Variability in antipsychotic response results from interaction of illness-related, treatment-related, environmental factors, and intrinsic interindividual differences that have not yet been addressed. Since early non-response may predict later non-response, biomarkers capable of identifying individuals at higher risk of treatment failure may have important implications for management personalization. This study aimed to evaluate whether baseline neuroimaging can predict subsequent treatment outcomes in Schizophrenia-spectrum Disorders. A systematic search of PubMed/EMBASE/IEEE Xplore was conducted until 04/20/2026, in accordance with PRISMA-DTA guidelines and a pre-registered protocol. Prospective studies using Magnetic Resonance Imaging/Positron Emission Tomography with predictive models for subsequent treatment outcomes were included. A random-effects multi-level meta-analysis was performed to pool areas under the curve (AUC). Hierarchical summary receiver operating characteristic (HSROC) curves estimated sensitivity/specificity. QUADAS-2 assessed Risk-of-bias. Sixteen studies were included. The overall pooled discriminatory performance of multi-level hierarchical models was good (AUC = 0.75,95
Personality-related phenotypes are genetically correlated with psychiatric disorders, but whether these relationships reflect shared genetic loci and differ across individual phenotypes remains unclear. We investigated their shared genetic architecture at the level of specific phenotype–disorder pairs. We analyzed genome-wide association study summary statistics for 13 personality-related phenotypes and eight psychiatric disorders in populations of European ancestry. Genetic correlations were evaluated separately for 104 phenotype-disorder pairs using linkage disequilibrium score regression and high-definition likelihood. For pairs supported by both methods, MTAG and CPASSOC were applied separately to identify pleiotropic signals, followed by linkage disequilibrium clumping, Bayesian colocalization, gene prioritization, functional enrichment and bidirectional two-sample Mendelian randomization analyses. No composite personality or psychiatric-disorder phenotype was constructed. Among the 104 evaluated pairs, 77 showed significant positive genetic correlations in both analyses. Joint screening of MTAG and CPASSOC results identified pleiotropic signals in 61 pairs, comprising 1088 independent lead SNV-pair associations and 776 unique SNVs. Bayesian colocalization supported 351 signals across 42 pairs and 284 unique lead SNVs. MAGMA identified 1293 unique genes, of which 379 were prioritized by PoPS and 151 were further supported by SMR. These genes were enriched in brain tissues and biological processes involving nervous system development, synaptic organization and intercellular connectivity. Inverse-variance weighted Mendelian randomization identified 41 forward and 32 reverse associations after false-discovery-rate correction, including 21 pairs with bidirectional evidence. These item-resolved analyses identify widespread but heterogeneous genetic sharing between personality-related phenotypes and psychiatric disorders. The findings provide a pair-specific map of shared loci and prioritized genes, while the Mendelian randomization results should be interpreted cautiously because of residual heterogeneity and potential horizontal pleiotropy. Further validation in diverse populations and functional studies is required.
Childhood maltreatment (CM) is associated with depressive symptoms in methamphetamine use disorder (MAUD), but the emotional-processing mechanisms underlying this association remain unclear. Alexithymia may be particularly relevant, yet evidence from rehabilitation samples is limited. This study examined whether overall alexithymia and specific alexithymia dimensions showed statistical indirect associations between CM and depressive symptoms among men with MAUD. This cross-sectional study included 605 Chinese men with MAUD recruited from a rehabilitation center. CM was measured using the Childhood Trauma Questionnaire–Short Form; participants meeting the moderate-to-severe threshold on at least one subscale were classified into the CM group (n = 348), and the remaining participants into the non-CM group (n = 257). Alexithymia was assessed using the Toronto Alexithymia Scale-20, including difficulty identifying feelings (DIF), difficulty describing feelings (DDF), and externally oriented thinking (EOT). Depressive symptoms were assessed using the Beck Depression Inventory–Short Form. The CM group showed higher levels of depressive symptoms, overall alexithymia, and each alexithymia dimension than the non-CM group. Greater CM severity was positively associated with depressive symptoms, overall alexithymia, and each alexithymia dimension. Depressive symptoms were positively associated with overall alexithymia and its dimensions in the total sample and both groups. Furthermore, overall alexithymia showed a significant statistical indirect association between CM and depressive symptoms. In the parallel mediation model, only DIF showed a significant specific indirect association; DDF and EOT did not. CM was associated with greater alexithymia and depressive symptoms in men with MAUD. Overall alexithymia showed a modest statistical indirect association between CM and depressive symptoms, with DIF as the only dimension showing a significant specific indirect association.
Prenatal androgen exposure organizes the development of the brain with permanent effects on brain structure and function. The second-to-fourth digit length ratio (2D:4D) has been associated with mental illnesses, including addictive disorders, with some studies reporting sex-dependent associations. Preliminary evidence suggests that in healthy male adolescents lower 2D:4D (indicating higher prenatal androgenization) is related to lower volumes of the right anterior cingulate cortex (ACC) which has previously been linked to a higher risk of alcohol use disorder (AUD). We aimed at transferring this association into an older cohort with AUD. Further, we explored relationships between 2D:4D and brain volumes on a whole brain level. We investigated 253 men and 155 women with AUD (mean age 37.31 ± 12.54 years) and associated mean of the right and left hand 2D:4D (M2D:4D = primary predictor) with brain volumes from 3 T MRI using FreeSurfer. We found that lower M2D:4D was associated with smaller right ACC volume in men using a pre-specified directional one-tailed test. Secondary subsegment analyses indicated this association may primarily be observed in the right caudal ACC. Exploratory analyses suggested sex- and hemisphere-stratified associations with other brain volumes, unaffected by age moderation and largely robust after adjustment for education and AUD criteria count across models examined. In line with previous findings, the results indicate that in men with AUD, lower 2D:4D ratios are associated with smaller right ACC volumes. The findings contribute to understanding brain variability in AUD.
Hyperprolactinemia and glucose dysregulation frequently co-occur in schizophrenia; however, their sex-specific interplay at illness onset remains poorly understood. We hypothesized that there was sex difference in abnormal glucose metabolism and prolactin (PRL) levels, as well as in their interaction, among patients with schizophrenia. This study aimed to examine sex differences in the interrelationship between PRL and glucose metabolism in first-episode schizophrenia patients. One hundred and eighty-nine first-episode patients with schizophrenia were recruited. Fasting glucose, insulin, and PRL levels were determined in all patients. We found that 35.4
One of the most outstanding contributions to the understanding of the etiopathogenesis of schizophrenia spectrum disorders (SSD) was the neurodevelopmental hypothesis. SSD and neurodevelopmental disorders (NDD) share pathogenetic mechanisms and overlapping clinical and cognitive impairment features. We investigated whether polygenic risk scores (PRSs) for NDD are associated with cognitive performance in patients with first-episode psychosis (FEP). The sample comprised 127 patients with FEP who were followed up for a mean of 20.9 years. Cognitive examination was performed using the MoCA test at follow-up. Pearson coefficient correlations and multiple regression analyses were performed to examine the contribution of the three PRSs for rare neurodevelopmental conditions (PRSNDD), attention-deficit hyperactivity disorder (PRSADHD) and autism spectrum disorder (PRSASD) to cognitive impairment after allowing for the effect of covariates. Furthermore, we examined the interconnections between the PRS for NDD and cognitive impairment using network analysis (NA), including core premorbid variables. PRSNDD showed significant associations with impairment on visuospatial/executive, attention, and language MoCA subtests, after allowing for the influence of covariates. PRSNDD and PRSADHD, but not PRSASD, were significantly associated with worse performance on the total MoCA score. Moreover, in the network analysis, the relationships between PRSs for NDD and cognitive impairment were highly interconnected with premorbid variables and PRSs for schizophrenia and educational attainment. These results provide evidence for a possible direct genetic effect on cognitive performance for the PRS of common genetic variations related to neurodevelopment and attention deficit hyperactivity disorder in patients with FEP.
Attention-deficit/hyperactivity disorder (ADHD) is associated with an elevated risk of substance use disorders (SUDs), yet most affected individuals do not develop addiction, indicating that vulnerability is selectively distributed rather than intrinsic to the disorder itself. This Review synthesizes current evidence on the neurodevelopmental mechanisms linking ADHD to SUD vulnerability, examines reward-related dysregulation as a unifying mechanistic framework underlying this association, and proposes a subgroup-based precision psychiatry perspective to explain the heterogeneity of addiction risk among individuals with ADHD. Integrating evidence across genetics, molecular neuroscience, neurodevelopment, systems-level circuitry, computational modeling, and environmental modulation, converging findings implicate polygenic variation affecting synaptic and dopaminergic pathways that interacts with atypical maturation of frontostriatal and frontocortical systems supporting reward valuation, inhibitory control, and salience processing. These multilayered perturbations may manifest computationally as dysregulated reinforcement learning, including altered dopamine signaling dynamics and impaired integration of delayed outcomes, biasing decision-making toward immediate reward. At the circuit level, disrupted coordination between mesolimbic reward systems and prefrontal control networks may facilitate a shift from goal-directed behavior to habit-based responding following repeated substance exposure, further shaped by experience-dependent neuroplasticity. Importantly, available evidence suggests that addiction risk is concentrated within distinct ADHD subgroups characterized by reduced responsiveness to anticipated rewards, impaired reinforcement learning, preference for immediate over delayed rewards, impaired inhibitory control, emotional dysregulation, and impulsive decision-making that emerge and evolve across development. Collectively, this synthesis supports a precision psychiatry framework integrating genetic, neuroimaging, computational, and digital phenotyping approaches to improve the identification, prediction, and prevention of SUD vulnerability in ADHD.
Previous studies have reported a cross-sectional association between the remnant cholesterol inflammatory index (RCII) and depressive symptoms. However, longitudinal evidence remains limited. This study aimed to examine the associations between RCII, depressive symptoms, and sleep quality, and to assess the mediating role of sleep quality and potential sex differences. Using data from three nationally representative cohorts—NHANES (n = 7,359, USA, cross-sectional), CHARLS (n = 4,551, China, longitudinal), and ELSA (n = 4,808, UK, longitudinal). Multivariable regression models were used to evaluate associations of RCII with depressive symptoms and sleep quality. Mediation analyses were conducted to estimate the indirect effect of sleep quality, with stratification by sex. Higher RCII levels were consistently associated with greater odds of depressive symptoms after multivariable adjustment in NHANES (OR = 1.16, 95
Abnormal circulating metabolite profiles have been reported in major depressive disorder (MDD), but whether specific metabolites contribute to MDD or reflect consequences of this disorder remains uncertain. We used two-sample Mendelian randomization (MR) to evaluate 233 genetically proxied circulating metabolites in relation to MDD (294,322 cases and 741,438 controls). We additionally conducted reverse MR with MDD as the exposure and validated the set of 56 discovery-stage forward associations using an independent FinnGen R12 dataset with MDD as an outcome (N = 494,164). Random-effects inverse-variance weighted (IVW) estimates were primary, with weighted-median, MR-Egger, heterogeneity, and directional-pleiotropy analyses used for sensitivity assessment. In the discovery analysis, a total of 25 metabolites were inversely associated with MDD (odds ratio [OR], 0.93–0.98) and further 31 were positively associated with MDD (OR, 1.03–1.07). In FinnGen, all 56 IVW point estimates were directionally concordant; a total of 41 associations had P < 0.05 and 35 of them remained significant after false discovery rate (FDR) correction. Among the 35 FDR-significant associations, weighted-median and MR-Egger estimates were directionally concordant with IVW. Reverse MR identified two FDR-surviving associations: genetic liability to MDD was associated with a lower omega-6 fatty acids-to-total fatty acids ratio (OR, 0.93; 95
Suicide contributes substantially to mortality in schizophrenia, yet metabolic signatures associated with suicidality remain poorly understood. We applied untargeted plasma metabolomics with multivariate modeling to identify plasma metabolic signatures associated with suicidality status and clinical features. We enrolled 146 frequency-matched psychiatric inpatients with chronic schizophrenia: 73 in the suicide-risk (SR) group, defined by current suicidal ideation or suicidal behavior/attempt history at admission, and 73 in the non-suicide-risk (NSR) group. Plasma samples underwent untargeted metabolomic profiling. Discriminating metabolites were identified using orthogonal partial least squares discriminant analysis (OPLS-DA) and Benjamini-Hochberg-adjusted Mann–Whitney U testing (variable importance in projection [VIP] >1.0 and adjusted p <0.05). Stepwise logistic regression with forced clinical covariates generated an exploratory metabolite-based classification model, and Spearman correlations examined associations with Positive and Negative Syndrome Scale (PANSS) and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) scores. OPLS-DA identified 70 discriminating metabolites (R2Y = 0.938, Q2Y = 0.650), with nominal enrichment of lysine degradation, glutathione metabolism, phenylalanine/tyrosine/tryptophan biosynthesis, and sphingolipid metabolism. Stepwise regression retained six metabolites associated with SR status (area under the curve [AUC] = 0.774): Sphingosine, 3-OH-TML, Ile-Leu+Leu-Ile, TML, Taurine, and 12-HETE. Gamma-Glu-Thr showed the highest VIP (5.003) and broad clinical correlations. Plasma metabolic differences involving sphingolipid, lysine/carnitine, neuroinflammatory, amino-acid, and glutathione-related pathways were associated with suicidality status in chronic schizophrenia. These exploratory cross-sectional findings require validation in larger longitudinal cohorts using dedicated suicidality assessments.
Depression is a highly prevalent condition, and antidepressants are widely used to manage its symptoms. However, concerns have emerged regarding a potential causal relationship between antidepressant use and the development of type 2 diabetes (T2D). Understanding these potential relationships may provide insights into the metabolic heterogeneity of antidepressant medications. This study utilized two-sample Mendelian randomization (MR) to investigate the potential causal effects of genetic liability to antidepressant use on the risk of T2D. Genome-wide association study (GWAS) summary datasets were employed, covering various classes of antidepressants (120,446 cases and 94,450 controls) and T2D (discovery set: 80,154 cases and 853,816 controls; validation set: 71,728 cases and 369,007 controls). MR analysis was performed to estimate odds ratios (ORs) and assess the causal associations between antidepressant use and T2D. The MR analysis identified significant causal associations between liability to use of specific antidepressants, including citalopram and sertraline, and T2D susceptibility. Validation using meta-analysis data of T2D confirmed these findings, with citalopram (OR 1.05, 95
Treatment-resistant depression (TRD) remains a highly burdensome clinical condition, and improvement in depressive severity does not necessarily imply parallel modification of maladaptive cognitive-affective processes such as rumination. We compared 6-month trajectories of depressive symptoms and depressive rumination across three active treatment conditions in routine clinical care: intranasal esketamine-based treatment without depression-specific metacognitive training (ESK), depression-specific metacognitive training without esketamine exposure (D-MCT), and combined esketamine plus D-MCT (D-MCT + ESK). Of 65 screened patients, 12 were excluded because of at least one absolute contraindication and 53 were enrolled (ESK n = 15, D-MCT n = 12, D-MCT + ESK n = 26). Seven participants did not complete the 6-month endpoint assessment (six in ESK and one in D-MCT + ESK), yielding a complete-case analysis set of 46 patients (ESK n = 9, D-MCT n = 12, D-MCT + ESK n = 25). Generalized estimating equations showed significant time effects and time-by-group interactions for both MADRS and RRS total scores. Endpoint ANCOVA models adjusting for baseline outcome value showed significant group effects at 6 months for MADRS (F(2,42) = 24.97, p<.001) and RRS (F(2,42) = 5.59, p=.007). Six-month MADRS response among completers was 3/9 (33.3
Emerging evidence links dysregulation of circular RNAs (circRNAs) to neuropsychiatric disorders, but their pathophysiological roles in schizophrenia (SCZ) remain unclear. We investigated the clinical significance, biological function, and underlying mechanisms of circSUCO22-20 in SCZ. Previous whole-transcriptome sequencing identified circSUCO22-20 as differentially expressed in SCZ. Sanger sequencing and RNase R digestion confirmed its covalently closed-loop structure. RT-qPCR validation was performed in 158 patients with SCZ and 158 healthy controls. Associations with Positive and Negative Syndrome Scale (PANSS) scores and systemic inflammatory indicators were assessed using Pearson correlation and restricted cubic spline (RCS) analyses. Cell Counting Kit-8 (CCK-8) and apoptosis assays were used to detect the viability and apoptosis of MK-801 (dizocilpine)-treated SH-SY5Y cells. A dual-luciferase assay was used to confirm the binding relationships among circSUCO22-20, hsa-miR-3913-3p, and SLC7A11. The GSE25673 dataset (iPSC-derived neurons) was analyzed for downstream validation. circSUCO22-20 was significantly upregulated in both patients with SCZ and MK-801-treated SH-SY5Y cells. RCS analysis revealed significant non-linear dose–response correlations between circSUCO22-20 and white blood cell (WBC) count (Poverall = 0.035, Pnon-linear = 0.011), neutrophil count (NEUT) (Poverall = 0.018, Pnon-linear = 0.005), and lymphocyte percentage (LYMPH
Bipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood. We integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening. The integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure. This integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.
Paper-pencil assessments face limitations in accessibility, lengthy administration, and interrater reliability. Digital tools may overcome these by offering user-friendly, non-verbal, and scalable assessments. This study investigated the diagnostic accuracy of BraincheX, a novel digital test battery focused on accessibility and usability, by comparing its subtest performance to CERAD-Plus equivalents. Fifty-six participants with early AD and amyloid negative cognitively healthy controls were recruited from the LMU hospital memory clinic. Diagnostic groups were defined by amyloid positivity and clinical expert consensus according to the IWG-2 criteria. Participants completed the BraincheX digital battery and CERAD-Plus. BraincheX total score was calculated by summing standardized subtest scores. Data were analyzed using ROC analysis and the Youden Index. Correlations between subtests were examined, and group differences analyzed via ANOVA. ROC analysis revealed strong diagnostic accuracy for the BraincheX total score in differentiating between early AD and controls (AUC = 0.86; optimal cut-off = − 1.51), with high sensitivity of 89.7
This study aimed to investigate the whole-brain functional connectivity (FC) patterns of goal-directed/habitual systems in patients with obsessive-compulsive disorder (OCD), and to explore their exploratory classification potential and spatial associations with gene expression profiles. Resting-state functional magnetic resonance imaging (fMRI) data and clinical variables were collected from 60 patients with OCD and 60 matched healthy controls (HCs). Seed-to-whole-brain FC analyses were conducted using the regions of interest (ROIs) implicated in goal-directed/habitual systems. Pearson correlation analyses were conducted to assess the associations between altered FCs and clinical characteristics. An exploratory support vector machine (SVM) analysis was utilized to evaluate whether altered FC patterns could distinguish patients with OCD from HCs, and neuroimaging-transcriptomic analysis was performed to investigate the spatial association between aberrant FCs and gene expression profiles. Compared to HCs, patients with OCD exhibited decreased FCs between goal-directed system and the default mode network (DMN) and central executive network (CEN), as well as between habitual system and salience network (SN). Conversely, increased FCs were observed between habitual system and DMN. No significant correlations were observed between altered FCs and clinical characteristics after multiple-comparison correction. Exploratory SVM analysis indicated that altered FC patterns of goal-directed system showed higher classification performance (accuracy = 90.83
Early identification of individuals at high risk for Alzheimer’s disease (AD) is crucial for disease prevention and intervention. This study aims to develop AD-specific transcriptomic risk scores (TRSs) through multi-tissue transcriptome-wide association study (TWAS) and to evaluate its clinical utility in AD diagnosis and risk prediction. Using GWAS summary statistics combined with expression quantitative trait loci (eQTL) data from 14 tissues, a multi-tissue TWAS approach was applied to identify AD-associated genes. Peripheral blood RNA expression data from the ADNI and GEO databases were used to construct the AD-specific TRSs. The associations of TRSs with AD pathological features and cognitive function were assessed in two independent cohorts. Furthermore, the diagnostic performance, differential diagnostic capability, and risk prediction efficiency of TRSs were evaluated. The TWAS identified 131 genes significantly associated with AD. The TRSs were significantly elevated in patients with AD and mild cognitive impairment (MCI) compared to cognitively normal (CN) individuals, and showed significant correlations with AD pathological markers and cognitive performance. When combined with APOE4 status, the TRSs demonstrated robust diagnostic ability for AD and MCI. When combined with age, the TRSs showed good diagnostic performance in distinguishing AD from frontotemporal dementia (FTD) (AUC = 0.86). Additionally, the TRSs effectively predicted the risk of progression to AD in non-AD individuals (HR = 1.74). The AD-specific TRSs developed in this study shows promising clinical utility in AD diagnosis, differential diagnosis, and risk prediction, providing valuable translational medical evidence for early screening and precision prevention of Alzheimer’s disease.
Postpartum depression (PPD) is one of the most common and debilitating complications of childbirth, yet the candidate proteins linking genetic risk to disease remain poorly defined. Building on recent genome-wide association studies (GWAS), we sought to integrate cross-tissue proteogenomic data to identify candidate proteins for PPD and explore therapeutic opportunities. We conducted two-sample Mendelian randomization (MR) using genome-wide significant cis-protein QTLs from brain (n = 608 proteins), cerebrospinal fluid (CSF; n = 214), and plasma (n = 612). PPD summary statistics were obtained from FinnGen R8 (13,657 cases, 236,178 controls) and replicated in an independent GWAS. Phenome-wide association (PheWAS) was used to assess pleiotropy. Potential therapeutic targets were evaluated through DSigDB drug repurposing, molecular docking, and molecular dynamics simulations. Among all proteins tested, RAB27B was the only brain-derived protein surpassing Bonferroni correction (OR = 1.60; 95
