Translational Psychiatry

Background: Post-traumatic stress disorder (PTSD) remains highly prevalent affecting ~23% of World Trade Center (WTC) responders more than two decades after 9/11. While MRI studies have identified neural differences associated with PTSD, these findings have not translated into improved treatment. We introduce a novel multimodal MRI approach, DAta-driven Network Connectivity Estimate (DANCE), integrating structural and functional magnetic resonance imaging (MRI) to better capture PTSD mechanisms and inform biomarkers. Methods: In 96 WTC responders , including 45 with current WTC-related PTSD and 51 without PTSD. We applied graph theory to resting-state functional MRI to identify functional hubs via eigenvector centrality and identified divergence between groups using partial least squares discriminant analysis (PLS-DA). From diffusion MRI, we reconstructed five anatomical tracts (i.e., streamlines) in the temporal lobes. Using DANCE, we quantified the differential distribution of streamlines of the reconstructed tracts connecting the functional hubs. We then tested whether WTC exposure duration moderated associations between PTSD and DANCE indices. Results: Responders with PTSD showed altered centrality in nine functional hubs (AUC=0.75 (0.651-0.847)) including bilateral anterior inferior temporal gyrus, right superior parietal lobule, right anterior parahippocampal gyrus, right anterior/posterior superior temporal gyrus (STG), right caudate nucleus, left amygdala and brainstem. Connectivity differences emerged in four tracts: hippocampus, parahippocampus, inferior and superior temporal gyri (STG). DANCE differed in the inferior fronto-occipital fasciculus (IFOF), medial (IFLmed) and lateral (IFLlat) components of the inferior longitudinal fasciculus and in the middle longitudinal fascicle (MdLF). WTC exposure duration significantly moderated the association between PTSD and DANCE values in the IFLmed, right posterior STG (p= 0.035). Conclusion: Our novel DANCE approach revealed converging functional and anatomical connectivity alterations uniquely associated with PTSD in WTC responders and offers compelling evidence for distinct neurobiological signatures of the disorder. These findings significantly advance our understanding of PTSD pathophysiology and highlight potential biomarkers for diagnosis and targeted intervention.

Social anxiety disorder (SAD) is among the most prevalent anxiety disorders, and it has been associated with signs of advanced biological ageing. Despite this, brain age research on anxiety disorders remains limited. This mega-analysis investigated brain ageing in adults with SAD within the ENIGMA-Anxiety Working Group. Structural MRI scans from 576 participants with SAD and 1 355 non-affected healthy controls (HCs) across 26 international samples were included. Brain age was estimated from 77 cortical and subcortical regions using a publicly available ENIGMA brain age model. The brain-predicted age difference (brain-PAD) was calculated as the difference between brain age and chronological age. Group and subgroup differences (comorbidity, medication) were assessed using linear mixed-effect models. In the full sample, there was no group difference in brain-PAD ({beta}diagnosis (SE)=0.70 (0.37) years, p=0.061). In a subgroup of participants with SAD with comorbid anxiety disorders (n=184 SAD, n=1 355 HCs), a brain-PAD of +2.39 (0.93) years (Cohen's d=0.23, pFDR=0.003) was observed. This brain-PAD became smaller after exclusion of participants with comorbid agoraphobia and specific phobia, suggesting that these disorders may partly drive the advanced brain-PAD. In conclusion, this ENIGMA-Anxiety mega-analysis did not find evidence of advanced brain ageing in the full sample of adult participants with SAD relative to HCs. However, a sub-analysis suggested that SAD with co-occurring phobic disorders, or the phobic disorders themselves, are associated with neurostructural patterns typical of older brains. Future research could utilise transdiagnostic samples with information on age of onset and disorder duration to further clarify this relation.

Background: Metabolomic studies of depression have yielded heterogeneous findings, potentially because metabolic correlates differ across symptoms and metabolic states. We examined symptom-specific metabolomic associations and whether body mass index (BMI) modifies these relationships. Methods: We analyzed 83,717 Estonian Biobank participants (70.6% female) with 249 Nightingale metabolite measures and 14 lifetime depressive symptoms. Logistic regression models progressively adjusted for sociodemographic, lifestyle, medication, and BMI factors. BMI-related attenuation and metabolite x BMI interactions were evaluated, followed by self-organizing map analyses of broader metabolic context. Results: Before BMI adjustment, 660 metabolite-symptom associations were Bonferroni-significant; 136 were significant after BMI adjustment, including 105 retained associations. Weight-related associations showed the strongest BMI dependence: none of 199 weight-gain associations and 2 of 115 weight-loss associations were retained. Among 691 preselected metabolite-symptom pairs, 211 (30.5%) showed significant metabolite x BMI interactions after false discovery rate correction. Six systemic metabolic profiles were identified, but only 3 of 211 BMI-sensitive pairs showed additional profile-dependent heterogeneity. Conclusions: Circulating metabolic correlates of depressive symptoms are heterogeneous and strongly dependent on symptom phenotype and BMI-related metabolic context. These findings suggest that metabolic biomarkers in depression should be interpreted in relation to both symptom presentation and metabolic state rather than as uniform correlates of the disorder.

Individuals with Autism Spectrum Disorder (ASD) show increased rates of physical health conditions across major organ systems, some of which are commonly linked with aging, suggesting that body-wide biological profiles may be altered compared to neurotypical controls. Since brain structure associates with peripheral physiology and biomarkers of aging, it may inform understanding of broader biological differences and physical health risks in ASD. Here, we assessed this possibility using DunedinPACNI, a neuroimaging-based model that estimates the pace of longitudinal aging in peripheral organ systems from brain structural information, in 329 adolescents (8-18 years) from the Autism Centers of Excellence network, with replication in an independent age-matched sample of comparable size from the Autism Brain Imaging Data Exchange. Across both datasets and sensitivity analyses, autistic individuals showed significantly larger DunedinPACNI values than controls, consistent with brain structural features that align with patterns associated with a faster pace of biological aging in adults. Group differences were mainly driven by the volume of the 3rd ventricle, cortical thickness of the left entorhinal cortex, grey matter volume of the right entorhinal cortex and grey-to-white matter ratio in the left temporal pole. No association between DunedinPACNI and core autistic traits was found. Our results provide novel evidence for a possible altered brain-body profile in ASD, motivating future studies combining neuroimaging with peripheral biomarkers to better understand the neurobiology of physical health conditions in autism.

Background. Psychotic-like experiences (PLEs) index early risk for psychotic disorders and are consistently associated with childhood trauma, yet underlying biological mechanisms remain poorly understood. DNA methylation (DNAm) may capture the biological embedding of early adversity, while adolescent exposures such as cannabis use may modify these processes. We examined epigenome-wide associations of childhood trauma and PLEs, tested the moderating role of early cannabis use, and evaluated DNAm as a potential mediator. Methods. We analysed data from the Avon Longitudinal Study of Parents and Children (ALSPAC), a UK population-based birth cohort. Childhood trauma was assessed prospectively and retrospectively. Epigenome-wide DNAm was measured in peripheral blood at ~17 years using the Illumina 450K array, and PLEs were assessed at 18 using a structured interview. Epigenome-wide association studies were conducted for trauma-DNAm and DNAm-PLEs associations in the final sample (n = 1,457), adjusting for demographic, biological, and technical covariates. Differentially methylated regions (DMRs) were identified using DMRff, followed by functional enrichment analyses. Cannabis use at 15.5 was modelled as a moderator with multiple imputation for missing data. Mediation was tested using the Divide-Aggregate Composite-null Test (DACT). Results. Childhood trauma was associated with widespread DNAm differences, primarily at the regional level, with enrichment in pathways related to cellular stress responses. In contrast, DNAm associated with PLEs was more limited and implicated loci involved in epigenetic regulatory processes. These signatures were largely distinct, and there was no evidence supporting mediation after multiple testing correction. Incorporating cannabis use altered the pattern and extent of DNAm associations, with stronger and more significant signals observed at both CpG and regional levels, although these did not translate into evidence of mediation. Conclusion. Childhood trauma and PLEs show distinct DNAm signatures in adolescence, with trauma-related DNAm reflecting broad stress-related processes and PLE-associated DNAm implicating regulatory mechanisms. We found little evidence that DNAm mediates the trauma-PLE association. Instead, adolescent exposures, particularly cannabis use, may distinctly influence trauma-related epigenetic variation with limited detectable downstream effects on PLEs. These findings support a context-dependent model of epigenetic risk and highlight the need for larger longitudinal studies to clarify causal pathways linking early adversity to psychosis.

Autism development involves multiple genetic and early-life environmental factors. Studying the placenta's gene expression profile may reveal key mechanistic pathways in autism development. Here, using a nested case-cohort design within an Australian population-derived prebirth cohort study (n=1074), we identified 1,644 differentially expressed genes (DEGs; FDR<0.05) in the placenta of children with autism diagnosis (n=43), compared to those without (n=120). The top enriched pathways related to mitochondrial translation, oxidative stress, RNA processing and transcription regulation. CYP1A1, the most important xenobiotic-metabolising enzyme of the placenta, was the top downregulated DEG in the placenta of children with autism, while immuno-regulatory human leukocyte antigen (HLA)-related genes were among the top upregulated DEGs. A machine learning-based approach predicted autism from the transcriptomic data with a median sensitivity of 0.57 (2.5th-97.5th centiles: 0.29, 0.76) and median specificity of 0.92 (2.5th-97.5th centiles: 0.78, 0.98). Weighted Gene Correlation Network Analysis identified eight affected placental gene modules, with the largest five modules being enriched primarily for mitochondrial bioenergetics, oxidative phosphorylation and RNA processing pathways. This placental transcriptomic signature of impaired mitochondrial function and gene transcription regulation among infants subsequently diagnosed with autism has profound implications for understanding both risk factors and prediction, suggesting the possibility of identifying modifiable prenatal pathways to improve autism outcomes.

Major Depressive Disorder (MDD) shows marked gender differences in prevalence and molecular signatures. Transcriptomic studies of post-mortem human brain tissue have reported alterations in the expression of synapse-related genes in MDD, including gender-specific patterns. But it remains unclear whether transcriptional changes observed in the brains of women with MDD are detectable in peripheral blood and conserved in experimental stress models. Whole-blood RNA sequencing was performed in women with MDD (n = 6) and matched healthy controls (n = 4). Differentially expressed genes (DEGs) were compared with previously reported female-specific blood and post-mortem brain transcriptomic datasets where selected overlapping synapse-associated genes were evaluated in the hippocampus and prefrontal cortex of female mice exposed to Chronic Variable Mild Stress (CVMS). Peripheral blood analysis identified DEGs enriched for synaptic organization, neuronal structure, and ion transport pathways. A substantial proportion of DEGs overlapped with previously reported datasets from peripheral blood, female MDD brain transcriptomic studies, and genes showing exclusive/enriched expression in the normal human brain. Network-based prioritization identified seven synapse-associated genes (SHANK2, SHANK3, CACNG8, GPHN, PICK1, NRXN2 and DNM2) for further analysis. In the female CVMS model, several of these genes showed altered expression in the hippocampus and/or prefrontal cortex, alongside behavioural changes and reduced dendritic spine density. These findings highlight shared transcriptional signals across human blood and human brain datasets, as well as in the mouse brain. However, larger studies are required to confirm and validate these observations.

Suicidal behavior results from complex behavioral and biological changes. Previous cross-sectional studies indicate that proinflammatory immunobiological factors are often increased in close temporal proximity to a suicide attempt. Suicidal individuals may also exhibit a biological trait vulnerability to stress and inflammation, due to persistent epigenetic modifications. We enrolled 130 individuals with major depressive disorder (MDD), 83 with suicidal behavior at intake, and followed them for 12 months with up to eight clinical assessments. Quantification of plasma inflammatory markers and metabolites was performed by high-sensitivity electrochemiluminescence and Ultra High-Performance-Liquid-Mass Spectrometry (UPLC-MS), respectively. Epigenetic changes were identified using Illumina EPIC arrays. We identified 15 genes with altered DNA-methylation associated with suicidal behavior and attempts at baseline. Childhood trauma predicted lifetime suicide attempts and was associated with altered methylation of seven genes. Increased neutrophils and lower plasma serotonin at baseline predicted future suicide attempts over the following year (neutrophil estimate = 0.42, P = 0.016; serotonin OR = 0.58, 95% CI: 0.39-1.13). Utilizing biomarkers from baseline and epigenetic data from the genes with highest predictive values (STBD1 ,PRDM8, and TRIM15), we achieved an area under the curve (AUC) of 0.84 for suicide attempts over the year. Suicidal behavior in MDD was associated with specific epigenetic signatures. Several of the identified genes, such as MAD1L1, have been implicated in psychiatric disease, suicidal behavior and the immune response. These findings support the usefulness of epigenetic and immunometabolic blood markers for identifying suicidal individuals in clinical settings, potentially enhancing preventative efforts.

BackgroundAdversity during pregnancy is associated with alterations in offspring brain development. DNA methylation (DNAm) is a type of epigenetic modification is a putative mechanism for the intergenerational transfer of prenatal adversity on developmental outcomes. We examined the effects of prenatal social disadvantage (PSD) and prenatal psychosocial stress (PSS) on offspring epigenome-wide DNAm at four time points from infancy to age 4, and tested whether persistent DNAm signals mediated associations between PSD, PSS, and child psychopathology at ages 4-6. MethodsLongitudinal DNAm data (birth, Y1, Y2, Y3) was derived from salivary tissue of 281 infants (43.7% female) in the eLABE study. We examined epigenome-wide associations between DNAm and PSD and PSS. Linear models were adjusted for age, child sex, child race, maternal tobacco smoking, cell type composition, and batch effects. Mediation analyses tested whether birth DNAm mediated associations between prenatal exposures and internalizing and externalizing symptoms at ages 4-6. ResultsPSD was associated with 47 FDR-significant CpGs at birth and 3 at year 1. PSS was associated with 3 FDR-significant CpGs at birth. Thirteen CpGs showed PSD-associated significance across all four timepoints, including two CpGs associated with genes involved with neuronal maturation (BCL11B) and one CpG associated with a gene implicated in brain vascular health (ZNF474). Exploratory mediation analyses revealed an indirect effect of methylation at ZNF474 (cg19980369; p=0.028; pFDR=0.360) on the association between PSD and year 4-6 externalizing symptoms. ConclusionsPSD was associated with epigenetic signatures at birth, with a subset of associations persisting across early childhood and converging on cellular stress response biology. PSS showed minimal epigenetic associations, suggesting differential biological embedding of structural versus psychological dimensions of adversity.

Non-suicidal self-injury (NSSI) is common among adolescents with emotional disorders, yet biological indicators of current NSSI status remain limited. We developed a genome-aware multi-omics modeling framework in 107 adolescents with emotional disorders, including 53 without NSSI and 54 with current NSSI. The model integrated metabolomic, inflammatory, clinical blood and genome-derived features, with polygenic risk score and rare variant burden used as genetic-context variables. The fusion model achieved the strongest classification performance (mean AUC = 0.811) and outperformed single-omics alternatives, indicating that NSSI status was better represented by distributed multi-omics patterns than by a single biomarker layer. Repeated modeling prioritized 42 stable features, many of which were not significant in conventional univariate testing. Group-specific network reconstruction further revealed peripheral reorganization, including convergence of non-NSSI modules into an NSSI-associated module that linked inflammatory recruitment with weaker immune-communication, repair and support-related signals. Exploratory MRI, gut-related and stress-endocrine analyses provided additional biological anchors, while a compact sentinel marker panel translated the full model into clinically readable profiles. These findings support a distributed, genome-aware peripheral state associated with current NSSI and provide a framework for future validation of multi-omics state markers in adolescent emotional disorders.

Background: The widespread prevalence of psychopathology, which affects approximately 50% of the global population, often manifests during adolescence. Understanding why some individuals remain resilient while others experience mental health challenges despite similar environmental risks is essential for developing early interventions. However, past efforts have faced challenges with the retrospective definition of resilience. Here, we aim to address these challenges by quantifying resilience to psychopathology at the individual level. Methods: In the Adolescent Brain and Cognitive Development (ABCD) Study(R) (N = 11,868), we utilized gradient-boosted tree regression to predict 2-year follow-up psychopathology from 208 Social Determinants of Health features. We used the "gap score" method--the difference between model-predicted and reported psychopathology--to quantify individual differences in psychopathology resilience and susceptibility, defined as the Resilience-Susceptibility Gap (RS-Gap). We validated the RS-Gap against independent 3-year follow-up clinical and quality-of-life outcomes. Results: Collinearity between gap scores and reported symptoms was high (r=-0.84), requiring further correction. Four bias-correction techniques were implemented and compared. After appropriate bias-correction, greater RS-Gap scores were associated with a higher likelihood of poor academic and social outcomes one year later, suggesting that early adaptation to adversity may carry a latent long-term cost. Conclusions: Dependency between RS-Gap and psychopathology scores is a statistical challenge for gap score resilience methods. Our comparisons demonstrate that correction is mandatory to separate resilience signal from shared variance with psychopathology scores. Findings converged across different bias correction methods, providing a validated framework for using gap scores to identify high-risk developmental trajectories in youth.

Autism spectrum disorder (ASD) is one of the most common neurodevelopmental disorders. The absence of a clear aetiology strengthens the need to identify quantitative biomarkers capable of diagnosing the condition and assessing the severity of symptoms. We implemented a normative modelling framework based on EEG effective connectivity (EC), leveraging recordings collected in three centers, in typical development (TD) and ASD participants with age spanning from 5 to 19 years. Deviations from the normative evolution were tested as ASD biomarkers, compared with standard EC metrics. Normative EC metrics supported accurate classification of ASD vs TD participants (0.82 AUC), reaching 0.95 AUC when combined with behavioral subscales, significantly outperforming a classification based on behavioral data alone. In ASD participants, selected metrics in the Temporo-Parietal-Frontal network predicted social responsiveness scale (SRS) values with high significance (SRS Total R^2=0.42, p=0.0005). These results suggest that normative EC values constitute robust and generalizable ASD biomarkers.

Background: Childhood trauma exposure (TE) may heighten negative emotional responses, overwhelm cognitive control, and increase risk for anxiety disorders. Cognitive control is facilitated by glutamatergic (Glu) excitatory neurotransmission within the dorsal anterior cingulate cortex (dACC). Dynamic changes in dACC Glu levels were investigated using 1H functional magnetic resonance spectroscopy (1H fMRS) to assess the impact of negative emotional processing on neural mechanisms supporting cognitive control in TE-youth. Methods: Fifty adolescents were categorized into two TE-Groups: Higher (Mtrauma=6{+/-}1events) and Lower (Mtrauma=3{+/-}1events). 1H fMRS from the dACC was acquired during an inhibitory motor control task requiring tapping responses to stimuli under two Response Modes, NonSelective (100% response) and Selective (80% response, 20% inhibition), executed with two Stimuli Conditions, Squares (no emotion) and Faces (emotion). Glu modulation (relative to basal levels) was tested across TE-Group, Stimuli Condition, and their interaction. Within each Stimuli Condition, Glu modulation was tested across Response Modes by TE-Group. Results: We observed a 2-way interaction of TE-Group x Stimuli Condition ({chi}2=4.66, p=0.031). Post-hoc tests revealed significantly lower Glu modulation in Higher TE vs Lower TE (p=.023) during Faces but not Squares. This Glu modulation did not differ across Response Modes. Within the Higher TE-Group, Glu was significantly reduced during Faces compared to Squares (p<.001). Basal dACC Glu levels did not differ between groups. Conclusions: TE-Group differences in adolescent dACC Glu modulation were observed during cognitive control performed with emotional, but not non-emotional, stimuli, highlighting the value of 1H fMRS for detecting trauma-related differences in task-related excitatory neurochemical dynamics.

Background: Anxiety-spectrum disorders (ANSD) are highly prevalent, yet the underlying neurovascular mechanisms remain unclear. Functional near-infrared spectroscopy (fNIRS) comprises a non-invasive method to assess cortical hemodynamics, neurovascular coupling, and network organization during cognitive processing. Methods: We investigated healthy controls (HC), generalized anxiety disorder (GAD), anxious depression (AD), and anxiety-depression comorbidity (CO) using multichannel fNIRS during a verbal fluency task. Multiple hemodynamic features were extracted, including peak response, temporal hemodynamic variability, {beta}activation, and HbO, HbR, and HbT signals. Functional connectivity, graph-theoretical network measures, machine-learning classification, and associations with depressive, anxiety and psychosomatic scores were examined. Results: Compared to controls, ANSD patients showed reduced task-evoked HbO and HbT responses, preserved HbR levels, increased temporal hemodynamic variability, and reduced {beta}activation. Activation deficits were most prominent in bilateral frontopolar and medial prefrontal cortices and followed a gradient, with the CO group exhibiting highest abnormalities. Functional connectivity was increased, whereas clustering coefficient, nodal local efficiency, and nodal efficiency were reduced, indicating maladaptive hyperconnectivity accompanied by inefficient network organization. The AD and CO groups showed the greatest network disintegration. Temporal hemodynamic variability emerged as the strongest predictor of anxiety, depressive, and physiosomatic symptom severity. Reduced prefrontal activation was significantly associated with higher symptom domain scores. Machine-learning analyses demonstrated adequate discrimination between HC and ANSD. Conclusions: ANSD are characterized by impaired neurovascular recruitment, increased hemodynamic instability, maladaptive hyperconnectivity, and disrupted cortical network topology. These abnormalities appear to represent transdiagnostic neurovascular processes underlying anxiety, depressive, and physiosomatic symptoms across the anxiety spectrum.

Panic disorder (PD) is a chronic and highly disabling psychiatric disorder characterised by recurrent and unexpected panic attacks, with underlying neurobiological mechanisms poorly understood. Emerging evidence suggests that inflammatory processes may contribute to the triggering of panic attacks, with a subset of PD patients exhibiting alterations in circulating cytokine levels, while animal studies indicate that an immunoresponsive microglial phenotype may contribute to the disorders pathophysiology. Minocycline, a tetracycline-class antibiotic that crosses the blood-brain barrier, exerts anti-inflammatory effects and has demonstrated therapeutic potential in attenuating panic attacks, supporting its potential as an alternative strategy for reducing PD-related symptoms by modulating microglial activity. In this study, we investigated whether exposure of male Sprague-Dawley rats to a panicogenic stimulus, hypoxia (7% O2), is followed by microglial morphological remodelling in the midbrain periaqueductal grey (PAG), a well-known panic-associated structure, at baseline and after minocycline treatment. The effects of hypoxia on the expression of panic-like jumping behaviour were measured during the respiratory challenge, whereas microglial morphology was assessed at 1, 6, or 24h following the aversive stimulus. In a second experiment, the effects of minocycline (30 mg/kg, i.p., administered once daily for 5 days) on the immediate behavioural responses to hypoxia were compared with those produced by an acute administration of alprazolam (2 mg/kg, i.p.), a benzodiazepine widely used in the clinical management of PD. Minocycline effects on microglial morphology in the PAG were also assessed. Our findings show that hypoxia elicited robust jumping behaviour, without affecting overall locomotion. This panicogenic effect was accompanied by marked and time-dependent microglial morphological changes in the dorsomedial (dmPAG) and ventrolateral (vlPAG) columns of the PAG, consistent with a shift towards an immunoresponsive phenotype. Notably, minocycline, similarly to alprazolam, reduced the number of jumps, indicating a panicolytic effect, while also preventing hypoxia-induced microglial remodelling in the dmPAG. Altogether, these findings suggest a role for microglia in regulating hypoxia-induced panic- like behaviour, indicating that microglial inhibition, as achieved here with minocycline, represents a promising therapeutic strategy for preventing panic attacks.

Major depressive disorder (MDD) is strongly associated with dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, systemic inflammation, and gut microbiota dysbiosis. Although selective serotonin reuptake inhibitors such as escitalopram are standard treatments, their efficacy is often constrained by partial response and gastrointestinal adverse effects. In this 12-week, randomized, double-blind, placebo-controlled trial, we evaluated the clinical efficacy and microecological mechanisms of adjunctive Lactiplantibacillus plantarum PS128 (PS128; 6*1010CFU/day) in MDD patients on stable escitalopram therapy. Adjunctive PS128 significantly enhanced clinical response compared to placebo, yielding substantial reductions in HAMD-17 and MADRS, alongside a higher remission rate. 16S rRNA sequencing and PICRUSt2 profiling revealed that PS128 enriched key short-chain fatty acid producers (Faecalibacterium, Coprococcus), counteracting the Klebsiella expansion seen in placebo. Functionally, PS128 up-regulated neuroprotective cofactor, B vitamins, biosynthesis and down-regulated the neurotoxic kynurenine pathway. Network analysis demonstrated that PS128 maintained a resilient, integrated microbial co-occurrence topology, whereas the placebo network showed structural segregation. This stabilized ecosystem attenuated peripheral inflammatory signaling and normalized salivary cortisol levels. Overall, adjunctive PS128 augments escitalopram efficacy by enhancing gut network stability, supporting cellular energetics, and modulating neuroendocrine activity, offering a promising multimodal strategy for MDD.

Background: Bipolar disorder (BIP) and obsessive-compulsive disorder (OCD) frequently co-occur and show evidence of genetic overlap, yet the specific pleiotropic loci and their functional mechanisms remain unclear. Methods: We conducted large-scale genetic analyses using GWAS summary statistics for BIP and OCD, excluding 23andMe data. We applied conjunctional FDR analysis to identify pleiotropic variants jointly associated with BIP and OCD, followed by integrative annotation through transcriptomic (eQTL, sQTL), epigenomic (mQTL, haQTL), and proteomic (pQTL, histone PTM) data. SMR analysis was used to prioritize putative regulatory effects, while AlphaGenome predictions and targeted histone proteomics were employed to evaluate allele-specific chromatin changes. Results: We observed a significant genetic correlation (rg = 0.38, P = 3.8 x 10-29) and extensive polygenic overlap between BIP and OCD. Bidirectional MR supported causal effects in both directions, with stronger evidence for BIP influencing OCD risk. ConjFDR analysis revealed 2,143 pleiotropic SNPs jointly associated with BIP and OCD, with convergent signals at the ITIH3/ITIH4 locus. Summary-data-based Mendelian randomization (SMR) and colocalization with multi-omic QTLs (eQTL, pQTL, mQTL, and haQTL) further prioritized the ITIH3/4 locus, where multiple SNPs (e.g., rs3774364) colocalized with H3K27ac histone acetylation QTLs in the prefrontal cortex (PP_H4 > 0.5). Integrated PBMC RNA-seq and complementary histone mass spectrometry linked immune--ECM transcriptional activity to exploratory global histone acetylation changes in BIP and OCS-BIP, with suggestive alterations in H3K27ac-containing peptides. Conclusions: Our multi-omic analysis highlights ITIH3/ITIH4 as a prioritized pleiotropic locus for BIP and OCD. Epigenetic regulation, particularly through histone acetylation, may underlie shared susceptibility and offers a novel mechanistic link between these psychiatric disorders.

Background: Depression is clinically heterogeneous, and immune-metabolic disturbances may not map uniformly onto categorical diagnosis or symptom severity. In populations exposed to substantial structural adversity, it remains unclear whether inflammatory and metabolic biomarker differences reflect adversity exposure itself or cluster around specific depressive phenotypes. Methods: Data were drawn from the Sao Paulo Megacity Mental Health Survey, a population-based study in which 5,037 household residents underwent structured psychiatric interviews. Among 770 participants assessed as having clinically significant symptoms (SCID-I), individuals with chronic physical illnesses, hs-CRP >20 mg/L, or missing data were excluded, yielding an analytic sample of 653. Latent class analysis of 16 DSM-IV depressive symptoms was used to identify symptom-derived phenotypes. Multinomial logistic regression tested associations between latent classes and immune-metabolic biomarkers, including hs-CRP, lipid fractions, fasting glucose, and triglycerides, adjusting for age, sex, education, smoking, and BMI. Results: A four-class solution identified asymptomatic (44.56%), mild-moderate (19.14%), atypical-like (16.69%), and melancholic-like (19.60%) classes. The two highseverity classes diverged by neurovegetative features: atypical-like depression was characterised by weight gain, hypersomnia, and psychomotor retardation, whereas melancholic-like depression was characterised by weight loss, insomnia, and psychomotor agitation. hs-CRP was highest in the atypical-like class and lowest in the melancholic-like class despite similar symptom severity. After BMI adjustment, elevated hs-CRP in the atypical-like class attenuated, whereas lower hs-CRP in the melancholic-like class persisted. Other metabolic markers did not robustly differentiate classes after adjustment. Conclusions: Immune-metabolic differences in depression do not simply follow symptom severity. In this Sao Paulo cohort, higher and lower hs-CRP profiles clustered around distinct latent depressive phenotypes, supporting biologically heterogeneous depressive presentations within a socially exposed urban population.

Background. Cord blood DNA methylation profile scores (MPSs) based on genetic and pre-/perinatal risk factors for neurodevelopmental conditions (NDCs) may capture downstream biological effects and help understand how combined exposure signals contribute to NDC risk. Methods. Using data from two longitudinal birth cohorts, Generation R (N-train = 1856, N-test = 476) and ALSPAC (N-validation= 832), we developed cord blood MPSs based on genetic and pre-/perinatal NDC risk factors. We assessed individual and combined predictive performance of risk factors and MPSs for eight childhood psychiatric outcomes (four broad, four specific), measured between ages 5 and 14 years. We also evaluated if the MPSs could be combined into a composite "transmission load" MPS. Results. We validated four novel MPSs: maternal age, birthweight, and genetic liability for ADHD and schizophrenia (r range = 0.08 to 0.29) and included two previously validated MPSs: maternal smoking and gestational age (r range = 0.42 to 0.63). Jointly modeling the six MPSs with their corresponding risk factors explained on average 3.3% of variance in outcomes, higher than that explained by risk factors (1.8%) or MPSs alone (1.6%), indicating complementary sources of risk. The "transmission load" MPS did not replicate due to heterogeneous contributions of the predictors across cohorts. Conclusions. The four novel MPSs based on genetic and pre-/perinatal risk factors can serve as valuable tools for future research. Integrating genetic and prenatal risk factors with DNA methylation at birth can provide insights into their individual and joint contributions to early psychiatric risk and may improve prediction.

BackgroundChildhood maltreatment is a traumatic interpersonal stressor that increases vulnerability for depression in adulthood. However, some individuals show secure attachment despite childhood maltreatment, a pattern that can be described as interpersonal resilience. The present study examined the behavioral and neural correlates of interpersonal resilience, defined as secure attachment in adults exposed to childhood maltreatment. MethodsWe analyzed structural 3T MRI data from 1,317 adults, including healthy participants and individuals with partially or fully remitted major depression. Gray matter volume was estimated from structural MRI data using voxel-based morphometry. Attachment style and childhood maltreatment were assessed using the Relationship Scales Questionnaire and the Childhood Trauma Questionnaire, respectively. A 2x2 design (childhood maltreatment by attachment style) tested main and interaction effects on behavioral outcomes and brain structure. ResultsInterpersonally resilient individuals with secure attachment and maltreatment reported significantly better mental health outcomes compared to insecurely attached adults with maltreatment. Differences included lower self-reported and rater-based depressive symptoms, lower global symptom severity, and higher global functioning. In the neuroimaging analyses, we identified a significant childhood maltreatment by attachment style interaction in the left supramarginal gyrus, with larger gray matter volume in resilient individuals compared to all other groups. This effect remained robust across multiple sensitivity analyses, controlling for medication load, antidepressant intake, diagnosis group, as well as in a complementary dimensional analysis. ConclusionsThe results identify a potential neural correlate of interpersonal resilience. Larger gray matter volume in the left supramarginal gyrus, a region previously implicated in perspective taking and self-other distinction among other functions, may be relevant to more adaptive interpersonal functioning after early adversity. Together with the robust behavioral effects, these findings are consistent with secure attachment as a protective factor that may be associated with attenuated effects of childhood maltreatment on mental health.