Schizophrenia Genome-wide Association Studies Research Articles

Associations of schizophrenia with arrhythmic disorders and electrocardiogram traits: genetic exploration of population samples.

An important contributor to the decreased life expectancy of individuals with schizophrenia is sudden cardiac death. Arrhythmic disorders may play an important role herein, but the nature of the relationship between schizophrenia and arrhythmia is unclear. To assess shared genetic liability and potential causal effects between schizophrenia and arrhythmic disorders and electrocardiogram (ECG) traits. We leveraged summary-level data of large-scale genome-wide association studies of schizophrenia (53 386 cases, 77 258 controls), arrhythmic disorders (atrial fibrillation, 55 114 cases, 482 295 controls; Brugada syndrome, 2820 cases, 10 001 controls) and ECG traits (heart rate (variability), PR interval, QT interval, JT interval and QRS duration, n = 46 952-293 051). We examined shared genetic liability by assessing global and local genetic correlations and conducting functional annotation. Bidirectional causal relations between schizophrenia and arrhythmic disorders and ECG traits were explored using Mendelian randomisation. There was no evidence for global genetic correlation, except between schizophrenia and Brugada syndrome (rg = 0.14, 95% CIs = 0.06-0.22, P = 4.0E-04). In contrast, strong positive and negative local correlations between schizophrenia and all cardiac traits were found across the genome. In the most strongly associated regions, genes related to immune and viral response mechanisms were overrepresented. Mendelian randomisation indicated that liability to schizophrenia causally increases Brugada syndrome risk (beta = 0.14, CIs = 0.03-0.25, P = 0.009) and heart rate during activity (beta = 0.25, CIs = 0.05-0.45, P = 0.015). Despite little evidence for global genetic correlation, specific genomic regions and biological pathways emerged that are important for both schizophrenia and arrhythmia. The putative causal effect of liability to schizophrenia on Brugada syndrome warrants increased cardiac monitoring and early medical intervention in people with schizophrenia.

Etiology of Cognitive Deficits in Schizophrenia: a Review of Studies Based on Polygenic Risk Scores

Background: cognitive deficits in schizophrenia have long been believed to reflect the influence of genetic predisposition to the disease. Schizophrenia genome-wide association studies of the last decade have made it possible to test this hypothesis. The aim: to analyze studies on the relationship between cognitive impairment in schizophrenia patients and polygenic risk scores for schizophrenia (SZ-PRS). Additionally, the associations of PRS for intelligence with cognitive deficits in patients and the associations of SZ-PRS with cognitive functions in healthy people were considered. Material and methods: the literature search was carried out in the PubMed database using the following terms: (schizophr* OR schizoaffective* OR psychosis) AND (cogn* OR intelligence OR IQ) AND (GWAS OR polygenic). Results and discussion: from papers published between January 2015 and February 2024, 40 publications met the inclusion criteria. Their analysis indicate that in schizophrenia patients, in contrast to healthy people, the correlation of SZ-PRS with cognitive deficits and premorbid cognitive abilities is absent. Cognitive functions of patients are associated with PRS of intelligence, however, the bulk of the variance in cognitive deficits in schizophrenia, except for the group with intellectual disability, appears to be associated with non-genetic causes. It can be assumed that disease process factors play the most important role. Future studies should be aimed at establishing whether they are directly related to the pathophysiology of the disease, to the influence of concomitant exposures (treatment, hospitalization, etc.) or cognitive reserve, which will contribute to the correction of cognitive deficits.

Sex-specific association between schizophrenia polygenic risk and subclinical schizophrenia-related traits

BackgroundAccording to the dimensional view of psychiatric disorders, psychosis is expressed as a continuum in the general population. However, the investigation of the putative genetic aetiological continuity between its clinical and subclinical phenotypes has yielded mixed results. We aimed to replicate previous findings regarding the association of polygenic risk for schizophrenia with subclinical traits (i.e., schizotypy traits and psychotic-like experiences), and to examine the role of sex in this association in a large nonclinical sample. MethodsThe Multidimensional Schizotypy Scale and the Community Assessment of Psychic Experiences were assessed in 919 nonclinical participants. Polygenic Risk Scores for schizophrenia (SZ-PRSs) were computed using the PRS-CS method based on the latest genome-wide association study of schizophrenia. Summary statistics derived from the total GWAS sample and stratified by sex were used. Linear regression analyses tested the associations of the SZ-PRSs with the psychometric variables, both in the total sample and by sex. ResultsNo associations were found between the SZ-PRSs and the positive, negative or disorganized dimensions of schizotypy in the total sample. Likewise, no associations were found with psychotic-like experiences. However, the sex-stratified analyses revealed a male-specific association with positive schizotypy. Similar results were obtained with the PRSs derived from the sex-stratified summary statistics. DiscussionOur results are consistent with the lack of clear evidence of an association between SZ common genetic risk and its subclinical phenotypes. Nevertheless, the male-specific association found suggests that this PRS might explain better the male phenotype, as reported in previous studies. Future studies should put a focus on the role of sex in this association to unravel its sex specificities.

Cross-ancestry analysis of brain QTLs enhances interpretation of schizophrenia genome-wide association studies

Research on brain expression quantitative trait loci (eQTLs) has illuminated the genetic underpinnings of schizophrenia (SCZ). Yet most of these studies have been centered on European populations, leading to a constrained understanding of population diversities and disease risks. To address this gap, we examined genotype and RNA-seq data from African Americans (AA, n= 158), Europeans (EUR, n= 408), and East Asians (EAS, n= 217). When comparing eQTLs between EUR and non-EUR populations, we observed concordant patterns of genetic regulatory effect, particularly in terms of the effect sizes of the eQTLs. However, 343,737 cis-eQTLs linked to 1,276 genes and 198,769 SNPs were found to be specific to non-EUR populations. Over 90% of observed population differences in eQTLs could be traced back to differences in allele frequency. Furthermore, 35% of these eQTLs were notably rare in the EUR population. Integrating brain eQTLs with SCZ signals from diverse populations, we observed a higher disease heritability enrichment of brain eQTLs in matched populations compared to mismatched ones. Prioritization analysis identified five risk genes (SFXN2, VPS37B, DENR, FTCDNL1, and NT5DC2) and three potential regulatory variants in known risk genes (CNNM2, MTRFR, and MPHOSPH9) that were missed in the EUR dataset. Our findings underscore that increasing genetic ancestral diversity is more efficient for power improvement than merely increasing the sample size within single-ancestry eQTLs datasets. Such a strategy will not only improve our understanding of the biological underpinnings of population structures but also pave the way for the identification of risk genes in SCZ.

Relationship of metabolites and metabolic ratios with schizophrenia: a mendelian randomization study

BackgroundThis study aims to investigate the causal relationship of human plasma metabolites and metabolic ratios with schizophrenia (SCZ).MethodsWe employed Mendelian Randomization (MR) approach to comprehensively analyze two large-scale metabolomics and schizophrenia Genome-Wide Association Study (GWAS) datasets, incorporating a total of 1091 metabolites and 309 metabolic ratios, with 52017 schizophrenia patients and 75889 healthy controls. The inverse variance-weighted (IVW) method was utilized to estimate the causal relationship between exposure and outcome. To provide a more comprehensive evaluation, additional Mendelian Randomization (MR) approaches were employed, including MR-Egger regression, weighted median, simple mode, and weighted mode methods. These analyses assessed the causal effects between blood metabolites, metabolic ratios, and schizophrenia. Tests for pleiotropy and heterogeneity were conducted. False Discovery Rate (FDR) correction was applied to account for multiple comparisons and heterogeneity, ensuring the robustness and reliability of our findings. Consistent with previous studies, an FDR threshold of < 0.2 was considered suggestive of a causal relationship, while an FDR of < 0.05 was considered to indicate a significant causal relationship.ResultsThe final results revealed that a significant causal association was found between the levels of two metabolites and schizophrenia, Alliin (OR = 0.915, 95%CI = 0.879–0.953, P = 1.93 × 10− 5, FDR = 0.013) was associated with a decreased risk of schizophrenia, N-actylcitrulline (OR = 1.058, 95%CI = 1.034–1.083, P = 1.4 × 10− 6, FDR = 0.002) was associated with increased risk of schizophrenia. When adjusting FDR to 0.2, the results showed that 4 metabolite levels and 2 metabolite ratios were suggestively causally associated with a reduced risk of schizophrenia including 2-aminooctanoate (OR = 0.904, 95%CI = 0.847–0.964, P = 0.002, FDR = 0.160), N-lactoylvaline (OR = 0.853, 95%CI = 0.775–0.938, P = 0.001,FDR = 0.122), X − 21310 (OR = 0.917, 95%CI = 0.866–0.971, P = 0.003,FDR = 0.195), X − 26111 (OR = 0.932, 95%CI = 0.890–0.976, P = 0.003,FDR = 0.189), Arachidonate (20:4n6) to oleate to vaccenate (18:1) ratio (OR = 0.945, 95%CI = 0.914–0.977, P = 8.2 × 10− 4, FDR = 0.104), and Citrulline to ornithine ratio (OR = 0.924, 95%CI = 0.881–0.969, P = 0.001, FDR = 0.122), while 4 metabolite levels and 2 metabolite ratios were suggestively causally associated with an increased risk of schizophrenia including N2, N5-diacetylornithine (OR = 1.090, 95%CI = 1.031–1.153, P = 0.003, FDR = 0.185), N − acetyl − 2−aminooctanoate (OR = 1.069, 95%CI=(1.027–1.114, P = 0.001, FDR = 0.127), N − acetyl − 2−aminoadipate (OR = 1.081, 95%CI = 1.030–1.133, P = 0.001, FDR = 0.128), X − 13844 (OR = 1.110, 95%CI = 1.036–1.190, P = 0.003, FDR = 0.196), X − 24556 (OR = 1.083, 95%CI = 1.036–1.132, P = 4.5 × 10− 4, FDR = 0.098), X − 24736 (OR = 1.065, 95%CI = 1.028–1.104, P = 5.6 × 10− 4, FDR = 0.098), N − acetylasparagine (OR = 1.048, 95%CI = 1.021–1.075, P = 4.5 × 10− 4, FDR = 0.098), N − acetylarginine (OR = 1.060, 95%CI = 1.028–1.092, P = 1.8 × 10− 4, FDR = 0.083), Cysteine to alanine ratio (OR = 1.086, 95%CI = 1.036–1.138, P = 6.5 × 10− 4, FDR = 0.101), and Benzoate to linoleoyl − arachidonoyl − glycerol (18:2 to 20:4) ratio (OR = 1.070, 95%CI = 1.025–1.117, P = 0.002, FDR = 0.158).ConclusionOur study results provide valuable insights for identifying diagnostic biomarkers related to schizophrenia and offer preliminary research findings for further exploration of the mechanisms linking schizophrenia and metabolism.

Direct targets of MEF2C are enriched for genes associated with schizophrenia and cognitive function and are involved in neuron development and mitochondrial function.

Myocyte Enhancer Factor 2C (MEF2C) is a transcription factor that plays a crucial role in neurogenesis and synapse development. Genetic studies have identified MEF2C as a gene that influences cognition and risk for neuropsychiatric disorders, including autism spectrum disorder (ASD) and schizophrenia (SCZ). Here, we investigated the involvement of MEF2C in these phenotypes using human-derived neural stem cells (NSCs) and glutamatergic induced neurons (iNs), which represented early and late neurodevelopmental stages. For these cellular models, MEF2C function had previously been disrupted, either by direct or indirect mutation, and gene expression assayed using RNA-seq. We integrated these RNA-seq data with MEF2C ChIP-seq data to identify dysregulated direct target genes of MEF2C in the NSCs and iNs models. Several MEF2C direct target gene-sets were enriched for SNP-based heritability for intelligence, educational attainment and SCZ, as well as being enriched for genes containing rare de novo mutations reported in ASD and/or developmental disorders. These gene-sets are enriched in both excitatory and inhibitory neurons in the prenatal and adult brain and are involved in a wide range of biological processes including neuron generation, differentiation and development, as well as mitochondrial function and energy production. We observed a trans expression quantitative trait locus (eQTL) effect of a single SNP at MEF2C (rs6893807, which is associated with IQ) on the expression of a target gene, BNIP3L. BNIP3L is a prioritized risk gene from the largest genome-wide association study of SCZ and has a function in mitophagy in mitochondria. Overall, our analysis reveals that either direct or indirect disruption of MEF2C dysregulates sets of genes that contain multiple alleles associated with SCZ risk and cognitive function and implicates neuron development and mitochondrial function in the etiology of these phenotypes.

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.

Genomic insights into the shared and distinct genetic architecture of cognitive function and schizophrenia

Cognitive impairment is a major determinant of functional outcomes in schizophrenia, however, understanding of the biological mechanisms underpinning cognitive dysfunction in the disorder remains incomplete. Here, we apply Genomic Structural Equation Modelling to identify latent cognitive factors capturing genetic liabilities to 12 cognitive traits measured in the UK Biobank. We identified three broad factors that underly the genetic correlations between the cognitive tests. We explore the overlap between latent cognitive factors, schizophrenia, and schizophrenia symptom dimensions using a complementary set of statistical approaches, applied to data from the latest schizophrenia genome-wide association study (Ncase = 53,386, Ncontrol = 77,258) and the Thematically Organised Psychosis study (Ncase = 306, Ncontrol = 1060). Global genetic correlations showed a significant moderate negative genetic correlation between each cognitive factor and schizophrenia. Local genetic correlations implicated unique genomic regions underlying the overlap between schizophrenia and each cognitive factor. We found substantial polygenic overlap between each cognitive factor and schizophrenia and biological annotation of the shared loci implicated gene-sets related to neurodevelopment and neuronal function. Lastly, we show that the common genetic determinants of the latent cognitive factors are not predictive of schizophrenia symptoms in the Norwegian Thematically Organized Psychosis cohort. Overall, these findings inform our understanding of cognitive function in schizophrenia by demonstrating important differences in the shared genetic architecture of schizophrenia and cognitive abilities.

Genetic Implication of Prenatal GABAergic and Cholinergic Neuron Development in Susceptibility to Schizophrenia.

The ganglionic eminences (GE) are fetal-specific structures that give rise to gamma-aminobutyric acid (GABA)- and acetylcholine-releasing neurons of the forebrain. Given the evidence for GABAergic, cholinergic, and neurodevelopmental disturbances in schizophrenia, we tested the potential involvement of GE neuron development in mediating genetic risk for the condition. We combined data from a recent large-scale genome-wide association study of schizophrenia with single-cell RNA sequencing data from the human GE to test the enrichment of schizophrenia risk variation in genes with high expression specificity for developing GE cell populations. We additionally performed the single nuclei Assay for Transposase-Accessible Chromatin with Sequencing (snATAC-Seq) to map potential regulatory genomic regions operating in individual cell populations of the human GE, using these to test for enrichment of schizophrenia common genetic variant liability and to functionally annotate non-coding variants-associated with the disorder. Schizophrenia common variant liability was enriched in genes with high expression specificity for developing neuron populations that are predicted to form dopamine D1 and D2 receptor-expressing GABAergic medium spiny neurons of the striatum, cortical somatostatin-positive GABAergic interneurons, calretinin-positive GABAergic neurons, and cholinergic neurons. Consistent with these findings, schizophrenia genetic risk was concentrated in predicted regulatory genomic sequence mapped in developing neuronal populations of the GE. Our study implicates prenatal development of specific populations of GABAergic and cholinergic neurons in later susceptibility to schizophrenia, and provides a map of predicted regulatory genomic elements operating in cells of the GE.

Genetic Implication of Specific Glutamatergic Neurons of the Prefrontal Cortex in the Pathophysiology of Schizophrenia

BackgroundThe prefrontal cortex (PFC) has been strongly implicated in the pathophysiology of schizophrenia. Here, we combined high-resolution single-nuclei RNA sequencing data from the human PFC with large-scale genomic data for schizophrenia to identify constituent cell populations likely to mediate genetic liability to the disorder. MethodsGene expression specificity values were calculated from a single-nuclei RNA sequencing dataset comprising 84 cell populations from the human PFC, spanning gestation to adulthood. Enrichment of schizophrenia common variant liability and burden of rare protein-truncating coding variants were tested in genes with high expression specificity for each cell type. We also explored schizophrenia common variant associations in relation to gene expression across the developmental trajectory of implicated neurons. ResultsCommon risk variation for schizophrenia was prominently enriched in genes with high expression specificity for a population of mature layer 4 glutamatergic neurons emerging in infancy. Common variant liability to schizophrenia increased along the developmental trajectory of this neuronal population. Fine-mapped genes at schizophrenia genome-wide association study risk loci had significantly higher expression specificity than other genes in these neurons and in a population of layer 5/6 glutamatergic neurons. People with schizophrenia had a higher rate of rare protein-truncating coding variants in genes expressed by cells of the PFC than control individuals, but no cell population was significantly enriched above this background rate. ConclusionsWe identified a population of layer 4 glutamatergic PFC neurons likely to be particularly affected by common variant genetic risk for schizophrenia, which may contribute to disturbances in thalamocortical connectivity in the condition.

Causal relationship between psychiatric disorders and sensorineural hearing loss: A bidirectional two-sample mendelian randomization analysis

ObjectiveThis study employed bidirectional two-sample Mendelian randomization (MR) to investigate the causal links between psychiatric disorders and sensorineural hearing loss (SNHL). MethodsInstrumental variables were chosen from genome-wide association studies of schizophrenia (SCH, N = 127,906), bipolar disorder (BD, N = 51,710), major depressive disorder (MDD, N = 500,199), and SNHL (N = 212,544). In the univariable MR analysis, the inverse-variance weighted method (IVW) was conducted as the primary analysis, complemented by various sensitivity analyses to ensure result robustness. ResultsSCH exhibited a decreased the risk of SNHL (OR = 0.949, P = 0.005), whereas BD showed an increased incidence of SNHL (OR = 1.145, P = 0.005). No causal association was found for MDD on SNHL (OR = 1.088, P = 0.246). Multivariable MR validated these results. In the reverse direction, genetically predicted SNHL was linked to a decreased risk of SCH with suggestive significance (OR = 0.912, P = 0.023). No reverse causal relationships were observed for SNHL influencing BD or MDD. These findings remained consistent across various MR methods and sensitivity analyses. ConclusionThis study demonstrated that the causal relationships between diverse psychiatric disorders with SNHL were heterogeneous. Specifically, SCH was inversely associated with SNHL susceptibility, and similarly, a reduced risk of SNHL was observed in schizophrenia patients. In contrast, BD exhibited an increased incidence of SNHL, although SNHL did not influence the prevalence of BD. No causal association between MDD and SNHL was found.

Methylome-wide and meQTL analysis helps to distinguish treatment response from non-response and pathogenesis markers in schizophrenia.

Schizophrenia is a complex condition with entwined genetic and epigenetic risk factors, posing a challenge to disentangle the intermixed pathological and therapeutic epigenetic signatures. To resolve this, we performed 850K methylome-wide and 700K genome-wide studies on the same set of schizophrenia patients by stratifying them into responders, non-responders, and drug-naïve patients. The key genes that signified the response were followed up using real-time gene expression studies to understand the effect of antipsychotics at the gene transcription level. The study primarily implicates hypermethylation in therapeutic response and hypomethylation in the drug-non-responsive state. Several differentially methylated sites and regions colocalized with the schizophrenia genome-wide association study (GWAS) risk genes and variants, supporting the convoluted gene-environment association. Gene ontology and protein-protein interaction (PPI) network analyses revealed distinct patterns that differentiated the treatment response from drug resistance. The study highlights the strong involvement of several processes related to nervous system development, cell adhesion, and signaling in the antipsychotic response. The ability of antipsychotic medications to alter the pathology by modulating gene expression or methylation patterns is evident from the general increase in the gene expression of response markers and histone modifiers and the decrease in class II human leukocyte antigen (HLA) genes following treatment with varying concentrations of medications like clozapine, olanzapine, risperidone, and haloperidol. The study indicates a directional overlap of methylation markers between pathogenesis and therapeutic response, thereby suggesting a careful distinction of methylation markers of pathogenesis from treatment response. In addition, there is a need to understand the trade-off between genetic and epigenetic observations. It is suggested that methylomic changes brought about by drugs need careful evaluation for their positive effects on pathogenesis, course of disease progression, symptom severity, side effects, and refractoriness.

Causal link between gut microbiome and schizophrenia: a Mendelian randomization study.

Some observational studies have shown that gut microbiome is significantly changed in patients with schizophrenia. We aim to identify the genetic causal link between gut microbiome and schizophrenia. A two-sample Mendelian randomization (MR) study was used to evaluate the causal link between gut microbiome and schizophrenia with 28 gut microbiome-associated genetic instrumental variants chosen from recent MR reports and the largest schizophrenia genome-wide association studies (8-Apr-22 release). Inverse variance weighted method showed that genetically increased Bacteroidales_S24-7 (per SD) resulted in increased risk of schizophrenia (OR = 1.110, 95% CI: [1.012-1.217], P = 0.027). Similarly, genetically increased Prevotellaceae promoted schizophrenia risk (OR = 1.124, 95% CI: [1.030-1.228], P = 0.009). However, genetically increased Lachnospiraceae reduced schizophrenia risk (OR = 0.878, 95% CI: [0.785-0.983], P = 0.023). In addition, schizophrenia risk was also suppressed by genetically increased Lactobacillaceae (OR = 0.878, 95% CI: [0.776-0.994], P = 0.040) and Verrucomicrobiaceae (OR = 0.860, 95% CI: [0.749-0.987], P = 0.032). Finally, we did not find any significant results in the causal association of other 23 gut microbiome with schizophrenia. Our analysis suggests that genetically increased Bacteroidales_S24-7 and Prevotellaceae promotes schizophrenia risk, whereas genetically increased Lachnospiraceae, Lactobacillaceae, and Verrucomicrobiaceae reduces schizophrenia risk. Thus, regulation of the disturbed intestinal microbiota may represent a new therapeutic strategy for patients with schizophrenia.

De Novo Variants Found in Three Distinct Schizophrenia Populations Hit a Common Core Gene Network Related to Microtubule and Actin Cytoskeleton Gene Ontology Classes.

Schizophrenia (SZ) is a heterogeneous and debilitating psychiatric disorder with a strong genetic component. To elucidate functional networks perturbed in schizophrenia, we analysed a large dataset of whole-genome studies that identified SNVs, CNVs, and a multi-stage schizophrenia genome-wide association study. Our analysis identified three subclusters that are interrelated and with small overlaps: GO:0007017~Microtubule-Based Process, GO:00015629~Actin Cytoskeleton, and GO:0007268~SynapticTransmission. We next analysed three distinct trio cohorts of 75 SZ Algerian, 45 SZ French, and 61 SZ Japanese patients. We performed Illumina HiSeq whole-exome sequencing and identified de novo mutations using a Bayesian approach. We validated 88 de novo mutations by Sanger sequencing: 35 in French, 21 in Algerian, and 32 in Japanese SZ patients. These 88 de novo mutations exhibited an enrichment in genes encoding proteins related to GO:0051015~actin filament binding (p = 0.0011) using David, and enrichments in GO: 0003774~transport (p = 0.019) and GO:0003729~mRNA binding (p = 0.010) using Amigo. One of these de novo variant was found in CORO1C coding sequence. We studied Coro1c haploinsufficiency in a Coro1c+/- mouse and found defects in the corpus callosum. These results could motivate future studies of the mechanisms surrounding genes encoding proteins involved in transport and the cytoskeleton, with the goal of developing therapeutic intervention strategies for a subset of SZ cases.

Enrichment of the Local Synaptic Translatome for Genetic Risk Associated With Schizophrenia and Autism Spectrum Disorder

BackgroundGenes that encode synaptic proteins or messenger RNA targets of the RNA-binding protein FMRP (fragile X messenger ribonucleoprotein) have been linked to schizophrenia and autism spectrum disorder (ASD) through the enrichment of genetic variants that confer risk for these disorders. FMRP binds many transcripts with synaptic functions and is thought to regulate their local translation, a process that enables rapid and compartmentalized protein synthesis required for development and plasticity. MethodsWe used summary statistics from large-scale genome-wide association studies of schizophrenia (74,776 cases, 101,023 controls) and ASD (18,381 cases, 27,969 controls) to test the hypothesis that the subset of synaptic genes that encode localized transcripts is more strongly associated with each disorder than nonlocalized transcripts. We also postulated that this subset of synaptic genes is responsible for associations attributed to FMRP targets. ResultsSchizophrenia associations were enriched in genes encoding localized synaptic transcripts compared to the remaining synaptic genes or to the remaining localized transcripts; this also applied to ASD associations, although only for transcripts observed after stimulation by fear conditioning. The genetic associations with either disorder captured by these gene sets were independent of those derived from FMRP targets. Schizophrenia association was related to FMRP interactions with messenger RNAs in somata, but not in dendrites, while ASD association was related to FMRP binding in either compartment. ConclusionsOur data suggest that synaptic transcripts capable of local translation are particularly relevant to the pathogenesis of schizophrenia and ASD, but they do not characterize the associations attributed to current sets of FMRP targets.

Polygenic risk for schizophrenia, social dispositions, and pace of epigenetic aging: Results from the Young Finns Study.

Schizophrenia is often regarded as a disorder of premature aging. We investigated (a) whether polygenic risk for schizophrenia (PRSsch ) relates to pace of epigenetic aging and (b) whether personal dispositions toward active and emotionally close relationships protect against accelerated epigenetic aging in individuals with high PRSsch . The sample came from the population-based Young Finns Study (n = 1348). Epigenetic aging was measured with DNA methylation aging algorithms such as AgeAccelHannum , EEAAHannum , IEAAHannum , IEAAHorvath , AgeAccelHorvath , AgeAccelPheno , AgeAccelGrim , and DunedinPACE. A PRSsch was calculated using summary statistics from the most comprehensive genome-wide association study of schizophrenia to date. Social dispositions were assessed in terms of extraversion, sociability, reward dependence, cooperativeness, and attachment security. We found that PRSsch did not have a statistically significant effect on any studied indicator of epigenetic aging. Instead, PRSsch had a significant interaction with reward dependence (p = 0.001-0.004), cooperation (p = 0.009-0.020), extraversion (p = 0.019-0.041), sociability (p = 0.003-0.016), and attachment security (p = 0.007-0.014) in predicting AgeAccelHannum , EEAAHannum , or IEAAHannum . Specifically, participants with high PRSsch appeared to display accelerated epigenetic aging at higher (vs. lower) levels of extraversion, sociability, attachment security, reward dependence, and cooperativeness. A rather opposite pattern was evident for those with low PRSsch . No such interactions were evident when predicting the other indicators of epigenetic aging. In conclusion, against our hypothesis, frequent social interactions may relate to accelerated epigenetic aging in individuals at risk for psychosis. We speculate that this may be explained by social-cognitive impairments (perceiving social situations as overwhelming or excessively arousing) or ending up in less supportive or deviant social groups.

Interpretation of SNP combination effects on schizophrenia etiology based on stepwise deep learning with multi-precision data.

Schizophrenia genome-wide association studies (GWAS) have reported many genomic risk loci, but it is unclear how they affect schizophrenia susceptibility through interactions of multiple SNPs. We propose a stepwise deep learning technique with multi-precision data (SLEM) to explore the SNP combination effects on schizophrenia through intermediate molecular and cellular functions. The SLEM technique utilizes two levels of precision data for learning. It constructs initial backbone networks with more precise but small amount of multilevel assay data. Then, it learns strengths of intermediate interactions with the less precise but massive amount of GWAS data. The learned networks facilitate identifying effective SNP interactions from the intractably large space of all possible SNP combinations. We have shown that the extracted SNP combinations show higher accuracy than any single SNPs and preserve the accuracy in an independent dataset. The learned networks also provide interpretations of molecular and cellular interactions of SNP combinations toward schizophrenia etiology.

Causal relationship between schizophrenia and sex hormone binding globulin: A Mendelian randomization study

ObjectiveThe underlying etiology of schizophrenia is still not fully understood, and recent studies have pointed to a potential link between hormonal factors and the risk of developing this condition. Sex Hormone-Binding Globulin (SHBG) is a protein that regulates the bioavailability of sex hormones. However, the causal relationship between SHBG levels and schizophrenia remains unclear, this study aimed to investigate the causal relationship based on two-sample Mendelian randomization (MR) analysis. MethodsThis study was based on the summary data of genome-wide association studies (GWAS) of schizophrenia and SHBG in European populations. Two-sample MR was applied, and genetic factors were used as instrumental variables, and the causal relationship between schizophrenia and SHBG was assessed. ResultsWe selected 79 single nucleotide polymorphisms with genome-wide significance from the schizophrenia GWAS as instrumental variables. The inverse variance weighting (IVW) method results showed that there is a causal relationship and a positive correlation between schizophrenia and female SHBG, with an odds ratio (OR) of 1.024 (95%CI: 1.007–1.042, P = 0.005), and this result was further confirmed by the Weighted median odds ratio (OR) of 1.032 (95%CI: 1.016–1.048, P = 5.58E-05) and the Weighted mode of 1.035 (95%CI: 1.004–1.067, P = 0.028). Schizophrenia and male SHBG also have a causal relationship and a positive correlation, with an odds ratio (OR) of 1.027 (95%CI: 1.007–1.047, P = 0.008). ConclusionThis study found a positive correlation between schizophrenia and SHBG in both men and women through MR analysis, indicating that the level of SHBG may be elevated in patients with schizophrenia, regardless of gender.

Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants

Genome-wide association studies (GWASs) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium makes it challenging to discern causal variants. We performed a massively parallel reporter assay (MPRA) on 5,173 fine-mapped schizophrenia GWAS variants in primary human neural progenitors and identified 439 variants with allelic regulatory effects (MPRA-positive variants). Transcription factor binding had modest predictive power, while fine-map posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit expressive quantitative trait loci signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. To predict the combinatorial effect of MPRA-positive variants on gene regulation, we propose an accessibility-by-contact model that combines MPRA-measured allelic activity with neuronal chromatin architecture.

Longitudinal MicroRNA Signature of Conversion to Psychosis.

The emergence of psychosis in ultra-high-risk subjects (UHR) is influenced by gene-environment interactions that rely on epigenetic mechanisms such as microRNAs. However, whether they can be relevant pathophysiological biomarkers of psychosis' onset remains unknown. We present a longitudinal study of microRNA expression, measured in plasma by high-throughput sequencing at baseline and follow-up, in a prospective cohort of 81 UHR, 35 of whom developed psychosis at follow-up (converters). We combined supervised machine learning and differential graph analysis to assess the relative weighted contribution of each microRNA variation to the difference in outcome and identify outcome-specific networks. We then applied univariate models to the resulting microRNA variations common to both strategies, to interpret them as a function of demographic and clinical covariates. We identified 207 microRNA variations that significantly contributed to the classification. The differential network analysis found 276 network-specific correlations of microRNA variations. The combination of both strategies identified 25 microRNAs, whose gene targets were overrepresented in cognition and schizophrenia genome-wide association studies findings. Interpretable univariate models further supported the relevance of miR-150-5p and miR-3191-5p variations in psychosis onset, independent of age, sex, cannabis use, and medication. In this first longitudinal study of microRNA variation during conversion to psychosis, we combined 2 methodologically independent data-driven strategies to identify a dynamic epigenetic signature of the emergence of psychosis that is pathophysiologically relevant.