Depression and post-traumatic stress disorder (PTSD) are highly prevalent and debilitating stress-related psychiatric disorders, yet current pharmacological treatments fail to provide meaningful benefit for approximately half of patients. Converging evidence implicates metabolic dysregulation across psychiatric disorders, highlighting metabolic pathways as novel therapeutic targets. Given their established clinical safety in type 2 diabetes, glucagon-like peptide-1 receptor (GLP-1R) agonists represent promising candidates for repurposing in psychiatric treatment. Consequently, we sought to examine data from preclinical and experimental medicine studies to establish the translational rationale for repurposing GLP-1R agonists in psychiatric disorders. Using PubMed, Scopus and Web of Science, we conducted a search for peer-reviewed manuscripts exploring the use of GLP-1R agonists to treat depression and/or PTSD/relevant symptoms. Our search yielded 43 studies assessed as of at least medium quality using the Hawker tool, including 28 rodent models and 15 experimental medicine studies. Evidence across GLP-1R agonists was highly heterogeneous resulting in each drug being assessed separately. Some clinical studies reported improvements in depressive or anxiety-related symptoms, whereas others found minimal or inconsistent effects. Evidence for exenatide was particularly variable, with mood-related outcomes appearing dependent on neurobiological context and concomitant treatment. No studies directly evaluated GLP-1R agonists for the treatment of PTSD, with data limited to broader anxiety- and stress-related outcomes. Current evidence does not provide consistent support for GLP-1R agonists as treatments for depression or PTSD. However, evidence suggests that therapeutic effects (if any) may be most relevant in individuals with comorbid metabolic dysfunction. Further research using validated models of trauma-related pathology and targeted clinical studies is required to determine whether GLP-1 receptor agonism represents a viable therapeutic strategy.
Cortical and subcortical correlates of anxiety and stress disorders have been well defined over recent decades. However, the role of the locus coeruleus (LC), which is responsible for synthesizing and releasing a majority of the brains’ norepinephrine, has been less widely studied. Here, we used ultra-high field 7T imaging with 400 μm³ voxel resolution to individually segment the LC. We performed a functional connectivity analysis to elucidate the relationship between LC connectivity across the whole brain and measures of anxiety and stress, with a particular focus on anxious arousal, a core feature of pathological anxiety. We assessed 77 individuals with and without anxiety or posttraumatic stress disorder (PTSD). We found that higher anxious arousal was robustly associated with higher LC connectivity to the dorsal anterior cingulate cortex (dACC). A conjunction analysis utilizing additional measures of anxiety and stress revealed consistent mapping of LC connectivity to the dACC and the insula (all pcluster < 0.05, FWE whole-brain corrected). This study leveraged high resolution functional connectivity mapping and individualized segmentation of the LC to demonstrate a consistent neuropathological phenotype of LC hyper-connectivity with dACC and insula across anxiety disorders and PTSD. These findings suggest that functional interactions between LC and dACC and insula represent a core aspect of pathological anxiety.
Modern psychiatry is shifting from unitary diagnostic models toward identifying biologically distinct depression subtypes. Despite the potential of multi-omics and AI, the field is hindered by non-standardized pipelines and poor reproducibility. We propose a four-pillar computational framework to standardize the subtyping process: (1) standardized preprocessing and feature embedding to ensure data integrity; (2) integrative multi-omics modeling strategies tailored to diverse sample sizes; (3) robust subtype identification and Explainable Artificial Intelligence (XAI) interpretation, where we propose the Minimum Reporting Standards for Computational Psychiatry Subtyping (MiR-CPS) to ensure methodological transparency; and (4) hierarchical clinical validation to benchmark subtype stability and utility. Beyond this core trajectory, we extend the framework to longitudinal trajectories and cross-diagnostic approaches to address temporal and diagnostic heterogeneity. This framework provides a reproducible roadmap for transitioning from raw high-dimensional data to clinically actionable subtypes, advancing evidence-based precision psychiatry.
Fetal Alcohol Spectrum Disorders (FASDs) are common but require difficult-to-find multi-disciplinary teams for diagnosis. Consequently, a majority of children born with prenatal alcohol exposure (PAE) are never diagnosed and are at risk for adverse secondary outcomes. To address this deficit, we and other groups have searched for biomarkers that either reflect PAE or predict FASD. Plasma miRNAs were previously shown to be biomarkers for both PAE and FASD-associated child outcomes in maternal and neonate/infant plasma samples. The aim of this study was to identify miRNA signatures of atypical development in early childhood (3.1 ± 1.5 years old, range 1.7–8.9 years of age) related to FASD outcomes. miRNAs were assessed from purity-validated plasma samples, using low-density qRT-PCR arrays. Analysis of expressed miRNAs showed that 16 miRNAs were associated with neurodevelopment status, while only 3 were associated with PAE status. Child sex was a critical modifier of altered miRNA profiles, particularly for neurodevelopment status. We identified 7.3-times as many miRNAs associated with atypical neurodevelopment in female compared to male children. Groups of miRNAs and clinical variables were identified that were associated with cognitive performance in both infancy (~ 6 or ~12 month Bayley Scales of Infant Development) and early childhood (Differential Ability Scales-II), with a subset of miRNAs, namely miR-409-3p and let-7 family members, present in multiple models. Critically, model variables explained up to 24–41% of the variance in neurocognitive scores. Childhood plasma miRNAs are indicative of neurodevelopmental outcomes and can contribute to improving risk stratification for children with PAE.
Suicidal behavior is a clinically heterogeneous and biologically complex outcome. The shared genetic architecture underlying high-risk suicide-related phenotypes and its translational relevance for target discovery remain incompletely defined. Here, we developed an integrative framework combining genomic structural equation modeling (genomic SEM), transcriptome-wide association study (TWAS), causal gene fine‑mapping, artificial intelligence-assisted virtual screening, molecular dynamics simulations, binding free-energy analysis, and integrative causal genomics to characterize a high-suicide-risk syndrome and identify candidate therapeutic targets. Genomic SEM supported a shared latent genetic liability across suicide-related, psychiatric, environmental, socioeconomic, and pain-related phenotypes. Further multidimensional modeling resolved this liability into two biologically interpretable dimensions: endogenous affective risk and exogenous stress. Transcriptomic analyses identified six core risk genes supported by convergent TWAS and fine-mapping evidence: TM9SF4, SUSD3, PTPDC1, VPS33B, XRCC3, and LSM10. Five lead ligands targeting transmembrane 9 superfamily member 4 (TM9SF4) were prioritized following protein-structure prediction and DiffDock-based screening of marine natural products. In the subsequent molecular dynamics simulations and binding free‑energy analyses, all five small molecule–protein complexes maintained stable binding. Integrative analyses of protein and expression quantitative trait loci further identified seven gene associations across neural tissues. Collectively, these findings characterize a genetically informed high-suicide-risk syndrome, indicate TM9SF4 as a potential molecular target, and provide potential candidate natural-product ligands.
Abstract Brain-age models use neuroimaging features to predict chronological age. The resulting brain-age gap (BAG), defined as predicted brain age minus chronological age, quantifies deviations from age-expected brain characteristics. Structural brain-age acceleration is well established in schizophrenia spectrum disorders (SSD), but the utility of resting-state functional connectivity (rs-FC)–based brain age remains unclear. Here, we trained rs-FC brain-age models on aggregated lifespan data from healthy controls (n ≈ 2200) and evaluated them in four independent SSD case–control cohorts. Across independent cohorts and two brain atlases, SSD showed higher FC-based BAG than healthy controls (β ≈ 0.4–0.6), indicating modest functional brain-age elevation at the group level. However, within SSD, more negative (younger appearing) BAG was associated with poorer cognitive performance, longer duration of illness, and higher neurological soft signs (NSS). Over 12–24 weeks, increases in BAG were associated with reductions in NSS motor coordination and hard signs. Together, these findings suggest that rs-FC brain age captures both a small case–control shift and a clinically relevant dimension within SSD that is not well described by uniform “acceleration”. FC-based BAG may therefore reflect heterogeneity in network-level development and reorganization, with younger-appearing functional profiles potentially indexing greater neurodevelopmental burden.
Non-suicidal self-injury (NSSI) in adolescents has previously been linked to alterations in the endocannabinoid system. While increasing evidence supports endocannabinoid levels as potential biomarker in psychiatric care, little is known about their longitudinal trajectories over the course of treatment or in predicting clinical symptoms. This is the first study to investigate endocannabinoids in a longitudinal cohort of patients with NSSI, exploring associations with the development of symptoms over time. Plasma endocannabinoids and NSSI, using the German version of the Self-Injurious Thoughts and Behaviors Interview (SITBI-G), were assessed in n = 47 female adolescents with NSSI at both baseline and after one year of treatment (follow-up). Associations between endocannabinoid levels and clinical symptoms over time were analyzed. Anandamide (AEA) significantly decreased from baseline to follow-up while 2-arachidonoylglycerol (2-AG) increased after one year. While lower AEA levels have previously been reported in adolescents with NSSI, this longitudinal study found that AEA decreased over one year despite an overall improvement in NSSI symptoms. The overall pattern suggests that changes in circulating endocannabinoids do not closely correspond to symptom improvement. These findings indicate that circulating endocannabinoid levels change over time in adolescents with NSSI, but their complex and partly inconsistent associations with clinical symptoms limit their clinical utility as biomarkers.
Most human studies on perceptual decision-making are correlational, and few addressed the causal role of the neural markers they identify. Here, we took the opportunity offered by deep brain stimulation to study the causal role of subthalamo-cortical networks on perceptual decision-making and perceptual monitoring. We asked participants with obsessive-compulsive disorder (OCD) treated with subthalamic stimulation to detect visual stimuli and provide confidence reports while we recorded scalp electroencephalography. Following a preregistered plan, we compared behavioural and neural results between patients off-stimulation and matched healthy controls and among patients on and off-stimulation to identify the effect of subthalamic stimulation on perceptual choices and metacognitive judgments. Our results indicate that patients off-stimulation detected visual stimuli similarly to matched healthy controls but provided poorer confidence judgments, indicative of a potential metacognitive alteration. Moreover, chronic subthalamic stimulation significantly reduced clinical symptoms, but acute stimulation changes did not impact visual detection, confidence, nor corresponding event-related potentials at the scalp level. We conclude that acute changes in subthalamic stimulation are insufficient to modify the potential metacognitive alterations observed in OCD.
Glutathione (GSH), the brain’s primary antioxidant, confers a critical first line of defense against oxidative-stress-induced cellular damage, with some evidence supporting compensatory upregulation of anterior cingulate cortex (ACC) GSH in bipolar disorder (BD). N-acetylcysteine (NAC), which increases GSH by providing cells with the rate-limiting substrate of GSH synthesis (i.e., cysteine), has been investigated as an adjunctive treatment for BD and has been found to reduce residual depressive symptoms, though no studies have evaluated whether NAC affects brain GSH levels in these patients. To further evaluate brain GSH levels as a candidate oxidative-stress biomarker and interventional target for adjunctive treatment for BD, we present data from two independent proton MR spectroscopy (1H-MRS) investigations; a cross-sectional comparison of dorsal ACC (dACC) GSH levels in BD (n = 29) vs HC (n = 26) individuals, followed by a pilot (n = 12), randomized, placebo-controlled, double-blind, crossover study of 3 g/day of NAC versus placebo on dACC GSH levels. We demonstrate that BD individuals have significantly elevated dACC GSH levels (Cohen’s d = 0.56, p = 0.046), which are associated with a greater number of past-year depressive episodes (r = 0.39, p = 0.041), relative to HC individuals, and that NAC treatment is associated with significantly higher dACC GSH (Cohen’s d = 0.45, p = 0.040) but not glutamate (p = 0.325) levels, relative to placebo, in people with BD. These preliminary results, which should be interpreted with caution given the small sample sizes therein, further pave the way for ACC GSH levels to serve as a primary mechanistic target for novel antioxidant treatments for BD that overcome the bioavailability limitations of NAC.
Transcranial alternating current stimulation (tACS) is a non-invasive neuromodulation technique that modulates neural activity through frequency- and phase-dependent electrical currents and has shown potential for enhancing cognition and alleviating symptoms in neurological and psychiatric disorders. Temporal interference (TI) stimulation applies two or more kilohertz-frequency electric fields with slightly different frequencies to generate a low-frequency amplitude-modulated field within neural tissue, offering a potential strategy for preferentially engaging deeper neural targets with improved spatial steering. Foundational studies in this field have used diverse methodologies, including multiscale computational modeling, cellular experiments, intact-animal studies, and disease-specific animal models, to elucidate stimulation principles, parameter dependencies, neuromodulatory mechanisms, safety, and functional efficacy. This review synthesizes recent advances in the basic and preclinical research of tACS and TI, with an emphasis on biophysical and physiological mechanisms, safety evaluation, parameter optimization, technological developments, peripheral nerve applications, and therapeutic effects and associated mechanisms in animal disease models. Current evidence indicates that both approaches can influence neural function across membrane, cellular, circuit, network, synaptic, and behavioral levels. Although tACS has undergone extensive human and clinical investigation, transcranial temporal interference stimulation (tTIS) remains at an earlier stage of mechanistic and translational development. Further systematic studies are required to clarify direct and indirect stimulation mechanisms, long-term safety, dose-response relationships, target engagement, and protocol optimization, thereby facilitating the clinical translation of these techniques, particularly for individualized and precision neuromodulation of brain disorders.
Neuronavigated repetitive transcranial magnetic stimulation (rTMS) has shown encouraging efficacy in treating various brain disorders. However, substantial inter-individual heterogeneity in treatment response remains a major challenge. In this secondary analysis of a randomized clinical trial, we examined the predictive performance of transcranial features in relation to output measures and responses to rTMS treatment. Fifty-five elderly patients with depression and cognitive impairments were randomly assigned to receive a 3-week treatment of either 10 Hz active rTMS or sham rTMS. Left dorsolateral prefrontal cortex (DLPFC) and primary motor cortex (M1) were the predefined treatment targets. Scalp-to-cortex distance (SCD) was measured as the Euclidean distance between the scalp stimulation site and the corresponding cortical target. SCD-modified output difference (SCD-MOOD) was developed for quantifying the differences between the actual output and target-specific SCD-adjusted output. Responders to rTMS exhibited a greater SCD of left M1, a lower SCDDLPFC/M1 ratio and a higher SCD-MOOD than nonresponders. Logistic regression analyses revealed that clinical remission to active rTMS was significantly associated with SCD of left M1 (p = 0.038) and SCD-MOOD (p = 0.042). Moreover, using SCD metrics as predictive features, the responder-nonresponder classification model achieved an accuracy of 92.5% at week 3 and 86.2% at week 12. Pre-treatment SCD metrics of the stimulation targets can effectively predict early rTMS treatment responses. Predictive models integrating with MRI-derived SCD and SCD-MOOD showed strong specificity for active rTMS compared to sham stimulation. This approach may enable the development of effective, personalized protocols to improve region-specific TMS treatment outcomes in clinical practice. ChiCTR-IOR-16008191, registered on March 30, 2016. ClinicalTrials.gov Identifier: NCT05967390
The ε4 allele of the apolipoprotein E gene (APOE4) is the strongest genetic risk factor for sporadic Alzheimer’s disease (AD). However, its impact on monocyte-mediated amyloid-β (Aβ) clearance and associated immune dysfunction remains poorly understood. Through Aβ uptake assays in humans and mice coupled with transcriptomic profiling, we identified a significant and persistent monocytic Aβ uptake deficiency in APOE4 carriers. This deficit was quantitatively associated with poor cognitive function and elevated plasma Aβ levels. Mechanistically, RNA sequencing revealed that this impairment is driven by a stage-specific molecular transition: in cognitively normal individuals, APOE4 induces a functional mismatch characterized by proinflammatory priming and lipid metabolic dysregulation, whereas in AD patients, this evolves into profound immune exhaustion or transcriptional collapse of core immune and endocytosis pathways. These findings establish APOE4 as a systemic modulator of innate immune competence, suggesting that monocyte-targeted functional rejuvenation may be a potential therapeutic strategy for AD.
Individuals with methamphetamine use disorder (MUD) exhibited functional and structural brain recovery during abstinence. However, longitudinal neural changes of large-scale brain networks after prolonged abstinence remain unclear. Here, energy landscape analysis was applied to resting-state fMRI to characterize dominant activity patterns in 41 healthy controls and 40 individuals with MUD at baseline and after prolonged abstinence. We compared the dynamic characteristics of these patterns across groups and stages. Support vector regression model was constructed using baseline dynamic indices to predict craving changes after prolonged abstinence. We found that individuals with MUD exhibited rigid brain dynamics, which were correlated with abnormal brain network coordination and behaviors. Following prolonged abstinence, neural flexibility showed partial improvement, and dynamic indices could predict longitudinal craving changes. We revealed atypical brain network dynamics and their partial recovery during prolonged abstinence in MUD and suggested that dynamic indices could serve as biomarkers for predicting craving changes.
Oxylipin species are generated from omega-3 and omega-6 fatty acids during inflammation, including fatty acid epoxides by cytochrome P450s (CYP450) and their diol metabolites by soluble epoxide hydrolase (sEH). The CYP450-sEH pathway has been implicated in Alzheimer’s disease (AD) but it remains unclear how plasma oxylipins relate to AD biomarkers and neurodegeneration. Fasting plasma CYP450-sEH total (free + esterified) oxylipins were assayed by ultra-high pressure liquid chromatography-tandem mass spectrometry in participants (NCT04104373) clinically diagnosed with AD or mild cognitive impairment (MCI). Plasma AD biomarkers were assayed by SiMoA. At baseline, 1 and 2 years, regional grey matter and white matter hyperintensity (WMH) volumes were quantified using 3.0 T MRI, and cognitive assessments were performed. At baseline (n = 125), participants with AD vs. MCI had higher CYP450-sEH pathway metabolites, apolipoprotein E (APOE) ε4 carriers vs. non-carriers had higher diol levels, and females vs. males had higher omega-6 vs. omega-3 oxylipins. An oxylipin profile of higher diols and lower epoxides was associated with higher pTau181, temporal lobe and hippocampal atrophy, and declines in cognitive performance in multiple domains over 2 years. Higher CYP450-sEH pathway metabolites were associated with the progression of WMH. Larger oxylipin relationships with atrophy and cognitive decline were seen at the MCI stage, in APOE ε4 carriers, and in females. Elevated sEH metabolites were related to biomarkers of AD pathogenesis, and they predicted atrophy, white matter changes, and cognitive decline over 2 years.
Alterations in telomere length (TL), a marker of cellular ageing, have been reported in individuals with severe mental disorders (SMD). Epidemiological studies of the general population have highlighted that unhealthy lifestyles may exacerbate telomere attrition. However, the impact of lifestyle on TL within the context of SMD remains unexplored. The study consisted of 410 participants (schizophrenia spectrum [n = 225] and affective disorder [n = 185]) collected as part of the Norwegian Thematically Organised Psychosis (TOP) study. Leukocyte TL was measured via blood and determined by quantitative real-time Polymerase Chain Reaction (qPCR). Patients provided self-report data on six lifestyle domains including: diet, exercise, smoking, alcohol consumption, substance use, and coffee consumption. A global dichotomised (healthy vs unhealthy) lifestyle variable was created, as well as a health behaviour variable, indicating the level of unhealthy behaviours. Individuals with an unhealthy lifestyle had shorter TL compared to those with a healthy lifestyle (Cohen’s d = 0.58, F = 8.62, p = 0.004). A relationship was observed between increasing number of unhealthy behaviours and shorter TL (F = 2.69, p = 0.02), adjusted for age, sex, ethnicity, trauma exposure, medication daily defined dose (DDD), years of education and diagnosis. In terms of base-pair loss, individuals with healthy lifestyles exhibited a roughly 6-year lower biological age, compared to individuals with unhealthy lifestyles. Our study indicates that a healthier lifestyle is associated with longer TL in SMD. This highlights the importance of health behaviours as potential clinical targets for ensuring healthier cellular ageing in psychiatric populations.
Chronic stress was known to contribute to gut microbiota dysbiosis and central neuroinflammation, yet the underlying mechanisms remain poorly understood. In this study, forty-eight male C57BL/6 mice were randomly assigned to three groups: control, chronic unpredictable mild stress (CUMS), and CUMS with probiotic intervention. Mice in the CUMS group were exposed to four weeks of unpredictable stressors, while those in the probiotic group received oral administration of Bifidobacterium triple viable capsules during the stress period. Behavioral assessments revealed pronounced depression-like behaviors in CUMS mice, which were significantly ameliorated by probiotic treatment. 16S rRNA sequencing demonstrated that CUMS reduced gut microbial α-diversity, altered β-diversity, elevated the Firmicutes/Bacteroidetes ratio, and decreased beneficial genera such as Bifidobacterium and Lactobacillus, while increasing the abundance of Escherichia. Probiotic supplementation effectively restored these microbial alterations to near-control levels. Intestinal barrier function was compromised in CUMS mice, as indicated by reduced proteins ZO-1 and Occludin, which partially reversed by probiotic treatment. In the hippocampus and prefrontal cortex, CUMS increased the levels of pro-inflammatory cytokines (IL-1β, TNF-α, and IL-6), and upregulated microglial activation markers (Iba-1, iNOS, and COX-2) in the hippocampus. Probiotic intervention markedly suppressed these neuroinflammatory responses. Moreover, hippocampal CA1 neurons in CUMS mice exhibited structural disorganization, neuronal loss, and nuclear pyknosis, all of which were alleviated by probiotic administration. Collectively, these findings suggest that chronic stress disrupts the gut microbiota–gut–brain axis via microbial dysbiosis and intestinal barrier impairment, thereby promoting neuroinflammation and behavioral abnormalities.
Dyslipidemia affects patients with severe mental illness to varying degrees, partly due to medication side effects and genetic variations that modify drug-induced lipid changes. To identify these genetics contributors, we conducted a genome-wide association study (GWAS) on 829 patients of the PsyMetab cohort whose total-, LDL-, HDL- cholesterol and triglyceride levels were recorded pre- and up to one-year post psychotropic treatment. Seven different loci were associated at genome wide significance level (P < 5 × 10−8) with treatment-induced lipids changes. Three genetic variants were associated with total cholesterol change following aripiprazole, quetiapine, and combination of quetiapine, olanzapine, clozapine treatment (rs17313064 G > A, rs12543987 G > A, rs58331124 G > A, respectively). Two markers were associated with HDL-cholesterol change following lithium and mirtazapine treatment (rs12097296 C > T, rs10933971 C > T, respectively). One variant was associated with triglycerides change following risperidone treatment (rs10260518 G > T) and finally one genetic variation was associated with triglycerides change considering any drug treatment (rs56286230 T > G). To compensate for the lack of classical replication, sensitivity analyses were conducted by assessing the robustness of effects using different post-treatment interval lengths. Notably rs10933971 effect on HLD-cholesterol was consistently found across different patients and time-frames. These findings point to genes previously associated with total lipids level in the general population and highlight novel drug-specific associations which provide promising insights toward personalized psychotropic therapy.
Psychedelic drugs can induce intense changes in perception and thought, and some also promote long-lasting adaptations in brain circuits that are being explored for treatment of mood and anxiety disorders. How these compounds differ at the level of intracellular signaling, and how hallucinogenic drugs diverge from related non-hallucinogenic forms, is poorly understood. A central question is whether hallucinogenic serotonergic compounds are associated with intracellular signaling features that distinguish them from closely related non-hallucinogenic analogues. Here, we show that chemically diverse serotonergic psychedelics trigger a coordinated reorganization of phosphorylation patterns across many proteins in neural cells, and that this global response contains a distinct signature that separates hallucinogenic compounds from non-hallucinogenic counterparts of similar structure. We use phosphorylation of the glycolysis-regulating transcription factor FOXK2 as an example of biological follow-up from this signature and show that hallucinogenic compounds, but not their non-hallucinogenic analogues, enhance lactate accumulation. These findings indicate that hallucinogenic and non-hallucinogenic serotonergic compounds engage separable intracellular signalling architectures under defined in vitro conditions. The dataset is provided as a community resource to enable hypothesis generation and targeted mechanistic validation.
22q11.2 deletion syndrome (22q11.2DS) is a strong genetic risk factor for neuropsychiatric conditions, including schizophrenia, yet the underlying synaptic mechanisms remain unclear. Sleep EEG suggests thalamocortical dysfunction, but scalp data alone lack mechanistic resolution. Computational modelling can bridge this gap by inferring receptor-level dynamics from EEG. We applied a conductance-based thalamocortical Dynamic Causal Model (DCM) to sleep-wake EEG from children with 22q11.2DS (n=28) and their neurotypical siblings (n=17), estimating contributions of AMPA, NMDA, GABAA, and GABAB conductances. Building on these estimates, we investigated which receptor systems, if perturbed, could shift circuit dynamics toward sibling patterns. To address this, we implemented in silico pharmacology by systematically scaling receptor-mediated conductances. Increasing NMDA receptor (NMDA-R) efficacy consistently produced the strongest improvements in alignment with sibling spectra (effect size = 0.32 in light NREM, 0.45 in deep NREM), whereas AMPA- or GABA-based manipulations were weaker. The most influential pathways were recurrent NMDA-R excitation among superficial pyramidal cells and NMDA-R excitation from spiny stellates to superficial pyramidal populations. Exploratory regressions linked greater thalamocortical delay during deep sleep to greater sleep problems (β=0.34, pFDR=0.006), and AMPA-mediated excitation of interneurons during wakefulness to anxiety symptoms (β=−0.32, pFDR=0.032). These findings implicate NMDA receptor hypofunction as a key mechanism in 22q11.2DS and suggest it may serve as a treatment target. We further show that DCM-based virtual pharmacology can simulate drug-level interventions, and we are now testing whether NMDA receptor modulation restores network activity in preclinical models (e.g., mouse models of 22q11.2DS).
Most genome-wide association studies (GWASs) of obsessive-compulsive disorder (OCD) have been conducted in European populations, limiting the understanding of OCD genetics across populations. Here, we investigated the cross-ancestry and cross-disorder transferability of European-derived polygenic risk scores (PRSs) for OCD in the first East Asian OCD cohort. We performed a GWAS in 532 Korean OCD cases and 4376 controls, followed by PRS analyses using European GWASs for OCD and 10 psychiatric disorders. The European-derived OCD PRS was significantly associated with Korean OCD status (best-fit R² = 1.17%). In multivariable models, PRSs for OCD (odds ratio [OR] = 1.28, 95% confidence interval [CI] = 1.13–1.45), schizophrenia (SCZ; OR = 1.17, 95% CI = 1.03–1.32), and anorexia nervosa (AN; OR = 1.17, 95% CI = 1.03–1.32) were independently associated with OCD. A stepwise multi-PRS model including PRSs for OCD, AN, SCZ, post-traumatic stress disorder, anxiety disorder, attention deficit hyperactivity disorder, and bipolar disorder (BD) yielded the highest predictive performance (incremental R² = 2.99%). Where available, we evaluated PRSs derived from East Asian, European, and combined populations. For BD and SCZ, PRSs derived from cross-ancestry meta-analysis GWASs showed the greatest predictive performance for OCD, outperforming single-ancestry PRSs (incremental R² = 2.84 and 1.28%, respectively). Our findings demonstrate cross-ancestry transferability of OCD polygenic risk and highlight substantial genetic overlap between OCD and other psychiatric disorders, particularly SCZ and AN. Together, they underscore the importance of including diverse ancestral populations in psychiatric genetics and suggest that transdiagnostic polygenic frameworks may provide deeper insight into the biological basis of OCD.
