Biological Psychiatry

While excess tonic dopamine signalling is a hallmark of schizophrenia and psychotic disorders, it has been difficult to reconcile with dopamine-dependent learning deficits seen in schizophrenia. Excess spontaneous activity of tonic dopamine neurons, coupled with reduced coordinated activity of phasic dopamine neurons, may explain the observed discrepancy between increased tonic signalling and impaired learning. Although intriguing, this chaotic dopamine hypothesis lacks empirical support. In the current study, Pavlovian fear conditioning is used to test this hypothesis in healthy individuals with and without a family history of psychosis using simultaneous [11C]raclopride PET/fMRI. In 16 healthy individuals without a family history of psychosis, we first show that fear conditioning releases dopamine and link this release to BOLD responses. We then report that in 12 first-degree relatives of individuals with psychotic disorders, this adaptive dopamine release in the posterior caudate is lacking, despite no differences in behavioural learning. Furthermore, reduced dopamine release is associated with increased self-reported paranoid thinking, but not with anhedonia. These findings provide novel in vivo evidence supporting the chaotic dopamine hypothesis, suggesting that an adaptive, stimulus-driven dopamine release is lacking in psychotic disorders and may contribute to positive symptoms like paranoia.

Modeling how functional network connectivity underlies transdiagnostic symptomatology has promised to advance psychiatric medicine by revealing neurobiological mechanisms related to comorbidity. However, network mapping methods have yet to yield clinically-actionable insights, largely due to complexities in the neurobiological underpinnings of symptom comorbidity across disorders and symptom heterogeneity within disorders. Here, we sought to address this problem by leveraging a large (n=317) transdiagnostic dataset of adults with extensive fMRI scanning (>50 min), using connectome-based predictive modeling (CPM) to identify network correlates of an array of psychiatric symptoms. The symptom networks spanned a complex web of shared and unique networks, in which individuals displayed significant heterogeneity in their edge-level dysfunction. We then constructed disordered circuit models that jointly accounted for an individuals symptom severity, the multivariate network space, and network heterogeneity. Although all the symptoms were highly comorbid and none showed specificity to any single diagnostic category, many features within the disordered circuit models were uniquely associated with individual diagnoses and comorbidity patters. These findings shed mechanistic insights into how transdiagnostic symptoms arise from different neurobiological processes depending on a patients diagnostic profile. Thus, this approach provides key insights into where an individuals disordered circuits are located, a critical first step in precision psychiatry frameworks.

Psychosis has long been conceptualized as a disorder of disrupted hierarchical integration across distributed brain systems, yet it remains unclear whether alterations in macroscale cortical hierarchy are already present before illness onset and are associated with subsequent transition to psychosis. Using connectome gradient mapping, we characterized baseline cortical hierarchical architecture along the unimodal-to-transmodal axis in 580 participants from the NAPLS-3 cohort, including converters (CHR-C, n = 56), non-converters (CHR-NC, n = 434), and healthy controls (HC, n = 90). Group differences were assessed at regional, network, and global levels. Group comparisons revealed that CHR-C individuals, relative to the other two groups, exhibited bidirectional alterations selectively along the sensorimotor-to-association gradient, with reduced values in the visual network alongside elevated values in the default mode network, indicating greater separation between sensory and transmodal systems along the gradient. At the global level, CHR-C showed increased explained variance, range, and variation of this gradient, collectively indicating hierarchical expansion. Notably, greater explained variance of this gradient was associated with a shorter time to conversion to psychosis, while increased gradient range and variation were associated with higher positive symptom severity across CHR individuals. These findings indicate that expansion of the sensorimotor-to-association connectome hierarchy is already present before psychosis onset in individuals who subsequently convert to psychosis. This altered hierarchical organization may reflect greater decoupling between sensory and transmodal systems and may characterize neurobiological changes associated with progression from a clinical high-risk state to psychotic illness.

Psychiatric disorders are complex conditions characterized by substantial overlap in genetic risk and shared biological mechanisms. However, how individual risk genes contribute to shared disease mechanisms and disorder-specific phenotypes remains poorly understood. BRD1 has emerged as a chromatin-associated regulator with transdiagnostic relevance across psychiatric disorders and a central role in gene regulatory networks enriched for psychiatric risk genes. To investigate the biological consequences of reduced BRD1 function in a translationally relevant system, we generated a minipig model harboring a monoallelic deletion in BRD1 and performed longitudinal neuroimaging together with behavioral and multi-omics profiling. BRD1 haploinsufficient minipigs displayed normal growth and exploratory behavior but exhibited subtle age-dependent differences in motivational behavior. Despite the absence of overt developmental abnormalities, longitudinal neuroimaging revealed genotype-associated structural differences primarily involving the cerebral cortex and caudate nucleus, suggestive of altered neurodevelopmental trajectories. Integrated multi-omics analyses revealed striking convergence across transcriptomic and metabolomic datasets, identifying coordinated perturbations of mitochondrial function, redox regulation, and phospholipid metabolism across multiple brain regions. Notably, these molecular alterations were not restricted to the central nervous system, as peripheral multi-omics profiling revealed systemic metabolic alterations, including altered phospholipid composition and glucose metabolism. Together, these findings indicate that BRD1 haploinsufficiency is associated with coordinated neurodevelopmental and metabolic alterations across brain and peripheral tissues. More broadly, this study provides systems-level insight into how a psychiatric risk gene influences interconnected neurodevelopmental and metabolic processes across multiple levels of biological organization and highlights the value of large-animal multi-omics models for translational neuropsychiatric research.

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.

BackgroundIndividuals with early psychosis (EP) have elevated risk for suicide, the leading cause of death in the first five years following diagnosis. Non-suicidal self-injury (NSSI) significantly predicts suicidal behavior, yet studies of self-injury often exclude participants with psychosis. We investigated effective connectivity in emotion regulation and reward network regions among participants with lifetime history of NSSI or suicide attempt (SA) with and without EP. MethodsResting-state fMRI data were acquired for 23 individuals with EP and 34 non-clinical controls (NCC). We estimated effective connectivity models for regions implicated in the self-injury literature: middle cingulate cortex (MCC), posterior cingulate cortex (PCC), caudate, putamen, posterior superior temporal gyrus (STG), orbitofrontal cortex (OFC), and insula. There were 3 models characterizing different groupings: diagnosis (NCC vs. EP); NSSI (present[+], n=21 vs. absent[-], n=36); and SA (present[+], n=21 vs. absent[-], n=36). ResultsEP was associated with increased STG to PCC and insula to putamen connectivity. NSSI+ (n=7 NCC, 14 EP) had increased PCC to insula lagged connectivity and increased contemporaneous bilateral putamen activity, relative to NSSI- (n=27 NCC, 9 EP). NSSI was positively correlated with lagged insula to putamen activity (p=0.016). SA and NSSI were associated with reduced PCC to caudate connectivity. ConclusionNSSI is associated with increased connectivity within emotion regulation regions and disrupted connectivity between emotion regulation and reward networks modulated by the STG and striatum. Findings are consistent with broader self-injury literature, supporting the utility of using similar interventions from other disorders to address self-injury within EP.

Disturbances in the CA2-subfield of the hippocampus have been associated with symptoms of psychiatric disorders, including impaired social behavior. Using chemogenetic inhibition during functional ultrasound imaging, we found that dorsal CA2 pyramidal neurons broadly control prefrontal and thalamic communication, in addition to hippocampal and thalamic activity. Correspondingly, chronic CA2 inhibition altered social interaction.

Gathering information before committing to a choice is critical in real-world decision making, and biases thereof are hallmark features of psychiatric disorders. Here, we study the behavioural and neural mechanisms that guide information gathering and characterise several key cognitive constituents, including escalating urgency and systematically biased temporal weighting of information. Using fMRI, we identify an integrated information gathering signal in ventromedial and dorsomedial prefrontal cortices (dmPFC), signalling an overall likelihood for continued sampling of information. Teasing this signal apart, we find distinct neural circuits encoding separable information-gathering constituents: whilst an urgency signal primarily engaged locus coeruleus and dmPFC, accumulated evidence was represented in anterio-medial PFC, and evidence-strength prediction errors were computed in ventral striatum and dmPFC. These findings indicate that information gathering arises from functionally distinguishable prefrontal-subcortical computations that converge within medial prefrontal cortex, providing a mechanistic framework for understanding aberrant sampling in psychiatric conditions, including schizophrenia and obsessive-compulsive disorder.

Background: Cognitive impairment is the leading cause of disability in schizophrenia with limited treatments. A major barrier to treatment development is the absence of reproducible, mechanistically grounded neural targets. Cross-sectional studies have identified dorsomedial prefrontal cortex (DMPFC)-somatomotor connectivity as a neural marker of cognitive performance on the Auditory Continuous performance task (ACPT), a measure of attention. To test the stability of this marker, we tested the relationship between DMPFC-somatomotor connectivity and ACPT performance in a longitudinal psychosis sample. Methods: Individuals with early psychosis (n=251) and matched controls (n=90) were enrolled and underwent resting-state neuroimaging and neurocognitive assessment. A subset completed longitudinal assessments over 2-4 years. We calculated DMPFC-somatomotor resting-state functional connectivity using a previously identified DMPFC region and a seed in the somatomotor cortex. We performed linear mixed effects models to predict ACPT performance based on connectivity, time, psychosis type, and their interaction. Results: In the psychosis sample, time (p=.0037) and affective psychosis diagnosis (p<.0001) predicted better ACPT performance. In a model predicting ACPT performance, we observed a significant interaction effect of DMPFC-somatomotor connectivity*psychosis subtype (p=.0079) such that DMPFC-somatomotor connectivity predicted ACPT performance only in individuals with non-affective psychosis (p=.0051). We then tested the specificity of this connectivity-cognitive performance relationship. In a model predicting DMPFC-somatomotor connectivity, only ACPT performance (p=.017), but not fluid cognition, was a significant predictor. Conclusions: DMPFC-somatomotor connectivity is longitudinally associated with cognitive performance in early psychosis. This relationship is strongest in nonaffective psychosis, suggesting a novel, reliable target for intervention for cognitive deficits in early psychosis.

Dysregulation of the delta-type glutamate receptor GluD1 and N-methyl-D-aspartate receptors (NMDARs) is implicated in neuropsychiatric disorders including schizophrenia and intellectual disability, and GluD1 modulates NMDAR response in hippocampal neurons. However, the precise mechanisms by which GluD1 influences specific NMDAR subtypes remain undefined, representing a critical gap given the reliance of synaptic plasticity and cognition on NMDAR composition. GluN2A- and GluN2B-containing NMDARs are essential for synaptic long-term potentiation (LTP) and contextual learning and memory. Here, we used CRISPR/Cas9 to generate GluD1 knockout (KO) in cultured hippocampal neurons and observed a selective decrease in GluN2B-containing NMDAR responses. In acute hippocampal slices, GluD1 KO similarly reduced GluN2B-containing NMDAR currents at ventral CA1[-&gt;]subiculum synapses and impaired LTP at these synapses. In vivo, region-specific GluD1 deficiency in the ventral subiculum disrupted long-term contextual memory, indicating a critical role for GluD1 in cognitive processes. These findings demonstrate that GluD1 is indispensable for preserving GluN2B-containing NMDAR function, synaptic plasticity, and memory, providing molecular insight into how GluD1 regulates NMDAR subtypes implicated in synaptic dysfunction in neuropsychiatric disorders. Understanding this mechanism will guide the development of therapeutic strategies that selectively target GluD1-dependent modulation of NMDAR subtypes in brain disease.

Schizophrenia presents with several partially independent symptom dimensions, including positive symptoms, negative symptoms, and cognitive impairment; yet no neuroimaging framework has provided individual-level markers of symptom severity that remain anatomically interpretable. Here, we present an interpretable AI-based framework that addresses this gap by mapping high-dimensional resting-state rs-fMRI dynamics onto a low-dimensional latent manifold using self-supervised contrastive learning with a new attribution method to localize the highest decodable regions. Applied to two independent schizophrenia-spectrum cohorts, the label-free latent space supports individual-level prediction across clinical features of the disorder, including symptom severity and cognitive function. The attribution maps identify a disease-specific pathological footprint concentrated in prefrontal, posterior cerebellar and temporal areas that diverge from the manifold organization observed in healthy controls, which was dominated by auditory, limbic, and ventral-striatal circuits. These results establish an interpretable latent space framework for characterizing the distributed neural substrates of schizophrenia symptoms at the level of the individual patient, and provide an anatomically grounded route toward precision decoding of symptom severity.

Whereas brain systems mediating acute stress are essential for survival, chronic early-life stress (ELA) may lead to poor ability to experience pleasure (anhedonia), a core feature of depression. For decades, the stress neuropeptide corticotropin-releasing hormone (CRH) has been a target for treating depression. However the failure of several clinical trials blocking CRH receptor1 (CRHR1) has left the therapeutic role of CRH signaling a major unresolved mystery. Here, we uncover the signaling plasticity behind this enigma with the use of in vivo G protein-coupled activation-based (GRAB) imaging and viral-genetic and pharmacological mechanistic manipulations. We find that CRH signaling via CRHR1 indeed disrupts reward behaviors in control mice, but is disrupted in anhedonic mice with a history of ELA. Instead, activation of CRH receptor 2 (CRHR2) reverses anhedonia-like behaviors in adult ELA mice. These findings redefine our understanding of stress-mediated anhedonia and provide a precise, novel therapeutic target for stress-related mental illness.

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.

Relapse following prolonged abstinence is a primary challenge in the treatment of opioid and cocaine use disorders, driven in part by enduring dysfunction of medial prefrontal cortex (mPFC) circuits that impair inhibitory control over drug-seeking. The molecular substrates underlying this dysfunction, and whether they differ across drug classes, remain unknown. Here, we performed label-free quantitative proteomics of mPFC synaptosomes isolated from rats after 30-day abstinence following intravenous heroin or cocaine self-administration to profile synaptic adaptations that may contribute to relapse vulnerability. Heroin abstinence induced extensive synaptic proteomic remodeling characterized by coordinated downregulation of mitochondrial proteins involved in oxidative phosphorylation, including pyruvate dehydrogenase complex subunits that regulate carbon entry into mitochondrial metabolism. Targeted metabolomic profiling of whole mPFC revealed accumulation of upstream glycolytic and pentose phosphate pathway intermediates, consistent with altered pyruvate utilization and mitochondrial oxidation. Several bioenergetic metabolites also correlated positively with the severity of escalation of heroin intake. Consistent with the bioenergetic remodeling observed during protracted heroin abstinence, whole-cell patch-clamp recordings from layer V mPFC pyramidal neurons revealed lasting suppression of intrinsic excitability and a decreased spontaneous excitatory synaptic activity. Cocaine abstinence, by contrast, produced limited changes in synaptic bioenergetics while inducing a distinct cytoskeletal remodeling signature. Overall, these findings identify synaptic bioenergetic remodeling as a previously underappreciated feature of prolonged heroin abstinence and reveal a marked divergence in the molecular adaptations induced by heroin versus cocaine within the mPFC. These results implicate mitochondrial bioenergetic pathways as therapeutic targets for reducing relapse vulnerability specifically associated with opioid use disorder.

Relatively preserved insight distinguishes individuals at risk for psychosis from those with full-blown psychosis. Metacognitive processes thought to support insight and uncertainty monitoring may therefore serve as early markers of illness progression. Yet findings have been inconsistent, perhaps partly due to reliance on explicit confidence ratings that introduce reflection and response biases. To address these limitations, we used a novel implicit confidence measure derived from post-decision gaze in a virtual-reality probabilistic learning task. Gaze-based confidence quantifies the alignment between spatial predictions and gaze direction. We assessed first-order learning and gaze-based metacognition in four groups: clinical high-risk for psychosis (CHR-P), first episode psychosis (FEP), help-seeking controls (HSC), and healthy controls (HC). We tested whether implicit metacognition differentiates psychosis risk from psychosis. Learning accuracy was reduced in both CHR-P and FEP compared to control groups. At the metacognitive level, CHR-P confidence levels were approximately commensurate with their reduced first-order performance, indicating preserved confidence calibration, along with preserved metacognitive sensitivity--the ability to distinguish correct from incorrect decisions. In contrast, FEP showed impaired confidence calibration and reduced metacognitive sensitivity. Metacognitive calibration and sensitivity distinguished CHR-P from FEP and provided predictive value in distinguishing CHR-P from FEP, whereas learning accuracy did not. These findings reveal a dissociation between first-order cognitive processes and distinct aspects of implicit metacognition, including confidence calibration and metacognitive sensitivity, across the psychosis continuum. This dissociation may refine early clinical characterization and improve identification of preserved insight-related mechanisms in psychosis risk.

BackgroundInflammation-associated depression is a subtype of major depressive disorder that is often resistant to conventional pharmacotherapies, which act in a regionally non-specific manner and therefore also produce unwanted side effects. Here we test GPR151, an orphan GPCR associated with inflammation and highly expressed in the habenula--a region linked to negative valence and depression--as a therapeutic target for inflammation-associated depression. MethodsWe integrated mouse and human habenular expression analyses with genetic loss-of-function and adult habenular re-expression approaches in mice. Gpr151 knockout mice and littermate controls were exposed to lipopolysaccharide (LPS) inflammatory challenge and assessed for stress coping and motivated behavior, body weight loss, and peripheral immune activation. To test whether adult habenular GPR151 expression is sufficient to restore inflammation-associated behavioral vulnerability, GPR151 was re-expressed in the habenula of knockout mice. ResultsGPR151 was exceptionally enriched in the habenula and showed conserved topographic organization and similar expression relationships with habenular marker genes in mice and humans. Following LPS challenge, male Gpr151 knockout mice showed reduced passive coping despite body weight loss and immune activation comparable to littermate controls. Adult habenular GPR151 re-expression increased LPS-induced amotivation in male knockout mice without increasing LPS-induced weight loss or immune activation. Female Gpr151 knockout mice also showed reduced passive coping after LPS challenge; however, habenular GPR151 re-expression was insufficient to increase LPS-induced amotivation in females. ConclusionsThese findings identify GPR151 as a conserved, regionally enriched regulator of behavioral sensitivity to inflammatory challenge and support GPR151 as a candidate therapeutic target for inflammation-associated depression.

BackgroundSocial dysfunction is a major source of disability in schizophrenia, yet the neural mechanisms that contribute to impaired social understanding remain poorly understood. Converging evidence points to the role of the default mode network (DMN) in integrating social information over time to construct interpretations of social behaviors. Here, we tested the hypothesis that individuals with schizophrenia show reduced stimulus-driven coordination between brain regions within the DMN during free viewing of naturalistic social stimuli. MethodsA sample of 124 adults (schizophrenia: n=63; healthy controls: n=61) viewed naturalistic video clips during fMRI. Inter-subject functional connectivity (ISFC) was computed within the two groups. Group differences were identified via permutation testing. We also explored group differences in other brain networks to examine whether effects were specific to the DMN. ResultsIndividuals with schizophrenia showed weaker stimulus-driven coupling within the DMN compared to healthy controls, specifically between areas such as the parahippocampal gyrus, precuneus, and medial prefrontal cortex. Group differences in ISFC were specific to the DMN. Furthermore, no between-group differences emerged for within-participant functional connectivity in the DMN, suggesting that the observed effects reflect reduced stimulus-driven coordination among DMN regions when processing social stimuli rather than a more general decline in DMN connectivity. ConclusionsSchizophrenia is characterized by impaired coordination within the DMN as it dynamically integrates social information over time, which could contribute to difficulties in constructing coherent interpretations of real-world social situations. These findings suggest that disrupted stimulus-driven network coordination might underlie social cognitive impairments in schizophrenia, highlighting the value of naturalistic paradigms for revealing network-level dysfunction under conditions that closely approximate real-world experience.

Serotonergic psychedelics (SP) are increasingly used in clinical research and naturalistic settings, but their psychotic-like side effects, including persisting perceptual abnormalities (PPAs), are poorly understood. Psychosis-associated hallucinations are associated with susceptibility to conditioned hallucinations and computationally-estimated overweighting of perceptual expectations, or priors. However, SPs are widely argued to reduce prior weighting. We surveyed 186 naturalistic SP users on prior SP use, SP-associated PPA history, and current PPAs. Participants completed the visual conditioned hallucinations (VCH) task, in which conditioning induces perception of absent stimuli. Behavioral data were used to fit parameters of a computational model to estimate latent states driving percepts and responses. Past and current PPAs were associated with younger age at first use and higher SP doses, lower visual thresholds, higher VCH rate and confidence, and reduced sensory discrimination. Among model parameters, however, only reduced decision precision tracked both measures and mediated the dose-PPA relationship; relative prior weighting rose equivocally, as expected when priors and sensory evidence gain precision together. SP-related PPAs may therefore arise from a noisy visual system biased toward detection, in which priors act as templates that convert sensory noise into expected percepts. These findings may point to a tractable model for how psychotic-like perception emerges.

Background: Autism spectrum disorder is a prevalent neurodevelopmental condition featuring marked social difficulties. Oxytocin supplementation shows promising therapeutic efficacy in alleviating autism-like traits in rodent models, but clinical effects in humans remain inconsistent. The rodent-derived social salience network (SSN) comprises several oxytocin-modulated brain regions implicated in social behavior, but its conservation has not been established in humans. Here we assess, for the first time, functional connectivity (FC) within a homologous human SSN in autistic men to examine its relationship with behavioral traits and modulation by oxytocin. Methods: The human SSN atlas was collated from open-access cortical and subcortical parcellations, and used to retrospectively analyze a resting-state fMRI dataset of adult men with autism from a previously published, randomized, placebo-controlled oxytocin trial. SSN-wide and sub-network ROI-to-ROI FC correlations with social trait expression and salivary oxytocin concentrations were performed at baseline and post-administration. Treatment specific outcomes on FC were calculated using ANCOVA. Results: We observed SSN sub-network FC correlations with social and repetitive behavioral scores and identified strong oxytocin sensitivity of nucleus accumbens-somatosensory and paraventricular nucleus-somatosensory circuits at baseline. Following nasal spray administration, a strengthening of amygdala-somatosensory circuit was detected as the largest oxytocin-induced FC shift. Notably, baseline connectivity within this circuit strongly predicted treatment response, with individuals having lower baseline FC showing greater post-treatment FC. Conclusions: These findings provide first evidence for clinical relevance of the SSN in humans with autism and highlight circuits that may represent promising biomarkers for predicting oxytocin responsiveness.

Background: Autism polygenic scores (PGS) reliably predict case-control status yet explain little variance in autism-related traits. Landscape accounts of neurodevelopmental diversity propose that genetic liability broadens the range of viable neural configurations rather than shifting brain organisation toward dysfunction. We tested whether autism polygenic load is associated with increased variability in functional network organisation among non-autistic adults. Methods: We analysed resting-state functional connectivity from 910 non-autistic adults (aged 22-35) in the Human Connectome Project. Polygenic scores were derived from the iPSYCH autism GWAS at a pre-specified threshold (p = 0.1). Modularity (segregation) and global efficiency (integration) were computed at a pre-selected parcellation size and density (100-node, 20%), and residualised for age, intracranial volume, and head motion. Variance effects were assessed by variance regression including a PGS-by-sex interaction, decile-stratified dispersion trends, and PGS-balanced bootstrap resampling. Edge-wise analyses used false discovery rate correction. Results: Modularity variability broadened with polygenic load in a sex-dependent manner (sex-by-PGS beta = 1.92e-4, p = 0.031). Decile trends (male minus female difference = 0.82, p = 0.034) and balanced-bootstrap trends (difference = 1.19, p = 0.032) both differed by sex: variance increased across polygenic bins in males (r = 0.57, one-tailed p = 0.021) but not females. No comparable effect emerged for global efficiency (all p >= 0.54). Polygenic scores showed no association with social-cognitive difficulty (beta = 0.11, p = 0.209), mean network organisation, or connectivity after correction. Limitations: All participants were non-autistic adults and the analysis was cross-sectional. The identified effects are small and the sample size not sufficient to resolve very small effects often reported in genetics studies. Characterisation of genetic effects in women may be influenced by biases in the data used to calculate polygenic scores. Conclusions: Autism polygenic load broadened modular network configurations in males without shifting mean organisation or its behavioural correlates, offering partial support for landscape accounts.