Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Polygenic dissection of treatment-resistant depression with proxy phenotypes in the UK Biobank

BACKGROUND

Treatment-resistant depression (TRD) affects one-third of major depressive disorder (MDD) patients. Previous pharmacogenetic studies suggest genetic variation may influence medication response but findings are heterogeneous. We conducted a comprehensive genetic investigation using proxy TRD phenotypes (TRDp) that mirror the treatment options of MDD from UK Biobank primary care records.

METHODS

Among 15,125 White British MDD patients, we identified TRDp with medication changes (switching or receiving multiple antidepressants [AD]); augmentation therapy (antipsychotics; mood stabilizers; valproate; lithium); or electroconvulsive therapy (ECT). Hospitalized TRDp patients (HOSP-TRDp) were also identified. We conducted genome-wide association analysis, estimated SNP-heritability (hg2), and assessed the genetic burden for nine psychiatric diseases using polygenic risk scores (PRS).

RESULTS

TRDp patients were more often female, unemployed, less educated, and had higher BMI, with hospitalization rates twice as high as non-TRDp. While no credible risk variants emerged, heritability analysis showed significant genetic influence on TRDp (liability hg2 21-24 %), particularly for HOSP-TRDp (28-31 %). TRDp classified by AD changes and augmentation carried an elevated yet varied polygenic burden for MDD, ADHD, BD, and SCZ. Higher BD PRS increased the likelihood of receiving ECT, lithium, and valproate by 1.27-1.80 fold. Patients in the top 10 % PRS relative to the average had a 12-36 % and 24-51 % higher risk of TRDp and HOSP-TRDp, respectively.

CONCLUSIONS

Our findings support a significant polygenic basis for TRD, highlighting genetic and phenotypic distinctions from non-TRD. We demonstrate that different TRDp endpoints are enriched with various spectra of psychiatric genetic liability, offering insights into pharmacogenomics and TRD's complex genetic architecture.

Evaluation of the two-way associations between mental disorders and menstrual irregularities: A Mendelian randomization study from both directions

OBJECTIVE

We aimed to assess the bidirectional relationship between mental disorders and menstrual irregularities using a two-sample Mendelian randomization (MR) approach.

METHODS

The analyses were conducted using a two-sample MR method. Analytical tools were derived from large-scale genome-wide association studies, including those on schizophrenia (SCZ, n = 127,906), bipolar disorder (BIP, n = 353,899), major depressive disorder (MDD, n = 674,452), anxiety and stress-related disorder (ASRD, n = 1,096,458), irregular menses (n = 196,550), excessive menstruation (n = 144,388), and dysmenorrhea (n = 114,540). Inverse variance weighting was used for the two-sample MR analyses, while sensitivity analyses were performed using MR-Egger, weighted median, and simple median methods.

RESULTS

MDD and ASRD were associated with an increased risk of irregular menses (P < 0.05); however, no reliable outcomes were found regarding the relationship between SCZ, BIP, and the three types of menstrual irregularities (P > 0.05). Furthermore, ASRD was also associated with an increased likelihood of excessive menstruation and dysmenorrhea (P < 0.05). However, the relationship between MDD and excessive menstruation was not statistically significant (P > 0.05). Dysmenorrhea was associated with an increased risk of MDD and ASRD (P < 0.05).

CONCLUSION

This study provides strong evidence supporting the associations between ASRD and the three types of menstrual irregularities, as well as between MDD and irregular menses and dysmenorrhea.

Genetic insights into the role of mitochondria-related genes in mental disorders: An integrative multi-omics analysis

BACKGROUND

Mitochondrial dysfunction has been implicated in the development of mental disorders, yet the underlying mechanisms remain unclear. In this study, we employed summary-data-based Mendelian randomization (SMR) analysis to explore the associations between mitochondrial-related genes and seven common mental disorders across gene expression, DNA methylation, and protein levels.

METHOD

Summary statistics from genome-wide association studies were used for seven mental disorders, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, anxiety, bipolar disorder, major depressive disorder, post-traumatic stress disorder, and schizophrenia (SCZ). Instrumental variables associated with 1136 mitochondria-related genes were derived from summary statistics for DNA methylation, gene expression, and protein quantitative trait loci. SMR analyses and colocalization analyses were then conducted across these three biological levels to explore the associations with each of the seven mental disorders.

RESULTS

We identified mitochondria-related genes associated with mental disorders with multi-omics evidence: RMDN1 for ADHD, and ACADVL, ETFA, MMAB, and PPA2 for SCZ. Specifically, an increase of one standard deviation in the level of RMDN1 was linked to a 12 % decrease in the risk of developing ADHD (OR = 0.88, 95 % CI: 0.83-0.94). Increased levels of ETFA (OR = 1.79, 95 % CI: 1.24-2.60) and MMAB (OR = 1.10, 95 % CI: 1.05-1.16) were significantly associated with increased risk of SCZ. Conversely, high levels of ACADVL (OR = 0.50, 95 % CI: 0.33-0.77) and PPA2 (OR = 0.68, 95 % CI: 0.55-0.85) were associated with a reduced risk of SCZ.

CONCLUSIONS

These findings suggested that dysfunction in mitochondria-related genes may underlie the molecular mechanisms of ADHD and SCZ, providing novel biomarkers for diagnosis and therapeutic interventions.

Causal relationship between gut microbiota, lipids, and neuropsychiatric disorders: A Mendelian randomization mediation study

BACKGROUND

Numerous studies have shown an interconnection between the gut microbiota and the brain via the "gut-brain" axis. However, the causal relationships between gut microbiota, lipids, and neuropsychiatric disorders remain unclear. This study aimed to analyze potential associations among gut microbiota, lipids, and neuropsychiatric disorders-including AD, PD, ALS, MS, SCZ, MDD, and BD-using summary data from large-scale GWAS.

METHODS

Bidirectional Mendelian randomization (MR) with inverse variance weighting (IVW) was the primary method. Supplementary analyses included sensitivity analyses, Steiger tests, and Bayesian weighted MR (BWMR). Mediation analyses used two-step MR (TSMR) and multivariable MR (MVMR).

RESULTS

The analyses revealed 51 positive correlations (risk factors) (β > 0, P < 0.05) and 47 negative correlations (protective factors) (β < 0, P < 0.05) between gut microbiota and neuropsychiatric disorders. In addition, 35 positive correlations (β > 0, P < 0.05) and 22 negative correlations (β < 0, P < 0.05) between lipids and neuropsychiatric disorders were observed. Assessment of reverse causality with the seven neuropsychiatric disorders as exposures and the identified gut microbiota and lipids as outcomes revealed no evidence of reverse causality (P > 0.05). Mediation analysis indicated that the effect of the species Bacteroides plebeius on MDD is partially mediated through the regulation of phosphatidylcholine (16:0_20:4) levels (mediation proportion = 10.9 % [95 % CI = 0.0110-0.2073]).

CONCLUSION

This study provides evidence of a causal relationship between gut microbiota and neuropsychiatric disorders, suggesting lipids as mediators. These findings offer new insights into the mechanisms by which gut microbiota may influence neuropsychiatric disorders.

Schizophrenia, bipolar disorder and major depressive disorder are probably not risk factors for cardiovascular disease: A Mendelian randomized study

BACKGROUND

Individuals with severe mental illnesses (SMI) like schizophrenia, bipolar disorder (BD), and major depressive disorder (MDD) have an increased risk for cardiovascular diseases (CVD), but the causal relationship remains unclear.

METHODS

Mendelian randomization (MR) was used to investigate the potential causal relationship between SMI and CVD and its five subtypes of disease, coronary heart disease, myocardial infarction, stroke, heart failure, and atrial fibrillation. Subsequently, the MR results of SMI with CVD and its subtypes were meta-analyzed separately. To assess the robustness of the findings, Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis were used. Select single nucleotide polymorphisms (SNPs) related to SMI and CVD and their five subtypes (coronary heart disease, myocardial infarction, stroke, heart failure, and atrial fibrillation). Use univariable Mendelian randomization (UVMR) and multivariate Mendelian randomization (MVMR) to assess the causal relationship between these conditions. Conduct a meta-analysis of the MR results of SMI and CVD and their subtypes. Use MR mediation analysis to evaluate the mediating effect of BMI between BD and CVD. Use Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis to enhance the robustness of the study.

RESULTS

MR analyses have revealed correlations between schizophrenia and BD with CVD and their subtypes in certain datasets. No significant evidence of an association between MDD and CVD or its subtypes was observed in our MR analyses. After MVMR and MR meta-analysis, no basis for genetically predicted SMI increasing CVD and their subtypes was found. The MR mediation analysis showed that the reduced risk of certain CVDs in BD was partially related to BMI to some extent.

CONCLUSION

Our MR study did not provide conclusive evidence for a causal association between genetic predisposition to SMI and CVD. Based on the available evidence, it would be more appropriate to consider SMI as potential risk markers for CVD and its subtypes rather than definitive risk factors.

Relationship Between Problematic Alcohol Use and Various Psychiatric Disorders: A Genetically Informed Study

OBJECTIVE

Problematic alcohol use (PAU) adversely affects the clinical course of psychiatric disorders. Genetic studies have suggested that genetic factors underlie the co-occurrence of PAU with psychiatric disorders. This study aimed to elucidate shared genetic architectures, prioritizing genes that disorders may have in common.

METHODS

Using genome-wide association data of PAU including 435,563 samples from people of European ancestry, this study investigated the genetic relationship between PAU and 11 psychiatric disorders using a bivariate causal mixture model (MiXeR). Local genetic correlation and colocalization analyses were conducted to identify the genomic regions significantly associated with PAU and each psychiatric disorder. Postanalysis included the false discovery rate (FDR) and transcriptome-wide association studies (TWASs), as well as summary-data-based Mendelian randomization to prioritize shared genes by integrating brain transcriptome data.

RESULTS

MiXeR analysis revealed a substantial polygenic overlap (39%-73%) between PAU and psychiatric disorders. Four bivariate genomic regions with high correlations suggest shared causal variants of PAU with major depression and schizophrenia. Within these regions, four and six genes for the PAU-major depression and PAU-schizophrenia pairs, respectively, were mapped by conjunctional FDR analysis. Furthermore, TTC12 and ANKK1 were identified as potential causal genes for PAU and these disorders. The findings were replicated in multi-ancestry analyses of colocalization and TWASs.

CONCLUSIONS

Despite the varying degrees of genetic overlap and directions of shared genetic effect correlations, these results imply the presence of shared genetic factors influencing the comorbidity of PAU and psychiatric disorders. Additionally, TTC12 and ANKK1, located near DRD2, may be causally associated with comorbid conditions.

Polygenic risk for schizophrenia and subjective well-being in a general population sample

BACKGROUND

Previous evidence has reported associations of a polygenic risk score for schizophrenia (PRSSCZ) with negative developmental outcomes, such as psychiatric symptoms, adverse health behaviors, and reduced everyday functioning. We now investigated the relationship of PRSSCZ with subjectively experienced well-being.

METHODS

Participants (n = 1866) came from the prospective population-based Young Finns Study (YFS). Subjective well-being in adulthood was assessed in terms of life satisfaction, optimism, and self-acceptance (when participants were 20-50 years old). A PRSSCZ was calculated based on the most recent genome-wide association study on schizophrenia. Covariates included age, sex, early family environment, adulthood socioeconomic factors, and adulthood health behaviors.

RESULTS

The PRSSCZ did not predict any domain of subjective well-being, including life satisfaction, optimism, and self-acceptance. After adding covariates in a stepwise manner or including/excluding participants with diagnosed non-affective psychotic disorders, all the associations remained non-significant. Age- and sex-interaction analyses showed that PRSSCZ was not associated with subjective well-being in either sex or in any age between 20 and 50 years.

CONCLUSIONS

While high PRSSCZ has been linked to multiple adversities in previous studies, we did not find any association between high PRSSCZ and subjective measures of life satisfaction, optimism, and self-acceptance.

Causal effects of schizophrenia on sleep and eating disorders: A Mendelian randomization study

Previous studies have suggested a potential connection between schizophrenia (SCZ) and sleep and eating disorders. However, these studies have not sufficiently accounted for potential confounding factors, leaving the true causal relationship unclear. Understanding this causal link is essential for developing effective prevention and treatment strategies. To address this gap, we aim to investigate the causal effect of SCZ on sleep and eating disorders using Mendelian randomization (MR) analysis. This method offers a more robust approach by leveraging genetic variants as instrumental variables to rigorously examine the relationship between SCZ and its comorbidities. We conducted bidirectional MR analyses using genome-wide association study summary statistics of SCZ, sleep disorders, and eating disorders. These analyses were conducted after confirming adherence to the 3 core MR assumptions, removing instrumental variables with confounding effects, and directionally harmonizing all data. Then we used Cochran Q test, MR-Egger intercept analysis, and leave-one-out method to conduct the sensitivity analysis of this study to test its heterogeneity and pleiotropy. The results of the inverse-variance weighted (IVW) approach suggest that SCZ increases the risk of sleep disorders (IVW: odds ratio [OR] = 1.041, 95% confidence interval [CI]: 1.012-1.070, P < .01), whereas studies in the opposite direction have not found an effect of sleep disorders on SCZ. The results of IVW suggest that SCZ increases the risk of eating disorders (IVW: OR = 1.228, 95% CI: 1.090-1.384, P < .001), and the weighted median (WM) method similarly provided evidence that SCZ increases the risk of eating disorders (WM: OR = 1.200, 95% CI: 1.019-1.407, P < .05). This study concluded that SCZ is causally associated with sleep and eating disorders. In clinical practice, psychiatrists should pay attention to the daily sleep and eating status of patients with SCZ, and take appropriate measures and countermeasures as early as possible if there is any abnormality.

ErbB inhibition rescues nigral dopamine neuron hyperactivity and repetitive behaviors in a mouse model of fragile X syndrome

Repetitive stereotyped behaviors are core symptoms of autism spectrum disorders (ASD) and fragile X syndrome (FXS), the prevalent genetic cause of intellectual disability and autism. The nigrostriatal dopamine (DA) circuit rules movement and creation of habits and sequential behaviors; therefore, its dysregulation could promote autistic repetitive behaviors. Nevertheless, inspection of substantia nigra pars compacta (SNpc) DA neurons in ASD models has been overlooked and specific evidence of their altered activity in ASD and FXS is absent. Here, we show that hyperactivity of SNpc DA neurons is an early feature of FXS. The underlying mechanism relies on an interplay between metabotropic glutamate receptor 1 (mGluR1) and ErbB tyrosine kinases, receptors for the neurotrophic and differentiation factors known as neuregulins. Up-regulation of ErbB4 and ErbB2 in nigral DA neurons drives neuronal hyperactivity and repetitive behaviors of the FXS mouse, concurrently rescued by ErbB inhibition. In conclusion, beyond providing the first evidence that nigral DA neuron hyperactivity is a signature of FXS and nigral mGluR1 and ErbB4/2 play a relevant role in FXS etiology, we demonstrate that inhibiting ErbB is a valuable pharmacological approach to attenuate stereotyped repetitive behaviors, thus opening an avenue toward innovative therapies for ASD and FXS treatment.

Emerging insights into the genetics and evolution of human same-sex sexual behavior

Thanks to twin studies, it has been known for decades that human same-sex sexual behavior (SSB) has a substantial heritable component. However, only recently have large genome-wide association studies (GWAS) begun to illuminate the complex genetics involved. These studies have established that SSB is influenced by many common genetic variants, each with tiny but cumulative effects. The evolutionary explanation for the persistence of genetic variants associated with SSB, despite their apparent fitness costs, remains uncertain. In this review, we synthesize advances in understanding the genetic and evolutionary bases of SSB, while identifying the many areas in which we still have much to learn.

DCC in the cerebral cortex is required for cognitive functions in mouse

Schizophrenia (SZ) is a highly heritable mental disorder, and genome-wide association studies have identified the association between deleted in colorectal cancer (DCC) and SZ. Previous study has shown a lowered expression of DCC in the cerebral cortex of SZ patient. In this study, we identified novel single nucleotide polymorphisms (SNPs) of DCC statistically correlated with SZ. Based on these, we generated DCC conditional knockout (CKO) mice and explored behavioral phenotypes in these mice. We observed that deletion of DCC in cortical layer VI but not layer V led to deficits in fear and spatial memory, as well as defective sensorimotor gating revealed by the prepulse inhibition test (PPI). Critically, the defective sensorimotor gating could be restored by olanzapine, an antipsychotic drug. Furthermore, we found that the levels of p-AKT and p-GSK3α/β were decreased, which was responsible for impaired PPI in the DCC-deficient mice. Finally, the DCC-deficient mice also displayed reduced spine density of pyramidal neurons and disturbed delta-oscillations. Our data, for the first time, identified and explored downstream substrates and signaling pathway of DCC which supports the hypothesis that DCC is a SZ-related risky gene and when defective, may promote SZ-like pathogenesis and behavioral phenotypes in mice.

The Relationship of glutamate signaling to cannabis use and schizophrenia

PURPOSE OF REVIEW

This review examines the literature associating cannabis with schizophrenia, glutamate dysregulation in schizophrenia, and cannabis involvement in glutamate pathways. Cannabis use is widespread among adolescents world-wide and is sold legally in many countries for recreational use in a variety of forms. Most people use it without lasting effects, but a portion of individuals have negative reactions that manifest in acute psychotic symptoms, and in some, symptoms continue even after the use of cannabis has ceased. To date, there is a huge gap in our understanding of why this occurs.

RECENT FINDINGS

Recent studies have focused on abnormalities in the glutamate pathway in schizophrenia, the effect of cannabis on the glutamate system, and the role of glutamate in the brain Default Mode Network.

SUMMARY

Given these observations, we hypothesize that perturbance of glutamate neuronal connectivity by cannabis in the brains of individuals genetically at high risk for psychosis will initiate a schizophrenia-like psychosis. Future studies may tie together these diverse observations by combining magnetic resonance spectroscopy (MRS) and functional magnetic resonance imaging (fMRI) of the default resting state network in patients with new onset schizophrenia who do and do not use cannabis compared with nonpsychotic individuals who do and do not use cannabis.

Fine-mapping in admixed populations using CARMA-X, with applications to Latin American studies

Genome-wide association studies (GWASs) in ancestrally diverse populations are rapidly expanding, opening up unique opportunities for novel gene discoveries and increased utility of genetic findings in non-European individuals. A popular technique to identify putative causal variants at GWAS loci is via statistical fine-mapping. Despite tremendous efforts, fine-mapping remains a very challenging task, even in the relatively simple scenario of studies with a single, homogeneous population. For studies with admixed individuals, such as within Latin America and the Caribbean, methods for gene discovery are still limited. Here, we propose a Bayesian model for fine-mapping in admixed populations, CARMA-X, that addresses some of the unique challenges of admixed individuals. The proposed method includes an estimation method for the linkage disequilibrium (LD) matrix that accounts for small reference panels for admixed individuals, heterogeneity across populations and cross-ancestry LD, and a Bayesian hypothesis test that leads to robust fine-mapping when relying on external reference panels of modest size for LD estimation. Using simulations, we compare performance with recently proposed fine-mapping methods for multi-ancestry studies and show that the proposed model provides higher power while controlling false discoveries, especially when using an out-of-sample LD matrix. We further illustrate our approach through applications to two Latin American genetic studies, the Estudio Familiar de Influencia Genética en Alzheimer (EFIGA) study in the Dominican Republic and the Mexican Biobank, where we show the benefit of modeling ancestry-specific effects by prioritizing putative causal variants and genes, including several findings driven by ancestry-specific effects in the African and Native American ancestries.

Exposome-Wide Gene-By-Environment Interaction Study of Psychotic Experiences in the UK Biobank

Background

A previous study successfully identified 148 of 23,098 exposures associated with any psychotic experiences (PEs) in the UK Biobank using an exposome-wide association study (XWAS). Furthermore, research has shown that the polygenic risk score for schizophrenia (PRS-SCZ) is associated with PEs. However, the interaction of these exposures with PRS-SCZ remains unknown.

Method

To systematically investigate possible gene-by-environment interactions underlying PEs through data-driven agnostic analyses, we conducted 1) conditional XWAS adjusting for PRS-SCZ to estimate the main effects of the exposures and of PRS-SCZ, 2) exposome-wide interaction study (XWIS) to estimate multiplicative and additive interactions between PRS-SCZ and exposures, and 3) correlation analyses between PRS-SCZ and exposures. The study included 148,502 participants from the UK Biobank.

Results

In the conditional XWAS models, significant effects of PRS-SCZ and 148 exposures on PEs remained statistically significant. In the XWIS model, we found significant multiplicative (multiplicative scale, 1.23; 95% CI, 1.10-1.37; p = 4.0 × 10-4) and additive (relative excess risk due to interaction, 0.55; 95% CI, 0.32-0.77; synergy index, 0.22; 95% CI, 0.14-0.30; and attributable proportion, 1.59; 95% CI, 1.30-1.91; all ps < .05/148) interactions of PRS-SCZ and the variable serious medical conditions/disability with PEs. We additionally identified 6 additive gene-by-environment interactions for mental distress, help-/treatment-seeking behaviors (3 variables), sadness, and sleep problems. In the correlation test focused on 7 exposures that exhibited significant interactions with PRS-SCZ, nonsignificant or small (r < 0.04) gene-by-environment correlations were observed.

Conclusions

These findings reveal evidence for gene-by-environment interactions underlying PEs and suggest that intertwined pathways of genetic vulnerability and exposures may contribute to psychosis risk.

The effect of fampridine on working memory: a randomized controlled trial based on a genome-guided repurposing approach

Working memory (WM), a key component of cognitive functions, is often impaired in psychiatric disorders such as schizophrenia. Through a genome-guided drug repurposing approach, we identified fampridine, a potassium channel blocker used to improve walking in multiple sclerosis, as a candidate for modulating WM. In a subsequent double-blind, randomized, placebo-controlled, crossover trial in 43 healthy young adults (ClinicalTrials.gov, NCT04652557), we assessed fampridine's impact on WM (3-back d-prime, primary outcome) after 3.5 days of repeated administration (10 mg twice daily). Independently of baseline cognitive performance, no significant main effect was observed (Wilcoxon P = 0.87, r = 0.026). However, lower baseline performance was associated with higher working memory performance after repeated intake of fampridine compared to placebo (rs = -0.37, P = 0.014, n = 43). Additionally, repeated intake of fampridine lowered resting motor threshold (F(1,37) = 5.31, P = 0.027, R2β = 0.01), the non-behavioral secondary outcome, indicating increased cortical excitability linked to cognitive function. Fampridine's capacity to enhance WM in low-performing individuals and to increase brain excitability points to its potential value for treating WM deficits.

Circulating Blood-Based Proteins in Psychopathology and Cognition: A Mendelian Randomization Study

Importance

Peripheral (blood-based) biomarkers for psychiatric illness could benefit diagnosis and treatment, but research to date has typically been low throughput, and traditional case-control studies are subject to potential confounds of treatment and other exposures. Large-scale 2-sample mendelian randomization (MR) can examine the potentially causal impact of circulating proteins on neuropsychiatric phenotypes without these confounds.

Objective

To identify circulating proteins associated with risk for schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) as well as cognitive task performance (CTP).

Design, Setting, and Participants

In a 2-sample MR design, significant proteomic quantitative trait loci were used as candidate instruments, obtained from 2 large-scale plasma proteomics datasets: the UK Biobank Pharma Proteomics Project (2923 proteins per 34 557 UK individuals) and deCODE Genetics (4719 proteins per 35 559 Icelandic individuals). Data analysis was performed from November 2023 to November 2024.

Exposure

Genetic influence on circulating levels of proteins in plasma.

Main Outcomes and Measures

Outcome measures were summary statistics drawn from recent large-scale genome-wide association studies for SCZ (67 323 cases and 93 456 controls), BD (40 463 cases and 313 436 controls), MDD (166 773 cases and 507 679 controls), and CTP (215 333 individuals). MR was carried out for each phenotype, and proteins that showed statistically significant (Bonferroni-corrected P < .05) associations from MR analysis were used for pathway, protein-protein interaction, drug target enrichment, and potential druggability analysis for each outcome phenotype separately.

Results

MR analysis revealed 113 Bonferroni-corrected associations (46 novel) involving 91 proteins across the 4 outcome phenotypes. Immune-related proteins, such as interleukins and complement factors, showed pleiotropic effects across multiple outcome phenotypes. Drug target enrichment analysis provided support for repurposing of anti-inflammatory agents for SCZ, amantadine for BD, retinoic acid for MDD, and duloxetine for CTP.

Conclusions and Relevance

Identifying potentially causal effects of circulating proteins on neuropsychiatric phenotypes suggests potential biomarkers and offers insights for the development of innovative therapeutic strategies. The study also reveals pleiotropic effects of many proteins across different phenotypes, indicating shared etiology among serious psychiatric conditions and cognition.

A Hidden Mark of a Troubled Past: Neuroimaging and Transcriptomic Analyses Reveal Interactive Effects of Maternal Immune Activation and Adolescent THC Exposure Suggestive of Increased Neuropsychiatric Risk

Background

Maternal exposure to infections during gestation has been shown to predispose individuals to neuropsychiatric disorders. Additionally, clinical data suggest that cannabis use may trigger the onset of schizophrenia in vulnerable individuals. However, the direction of causality remains unclear.

Methods

To elucidate this issue, we utilized a rat model of maternal immune activation combined with exposure to increasing doses of Δ9-tetrahydrocannabinol during adolescence in both male and female rats. We investigated several behaviors in adulthood relevant for neuropsychiatric disorders, including impairments in working memory, deficits in sensorimotor gating, alterations in social behavior, anhedonia, and potential changes in implicit learning (conditioned taste aversion). Furthermore, we conducted a longitudinal positron emission tomography study to target affected brain regions and, subsequently, collected brain samples of one such region (the orbitofrontal cortex) for RNA sequencing analyses, which were also performed on peripheral blood mononuclear cells to identify peripheral biomarkers.

Results

While adolescent Δ9-tetrahydrocannabinol did not unmask latent behavioral disruptions, positron emission tomography scans revealed several brain alterations dependent on the combination of both hits. Additionally, the transcriptomic studies demonstrated that maternal immune activation affected dopaminergic, glutamatergic, and serotoninergic genes, with the combination of both exposures in most cases shifting the expression from downregulation to upregulation. In peripheral cells, interactive effects were observed on inflammatory pathways, and some genes were proposed as biomarkers.

Conclusions

These results suggest that the combination of these 2 vulnerability factors leaves a lasting mark on the body, potentially predisposing individuals to neuropsychiatric disorders even before behavioral alterations manifest.

Brain-based gene expression and corresponding behavioural relevance of risk genes for broad antisocial behaviour

Antisocial behaviour (ASB) involves persistent irresponsible, delinquent activities violating rights and safety of others. A meta-analysis of genome-wide association studies revealed significant genetic associations with ASB, yet their brain expression patterns and behavioural relevance remain unclear. Our investigation of fifteen genes associated with ASB examined their biological role and distribution across tissues, integrating post-mortem brain sample data from the Allen-Human-Brain Atlas and the Genotype-Tissue Expression project. We found that these genes were differentially expressed in the brain, particularly in regions like the cerebellum, putamen, and caudate, and were notably downregulated in the pancreas. Single cell type expression analysis revealed that ASB-associated genes had strong correlations with ductal and endothelial cells in the pancreas, indicating a possible metabolic influence on ASB. Certain genes like NTN1, SMAD5, NCAM2, and CDC42EP3 displayed specificity for cognitive terms including chronic pain, heart rate, and aphasia. These expression patterns aligned with neurocognitive domains related to thinking, and learning, distress, motor skills, as determined by fMRI analysis. This study connects specific brain gene expression with potential genetic and metabolic factors in ASB, offering novel insights into its biological basis and possible interdisciplinary approaches to understanding and addressing aggressive behaviours.

Blunted cortisol as a biomarker of depression based on the attenuation hypothesis: A Mendelian randomization analysis using depression as exposure

BACKGROUND

Both elevated and blunted cortisol responses have been associated with depression. Previous Mendelian randomization (MR) studies have largely ruled out cortisol as a cause of depression. Based on the attenuation hypothesis, this MR study used depression as exposure to assess whether cortisol might be a consequence and therefore a biomarker of depression.

METHODS

Strong (P < 5 × 10-8) and independent (r2 < 0.001) single nucleotide polymorphisms (SNPs) associated with broadly defined depression (294,322 cases, 741,438 controls) were used as instruments. These were applied to genetic associations with morning, fasting, and random plasma cortisol in the CORtisol NETwork (CORNET) consortium (n = 25,314), METabolic Syndrome in Men (METSIM) study (n = 6667), and Canadian Longitudinal Study on Aging (CLSA) cohort (n = 8299). Multivariable MR, adjusting for childhood maltreatment and major mental disorders, was conducted to address potential horizontal pleiotropy from dichotomous depression. Instruments were also selected by evidence of colocalization with major depressive disorder to address non-specificity.

RESULTS

Using 133 SNPs as instruments, depression was inversely associated with morning plasma cortisol (β per log-odds of genetic liability to depression = -0.107 [95 % CI, -0.181 to -0.032]) in the CORNET consortium. Replication in the METSIM study (β = -0.203 [95 % CI, -0.367 to -0.040]) and CLSA cohort (β = -0.091 [95 % CI, -0.220 to 0.039]) showed consistent but not always significant associations. Multivariable MR and follow-up analysis incorporating colocalization supported these findings.

CONCLUSIONS

Consistent with the attenuation hypothesis, blunted cortisol response appeared to be a consequence and potentially a biomarker of depression. Future studies are needed to provide more interpretable effect sizes and validate other biomarker measures.

Schizophrenia genetic risk and labour market outcomes in the Finnish general population: Are schizophrenia-related traits penalised or rewarded?

BACKGROUND

Schizophrenia polygenic risk scores (SCZPRS) have been linked to cognitive functioning, creativity, behavioural traits, and psychiatric conditions beyond schizophrenia. This study examines how labour market segments reward or penalise traits associated with SCZPRS in the general population.

METHODS

We merged genetic, socio-economic and health registry data with repeated cross-sectional survey data from six Finnish cohorts (1992 to 2017), representing individuals aged 25-64 across Finnish regions (N = 20,121). Various regression models were employed to study labour market outcomes.

RESULTS

Individuals in the highest SCZPRS quintile were 6.4 percentage points less likely to be employed than those in the lowest quintile (P < 0.001; 99.5 % CI: 3.9-9.0 pp). Among employed individuals in knowledge-based occupations, an inverse U-shaped relationship between SCZPRS and income emerged after 2000. Knowledge workers in both the lowest (P = 0.004) and highest (P = 0.03) SCZPRS quintiles were 4-5 percentage points less likely to be in the highest income tertile than those in the middle quintile. No significant association was found between SCZPRS and income in physical labour.

CONCLUSIONS

Beyond its overall negative association with employment, SCZPRS exhibits a non-linear relationship with income in cognitive-intensive occupations, where both low and high SCZPRS appear to be penalised. This pattern became more pronounced post-2000, coinciding with rising income inequality and technological advancements, likely reshaping labour market demands. While effect sizes are substantial, compensatory factors may mitigate these outcomes. Greater awareness of these associations and individual differences in labour market experiences could contribute to a more inclusive society.

Immunological drivers and potential novel drug targets for major psychiatric, neurodevelopmental, and neurodegenerative conditions

Immune dysfunction is implicated in the aetiology of psychiatric, neurodevelopmental, and neurodegenerative conditions, but the issue of causality remains unclear impeding attempts to develop new interventions. Using genomic data on protein and gene expression across blood and brain, we assessed evidence of a potential causal role for 736 immune response-related biomarkers on 7 neuropsychiatric conditions by applying Mendelian randomization (MR) and genetic colocalisation analyses. A systematic three-tier approach, grouping biomarkers based on increasingly stringent criteria, was used to appraise evidence of causality (passing MR sensitivity analyses, colocalisation, False Discovery Rate and Bonferroni thresholds). We provide evidence for a potential causal role of 29 biomarkers for 7 conditions. The identified biomarkers suggest a role of both brain specific and systemic immune response in the aetiology of schizophrenia, Alzheimer's disease, depression, and bipolar disorder. Of the identified biomarkers, 20 are therapeutically tractable, including ACE, TNFRSF17, SERPING1, AGER and CD40, with drugs currently approved or in advanced clinical trials. Based on the largest available selection of plasma immune-response related biomarkers, our study provides insight into possible influential biomarkers for the aetiology of neuropsychiatric conditions. These genetically prioritised biomarkers now require examination to further evaluate causality, their role in the aetiological mechanisms underlying the conditions, and therapeutic potential.

CHAS infers cell type-specific signatures in bulk brain histone acetylation studies of neurological and psychiatric disorders

Epigenomic profiling of the brain has largely been done on bulk tissues, limiting our understanding of cell type-specific epigenetic changes in disease states. Here, we introduce cell type-specific histone acetylation score (CHAS), a computational tool for inferring cell type-specific signatures in bulk brain H3K27ac profiles. We applied CHAS to >300 H3K27ac chromatin immunoprecipitation sequencing samples from studies of Alzheimer's disease, Parkinson's disease, autism spectrum disorder, schizophrenia, and bipolar disorder in bulk postmortem brain tissue. In addition to recapitulating known disease-associated shifts in cellular proportions, we identified cell type-specific biological insights into brain-disorder-associated regulatory variation. In most cases, genetic risk and epigenetic dysregulation targeted different cell types, suggesting independent mechanisms. For instance, genetic risk of Alzheimer's disease was exclusively enriched within microglia, while epigenetic dysregulation predominantly fell within oligodendrocyte-specific H3K27ac regions. In addition, reanalysis of the original datasets using CHAS enabled identification of biological pathways associated with each neurological and psychiatric disorder at cellular resolution.

Topoisomerase 3b facilitates piRNA biogenesis to promote transposon silencing and germ cell development

Topoisomerases typically function in the nucleus to relieve topological stress in DNA. Here, we show that a dual-activity topoisomerase, Top3b, and its partner, TDRD3, largely localize in the cytoplasm and interact biochemically and genetically with PIWI-interacting RNA (piRNA) processing enzymes to promote piRNA biogenesis, post-transcriptional gene silencing (PTGS) of transposons, and Drosophila germ cell development. Top3b requires its topoisomerase activity to promote PTGS of a transposon reporter and preferentially silences long and highly expressed transposons, suggesting that RNAs with these features may produce more topological stress for topoisomerases to solve. The double mutants between Top3b and piRNA processing enzymes exhibit stronger disruption of the signatures and levels of germline piRNAs, more de-silenced transposons, and larger defects in germ cells than either single mutant. Our data suggest that Top3b can act in an RNA-based process-piRNA biogenesis and PTGS of transposons-and this function is required for Top3b to promote normal germ cell function.

Exon-variant interplay and multi-modal evidence identify endocrine dysregulation in severe psychiatric disorders impacting excitatory neurons

Bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia share genetic architecture, yet their molecular mechanisms remain elusive. Both common and rare genetic variants contribute to neural dysfunction, impacting cognition and behavior. This study investigates the molecular effects of genetic variants on human cortical single-cell types using a single-exon analysis approach. Integrating exon-level eQTLs (common variants influencing exon expression) and joint exon eQT-Scores (combining polygenic risk scores with exon-level gene expression) from a postmortem psychiatric cohort (BD = 15, MDD = 24, schizophrenia = 68, controls = 62) with schizophrenia-focused rare variant data from the SCHEMA consortium, we identified 110 core genes enriched in pathways including circadian entrainment (FDR = 0.02), cortisol synthesis and secretion (FDR = 0.026), and dopaminergic synapse (FDR = 0.038). Additional enriched pathways included hormone signaling (FDRs < 0.0298, including insulin, GnRH, aldosterone, and growth hormone pathways) and, notably, adrenergic signaling in cardiomyocytes (FDR = 0.0028). These pathways highlight shared molecular mechanisms in the three disorders. Single-nuclei RNA sequencing data from three cortical regions revealed that these core set genes are predominantly expressed in excitatory neuron layers 2-6 of the dorsolateral prefrontal cortex, linking molecular changes to cell types involved in cognitive dysfunction. Our results demonstrate the power of integrating multimodal genetic and transcriptomic data at the exon level. This approach moves beyond symptom-based diagnoses toward molecular classifications, identifying potential therapeutic targets for psychiatric disorders.

HORNET: tools to find genes with causal evidence and their regulatory networks using eQTLs

Motivation

Nearly two decades of genome-wide association studies (GWAS) have identify thousands of disease-associated genetic variants, but very few genes with evidence of causality. Recent methodological advances demonstrate that Mendelian randomization (MR) using expression quantitative loci (eQTLs) as instrumental variables can detect potential causal genes. However, existing MR approaches are not well suited to handle the complexity of eQTL GWAS data structure and so they are subject to bias, inflation, and incorrect inference.

Results

We present a whole-genome regulatory network analysis tool (HORNET), which is a comprehensive set of statistical and computational tools to perform genome-wide searches for causal genes using summary level GWAS data, i.e. robust to biases from multiple sources. Applying HORNET to schizophrenia, eQTL effects in the cerebellum were spread throughout the genome, and in the cortex were more localized to select loci.

Availability and implementation

Freely available at https://github.com/noahlorinczcomi/HORNET or Mac, Windows, and Linux users.

Epigenetic and genetic profiling of comorbidity patterns among substance dependence diagnoses

This study investigated the genetic and epigenetic mechanisms underlying the comorbidity of five substance dependence diagnoses (SDs; alcohol, AD; cannabis, CaD; cocaine, CoD; opioid, OD; tobacco, TD). A latent class analysis (LCA) was performed on 22,668 individuals from six cohorts to identify comorbid DSM-IV SD patterns. In subsets of this sample, we tested SD-latent classes with respect to polygenic overlap of psychiatric and psychosocial traits in 7659 individuals of European descent and epigenome-wide changes in 886 individuals of African, European, and Admixed-American descents. The LCA identified four latent classes related to SD comorbidities: AD + TD, CoD + TD, AD + CoD + OD + TD (i.e., polysubstance addiction, PSU), and TD. In the epigenome-wide association analysis, SPATA4 cg02833127 was associated with CoD + TD, AD + TD, and PSU latent classes. AD + TD latent class was also associated with CpG sites located on ARID1B, NOTCH1, SERTAD4, and SIN3B, while additional epigenome-wide significant associations with CoD + TD latent class were observed in ANO6 and MOV10 genes. PSU-latent class was also associated with a differentially methylated region in LDB1. We also observed shared polygenic score (PGS) associations for PSU, AD + TD, and CoD + TD latent classes (i.e., attention-deficit hyperactivity disorder, anxiety, educational attainment, and schizophrenia PGS). In contrast, TD-latent class was exclusively associated with posttraumatic stress disorder-PGS. Other specific associations were observed for PSU-latent class (subjective wellbeing-PGS and neuroticism-PGS) and AD + TD-latent class (bipolar disorder-PGS). In conclusion, we identified shared and unique genetic and epigenetic mechanisms underlying SD comorbidity patterns. These findings highlight the importance of modeling the co-occurrence of SD diagnoses when investigating the molecular basis of addiction-related traits.

Abnormal eye movement, brain regional homogeneity in schizophrenia and clinical high-risk individuals and their associated gene expression profiles

Clinical high-risk (CHR) is a prodromal period before psychosis characterized by attenuated, transient, or intermittent psychotic symptoms and declining functioning. They exhibit eye movement abnormalities and brain functional damage compared with schizophrenia, potentially increasing vulnerability to psychosis. This study investigates eye movement dysfunction and brain activity alterations in CHR and first-episode schizophrenia (FSZ) individuals to identify early biomarkers for psychosis progression. Twenty-seven drug-naïve FSZ, 25 CHR, and 28 healthy controls (HCs) were recruited for eye-tracking tasks and resting-state functional magnetic resonance imaging to evaluate eye movement and regional homogeneity (ReHo) differences. Machine-learning algorithms were used to differentiate FSZ from CHR. In combination with the Allen Human Brain Atlas (AHBA), transcriptome-neuroimaging analysis was applied to identify ReHo-related gene expression profiles. FSZ exhibited a wide range of eye movement abnormalities across multiple tasks, while certain abnormalities were already present in CHR. Abnormal ReHo alterations were found in orbitofrontal gyrus, temporal gyrus, and cingulum among three groups, associated with specific eye movement parameters. These differences in eye movement and ReHo allowed for high-accuracy discrimination between them. Genetic analysis identified significant genes in FSZ and CHR, enriched in various biological functions and pathways (all corrected p < 0.05). FSZ and CHR exhibited different eye movement and ReHo patterns, indicating potential as early biomarkers. Our findings reveal correlations between these ReHo patterns and gene expression profiles using AHBA database, shedding light on possible genetic mechanisms underlying brain function in FSZ and CHR.

Identification of genetic architecture shared between schizophrenia and Alzheimer's disease

Both schizophrenia (SCZ) and Alzheimer's disease (AD) are highly heritable brain disorders. Despite of the observed comorbidity and shared psychosis and cognitive decline between the two disorders, the genetic risk architecture shared by SCZ and AD remains largely unknown. Based on summary statistics of the currently available largest genome-wide association studies for SCZ (n = 130,644) and AD (n = 455,258) in individuals of European ancestry, we conducted conditional/conjunctional false discovery rate (FDR) analysis to enhance the statistical power for discovering more genetic associations with SCZ or AD and to detect the common genetic variants shared by both disorders. We found shared genetic architecture in SCZ conditioned on AD and vice versa across different levels of significance, indicating polygenic overlap. We found 268 (78 novel) SCZ-only and 125 (55 novel) AD-only SNPs at conditional FDR < 0.01, and 16 lead SNPs shared by SCZ and AD at conjunctional FDR < 0.05. Only half of the shared SNPs showed concordant effect direction, which was consistent with the modest genetic correlation (r = 0.097; P = 0.026) between the two disorders. This study provides evidence for polygenic overlap between SCZ and AD, suggesting the existence of the shared molecular genetic mechanisms, which may inform therapeutic targets that are applicable for both disorders.

Integrated multi-omic characterizations of the synapse reveal RNA processing factors and ubiquitin ligases associated with neurodevelopmental disorders

The molecular composition of the excitatory synapse is incompletely defined due to its dynamic nature across developmental stages and neuronal populations. To address this gap, we apply proteomic mass spectrometry to characterize the synapse in multiple biological models, including the fetal human brain and human induced pluripotent stem cell (hiPSC)-derived neurons. To prioritize the identified proteins, we develop an orthogonal multi-omic screen of genomic, transcriptomic, interactomic, and structural data. This data-driven framework identifies proteins with key molecular features intrinsic to the synapse, including characteristic patterns of biophysical interactions and cross-tissue expression. The multi-omic analysis captures synaptic proteins across developmental stages and experimental systems, including 493 synaptic candidates supported by proteomics. We further investigate three such proteins that are associated with neurodevelopmental disorders-Cullin 3 (CUL3), DEAD-box helicase 3 X-linked (DDX3X), and Y-box binding protein-1 (YBX1)-by mapping their networks of physically interacting synapse proteins or transcripts. Our study demonstrates the potential of an integrated multi-omic approach to more comprehensively resolve the synaptic architecture.

Altered volume of thalamic nuclei and genetic expression in first-episode psychotic patients, and their association with childhood adversity

Childhood maltreatment is a significant risk factor for schizophrenia, and there are correlations between these adversities and thalamic gray matter density. The thalamus, a subcortical structure with various nuclei with specific connections, relays sensory information and participates in higher cognitive processes. Thalamic alterations are evident in psychotic disorders, and early-life adversities may affect its development, potentially contributing to psychosis. However, no evidence exists of volumetric alterations in thalamic nuclei in first-episode psychosis (FEP) patients related to early traumatic events. This study recruited 70 FEP patients and 68 age-matched healthy controls, who underwent 3 T structural MRI and clinical scales, including the Childhood Trauma Questionnaire (CTQ). The thalamus was analyzed for shape and segmented into nuclei to assess volume. Additionally, peripheral blood was analyzed for the expression of VCAN, CSGALNACT1, ST8SIA4, NRGN, SP4, and TOX genes, which are related to neuronal plasticity in the thalamus and psychosis. Results showed volumetric reductions in the whole thalamus and specific nuclei (lateral posterior, lateral geniculate, medial geniculate, ventrolateral, centromedian, anteroventral, mediodorsal, and pulvinar). The thalamus did not show shape alterations. A significant association was observed between physical neglect during childhood and the volume of the left thalamus and its anteroventral nucleus. Reduced expression of ST8SIA4 and SP4 genes was detected in FEP patients compared to healthy controls, with correlations between thalamic nuclei volumes and gene expression differing between groups. In conclusion, this study links thalamic nuclei volume with childhood adversities in FEP and highlights changes in ST8SIA4 and SP4 expression, correlating with thalamic nuclei volumes.

White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life

Advanced diffusion magnetic resonance imaging (dMRI) allows one to probe and assess brain white matter (WM) organisation and microstructure in vivo. Various dMRI models with different theoretical and practical assumptions have been developed, representing partly overlapping characteristics of the underlying brain biology with potentially complementary value in the cognitive and clinical neurosciences. To which degree the different dMRI metrics relate to clinically relevant geno- and phenotypes is still debated. Hence, we investigate how tract-based and whole WM skeleton parameters from different dMRI approaches associate with clinically relevant and white matter-related phenotypes (sex, age, pulse pressure (PP), body-mass-index (BMI), brain asymmetry) and genetic markers in the UK Biobank (UKB, n=52,140) and the Adolescent Brain Cognitive Development (ABCD) Study (n=5,844). In general, none of the imaging approaches could explain all examined phenotypes, though the approaches were overall similar in explaining variability of the examined phenotypes. Nevertheless, particular diffusion parameters of the used dMRI approaches stood out in explaining some important phenotypes known to correlate with general human health outcomes. A multi-compartment Bayesian dMRI approach provided the strongest WM associations with age, and together with diffusion tensor imaging, the largest accuracy for sex-classifications. We find a similar pattern of metric and tract-dependent asymmetries across datasets, with stronger asymmetries in ABCD data. The magnitude of WM associations with polygenic scores as well as PP depended more on the sample, and likely age, than dMRI metrics. However, kurtosis was most indicative of BMI and potentially of bipolar disorder polygenic scores. We conclude that WM microstructure is differentially associated with clinically relevant pheno- and genotypes at different points in life.

Refining Criteria for a Neurodevelopmental Subphenotype of Bipolar Disorders: A FondaMental Advanced Centers of Expertise for Bipolar Disorders Study

BACKGROUND

Bipolar disorder (BD) is a complex and heterogeneous psychiatric disorder. It has been suggested that neurodevelopmental factors contribute to the etiology of BD, but a specific neurodevelopmental phenotype (NDP) of the disorder has not been identified. Our objective was to define and characterize an NDP in BD and validate its associations with clinical outcomes, polygenic risk scores, and treatment responses.

METHODS

We analyzed the FondaMental Advanced Centers of Expertise for Bipolar Disorders cohort of 4468 patients with BD, a validation cohort of 101 patients with BD, and 2 independent replication datasets of 274 and 89 patients with BD. Using factor analyses, we identified a set of criteria for defining NDP. Next, we developed a scoring system for NDP load and assessed its association with prognosis, neurological soft signs, polygenic risk scores for neurodevelopmental disorders, and responses to treatment using multiple regressions, adjusted for age and gender with bootstrap replications.

RESULTS

Our study established an NDP in BD consisting of 9 clinical features: advanced paternal age, advanced maternal age, childhood maltreatment, attention-deficit/hyperactivity disorder, early onset of BD, early onset of substance use disorders, early onset of anxiety disorders, early onset of eating disorders, and specific learning disorders. Patients with higher NDP load showed a worse prognosis and increased neurological soft signs. Notably, these individuals exhibited a poorer response to lithium treatment. Furthermore, a significant positive correlation was observed between NDP load and polygenic risk score for attention-deficit/hyperactivity disorder, suggesting potential overlapping genetic factors or pathophysiological mechanisms between BD and attention-deficit/hyperactivity disorder.

CONCLUSIONS

The proposed NDP constitutes a promising clinical tool for patient stratification in BD.

Cross-Sectional Brain Age Assessments Are Limited in Predicting Future Brain Change

The concept of brain age (BA) describes an integrative imaging marker of brain health, often suggested to reflect aging processes. However, the degree to which cross-sectional MRI features, including BA, reflect past, ongoing, and future brain changes across different tissue types from macro- to microstructure remains controversial. Here, we use multimodal imaging data of 39,325 UK Biobank participants, aged 44-82 years at baseline and 2,520 follow-ups within 1.12-6.90 years to examine BA changes and their relationship to anatomical brain changes. We find insufficient evidence to conclude that BA reflects the rate of brain aging. However, modality-specific differences in brain ages reflect the state of the brain, highlighting diffusion and multimodal MRI brain age as potentially useful cross-sectional markers.

Sleep and schizophrenia polygenic scores in non-affective and affective psychotic disorders

BACKGROUND

Sleep problems are common in psychotic disorders and are associated with worse quality of life and disease prognosis. Genome-wide association studies (GWAS) have revealed genetic influences for schizophrenia and sleep, but polygenic scores (PGSs) for sleep traits have not been evaluated systematically in patients with psychotic disorders.

METHODS

This study investigated the associations between PGSs for sleep traits (insomnia, PGSINS; sleep duration, PGSSD; short sleep duration, PGSSS; long sleep duration; PGSLS), diurnal preference (eveningness, PGSME), and schizophrenia (PGSSZ) with clinical features of psychotic disorders in the Finnish SUPER study comprising 8,232 patients with psychotic disorders. The measures included self-reported sleep and well-being, cognitive assessments, clozapine use, and functional outcomes. Using FinnGen data of 356,077 individuals, we analyzed the distributions of PGSs in psychotic and bipolar disorders and the general population.

RESULTS

PGSINS associated with more sleep problems and worse well-being (e.g. worse health-related quality of life [β = -0.07, CI = -0.09, -0.05, p < .001]). High PGSSZ is associated with better sleep quality, worse clinical outcomes, and performance in cognitive tests (e.g. more errors in paired-associated learning [β = 0.07, CI = 0.04, 0.09, p < .001]). PGSINS was higher in affective psychotic and bipolar disorders, while PGSSD and PGSME were higher in schizophrenia as compared with individuals with no psychiatric disorders.

CONCLUSION

Genetic risks for sleep and diurnal preference vary between non-affective psychosis, affective psychosis, and the general population. The findings in this study emphasize the heterogeneity in genetic etiology of the objective features of disease severity and the more subjective measures related to well-being and self-reported measures of sleep.

Polygenic risk scores in relation to suicidality among youth with or at risk for bipolar disorder

PURPOSE

The risk of suicide among individuals with bipolar disorder (BD) is among the highest of all psychiatric disorders. The etiology of suicidality is complex and multifactorial, with genetic factors playing a prominent role according to twin-, family-, and molecular genetic studies. This study examines polygenic risk scores from adult studies in relation to suicidality in youth with or at risk for BD.

METHODS

Primary analyses examined the association of polygenic risk scores for suicide attempt, based on adult genome-wide association study data, with suicidal ideation, self-harm, and suicide attempt in 232 youth (mean age 16.7 years), including 125 with, and 107 at high-risk for, BD. We also tested polygenic risk scores for risk tolerance, schizophrenia, major depressive disorder, BD, and attention-deficit hyperactivity disorder in secondary analyses.

RESULTS

Polygenic risk scores for suicide attempt were not significantly associated with suicidal ideation, self-harm, or suicide attempt. Higher polygenic risk scores for major depressive disorder were nominally associated with increased risk of suicidal ideation in the overall sample (beta = 0.36, se(beta) = 0.16, p = 0.017), controlling for covariates.

IMPLICATIONS

Our finding that polygenic risk for depression is associated with suicidal ideation converges with prior findings in youth and adults. While present findings are constrained by sample size, they underscore the importance of undertaking genome-wide association studies in youth, rather than relying solely on prior adult genome-wide association studies.

Polygenic overlap between subjective well-being and psychiatric disorders and cross-ancestry validation

Subjective well-being (SWB) is important for understanding human behaviour and health. Although the connection between SWB and psychiatric disorders has been studied, common genetic mechanisms remain unclear. This study aimed to explore the genetic relationship between SWB and psychiatric disorders. Bivariate causal mixture modelling (MiXeR), polygenic risk score (PRS) and Mendelian randomization (MR) analyses showed substantial polygenic overlap and associations between SWB and the psychiatric disorders. Subsequent replication studies in East Asian populations confirmed the polygenic overlap between schizophrenia and SWB. The conditional and conjunctional false discovery rate analyses identified additional or shared genetic loci associated with SWB or psychiatric disorders. Functional annotation revealed enrichment of specific brain tissues and genes associated with SWB. The identified genetic loci showed cross-ancestry transferability between the European and Korean populations. Our findings provide valuable insights into the common genetic mechanisms underlying SWB and psychiatric disorders.

Local patterns of genetic sharing between neuropsychiatric and insulin resistance-related conditions

The co-occurrence of insulin resistance (IR)-related metabolic conditions with neuropsychiatric disorders is a major public health challenge. Evidence of the genetic links between these phenotypes is emerging, but little is currently known about the genomic regions and biological functions that are involved. To address this, we performed Local Analysis of [co]Variant Association (LAVA) using large-scale (N = 9,725-933,970) genome-wide association studies (GWASs) results for three IR-related conditions (type 2 diabetes mellitus, obesity, and metabolic syndrome) and nine neuropsychiatric disorders. Subsequently, positional and expression quantitative trait locus (eQTL)-based gene mapping and downstream functional genomic analyses were performed on the significant loci. Patterns of negative and positive local genetic correlations (|rg| = 0.21-1, pFDR < 0.05) were identified at 109 unique genomic regions across all phenotype pairs. Local correlations emerged even in the absence of global genetic correlations between IR-related conditions and Alzheimer's disease, bipolar disorder, and Tourette's syndrome. Genes mapped to the correlated regions showed enrichment in biological pathways integral to immune-inflammatory function, vesicle trafficking, insulin signalling, oxygen transport, and lipid metabolism. Colocalisation analyses further prioritised 10 genetically correlated regions for likely harbouring shared causal variants, displaying high deleterious or regulatory potential. These variants were found within or in close proximity to genes, such as SLC39A8 and HLA-DRB1, that can be targeted by supplements and already known drugs, including omega-3/6 fatty acids, immunomodulatory, antihypertensive, and cholesterol-lowering drugs. Overall, our findings highlight the complex genetic architecture of IR-neuropsychiatric multimorbidity, advocating for an integrated disease model and offering novel insights for research and treatment strategies in this domain.

Association between mental disorders and trigeminal neuralgia: a cohort study and Mendelian randomization analysis

BACKGROUND

Clinical observational evidence suggests a close association between Trigeminal Neuralgia (TN) and Mental disorders (MDs). However, the causal relationship between the two remains unclear. This study aims to observe and analyse the associations between depression, anxiety, insomnia, and TN through clinical research. It also employs Mendelian randomization (MR) analysis to verify the potential genetic correlation between TN and various mental disorders. offering new insights for the diagnosis, prevention, and intervention strategies for TN.

METHODS

In the cohort study section, clinical data were collected from 154 patients with TN, all of whom were excluded from preoperative use of psychotropic drugs such as carbamazepine. The PHQ-9, GAD-7, and ISI scales were used to assess preoperative symptoms of depression, anxiety, and insomnia. Multivariable linear regression models were used to identify factors associated with questionnaire scores, with model performance evaluated by adjusted R², AIC, BIC, and p-values. Patients with significant positive symptoms preoperatively were followed up one-year after surgery, and non-parametric tests were employed to examine changes in mental disorder symptoms after pain relief. In MR analysis section, the main MR analysis methods include Inverse Variance Weighted (IVW), MR Egger, Weighted Median, Simple Mode, and Weighted Mode. The Benjamini-Hochberg (BH) method was used to adjust the p -values ​​and control the false discovery rate (FDR). Subsequent sensitivity analyses involved Cochran's Q test, MR-Egger regression intercept, MR-pleiotropy residual sum and outlier test (MR-PRESSO).

RESULTS

Multiple linear regression analyses revealed that longer disease duration and greater involvement of trigeminal branches were consistently associated with higher PHQ-9, GAD-7, and ISI scores, while demographic factors and baseline BNI scores showed no significant predictive value. MR analysis indicated that autism (OR = 0.697, 95% CI [0.494-0.982], P = 0.039), schizophrenia (OR = 0.910, 95% CI [0.831-0.997], P = 0.042), and ADHD combined with OCD (OR = 0.175, 95% CI [0.044-0.693], P = 0.013) reduced the risk of TN. Conversely, bipolar disorder (OR = 1.249, 95% CI [1.016-1.535], P = 0.034), depression (OR = 2.375, 95% CI [1.043-5.409], P = 0.039), anxiety (OR = 1.174, 95% CI [1.008-1.368], P = 0.039), and insomnia (OR = 2.036, 95% CI [1.074-3.861], P = 0.029)increased the risk of TN. TN also elevated the risk of anxiety (OR = 1.43, 95% CI [1.04-1.96], P = 0.034), depression (OR = 1.00305, 95% CI [1.00036-1.00549], P = 0.013), and insomnia (OR = 1.00918, 95% CI [1.00236-1.01605], P = 0.008).

CONCLUSIONS

Longer disease duration and broader trigeminal nerve involvement were independently associated with increased severity of depressive, anxiety, and insomnia symptoms, highlighting the importance of early clinical intervention in patients with TN. And results of MR analysis provide evidence supporting a causal relationship between MDs and TN. In contrast to the traditional view that pain causes mood changes such as anxiety and depression, a variety of MDs such as anxiety, depression, and insomnia also alter the risk of developing TN.

Exploring the bidirectional causal relationship between Autism Spectrum Disorder and Schizophrenia using Mendelian randomization

Autism Spectrum Disorder (ASD), characterized mainly by stereotyped behaviors and social impairments, affects about one in 100 children worldwide. Schizophrenia (SCZ), a chronic mental illness, affects 1% of the global population. The pathogenesis and specific treatment strategies for ASD and SCZ remain unclear. Previous research has suggested similarities in SCZ and ASD etiology and symptoms. However, no definitive correlation has been confirmed. Therefore, we conducted a Mendelian randomization study to assess the relationship between SCZ and ASD, providing new insights into their etiology and treatment. We used the two-sample Mendelian randomization (TSMR) approach to investigate the bidirectional causal association between SCZ and ASD, employing summary-level genome-wide association studies (GWAS) data. ASD summary data from the IEU GWAS database and SCZ summary data from the Psychiatric Genomics Consortium (PGC) were used as exposure and outcome variables, respectively. Statistical analysis was performed using the TwoSampleMR package in R version 4.3.2, with sensitivity analysis conducted to verify the result's reliability. Based on the results of the MR analysis, we retrieved and analyzed the relevant genetic information from the GWAS Catalog. TSMR analysis revealed higher ASD risk in SCZ (IVW: OR: 1.19, 95% CI: 1.12-1.26, P < .001). Bidirectional MR analysis confirmed a causal relationship between ASD and SCZ (IVW: scz2018clozuk (Clozapine UK), OR: 1.12, 95% CI: 1.04-1.21, P = .003; scz2019asi, OR: 1.14, 95% CI: 1.05-1.23, P = .002). Our study demonstrated a bidirectional relationship between SCZ and ASD in the European population, suggesting that each may induce the onset of the other.

Associations between multiple ambient air pollutants, genetic risk, and incident mental disorders: An interaction study in the UK population

Mental disorders can be triggered by genetic and environmental risk factors. Limited studies have explored the effects of long-term exposure to air pollution on mental disorders, and most of the studies have focused on individual air pollutants. This study aimed to examine the relationship between long-term exposure to multiple air pollutants and incident mental disorders, including depression, anxiety, and schizophrenia, and whether the associations were affected by genetic susceptibility. Participants in the UK Biobank with no history of mental disorders were followed from baseline (2006 to 2010) to October 31st, 2022. Cox regression was applied to evaluate the correlation between PM2.5 absorbance, PM2.5, PM2.5-10, PM10, NO2, and NOx and any or specific mental disorders. Additive and multiplicative scales were used to measure the interaction between air pollution and schizophrenia polygenic risk score (PRS), depression PRS, or anxiety PRS on specific mental diseases. After a median of 13.36 years of follow-up on 252,376 participants, we observed per interquartile increase of PM2.5 absorbance (0.32 per meter), PM2.5 (1.28 μg/m3), NO2 (10.08 μg/m3), and NOx (16.78 μg/m3) were related to a 2-6 % higher risk of incident mental disorders. The HR (95 % CI) of incident mental disorder for the 2nd, 3rd, and 4th quartile of the air pollution score were 1.05 (1.01-1.18), 1.13 (1.09-1.18), and 1.14 (1.09-1.19), respectively, in comparison to the lowest level of the score. Per interquartile increase in the air pollution score was associated with a 6 %, 24 %, 4 %, and 6 % higher risk of incident mental disorders, schizophrenia, depression, and anxiety, respectively. No interaction between air pollution and genetic risk of schizophrenia, depression or anxiety on corresponding incident disorders was observed. These findings emphasize the importance of implementing air pollution control standards to decrease the burden of mental disorders.

Mapping dynamic regulation of gene expression using single-cell transcriptomics and application to complex disease genetics

Single-cell transcriptome data can provide insights into how genetic variation influences biological processes involved in human physiology and disease. However, the identification of gene-level associations in distinct cell types faces several challenges, including the limited reference resources from population-scale studies, data sparsity in single-cell RNA sequencing, and the complex cell state pattern of expression within individual cell types. Here, we develop genetic models of cell-type-specific and cell-state-adjusted gene expression in mid-brain neurons undergoing differentiation from induced pluripotent stem cells. The resulting framework quantifies the dynamics of the genetic regulation of gene expression and estimates its cell-type specificity. As an application, we show that the approach detects known and new genes associated with schizophrenia and enables insights into context-dependent disease mechanisms. We provide a genomic resource from a phenome-wide application of our models to more than 1,500 phenotypes from the UK Biobank. Using longitudinal, genetically determined expression, we implement a predictive causality framework, evaluating the prediction of future values of a target gene expression using prior values of a putative regulatory gene. Collectively, the results of this work demonstrate the insights that can be gained into the molecular underpinnings of disease by quantifying the genetic control of gene expression at single-cell resolution.

Incorporating multiple functional annotations to improve polygenic risk prediction accuracy

We present OmniPRS, a scalable biobank-scale framework that improves genetic risk prediction for complex traits by integrating genome-wide association study (GWAS) summary statistics and functional annotations. It employs a mixed model incorporating tissue-specific genetic variance components from annotations to re-estimate single-nucleotide polymorphism (SNP) effects and constructs tissue-specific polygenic risk scores (PRSs) and aggregates them into the final OmniPRS. Our experiments, encompassing 135 simulation scenarios and 11 representative traits, demonstrate that OmniPRS is flexible and robust, delivering efficient and accurate predictions comparable to ten leading PRS methods. For quantitative (binary) traits, OmniPRS achieved an average improvement of 52.31% (19.83%) versus the clumping and thresholding (C+T) method, 3.92% (1.31%) versus the annotation-integrated PRSs (LDpred-funct), and 8.44% (2.27%) versus the Bayesian-based PRSs (PRScs). Notably, it achieved 35× faster computation than the PRScs. This rapid, precise framework enables efficient polygenic risk scoring with multi-annotation integration for large-scale genomic studies.

A Genome-Wide Association Study of First-Episode Psychosis: A Genetic Exploration in an Italian Cohort

BACKGROUND

Psychosis, particularly schizophrenia (SZ), is influenced by genetic and environmental factors. The neurodevelopmental hypothesis suggests that genetic factors affect neuronal circuit connectivity during perinatal periods, hence causing the onset of the diseases. In this study, we performed a genome-wide association study (GWAS) in a sample of the first episode of psychosis (FEP).

METHODS

A sample of 147 individuals diagnosed with non-affective psychosis and 102 controls were recruited and assessed. After venous blood and DNA extraction, the samples were genotyped. Genetic data underwent quality controls, genotype imputation, and a case-control genome-wide association study (GWAS). After the GWAS, results were investigated using an in silico functional mapping and annotation approach.

RESULTS

Our GWAS showed the association of 27 variants across 13 chromosomes at genome-wide significance (p < 1 × 10-7) and a total of 1976 candidate variants across 188 genes at suggestive significance (p < 1 × 10-5), mostly mapping in non-coding or intergenic regions. Gene-based tests reported the association of the SUFU (p = 4.8 × 10-7) and NCAN (p = 1.6 × 10-5) genes. Gene-sets enrichment analyses showed associations in the early stages of life, spanning from 12 to 24 post-conception weeks (p < 1.4 × 10-3) and in the late prenatal period (p = 1.4 × 10-3), in favor of the neurodevelopmental hypothesis. Moreover, several matches with the GWAS Catalog reported associations with strictly related traits, such as SZ, as well as with autism spectrum disorder, which shares some genetic overlap, and risk factors, such as neuroticism and alcohol dependence.

CONCLUSIONS

The resulting genetic associations and the consequent functional analysis displayed common genetic liability between the non-affective psychosis, related traits, and risk factors. In sum, our investigation provided novel hints supporting the neurodevelopmental hypothesis in SZ and-in general-in non-affective psychoses.

Epigenetics factors in schizophrenia: future directions for etiologic and therapeutic study approaches

Schizophrenia is a complex, heterogeneous, and highly disabling severe mental disorder whose pathogenesis has not yet been fully elucidated. Epigenetics, as a bridge between genetic and environmental factors, plays an important role in the pathophysiology of schizophrenia. Over the past decade, epigenetic-wide association studies have rapidly become an important branch of psychiatric research, especially in deciphering the molecular mechanisms of schizophrenia. This review systematically analyzes recent advances in epigenome-wide association studies (EWAS) of schizophrenia, focusing on technological developments. We synthesize findings from large-scale EWAS alongside emerging evidence on DNA methylation patterns, histone modifications, and regulatory networks, emphasizing their roles in disease mechanisms and treatment responses. In addition, this review provides a prospective outlook, evaluating the impact that technological developments may have on future studies of schizophrenia. With the continuous advancement of high-throughput sequencing technology and the increasing maturity of big data analysis methods, epigenetics is expected to have a significant impact on the early diagnosis, prognosis assessment and even personalized treatment of schizophrenia.

Genetic and neural mechanisms shared by schizophrenia and depression

Schizophrenia (SCZ) and depression are two prevalent mental disorders characterized by comorbidity and overlapping symptoms, yet the underlying genetic and neural mechanisms remain largely elusive. Here, we investigated the genetic variants and neuroimaging changes shared by SCZ and depression in Europeans and then extended our investigation to cross-ancestry (Europeans and East Asians) populations. Using conditional and conjunctional analyses, we found 213 genetic variants shared by SCZ and depression in Europeans, of which 82.6% were replicated in the cross-ancestry population. The shared risk variants exhibited a higher degree of deleteriousness than random and were enriched for synapse-related functions, among which fewer than 3% of shared variants showed horizontal pleiotropy between the two disorders. Mendelian randomization analyses indicated reciprocal causal effects between SCZ and depression. Using multiple trait genetic colocalization analyses, we pinpointed 13 volume phenotypes shared by SCZ and depression. Particularly noteworthy were the shared volume reductions in the left insula and planum polare, which were validated through large-scale meta-analyses of previous studies and independent neuroimaging datasets of first-episode drug-naïve patients. These findings suggest that the shared genetic risk variants, synapse dysfunction, and brain structural changes may underlie the comorbidity and symptom overlap between SCZ and depression.

Schizophrenia-associated changes in neuronal subpopulations in the human midbrain

Dysfunctional GABAergic and dopaminergic neurons are thought to exist in the ventral midbrain of patients with schizophrenia, yet transcriptional changes underpinning these abnormalities have not yet been localized to specific neuronal subsets. In the ventral midbrain, control over dopaminergic activity is maintained by both excitatory (glutamate) and inhibitory (GABA) input neurons. To elucidate neuron pathology at the single-cell level, we characterized the transcriptional diversity of distinct NEUN+ populations in the human ventral midbrain and then tested for schizophrenia-associated changes in neuronal subset proportions and gene activity changes within neuronal subsets. Combining single nucleus RNA-sequencing with fluorescence-activated sorting of NEUN+ nuclei, we analysed 31 669 nuclei. Initially, we detected 18 transcriptionally distinct neuronal populations in the human ventral midbrain, including two 'mixed' populations. The presence of neuronal populations in the midbrain was orthogonally validated with immunohistochemical stainings. 'Mixed' populations contained nuclei expressing transcripts for vesicular glutamate transporter 2 (SLC17A6) and glutamate decarboxylase 2 (GAD2), but these transcripts were not typically co-expressed by the same nucleus. Upon more fine-grained subclustering of the two 'mixed' populations, 16 additional subpopulations were identified that were transcriptionally classified as excitatory or inhibitory. In the midbrains of individuals with schizophrenia, we observed potential differences in the proportions of two (sub)populations of excitatory neurons, two subpopulations of inhibitory neurons, one 'mixed' subpopulation, and one subpopulation of TH-expressing neurons. This may suggest that transcriptional changes associated with schizophrenia broadly affect excitatory, inhibitory, and dopamine neurons. We detected 99 genes differentially expressed in schizophrenia compared to controls within neuronal subpopulations identified from the two 'mixed' populations, with most (67) changes within small GABAergic neuronal subpopulations. Overall, single-nucleus transcriptomic analyses profiled a high diversity of GABAergic neurons in the human ventral midbrain, identified putative shifts in the proportion of neuronal subpopulations, and suggested dysfunction of specific GABAergic subpopulations in schizophrenia, providing directions for future research.

Genetically regulated eRNA expression predicts chromatin contact frequency and reveals genetic mechanisms at GWAS loci

The biological functions of extragenic enhancer RNAs and their impact on disease risk remain relatively underexplored. In this work, we develop in silico models of genetically regulated expression of enhancer RNAs across 49 cell and tissue types, characterizing their degree of genetic control. Leveraging the estimated genetically regulated expression for enhancer RNAs and canonical genes in a large-scale DNA biobank (N > 70,000) and high-resolution Hi-C contact data, we train a deep learning-based model of pairwise three-dimensional chromatin contact frequency for enhancer-enhancer and enhancer-gene pairs in cerebellum and whole blood. Notably, the use of genetically regulated expression of enhancer RNAs provides substantial tissue-specific predictive power, supporting a role for these transcripts in modulating spatial chromatin organization. We identify schizophrenia-associated enhancer RNAs independent of GWAS loci using enhancer RNA-based TWAS and determine the causal effects of these enhancer RNAs using Mendelian randomization. Using enhancer RNA-based TWAS, we generate a comprehensive resource of tissue-specific enhancer associations with complex traits in the UK Biobank. Finally, we show that a substantially greater proportion (63%) of GWAS associations colocalize with causal regulatory variation when enhancer RNAs are included.

Intergenerational transmission of complex traits and the offspring methylome

The genetic makeup of parents can directly or indirectly affect their offspring phenome through genetic transmission or via the environment that is influenced by parental heritable traits. Our understanding of the mechanisms by which indirect genetic effects operate is limited. Here, we hypothesize that one mechanism is via the offspring methylome. To test this hypothesis, polygenic scores (PGSs) for schizophrenia, smoking initiation, educational attainment (EA), social deprivation, body mass index (BMI), and height were analyzed in a cohort of 1528 offspring and their parents (51.5% boys, mean [SD] age = 10 [2.8] years). We modelled parent and offspring PGSs on offspring buccal-DNA methylation, accounting for the own PGS of offspring, and found significant associations between parental PGSs for schizophrenia, EA, BMI, and height, and offspring buccal methylation sites, comprising 16, 2, 1, and 6 sites, respectively (alpha = 2.7 × 10-5). More DNA methylation sites were associated with maternal than paternal PGSs, possibly reflecting the maternal pre- and periconceptional environment or stronger maternal involvement in shaping the offspring's environment during early childhood.

The independent role of fine particulate matter and genetic liability on cognition in older adults

BACKGROUND

Genetic susceptibility to mental health and cognitive traits, as well as air pollution, significantly impact cognition. The interplay between polygenic liability and fine particulate matter (PM2.5) remains unclear due to the limited number of large-scale studies in Asia. This study utilized the Taiwan Biobank, a nationwide community-based database, to investigate the main and modified effect of PM2.5 on individuals' polygenic susceptibility in cognition.

METHODS

Polygenic risk score (PRS) for cognitive performance (CP PRS), Alzheimer's disease (AD PRS), schizophrenia (SCZ PRS), and major depression (MDD PRS) were computed representing genetic susceptibility for an individual. APOE genotype was classified into E3/E3, E3/E4, and E4/E4. The five-year average concentration of PM2.5 from satellite images was used for defining environmental exposure. Cognitive performance was evaluated via the Mini-Mental State Examination (MMSE) score. The association between personal genetic susceptibility, PM2.5, and cognitive performance was examined using multilevel linear regression with the adjustment of age, sex, batch effect, and population stratification effect. The gene-environment synergism was examined with the inclusion of product term of PM2.5 and PRS in the multivariate model.

RESULTS

Our analyses included 25,593 participants from 164 townships. Participants exposed to higher PM2.5 concentrations had a lower MMSE score (Beta=-0.0830 corresponding to a 1 µg/m3 increase in PM2.5 concentration, 95% CI, -0.0973 to -0.0688, p-value < 0.0001). After controlling for PM2.5 concentration, CP PRS (Beta = 0.1729, 95% CI, 0.1470 to 0.1988, p-value < 0.0001), SCZ PRS (Beta=-0.0632, 95% CI, -0.0891 to -0.0374, p-value < 0.0001), and AD PRS (Beta=-0.0321, 95% CI, -0.0580 to -0.0062, p-value = 0.0153) were associated with MMSE score. After further examination of gene-environment synergism, no interaction effect was identified, indicating different mechanism of PM2.5 and genetic liability to influence cognitive performance.

CONCLUSIONS

Human polygenic loading and PM2.5 may impact cognition via an independent pathway. A prevention strategy targeting air pollution reduction may effectively improve the cognitive performance. Multiple exposures and their influences on the long-term change of cognition were required in future research.

Single-Nucleus Transcriptomics Identifies Neuroblast Migration Programs Sensitive to Reelin and Cannabis in the Adolescent Nucleus Accumbens

The interplay between cannabis exposure during adolescence and genetic predisposition has been linked to increased vulnerability to psychiatric disorders. To investigate the molecular underpinnings of this interaction, we performed single-nucleus RNA sequencing of the nucleus accumbens (NAc) in a mouse model of Reln haploinsufficiency, a genetic risk factor for psychiatric disorders, following adolescent exposure to tetrahydrocannabinol (THC), the primary psychoactive component of cannabis. We identified a gene co-expression network influenced by both Reln genotype and THC, enriched in genes associated with human psychiatric disorders and predominantly expressed in a GABAergic neuroblast subpopulation. We showed that neuroblasts actively migrated in the adolescent NAc, but declined with age. Cell-to-cell communication analysis further revealed that these neuroblasts receive migratory cues from cholecystokinin interneurons, which express high levels of cannabinoid receptors. Together, these findings provide mechanistic insights into how adolescent THC exposure and genetic risk factors may impair GABAergic circuit maturation.