Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap

Toripalimab plus platinum-doublet chemotherapy as perioperative therapy for initially unresectable NSCLC: An open-label, phase 2 trial

BACKGROUND

Perioperative treatment with toripalimab combined with chemotherapy was efficacious and safe in resectable stage II-IIIA non-small cell lung cancer (NSCLC); however, little is known about whether this treatment regimen could convert unresectable NSCLC to resectable.

METHODS

This study enrolled 40 treatment-naive patients with initially unresectable stage IIIA-IIIB NSCLC. Toripalimab (240 mg) and platinum-doublet chemotherapy were administered every 3 weeks for 2-4 cycles. Surgical resection was decided after assessing the efficacy of induction therapy. The primary outcome was the R0 resection rate. The secondary outcomes included safety, overall survival, disease-free survival, event-free survival, objective response rate, major pathological response (MPR), and pathological complete response (pCR). Available baseline tumor biopsy samples were used for molecular biomarker analyses, including bulk RNA sequencing and multiplex immunostaining. This study was registered at ClinicalTrials.gov: NCT04144608.

FINDINGS

Of the 40 patients who received induction toripalimab plus chemotherapy, 29 (72.5%) patients received surgery, and all achieved R0 resection (100% R0 rate). Of these patients, 17 (58.6%) achieved MPR, with 10 (34.5%) patients evaluated as pCR. With a median follow-up of 31.8 months (95% confidence interval [CI]: 24.2-39.4), the median event-free survival and overall survival were not reached. Molecular analyses revealed highly expressed gene sets for germinal center B cells (signatures of tertiary lymphoid structure [TLS]) at baseline among patients with pCR compared to patients with non-pCR, suggesting that the TLS status of the patients was associated with the induction of immunotherapy responses.

CONCLUSIONS

Toripalimab-based induction treatment of initially unresectable NSCLC yielded a high R0 rate and MPR rate, with a good safety profile and encouraging survival outcomes.

FUNDING

This work was funded by the National Natural Science Foundation of China.

Revealing differential psychotic symptoms in schizophrenia and bipolar I disorder by manifold learning and network analyses

The field of psychiatry has encountered ongoing challenges in understanding the intricate nature of psychotic symptoms, particularly when they manifest in individuals diagnosed with bipolar disorder or schizophrenia. In this study, we employed manifold and network analyses to investigate whether the pattern of symptom occurrence differs between schizophrenia and bipolar I disorder. We analyzed data collected from 555 individuals, 282 of whom were diagnosed with schizophrenia-related disorders and 273 with bipolar I disorder. In the context of schizophrenia, negative symptoms, particularly avolition, were prominent with manifold and network analyses, identifying avolition as a high central symptom associated with clozapine use, patterns of deterioration, tendency toward remission, and illness severity. Conversely, bipolar I disorder exhibits discernible patterns where positive symptoms play a central role in network analysis. Unexpectedly, manifold analysis revealed two distinct clusters of patients, suggesting variability in psychotic symptom profiles within bipolar I disorder. In conclusion, schizophrenia and bipolar I disorder, while sharing psychotic symptoms, exhibit distinct co-occurrence patterns. Schizophrenia demonstrates negative symptoms, whereas bipolar I disorder exhibits a stronger interconnectivity of psychotic symptoms, highlighting the complexity of psychotic symptom patterns and their relevance for understanding psychiatric disorders. These findings highlight the complexity of psychotic symptom patterns and their relevance for understanding psychiatric disorders.

Genetic analysis of psychosis Biotypes: shared Ancestry-adjusted polygenic risk and unique genomic associations

The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) created psychosis Biotypes based on neurobiological measurements in a multi-ancestry sample. These Biotypes cut across DSM diagnoses of schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis. Two recently developed post hoc ancestry adjustment methods of Polygenic Risk Scores (PRSs) generate Ancestry-Adjusted PRSs (AAPRSs), which allow for PRS analysis of multi-ancestry samples. Applied to schizophrenia PRS, we found the Khera AAPRS method to show superior portability and comparable prediction accuracy as compared with the Ge method. The three Biotypes of psychosis disorders had similar AAPRSs across ancestries. In genomic analysis of Biotypes, 12 genes, and isoforms showed significant genomic associations with specific Biotypes in a Transcriptome-Wide Association Study (TWAS) of genetically regulated expression (GReX) in the adult brain and fetal brain. TWAS inflation was addressed by the inclusion of genotype principal components in the association analyses. Seven of these 12 genes/isoforms satisfied Mendelian Randomization (MR) criteria for putative causality, including four genes TMEM140, ARTN, C1orf115, CYREN, and three transcripts ENSG00000272941, ENSG00000257176, ENSG00000287733. These genes are enriched in the biological pathways of Rearranged during Transfection (RET) signaling, Neural Cell Adhesion Molecule 1 (NCAM1) interactions, and NCAM signaling for neurite out-growth. The specific associations with Biotypes suggest that pharmacological clinical trials and biological investigations might benefit from analyzing Biotypes separately.

A review on the validity of animal models for neuropsychiatric disorders: an exploration of anhedonia

Despite major advances in neuroscience, there has been limited progress in improving pharmacological treatment for neuropsychiatric disorders. Neuropsychiatric disorders are heterogeneous with variance in symptoms within disorders and partial overlap in symptoms between disorders, leading to symptoms that remain untreated. To improve treatment outcomes, neuroscience has shifted to examining the neurobiological mechanisms underlying individual components, or dysfunctions, across disorders. Anhedonia, a decreased capacity to experience pleasure from positive stimuli or rewards, is a prominent symptom associated with poor functional outcome across neuropsychiatric disorders. This article reflects on Professor Paul Willner's contributions to the field of behavioural neuroscience, specifically his promotion of validity in animal models of neuropsychiatric disorders. Research can build upon Willner's scholarship by continuing to refine and explore the validity of animal models as our understanding of neuropsychiatric disorders improves. To exemplify this, we discuss current understanding of the neurobiological basis and clinical presentation of the two domains of anhedonia: anticipation and consumption. We argue for the examination of anticipatory anhedonia and consummatory anhedonia within a single paradigm to improve understanding of these domains, aligning animal models to the clinical reality in humans.

Recent Advances in Schizophrenia Genomics and Emerging Clinical Implications

The conceptualization of schizophrenia has evolved from Emil Kraepelin's identification of "dementia praecox" as a distinct illness characterized by cognitive and functional deficits to the modern understanding of its complex nature. Recent research, including the "deficit syndrome," highlights enduring negative symptoms that correlate with poor functional outcomes. Genetic epidemiologic studies reveal a strong heritable basis (60%-80%) for schizophrenia, with its polygenic architecture overlapping with various mental health disorders. This complexity raises questions about targeted precision medicine. Recent advancements in biobanks and neurogenomics research are providing valuable insights that aim to improve patient outcomes through enhanced genomic understanding.

Genome-wide analyses identify 30 loci associated with obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) affects ~1% of children and adults and is partly caused by genetic factors. We conducted a genome-wide association study (GWAS) meta-analysis combining 53,660 OCD cases and 2,044,417 controls and identified 30 independent genome-wide significant loci. Gene-based approaches identified 249 potential effector genes for OCD, with 25 of these classified as the most likely causal candidates, including WDR6, DALRD3 and CTNND1 and multiple genes in the major histocompatibility complex (MHC) region. We estimated that ~11,500 genetic variants explained 90% of OCD genetic heritability. OCD genetic risk was associated with excitatory neurons in the hippocampus and the cortex, along with D1 and D2 type dopamine receptor-containing medium spiny neurons. OCD genetic risk was shared with 65 of 112 additional phenotypes, including all the psychiatric disorders we examined. In particular, OCD shared genetic risk with anxiety, depression, anorexia nervosa and Tourette syndrome and was negatively associated with inflammatory bowel diseases, educational attainment and body mass index.

Validation of the Hebrew version of the Community Assessment of Psychic Experiences in a sample of Israeli Hebrew speakers

Introduction

The Community Assessment of Psychic Experiences (CAPE-42) is a reliable tool to assess psychotic experiences (PEs) in clinical and non-clinical populations, in research and clinical settings.

Methods

To investigate cultural differences in PEs and control for pathological behavior in non-clinical groups, we developed a Hebrew version of the CAPE-42 using the translation/back-translation method. A total of 359 Hebrew speaking Israelis participated in an online study comprising the CAPE-42, the Autistic Quotient (AQ), the Center for Epidemiological Study - Depression Scale (CES-D), and the Prodromal Questionnaire - Brief Version (PQ-B). We examined the psychometric properties of the Hebrew CAPE-42-including its factor structure, internal consistency, gender invariance, and validity. We also investigated the independent and interaction effects of psychotic and autistic traits on depressive symptoms.

Results

Reliability analysis demonstrated very good internal consistency, and confirmatory factor analysis supported the eight-factor model, which included depressive, social withdrawal, affective flattening, avolition, bizarre experiences, perceptual abnormalities, persecutory ideation, and magical thinking. Demonstrating its predictive and convergent validity, we found significant correlations with the CES-D and the PQ-B. The predictive model showed that both psychotic and autistic traits are independent, non-interacting, predictors of depressive symptoms.

Conclusions

The Hebrew CAPE-42 offers a valuable instrument for investigating PEs in the Hebrew-speaking population and facilitates cross-cultural studies.

Mitochondrial Oxidative Phosphorylation System Dysfunction in Schizophrenia

Schizophrenia (SCZ) is a severe, chronic mental disorder of unknown etiology and limited therapeutic options. Bioenergetic deficits in the oxidative phosphorylation system (OXPHOS) during early postnatal brain development may underlie disrupted neuronal metabolism and synaptic signaling, contributing to the neurodevelopmental and behavioral disturbances observed in patients. This narrative review summarizes updated evidence linking mitochondrial-OXPHOS dysfunction to SCZ pathophysiology. The novelty lies in the focus on OXPHOS dysfunction at the enzymatic/functional level, rather than on genetic, transcriptional, or oxidative parameters. While complex I impairment has long been highlighted and proposed as a peripheral marker of the disease, recent studies also report alterations in other OXPHOS complexes and their precursors. These findings suggest that OXPHOS dysfunction is not isolated to a single enzymatic component but affects broader mitochondrial function, alongside oxidative stress, contributing to disease progression through mechanisms involving apoptosis, accelerated aging, and synaptic deterioration. OXPHOS dysfunction in both central and peripheral tissues further supports its relevance to SCZ. Overall, the literature points to mitochondrial OXPHOS abnormalities as a significant biological feature of SCZ. Whether these alterations are causal factors or consequences of disease processes remains unclear. Understanding OXPHOS dysregulation may open new avenues for targeted therapies.

Identifying novel protein biomarkers with cross-psychiatric disorders effects and potential intervention targets: Evidence from proteomic-Mendelian randomization

Plasma proteins are the potential therapeutic targets for psychiatric disorders due to their important roles in signal transduction. We aimed to explore the plasma protein biomarkers with cross-psychiatric disorders effects. Proteome-wide Mendelian randomization (MR) and colocalization analyses were performed to investigate the potential causal relationship between plasma protein biomarkers and 12 psychiatric disorders and further identify the potential proteins with cross-effects. To assess the directionality and exclude potential reverse causation, Steiger directionality tests and reverse MR analyses were additionally conducted. Then, validation analysis was performed by employing summary data from cross-psychiatric disorder GWAS to validate the cross-psychiatric effects of proteins. Protein-protein interactions were conducted to evaluate the interaction between candidate proteins and druggability assessment was used to prioritize potential drug targets for psychiatric disorders. We identified novel plasma proteins that possessed cross-psychiatric disorder effects, especially BTN2A1 and BTN3A2 associated with major depressive disorder (MDD), schizophrenia (SCZ), and bipolar disorder (BIP); ITIH1, ITIH3, ITIH4 and FES associated with SCZ and BIP, and the cross-effects of these proteins on SCZ and BIP were confirmed by validation analyses. Steiger tests and reverse MR supported causal directionality. Besides, the protein-protein interactions (PPI) analysis indicated cross-effects proteins had significant interaction, especially ITIH1-ITIH3. The druggability assessment prioritized eight proteins, two of which (ITIH3 and NCAM1) has been targeted by antipsychotic drugs. Our findings provided insights into shared biological mechanisms underlying these conditions.

Macrophage HM13/SPP Enhances Foamy Macrophage Formation and Atherogenesis

Aryl Hydrocarbon Receptor-Interacting Protein (AIP) reduces macrophage cholesterol-ester accumulation and may prevent atherogenic foamy macrophage formation. Analyzing AIP-associated regulatory gene networks can aid in identifying key regulatory mechanism(s) underlying foamy macrophage formation. A weighted gene co-expression network analysis on the Stockholm Atherosclerosis Gene Expression (STAGE) patient cohort identifies AIP as a negative correlate of Histocompatibility Minor 13 (HM13), which encodes the ER-associated degradation (ERAD) protein Signal Peptide Peptidase (HM13/SPP). The negative correlation between AIP and HM13/SPP on mRNA and protein levels is validated in oxLDL-stimulated macrophages and human plaque foamy macrophages. Mechanistically, AIP, via its chaperone interaction with Aryl Hydrocarbon Receptor (AHR), inhibits p38-c-JUN-mediated HM13 transactivation, thereby suppressing macrophage lipid accumulation. Myeloid HM13/SPP overexpression enhances oxLDL-induced foamy macrophage formation in vitro as well as atherogenesis and plaque foamy macrophage load in vivo, while myeloid HM13/SPP knockout produces the opposite effects. Mechanistically, myeloid HM13/SPP enhances oxLDL-induced foamy macrophage formation in vitro as well as atherogenesis and plaque foamy macrophage load in vivo via promoting ERAD-mediated proteasomal degradation of the metabolic regulator Heme Oxygenase-1 (HO-1). In conclusion, AIP downregulates macrophage HM13/SPP, a driver of oxLDL-induced lipid loading, foamy macrophage generation, and atherogenesis.

Transcriptome-wide analysis of differential expression in perturbation atlases

Single-cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of genetic perturbations at scale. However, the data produced by these screens are noisy, and many effects may go undetected. Here we introduce transcriptome-wide analysis of differential expression (TRADE)-a statistical model for the distribution of true differential expression effects that accounts for estimation error appropriately. TRADE estimates the 'transcriptome-wide impact', which quantifies the total effect of a perturbation across the transcriptome. Analyzing several large Perturb-seq datasets, we show that many transcriptional effects remain undetected in standard analyses but emerge in aggregate using TRADE. A typical gene perturbation affects an estimated 45 genes, whereas a typical essential gene affects over 500. We find moderate consistency of perturbation effects across cell types, identify perturbations where transcriptional responses vary qualitatively across dosage levels and clarify the relationship between genetic and transcriptomic correlations across neuropsychiatric disorders.

A multi-omic approach implicates novel protein dysregulation in post-traumatic stress disorder

BACKGROUND

Post-traumatic stress disorder (PTSD) is a common and disabling psychiatric disorder. PTSD involves multiple brain regions and is often comorbid with other psychiatric disorders, such as major depressive disorder (MDD). Recent genome-wide association studies (GWASs) have identified many PTSD risk loci and transcriptomics studies of postmortem brain have found differentially expressed genes associated with PTSD cases. In this study, we integrated genome-wide measures across modalities to identify convergent molecular effects in the PTSD brain.

METHODS

We performed tandem mass spectrometry (MS/MS) on a large cohort of donors (N = 66) in two prefrontal cortical areas, dorsolateral prefrontal cortex (DLPFC), and subgenual prefrontal cortex (sgPFC). We also coupled the proteomics data with transcriptomics and microRNA (miRNA) profiling from RNA-seq and small-RNA sequencing, respectively for the same cohort. Additionally, we utilized published GWAS results of multiple psychiatric disorders for integrative analysis.

RESULTS

We found differentially expressed proteins and co-expression protein modules disrupted by PTSD. Integrative analysis with transcriptomics and miRNA data from the same cohort pointed to hsa-mir-589 as a regulatory miRNA responsible for dysregulation of neuronal protein networks for PTSD, including the gamma-aminobutyric acid (GABA) vesicular transporter, SLC32A1. In addition, we identified significant enrichment of risk genes for other psychiatric disorders, such as autism spectrum disorder (ASD) and major depressive disorder (MDD) within PTSD protein co-expression modules, suggesting shared molecular pathology.

CONCLUSIONS

We integrated genome-wide measures of mRNA and miRNA expression and proteomics profiling from PTSD, MDD, and control (CON) brains to identify convergent and divergent molecular processes across genomic modalities. We substantially expand the number of differentially expressed genes and proteins in PTSD and identify downregulation of GABAergic processes in the PTSD proteome. This provides a novel framework for future studies integrating proteomic profiling with transcriptomics and non-coding RNAs in the human brain studies.

Acute and Long-Term Consequences of Neonatal NMDA Blockade in the Cx3cr1 Knock-Out Mouse

Neuron-microglia communication through the fractalkine pathway is a critical factor mediating microglial proliferation, migration, release of mediators, and clearance of cellular debris, as well as the function of neuronal NMDA receptors. Disruption of the fractalkine-mediated microglia-neuron communication is associated with divergent outcomes, from damaging to protective, in different neurological conditions (including schizophrenia and epilepsy). In the present work we explore the impact of the absence of the fractalkine receptor (CX3CR1) after neonatal blockade of NMDA receptors, which induces acute and long-term alterations in behavior, neuronal integrity and excitability. Wild-type (WT) and Cx3cr1-/- (KO) mice of both sexes randomly received either a low (0.5 mg/kg) or high dose (1 mg/kg) of MK-801 (NMDA receptor antagonist) or saline, for five consecutive days, during early postnatal development. Neuronal apoptosis was assessed at a midpoint of the pharmacological protocol. Survival and growth rates were determined up to adulthood when innate behaviors, unconditioned anxiety, contextual memory and seizure susceptibility were evaluated, as well as hippocampal local field potential and sensory gating. CX3CR1 depletion and neonatal MK-801 treatment had a synergistic acute effect, increasing neuronal apoptosis and overall mortality. Both factors independently induced long-lasting impairments in the wide array of behavioral tasks assessed during adulthood. However, low MK-801 dose treatment greatly augmented the mortality of pentylenetetrazol-induced seizures in WT mice, an effect prevented by CX3CR1 depletion. MK-801 treatment induced a shift in the power spectrum of the hippocampal local field potential towards higher frequencies that was averted in Cx3cr1-/- mice by an opposite shift. Our results reveal that CX3CR1 depletion severely increases the vulnerability to neonatal NMDA antagonism with additional complex interactions regarding cognitive and neurophysiological effects, which should be considered in the context of neuron-microglia miscommunication in many neurological disorders including schizophrenia and epilepsy.

Large-scale transcriptomic analyses of major depressive disorder reveal convergent dysregulation of synaptic pathways in excitatory neurons

Major Depressive Disorder (MDD) is a common, complex disorder that is a leading cause of disability worldwide and a significant risk factor for suicide. In this study, we have performed the largest molecular analysis of MDD in postmortem human brains (846 samples across 458 individuals) in the subgenual Anterior Cingulate Cortex (sACC) and the Amygdala, two regions central to mood regulation and the pathophysiology of MDD. We found extensive expression differences, particularly at the level of specific transcripts, with prominent enrichment for genes associated with the vesicular functioning, the postsynaptic density, GTPase signaling, and gene splicing. We find associated transcriptional features in 107 of 243 genome-wide significant loci for MDD and, through integrative analyses, highlight convergence of genetic risk, gene expression, and network-based analyses on dysregulated glutamatergic signaling and synaptic vesicular functioning. Together, these results provide an initial mechanistic understanding of MDD and highlight potential targets for novel drug discovery.

Advances in discerning the mechanisms underlying depression and resiliency: relation to the neurobiology of stress and the effects of antidepressants

Depression denotes a dysregulated stress response with significant mental and health implications. This review examines the neurobiological mechanisms underlying depression and resilience, focusing on how stress mediators influence vulnerability to severe stressors contrasted with resilience. We analyze structural and functional alterations in key brain regions, genetic factors, and potential therapeutic interventions. Understanding these mechanisms offers insights into preventing depression onset instead of solely treating its manifestations.

Simultaneous CRISPR screening and spatial transcriptomics reveal intracellular, intercellular, and functional transcriptional circuits

Pooled optical screens have enabled the study of cellular interactions, morphology, or dynamics at massive scale, but they have not yet leveraged the power of highly plexed single-cell resolved transcriptomic readouts to inform molecular pathways. Here, we present a combination of imaging spatial transcriptomics with parallel optical detection of in situ amplified guide RNAs (Perturb-FISH). Perturb-FISH recovers intracellular effects that are consistent with single-cell RNA-sequencing-based readouts of perturbation effects (Perturb-seq) in a screen of lipopolysaccharide response in cultured monocytes, and it uncovers intercellular and density-dependent regulation of the innate immune response. Similarly, in three-dimensional xenograft models, Perturb-FISH identifies tumor-immune interactions altered by genetic knockout. When paired with a functional readout in a separate screen of autism spectrum disorder risk genes in human-induced pluripotent stem cell (hIPSC) astrocytes, Perturb-FISH shows common calcium activity phenotypes and their associated genetic interactions and dysregulated molecular pathways. Perturb-FISH is thus a general method for studying the genetic and molecular associations of spatial and functional biology at single-cell resolution.

Hypometabolism in Autism Spectrum Disorder: Insights from Brain and Blood Transcriptomics

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by challenges in social communication, repetitive behaviors, and restricted interests. Recent research has emphasized the importance of metabolic dysfunctions in the pathophysiology of ASD. This study investigates metabolic alterations associated with ASD by analyzing transcriptomic data obtained from the prefrontal cortex (bulk tissue and single-nucleus) and data from peripheral blood mononuclear cells (PBMC). We assessed the metabolic activity of each patient based on gene expression profiles, revealing significant downregulation of vital metabolic pathways, including glycolysis, the tricarboxylic acid (TCA) cycle, and oxidative phosphorylation, indicative of hypometabolism. Our analysis also highlighted dysregulation in lipid, vitamin, amino acid, and heme metabolism, which may contribute to the neurodevelopmental delays associated with ASD. Cell-specific metabolic activities in the ASD brain showed altered pathways in astrocytes, oligodendrocytes, excitatory neurons, and interneurons. Furthermore, we identified critical metabolic pathways and genes from PBMC gene expression data that distinguish ASD patients from typically developing individuals. Our findings demonstrate a consistent pattern of metabolic dysfunction across brain and blood samples. This research provides a comprehensive understanding of metabolic alterations in ASD, paving the way for exploring potential therapeutic strategies targeting metabolic dysregulation.

Rare mutations implicate CGE interneurons as a vulnerable axis of cognitive deficits across psychiatric disorders

Neuropsychiatric disorders such as autism spectrum disorder (ASD) and schizophrenia (SCZ) share genetic risk factors, including rare high penetrance single nucleotide variants and copy number variants (CNVs), and exhibit both overlapping and distinct clinical phenotypes. Cognitive deficits and intellectual disability-critical predictors of long-term outcomes-are common to both conditions. To investigate shared and disorder-specific neurobiological impact of highly penetrant rare mutations in ASD and SCZ, we analyzed human single-nucleus whole-brain sequencing data to identify strongly affected brain cell types. Our analysis revealed Caudal Ganglionic Eminence (CGE)-derived GABAergic interneurons as a key nexus for cognitive deficits across these disorders. Notably, genes within 22q11.2 deletions, known to confer a high risk of SCZ, ASD, and cognitive impairment, showed a strong expression bias toward vasoactive intestinal peptide-expressing cells (VIP+) among CGE subtypes. To explore VIP+ GABAergic interneuron perturbations in the 22q11.2 deletion syndrome in vivo , we examined their activity in the Df(16)A +/- mouse model during a spatial navigation task and observed reduced activity along with altered responses to random rewards. At the population level, VIP+ interneurons exhibited impaired spatial encoding and diminished subtype-specific activity suggesting deficient disinhibition in CA1 microcircuits in the hippocampus, a region essential for learning and memory. Overall, these results demonstrate the crucial role of CGE-derived interneurons in mediating cognitive processes that are disrupted across a range of psychiatric and neurodevelopmental disorders.

Astrocyte glypican 5 regulates synapse maturation and stabilization

The maturation and stabilization of appropriate synaptic connections is a vital step in neural circuit development; however, the molecular signals underlying these processes are not fully understood. We show that astrocytes, through production of glypican 5 (GPC5), are required for maturation and refinement of synapses in the mouse cortex during the critical period. In the absence of astrocyte GPC5, thalamocortical synapses show structural immaturity, including smaller presynaptic terminals, decreased postsynaptic density area, and presence of more postsynaptic partners at multisynaptic connections. This structural immaturity is accompanied by a delay in developmental incorporation of GLUA2-containing AMPARs at intracortical synapses. The functional impact of this is that mice lacking astrocyte GPC5 exhibit increased levels of ocular dominance plasticity in adulthood. This demonstrates that astrocyte GPC5 is necessary for maturation and stabilization of synaptic connections, which has implications for disorders with altered synaptic function where GPC5 levels are altered, including Alzheimer's disease and frontotemporal dementia.

Transcriptomic and genetic analysis suggests a role for mitochondrial dysregulation in schizophrenia

Schizophrenia is an often devastating disorder characterized by persistent and idiopathic cognitive deficits, delusions and hallucinations. Schizophrenia has been associated with impaired nervous system development and an excitation/inhibition imbalance in the prefrontal cortex. On a molecular level, schizophrenia is moderately heritable and genetically complex. Hundreds of risk genes have been identified, spanning a heterogeneous landscape dominated by loci that confer relatively small risk. Bioinformatic analyses of genetic associations point to a limited set of neurons, mainly excitatory cortical neurons, but other analyses suggest the importance of astrocytes and microglia. To understand different cell type roles in schizophrenia and reveal novel cell-type specific aetiologically relevant perturbations in schizophrenia, our study integrated genetic analysis with single nucleus RNA-seq of 536,618 nuclei from postmortem samples of dorsal prefrontal cortex (Brodmann Area 8/9) of 43 cases with schizophrenia and 42 neurotypical controls. We found no significant difference in cell type abundance. Gene expression in excitatory layer 2-3 intra-telencephalic neurons had the greatest number of differentially expressed transcripts and, together with excitatory deep layer intra-telencephalic neurons, conferred most of the genetic risk for schizophrenia. Most differential expression of genes was found in specific cell types and was dominated by down-regulated transcripts. Down-regulated transcripts were enriched in gene sets including transmembrane transport, mitochondrial function, protein folding, and cell-cell signaling whereas up-regulated transcripts were enriched in gene sets related to RNA processing, including RNA splicing in neurons. Co-regulation network analysis identified 40 schizophrenia-relevant programs across 13 cell types. A gene program largely shared between neuronal subtypes, astrocytes, and oligodendrocytes was significantly enriched for schizophrenia risk, supporting an aetiological role for perturbed protein modification, ion transport, and mitochondrial function. These results were largely consistent with cell-type expression quantitative trait locus and transcriptome-wide association analyses. Moreover, single-cell RNA sequencing results, most prominently mitochondrial dysfunction, had multiple points of convergence with proteomic and long-read RNA sequencing results from samples from the same donors. Our study integrates genetic analysis with transcriptomics to reveal novel cell-type specific aetiologically relevant perturbations in schizophrenia.

Involvement of virus infections and antiviral agents in schizophrenia

BACKGROUND

Schizophrenia is a chronic and complex mental disorder resulting from interactions between cumulative and synergistic genetic and environmental factors. Viral infection during the prenatal stage constitutes one of the most relevant risk factors for the development of schizophrenia later in adulthood.

METHODS

A narrative review was conducted to explore the link between viral infections and schizophrenia, as well as the neuropsychiatric effects of antiviral drugs, particularly in the context of this specific mental condition. Literature searches were performed using the PubMed, Scopus, and Web of Science databases.

RESULTS

Several viral infections, such as herpesviruses, influenza virus, Borna disease virus, and coronaviruses, can directly or indirectly disrupt normal fetal brain development by modifying gene expression in the maternal immune system, thereby contributing to the pathophysiological symptoms of schizophrenia. In addition, neuropsychiatric effects caused by antiviral drugs are frequent and represent significant adverse outcomes for viral treatment.

CONCLUSIONS

Epidemiological evidence suggests a potential relationship between viruses and schizophrenia. Increases in inflammatory cytokine levels and changes in the expression of key genes observed in several viral infections may constitute potential links between these viral infections and schizophrenia. Furthermore, antivirals may affect the central nervous system, although for most drugs, their mechanisms of action are still unclear, and a strong relationship between antivirals and schizophrenia has not yet been established.

Transcriptomic pathology of neocortical microcircuit cell types across psychiatric disorders

Psychiatric disorders such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are characterized by altered cognition and mood, brain functions that depend on information processing by cortical microcircuits. We hypothesized that psychiatric disorders would display cell type-specific transcriptional alterations in neuronal subpopulations that make up cortical microcircuits: excitatory pyramidal (PYR) neurons and vasoactive intestinal peptide- (VIP), somatostatin- (SST), and parvalbumin- (PVALB) expressing inhibitory interneurons. Using laser capture microdissection followed by RNA sequencing (LCM-seq), we performed cell type-specific molecular profiling of subgenual anterior cingulate cortex, a region implicated in mood and cognitive control. We sequenced libraries from 130 whole cells pooled per neuronal subtype (VIP, SST, PVALB, superficial and deep PYR) in 76 subjects from the University of Pittsburgh Brain Tissue Donation Program, evenly split between MDD, BD and SCZ subjects and healthy controls (totaling 380 bulk transcriptomes from ~50,000 neurons). We identified hundreds of differentially expressed (DE) genes and biological pathways across disorders and neuronal subtypes, with the vast majority in interneurons, particularly PVALB. While DE genes were unique to each cell type, there was a partial overlap across disorders for genes involved in the formation and maintenance of neuronal circuits. We observed coordinated alterations in biological pathways between select pairs of microcircuit cell types, also partially shared across disorders. Finally, DE genes coincided with known risk variants from psychiatric genome-wide association studies, suggesting cell type-specific convergence between genetic and transcriptomic risk for psychiatric disorders. Our study suggests transdiagnostic cortical microcircuit pathology in SCZ, BD, and MDD and sets the stage for larger-scale studies investigating how cell circuit-based changes contribute to shared psychiatric risk.

Weighted Gene Networks Derived from Multi-Omics Reveal Core Cancer Genes in Lung Cancer

Lung cancer remains the leading cause of cancer-related deaths worldwide, driven by its complexity and the heterogeneity of its subtypes, which influence pathogenesis, tumor microenvironment, and genetic alterations. We developed a novel weighted gene regulatory network reconstruction method based on maximum entropy and Markov chain entropy principles, which integrates gene expression and DNA methylation data to generate biologically informed networks. Applied to LUAD and LUSC datasets, we define a network methylation index to determine whether gene methylation acts as oncogenic or tumor-suppressive. By revealing a stable core set of pathogenic genes, we identify not only genes with significant expression changes, such as CD74 and HGF, but also pathogenic genes with stable expression, such as BRAF and KDM6A. Additionally, we uncover potential driver genes, such as CORO2B and C20orf194, associated with disease stage, gender, and smoking status. This method offers a more comprehensive understanding of NSCLC mechanisms, paving the way for improved therapeutic strategies.

A neuro-immune axis of transcriptomic dysregulation within the subgenual anterior cingulate cortex in schizophrenia

Many genes are linked to psychiatric disorders, but genome-wide association studies (GWAS) and differential gene expression (DGE) analyses in post-mortem brain tissue often implicate distinct gene sets. This disconnect impedes therapeutic development, which relies on integrating genetic and genomic insights. We address this issue using a novel multivariate technique that reduces DGE bias by leveraging gene co-expression networks and controlling for confounds such as drug exposure. Deep RNA sequencing was performed in bulk post-mortem sgACC from individuals with bipolar disorder (BD; N=35), major depression (MDD; N=51), schizophrenia (SCZ; N=44), and controls (N=55). Toxicology data dimensionality was reduced using multiple correspondence analysis; case-control gene expression was then analyzed using 1) traditional DGE and 2) group regularized canonical correlation analysis (GRCCA) - a multivariate regression method that accounts for feature interdependence. Gene set enrichment analyses compared results with established neuropsychiatric risk genes, gene ontology pathways, and cell type enrichments. GRCCA revealed a significant association with SCZ ( P perm =0.001; no significant BD or MDD association), and the resulting gene weight vector correlated with DGE SCZ-control t-statistics ( R =0.53; P <0.05). Both methods indicated down-regulation of immune and microglial genes and upregulation of ion transport and excitatory neuron genes. However, GRCCA - at both the gene and transcript level - showed stronger enrichments (FDR<0.05). Notably, GRCCA results were enriched for SCZ GWAS-implicated genes (FDR<0.05), while DGE results were not. These findings identify a SCZ-specific sgACC gene expression pattern that highlights SCZ risk genes and implicates neuro-immune pathways, thus demonstrating the utility of multivariate approaches to integrate genetic and genomic signals.

Impact of life adversity and gene expression on psychiatric symptoms in children and adolescents: findings from the Brazilian high risk cohort study

Introduction

While the influence of both genetic and environmental factors on the development of psychiatric symptoms is well-recognized, the precise nature of their interaction throughout development remains a subject of ongoing debate. This study investigated the association between the expression of 78 candidate genes, previously associated with psychiatric phenotypes, in peripheral blood and both adversity and psychopathology in a sample of 298 young individuals assessed at two time points from the Brazilian High Risk Cohort Study for Mental Conditions (BHRCS).

Methods

Psychopathology was assessed using the Child Behavior Checklist (CBCL), considering the total CBCL, p-factor (i.e. general factor of psychopathology), and internalizing and externalizing symptoms as clinical variables. The life adversities considered in this study includes four composite variables: child maltreatment, stressful life events, threat and deprivation. Gene expression was measured using next-generation sequencing for target genes and differential gene expression was analyzed with the DESeq2 package.

Results

Mixed models revealed six genes associated with internalizing symptoms: NR3C1, HSPBP1, SIN3A, SMAD4, and CRLF3 genes exhibited a negative correlation with these symptoms, while FAR1 gene showed a positive correlation. Additionally, we also found a negative association between USP38 gene expression and externalizing symptoms. Finally, DENND11 and PRRC1 genes were negatively associated with deprivation, a latent factor characterized by neglect, parental absence, and measures of material forms of deprivation. No mediation or moderation effect was observed of gene expression on the association between life adversities and psychiatric symptoms, meaning that they might influence distinct pathways.

Discussion

Among these nine genes, NR3C1, which encodes a glucocorticoid receptor, is by far the most investigated, being associated with depressive symptoms, early life adversity, and stress. While further research is needed to fully understand the complex relationship between gene expression, life adversities, and psychopathology, our findings provide valuable insights into the molecular mechanisms underlying mental disorders.

Investigating Connectivity Gradients in Schizophrenia: Integrating Functional, Structural, and Genetic Perspectives

Background: Schizophrenia is a complex disorder characterized by disruptions in cognition, behavior, and emotions. Extensive research has uncovered alterations in a single modality (either the brain structure or function) in schizophrenia. However, the limitation is that a single modality could not offer a synchronous result between the brain structure and function because of different samples. Here, a multiparametric approach is essential to understand the common and distinct alterations between the brain structure and function in schizophrenia. Methods: We analyzed structural and functional magnetic resonance imaging data from 146 participants (72 individuals with schizophrenia and 74 healthy controls). Individual morphological similarity and functional connectivity gradients were computed using a nonlinear dimensionality reduction technique with diffusion map embedding. Furthermore, to understand how the alterations may be related to genetic underpinnings, gene expression enrichment analyses were conducted using Allen Brain Human Atlas and GOrilla. Results: Compared with controls, patients with schizophrenia had reduced scores on the principal functional gradient of the visual network and elevated scores on the principal functional gradient of the limbic network, the frontoparietal control network, and the default mode network. Additionally, the main functional gradient in individuals with schizophrenia showed compression along the primary axis compared to the healthy control group. These changes were linked to genes involved in synaptic signaling and neuronal development. Conclusions: These results indicate connectome gradient dysfunction in schizophrenia and its linkage with gene expression profiles, supporting widespread network-level abnormalities. The integration of neuroimaging provides insight into the neurobiological underpinnings and potential biomarkers for treatment evaluation in this disorder.

Dysregulated Pathways During Pregnancy Predict Drug Candidates in Neurodevelopmental Disorders

Maternal health during pregnancy has a direct impact on the risk and severity of neurodevelopmental disorders (NDDs) in the offspring, especially in the case of drug exposure. However, little progress has been made to assess the risk of drug exposure during pregnancy due to ethical constraints and drug use factors. We collected and manually curated sub-pathways and pathways (sub-/pathways) and drug information to propose an analytical framework for predicting drug candidates. This framework linked sub-/pathway activity and drug response scores derived from gene transcription data and was applied to human fetal brain development and six NDDs. Further, specific and pleiotropic sub-/pathways/drugs were identified using entropy, and sex bias was analyzed in conjunction with logistic regression and random forest models. We identified 19 disorder-associated and 256 regionally pleiotropic and specific candidate drugs that targeted risk sub-/pathways in NDDs, showing temporal or spatial changes across fetal development. Moreover, 5443 differential drug-sub-/pathways exhibited sex-biased differences after filling in the gender labels. A user-friendly NDDP visualization website ( https://ndd-lab.shinyapps.io/NDDP ) was developed to allow researchers and clinicians to access and retrieve data easily. Our framework overcame data gaps and identified numerous pleiotropic and specific candidates across six disorders and fetal developmental trajectories. This could significantly contribute to drug discovery during pregnancy and can be applied to a wide range of traits.

Aberrant Modular Dynamics of Functional Networks in Schizophrenia and Their Relationship with Neurotransmitter and Gene Expression Profiles

Introduction

Numerous studies have emphasized the time-varying modular architecture of functional brain networks and its relevance to cognitive functions in healthy participants. However, how brain modular dynamics change in schizophrenia and how these alterations relate to neurotransmitter and transcriptomic signatures have not been well elucidated.

Methods

We harmonized resting-state fMRI data from a multi-site sample including 223 patients and 279 healthy controls and applied the multilayer network method to estimate the regional module switching rate (flexibility) of functional brain connectomes. We examined aberrant flexibility in patients relative to controls and explored its relations to neurotransmitter systems and postmortem gene expression.

Results

Compared with controls, patients with schizophrenia had significantly higher flexibility in the somatomotor and right visual regions, and lower flexibility in the left parahippocampal gyrus, right supramarginal gyrus, right frontal-operculum-insula, bilateral precuneus posterior cingulate cortex, and bilateral inferior parietal gyrus. These alterations were associated with multiple neurotransmitter systems and weighted gene transcriptomic profiles. The most relevant genes were preferentially enriched for biological processes of transmembrane transport and brain development, specific cell types, and previously identified schizophrenia-related genes.

Conclusions

This study reveals aberrant modular dynamics in schizophrenia and its relations to neurotransmitter systems and schizophrenia-related transcriptomic profiles, providing insights into the understanding of the pathophysiology underlying schizophrenia.

Identification of Hub Genes Involved in Early-onset Schizophrenia: From Genetic Susceptibility to Predicted Regulated Gene Expression

BACKGROUND

Despite a high heritability of schizophrenia (SZ), only limited variance was attributed to gene loci or the polygenic risk score in genome-wide association studies (GWAS). Early-onset SZ, a more homogeneous SZ subtype, may aid in bridging the genotype-phenotype gap and the identification of its hub genes is critical for early intervention in clinical practice. We aimed to examine the gene expression risk score (GeRS) in patients from both multiplex and simplex families to identify hub genes for early-onset SZ, and perform enrichment analysis to understand the biological functions of the hub genes.

METHODS

Based on the GWAS genotype data from patients with SZ in multiplex families (223 early-onset and 372 late-onset) and those from simplex families (matched for sex and onset age), GeRSs for SZ (SZ-GeRSs) were estimated using the SNP-expression prediction model derived from existing brain tissues of patients with psychiatric disorders. Module-based SZ-GeRS was summed over genes from empirically derived gene clusters, network analysis was conducted to identify hub genes, and enrichment analysis was used for functional mapping.

RESULTS

Among the 13 modules from existing coexpression analyses of postmortem brains of patients with psychiatric disorders, the meta-analysis revealed that associations with early-onset SZ existed for the GeRS of module 10 in subset, M10sub-GeRS (adjusted odds ratio [aOR] = 1.38, 95% CI = 1.22-1.57), and six hub genes, M10hub-GeRS (aOR = 1.22, 95% CI = 1.07-1.39), after adjustment for covariates. Functional mapping of the genes revealed their enrichment in excitatory neurons and immune-regulatory pathways.

CONCLUSIONS

GeRS for SZ helps identify six hub genes for early-onset schizophrenia, and the enrichment analysis sheds light on their possible roles in the pathophysiology. These findings will enhance the understanding of SZ etiology and may contribute to early screening and personalized prevention efforts.

Gene expression is associated with brain function of insomnia disorder, rather than brain structure

Previous research has found brain structural and functional abnormalities in patients with insomnia disorder (ID). However, the relationship between brain abnormalities in ID and brain gene expression is unclear. This study explored the relationship between gene expression and brain structural or functional abnormalities in ID, and we validated the reliability of the results with two independent datasets (discover dataset: healthy control (HC) = 129, ID = 264; validation dataset: HC = 160, ID = 115). Brain imaging results show that ID has abnormal resting-state spontaneous activity, regional homogeneity, and widespread gray matter volume reduction compared to HC. The association analysis results with gene expression further revealed that brain function abnormalities in ID were significantly associated with gene expression, but structural abnormalities were not. This study establishes a link between transcriptional changes and brain functional abnormalities in ID, revealing a genetic basis that may involve several biological pathways. Specifically, these pathways include hormonal regulation of the hypothalamic-pituitary-adrenal (HPA) axis, which plays a crucial role in stress response and sleep regulation; ion transport across membranes, vital for neuronal communication; and inhibitory neuronal regulation, essential for maintaining normal brain function. Furthermore, the ID-related genes are enriched for brain tissue and cortical cells, emphasizing their relevance in understanding the biological underpinnings of ID.

Functional genomics of human skeletal development and the patterning of height heritability

Underlying variation in height are regulatory changes to chondrocytes, cartilage cells comprising long-bone growth plates. Currently, we lack knowledge on epigenetic regulation and gene expression of chondrocytes sampled across the human skeleton, and therefore we cannot understand basic regulatory mechanisms controlling height biology. We first rectify this issue by generating extensive epigenetic and transcriptomic maps from chondrocytes sampled from different growth plates across developing human skeletons, discovering novel regulatory networks shaping human bone/joint development. Next, using these maps in tandem with height genome-wide association study (GWAS) signals, we disentangle the regulatory impacts that skeletal element-specific versus global-acting variants have on skeletal growth, revealing the prime importance of regulatory pleiotropy in controlling height variation. Finally, as height is highly heritable, and thus often the test case for complex-trait genetics, we leverage these datasets within a testable omnigenic model framework to discover novel chondrocyte developmental modules and peripheral-acting factors shaping height biology and skeletal growth.

Targeting S100A9 attenuates social dysfunction by modulating neuroinflammation and myelination in a mouse model of autism

Growing evidence supports a role for dysregulated neuroinflammation in autism. However, the underlying mechanisms of microglia-evoked neuroinflammation in the development of autistic phenotypes have not been elucidated. This study aimed to investigate the role and underlying mechanisms of microglial S100 calcium-binding protein A9 (S100A9) in autistic phenotypes. We utilized the BTBR T + tf/J (BTBR) mouse, a reliable preclinical model for autism that displays core behavioral features of autism as well as persistent immune dysregulation. A combination of behavioral, pharmacological, immunological, genetic, molecular, and transcriptomics approaches were used to uncover the potential role of S100A9 in autism. Significant overexpression of microglial S100A9 was observed in the hippocampus of BTBR mice. BTBR mice displayed decreased social communication and increased repetitive behaviors compared to C57BL/6 mice. Interestingly, the above social dysfunction was attenuated by a pharmacological inhibitor of S100A9, accompanied by a significant reduction in the activated microglia morphological phenotype, inflammatory receptors, and proinflammatory cytokines. Notably, S100A9 inhibition decreased c-Fos+ cells and promoted myelination in the cornu ammonis 3 of BTBR mice. Furthermore, the promyelinating compound administration ameliorated the autism-relevant behaviors in BTBR mice. Our findings indicate that microglia-derived S100A9 triggers the neuroinflammation cascade, myelination deficits, and social dysfunction. Targeting S100A9 could, therefore, be a promising therapeutic strategy for neuroinflammation-related neurodevelopmental disorders.

Subtypes of Insomnia Disorder Identified by Cortical Morphometric Similarity Network

Insomnia disorder (ID) is a highly heterogeneous psychiatric disease, and the use of neuroanatomical data to objectively define biological subtypes is essential. We aimed to examine the neuroanatomical subtypes of ID by morphometric similarity network (MSN) and the association between MSN changes and specific transcriptional expression patterns. We recruited 144 IDs and 124 healthy controls (HC). We performed heterogeneity through discriminant analysis (HYDRA) and identified subtypes within the MSN strength. Differences in MSN between subtypes and HC were compared, and clinical behavioral differences were compared between subtypes. In addition, we investigated the association between MSN changes and brain gene expression in different ID subtypes using partial least squares regression to assess genetic commonalities in psychiatric disorders and further performed functional enrichment analyses. Two distinct subtypes of ID were identified, each exhibiting different MSN changes compared to HC. Furthermore, subtype 1 is characterized by objective short sleep, impaired cognitive function, and some relationships with major depressive disorder and autism spectrum disorder (ASD). In contrast, subtype 2 has normal objective sleep duration but subjectively reports poor sleep and is only related to ASD. The pathogenesis of subtype 1 may be related to genes that regulate sleep rhythms and sleep-wake cycles. In contrast, subtype 2 is more due to adverse emotion perception and regulation. Overall, these findings provide insights into the neuroanatomical subtypes of ID, elucidating the relationships between structural and molecular aspects of the relevant subtypes.

Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens

Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models. We explore the roles of common and rare genetic variants, gene-gene and gene-environment interactions, and epigenetic influences in shaping disease phenotypes. Additionally, we emphasize the importance of multi-omics layers including genomic, transcriptomic, proteomic, epigenetic, and metabolomic data in elucidating the molecular mechanisms underlying neurodegeneration. Special attention is given to missing heritability and the contribution of rare variants, particularly in the context of pleiotropy and network pleiotropy. We examine the application of single-cell omics technologies, transcriptome-wide association studies, and epigenome-wide association studies as key approaches for dissecting disease mechanisms at tissue- and cell-type levels. Our review introduces the OmicPeak Disease Trajectory Model, a conceptual framework for understanding the genetic architecture of neurodegenerative disease progression, which integrates multi-omics data across biological layers and time points. This review highlights the critical importance of adopting a systems genetics approach to unravel the complex genetic architecture of neurodegenerative diseases. Finally, this emerging holistic understanding of multi-omics data and the exploration of the intricate genetic landscape aim to provide a foundation for establishing more refined genetic architectures of these diseases, enhancing diagnostic precision, predicting disease progression, elucidating pathogenic mechanisms, and refining therapeutic strategies for neurodegenerative conditions.

mFusion: a multiscale fusion method bridging neuroimages to genes through neurotransmissions in mental health disorders

Mental health disorders emerge from complex interactions among neurobiological processes across multiple scales, which poses challenges in uncovering pathological pathways from molecular dysfunction to neuroimaging changes. Here, we proposed a multiscale fusion (mFusion) method to evaluate the relevance of each gene to the neuroimaging traits of mental health disorders. We combined gene-neuroimaging associations with gene-positron emission tomography (PET) and PET-neuroimaging associations using protein-protein interaction networks, where various genes traced by PET maps are involved in neurotransmission. Compared with previous methods, the proposed algorithm identified more disease genes on both simulated and empirical data sets. Applying mFusion to eight mental health disorders, we found that these disorders formed three clusters with distinct associated genes. In summary, mFusion is a promising tool of prioritizing genes for mental health disorders by establishing gene-PET-neuroimaging pathways.

Comprehensive profiling of small RNAs and their changes and linkages to mRNAs in schizophrenia and bipolar disorder

We investigated small non-coding RNAs (sncRNAs) from the prefrontal cortex of 93 individuals diagnosed with schizophrenia (SCZ) or bipolar disorder (BD) and 77 controls. We uncovered recurring complex sncRNA profiles, with 98% of all sncRNAs being accounted for by miRNA isoforms (60.6%), tRNA-derived fragments (17.8%), rRNA-derived fragments (11.4%), and Y RNA-derived fragments (8.3%). In SCZ, 15% of all sncRNAs exhibit statistically significant changes in their abundance. In BD, the fold changes (FCs) are highly correlated with those in SCZ but less acute. Non-templated nucleotide additions to the 3´-ends of many miRNA isoforms determine their FC independently of miRNA identity or genomic locus of origin. In both SCZ and BD, disease- and age-associated sncRNAs and mRNAs reveal accelerated aging. Co-expression modules between sncRNAs and mRNAs align with the polarities of SCZ changes and implicate sncRNAs in critical processes, including synaptic signaling, neurogenesis, memory, behavior, and cognition.

Endophenotype 2.0: updated definitions and criteria for endophenotypes of psychiatric disorders, incorporating new technologies and findings

Recent genetic studies have linked numerous loci to psychiatric disorders. However, the biological pathways that connect these genetic associations to psychiatric disorders' specific pathophysiological processes are largely unclear. Endophenotypes, first defined over five decades ago, are heritable traits, independent of disease state that are associated with a disease, encompassing a broad range of neurophysiological, biochemical, endocrinological, neuroanatomical, cognitive, and neuropsychological characteristics. Considering the advancements in genetics and genomics over recent decades, we propose a revised definition of endophenotypes as 'genetically influenced phenotypes linked to disease or treatment characteristics and their related events.' We also updated endophenotype criteria to include (1) reliable measurement, (2) association with the disease or its related events, and (3) genetic mediation. 'Genetic mediation' is introduced to differentiate between causality and pleiotropic effects and allows non-linear relationships. Furthermore, this updated Endophenotype 2.0 framework expands to encompass genetically regulated responses to disease-related factors, including environmental risks, illness progression, treatment responses, and resilience phenotypes, which may be state-dependent. This broadened definition paves the way for developing new endophenotypes crucial for genetic analyses in psychiatric disorders. Integrating genetics, genomics, and diverse endophenotypes into multi-dimensional mechanistic models is vital for advancing our understanding of psychiatric disorders. Crucially, elucidating the biological underpinnings of endophenotypes will enhance our grasp of psychiatric genetics, thereby improving disease risk prediction and treatment approaches.

The Mechanisms Underlying the Intergenerational Transmission of Substance Use and Misuse: An Integrated Research Approach

Substance use and substance use disorders run in families. While it has long been recognized that the etiology of substance use behaviors and disorders involves a combination of genetic and environmental factors, two key questions remain largely unanswered: (1) the intergenerational transmission through which these genetic predispositions are passed from parents to children, and (2) the molecular mechanisms linking genetic variants to substance use behaviors and disorders. This article aims to provide a comprehensive conceptual framework and methodological approach for investigating the intergenerational transmission of substance use behaviors and disorders, by integrating genetic nurture analysis, gene expression imputation, and weighted gene co-expression network analysis. We also additionally describe two longitudinal cohorts - the Brisbane Longitudinal Twin Study in Australia and the Lifelines Cohort Study in the Netherlands. By applying the methodological framework to these two unique datasets, our future research will explore the complex interplay between genetic factors, gene expression, and environmental influences on substance use behaviors and disorders across different life stages and populations.

Functional Connectome Hierarchy in Schizotypy and Its Associations With Expression of Schizophrenia-Related Genes

BACKGROUND AND HYPOTHESIS

Schizotypy has been conceptualized as a continuum of symptoms with marked genetic, neurobiological, and sensory-cognitive overlaps to schizophrenia. Hierarchical organization represents a general organizing principle for both the cortical connectome supporting sensation-to-cognition continuum and gene expression variability across the cortex. However, a mapping of connectome hierarchy to schizotypy remains to be established. Importantly, the underlying changes of the cortical connectome hierarchy that mechanistically link gene expressions to schizotypy are unclear.

STUDY DESIGN

The present study applied novel connectome gradient on resting-state fMRI data from 1013 healthy young adults to investigate schizotypy-associated sensorimotor-to-transmodal connectome hierarchy and assessed its similarity with the connectome hierarchy of schizophrenia. Furthermore, normative and differential postmortem gene expression data were utilized to examine transcriptional profiles linked to schizotypy-associated connectome hierarchy.

STUDY RESULTS

We found that schizotypy was associated with a compressed functional connectome hierarchy. Moreover, the pattern of schizotypy-related hierarchy exhibited a positive correlation with the connectome hierarchy observed in schizophrenia. This pattern was closely colocated with the expression of schizophrenia-related genes, with the correlated genes being enriched in transsynaptic, receptor signaling and calcium ion binding.

CONCLUSIONS

The compressed connectome hierarchy suggests diminished functional system differentiation, providing a novel and holistic system-level basis for various sensory-cognition deficits in schizotypy. Importantly, its linkage with schizophrenia-altered hierarchy and schizophrenia-related gene expression yields new insights into the neurobiological continuum of psychosis. It also provides mechanistic insight into how gene variation may drive alterations in functional hierarchy, mediating biological vulnerability of schizotypy to schizophrenia.

Disorder-specific neurodynamic features in schizophrenia inferred by neurodynamic embedded contrastive variational autoencoder model

Neurodynamic models that simulate how micro-level alterations propagate upward to impact macroscopic neural circuits and overall brain function may offer valuable insights into the pathological mechanisms of schizophrenia (SCZ). In this study, we integrated a neurodynamic model with the classical Contrastive Variational Autoencoder (CVAE) to extract and evaluate macro-scale SCZ-specific features, including subject-level, region-level parameters, and time-varying states. Firstly, we demonstrated the robust fitting of the model within our multi-site dataset. Subsequently, by employing representational similarity analysis and a deep learning classifier, we confirmed the specificity and disorder-related information capturing ability of SCZ-specific features. Moreover, analysis of the attractor characteristics of the neurodynamic system revealed significant differences in attractor space patterns between SCZ-specific states and shared states. Finally, we utilized Partial Least Squares (PLS) regression to examine the multivariate mapping relationship between SCZ-specific features and symptoms, identifying two sets of correlated modes implicating unique molecular mechanisms: one mode corresponding to negative and general symptoms, and another mode corresponding to positive symptoms. Our results provide valuable insights into disorder-specific neurodynamic features and states associated with SCZ, laying the foundation for understanding the intricate pathophysiology of this disorder.

Molecular Rhythmicity in Glia: Importance for Brain Health and Relevance to Psychiatric Disease

Circadian rhythms are approximate 24-hour rhythms present in nearly all aspects of human physiology, including proper brain function. These rhythms are produced at the cellular level through a transcriptional-translational feedback loop known as the molecular clock. Diurnal variation in gene expression has been demonstrated in brain tissue from multiple species, including humans, in both cortical and subcortical regions. Interestingly, these rhythms in gene expression have been shown to be disrupted across psychiatric disorders and may be implicated in their underlying pathophysiology. However, little is known regarding molecular rhythms in specific cell types in the brain and how they might be involved in psychiatric disease. Although glial cells (e.g., astrocytes, microglia, and oligodendrocytes) have been historically understudied compared to neurons, evidence of the molecular clock is found within each of these cell subtypes. Here, we review the current literature, which suggests that molecular rhythmicity is essential to functional physiologic outputs from each glial subtype. Furthermore, disrupted molecular rhythms within these cells and the resultant functional deficits may be relevant to specific phenotypes across psychiatric illnesses. Given that circadian rhythm disruptions have been so integrally tied to psychiatric disease, the molecular mechanisms governing these associations could represent exciting new avenues for future research and potential novel pharmacologic targets for treatment.

Genetic Analysis of Psychosis Biotypes: Shared Ancestry-Adjusted Polygenic Risk and Unique Genomic Associations

The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) created psychosis Biotypes based on neurobiological measurements in a multi-ancestry sample. These Biotypes cut across DSM diagnoses of schizophrenia, schizoaffective disorder and bipolar disorder with psychosis. Two recently developed post hoc ancestry adjustment methods of Polygenic Risk Scores (PRSs) generate Ancestry-Adjusted PRSs (AAPRSs), which allow for PRS analysis of multi-ancestry samples. Applied to schizophrenia PRS, we found the Khera AAPRS method to show superior portability and comparable prediction accuracy as compared with the Ge method. The three Biotypes of psychosis disorders had similar AAPRSs across ancestries. In genomic analysis of Biotypes, 12 genes and isoforms showed significant genomic associations with specific Biotypes in Transcriptome-Wide Association Study (TWAS) of genetically regulated expression (GReX) in adult brain and fetal brain. TWAS inflation was addressed by inclusion of genotype principal components in the association analyses. Seven of these 12 genes/isoforms satisfied Mendelian Randomization (MR) criteria for putative causality, including four genes TMEM140, ARTN, C1orf115, CYREN, and three transcripts ENSG00000272941, ENSG00000257176, ENSG00000287733. These genes are enriched in the biological pathways of Rearranged during Transfection (RET) signaling, Neural Cell Adhesion Molecule 1 (NCAM1) interactions, and NCAM signaling for neurite out-growth. The specific associations with Biotypes suggest that pharmacological clinical trials and biological investigations might benefit from analyzing Biotypes separately.

Identification and characterization of human KALRN mRNA and Kalirin protein isoforms

Kalirin is a multidomain protein with important roles in neurite outgrowth, and synaptic spine formation and remodeling. Genetic and pathophysiological links with various neuropsychiatric disorders associated with synaptic dysfunction and cognitive impairment have sparked interest in its potential as a pharmacological target. Multiple Kalirin proteoforms are detected in the adult human brain, yet we know little about the diversity of the transcripts that encode them or their tissue profiles. Here, we characterized full-length KALRN transcripts expressed in the adult human frontal lobe and hippocampus using rapid amplification of complementary DNA (cDNA) ends and nanopore long-read sequencing. For comparison with non-neural tissue, we also analyzed KALRN transcripts in the aorta. Multiple novel isoforms were identified and were largely similar between the two brain regions analyzed. Alternative splicing in the brain results in preferential inclusion of exon 37, which encodes 32 amino acids upstream of the second guanine nucleotide exchange factor (GEF) domain. Structural modeling predicts that a subset of these amino acids forms a conserved alpha helix. Although deletion of these amino acids had little effect on GEF activity, it did alter Kalirin-induced neurite outgrowth suggesting that this brain-enriched splicing event may be important for neural function. These data indicate that alternative splicing is potentially important for regulating Kalirin actions in the human brain.

Microglial Dysfunction in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder with onset in childhood. The molecular mechanisms underlying ASD have not yet been elucidated completely. Evidence has emerged to support a link between microglial dysfunction and the etiology of ASD. This review summarizes current research on microglial dysfunction in neuroinflammation and synaptic pruning, which are associated with altered transcriptomes and autophagy in ASD. Dysbiosis of gut microbiota in ASD and its correlation with microglial dysfunction are also addressed.

Lower levels of kainate receptors, but not AMPA or NMDA receptors, in Brodmann's area (BA) 9, but not BA 10, from a subgroup of people with schizophrenia who have a marked deficit in cortical muscarinic M1 receptors

In a previous study on ionotropic glutamate receptors, we have shown that [3H]kainate, but not [3H]AMPA or [3H]NMDA, receptor binding was lower in Brodmann's area (BA) 9 from people with schizophrenia. Subsequently, we defined a subgroup within the syndrome of schizophrenia who are termed the Muscarinic Receptor Deficit subgroup of Schizophrenia (MRDS) as they have markedly lower levels of [3H]pirenzepine binding to the muscarinic M1 receptor. The previous glutamate receptor study did not contain enough people with MRDS and other forms of schizophrenia (non-MRDS) to study any subgroup-specific differences. Hence, in this study we first measured [3H]pirenzepine binding to the muscarinic M1 receptor to confirm the MRDS subgroup, then measured [3H]kainate, [3H]AMPA and [3H]NMDA receptor binding using autoradiography in BA 9 from people with MRDS, non-MRDS and controls. We also measured binding in BA 10 as our gene expression study indicated that BA 10 is disproportionally affected by the molecular pathology of schizophrenia. As expected, due to case-selection criteria, [3H]pirenzepine binding to the M1 receptor was lower in BA 9 and BA 10 from people with MRDS, although more profound in BA 10. [3H]kainate receptor binding was lower only in BA 9 from people with MRDS, while [3H]AMPA and [3H]NMDA receptor binding was not altered in either region. Muscarinic M1 receptors and kainate receptors are both located on glutamatergic pyramidal neurons so a perturbation in both receptors could indicate altered excitatory neurotransmission in BA 9 from people with MRDS.

Resource: A curated database of brain-related functional gene sets (Brain.GMT)

Transcriptional profiling has become a common tool for investigating the nervous system. During analysis, differential expression results are often compared to functional ontology databases, which contain curated gene sets representing well-studied pathways. This dependence can cause neuroscience studies to be interpreted in terms of functional pathways documented in better studied tissues (e.g., liver) and topics (e.g., cancer), and systematically emphasizes well-studied genes, leaving other findings in the obscurity of the brain "ignorome". To address this issue, we compiled a curated database of 918 gene sets related to nervous system function, tissue, and cell types ("Brain.GMT") that can be used within common analysis pipelines (GSEA, limma, edgeR) to interpret results from three species (rat, mouse, human). Brain.GMT includes brain-related gene sets curated from the Molecular Signatures Database (MSigDB) and extracted from public databases (GeneWeaver, Gemma, DropViz, BrainInABlender, HippoSeq) and published studies containing differential expression results. Although Brain.GMT is still undergoing development and currently only represents a fraction of available brain gene sets, "brain ignorome" genes are already better represented than in traditional Gene Ontology databases. Moreover, Brain.GMT substantially improves the quantity and quality of gene sets identified as enriched with differential expression in neuroscience studies, enhancing interpretation. •We compiled a curated database of 918 gene sets related to nervous system function, tissue, and cell types ("Brain.GMT").•Brain.GMT can be used within common analysis pipelines (GSEA, limma, edgeR) to interpret neuroscience transcriptional profiling results from three species (rat, mouse, human).•Although Brain.GMT is still undergoing development, it substantially improved the interpretation of differential expression results within our initial use cases.

Developmental perspectives on the origins of psychotic disorders: The need for a transdiagnostic approach

Research on serious mental disorders, particularly psychosis, has revealed highly variable symptom profiles and developmental trajectories prior to illness-onset. As Dante Cicchetti pointed out decades before the term "transdiagnostic" was widely used, the pathways to psychopathology emerge in a system involving equifinality and multifinality. Like most other psychological disorders, psychosis is associated with multiple domains of risk factors, both genetic and environmental, and there are many transdiagnostic developmental pathways that can lead to psychotic syndromes. In this article, we discuss our current understanding of heterogeneity in the etiology of psychosis and its implications for approaches to conceptualizing etiology and research. We highlight the need for examining risk factors at multiple levels and to increase the emphasis on transdiagnostic developmental trajectories as a key variable associated with etiologic subtypes. This will be increasingly feasible now that large, longitudinal datasets are becoming available and researchers have access to more sophisticated analytic tools, such as machine learning, which can identify more homogenous subtypes with the ultimate goal of enhancing options for treatment and preventive intervention.

Convergent molecular signatures across eating disorders and obsessive-compulsive disorder in the human brain

Eating disorders (ED) and obsessive-compulsive disorder (OCD) exhibit significant clinical and genetic overlap, yet their shared molecular mechanisms remain unclear. We conducted a transcriptomic investigation of the dorsolateral prefrontal cortex (DLPFC) and caudate from 86 controls, 57 ED, and 27 OCD cases. ED was associated with robust differentially expressed genes (DEGs): 102 DEGs the DLPFC and 222 in the caudate (FDR < 1%) and replicated in an independent cohort. For OCD, no DEGs reached significance; however, meta-analysis with extant data identified 57 DEGs in the caudate. High concordance in transcriptomic changes was observed between ED and OCD in both regions (DLPFC r=0.67, caudate r=0.75). A combined ED+OCD analysis uncovered 233 DEGs in the DLPFC and 816 in the caudate, implicating disrupted GABAergic neuron function, neuroendocrine pathways, metabolism, and synaptic processes. Genetically regulated expression analysis identified nine genes with strong evidence for increasing ED risk, further validating these pathways. These findings reveal a shared molecular basis for ED and OCD, offering new insights into their pathobiology and potential therapeutic targets.

KCTD10 p.C124W variant contributes to schizophrenia by attenuating LLPS-mediated synapse formation

KCTD10, a member of the potassium channel tetramerization domain (KCTD) family, is implicated in neuropsychiatric disorders and functions as a substrate recognition component within the RING-type ubiquitin ligase complex. A rare de novo variant of KCTD10, p.C124W, was identified in schizophrenia cases, yet its underlying pathogenesis remains unexplored. Here, we demonstrate that heterozygous KCTD10 C124W mice display pronounced synaptic abnormalities and exhibit schizophrenia-like behaviors. Mechanistically, we reveal that KCTD10 undergoes liquid-liquid phase separation (LLPS), a process orchestrated by its intrinsically disordered region (IDR). p.C124W mutation disrupts this LLPS capability, leading to diminished degradation of RHOB and subsequent excessive accumulation in the postsynaptic density fractions. Notably, neither IDR deletion nor p.C124W mutation in KCTD10 mitigates the synaptic abnormalities caused by Kctd10 deficiency. Thus, our findings implicate that LLPS may be associated with the pathogenesis of KCTD10-associated brain disorders and highlight the potential of targeting RHOB as a therapeutic strategy for diseases linked to mutations in KCTD10 or RHOB.

Functional gradient dysfunction in drug-naïve first-episode schizophrenia and its correlation with specific transcriptional patterns and treatment predictions

BACKGROUND

First-episode schizophrenia (FES) is a progressive psychiatric disorder influenced by genetics, environmental factors, and brain function. The functional gradient deficits of drug-naïve FES and its relationship to gene expression profiles and treatment outcomes are unknown.

METHODS

In this study, we engaged a cohort of 116 FES and 100 healthy controls (HC), aged 7 to 30 years, including 15 FES over an 8-week antipsychotic medication regimen. Our examination focused on primary-to-transmodal alterations in voxel-based connection gradients in FES. Then, we employed network topology, Neurosynth, postmortem gene expression, and support vector regression to evaluate integration and segregation functions, meta-analytic cognitive terms, transcriptional patterns, and treatment predictions.

RESULTS

FES displayed diminished global connectome gradients (Cohen's d = 0.32-0.57) correlated with compensatory integration and segregation functions (Cohen's d = 0.31-0.36). Predominant alterations were observed in the default (67.6%) and sensorimotor (21.9%) network, related to high-order cognitive functions. Furthermore, we identified notable overlaps between partial least squares (PLS1) weighted genes and dysregulated genes in other psychiatric conditions. Genes linked with gradient alterations were enriched in synaptic signaling, neurodevelopment process, specific astrocytes, cortical layers (layer II and IV), and developmental phases from late/mid fetal to young adulthood. Additionally, the onset age influenced the severity of FES, with discernible differences in connection gradients between minor- and adult-FES. Moreover, the connectivity gradients of FES at baseline significantly predicted treatment outcomes.

CONCLUSIONS

These results offer significant theoretical foundations for elucidating the intricate interplay between macroscopic functional connection gradient changes and microscopic transcriptional patterns during the onset and progression of FES.