The Association Between Functional Variants in Long Non-coding RNAs and the Risk of Autism Spectrum Disorder Was Not Mediated by Gut Microbiota

The effect of functional variants in long non-coding RNA (lncRNA) gene regions on autism spectrum disorder (ASD) remains unclear. The present study aimed to investigate the association of functional variants located in lncRNA genes with the risk of ASD and explore whether gut microbiota would mediate the relationship. A total of 87 cases and 71 healthy controls were enrolled in the study. MassARRAY platform and 16S rRNA sequencing were respectively applied to assess the genotype of candidate SNPs and gut microbiota of children. The logistic regression models showed that the association between rs2295412 and the risk of ASD was statistically significant after Bonferroni adjustments. The risk of ASD decreased by 19% for each additional C allele carried by children in multiplicative models (OR = 0.81, 95% CI, 0.69-0.94, P = 0.007). Although we identified significant correlations between rs8113922 polymorphisms, Bifidobacteriales, and ASD, the mediating effect of gut microbiota on the relationship of the polymorphisms with the risk of ASD was not significant. The findings demonstrated that functional variants in lncRNA genes play an important role in ASD and gut microbiota could not mediate the association. Future studies are warranted to verify the results and search for more possible mechanisms of variants located in lncRNA genes implicated in ASD.

Study Protocol: Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project

BACKGROUND

Objective and quantifiable markers are crucial for developing novel therapeutics for mental disorders by 1) stratifying clinically similar patients with different underlying neurobiological deficits and 2) objectively tracking disease trajectory and treatment response. Schizophrenia is often confounded with other psychiatric disorders, especially bipolar disorder, if based on cross-sectional symptoms. Awake and sleep EEG have shown promise in identifying neurophysiological differences as biomarkers for schizophrenia. However, most previous studies, while useful, were conducted in European and American populations, had small sample sizes, and utilized varying analytic methods, limiting comprehensive analyses or generalizability to diverse human populations. Furthermore, the extent to which wake and sleep neurophysiology metrics correlate with each other and with symptom severity or cognitive impairment remains unresolved. Moreover, how these neurophysiological markers compare across psychiatric conditions is not well characterized. The utility of biomarkers in clinical trials and practice would be significantly advanced by well-powered transdiagnostic studies. The Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project aims to address these questions through a large, multi-center cohort study involving East Asian populations. To promote transparency and reproducibility, we describe the protocol for the GRINS project.

METHODS

The research procedure consists of an initial screening interview followed by three subsequent sessions: an introductory interview, an evaluation visit, and an overnight neurophysiological recording session. Data from multiple domains, including demographic and clinical characteristics, behavioral performance (cognitive tasks, motor sequence tasks), and neurophysiological metrics (both awake and sleep electroencephalography), are collected by research groups specialized in each domain.

CONCLUSION

Pilot results from the GRINS project demonstrate the feasibility of this study protocol and highlight the importance of such research, as well as its potential to study a broader range of patients with psychiatric conditions. Through GRINS, we are generating a valuable dataset across multiple domains to identify neurophysiological markers of schizophrenia individually and in combination. By applying this protocol to related mental disorders often confounded with each other, we can gather information that offers insight into the neurophysiological characteristics and underlying mechanisms of these severe conditions, informing objective diagnosis, stratification for clinical research, and ultimately, the development of better-targeted treatment matching in the clinic.

Transcriptomic Evaluation of a Stress Vulnerability Network Using Single-Cell RNA Sequencing in Mouse Prefrontal Cortex

BACKGROUND

Increased vulnerability to stress is a major risk factor for several mood disorders, including major depressive disorder. Although cellular and molecular mechanisms associated with depressive behaviors following stress have been identified, little is known about the mechanisms that confer the vulnerability that predisposes individuals to future damage from chronic stress.

METHODS

We used multisite in vivo neurophysiology in freely behaving male and female C57BL/6 mice (n = 12) to measure electrical brain network activity previously identified as indicating a latent stress vulnerability brain state. We combined this neurophysiological approach with single-cell RNA sequencing of the prefrontal cortex to identify distinct transcriptomic differences between groups of mice with inherent high and low stress vulnerability.

RESULTS

We identified hundreds of differentially expressed genes (padjusted < .05) across 5 major cell types in animals with high and low stress vulnerability brain network activity. This unique analysis revealed that GABAergic (gamma-aminobutyric acidergic) neuron gene expression contributed most to the network activity of the stress vulnerability brain state. Upregulation of mitochondrial and metabolic pathways also distinguished high and low vulnerability brain states, especially in inhibitory neurons. Importantly, genes that were differentially regulated with vulnerability network activity significantly overlapped (above chance) with those identified by genome-wide association studies as having single nucleotide polymorphisms significantly associated with depression as well as genes more highly expressed in postmortem prefrontal cortex of patients with major depressive disorder.

CONCLUSIONS

This is the first study to identify cell types and genes involved in a latent stress vulnerability state in the brain.

Three-dimensional chromatin mapping of sensory neurons reveals that cohesin-dependent genomic domains are required for axonal regeneration

The in vivo three-dimensional genomic architecture of adult mature neurons at homeostasis and after medically relevant perturbations such as axonal injury remains elusive. Here we address this knowledge gap by mapping the three-dimensional chromatin architecture and gene expression programme at homeostasis and after sciatic nerve injury in wild-type and cohesin-deficient mouse sensory dorsal root ganglia neurons via combinatorial Hi-C and RNA-seq. We find that cohesin is required for the full induction of the regenerative transcriptional program, by organising 3D genomic domains required for the activation of regenerative genes. Importantly, loss of cohesin results in disruption of chromatin architecture at regenerative genes and severely impaired nerve regeneration. Together, these data provide an original three-dimensional chromatin map of adult sensory neurons in vivo and demonstrate a role for cohesin-dependent chromatin interactions in neuronal regeneration.

Genome-wide association studies (GWAS) and post-GWAS analyses of impulsivity: A systematic review

Impulsivity is related to a host of mental and behavioral problems. It is a complex construct with many different manifestations, most of which are heritable. The genetic compositions of these impulsivity manifestations, however, remain unclear. A number of genome-wide association studies (GWAS) and post-GWAS analyses have tried to address this issue. We conducted a systematic review of all GWAS and post-GWAS analyses of impulsivity published up to December 2023. Available data suggest that single nucleotide polymorphisms (SNPs) in more than a dozen of genes (e.g., CADM2, CTNNA2, GPM6B) are associated with different measures of impulsivity at genome-wide significant levels. Post-GWAS analyses further show that different measures of impulsivity are subject to different degrees of genetic influence, share few genetic variants, and have divergent genetic overlap with basic personality traits such as extroversion and neuroticism, cognitive ability, psychiatric disorders, substance use, and obesity. These findings shed light on controversies in the conceptualization and measurement of impulsivity, while providing new insights on the underlying mechanisms that yoke impulsivity to psychopathology.

Therapeutic potential of Bergenin in the management of neurological-based diseases and disorders

Originally sourced from plants, Bergenin has been used as a medicinal compound in traditional medicine for centuries, and anecdotal reports suggest a wide range of therapeutic uses. Naturally-occurring and lab-synthesized Bergenin, as well as some of its related compounds, have been shown in in vivo and in vitro studies to alter activity of several enzymes and proteins critical in cellular functioning, including reelin, GSK-3β, Lingo-1, Ten-4, GP-43, Aβ 1-42, P-tau, SOD1,2, GPx, Glx1, NQO1, HO1, PPAR-ɣ, BDNF, VEGF, and STAT6. Additionally, Bergenin alters levels of several cytokines, such as IL-6, IL-1β, TNF-α, and TGF-β. Behavioral and cellular effects of Bergenin have been shown to involve PI3K/Akt, NF-κB, PKC, Nrf2, and Sirt1/FOXO3a pathways. These pathways, enzymes, and proteins have been shown to be important in normal neurological functioning, and/or dysfunctions in these pathways and proteins have been shown to be important in several neuro-based disorders or diseases, which suggests that Bergenin could be therapeutic in management of neuropsychiatric conditions or neurological disorders. In preclinical studies, Bergenin has been shown to be useful for the management of Alzheimer's disease, Parkinson's disease, anxiety, depression, addiction, epilepsy, insomnia, stroke, and potentially, state control. Our review aims to summarize current evidence supporting the conclusion that Bergenin could play a role in treating various neuro-based disorders and that future studies should be conducted to evaluate the mechanisms by which Bergenin could exert its therapeutic effects.

Genetic and phenotypic heterogeneity in early neurodevelopmental traits in the Norwegian Mother, Father and Child Cohort Study

BACKGROUND

Autism and different neurodevelopmental conditions frequently co-occur, as do their symptoms at sub-diagnostic threshold levels. Overlapping traits and shared genetic liability are potential explanations.

METHODS

In the population-based Norwegian Mother, Father, and Child Cohort study (MoBa), we leverage item-level data to explore the phenotypic factor structure and genetic architecture underlying neurodevelopmental traits at age 3 years (N = 41,708-58,630) using maternal reports on 76 items assessing children's motor and language development, social functioning, communication, attention, activity regulation, and flexibility of behaviors and interests.

RESULTS

We identified 11 latent factors at the phenotypic level. These factors showed associations with diagnoses of autism and other neurodevelopmental conditions. Most shared genetic liabilities with autism, ADHD, and/or schizophrenia. Item-level GWAS revealed trait-specific genetic correlations with autism (items rg range = - 0.27-0.78), ADHD (items rg range = - 0.40-1), and schizophrenia (items rg range = - 0.24-0.34). We find little evidence of common genetic liability across all neurodevelopmental traits but more so for several genetic factors across more specific areas of neurodevelopment, particularly social and communication traits. Some of these factors, such as one capturing prosocial behavior, overlap with factors found in the phenotypic analyses. Other areas, such as motor development, seemed to have more heterogenous etiology, with specific traits showing a less consistent pattern of genetic correlations with each other.

CONCLUSIONS

These exploratory findings emphasize the etiological complexity of neurodevelopmental traits at this early age. In particular, diverse associations with neurodevelopmental conditions and genetic heterogeneity could inform follow-up work to identify shared and differentiating factors in the early manifestations of neurodevelopmental traits and their relation to autism and other neurodevelopmental conditions. This in turn could have implications for clinical screening tools and programs.

Bidirectional causal relational between frailty and mental illness: a two-sample Mendelian randomization study

Background

Frailty has been associated with mental illness (MI) observational studies, but the causal relationship between these factors remains uncertain. We aimed to assess the bidirectional causality between frailty and MI by two-sample Mendelian randomization (MR) analyses.

Methods

To investigate the causal relationship among them, summary statistics of frailty index (FI) and six types of MI: anxiety, depression, affective disorder, mania, schizophrenia, and obsessive-compulsive disorder (OCD) were included in this MR study. This MR analysis was performed using inverse variance weighting (IVW), MR-Egger regression, and weighted median. The stability of the results was evaluated using Cochran's Q test, MR-Egger intercept test, Funnel Plots, and leave-one-out analysis.

Results

Genetic predisposition to FI was significantly associated with increased anxiety (odds ratio [OR] = 1.62, 95% confidence interval [CI] 1.13-2.33, P = 8.18E-03), depression (OR = 1.88, 95% CI 1.30-2.71, P = 8.21E-04), affective disorder (OR = 1.70, 95% CI 1.28-2.27, P = 2.57E-04). However, our study findings do not demonstrate a causal relationship between FI and mania (OR = 1.02, 95% CI 0.99-1.06, P = 2.20E-01), schizophrenia (OR = 1.02, 95% CI 0.07-0.86, P = 9.28E-01). In particular, although the IVW results suggest a potential causal relationship between FI and OCD (OR = 0.64, 95% CI 0.07-0.86, P = 2.85E-02), the directions obtained from the three methods we employed ultimately show inconsistency. Therefore, the result must be interpreted with caution. The results of the reverse MR analysis indicated a statistically significant and causal relationship between anxiety (OR = 1.06, 95% CI 1.01-1.11, P = 2.00E-02), depression (OR = 1.14, 95% CI 1.04-1.26, P = 7.99E-03), affective disorder (OR = 1.15, 95% CI 1.09-1.21, P = 3.39E-07), and schizophrenia (OR = 1.02, 95% CI 1.01-1.04, P = 1.70E-03) with FI. However, our findings do not provide support for a link between mania (OR = 1.46, 95% CI 0.79-2.72, P = 2.27E-01), OCD (OR = 1.01, 95% CI 1.00-1.02, P = 2.11E-01) and an increased risk of FI.

Conclusion

The MR results suggest a potential bidirectional causal relationship between FI and anxiety, depression, and affective disorder. Schizophrenia was found to be associated with a higher risk of FI. The evidence was insufficient to support a causal relationship between Fl and other Ml. These findings offer new insights into the development of effective management strategies for frailty and MI.

Genetically Informed Study Highlights Income-Independent Effect of Schizophrenia Liability on Mental and Physical Health

BACKGROUND AND HYPOTHESIS

Individuals with schizophrenia (SCZ) suffer from comorbidities that substantially reduce their life expectancy. Socioeconomic inequalities could contribute to many of the negative health outcomes associated with SCZ.

STUDY DESIGN

We investigated genome-wide datasets related to SCZ (52 017 cases and 75 889 controls) from the Psychiatric Genomics Consortium, household income (HI; N = 361 687) from UK Biobank, and 2202 medical endpoints assessed in up to 342 499 FinnGen participants. A phenome-wide genetic correlation analysis of SCZ and HI was performed, also assessing whether SCZ genetic correlations were influenced by the HI effect on SCZ. Additionally, SCZ and HI direct effects on medical endpoints were estimated using multivariable Mendelian randomization (MR).

STUDY RESULTS

SCZ and HI showed overlapping genetic correlations with 70 traits (P < 2.89 × 10-5), including mental health, substance use, gastrointestinal illnesses, reproductive outcomes, liver diseases, respiratory problems, and musculoskeletal phenotypes. SCZ genetic correlations with these traits were not affected by the HI effect on SCZ. Considering Bonferroni multiple testing correction (P < 7.14 × 10-4), MR analysis indicated that SCZ and HI may affect medical abortion (SCZ OR = 1.07; HI OR = 0.78), panic disorder (SCZ OR = 1.20; HI OR = 0.60), personality disorders (SCZ OR = 1.31; HI OR = 0.67), substance use (SCZ OR = 1.2; HI OR = 0.68), and adjustment disorders (SCZ OR = 1.18; HI OR = 0.78). Multivariable MR analysis confirmed that SCZ effects on these outcomes were independent of HI.

CONCLUSIONS

The effect of SCZ genetic liability on mental and physical health may not be strongly affected by socioeconomic differences. This suggests that SCZ-specific strategies are needed to reduce negative health outcomes affecting patients and high-risk individuals.

Shared Genetic Architecture Between Schizophrenia and Anorexia Nervosa: A Cross-trait Genome-Wide Analysis

BACKGROUND AND HYPOTHESIS

Schizophrenia (SCZ) and anorexia nervosa (AN) are 2 severe and highly heterogeneous disorders showing substantial familial co-aggregation. Genetic factors play a significant role in both disorders, but the shared genetic etiology between them is yet to be investigated.

STUDY DESIGN

Using summary statistics from recent large genome-wide association studies on SCZ (Ncases = 53 386) and AN (Ncases = 16 992), a 2-sample Mendelian randomization analysis was conducted to explore the causal relationship between SCZ and AN. MiXeR was employed to quantify their polygenic overlap. A conditional/conjunctional false discovery rate (condFDR/conjFDR) framework was adopted to identify loci jointly associated with both disorders. Functional annotation and enrichment analyses were performed on the shared loci.

STUDY RESULTS

We observed a cross-trait genetic enrichment, a suggestive bidirectional causal relationship, and a considerable polygenic overlap (Dice coefficient = 62.2%) between SCZ and AN. The proportion of variants with concordant effect directions among all shared variants was 69.9%. Leveraging overlapping genetic associations, we identified 6 novel loci for AN and 33 novel loci for SCZ at condFDR <0.01. At conjFDR <0.05, we identified 10 loci jointly associated with both disorders, implicating multiple genes highly expressed in the cerebellum and pituitary and involved in synapse organization. Particularly, high expression of the shared genes was observed in the hippocampus in adolescence and orbitofrontal cortex during infancy.

CONCLUSIONS

This study provides novel insights into the relationship between SCZ and AN by revealing a shared genetic component and offers a window into their complex etiology.

Influence of antipsychotic drugs on microRNA expression in schizophrenia patients - A systematic review

Schizophrenia (SCZ) is a severe psychiatric disorder with unclear pathophysiology. Moreover, there is no specific biological marker to help clinicians to define a diagnosis, and medication is decided according to the psychiatrist's experience. In this scenario, microRNAs (miRNAs), which are small noncoding RNA molecules that regulate several genes, emerge as potential peripheral biomarkers to help not only the evaluation of the disease state but also the treatment response. Here, we systematically reviewed indexed literature and evaluated follow-up studies investigating the changes in miRNA expression due to antipsychotic treatment. We also assessed target genes and performed pathway enrichment analysis of miRNAs listed in this systematic review. A total of 11 studies were selected according to research criteria, and we observed that 28 miRNAs play a relevant role in schizophrenia pathogenesis or response to antipsychotic treatment, seven of those of extreme interest as possible biomarkers either for condition or treatment. Predicted targets of the miRNAs reviewed here were previously associated with schizophrenia in genome-wide studies, and pathway analysis showed enrichment for genes related to neural processes. With this review, we expect to highlight the importance of miRNAs in schizophrenia pathogenesis and its treatment and point out interesting miRNAs to future studies.

High-frequency hearing vulnerability associated with the different supporting potential of Hensen's cells: SMART-Seq2 RNA sequencing

Hearing loss is the third most prevalent physical condition affecting communication, well-being, and healthcare costs. Sensorineural hearing loss often occurs first in the high-frequency region (basal turn), then towards the low-frequency region (apical turn). However, the mechanism is still unclear. Supporting cells play a critical role in the maintenance of normal cochlear function. The function and supporting capacity of these cells may be different from different frequency regions. Hensen's cells are one of the unique supporting cell types characterized by lipid droplets (LDs) in the cytoplasm. Here, we investigated the morphological and gene expression differences of Hensen's cells along the cochlear axis. We observed a gradient change in the morphological characteristics of Hensen's cells along the cochlear tonotopic axis, with larger and more abundant LDs observed in apical Hensen's cells. Smart-seq2 RNA-seq revealed differentially expressed genes (DEGs) between apical and basal Hensen's cells that clustered in several pathways, including unsaturated fatty acid biosynthesis, cholesterol metabolism, and fatty acid catabolism, which are associated with different energy storage capacities and metabolic potential. These findings suggest potential differences in lipid metabolism and oxidative energy supply between apical and basal Hensen's cells, which is consistent with the morphological differences of Hensen's cells. We also found differential expression patterns of candidate genes associated with hereditary hearing loss (HHL), noise-induced hearing loss (NIHL), and age-related hearing loss (ARHL). These findings indicate functional heterogeneity of SCs along the cochlear axis, contribute to our understanding of cochlear physiology and provide molecular basis evidence for future studies of hearing loss.

Genome-Wide Gene-Environment Interaction Analysis Identifies Novel Candidate Variants for Growth Traits in Beef Cattle

Complex traits are widely considered to be the result of a compound regulation of genes, environmental factors, and genotype-by-environment interaction (G × E). The inclusion of G × E in genome-wide association analyses is essential to understand animal environmental adaptations and improve the efficiency of breeding decisions. Here, we systematically investigated the G × E of growth traits (including weaning weight, yearling weight, 18-month body weight, and 24-month body weight) with environmental factors (farm and temperature) using genome-wide genotype-by-environment interaction association studies (GWEIS) with a dataset of 1350 cattle. We validated the robust estimator's effectiveness in GWEIS and detected 29 independent interacting SNPs with a significance threshold of 1.67 × 10-6, indicating that these SNPs, which do not show main effects in traditional genome-wide association studies (GWAS), may have non-additive effects across genotypes but are obliterated by environmental means. The gene-based analysis using MAGMA identified three genes that overlapped with the GEWIS results exhibiting G × E, namely SMAD2, PALMD, and MECOM. Further, the results of functional exploration in gene-set analysis revealed the bio-mechanisms of how cattle growth responds to environmental changes, such as mitotic or cytokinesis, fatty acid β-oxidation, neurotransmitter activity, gap junction, and keratan sulfate degradation. This study not only reveals novel genetic loci and underlying mechanisms influencing growth traits but also transforms our understanding of environmental adaptation in beef cattle, thereby paving the way for more targeted and efficient breeding strategies.

Investigating the increased risk of schizophrenia and bipolar disorders in relatives of ADHD probands using colocalization analysis of common genetic variants

BACKGROUND

Relatives of ADHD probands are known to be at increased risk of schizophrenia and bipolar disorder, suggesting shared genetic factors. In this study, we aim to identify shared common risk variants (i.e., Single-Nucleotide Polymorphisms, SNPs) between ADHD and schizophrenia, and between ADHD and bipolar disorder.

METHODS

With the summary data from three GWAS, one on ADHD (20,183 cases with ADHD and 35,191 controls), another on schizophrenia (76,755 cases with schizophrenia and 243,649 controls) and another on bipolar disorder (41,917 cases with bipolar disorder and 371,549 controls), we used colocalization analysis to identify SNPs shared by ADHD and schizophrenia, and SNPs shared by ADHD and bipolar disorder. Functional genomic analyses were then conducted on these two sets of shared common genetic variants.

RESULTS

We found that three of the 12 SNPs associated with ADHD colocalized with schizophrenia SNPs and one of the 12 SNPs associated with ADHD colocalized with bipolar disorder. Only 0.4% of the SNPs associated with schizophrenia (2 out of 431) and 2.3% of the SNPs associated with bipolar disorder (2 out of 86), colocalized with ADHD SNPs. Some genes mapped to these shared genetic variants (SCN2A and UNC5D) are involved in the development of the nervous system.

CONCLUSIONS

Using colocalization analysis, the present study uncovers shared genetic variants associated with ADHD and schizophrenia as well as ADHD and bipolar disorder, and may at least partially explain the increased risk of schizophrenia and bipolar disorder in relatives of ADHD probands.

Novel early-onset Alzheimer-associated genes influence risk through dysregulation of glutamate, immune activation, and intracell signaling pathways

Alzheimer Disease (AD) is a highly polygenic disease that presents with relatively earlier onset (≤70yo; EOAD) in about 5% of cases. Around 90% of these EOAD cases remain unexplained by pathogenic mutations. Using data from EOAD cases and controls, we performed a genome-wide association study (GWAS) and trans-ancestry meta-analysis on non-Hispanic Whites (NHW, NCase=6,282, NControl=13,386), African Americans (AA NCase=782, NControl=3,663) and East Asians (NCase=375, NControl=838 CO). We identified eight novel significant loci: six in the ancestry-specific analyses and two in the trans-ancestry analysis. By integrating gene-based analysis, eQTL, pQTL and functional annotations, we nominate four novel genes that are involved in microglia activation, glutamate production, and signaling pathways. These results indicate that EOAD, although sharing many genes with LOAD, harbors unique genes and pathways that could be used to create better prediction models or target identification for this type of AD.

Normative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients

Advanced methods such as REACT have allowed the integration of fMRI with the brain's receptor landscape, providing novel insights transcending the multiscale organisation of the brain. Similarly, normative modelling has allowed translational neuroscience to move beyond group-average differences and characterise deviations from health at an individual level. Here, we bring these methods together for the first time. We used REACT to create functional networks enriched with the main modulatory, inhibitory, and excitatory neurotransmitter systems and generated normative models of these networks to capture functional connectivity deviations in patients with schizophrenia, bipolar disorder (BPD), and ADHD. Substantial overlap was seen in symptomatology and deviations from normality across groups, but these could be mapped into a common space linking constellations of symptoms through to underlying neurobiology transdiagnostically. This work provides impetus for developing novel biomarkers that characterise molecular- and systems-level dysfunction at the individual level, facilitating the transition towards mechanistically targeted treatments.

In vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth

A balanced excitation-inhibition ratio (E/I ratio) is critical for healthy brain function. Normative development of cortex-wide E/I ratio remains unknown. Here, we noninvasively estimate a putative marker of whole-cortex E/I ratio by fitting a large-scale biophysically plausible circuit model to resting-state functional MRI (fMRI) data. We first confirm that our model generates realistic brain dynamics in the Human Connectome Project. Next, we show that the estimated E/I ratio marker is sensitive to the gamma-aminobutyric acid (GABA) agonist benzodiazepine alprazolam during fMRI. Alprazolam-induced E/I changes are spatially consistent with positron emission tomography measurement of benzodiazepine receptor density. We then investigate the relationship between the E/I ratio marker and neurodevelopment. We find that the E/I ratio marker declines heterogeneously across the cerebral cortex during youth, with the greatest reduction occurring in sensorimotor systems relative to association systems. Importantly, among children with the same chronological age, a lower E/I ratio marker (especially in the association cortex) is linked to better cognitive performance. This result is replicated across North American (8.2 to 23.0 y old) and Asian (7.2 to 7.9 y old) cohorts, suggesting that a more mature E/I ratio indexes improved cognition during normative development. Overall, our findings open the door to studying how disrupted E/I trajectories may lead to cognitive dysfunction in psychopathology that emerges during youth.

Assessing rates and predictors of cannabis-associated psychotic symptoms across observational, experimental and medical research

Cannabis, one of the most widely used psychoactive substances worldwide, can give rise to acute cannabis-associated psychotic symptoms (CAPS). While distinct study designs have been used to examine CAPS, an overarching synthesis of the existing findings has not yet been carried forward. To that end, we quantitatively pooled the evidence on rates and predictors of CAPS (k = 162 studies, n = 210,283 cannabis-exposed individuals) as studied in (1) observational research, (2) experimental tetrahydrocannabinol (THC) studies, and (3) medicinal cannabis research. We found that rates of CAPS varied substantially across the study designs, given the high rates reported by observational and experimental research (19% and 21%, respectively) but not medicinal cannabis studies (2%). CAPS was predicted by THC administration (for example, single dose, Cohen's d = 0.7), mental health liabilities (for example, bipolar disorder, d = 0.8), dopamine activity (d = 0.4), younger age (d = -0.2), and female gender (d = -0.09). Neither candidate genes (for example, COMT, AKT1) nor other demographic variables (for example, education) predicted CAPS in meta-analytical models. The results reinforce the need to more closely monitor adverse cannabis-related outcomes in vulnerable individuals as these individuals may benefit most from harm-reduction efforts.

Polygenic Resilience Scores are Associated with Lower Penetrance of Schizophrenia Risk Genes, Protection Against Psychiatric and Medical Disorders, and Enhanced Mental Well-Being and Cognition

In the past decade, significant advances have been made in finding genomic risk loci for schizophrenia (SCZ). This, in turn, has enabled the search for SCZ resilience loci that mitigate the impact of SCZ risk genes. Recently, we discovered the first genomic resilience profile for SCZ, completely independent from the established risk loci for SCZ. We posited that these resilience loci protect against SCZ for those having a heighted genomic risk for SCZ. Nevertheless, our understanding of genetic resilience remains limited. It remains unclear whether resilience loci foster protection against adverse states associated with SCZ risk related to clinical, cognitive, and brain-structural phenotypes. To address this knowledge gap, we analyzed data from 487,409 participants from the UK Biobank, and found that resilience loci for SCZ afforded protection against lifetime psychiatric (schizophrenia, bipolar disorder, anxiety, and depression) and non-psychiatric medical disorders (such as asthma, cardiovascular disease, digestive disorders, metabolic disorders, and external causes of morbidity and mortality). Resilience loci also protected against self-harm behaviors, improved fluid intelligence, and larger whole-brain and brain-regional sizes. Overall, this study sheds light on the range of phenotypes that are significantly associated with resilience loci within the general population, revealing distinct patterns separate from those associated with SCZ risk loci. Our findings indicate that resilience loci may offer protection against serious psychiatric and medical outcomes, co-morbidities, and cognitive impairment. Therefore, it is conceivable that resilience loci facilitate adaptive processes linked to improved health and life expectancy.

Differential Impact of Smoking on Methylome and Transcriptome in Crohn's Disease and Ulcerative Colitis

BACKGROUND

Smoking is an environmental factor that differentially impacts Crohn's disease (CD) and ulcerative colitis (UC). The mechanism of impact of smoking on disease risk and clinical outcomes remains to be established.

METHODS

This study used a prospective cohort of patients with CD or UC. Self-reported smoking status was validated using serum cotinine measurement. We profiled methylation changes in peripheral blood using the Illumina Methylation BeadChip. Transcriptomic profiling was performed on ileal and colonic tissue using an Illumina TruSeq platform. We compared the methylation and transcriptional changes in current, former, and never smokers stratified by disease type.

RESULTS

Our cohort included 200 patients with CD or UC with methylation profiles and 160 with transcriptomic data. The mean serum cotinine level was higher in current compared with former or never smokers. Epigenetic changes common to both CD and UC included hypomethylation at AHRR. Smoking-associated MGAT3 hypomethylation was associated with severe disease course only in UC, while IER3 hypomethylation was associated with worse course only in CD. Smoking downregulated several inflammatory pathways in UC. Current smoking in CD but not in UC was associated with upregulation of several genes mediating Paneth cell function. Genes with opposite direction of effects in CD and UC include HSD3B2 and GSTA1.

CONCLUSIONS

Our findings suggest both common and differential effects of cigarette smoking on CD and UC. Paneth cell dysfunction may mediate adverse impact of smoking on CD. Bile acid and oxidative stress pathways may be relevant for the differential effect of smoking on CD and UC.

Leveraging sex-genetic interactions to understand brain disorders: recent advances and current gaps

It is established that there are sex differences in terms of prevalence, age of onset, clinical manifestations, and response to treatment for a variety of brain disorders, including neurodevelopmental, psychiatric, and neurodegenerative disorders. Cohorts of increasing sample sizes with diverse data types collected, including genetic, transcriptomic and/or phenotypic data, are providing the building blocks to permit analytical designs to test for sex-biased genetic variant-trait associations, and for sex-biased transcriptional regulation. Such molecular assessments can contribute to our understanding of the manifested phenotypic differences between the sexes for brain disorders, offering the future possibility of delivering personalized therapy for females and males. With the intention of raising the profile of this field as a research priority, this review aims to shed light on the importance of investigating sex-genetic interactions for brain disorders, focusing on two areas: (i) variant-trait associations and (ii) transcriptomics (i.e. gene expression, transcript usage and regulation). We specifically discuss recent advances in the field, current gaps and provide considerations for future studies.

Factor analysis of lifetime psychopathology and its brain morphometric and genetic correlates in a transdiagnostic sample

There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.

Analysis of human neuronal cells carrying ASTN2 deletion associated with psychiatric disorders

Recent genetic studies have found common genomic risk variants among psychiatric disorders, strongly suggesting the overlaps in their molecular and cellular mechanism. Our research group identified the variant in ASTN2 as one of the candidate risk factors across these psychiatric disorders by whole-genome copy number variation analysis. However, the alterations in the human neuronal cells resulting from ASTN2 variants identified in patients remain unknown. To address this, we used patient-derived and genome-edited iPS cells with ASTN2 deletion; cells were further differentiated into neuronal cells. A comprehensive gene expression analysis using genome-edited iPS cells with variants on both alleles revealed that the expression level of ZNF558, a gene specifically expressed in human forebrain neural progenitor cells, was greatly reduced in ASTN2-deleted neuronal cells. Furthermore, the expression of the mitophagy-related gene SPATA18, which is repressed by ZNF558, and mitophagy activity were increased in ASTN2-deleted neuronal cells. These phenotypes were also detected in neuronal cells differentiated from patient-derived iPS cells with heterozygous ASTN2 deletion. Our results suggest that ASTN2 deletion is related to the common pathogenic mechanism of psychiatric disorders by regulating mitophagy via ZNF558.

Prenatal Immune Challenge Differentiates the Effect of Aripiprazole and Risperidone on CD200-CD200R and CX3CL1-CX3CR1 Dyads and Microglial Polarization: A Study in Organotypic Cortical Cultures

Microglia are the primary innate immune cells of the central nervous system and extensively contribute to brain homeostasis. Dysfunctional or excessive activity of microglia may be associated with several neuropsychiatric disorders, including schizophrenia. Therefore, we examined whether aripiprazole and risperidone could influence the expression of the Cd200-Cd200r and Cx3cl1-Cx3cr1 axes, which are crucial for the regulation of microglial activity and interactions of these cells with neurons. Additionally, we evaluated the impact of these drugs on microglial pro- and anti-inflammatory markers (Cd40, Il-1β, Il-6, Cebpb, Cd206, Arg1, Il-10 and Tgf-β) and cytokine release (IL-6, IL-10). The research was executed in organotypic cortical cultures (OCCs) prepared from the offspring of control rats (control OCCs) or those exposed to maternal immune activation (MIA OCCs), which allows for the exploration of schizophrenia-like disturbances in animals. All experiments were performed under basal conditions and after additional stimulation with lipopolysaccharide (LPS), following the "two-hit" hypothesis of schizophrenia. We found that MIA diminished the mRNA level of Cd200r and affected the OCCs' response to additional LPS exposure in terms of this parameter. LPS downregulated the Cx3cr1 expression and profoundly changed the mRNA levels of pro- and anti-inflammatory microglial markers in both types of OCCs. Risperidone increased Cd200 expression in MIA OCCs, while aripiprazole treatment elevated the gene levels of the Cx3cl1-Cx3cr1 dyad in control OCCs. The antipsychotics limited the LPS-generated increase in the expression of proinflammatory factors (Il-1β and Il-6) and enhanced the mRNA levels of anti-inflammatory components (Cd206 and Tgf-β) of microglial polarization, mostly in the absence of the MIA procedure. Finally, we observed a more pronounced modulating impact of aripiprazole on the expression of pro- and anti-inflammatory cytokines when compared to risperidone in MIA OCCs. In conclusion, our data suggest that MIA might influence microglial activation and crosstalk of microglial cells with neurons, whereas aripiprazole and risperidone could beneficially affect these changes in OCCs.

Whole-exome sequencing in a Chinese sample provides preliminary evidence for the link between rare/low-frequency immune-related variants and early-onset schizophrenia

Rare and low-frequency variants contribute to schizophrenia (SCZ), and may influence its age-at-onset (AAO). We examined the association of rare or low-frequency deleterious coding variants in Chinese patients with SCZ. We collected DNA samples in 197 patients with SCZ spectrum disorder and 82 healthy controls (HC), and performed exome sequencing. The AAO variable was ascertained in the majority of SCZ participants for identify the early-onset (EOS, AAO<=18) and adult-onset (AOS, AAO>18) subgroups. We examined the overall association of rare/low-frequency, damaging variants in SCZ versus HC, EOS versus HC, and AOS versus HC at the gene and gene-set levels using Sequence Kernel Association Test. The quantitative rare-variant association test of AAO was conducted. Resampling was used to obtain empirical p-values and to control for family-wise error rate (FWER). In binary-trait association tests, we identified 5 potential candidate risk genes and 10 gene ontology biological processes (GOBP) terms, among which PADI2 reached FWER-adjusted significance. In quantitative rare-variant association tests, we found marginally significant correlations of AAO with alterations in 4 candidate risk genes, and 5 GOBP pathways. Together, the biological and functional profiles of these genes and gene sets supported the involvement of perturbations of neural systems in SCZ, and altered immune functions in EOS.

Improved functional mapping of complex trait heritability with GSA-MiXeR implicates biologically specific gene sets

While genome-wide association studies are increasingly successful in discovering genomic loci associated with complex human traits and disorders, the biological interpretation of these findings remains challenging. Here we developed the GSA-MiXeR analytical tool for gene set analysis (GSA), which fits a model for the heritability of individual genes, accounting for linkage disequilibrium across variants and allowing the quantification of partitioned heritability and fold enrichment for small gene sets. We validated the method using extensive simulations and sensitivity analyses. When applied to a diverse selection of complex traits and disorders, including schizophrenia, GSA-MiXeR prioritizes gene sets with greater biological specificity compared to standard GSA approaches, implicating voltage-gated calcium channel function and dopaminergic signaling for schizophrenia. Such biologically relevant gene sets, often with fewer than ten genes, are more likely to provide insights into the pathobiology of complex diseases and highlight potential drug targets.

Dynamic structure-function coupling across three major psychiatric disorders

BACKGROUND

Convergent evidence has suggested atypical relationships between brain structure and function in major psychiatric disorders, yet how the abnormal patterns coincide and/or differ across different disorders remains largely unknown. Here, we aim to investigate the common and/or unique dynamic structure-function coupling patterns across major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ).

METHODS

We quantified the dynamic structure-function coupling in 452 patients with psychiatric disorders (MDD/BD/SZ = 166/168/118) and 205 unaffected controls at three distinct brain network levels, such as global, meso-, and local levels. We also correlated dynamic structure-function coupling with the topological features of functional networks to examine how the structure-function relationship facilitates brain information communication over time.

RESULTS

The dynamic structure-function coupling is preserved for the three disorders at the global network level. Similar abnormalities in the rich-club organization are found in two distinct functional configuration states at the meso-level and are associated with the disease severity of MDD, BD, and SZ. At the local level, shared and unique alterations are observed in the brain regions involving the visual, cognitive control, and default mode networks. In addition, the relationships between structure-function coupling and the topological features of functional networks are altered in a manner indicative of state specificity.

CONCLUSIONS

These findings suggest both transdiagnostic and illness-specific alterations in the dynamic structure-function relationship of large-scale brain networks across MDD, BD, and SZ, providing new insights and potential biomarkers into the neurodevelopmental basis underlying the behavioral and cognitive deficits observed in these disorders.

Comparative proteomic analysis of three major extracellular vesicle classes secreted from human primary and metastatic colorectal cancer cells: Exosomes, microparticles, and shed midbody remnants

Cell-derived extracellular vesicles (EVs) are evolutionary-conserved secretory organelles that, based on their molecular composition, are important intercellular signaling regulators. At least three classes of circulating EVs are known based on mechanism of biogenesis: exosomes (sEVs/Exos), microparticles (lEVs/MPs), and shed midbody remnants (lEVs/sMB-Rs). sEVs/Exos are of endosomal pathway origin, microparticles (lEVs/MPs) from plasma membrane blebbing and shed midbody remnants (lEVs/sMB-Rs) arise from symmetric cytokinetic abscission. Here, we isolate sEVs/Exos, lEVs/MPs, and lEVs/sMB-Rs secreted from human isogenic primary (SW480) and metastatic (SW620) colorectal cancer (CRC) cell lines in milligram quantities for label-free MS/MS-based proteomic profiling. Purified EVs revealed selective composition packaging of exosomal protein markers in SW480/SW620-sEVs/Exos, metabolic enzymes in SW480/SW620-lEVs/MPs, while centralspindlin complex proteins, nucleoproteins, splicing factors, RNA granule proteins, translation-initiation factors, and mitochondrial proteins selectively traffic to SW480/SW620- lEVs/sMB-Rs. Collectively, we identify 39 human cancer-associated genes in EVs; 17 associated with SW480-EVs, 22 with SW620-EVs. We highlight oncogenic receptors/transporters selectively enriched in sEVs/Exos (EGFR/FAS in SW480-sEVs/Exos and MET, TGFBR2, ABCB1 in SW620-sEVs/Exos). Interestingly, MDK, STAT1, and TGM2 are selectively enriched in SW480-lEVs/sMB-Rs, and ADAM15 to SW620-lEVs/sMB-Rs. Our study reveals sEVs/Exos, lEVs/MPs, and lEVs/sMB-Rs have distinct protein signatures that open potential diagnostic avenues of distinct types of EVs for clinical utility.

Antipsychotic medications associated with increased length of hospital stay in autoimmune encephalitis and multiple sclerosis: A retrospective study

BACKGROUND

Antipsychotic medications (APMs) and selective serotonin reuptake inhibitors (SSRIs) are frequently utilized in patients with neuroinflammatory disorders, such as autoimmune encephalitis and multiple sclerosis (MS). This retrospective study investigates how in-hospital treatment with APMs and SSRIs in patients with these neuroinflammatory diseases are associated with differences in hospital length-of-stay (LOS) and mortality.

METHODS

We evaluated all the inpatients in the Stanford University Hospital from 2008 to 2023 diagnosed with either non-infectious encephalitis or MS and subdivided them into those who did or did not receive APMs or SSRIs while hospitalized. We then analyzed whether hospital LOS and mortality differed with these medications.

RESULTS

Among inpatients with non-infectious encephalitis (n = 114), those who were exposed to APMs had a significantly increased mean LOS (11.8 vs 20.9 days, p < 0.01). For inpatients with MS (n = 1095), treatment with an APM was associated with a significant increase in mean LOS (2.8 vs. 7.1, p < 0.00001). When comparing typical to atypical APMs given to subjects with MS, those who received atypical APMs showed a significant increase in LOS (4.3 vs 10.5, p < 0.01), although typical APMs showed significantly increased risk of mortality (p < 0.05). For inpatients with MS and SSRI use, there was a significant increase in mean hospital LOS (3.5 vs 5.3, p < 0.01), with a significant difference found in those who received fluoxetine or citalopram, but not sertraline or escitalopram. Finally, several healthcare disparities were found, including that Black patients were more likely to receive APMs, and those with MS were more likely to receive typical rather than atypical APMs. Conversely, Black patients with MS were less likely to receive SSRI treatment.

CONCLUSIONS

There was a statistically significant increase in LOS associated with APM use in non-infectious encephalitis and MS, as well as with SSRI use in MS. These data reflect the importance of these medications in these neuroinflammatory disorders and suggest that further investigation into their risks and benefits would be warranted.

The Genesis of Schizophrenia: An Origin Story

Schizophrenia is routinely referred to as a neurodevelopmental disorder, but the role of brain development in a disorder typically diagnosed during early adult life is enigmatic. The authors revisit the neurodevelopmental model of schizophrenia with genomic insights from the most recent schizophrenia clinical genetic association studies, transcriptomic and epigenomic analyses from human postmortem brain studies, and analyses from cellular models that recapitulate neurodevelopment. Emerging insights into schizophrenia genetic risk continue to converge on brain development, particularly stages of early brain development, that may be perturbed to deviate from a typical, normative course, resulting in schizophrenia clinical symptomatology. As the authors explicate, schizophrenia genetic risk is likely dynamic and context dependent, with effects of genetic risk varying spatiotemporally, across the neurodevelopmental continuum. Optimizing therapeutic strategies for the heterogeneous collective of individuals with schizophrenia may likely be guided by leveraging markers of genetic risk and derivative functional insights, well before the emergence of psychosis. Ultimately, rather than a focus on therapeutic intervention during adolescence or adulthood, principles of prediction and prophylaxis in the pre- and perinatal and neonatal stages may best comport with the biology of schizophrenia to address the early-stage perturbations that alter the normative neurodevelopmental trajectory.

A disease-associated gene desert directs macrophage inflammation through ETS2

Increasing rates of autoimmune and inflammatory disease present a burgeoning threat to human health1. This is compounded by the limited efficacy of available treatments1 and high failure rates during drug development2, highlighting an urgent need to better understand disease mechanisms. Here we show how functional genomics could address this challenge. By investigating an intergenic haplotype on chr21q22-which has been independently linked to inflammatory bowel disease, ankylosing spondylitis, primary sclerosing cholangitis and Takayasu's arteritis3-6-we identify that the causal gene, ETS2, is a central regulator of human inflammatory macrophages and delineate the shared disease mechanism that amplifies ETS2 expression. Genes regulated by ETS2 were prominently expressed in diseased tissues and more enriched for inflammatory bowel disease GWAS hits than most previously described pathways. Overexpressing ETS2 in resting macrophages reproduced the inflammatory state observed in chr21q22-associated diseases, with upregulation of multiple drug targets, including TNF and IL-23. Using a database of cellular signatures7, we identified drugs that might modulate this pathway and validated the potent anti-inflammatory activity of one class of small molecules in vitro and ex vivo. Together, this illustrates the power of functional genomics, applied directly in primary human cells, to identify immune-mediated disease mechanisms and potential therapeutic opportunities.

Independent Prediction of Child Psychiatric Symptoms by Maternal Mental Health and Child Polygenic Risk Scores

OBJECTIVE

Prenatal maternal symptoms of depression and anxiety are associated with an increased risk for child socioemotional and behavioral difficulties, supporting the fetal origins of mental health hypothesis. However, to date, studies have not considered specific genomic risk as a possible confound.

METHOD

The Avon Longitudinal Study of Parents and Children (ALSPAC) cohort (n = 5,546) was used to test if child polygenic risk score for attention-deficit/hyperactivity disorder (ADHD), schizophrenia, or depression confounds or modifies the impact of prenatal maternal depression and anxiety on child internalizing, externalizing, and total emotional/behavioral symptoms from age 4 to 16 years. Longitudinal child and adolescent symptom data were analyzed in the ALSPAC cohort using generalized estimating equations. Replication analyses were done in an independent cohort (Prevention of Preeclampsia and Intrauterine Growth Restriction [PREDO] cohort; n = 514) from Finland, which provided complementary measures of maternal mental health and child psychiatric symptoms.

RESULTS

Maternal depression and anxiety and child polygenic risk scores independently and additively predicted behavioral and emotional symptoms from childhood through mid-adolescence. There was a robust prediction of child and adolescent symptoms from both prenatal maternal depression (generalized estimating equation estimate = 0.093, 95% CI 0.065-0.121, p = 2.66 × 10-10) and anxiety (generalized estimating equation estimate = 0.065, 95% CI 0.037-0.093, p = 1.62 × 10-5) after adjusting for child genomic risk for mental disorders. There was a similar independent effect of maternal depression (B = 0.156, 95% CI 0.066-0.246, p = .001) on child symptoms in the PREDO cohort. Genetically informed sensitivity analyses suggest that shared genetic risk only partially explains the reported association between prenatal maternal depression and offspring mental health.

CONCLUSION

These findings highlight the genomic contribution to the fetal origins of mental health hypothesis and further evidence that prenatal maternal depression and anxiety are robust in utero risks for child and adolescent psychiatric symptoms.

PLAIN LANGUAGE SUMMARY

Depression and anxiety affect approximately 15% of pregnant women, and children exposed to maternal depression or anxiety during pregnancy are at higher risk of developing mental health problems. However, the degree to which shared genetics explains the association between maternal and child mental health is unknown. In this study the authors generated polygenic risk scores (PRS), which provide a single measure of genetic risk for complex traits, to investigate the impact of shared genetic risk on the development of childhood mental health problems. Utilizing two longitudinal studies (n = 6,060), the authors found that PRS only partially explained the association between prenatal maternal depression and childhood mental health problems. These analyses show prenatal maternal depression remained a significant predictor of childhood mental health problems after accounting for shared genetic risk, further highlighting that prenatal maternal mental health is a robust predictor of child and adolescent mental health problems.

Is auditory processing measured by the N100 an endophenotype for psychosis? A family study and a meta-analysis

BACKGROUND

The N100, an early auditory event-related potential, has been found to be altered in patients with psychosis. However, it is unclear if the N100 is a psychosis endophenotype that is also altered in the relatives of patients.

METHODS

We conducted a family study using the auditory oddball paradigm to compare the N100 amplitude and latency across 243 patients with psychosis, 86 unaffected relatives, and 194 controls. We then conducted a systematic review and a random-effects meta-analysis pooling our results and 14 previously published family studies. We compared data from a total of 999 patients, 1192 relatives, and 1253 controls in order to investigate the evidence and degree of N100 differences.

RESULTS

In our family study, patients showed reduced N100 amplitudes and prolonged N100 latencies compared to controls, but no significant differences were found between unaffected relatives and controls. The meta-analysis revealed a significant reduction of the N100 amplitude and delay of the N100 latency in both patients with psychosis (standardized mean difference [s.m.d.] = -0.48 for N100 amplitude and s.m.d. = 0.43 for N100 latency) and their relatives (s.m.d. = - 0.19 for N100 amplitude and s.m.d. = 0.33 for N100 latency). However, only the N100 latency changes in relatives remained significant when excluding studies with affected relatives.

CONCLUSIONS

N100 changes, especially prolonged N100 latencies, are present in both patients with psychosis and their relatives, making the N100 a promising endophenotype for psychosis. Such changes in the N100 may reflect changes in early auditory processing underlying the etiology of psychosis.

Mendelian randomization: causal inference leveraging genetic data

Mendelian randomization (MR) leverages genetic information to examine the causal relationship between phenotypes allowing for the presence of unmeasured confounders. MR has been widely applied to unresolved questions in epidemiology, making use of summary statistics from genome-wide association studies on an increasing number of human traits. However, an understanding of essential concepts is necessary for the appropriate application and interpretation of MR. This review aims to provide a non-technical overview of MR and demonstrate its relevance to psychiatric research. We begin with the origins of MR and the reasons for its recent expansion, followed by an overview of its statistical methodology. We then describe the limitations of MR, and how these are being addressed by recent methodological advances. We showcase the practical use of MR in psychiatry through three illustrative examples - the connection between cannabis use and psychosis, the link between intelligence and schizophrenia, and the search for modifiable risk factors for depression. The review concludes with a discussion of the prospects of MR, focusing on the integration of multi-omics data and its extension to delineating complex causal networks.

Bipolar disorder staging and the impact it has on its management: an update

INTRODUCTION

The longitudinal course of bipolar disorder (BD) is associated with an active process of neuroprogression, characterized by structural brain alterations and progressive functional impairment. In the last decades, a growing need of a standardized staging model for BD arose, with the aim of a more appropriate definition of stage-specific clinical manifestations and the identification of more customized therapeutic tools.

AREAS COVERED

The authors review the literature on clinical aspects, neurobiological correlates and treatment issues related to BD progression. Thereafter, they address the definition, constructs, and evolution of the staging concept, focusing on the clinical applications of BD staging models available in literature.

EXPERT OPINION

Although several staging models for BD have been proposed to date, their application in clinical practice is still relatively scant. This may have a detrimental impact on the clinical and therapeutic management of BD, in terms of early and proper diagnosis as well as tailored treatment interventions according to the different stages of illness. Future research efforts should tend to the integration of recent insights on neuroimaging and epigenetic markers, toward a standardized and multidimensional staging model.

Altered excitatory and inhibitory ionotropic receptor subunit expression in the cortical visuospatial working memory network in schizophrenia

Dysfunction of the cortical dorsal visual stream and visuospatial working memory (vsWM) network in individuals with schizophrenia (SZ) likely reflects alterations in both excitatory and inhibitory neurotransmission within nodes responsible for information transfer across the network, including primary visual (V1), visual association (V2), posterior parietal (PPC), and dorsolateral prefrontal (DLPFC) cortices. However, the expression patterns of ionotropic glutamatergic and GABAergic receptor subunits across these regions, and alterations of these patterns in SZ, have not been investigated. We quantified transcript levels of key subunits for excitatory N-methyl-D-aspartate receptors (NMDARs), excitatory alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors (AMPARs), and inhibitory GABAA receptors (GABAARs) in postmortem total gray matter from V1, V2, PPC, and DLPFC of unaffected comparison (UC) and matched SZ subjects. In UC subjects, levels of most AMPAR and NMDAR mRNAs exhibited opposite rostral-to-caudal gradients, with AMPAR GRIA1 and GRIA2 mRNA levels highest in DLPFC and NMDAR GRIN1 and GRIN2A mRNA levels highest in V1. GABRA5 and GABRA1 mRNA levels were highest in DLPFC and V1, respectively. In SZ, most transcript levels were lower relative to UC subjects, with these differences largest in V1, intermediate in V2 and PPC, and smallest in DLPFC. In UC subjects, these distinct patterns of receptor transcript levels across the cortical vsWM network suggest that the balance between excitation and inhibition is achieved in a region-specific manner. In SZ subjects, the large deficits in excitatory and inhibitory receptor transcript levels in caudal sensory regions suggest that abnormalities early in the vsWM pathway might contribute to altered information processing in rostral higher-order regions.

Adolescent Psychedelic Use and Psychotic or Manic Symptoms

Importance

While psychedelic-assisted therapy has shown promise in the treatment of certain psychiatric disorders, little is known about the potential risk of psychotic or manic symptoms following naturalistic psychedelic use, especially among adolescents.

Objective

To investigate associations between naturalistic psychedelic use and self-reported psychotic or manic symptoms in adolescents using a genetically informative design.

Design, Setting, and Participants

This study included a large sample of adolescent twins (assessed at age 15, 18, and 24 years) born between July 1992 and December 2005 from the Swedish Twin Registry and cross-sectionally evaluated the associations between past psychedelic use and psychotic or manic symptoms at age 15 years. Individuals were included if they answered questions related to past use of psychedelics. Data were analyzed from October 2022 to November 2023.

Main Outcomes and Measures

Primary outcome measures were self-reported psychotic and manic symptoms at age 15 years. Lifetime use of psychedelics and other drugs was also assessed at the same time point.

Results

Among the 16 255 participants included in the analyses, 8889 were female and 7366 were male. Among them, 541 participants reported past use of psychedelics, most of whom (535 of 541 [99%]) also reported past use of other drugs (ie, cannabis, stimulants, sedatives, opioids, inhalants, or performance enhancers). When adjusting for substance-specific and substance-aggregated drug use, psychedelic use was associated with reduced psychotic symptoms in both linear regression analyses (β, -0.79; 95% CI, -1.18 to -0.41 and β, -0.39; 95% CI, -0.50 to -0.27, respectively) and co-twin control analyses (β, -0.89; 95% CI, -1.61 to -0.16 and β, -0.24; 95% CI, -0.48 to -0.01, respectively). In relation to manic symptoms, likewise adjusting for substance-specific and substance-aggregated drug use, statistically significant interactions were found between psychedelic use and genetic vulnerability to schizophrenia (β, 0.17; 95% CI, 0.01 to 0.32 and β, 0.17; 95% CI, 0.02 to 0.32, respectively) or bipolar I disorder (β, 0.20; 95% CI, 0.04 to 0.36 and β, 0.17; 95% CI, 0.01 to 0.33, respectively).

Conclusions and Relevance

The findings in this study suggest that, after adjusting for other drug use, naturalistic use of psychedelic may be associated with lower rates of psychotic symptoms among adolescents. At the same time, the association between psychedelic use and manic symptoms seems to be associated with genetic vulnerability to schizophrenia or bipolar I disorder. These findings should be considered in light of the study's limitations and should therefore be interpreted with caution.

Decoding frontotemporal and cell-type-specific vulnerabilities to neuropsychiatric disorders and psychoactive drugs

Frontotemporal lobe abnormalities are linked to neuropsychiatric disorders and cognition, but the role of cellular heterogeneity between temporal lobe (TL) and frontal lobe (FL) in the vulnerability to genetic risk factors remains to be elucidated. We integrated single-nucleus transcriptome analysis in 'fresh' human FL and TL with genetic susceptibility, gene dysregulation in neuropsychiatric disease and psychoactive drug response data. We show how intrinsic differences between TL and FL contribute to the vulnerability of specific cell types to both genetic risk factors and psychoactive drugs. Neuronal populations, specifically PVALB neurons, were most highly vulnerable to genetic risk factors for psychiatric disease. These psychiatric disease-associated genes were mostly upregulated in the TL, and dysregulated in the brain of patients with obsessive-compulsive disorder, bipolar disorder and schizophrenia. Among these genes, GRIN2A and SLC12A5, implicated in schizophrenia and bipolar disorder, were significantly upregulated in TL PVALB neurons and in psychiatric disease patients' brain. PVALB neurons from the TL were twofold more vulnerable to psychoactive drugs than to genetic risk factors, showing the influence and specificity of frontotemporal lobe differences on cell vulnerabilities. These studies provide a cell type resolved map of the impact of brain regional differences on cell type vulnerabilities in neuropsychiatric disorders.

Recapitulation of Perturbed Striatal Gene Expression Dynamics of Donors' Brains With Ventral Forebrain Organoids Derived From the Same Individuals With Schizophrenia

OBJECTIVE

Schizophrenia is a brain disorder that originates during neurodevelopment and has complex genetic and environmental etiologies. Despite decades of clinical evidence of altered striatal function in affected patients, studies examining its cellular and molecular mechanisms in humans are limited. To explore neurodevelopmental alterations in the striatum associated with schizophrenia, the authors established a method for the differentiation of induced pluripotent stem cells (iPSCs) into ventral forebrain organoids (VFOs).

METHODS

VFOs were generated from postmortem dural fibroblast-derived iPSCs of four individuals with schizophrenia and four neurotypical control individuals for whom postmortem caudate genotypes and transcriptomic data were profiled in the BrainSeq neurogenomics consortium. Individuals were selected such that the two groups had nonoverlapping schizophrenia polygenic risk scores (PRSs).

RESULTS

Single-cell RNA sequencing analyses of VFOs revealed differences in developmental trajectory between schizophrenia and control individuals in which inhibitory neuronal cells from the patients exhibited accelerated maturation. Furthermore, upregulated genes in inhibitory neurons in schizophrenia VFOs showed a significant overlap with upregulated genes in postmortem caudate tissue of individuals with schizophrenia compared with control individuals, including the donors of the iPSC cohort.

CONCLUSIONS

The findings suggest that striatal neurons derived from high-PRS individuals with schizophrenia carry abnormalities that originated during early brain development and that the VFO model can recapitulate disease-relevant cell type-specific neurodevelopmental phenotypes in a dish.

Variation of subclinical psychosis across 16 sites in Europe and Brazil: findings from the multi-national EU-GEI study

BACKGROUND

Incidence of first-episode psychosis (FEP) varies substantially across geographic regions. Phenotypes of subclinical psychosis (SP), such as psychotic-like experiences (PLEs) and schizotypy, present several similarities with psychosis. We aimed to examine whether SP measures varied across different sites and whether this variation was comparable with FEP incidence within the same areas. We further examined contribution of environmental and genetic factors to SP.

METHODS

We used data from 1497 controls recruited in 16 different sites across 6 countries. Factor scores for several psychopathological dimensions of schizotypy and PLEs were obtained using multidimensional item response theory models. Variation of these scores was assessed using multi-level regression analysis to estimate individual and between-sites variance adjusting for age, sex, education, migrant, employment and relational status, childhood adversity, and cannabis use. In the final model we added local FEP incidence as a second-level variable. Association with genetic liability was examined separately.

RESULTS

Schizotypy showed a large between-sites variation with up to 15% of variance attributable to site-level characteristics. Adding local FEP incidence to the model considerably reduced the between-sites unexplained schizotypy variance. PLEs did not show as much variation. Overall, SP was associated with younger age, migrant, unmarried, unemployed and less educated individuals, cannabis use, and childhood adversity. Both phenotypes were associated with genetic liability to schizophrenia.

CONCLUSIONS

Schizotypy showed substantial between-sites variation, being more represented in areas where FEP incidence is higher. This supports the hypothesis that shared contextual factors shape the between-sites variation of psychosis across the spectrum.

Identification of important gene signatures in schizophrenia through feature fusion and genetic algorithm

Schizophrenia is a debilitating psychiatric disorder that can significantly affect a patient's quality of life and lead to permanent brain damage. Although medical research has identified certain genetic risk factors, the specific pathogenesis of the disorder remains unclear. Despite the prevalence of research employing magnetic resonance imaging, few studies have focused on the gene level and gene expression profile involving a large number of screened genes. However, the high dimensionality of genetic data presents a great challenge to accurately modeling the data. To tackle the current challenges, this study presents a novel feature selection strategy that utilizes heuristic feature fusion and a multi-objective optimization genetic algorithm. The goal is to improve classification performance and identify the key gene subset for schizophrenia diagnostics. Traditional gene screening techniques are inadequate for accurately determining the precise number of key genes associated with schizophrenia. Our innovative approach integrates a filter-based feature selection method to reduce data dimensionality and a multi-objective optimization genetic algorithm for improved classification tasks. By combining the filtering and wrapper methods, our strategy leverages their respective strengths in a deliberate manner, leading to superior classification accuracy and a more efficient selection of relevant genes. This approach has demonstrated significant improvements in classification results across 11 out of 14 relevant datasets. The performance on the remaining three datasets is comparable to the existing methods. Furthermore, visual and enrichment analyses have confirmed the practicality of our proposed method as a promising tool for the early detection of schizophrenia.

Polygenic risk scores and the prediction of onset of mood and psychotic disorders in adolescents and young adults

AIM

To examine whether polygenic risk scores (PRS) for neuroticism, depression, bipolar disorder and schizophrenia are higher in individuals manifesting trans-diagnostic risk factors for the development of major mental disorders and whether PRS enhance prediction of early onset full-threshold disorders.

METHODS

Using data from the Brisbane Longitudinal Twin Study, we examined individual PRS for neuroticism, depression, bipolar disorder and schizophrenia, recorded evidence of subthreshold syndromes and family history of mood and/or psychotic disorders and noted progression to trans-diagnostic clinical caseness (onset of major mental disorders) at follow-up. We undertook multivariate, receiver operating curve and logistic regression analyses that were adjusted for known variables of influence (age, twin status, and so on).

RESULTS

Of 1473 eligible participants (female = 866, 59%; mean age 26.3 years), 28% (n = 409) met caseness criteria for a mood and/or psychotic disorder. All PRS were higher in cases versus non-cases but associations with different levels of risk were inconsistent. The prediction of caseness (reported as area under the curve with 95% confidence intervals [CI]) improved from 0.68 (95% CI: 0.65, 0.71) when estimated using clinical risk factors alone up to 0.71 (95% CI: 0.69, 0.73) when PRS were added to the model. Logistic regression identified five variables that optimally classified individuals according to caseness: age, sex, individual risk characteristics, PRS for depression and mental health case status of cotwins or siblings.

CONCLUSIONS

The findings need replication. However, this exploratory study suggests that combining PRS with other risk factors has the potential to improve outcome prediction in youth.

Identification of Immune-Related Gene Signature in Schizophrenia

BACKGROUND

Schizophrenia (SCZ) is a type of psychiatric disorder characterized by multiple symptoms. Our aim is to decipher the relevant mechanisms of immune-related gene signatures in SCZ.

METHODS

The SCZ dataset and its associated immunoregulatory genes were retrieved using Gene Expression Omnibus (GEO) and single-sample gene set enrichment analysis (ssGSEA). Co-expressed gene modules were determined through weighted gene correlation network analysis (WGCNA). To elucidate the functional characteristics of these clusters, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used. Additionally, gene set enrichment analysis (GSEA) and Gene Set Variation Analysis (GSVA) were conducted to identify enriched pathways for the immune subgroups. A protein-protein interaction (PPI) network analysis was performed to identify core genes relevant to SCZ.

RESULTS

A significantly higher immune score was observed in SCZ compared to control samples. Seven distinct gene modules were identified, with genes highlighted in green selected for further analysis. Using the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) method, degrees of immune cell adhesion and accumulation related to 22 different immune cell types were calculated. Significantly enriched bioprocesses concerning the immunoregulatory genes with differential expressions included interferon-beta, IgG binding, and response to interferon-gamma, according to GO and KEGG analyses. Eleven hub genes related to immune infiltration emerged as key players among the three top-ranked GO terms.

CONCLUSIONS

This study underscores the involvement of immunoregulatory reactions in SCZ development. Eleven immune-related genes (IFITM1 (interferon induced transmembrane protein 1), GBP1 (guanylate binding protein 1), BST2 (bone marrow stromal cell antigen 2), IFITM3 (interferon induced transmembrane protein 3), GBP2 (guanylate binding protein 2), CD44 (CD44 molecule), FCER1G (Fc epsilon receptor Ig), HLA-DRA (major histocompatibility complex, class II, DR alpha), FCGR2A (Fc gamma receptor IIa), IFI16 (interferon gamma inducible protein 16), and FCGR3B (Fc gamma receptor IIIb)) were identified as hub genes, representing potential biomarkers and therapeutic targets associated with the immune response in SCZ patients.

Exploring the multifaceted role of GCN1: Implications in cellular responses and disease pathogenesis

GCN1 is a highly conserved protein present widely across eukaryotes. As an upstream activator of protein kinase GCN2, GCN1 plays a pivotal role in integrated stress responses, such as amino acid starvation and oxidative stress. Through interaction with GCN2, GCN1 facilitates the activation of GCN2, thus initiating downstream signaling cascades in response to cellular stressors. In these contexts, the activation of GCN2 necessitates the presence and action of GCN1. Notably, GCN1 also operates as a ribosome collision sensor, contributing significantly to the translation quality control pathway. These discoveries offer valuable insights into cellular responses to internal stresses, vital for maintaining cellular homeostasis. Additionally, GCN1 exhibits the ability to regulate the cell cycle and suppress inflammation, among other processes, independently of GCN2. Our review outlines the structural characteristics and biological functions of GCN1, shedding light on its significant involvement in the onset and progression of various cancer and non-cancer diseases. Our work underscores the role of GCN1 in the context of drug therapeutic effects, hinting at its potential as a promising drug target. Furthermore, our work delves deep into the functional mechanisms of GCN1, promising innovative avenues for the diagnosis and treatment of diseases in the future. The exploration of GCN1's multifaceted roles not only enhances our understanding of its mechanisms but also paves the way for novel therapeutic interventions. The ongoing quest to unveil additional functions of GCN1 holds the promise of further enriching our comprehension of its mode of action.

The interaction between early life complications and a polygenic risk score for schizophrenia is associated with brain activity during emotion processing in healthy participants

BACKGROUND

Previous evidence suggests that early life complications (ELCs) interact with polygenic risk for schizophrenia (SCZ) in increasing risk for the disease. However, no studies have investigated this interaction on neurobiological phenotypes. Among those, anomalous emotion-related brain activity has been reported in SCZ, even if evidence of its link with SCZ-related genetic risk is not solid. Indeed, it is possible this relationship is influenced by non-genetic risk factors. Thus, this study investigated the interaction between SCZ-related polygenic risk and ELCs on emotion-related brain activity.

METHODS

169 healthy participants (HP) in a discovery and 113 HP in a replication sample underwent functional magnetic resonance imaging (fMRI) during emotion processing, were categorized for history of ELCs and genome-wide genotyped. Polygenic risk scores (PRSs) were computed using SCZ-associated variants considering the most recent genome-wide association study. Furthermore, 75 patients with SCZ also underwent fMRI during emotion processing to verify consistency of their brain activity patterns with those associated with risk factors for SCZ in HP.

RESULTS

Results in the discovery and replication samples indicated no effect of PRSs, but an interaction between PRS and ELCs in left ventrolateral prefrontal cortex (VLPFC), where the greater the activity, the greater PRS only in presence of ELCs. Moreover, SCZ had greater VLPFC response than HP.

CONCLUSIONS

These results suggest that emotion-related VLPFC response lies in the path from genetic and non-genetic risk factors to the clinical presentation of SCZ, and may implicate an updated concept of intermediate phenotype considering early non-genetic factors of risk for SCZ.

Latin American Trans-ancestry INitiative for OCD genomics (LATINO): Study protocol

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder. Worldwide, its prevalence is ~2% and its etiology is mostly unknown. Identifying biological factors contributing to OCD will elucidate underlying mechanisms and might contribute to improved treatment outcomes. Genomic studies of OCD are beginning to reveal long-sought risk loci, but >95% of the cases currently in analysis are of homogenous European ancestry. If not addressed, this Eurocentric bias will result in OCD genomic findings being more accurate for individuals of European ancestry than other ancestries, thereby contributing to health disparities in potential future applications of genomics. In this study protocol paper, we describe the Latin American Trans-ancestry INitiative for OCD genomics (LATINO, https://www.latinostudy.org). LATINO is a new network of investigators from across Latin America, the United States, and Canada who have begun to collect DNA and clinical data from 5000 richly phenotyped OCD cases of Latin American ancestry in a culturally sensitive and ethical manner. In this project, we will utilize trans-ancestry genomic analyses to accelerate the identification of OCD risk loci, fine-map putative causal variants, and improve the performance of polygenic risk scores in diverse populations. We will also capitalize on rich clinical data to examine the genetics of treatment response, biologically plausible OCD subtypes, and symptom dimensions. Additionally, LATINO will help elucidate the diversity of the clinical presentations of OCD across cultures through various trainings developed and offered in collaboration with Latin American investigators. We believe this study will advance the important goal of global mental health discovery and equity.

Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study

Genomic prediction of antipsychotic dose and polypharmacy has been difficult, mainly due to limited access to large cohorts with genetic and drug prescription data. In this proof of principle study, we investigated if genetic liability for schizophrenia is associated with high dose requirements of antipsychotics and antipsychotic polypharmacy, using real-world registry and biobank data from five independent Nordic cohorts of a total of N = 21,572 individuals with psychotic disorders (schizophrenia, bipolar disorder, and other psychosis). Within regression models, a polygenic risk score (PRS) for schizophrenia was studied in relation to standardized antipsychotic dose as well as antipsychotic polypharmacy, defined based on longitudinal prescription registry data as well as health records and self-reported data. Meta-analyses across the five cohorts showed that PRS for schizophrenia was significantly positively associated with prescribed (standardized) antipsychotic dose (beta(SE) = 0.0435(0.009), p = 0.0006) and antipsychotic polypharmacy defined as taking ≥2 antipsychotics (OR = 1.10, CI = 1.05-1.21, p = 0.0073). The direction of effect was similar in all five independent cohorts. These findings indicate that genotypes may aid clinically relevant decisions on individual patients´ antipsychotic treatment. Further, the findings illustrate how real-world data have the potential to generate results needed for future precision medicine approaches in psychiatry.

Associations between workplace violence and suicidal ideation among Chinese medical staff: a propensity score matching analysis

Physical and mental health problems had been identified as the negative outcomes of workplace violence (WPV) against medical staff. Considering the proven associations between physical and mental health and suicidal ideation, it is reasonable to assume that WPV may associate with suicidal ideation. However, few studies were conducted to explore the relationship between WPV and their suicidal ideation against medical staff. Based on a cross-sectional design, 3, 426 medical staff working in general hospitals were interviewed in Shandong Province, China. Socio-demographic characteristics, work-related factors, psychological variables, WPV, and suicidal ideation were evaluated. Propensity score matching (PSM) was performed to explore the association between WPV and suicidal ideation. The prevalence of suicidal ideation among medical staff was 9.1% (312/3426), and 52.2% (1788/3426) of medical staff reported the WPV experience. Before PSM, we found that the association between WPV and suicidal ideation was statistically significant (aOR = 1.606, p < 0.01). After PSM, there was a statistically significant correlation between WPV and suicidal ideation (aOR = 1.525, p < 0.01). This study supported the correlations between WPV against medical staff and their suicidal ideation. The results of PSM further implied that WPV might cause suicidal ideation among medical staff. Psychological health, especially for suicidal ideation, should be paid attention for medical staff with WPV experiences.

Single-cell mapping of cell-type specific chromatin architecture in the central nervous system

Determining how chromatin is structured in the nucleus is critical to studying its role in gene regulation. Recent advances in the analysis of single-cell chromatin architecture have considerably improved our understanding of cell-type-specific chromosome conformation and nuclear architecture. In this review, we discuss the methods used for analysis of 3D chromatin conformation, including sequencing-based methods, imaging-based techniques, and computational approaches. We further review the application of these methods in the study of the role of chromatin topology in neural development and disorders.