Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways

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.

Sex-differentiated placental methylation and gene expression regulation has implications for neonatal traits and adult diseases

Sex differences in physiological and disease traits are pervasive and begin during early development, but the genetic architecture of these differences is largely unknown. Here, we leverage the human placenta, a transient organ during pregnancy critical to fetal development, to investigate the impact of sex in the regulatory landscape of placental autosomal methylome and transcriptome, and its relevance to health and disease. We find that placental methylation and its genetic regulation are extensively impacted by fetal sex, whereas sex differences in placental gene expression and its genetic regulation are limited. We identify molecular processes and regulatory targets that are enriched in a sex-specific manner, and find enrichment of imprinted genes in sex-differentiated placental methylation, including female-biased methylation within the well-known KCNQ1OT1/CDKN1C imprinting cluster of genes expressed in a parent-of-origin dependent manner. We establish that several sex-differentiated genetic effects on placental methylation and gene expression colocalize with birthweight and adult disease genetic associations, facilitating mechanistic insights on early life origins of health and disease outcomes shaped by sex.

Clinical Staging for Psychiatry and Psychology

A global mental health crisis is threatening a generation of young people with a lifetime of symptoms that do not fit neatly into diagnostic systems. Optimal decisions regarding treatments, services, research, and policies are critically needed, yet such decisions are based on idiosyncratic categorization of clinical courses. This review suggests clinical staging approaches may unite mental health stakeholders around shared targets to reduce mental illness. It first presents key approaches to clinical staging and then outlines how clinical knowledge has been translated into a unified transdiagnostic staging heuristic and clinical service structure over the past 30 years. Directions for short-, medium-, and long-term action are recommended with global community engagement. With investment from the mental health community, staging could reduce suffering through the use of an ethical, organized, and targeted system of communication.

Multigene overlap analysis of bipolar disorder subtypes and educational attainment

OBJECTIVE

Bipolar disorder subtypes (BIP-I and BIP-II) differ in clinical presentation and genetic basis, yet their patterns of genetic association with educational attainment (EA) remain poorly understood. This study investigated the genetic overlap between BIP subtypes and EA, along with their underlying molecular mechanisms.

METHODS

Using genome-wide association study (GWAS) data for BIP-I (n = 25,060), BIP-II (n = 6781), and EA (n = 765,283), we estimated genetic overlap using bivariate causal mixed models (MiXeR) and identified shared gene loci through the joint false discovery rate (conjFDR) method.

RESULTS

MiXeR analysis revealed approximately 7.4 K single nucleotide polymorphisms (SNPs) shared between BIP-I and EA, accounting for 97.4 % of SNPs influencing BIP-I and 56.5 % of those affecting EA. ConjFDR identified 264 loci commonly associated with BIP-I and EA, including 168 novel loci for both traits. Among the 312 lead SNPs at these loci, 219 exhibited consistent effects, while 93 demonstrated opposing effects. In contrast, only two loci were co-associated between BIP-II and EA. Functional annotation and enrichment analyses showed that most loci shared by BIP-I and EA were located in intronic and intergenic regions, with associated genes enriched in processes such as protein binding and nervous system development.

CONCLUSIONS

This study highlights the distinct degrees and patterns of genetic association between BIP subtypes and EA, offering insights into the heterogeneity of BIP and a potential genetic basis for clinical subtyping and personalized treatment strategies.

Associations between common genetic variants and income provide insights about the socio-economic health gradient

We conducted a genome-wide association study on income among individuals of European descent (N = 668,288) to investigate the relationship between socio-economic status and health disparities. We identified 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes (the Income Factor). Our polygenic index captures 1-5% of income variance, with only one fourth due to direct genetic effects. A phenome-wide association study using this index showed reduced risks for diseases including hypertension, obesity, type 2 diabetes, depression, asthma and back pain. The Income Factor had a substantial genetic correlation (0.92, s.e. = 0.006) with educational attainment. Accounting for the genetic overlap of educational attainment with income revealed that the remaining genetic signal was linked to better mental health but reduced physical health and increased risky behaviours such as drinking and smoking. These findings highlight the complex genetic influences on income and health.

Effects of sulforaphane on negative symptoms and cognitive impairments in chronic schizophrenia patients: A randomized double-blind trial

BACKGROUND

The pathological mechanisms of negative symptoms and cognitive impairment in schizophrenia may involve oxidative stress and neuroinflammation. Sulforaphane is an organosulfur compound with antioxidant and anti-inflammatory properties. This study aimed to evaluate its efficacy in ameliorating negative symptoms and cognitive impairments in chronic schizophrenia patients.

METHOD

This 24-week double-blind randomised trial (NCT04521868) recruited schizophrenia patients with significant negative symptoms. Participants were randomly assigned to receive either sulforaphane or placebo and were required to complete at least one post-intervention assessment to evaluate changes in negative symptoms and cognitive functioning. Existing antipsychotic medication treatment regimens remained unchanged throughout the study.

RESULTS

A total of 42 patients were included in the statistical analysis, with 28 receiving sulforaphane and 14 assigned to placebo. Sulforaphane significantly reduced the Negative Symptom Score from the PANSS 5-Factor model between groups (p = 0.007) and exhibited a significant time-by-group interaction (p = 0.023), with more pronounced group differences observed after 12 weeks compared to 24 weeks of treatment. Sulforaphane also demonstrated a significant reduction in the original PANSS Negative Symptom Score between groups (p = 0.029). However, sulforaphane showed no significant effects on the MATRICS Consensus Cognitive Battery composite score or its subscores.

CONCLUSION

The significant improvements in the Negative Symptom Score from the PANSS 5-Factor model and the original PANSS Negative Symptom Score in the sulforaphane group suggest the potential of sulforaphane as an adjunctive treatment for ameliorating negative symptoms in chronic schizophrenia. Further research is warranted to explore the effects of sulforaphane on cognitive function.

Protein arginine methyltransferase 7 linked to schizophrenia through regulation of neural progenitor cell proliferation and differentiation

Genome-wide association studies (GWASs) have identified numerous genomic loci linked to schizophrenia (SCZ), while their pathogenic mechanisms largely remain unclear. This study demonstrated protein arginine methyltransferase 7 (PRMT7) as a key target of SCZ risk SNPs with allele-specific enhancer activity at 16q22.1. Downregulating PRMT7 in neural progenitor cells (NPCs) decreased proliferation, increased neuronal differentiation, and also led to longer neurites in these neurons. Conversely, overexpressing PRMT7 enhanced NPC proliferation and reduced neuronal differentiation. In three-dimensional (3D) cerebral organoids, similar NPC phenotypic changes were noted following PRMT7 depletion. Mechanistically, PRMT7 regulates the expression of genes related to the cell cycle and neuronal functions, such as CDKN2A and SYP, via symmetrical di-methylation at arginine 3 of histone 4 (H4R3me2s) modification in their promoters. Notably, these genes have a stronger association with SCZ compared to other mental disorders. Together, the results of this study reveal that PRMT7 is a functional gene at 16q22.1, contributing to the etiology of SCZ by modulating NPC proliferation and differentiation as an epigenetic regulator.

Dissecting Schizophrenia Biology Using Pleiotropy With Cognitive Genomics

BACKGROUND

Given the increasingly large number of loci discovered by psychiatric genome-wide association studies (GWASs), specification of the key biological pathways that underlie these loci has become a priority for the field. We have previously leveraged the pleiotropic genetic relationships between schizophrenia (SCZ) and 2 cognitive phenotypes (educational attainment and cognitive task performance) to differentiate 2 subsets of illness-relevant single nucleotide polymorphisms (SNPs): 1) those with concordant alleles, which are associated with reduced cognitive performance and educational attainment and increased SCZ risk, and 2) those with discordant alleles, which are linked to reduced educational and/or cognitive levels but lower SCZ susceptibility.

METHODS

In the current study, we extended our prior work, utilizing larger input GWAS datasets and a more powerful statistical approach to pleiotropic meta-analysis, the pleiotropic locus exploration and interpretation using optimal test (PLEIO).

RESULTS

Our pleiotropic meta-analysis of SCZ and the 2 cognitive phenotypes revealed 768 significant pleiotropic loci (166 novel). Among these, 347 loci harbored concordant SNPs, 270 encompassed discordant SNPs, and 151 dual loci contained concordant and discordant SNPs. Competitive gene-set analysis using MAGMA linked concordant SNP loci with neurodevelopmental pathways (e.g., neurogenesis), whereas discordant loci were associated with mature neuronal synaptic functions. These distinctions were also observed in BrainSpan analysis of temporal enrichment patterns across developmental periods, with concordant loci containing more prenatally expressed genes than discordant loci. Dual loci were enriched for genes related to messenger RNA translation initiation, which represents a novel finding in the SCZ literature.

CONCLUSIONS

Pleiotropic analysis permits not only enhanced statistical power for locus discovery but also the ability to parse distinct biological processes associated with endophenotypes.

ATR-hippo drives force signaling to nuclear F-actin and links mechanotransduction to neurological disorders

The mechanical environment is sensed through cell-matrix contacts with the cytoskeleton, but how signals transit the nuclear envelope to affect cell fate decisions remains unknown. Nuclear actin coordinates chromatin motility during differentiation and genome maintenance, yet it remains unclear how nuclear actin responds to mechanical force. The DNA-damage kinase ataxia telangiectasia and Rad3-related protein (ATR) translocates to the nuclear envelope to protect the nucleus during cell motility or compression. Here, we show that ATR drives nuclear actin assembly via recruitment of Filamin-A to the inner nuclear membrane through binding of the hippo pathway scaffold and ATR substrate, RASSF1A. Moreover, we demonstrate how germline RASSF1 mutation disables nuclear mechanotransduction resulting in cerebral cortex thinning and associates with common psychological traits. Thus, defective mechanical-regulated pathways may contribute to complex neurological disorders.

Independent inheritance of cognition and bipolar disorder in a family sample

Cognitive deficits in people with bipolar disorder (BD) may be the result of the illness or its treatment, but they could also reflect genetic risk factors shared between BD and cognition. We investigated this question using empirical genetic relationships within a sample of patients with BD and their unaffected relatives. Participants with bipolar I, II, or schizoaffective disorder ("narrow" BD, n = 69), related mood disorders ("broad" BD, n = 135), and their clinically unaffected relatives (n = 227) completed five cognitive tests. General cognitive function (g) was quantified via principal components analysis (PCA). Heritability and genetic correlations were estimated with SOLAR-Eclipse. Participants with "narrow" or "broad" diagnoses showed deficits in g, although affect recognition was unimpaired. Cognitive performance was significantly heritable (h2 = 0.322 for g, p < 0.005). Coheritability between psychopathology and g was small (0.0184 for narrow and 0.0327 for broad) and healthy relatives of those with BD were cognitively unimpaired. In this family sample, cognitive deficits were present in participants with BD but were not explained by substantial overlaps in genetic determinants of mood and cognition. These findings support the view that cognitive deficits in BD are largely the result of the illness or its treatment.

Cross-ancestry genetic investigation of schizophrenia, cannabis use disorder, and tobacco smoking

Individuals with schizophrenia frequently experience co-occurring substance use, including tobacco smoking and heavy cannabis use, and substance use disorders. There is interest in understanding the extent to which these relationships are causal, and to what extent shared genetic factors play a role. We explored the relationships between schizophrenia (Scz; European ancestry N = 161,405; African ancestry N = 15,846), cannabis use disorder (CanUD; European ancestry N = 886,025; African ancestry N = 120,208), and ever-regular tobacco smoking (Smk; European ancestry N = 805,431; African ancestry N = 24,278) using the largest available genome-wide studies of these phenotypes in individuals of African and European ancestries. All three phenotypes were positively genetically correlated (rgs = 0.17-0.62). Genetic instrumental variable analyses suggested the presence of shared heritable factors, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for these shared genetic factors. We identified 327 pleiotropic loci with 439 lead SNPs in the European ancestry data, 150 of which were novel (i.e., not genome-wide significant in the original studies). Of these pleiotropic loci, 202 had lead variants which showed convergent effects (i.e., same direction of effect) on Scz, CanUD, and Smk. Genetic variants convergent across all three phenotypes showed strong genetic correlations with risk-taking, executive function, and several mental health conditions. Our results suggest that both shared genetic factors and causal mechanisms may play a role in the relationship between CanUD, Smk, and Scz, but longitudinal, prospective studies are needed to confirm a causal relationship.

Oxygen-induced stress reveals context-specific gene regulatory effects in human brain organoids

The interaction between genetic variants and environmental stressors is key to understanding the mechanisms underlying neurological diseases. In this study, we used human brain organoids to explore how varying oxygen levels expose context-dependent gene regulatory effects. By subjecting a genetically diverse panel of 21 brain organoids to hypoxic and hyperoxic conditions, we identified thousands of gene regulatory changes that are undetectable under baseline conditions, with 1,745 trait-associated genes showing regulatory effects only in response to oxygen stress. To capture more nuanced transcriptional patterns, we employed topic modeling, which revealed context-specific gene regulation linked to dynamic cellular processes and environmental responses, offering a deeper understanding of how gene regulation is modulated in the brain. These findings underscore the importance of genotype-environment interactions in genetic studies of neurological disorders and provide new insights into the hidden regulatory mechanisms influenced by environmental factors in the brain.

Biological Insights from Schizophrenia-associated Loci in Ancestral Populations

Large-scale genome-wide association studies of schizophrenia have uncovered hundreds of associated loci but with extremely limited representation of African diaspora populations. We surveyed electronic health records of 200,000 individuals of African ancestry in the Million Veteran and All of Us Research Programs, and, coupled with genotype-level data from four case-control studies, realized a combined sample size of 13,012 affected and 54,266 unaffected persons. Three genome-wide significant signals - near PLXNA4, PMAIP1, and TRPA1 - are the first to be independently identified in populations of predominantly African ancestry. Joint analyses of African, European, and East Asian ancestries across 86,981 cases and 303,771 controls, yielded 376 distinct autosomal loci, which were refined to 708 putatively causal variants via multi-ancestry fine-mapping. Utilizing single-cell functional genomic data from human brain tissue and two complementary approaches, transcriptome-wide association studies and enhancer-promoter contact mapping, we identified a consensus set of 94 genes across ancestries and pinpointed the specific cell types in which they act. We identified reproducible associations of schizophrenia polygenic risk scores with schizophrenia diagnoses and a range of other mental and physical health problems. Our study addresses a longstanding gap in the generalizability of research findings for schizophrenia across ancestral populations, underlining shared biological underpinnings of schizophrenia across global populations in the presence of broadly divergent risk allele frequencies.

Estimating the direct effects of the genetic liabilities to bipolar disorder, schizophrenia, and behavioral traits on suicide attempt using a multivariable Mendelian randomization approach

Bipolar disorder (BD) and schizophrenia (SZ) are associated with higher odds of suicide attempt (SA). In this study, we aimed to explore the effect of BD and SZ genetic liabilities on SA, also considering the contribution of behavioral traits, socioeconomic factors, and substance use disorders. Leveraging large-scale genome-wide association data from the Psychiatric Genomics Consortium (PGC) and the UK Biobank (UKB), we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the putative causal effect of BD (41,917 cases, 371,549 controls) and SZ (53,386 cases, 77,258 controls) on SA (26,590 cases, 492,022 controls). Then, we assessed the putative causal effect of BD and SZ on behavioral traits, socioeconomic factors, and substance use disorders. Considering the associations identified, we evaluated the direct causal effect of behavioral traits, socioeconomic factors, and substance use disorders on SA using a multivariable MR approach. The genetic liabilities to BD and SZ were associated with higher odds of SA (BD odds ratio (OR) = 1.24, p = 3.88 × 10-12; SZ OR = 1.09, p = 2.44 × 10-20). However, while the effect of mental distress (OR = 1.17, p = 1.02 × 10-4) and risk-taking (OR = 1.52, p = 0.028) on SA was independent of SZ genetic liability, the BD-SA relationship appeared to account for the effect of these risk factors. Similarly, the association with loneliness on SA was null after accounting for the effect of SZ genetic liability. These findings highlight the complex interplay between genetic risk of psychiatric disorders and behavioral traits in the context of SA, suggesting the need for a comprehensive mental health assessment for high-risk individuals.

A systematic review and meta-analysis of neuroimaging studies examining synaptic density in individuals with psychotic spectrum disorders

BACKGROUND

Psychotic disorders have long been considered neurodevelopmental disorders where excessive synaptic pruning and cortical volume loss are central to disease pathology. We conducted a systematic review of the literature to identify neuroimaging studies specifically examining synaptic density across the psychosis spectrum.

METHODS

PRISMA guidelines on reporting were followed. We systematically searched MEDLINE, Embase, APA PsycINFO, Web of Science and The Cochrane Library from inception to December 8, 2023, and included all original peer-reviewed articles or completed clinical neuroimaging studies of any modality measuring synaptic density in participants with a diagnosis of psychosis spectrum disorder as well as individuals with psychosis-risk states. The NIH quality assessment tool for observational cohort and cross-sectional studies was used for the risk of bias assessment.

RESULTS

Five studies (k = 5) met inclusion criteria, comprising n = 128 adults (psychotic disorder; n = 61 and healthy volunteers; n = 67 and specifically measuring synaptic density via positron emission tomography (PET) imaging of the synaptic vesicle glycoprotein 2 A (SV2A). Three studies were included in our primary meta-analysis sharing the same outcome measure of SV2A binding, volume of distribution (VT). Regional SV2A VT was reduced in psychotic disorder participants in comparison to healthy volunteers, including the occipital lobe (Mean Difference (MD)= -2.17; 95% CI: -3.36 to -0.98; P < 0.001 ), temporal lobe (MD: -2.03; 95% CI: -3.19 to -0.88; P < 0.001 ), parietal lobe (MD:-1.61; 95% CI: -2.85 to -0.37; P = 0.01), anterior cingulate cortex (MD= -1.47; 95% CI: -2.45 to -0.49; P = 0.003), frontal cortex (MD: -1.16; 95% CI: -2.18 to -0.15; P = 0.02), amygdala (MD: -1.36; 95% CI: -2.20 to -0.52, p = 0.002), thalamus (MD:-1.46; 95% CI:-2.46 to -0.46, p = 0.004) and hippocampus (MD= -0.96; 95% CI: -1.59 to -0.33; P = 0.003).

CONCLUSIONS

Preliminary studies provide in vivo evidence for reduced synaptic density in psychotic disorders. However, replication of findings in larger samples is required prior to definitive conclusions being drawn.

PROSPERO

CRD42022359018.

Genetic modifiers of rare variants in monogenic developmental disorder loci

Rare damaging variants in a large number of genes are known to cause monogenic developmental disorders (DDs) and have also been shown to cause milder subclinical phenotypes in population cohorts. Here, we show that carrying multiple (2-5) rare damaging variants across 599 dominant DD genes has an additive adverse effect on numerous cognitive and socioeconomic traits in UK Biobank, which can be partially counterbalanced by a higher educational attainment polygenic score (EA-PGS). Phenotypic deviators from expected EA-PGS could be partly explained by the enrichment or depletion of rare DD variants. Among carriers of rare DD variants, those with a DD-related clinical diagnosis had a substantially lower EA-PGS and more severe phenotype than those without a clinical diagnosis. Our results suggest that the overall burden of both rare and common variants can modify the expressivity of a phenotype, which may then influence whether an individual reaches the threshold for clinical disease.

Dissecting Schizophrenia Biology Using Pleiotropy with Cognitive Genomics

Given the increasingly large number of loci discovered by psychiatric GWAS, specification of the key biological pathways underlying these loci has become a priority for the field. We have previously leveraged the pleiotropic genetic relationships between schizophrenia and two cognitive phenotypes (educational attainment and cognitive task performance) to differentiate two subsets of illness-relevant SNPs: (1) those with "concordant" alleles, which are associated with reduced cognitive ability/education and increased schizophrenia risk; and (2) those with "discordant" alleles linked to reduced educational and/or cognitive levels but lower schizophrenia susceptibility. In the present study, we extend our prior work, utilizing larger input GWAS datasets and a more powerful statistical approach to pleiotropic meta-analysis, the Pleiotropic Locus Exploration and Interpretation using Optimal test (PLEIO). Our pleiotropic meta-analysis of schizophrenia and the two cognitive phenotypes revealed 768 significant loci (159 novel). Among these, 347 loci harbored concordant SNPs, 270 encompassed discordant SNPs, and 151 "dual" loci contained concordant and discordant SNPs. Competitive gene-set analysis using MAGMA related concordant SNP loci with neurodevelopmental pathways (e.g., neurogenesis), whereas discordant loci were associated with mature neuronal synaptic functions. These distinctions were also observed in BrainSpan analysis of temporal enrichment patterns across developmental periods, with concordant loci containing more prenatally expressed genes than discordant loci. Dual loci were enriched for genes related to mRNA translation initiation, representing a novel finding in the schizophrenia literature.

Genetic overlap between schizophrenia and cognitive performance

Schizophrenia (SCZ), a highly heritable mental disorder, is characterized by cognitive impairment, yet the extent of the shared genetic basis between schizophrenia and cognitive performance (CP) remains poorly understood. Therefore, we aimed to explore the polygenic overlap between SCZ and CP. Specifically, the bivariate causal mixture model (MiXeR) was employed to estimate the extent of genetic overlap between SCZ (n = 130,644) and CP (n = 257,841), and conjunctional false discovery rate (conjFDR) approach was used to identify shared genetic loci. Subsequently, functional annotation and enrichment analysis were carried out on the identified genomic loci. The MiXeR analyses revealed that 9.6 K genetic variants are associated with SCZ and 10.9 K genetic variants for CP, of which 9.5 K variants are shared between these two traits (Dice coefficient = 92.8%). By employing conjFDR, 236 loci were identified jointly associated with SCZ and CP, of which 139 were novel for the two traits. Within these shared loci, 60 exhibited consistent effect directions, while 176 had opposite effect directions. Functional annotation analysis indicated that the shared genetic loci were mainly located in intronic and intergenic regions, and were found to be involved in relevant biological processes such as nervous system development, multicellular organism development, and generation of neurons. Together, our findings provide insights into the shared genetic architecture between SCZ and CP, suggesting common pathways and mechanisms contributing to both traits.

Genome-wide association analyses using machine learning-based phenotyping reveal genetic architecture of occupational creativity and overlap with psychiatric disorders

Creativity is known to be heritable and exhibits familial aggregation with psychiatric disorders; however, the complex nature of their relationship has not been well-established. In the present study, we demonstrate that using an expanded and validated machine learning (ML)-based phenotyping of occupational creativity (OC) can allow us to further understand the trait of creativity, which was previously difficult to define and study. We conducted the largest genome-wide association study (GWAS) on OC with 241,736 participants from the UK Biobank and identified 25 lead variants that have not yet been reported and three candidate causal genes that were previously associated with educational attainment and psychiatric disorders. We found extensive genetic overlap between OC and psychiatric disorders with mixed effect direction through various post-GWAS analyses, including the bivariate causal mixture model. In addition, we discovered a strongly genetic correlation between our original GWAS and the GWAS adjusted for education years (rg = 0.95). Our GWAS analysis via ML-based phenotyping contributes to the understanding of the genetic architecture of creativity, which may inform genetic discovery and genetic prediction in human cognition and psychiatric disorders.

Genome-wide analyses reveal shared genetic architecture and novel risk loci between opioid use disorder and general cognitive ability

BACKGROUND

Opioid use disorder (OUD), a serious health burden worldwide, is associated with lower cognitive function. Recent studies have demonstrated a negative genetic correlation between OUD and general cognitive ability (COG), indicating a shared genetic basis. However, the specific genetic variants involved, and the underlying molecular mechanisms remain poorly understood. Here, we aimed to quantify and identify the genetic basis underlying OUD and COG.

METHODS

We quantified the extent of genetic overlap between OUD and COG using a bivariate causal mixture model (MiXeR) and identified specific genetic loci applying conditional/conjunctional FDR. Finally, we investigated biological function and expression of implicated genes using available resources.

RESULTS

We estimated that ~94% of OUD variants (4.8k out of 5.1k variants) also influence COG. We identified three novel OUD risk loci and one locus shared between OUD and COG. Loci identified implicated biological substrates in the basal ganglia.

CONCLUSION

We provide new insights into the complex genetic risk architecture of OUD and its genetic relationship with COG.

SATB2 organizes the 3D genome architecture of cognition in cortical neurons

The DNA-binding protein SATB2 is genetically linked to human intelligence. We studied its influence on the three-dimensional (3D) epigenome by mapping chromatin interactions and accessibility in control versus SATB2-deficient cortical neurons. We find that SATB2 affects the chromatin looping between enhancers and promoters of neuronal-activity-regulated genes, thus influencing their expression. It also alters A/B compartments, topologically associating domains, and frequently interacting regions. Genes linked to SATB2-dependent 3D genome changes are implicated in highly specialized neuronal functions and contribute to cognitive ability and risk for neuropsychiatric and neurodevelopmental disorders. Non-coding DNA regions with a SATB2-dependent structure are enriched for common variants associated with educational attainment, intelligence, and schizophrenia. Our data establish SATB2 as a cell-type-specific 3D genome modulator, which operates both independently and in cooperation with CCCTC-binding factor (CTCF) to set up the chromatin landscape of pyramidal neurons for cognitive processes.

Large-Scale Mendelian Randomization Study Reveals Circulating Blood-based Proteomic Biomarkers for Psychopathology and Cognitive Task Performance

Background

Research on peripheral (e.g., blood-based) biomarkers for psychiatric illness has typically been low-throughput in terms of both the number of subjects and the range of assays performed. Moreover, traditional case-control studies examining blood-based biomarkers are subject to potential confounds of treatment and other exposures common to patients with psychiatric illnesses. Our research addresses these challenges by leveraging large-scale, high-throughput proteomics data and Mendelian Randomization (MR) to examine the causal impact of circulating proteins on psychiatric phenotypes and cognitive task performance.

Methods

We utilized plasma proteomics data from the UK Biobank (3,072 proteins assayed in 34,557 European-ancestry individuals) and deCODE Genetics (4,719 proteins measured across 35,559 Icelandic individuals). Significant proteomic quantitative trait loci (both cis-pQTLs and trans-pQTLs) served as MR instruments, with the most recent GWAS for schizophrenia, bipolar disorder, major depressive disorder, and cognitive task performance (all excluding overlapping UK Biobank participants) as phenotypic outcomes.

Results

MR revealed 109 Bonferroni-corrected causal associations (44 novel) involving 88 proteins across the four phenotypes. Several immune-related proteins, including interleukins and complement factors, stood out as pleiotropic across multiple outcome phenotypes. Drug target enrichment analysis identified several novel potential pharmacologic repurposing opportunities, including anti-inflammatory agents for schizophrenia and bipolar disorder and duloxetine for cognitive performance.

Conclusions

Identification of causal effects for these circulating proteins suggests potential biomarkers for these conditions and offers insights for developing innovative therapeutic strategies. The findings also indicate substantial evidence for the pleiotropic effects of many proteins across different phenotypes, shedding light on the shared etiology among psychiatric conditions and cognitive ability.

Cross-ancestry genetic investigation of schizophrenia, cannabis use disorder, and tobacco smoking

Individuals with schizophrenia frequently experience co-occurring substance use, including tobacco smoking and heavy cannabis use, and substance use disorders. There is interest in understanding the extent to which these relationships are causal, and to what extent shared genetic factors play a role. We explored the relationships between schizophrenia (Scz), cannabis use disorder (CanUD), and ever-regular tobacco smoking (Smk) using the largest available genome-wide studies of these phenotypes in individuals of African and European ancestries. All three phenotypes were positively genetically correlated (rgs = 0.17 - 0.62). Causal inference analyses suggested the presence of horizontal pleiotropy, but evidence for bidirectional causal relationships was also found between all three phenotypes even after correcting for horizontal pleiotropy. We identified 439 pleiotropic loci in the European ancestry data, 150 of which were novel (i.e., not genome-wide significant in the original studies). Of these pleiotropic loci, 202 had lead variants which showed convergent effects (i.e., same direction of effect) on Scz, CanUD, and Smk. Genetic variants convergent across all three phenotypes showed strong genetic correlations with risk-taking, executive function, and several mental health conditions. Our results suggest that both horizontal pleiotropy and causal mechanisms may play a role in the relationship between CanUD, Smk, and Scz, but longitudinal, prospective studies are needed to confirm a causal relationship.

The role of cell adhesion molecule IgSF9b at the inhibitory synapse and psychiatric disease

Understanding perturbations in synaptic function between health and disease states is crucial to the treatment of neuropsychiatric illness. While genome-wide association studies have identified several genetic loci implicated in synaptic dysfunction in disorders such as autism and schizophrenia, many have not been rigorously characterized. Here, we highlight immunoglobulin superfamily member 9b (IgSF9b), a cell adhesion molecule thought to localize exclusively to inhibitory synapses in the brain. While both pre-clinical and clinical studies suggest its association with psychiatric diseases, our understanding of IgSF9b in synaptic maintenance, neural circuits, and behavioral phenotypes remains rudimentary. Moreover, these functions wield undiscovered influences on neurodevelopment. This review evaluates current literature and publicly available gene expression databases to explore the implications of IgSF9b dysfunction in rodents and humans. Through a focused analysis of one high-risk gene locus, we identify areas requiring further investigation and unearth clues related to broader mechanisms contributing to the synaptic etiology of psychiatric disorders.

ASCL1 Is Involved in the Pathogenesis of Schizophrenia by Regulation of Genes Related to Cell Proliferation, Neuronal Signature Formation, and Neuroplasticity

Schizophrenia (SZ) is a common psychiatric neurodevelopmental disorder with a complex genetic architecture. Genome-wide association studies indicate the involvement of several transcription factors, including ASCL1, in the pathogenesis of SZ. We aimed to identify ASCL1-dependent cellular and molecular mechanisms associated with SZ. We used Capture-C, CRISPR/Cas9 systems and RNA-seq analysis to confirm the involvement of ASCL1 in SZ-associated pathogenesis, establish a mutant SH-SY5Y line with a functional ASCL1 knockout (ASCL1-del) and elucidate differentially expressed genes that may underlie ASCL1-dependent pathogenic mechanisms. Capture-C confirmed the spatial interaction of the ASCL1 promoter with SZ-associated loci. Transcriptome analysis showed that ASCL1 regulation may be through a negative feedback mechanism. ASCL1 dysfunction affects the expression of genes associated with the pathogenesis of SZ, as well as bipolar and depressive disorders. Genes differentially expressed in ASCL1-del are involved in cell mitosis, neuronal projection, neuropeptide signaling, and the formation of intercellular contacts, including the synapse. After retinoic acid (RA)-induced differentiation, ASCL1 activity is restricted to a small subset of genes involved in neuroplasticity. These data suggest that ASCL1 dysfunction promotes SZ development predominantly before the onset of neuronal differentiation by slowing cell proliferation and impeding the formation of neuronal signatures.

Recent natural selection conferred protection against schizophrenia by non-antagonistic pleiotropy

Schizophrenia is a debilitating psychiatric disorder associated with a reduced fertility and decreased life expectancy, yet common predisposing variation substantially contributes to the onset of the disorder, which poses an evolutionary paradox. Previous research has suggested balanced selection, a mechanism by which schizophrenia risk alleles could also provide advantages under certain environments, as a reliable explanation. However, recent studies have shown strong evidence against a positive selection of predisposing loci. Furthermore, evolutionary pressures on schizophrenia risk alleles could have changed throughout human history as new environments emerged. Here in this study, we used 1000 Genomes Project data to explore the relationship between schizophrenia predisposing loci and recent natural selection (RNS) signatures after the human diaspora out of Africa around 100,000 years ago on a genome-wide scale. We found evidence for significant enrichment of RNS markers in derived alleles arisen during human evolution conferring protection to schizophrenia. Moreover, both partitioned heritability and gene set enrichment analyses of mapped genes from schizophrenia predisposing loci subject to RNS revealed a lower involvement in brain and neuronal related functions compared to those not subject to RNS. Taken together, our results suggest non-antagonistic pleiotropy as a likely mechanism behind RNS that could explain the persistence of schizophrenia common predisposing variation in human populations due to its association to other non-psychiatric phenotypes.

An overview of clustering methods with guidelines for application in mental health research

Cluster analyzes have been widely used in mental health research to decompose inter-individual heterogeneity by identifying more homogeneous subgroups of individuals. However, despite advances in new algorithms and increasing popularity, there is little guidance on model choice, analytical framework and reporting requirements. In this paper, we aimed to address this gap by introducing the philosophy, design, advantages/disadvantages and implementation of major algorithms that are particularly relevant in mental health research. Extensions of basic models, such as kernel methods, deep learning, semi-supervised clustering, and clustering ensembles are subsequently introduced. How to choose algorithms to address common issues as well as methods for pre-clustering data processing, clustering evaluation and validation are then discussed. Importantly, we also provide general guidance on clustering workflow and reporting requirements. To facilitate the implementation of different algorithms, we provide information on R functions and libraries.

Estimating the direct effects of the genetic liabilities to bipolar disorder, schizophrenia, and behavioral traits on suicide attempt using a multivariable Mendelian randomization approach

Bipolar disorder (BD) and schizophrenia (SZ) are associated with higher odds of suicide attempt (SA). In this study, we aimed to explore the effect of BD and SZ genetic liabilities on SA, also considering the contribution of behavioral traits, socioeconomic factors, and substance use disorders. Leveraging large-scale genome-wide association data from the Psychiatric Genomics Consortium (PGC) and the UK Biobank (UKB), we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the putative causal effect of BD (41,917 cases, 371,549 controls) and SZ (53,386 cases, 77,258 controls) on SA (26,590 cases, 492,022 controls). Then, we assessed the putative causal effect of BD and SZ on behavioral traits, socioeconomic factors, and substance use disorders. Considering the associations identified, we evaluated the direct causal effect of behavioral traits, socioeconomic factors, and substance use disorders on SA using a multivariable MR approach. The genetic liabilities to BD and SZ were associated with higher odds of SA (BD odds ratio (OR)=1.24, p=3.88×10-12; SZ OR=1.09, p=2.44×10-20). However, while the effect of mental distress (OR=1.17, p=1.02×10-4) and risk-taking (OR=1.52, p=0.028) on SA was independent of SZ genetic liability, the BD-SA relationship appeared to account for the effect of these risk factors. Similarly, the association with loneliness on SA was null after accounting for the effect of SZ genetic liability. These findings highlight the complex interplay between genetic risk of psychiatric disorders and behavioral traits in the context of SA, suggesting the need for a comprehensive mental health assessment for high-risk individuals.

Polygenic contributions to performance on the Balloon Analogue Risk Task

Risky decision-making is a common, heritable endophenotype seen across many psychiatric disorders. Its underlying genetic architecture is incompletely explored. We examined behavior in the Balloon Analogue Risk Task (BART), which tests risky decision-making, in two independent samples of European ancestry. One sample (n = 1138) comprised healthy participants and some psychiatric patients (53 schizophrenia, 42 bipolar disorder, 47 ADHD); the other (n = 911) excluded for recent treatment of various psychiatric disorders but not ADHD. Participants provided DNA and performed the BART, indexed by mean adjusted pumps. We constructed a polygenic risk score (PRS) for discovery in each dataset and tested it in the other as replication. Subsequently, a genome-wide MEGA-analysis, combining both samples, tested genetic correlation with risk-taking self-report in the UK Biobank sample and psychiatric phenotypes characterized by risk-taking (ADHD, Bipolar Disorder, Alcohol Use Disorder, prior cannabis use) in the Psychiatric Genomics Consortium. The PRS for BART performance in one dataset predicted task performance in the replication sample (r = 0.13, p = 0.000012, pFDR = 0.000052), as did the reciprocal analysis (r = 0.09, p = 0.0083, pFDR=0.04). Excluding participants with psychiatric diagnoses produced similar results. The MEGA-GWAS identified a single SNP (rs12023073; p = 3.24 × 10-8) near IGSF21, a protein involved in inhibitory brain synapses; replication samples are needed to validate this result. A PRS for self-reported cannabis use (p = 0.00047, pFDR = 0.0053), but not self-reported risk-taking or psychiatric disorder status, predicted behavior on the BART in our MEGA-GWAS sample. The findings reveal polygenic architecture of risky decision-making as measured by the BART and highlight its overlap with cannabis use.

Cognitive impairment in schizophrenia: aetiology, pathophysiology, and treatment

Cognitive deficits are a core feature of schizophrenia, account for much of the impaired functioning associated with the disorder and are not responsive to existing treatments. In this review, we first describe the clinical presentation and natural history of these deficits. We then consider aetiological factors, highlighting how a range of similar genetic and environmental factors are associated with both cognitive function and schizophrenia. We then review the pathophysiological mechanisms thought to underlie cognitive symptoms, including the role of dopamine, cholinergic signalling and the balance between GABAergic interneurons and glutamatergic pyramidal cells. Finally, we review the clinical management of cognitive impairments and candidate novel treatments.

Genome-wide association study of population-standardised cognitive performance phenotypes in a rural South African community

Cognitive function is an indicator for global physical and mental health, and cognitive impairment has been associated with poorer life outcomes and earlier mortality. A standard cognition test, adapted to a rural-dwelling African community, and the Oxford Cognition Screen-Plus were used to capture cognitive performance as five continuous traits (total cognition score, verbal episodic memory, executive function, language, and visuospatial ability) for 2,246 adults in this population of South Africans. A novel common variant, rs73485231, reached genome-wide significance for association with episodic memory using data for ~14 million markers imputed from the H3Africa genotyping array data. Window-based replication of previously implicated variants and regions of interest support the discovery of African-specific associated variants despite the small population size and low allele frequency. This African genome-wide association study identifies suggestive associations with general cognition and domain-specific cognitive pathways and lays the groundwork for further genomic studies on cognition in Africa.

Association between mitochondria-related genes and cognitive performance in the PsyCourse Study

BACKGROUND

Mitochondria generate energy through oxidative phosphorylation (OXPHOS). The function of key OXPHOS proteins can be altered by variation in mitochondria-related genes, which may increase the risk of mental illness. We investigated the association of mitochondria-related genes and their genetic risk burden with cognitive performance.

METHODS

We leveraged cross-sectional data from 1320 individuals with a severe psychiatric disorder and 466 neurotypical individuals from the PsyCourse Study. The cognitive tests analyzed were the Trail-Making Test, Verbal Digit Span Test, Digit-Symbol Test, and Multiple Choice Vocabulary Intelligence Test. Association analyses between the cognitive tests, and single-nucleotide polymorphisms (SNPs) mapped to mitochondria-related genes, and their polygenic risk score (PRS) for schizophrenia (SCZ) were performed with PLINK 1.9 and R program.

RESULTS

We found a significant association (FDR-adjusted p < 0.05) in the Cytochrome C Oxidase Assembly Factor 8 (COA8) gene locus of the OXPHOS pathway with the Verbal Digit Span (forward) test. Mitochondrial PRS was not significantly associated with any of the cognitive tests.

LIMITATIONS

Moderate statistical power due to relatively small sample size.

CONCLUSIONS

COA8 encodes a poorly characterized mitochondrial protein involved in apoptosis. Here, this gene was associated with the Verbal Digit Span (forward) test, which evaluates short-term memory. Our results warrant replication and may lead to better understanding of cognitive impairment in mental disorders.

Shared genetic architecture between attention-deficit/hyperactivity disorder and lifespan

There is evidence linking ADHD to a reduced life expectancy. The mortality rate in individuals with ADHD is twice that of the general population and it is associated with several factors, such as unhealthy lifestyle behaviors, social adversity, and mental health problems that may in turn increase mortality rates. Since ADHD and lifespan are heritable, we used data from genome-wide association studies (GWAS) of ADHD and parental lifespan, as proxy of individual lifespan, to estimate their genetic correlation, identify genetic loci jointly associated with both phenotypes and assess causality. We confirmed a negative genetic correlation between ADHD and parental lifespan (rg = -0.36, P = 1.41e-16). Nineteen independent loci were jointly associated with both ADHD and parental lifespan, with most of the alleles that increased the risk for ADHD being associated with shorter lifespan. Fifteen loci were novel for ADHD and two were already present in the original GWAS on parental lifespan. Mendelian randomization analyses pointed towards a negative causal effect of ADHD liability on lifespan (P = 1.54e-06; Beta = -0.07), although these results were not confirmed by all sensitivity analyses performed, and further evidence is required. The present study provides the first evidence of a common genetic background between ADHD and lifespan, which may play a role in the reported effect of ADHD on premature mortality risk. These results are consistent with previous epidemiological data describing reduced lifespan in mental disorders and support that ADHD is an important health condition that could negatively affect future life outcomes.

The interplay between micro RNAs and genetic liability to Alzheimer's Disease on memory trajectories in the general population

Deficits in cognitive function and memory are common early symptoms of neurodegenerative disorders, such as Alzheimer's Disease (AD). Several studies have discussed micro RNAs (miRNAs) as potential epigenetic early detection biomarkers. In a longitudinal general population sample (n = 548) from the Study of Health in Pomerania, we analyzed the associations between 167 baseline miRNA levels and changes in verbal memory scores with a mean follow-up time of 7.4 years. We additionally assessed the impact of an individual's genetic liability for AD on verbal memory scores in n = 2,334 subjects and a possible interactions between epigenetic and genetic markers. Results revealed two miRNAs associated with changes in immediate verbal memory over time. In interaction analyses between miRNAs and a polygenic risk score for AD, five miRNAs showed a significant interaction effect on changes in verbal memory. All of these miRNAs have previously been identified in the context of AD, neurodegeneration or cognition. Our study provides candidate miRNAs for a decline in verbal memory as an early symptom of neurodegeneration and AD. Further experimental studies are needed to verify the diagnostic value of these miRNA markers in the prodromal stage of AD.

Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder

BACKGROUND

Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.

METHODS

We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.

RESULTS

We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).

CONCLUSIONS

Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.

The shared genetic architecture of suicidal behaviour and psychiatric disorders: A genomic structural equation modelling study

Background: Suicidal behaviour (SB) refers to behaviours, ranging from non-fatal suicidal behaviour, such as suicidal ideation and attempt, to completed suicide. Despite recent advancements in genomic technology and statistical methods, it is unclear to what extent the spectrum of suicidal behaviour is explained by shared genetic aetiology. Methods: We identified nine genome-wide association statistics of suicidal behaviour (sample sizes, n, ranging from 62,648 to 125,844), ten psychiatric traits [n up to 386,533] and collectively, nine summary datasets of anthropometric, behavioural and socioeconomic-related traits [n ranging from 58,610 to 941,280]. We calculated the genetic correlation among these traits and modelled this using genomic structural equation modelling, identified shared biological processes and pathways between suicidal behaviour and psychiatric disorders and evaluated potential causal associations using Mendelian randomisation. Results: Among populations of European ancestry, we observed strong positive genetic correlations between suicide ideation, attempt and self-harm (rg range, 0.71-1.09) and moderate to strong genetic correlations between suicidal behaviour traits and a range of psychiatric disorders, most notably, major depression disorder (rg = 0.86, p = 1.62 × 10^-36). Multivariate analysis revealed a common factor structure for suicidal behaviour traits, major depression, attention deficit hyperactivity disorder (ADHD) and alcohol use disorder. The derived common factor explained 38.7% of the shared variance across the traits. We identified 2,951 genes and 98 sub-network hub genes associated with the common factor, including pathways associated with developmental biology, signal transduction and RNA degradation. We found suggestive evidence for the protective effects of higher household income level on suicide attempt [OR = 0.55 (0.44-0.70), p = 1.29 × 10^-5] and while further investigation is needed, a nominal significant effect of smoking on suicide attempt [OR = 1.24 (1.04-1.44), p = 0.026]. Conclusion: Our findings provide evidence of shared aetiology between suicidal behaviour and psychiatric disorders and indicate potential common molecular mechanisms contributing to the overlapping pathophysiology. These findings provide a better understanding of the complex genetic architecture of suicidal behaviour and have implications for the prevention and treatment of suicidal behaviour.

A genome-wide association study of tinnitus reveals shared genetic links to neuropsychiatric disorders

Tinnitus, a phantom perception of sound in the absence of any external sound source, is a prevalent health condition often accompanied by psychiatric comorbidities. Recent genome-wide association studies (GWAS) highlighted a polygenic nature of tinnitus susceptibility. A shared genetic component between tinnitus and psychiatric conditions remains elusive. Here we present a GWAS using the UK Biobank to investigate the genetic processes linked to tinnitus and tinnitus-related distress, followed by gene-set enrichment analyses. The UK Biobank sample comprised 132,438 individuals with tinnitus and genotype data. Among the study sample, 38,525 individuals reported tinnitus, and 26,889 participants mentioned they experienced tinnitus-related distress in daily living. The genome-wide association analyses were conducted on tinnitus and tinnitus-related distress. We conducted enrichment analyses using FUMA to further understand the genetic processes linked to tinnitus and tinnitus-related distress. A genome-wide significant locus (lead SNP: rs71595470) for tinnitus was obtained in the vicinity of GPM6A. Nineteen independent loci reached suggestive association with tinnitus. Fifteen independent loci reached suggestive association with tinnitus-related distress. The enrichment analysis revealed a shared genetic component between tinnitus and psychiatric traits, such as bipolar disorder, feeling worried, cognitive ability, fast beta electroencephalogram, and sensation seeking. Metabolic, cardiovascular, hematological, and pharmacological gene sets revealed a significant association with tinnitus. Anxiety and stress-related gene sets revealed a significant association with tinnitus-related distress. The GWAS signals for tinnitus were enriched in the hippocampus and cortex, and for tinnitus-related distress were enriched in the brain and spinal cord. This study provides novel insights into genetic processes associated with tinnitus and tinnitus-related distress and demonstrates a shared genetic component underlying tinnitus and psychiatric conditions. Further collaborative attempts are necessary to identify genetic components underlying the phenotypic heterogeneity in tinnitus and provide biological insight into the etiology.

Collective genomic segments with differential pleiotropic patterns between cognitive dimensions and psychopathology

Cognitive deficits are known to be related to most forms of psychopathology. Here, we perform local genetic correlation analysis as a means of identifying independent segments of the genome that show biologically interpretable pleiotropic associations between cognitive dimensions and psychopathology. We identify collective segments of the genome, which we call "meta-loci", showing differential pleiotropic patterns for psychopathology relative to either cognitive task performance (CTP) or performance on a non-cognitive factor (NCF) derived from educational attainment. We observe that neurodevelopmental gene sets expressed during the prenatal-early childhood period predominate in CTP-relevant meta-loci, while post-natal gene sets are more involved in NCF-relevant meta-loci. Further, we demonstrate that neurodevelopmental gene sets are dissociable across CTP meta-loci with respect to their spatial distribution across the brain. Additionally, we find that GABA-ergic, cholinergic, and glutamatergic genes drive pleiotropic relationships within dissociable meta-loci.

Upper cortical layer-driven network impairment in schizophrenia

Schizophrenia is one of the most widespread and complex mental disorders. To characterize the impact of schizophrenia, we performed single-nucleus RNA sequencing (snRNA-seq) of >220,000 neurons from the dorsolateral prefrontal cortex of patients with schizophrenia and matched controls. In addition, >115,000 neurons were analyzed topographically by immunohistochemistry. Compositional analysis of snRNA-seq data revealed a reduction in abundance of GABAergic neurons and a concomitant increase in principal neurons, most pronounced for upper cortical layer subtypes, which was substantiated by histological analysis. Many neuronal subtypes showed extensive transcriptomic changes, the most marked in upper-layer GABAergic neurons, including down-regulation in energy metabolism and up-regulation in neurotransmission. Transcription factor network analysis demonstrated a developmental origin of transcriptomic changes. Last, Visium spatial transcriptomics further corroborated upper-layer neuron vulnerability in schizophrenia. Overall, our results point toward general network impairment within upper cortical layers as a core substrate associated with schizophrenia symptomatology.

Epigenome-wide association study of global cortical volumes in generation Scotland: Scottish family health study

A complex interplay of genetic and environmental risk factors influence global brain structural alterations associated with brain health and disease. Epigenome-wide association studies (EWAS) of global brain imaging phenotypes have the potential to reveal the mechanisms of brain health and disease and can lead to better predictive analytics through the development of risk scores.We perform an EWAS of global brain volumes in Generation Scotland using peripherally measured whole blood DNA methylation (DNAm) from two assessments, (i) at baseline recruitment, ~6 years prior to MRI assessment (N = 672) and (ii) concurrent with MRI assessment (N=565). Four CpGs at baseline were associated with global cerebral white matter, total grey matter, and whole-brain volume (Bonferroni p≤7.41×10-8, βrange = -1.46x10-6 to 9.59 × 10-7). These CpGs were annotated to genes implicated in brain-related traits, including psychiatric disorders, development, and ageing. We did not find significant associations in the meta-analysis of the EWAS of the two sets concurrent with imaging at the corrected level.These findings reveal global brain structural changes associated with DNAm measured ~6 years previously, indicating a potential role of early DNAm modifications in brain structure. Although concurrent DNAm was not associated with global brain structure, the nominally significant findings identified here present a rationale for future investigation of associations between DNA methylation and structural brain phenotypes in larger population-based samples.

Does better education mitigate risky health behavior? A mendelian randomization study

Education and risky health behaviors are strongly negatively correlated. Education may affect health behaviors by enabling healthier choices through higher disposable income, increasing information about the harmful effects of risky health behaviors, or altering time preferences. Alternatively, the observed negative correlation may stem from reverse causality or unobserved confounders. Based on the data from the Cardiovascular Risk in Young Finns Study linked to register-based information on educational attainment and family background, this paper identifies the causal effect of education on risky health behaviors. To examine causal effects, we used a genetic score as an instrument for years of education. We found that individuals with higher education allocated more attention to healthy habits. In terms of health behaviors, highly educated people were less likely to smoke. Some model specifications also indicated that the highly educated consumed more fruit and vegetables, but the results were imprecise in this regard. No causal effect was found between education and abusive drinking. In brief, inference based on genetic instruments showed that higher education leads to better choices in some but not all dimensions of health behaviors.

Age-dependent patterns of schizophrenia genetic risk affect cognition

Cognition shares substantial genetic overlap with schizophrenia, yet it remains unclear whether such genetic effects become significant during developmental periods of elevated risk for schizophrenia, such as the peak age of onset. We introduce an investigative framework integrating epidemiological, developmental, and genetic approaches to determine whether genetic effects shared between schizophrenia and cognition are significant across periods of differing risk for schizophrenia onset, and whether these effects are shared with depression. 771 European-American participants, including 636 (ages 15-84 years) from families with at least two first-degree relatives with schizophrenia and 135 unrelated controls, were divided into three age-risk groups based on ages relative to epidemiological age of onset patterns for schizophrenia: Pre-Peak (before peak age-of-onset: 15 to 22 years), Post-Peak (after peak age-of-onset: 23-42 years), and Plateau (during plateau of age-of-onset: over 42 years). For general cognition and 11 specific cognitive traits, we estimated genetic correlations with schizophrenia and with depression within each age-risk group. Genetic effects shared between deficits in general cognition and schizophrenia were nonsignificant before peak age of onset, yet were high and significant after peak age of onset and during the plateau of onset. These age-dependent genetic effects were largely consistent across specific cognitive traits and not transdiagnostically shared with depression. Schizophrenia genetic effects appear to influence cognitive traits in an age-dependent manner, supporting late developmental and perhaps neurodegenerative models that hypothesize increased expression of schizophrenia risk genes during and after the peak age of risk. Our findings underscore the utility of cognitive traits for tracking schizophrenia genetic effects across the lifespan.

Integration of multidimensional splicing data and GWAS summary statistics for risk gene discovery

A common strategy for the functional interpretation of genome-wide association study (GWAS) findings has been the integrative analysis of GWAS and expression data. Using this strategy, many association methods (e.g., PrediXcan and FUSION) have been successful in identifying trait-associated genes via mediating effects on RNA expression. However, these approaches often ignore the effects of splicing, which can carry as much disease risk as expression. Compared to expression data, one challenge to detect associations using splicing data is the large multiple testing burden due to multidimensional splicing events within genes. Here, we introduce a multidimensional splicing gene (MSG) approach, which consists of two stages: 1) we use sparse canonical correlation analysis (sCCA) to construct latent canonical vectors (CVs) by identifying sparse linear combinations of genetic variants and splicing events that are maximally correlated with each other; and 2) we test for the association between the genetically regulated splicing CVs and the trait of interest using GWAS summary statistics. Simulations show that MSG has proper type I error control and substantial power gains over existing multidimensional expression analysis methods (i.e., S-MultiXcan, UTMOST, and sCCA+ACAT) under diverse scenarios. When applied to the Genotype-Tissue Expression Project data and GWAS summary statistics of 14 complex human traits, MSG identified on average 83%, 115%, and 223% more significant genes than sCCA+ACAT, S-MultiXcan, and UTMOST, respectively. We highlight MSG's applications to Alzheimer's disease, low-density lipoprotein cholesterol, and schizophrenia, and found that the majority of MSG-identified genes would have been missed from expression-based analyses. Our results demonstrate that aggregating splicing data through MSG can improve power in identifying gene-trait associations and help better understand the genetic risk of complex traits.

Ancestry-inclusive dog genomics challenges popular breed stereotypes

Behavioral genetics in dogs has focused on modern breeds, which are isolated subgroups with distinctive physical and, purportedly, behavioral characteristics. We interrogated breed stereotypes by surveying owners of 18,385 purebred and mixed-breed dogs and genotyping 2155 dogs. Most behavioral traits are heritable [heritability (h²) > 25%], and admixture patterns in mixed-breed dogs reveal breed propensities. Breed explains just 9% of behavioral variation in individuals. Genome-wide association analyses identify 11 loci that are significantly associated with behavior, and characteristic breed behaviors exhibit genetic complexity. Behavioral loci are not unusually differentiated in breeds, but breed propensities align, albeit weakly, with ancestral function. We propose that behaviors perceived as characteristic of modern breeds derive from thousands of years of polygenic adaptation that predates breed formation, with modern breeds distinguished primarily by aesthetic traits.

Different responses to risperidone treatment in Schizophrenia: a multicenter genome-wide association and whole exome sequencing joint study

Risperidone is routinely used in the clinical management of schizophrenia, but the treatment response is highly variable among different patients. The genetic underpinnings of the treatment response are not well understood. We performed a pharmacogenomic study of the treatment response to risperidone in patients with schizophrenia by using a SNP microarray -based genome-wide association study (GWAS) and whole exome sequencing (WES)-based GWAS. DNA samples were collected from 189 patients for the GWAS and from 222 patients for the WES after quality control in multiple centers of China. Antipsychotic response phenotypes of patients who received eight weeks of risperidone treatment were quantified with percentage change on the Positive and Negative Syndrome Scale (PANSS). The GWAS revealed a significant association between several SNPs and treatment response, such as three GRM7 SNPs (rs141134664, rs57521140, and rs73809055). Gene-based analysis in WES revealed 13 genes that were associated with antipsychotic response, such as GPR12 and MAP2K3. We did not identify shared loci or genes between GWAS and WES, but association signals tended to cluster into the GPCR gene family and GPCR signaling pathway, which may play an important role in the treatment response etiology. This study may provide a research paradigm for pharmacogenomic research, and these data provide a promising illustration of our potential to identify genetic variants underlying antipsychotic responses and may ultimately facilitate precision medicine in schizophrenia.

Annual Research Review: The transdiagnostic revolution in neurodevelopmental disorders

Practitioners frequently use diagnostic criteria to identify children with neurodevelopmental disorders and to guide intervention decisions. These criteria also provide the organising framework for much of the research focussing on these disorders. Study design, recruitment, analysis and theory are largely built on the assumption that diagnostic criteria reflect an underlying reality. However, there is growing concern that this assumption may not be a valid and that an alternative transdiagnostic approach may better serve our understanding of this large heterogeneous population of young people. This review draws on important developments over the past decade that have set the stage for much-needed breakthroughs in understanding neurodevelopmental disorders. We evaluate contemporary approaches to study design and recruitment, review the use of data-driven methods to characterise cognition, behaviour and neurobiology, and consider what alternative transdiagnostic models could mean for children and families. This review concludes that an overreliance on ill-fitting diagnostic criteria is impeding progress towards identifying the barriers that children encounter, understanding underpinning mechanisms and finding the best route to supporting them.

Gene-based association tests using GWAS summary statistics and incorporating eQTL

Although genome-wide association studies (GWAS) have been successfully applied to a variety of complex diseases and identified many genetic variants underlying complex diseases via single marker tests, there is still a considerable heritability of complex diseases that could not be explained by GWAS. One alternative approach to overcome the missing heritability caused by genetic heterogeneity is gene-based analysis, which considers the aggregate effects of multiple genetic variants in a single test. Another alternative approach is transcriptome-wide association study (TWAS). TWAS aggregates genomic information into functionally relevant units that map to genes and their expression. TWAS is not only powerful, but can also increase the interpretability in biological mechanisms of identified trait associated genes. In this study, we propose a powerful and computationally efficient gene-based association test, called Overall. Using extended Simes procedure, Overall aggregates information from three types of traditional gene-based association tests and also incorporates expression quantitative trait locus (eQTL) information into a gene-based association test using GWAS summary statistics. We show that after a small number of replications to estimate the correlation among the integrated gene-based tests, the p values of Overall can be calculated analytically. Simulation studies show that Overall can control type I error rates very well and has higher power than the tests that we compared with. We also apply Overall to two schizophrenia GWAS summary datasets and two lipids GWAS summary datasets. The results show that this newly developed method can identify more significant genes than other methods we compared with.

The "Golden Age" of Behavior Genetics?

The search for genetic risk factors underlying the presumed heritability of all human behavior has unfolded in two phases. The first phase, characterized by candidate-gene-association (CGA) studies, has fallen out of favor in the behavior-genetics community, so much so that it has been referred to as a "cautionary tale." The second and current iteration is characterized by genome-wide association studies (GWASs), single-nucleotide polymorphism (SNP) heritability estimates, and polygenic risk scores. This research is guided by the resurrection of, or reemphasis on, Fisher's "infinite infinitesimal allele" model of the heritability of complex phenotypes, first proposed over 100 years ago. Despite seemingly significant differences between the two iterations, they are united in viewing the discovery of risk alleles underlying heritability as a matter of finding differences in allele frequencies. Many of the infirmities that beset CGA studies persist in the era of GWASs, accompanied by a host of new difficulties due to the human genome's underlying complexities and the limitations of Fisher's model in the postgenomics era.

Involvement of the long intergenic non-coding RNA LINC00461 in schizophrenia

OBJECTIVE

LINC00461 is a highly conserved intergenic non-protein coding RNA that was implicated in schizophrenia at the genome-wide level. We aim to explore potential mechanisms underlying the involvement of LINC00461 in schizophrenia.

METHODS

We performed a meta-analysis to investigate the association of LINC00461 rs410216 with schizophrenia, and evaluate the effects of the rs410216 on hippocampal volume and function using the functional magnetic resonance imaging (fMRI) analysis. We utilized the GTEx dataset to profile the expression distribution of LINC00461 across different brain regions, and to investigate the potential impact of the risk SNPs on the expression of LINC00461 and other nearby genes. We compared blood expression levels of LINC00461 between schizophrenia patients and controls.

RESULTS

Here we show that single-nucleotide polymorphisms (SNPs) located in regulatory elements spanning the LINC00461 region are significantly associated with schizophrenia (index SNP rs410216, P_meta = 1.43E-05); subjects carrying the risk allele of rs410216 showed decreased hippocampal volume. However, no significant association of the rs410216 variant with hippocampal activation was observed. Moreover, the expression level of LINC00461 mRNA was significantly lower in first-onset schizophrenia patients, and the risk allele also predicts a lower transcriptional level of LINC00461 in the hippocampus.

CONCLUSION

Together, these convergent lines of evidence implicate inadequate LINC00461 expression in the hippocampus in the development of schizophrenia, providing novel insight into the genetic architecture and biological etiology of schizophrenia.

Developmental Brain Asymmetry. The Good and the Bad Sides

Brain asymmetry is a hallmark of the human brain. Recent studies report a certain degree of abnormal asymmetry of brain lateralization between left and right brain hemispheres can be associated with many neuropsychiatric conditions. In this regard, some questions need answers. First, the accelerated brain asymmetry is programmed during the pre-natal period that can be called “accelerated brain decline clock”. Second, can we find the right biomarkers to predict these changes? Moreover, can we establish the dynamics of these changes in order to identify the right time window for proper interventions that can reverse or limit the neurological decline? To find answers to these questions, we performed a systematic online search for the last 10 years in databases using keywords. Conclusion: we need to establish the right in vitro model that meets human conditions as much as possible. New biomarkers are necessary to establish the “good” or the “bad” borders of brain asymmetry at the epigenetic and functional level as early as possible.