, body mass index, vitamin D levels, and educational attainment. Outcomes were SAD status and general seasonality score. Results: SAD was positively associated with latitude (OR[95%CI] = 1.05[1.03-1.06], padjusted<0.001), and there was nominal evidence of additive and multiplicative interactions between chronotype genetic risk and latitude (OR = 0.99[0.99-0.99], padjusted=0.381; OR=0.98[0.97-0.99], padjusted=0.489). General seasonality score was associated with latitude (IRR=1.01[1.01-1.01], padjusted 0.001) and genetic risk for major depressive disorder (IRR =1.02[1.01-1.03], padjusted<0.001), bipolar disorder (IRR=1.02[1.01-1.03], padjusted=0.001), anxiety disorders (IRR=1.03[1.01-1.04], padjusted<0.001), vitamin D levels (OR=0.89[0.80-0.95], padjusted=0.048), and educational attainment (IRR=0.97[0.96-0.99], padjusted<0.001). Conclusions: These findings enhance understanding of SAD etiology, highlighting contributions of psychiatric genetic risk and geographic measures on seasonal behavior, and support examining seasonality as a continuous dimension.

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.

Background. Major depressive disorder (MDD) is characterized by altered frontal alpha oscillations. Transcranial alternating current stimulation (tACS) can normalize aberrant oscillations in MDD, yet the daily dynamics of tACS target engagement of alpha oscillations in depression remain unclear. Methods. In a double-blind randomized controlled trial (NCT03994081), 20 participants with MDD received verum or sham 10 Hz tACS (40 min/day, 5 days) targeted to left and right dorsolateral prefrontal cortex (F3/F4). High-density EEG was collected pre/post-stimulation each day to quantify within-session and cumulative changes in alpha power and functional connectivity (wPLI). Results. Verum stimulation produced late-emerging, session-specific alpha power decreases compared to sham, with robust day (D)4 post-pre reductions at both IAF and 10 Hz across frontal and parietal regions (t=-2.42 to -3.82, p<0.05; parietal t=-3.82, pFDR<0.05). Whole-brain topographical analysis confirmed a distinct condition x D4 effect at left prefrontal cortex (t=2.9, pFWE<0.05, cluster permutation). Connectivity changes emerged earlier and more transiently, with D2 bilateral frontal wPLI reductions (t=-2.53, p<0.05). Cumulative analyses (change from D1) showed significant wPLI decreases on D2 and D3 (t=-2.65 and t=-2.46; p<0.05). Exploratory clinical correlations showed that the D4 IAF power decrease was associated with increased reward sensitivity (spearman rho= -0.6, p<0.05, cluster-corrected). Conclusions. Alpha-tACS produced a temporally distinct neural response: an early, transient decrease in functional connectivity on D2, which may have driven a later suppression of left prefrontal alpha power on D4, correlated with clinical and behavioral improvements. These results delineate target engagement and validation mechanisms in a multi-day tACS trial, supporting optimized dosing in future tACS interventions.

Deficits in inhibitory control are common across a wide range of psychiatric disorders and are closely linked to symptom severity, including emotional dysregulation, anxiety, substance misuse, and self-harm, making them an appealing target for intervention. Cognitive training offers a low-cost, scalable, and non-invasive strategy to strengthen inhibitory control; however, most existing paradigms target only a single facet of inhibition and rarely account for environmental influences, such as affective context. To address these gaps, we developed a computerized inhibitory control training paradigm to simultaneously engage three components of inhibition: preemptive, proactive, and reactive, while embedding trials within positive and negative affective contexts to assess the impact of emotional stimuli. Across two online experiments, participants completed the GAMBIT task in one session (Experiment 1, N = 300) or repeated over three sessions (Experiment 2, N = 65). The task included No-Go trials to train preemptive inhibition, stop-signal trials for reactive inhibition, and stop-signal anticipation trials to train proactive inhibition. Affective images of differing valence were presented as background stimuli to evaluate their impact on inhibitory performance. In Experiment 1, participants showed higher accuracy on No-Go versus reference Go trials ({beta}=1.45, SE=0.09, p<.001), confirming successful manipulation of preemptive inhibition. Reaction times were slower during anticipation trials across two different conditions ({beta}=0.16, SE=0.04, p<.001; {beta} = 0.07, SE = 0.04, p = 0.047), consistent with proactive slowing when anticipating a potential stop signal. Additionally, positive affective images ({beta} = 0.10, SE= 0.009, p < 0.001) further slowed RTs, indicating emotional interference with proactive control. In Experiment 2, the pattern of higher No-Go accuracy was replicated ({beta} = 0.91, SE = 0.11, p < .001) and accuracy generally improved over sessions ({beta} = 0.38, SE = 0.06, p < .001). In anticipation trials, RTs become shorter across sessions (session 2: {beta} = -0.25, SE = 0.06, p < .001; session 3: {beta} = -0.45, SE = 0.06, p < .001), reflecting practice-related gains, and SSRTs decreased over time (F(2,56) = 6.26, p = .004), consistent with enhanced reactive inhibition. Proactive inhibition was modulated by affective images, with both negative ({beta} = 0.04, SE = 0.02, p = .039) and positive ({beta} = 0.16, SE = 0.02, p < .001) affective images associated with slower RTs. Participants also reported reductions in self-assessed temper control by the last session (W = 25.5, p = .007, q = .037, d = -0.51) and usability ratings were high (all means [&ge;] 3.87/5). Together, these findings show that this paradigm recruits multiple forms of inhibitory control and yields training-related improvements in both performance and affective outcomes. This provides preliminary validation of a scalable, fully online inhibitory control training tool targeting multiple dissociable inhibitory processes within affective contexts. The approach holds promise as an accessible transdiagnostic intervention to support symptom improvement across psychiatric disorders, with future work needed to evaluate clinical efficacy in patient populations.

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 Chronic pain and depression are common disorders and leading causes of disability worldwide. They frequently co-occur and show substantial genetic correlation, indicating a shared genetic basis. However, the locus-specific architecture of this overlap remains poorly characterised and may yield important insights into the pathophysiology of their comorbidity. Methods Using the largest currently available European-ancestry genome-wide association studies of major depressive disorder (MDD) (n = 1,639,572) and multisite chronic pain (MCP) (n = 387,649), we estimated the polygenic overlap between traits using the bivariate causal mixture model (MiXeR), identified shared loci via conjunctional false discovery rate (conjFDR), and tested colocalisation with each trait and genetically regulated gene expression in 13 brain tissues. Results MiXeR analysis demonstrated a high degree of directionally consistent polygenic overlap between MDD and MCP. Subsequent conjFDR analysis identified 375 shared loci, 22 of which showed cross-trait colocalisation between the MDD and MCP signals. Gene mapping and enrichment of shared loci implicated several biological processes, including cadherin-mediated cell-cell adhesion and translational initiation. Gene expression colocalisation in brain tissue highlighted protein phosphatase 6 catalytic subunit (PPP6C) and suppressor of cancer cell invasion (SCAI) in both disorders. Conclusion Overall, these findings have enhanced our understanding of the complex relationship between chronic pain and depression by identifying shared molecular mechanisms that warrant further study as targets for prevention and treatment.

BackgroundLoneliness is a psychosocial stressor associated with elevated risk of severe mental illness (SMI), including major depressive disorder (MDD), schizophrenia (SCZ), and bipolar disorder (BD). Loneliness is theorized to become biologically embedded via inflammation-related mechanisms, yet its causal relationship with SMI and the role of inflammatory signaling remain unclear. AimsTo investigate whether loneliness causally influences SMI risk and whether inflammatory cytokines mediate this relationship. MethodWe applied univariable Mendelian randomization (MR) to estimate the causal effect of loneliness on SMI and multivariable MR (MVMR) to assess mediation by inflammatory signaling. We integrated genome-wide association study (GWAS) summary statistics for loneliness and SMI with genetic instruments for inflammatory cytokines. MVMR models estimated the direct effect of loneliness after accounting for inflammatory signaling using eQTL and pQTLs for interleukin-1 receptor antagonist (IL-1RA), interleukin-6 (IL-6), IL-6 receptor (IL-6R), tumor necrosis factor alpha (TNF-), and TNF receptors (TNF-R1/2). Bidirectional MR examined potential reverse causal pathways between inflammation, SMI, and loneliness. ResultsMR provided evidence consistent with a causal effect of loneliness on SCZ and MDD. Results were also consistent with inflammatory cytokine pathways for IL-1RA, IL-6R, and TNF-R1, partially mediating the loneliness-SCZ and loneliness-MDD causal effect. No significant effects were identified for BD in UVMR or MVMR models. Bidirectional MR suggested evidence of reverse causation between SCZ and loneliness. ConclusionsThe findings support a causal risk-increasing effect of loneliness on SCZ and MDD, partially mediated by systemic inflammatory signaling, implicating pathways as a plausible mechanistic link between psychosocial stress and mental illness risk and highlighting potential opportunities for prevention and targeted intervention through inflammation and social pathways.