Study of the genetic association between selected 3q29 region genes and schizophrenia and autism spectrum disorder in the Japanese population.

Psychiatric disorders are highly inheritable, and most psychiatric disorders exhibit genetic overlap. Recent studies associated the 3q29 recurrent deletion with schizophrenia (SCZ) and autism spectrum disorder (ASD). In this study, we investigated the association of genes in the 3q29 region with SCZ and ASD. TM4SF19 and PAK2 were chosen as candidate genes for this study based on evidence from previous research. We sequenced TM4SF19 and PAK2 in 437 SCZ cases, 187 ASD cases and 524 controls in the Japanese population. Through targeted sequencing, we identified 6 missense variants among the cases (ASD & SCZ), 3 missense variants among controls, and 1 variant common to both cases and controls; however, no loss-of-function variants were identified. Fisher's exact test showed a significant association of variants in TM4SF19 among cases (p=0.0160). These results suggest TM4SF19 variants affect the etiology of SCZ and ASD in the Japanese population. Further research examining 3q29 region genes and their association with SCZ and ASD is thus needed.

Genetic components of microdeletion syndromes and their role in determining schizophrenia traits.

Schizophrenia is a neuropsychiatric disorder characterized by various symptoms such as hallucinations, delusions, and disordered thinking. The etiology of this disease is unknown; however, it has been linked to many microdeletion syndromes that are likely to contribute to the pathology of schizophrenia. In this review we have comprehensively analyzed the role of various microdeletion syndromes, like 3q29, 15q13.3, and 22q11.2, which are known to be involved with schizophrenia. A variety of factors lead to schizophrenia phenotypes, but copy number variants that disrupt gene regulation and impair brain function and cognition are one of the causes that have been identified. Multiple case studies have shown that loss of one or more genes in the microdeletion regions lead to brain activity defects. In this article, we present a coherent paradigm that connects copy number variations (CNVs) to numerous neurological and behavioral abnormalities associated with schizophrenia. It would be helpful in understanding the different aspects of the microdeletions and how they contribute in the pathophysiology of schizophrenia.

Distinct genetic liability profiles define clinically relevant patient strata across common diseases.

Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms.

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.

Loss of dysbindin-1 in excitatory neurons in mice impacts NMDAR-dependent behaviors, neuronal morphology and synaptic transmission in the ventral hippocampus.

Dysbindin-1, a protein encoded by the schizophrenia susceptibility gene DTNBP1, is reduced in the hippocampus of schizophrenia patients. It is expressed in various cellular populations of the brain and implicated in dopaminergic and glutamatergic transmission. To investigate the impact of reduced dysbindin-1 in excitatory cells on hippocampal-associated behaviors and synaptic transmission, we developed a conditional knockout mouse model with deletion of dysbindin-1 gene in CaMKIIα expressing cells. We found that dysbindin-1 reduction in CaMKII expressing cells resulted in impaired spatial and social memories, and attenuation of the effects of glutamate N-methyl-d-asparate receptor (NMDAR) antagonist MK801 on locomotor activity and prepulse inhibition of startle (PPI). Dysbindin-1 deficiency in CaMKII expressing cells also resulted in reduced protein levels of NMDAR subunit GluN1 and GluN2B. These changes were associated with increased expression of immature dendritic spines in basiliar dendrites and abnormalities in excitatory synaptic transmission in the ventral hippocampus. These results highlight the functional relevance of dysbindin-1 in excitatory cells and its implication in schizophrenia-related pathologies.

The contribution of silencer variants to human diseases.

BACKGROUND: Although disease-causal genetic variants have been found within silencer sequences, we still lack a comprehensive analysis of the association of silencers with diseases. Here, we profiled GWAS variants in 2.8 million candidate silencers across 97 human samples derived from a diverse panel of tissues and developmental time points, using deep learning models. RESULTS: We show that candidate silencers exhibit strong enrichment in disease-associated variants, and several diseases display a much stronger association with silencer variants than enhancer variants. Close to 52% of candidate silencers cluster, forming silencer-rich loci, and, in the loci of Parkinson's-disease-hallmark genes TRIM31 and MAL, the associated SNPs densely populate clustered candidate silencers rather than enhancers displaying an overall twofold enrichment in silencers versus enhancers. The disruption of apoptosis in neuronal cells is associated with both schizophrenia and bipolar disorder and can largely be attributed to variants within candidate silencers. Our model permits a mechanistic explanation of causative SNP effects by identifying altered binding of tissue-specific repressors and activators, validated with a 70% of directional concordance using SNP-SELEX. Narrowing the focus of the analysis to individual silencer variants, experimental data confirms the role of the rs62055708 SNP in Parkinson's disease, rs2535629 in schizophrenia, and rs6207121 in type 1 diabetes. CONCLUSIONS: In summary, our results indicate that advances in deep learning models for the discovery of disease-causal variants within candidate silencers effectively "double" the number of functionally characterized GWAS variants. This provides a basis for explaining mechanisms of action and designing novel diagnostics and therapeutics.

Increased regional activity of a pro-autophagy pathway in schizophrenia as a contributor to sex differences in the disease pathology.

Based on recent genome-wide association studies, it is theorized that altered regulation of autophagy contributes to the pathophysiology of schizophrenia and bipolar disorder. As activity of autophagy-regulatory pathways is controlled by discrete phosphorylation sites on the relevant proteins, phospho-protein profiling is one of the few approaches available for enabling a quantitative assessment of autophagic activity in the brain. Despite this, a comprehensive phospho-protein assessment in the brains of schizophrenia and bipolar disorder subjects is currently lacking. Using this direction, our broad screening identifies an increase in AMP-activated protein kinase (AMPK)-mediated phospho-activation of the pro-autophagy protein beclin-1 solely in the prefrontal cortex of female, but not male, schizophrenia subjects. Using a reverse translational approach, we surprisingly find that this increase in beclin-1 activity facilitates synapse formation and enhances cognition. These findings are interpreted in the context of human studies demonstrating that female schizophrenia subjects have a lower susceptibility to cognitive dysfunction than males.

Whole-exome sequencing of individuals from an isolated population under extreme conditions implicates rare risk variants of schizophrenia.

Schizophrenia (SCZ), which affects approximately 1% of the world's population, is a global public health concern. It is generally considered that the interplay between genes and the environment is important in the onset and/or development of SCZ. Although several whole-exome sequencing studies have revealed rare risk variants of SCZ, no rare coding variants have been strongly replicated. Assessing isolated populations under extreme conditions might lead to the discovery of variants with a recent origin, which are more likely to have a higher frequency than chance to reflect gene-environment interactions. Following this approach, we examined a unique cohort of Tibetans living at an average altitude above 4500 meters. Whole-exome sequencing of 47 SCZ cases and 53 controls revealed 275 potential novel risk variants and two known variants (12:46244485: A/G and 22:18905934: A/G) associated with SCZ that were found in existing databases. Only one gene (C5orf42) in the gene-based statistics surpassed the exome-wide significance in the cohort. Metascape enrichment analysis suggested that novel risk genes were strongly enriched in pathways relevant to hypoxia, neurodevelopment, and neurotransmission. Additionally, 47 new risk genes were followed up in Han sample of 279 patients with SCZ and 95 controls, only BAI2 variant appearing in one case. Our findings suggest that SCZ patients living at high altitudes may have a unique risk gene signature, which may provide additional information on the underlying biology of SCZ, which can be exploited to identify individuals at greater risk of exposure to hypoxia.

A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning.

Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention has been given to epigenetic biomarkers in SCZ. In this study, we introduce a three-step, automated machine learning (AutoML)-based, data-driven, biomarker discovery pipeline approach, using genome-wide DNA methylation datasets and laboratory validation, to deliver a highly performing, blood-based epigenetic biosignature of diagnostic clinical value in SCZ. Publicly available blood methylomes from SCZ patients and healthy individuals were analyzed via AutoML, to identify SCZ-specific biomarkers. The methylation of the identified genes was then analyzed by targeted qMSP assays in blood gDNA of 30 first-episode drug-naïve SCZ patients and 30 healthy controls (CTRL). Finally, AutoML was used to produce an optimized disease-specific biosignature based on patient methylation data combined with demographics. AutoML identified a SCZ-specific set of novel gene methylation biomarkers including IGF2BP1, CENPI, and PSME4. Functional analysis investigated correlations with SCZ pathology. Methylation levels of IGF2BP1 and PSME4, but not CENPI were found to differ, IGF2BP1 being higher and PSME4 lower in the SCZ group as compared to the CTRL group. Additional AutoML classification analysis of our experimental patient data led to a five-feature biosignature including all three genes, as well as age and sex, that discriminated SCZ patients from healthy individuals [AUC 0.755 (0.636, 0.862) and average precision 0.758 (0.690, 0.825)]. In conclusion, this three-step pipeline enabled the discovery of three novel genes and an epigenetic biosignature bearing potential value as promising SCZ blood-based diagnostics.

The Genesis of Schizophrenia: An Origin Story.

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

Causal associations between psoriasis, eczema, urticaria, and mental illness: A bidirectional Mendelian randomization study of the European population.

Observational studies have reported a relationship between multiple common dermatoses and mental illness. To assess the potential bidirectional causality between 3 skin disorders (psoriasis, eczema, and urticaria) and 4 psychiatric disorders (bipolar disorder, schizophrenia, major depressive disorder, and anxiety) in the European population, we used Mendelian randomization (MR) analysis, which provides definitive evidence for causal inference. Eligible single nucleotide polymorphisms were screened for dermatological and psychiatric disorders using a genome-wide association study database. We conducted bidirectional, 2-sample MR analysis using instrumental variables related to psoriasis, eczema, and urticaria as exposure factors, and bipolar disorder, schizophrenia, major depression, and anxiety as outcomes. Reverse MR analysis with bipolar disorder, schizophrenia, major depression, and anxiety as exposure and psoriasis, eczema, and urticaria as outcomes were also performed, and the causality was analyzed using inverse-variance weighting (IVW), MR-Egger, and weighted median methods. To thoroughly assess causality, sensitivity analyses were conducted using the IVW, MR-PRESSO, and MR-Egger methods. The results showed that bipolar disorder increased the incidence of psoriasis (odds ratio = 1.271, 95% confidence interval = 1.003-1.612, P = .047), heterogeneity test with Cochran Q test in the IVW showed P value > .05, (P = .302), the MR-Pleiotropy and MR-PRESSO (outlier methods) in the multiplicity test showed P value > .05, (P = .694; P = .441), and MR-Pleiotropy evidence showed no apparent intercept (intercept = -0.060; SE = 0.139; P = .694). Major depression increased the risk of eczema (odds ratio = 1.002, 95% confidence interval = 1.000-1.004, P = .024), heterogeneity test showed P value > .05, (P = .328), multiplicity detection showed P value > .05, (P = .572; P = .340), and MR-Pleiotropy evidence showed no apparent intercept (intercept = -0.099; SE = 0.162; P = .572). Sensitivity analyses of the above results were reliable, and no heterogeneity or multiplicity was found. This study demonstrated a statistically significant causality between bipolar disorder and psoriasis, major depression, and eczema in a European population, which could provide important information for physicians in the clinical management of common skin conditions.

Family-based genome-wide association analysis of novelty seeking in a Korean schizophrenic population: A pilot study.

Schizophrenia (SPR) is the most devastating mental illness that causes severe deterioration in social and occupational functioning, but, the etiology remains unknown. The objective of this study is to explore the genetic underpinnings of novelty seeking behavior in schizophrenic family within the Korean population. By conducting a family-based genome-wide association study, we aim to identify potential genetic markers and variations associated with novelty seeking traits in the context of SPR. We have recruited 27 probands (with SPR) with their parents and siblings whenever possible. DNA was extracted from blood sampling of 58 individuals in 27 families and analyzed in an Illumina core exome single nucleotide polymorphism (SNP) array. A family-based association test (qFAM) was used to derive SNP association values across all chromosomes. Although none of the final 800,000 SNPs reached the genome-wide significant threshold of 8.45 × 10-7, the most significant 4 SNPs were within the 10-5 to 10-7. This study identifies genetic associations between novelty seeking behavior and SPR within families. RAPGEF5 emerges as a significant gene, along with other neuropsychiatric-related genes. Noteworthy genes like DRD4 and COMT did not show associations, possibly due to the focus on schizophrenic family. While shedding light on this complex relationship, larger studies are needed for robust conclusions and deeper mechanistic insights.

Linking haploinsufficiency of the autism- and schizophrenia-associated gene Cyfip1 with striatal-limbic-cortical network dysfunction and cognitive inflexibility.

Impaired behavioural flexibility is a core feature of neuropsychiatric disorders and is associated with underlying dysfunction of fronto-striatal circuitry. Reduced dosage of Cyfip1 is a risk factor for neuropsychiatric disorder, as evidenced by its involvement in the 15q11.2 (BP1-BP2) copy number variant: deletion carriers are haploinsufficient for CYFIP1 and exhibit a two- to four-fold increased risk of schizophrenia, autism and/or intellectual disability. Here, we model the contributions of Cyfip1 to behavioural flexibility and related fronto-striatal neural network function using a recently developed haploinsufficient, heterozygous knockout rat line. Using multi-site local field potential (LFP) recordings during resting state, we show that Cyfip1 heterozygous rats (Cyfip1+/-) harbor disrupted network activity spanning medial prefrontal cortex, hippocampal CA1 and ventral striatum. In particular, Cyfip1+/- rats showed reduced influence of nucleus accumbens and increased dominance of prefrontal and hippocampal inputs, compared to wildtype controls. Adult Cyfip1+/- rats were able to learn a single cue-response association, yet unable to learn a conditional discrimination task that engages fronto-striatal interactions during flexible pairing of different levers and cue combinations. Together, these results implicate Cyfip1 in development or maintenance of cortico-limbic-striatal network integrity, further supporting the hypothesis that alterations in this circuitry contribute to behavioural inflexibility observed in neuropsychiatric diseases including schizophrenia and autism.

Quantifying the relative importance of genetics and environment on the comorbidity between mental and cardiometabolic disorders using 17 million Scandinavians.

Mental disorders are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders. Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and near-complete genealogies of Denmark and Sweden (n = 17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six mental disorders and 15 cardiometabolic disorders. Genetic factors contributed about 50% to the comorbidity of schizophrenia, affective disorders, and autism spectrum disorder with cardiometabolic disorders, whereas the comorbidity of attention-deficit/hyperactivity disorder and anorexia with cardiometabolic disorders was mainly or fully driven by environmental factors. In this work we provide causal insight to guide clinical and scientific initiatives directed at achieving mechanistic understanding as well as preventing and alleviating the consequences of these disorders.

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

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

Shared genetic links between hypothyroidism and psychiatric disorders: evidence from a comprehensive genetic analysis.

Background: Epidemiologic studies have suggested co-morbidity between hypothyroidism and psychiatric disorders. However, the shared genetic etiology and causal relationship between them remain currently unclear. Methods: We assessed the genetic correlations between hypothyroidism and psychiatric disorders [anxiety disorders (ANX), schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP)] using summary association statistics from genome-wide association studies (GWAS). Two disease-associated pleiotropic risk loci and genes were identified, and pathway enrichment, tissue enrichment, and other analyses were performed to determine their specific functions. Furthermore, we explored the causal relationship between them through Mendelian randomization (MR) analysis. Results: We found significant genetic correlations between hypothyroidism with ANX, SCZ, and MDD, both in the Linkage disequilibrium score regression (LDSC) approach and the high-definition likelihood (HDL) approach. Meanwhile, the strongest correlation was observed between hypothyroidism and MDD (LDSC: rg=0.264, P=7.35×10-12; HDL: rg=0.304, P=4.14×10-17). We also determined a significant genetic correlation between MDD with free thyroxine (FT4) and thyroid-stimulating hormone (TSH) levels. A total of 30 pleiotropic risk loci were identified between hypothyroidism and psychiatric disorders, of which the 15q14 locus was identified in both ANX and SCZ (P values are 6.59×10-11 and 2.10×10-12, respectively) and the 6p22.1 locus was identified in both MDD and SCZ (P values are 1.05×10-8 and 5.75×10-14, respectively). Sixteen pleiotropic risk loci were identified between MDD and indicators of thyroid function, of which, four loci associated with MDD (1p32.3, 6p22.1, 10q21.1, 11q13.4) were identified in both FT4 normal level and Hypothyroidism. Further, 79 pleiotropic genes were identified using Magma gene analysis (P<0.05/18776 = 2.66×10-6). Tissue-specific enrichment analysis revealed that these genes were highly enriched into six brain-related tissues. The pathway analysis mainly involved nucleosome assembly and lipoprotein particles. Finally, our two-sample MR analysis showed a significant causal effect of MDD on the increased risk of hypothyroidism, and BIP may reduce TSH normal levels. Conclusions: Our findings not only provided evidence of a shared genetic etiology between hypothyroidism and psychiatric disorders, but also provided insights into the causal relationships and biological mechanisms that underlie their relationship. These findings contribute to a better understanding of the pleiotropy between hypothyroidism and psychiatric disorders, while having important implications for intervention and treatment goals for these disorders.

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

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

Association of cancer and schizophrenia, major depression and bipolar disorder: A Mendelian randomization study.

BACKGROUND: Schizophrenia, bipolar disorder and major depression have been reported to be associated with some cancers. However, the magnitude of the causal relationship between them remains unclear. This study aims to explore the potential association between three major mental diseases and the risk of some cancers. METHODS: We performed the two-sample Mendelian randomization(MR) analysis using publicly available genome-wide association studies (GWAS) statistics to investigate the causal relationship between these three mental diseases and some common types of cancers, including breast cancer, ovarian cancer, lung cancer, colorectal cancer, bladder cancer, prostate cancer, thyroid cancer, pancreatic cancer, malignant melanoma and glioma. We obtained genetic association estimates for schizophrenia, bipolar disorder and depression from the Psychiatric Genomics Consortium.The genetic association estimates for cancers were obtained from the UK Biobank, the MRC-IEU consortium and the GliomaScan consortium. RESULTS: After correction for heterogeneity and horizontal pleiotropy, we detected suggestive evidence for the association between thyroid cancer and genetically predicted schizophrenia (OR = 1.543, 95% CI: 1.023-2.328, P = 0.039), and thyroid cancer and major depression (OR = 3.573, 95% CI: 1.068-11.953, P = 0.039). No evidence of causal effects of schizophrenia, major depression and bipolar disorder on other types of cancers. CONCLUSIONS: Our findings suggest the association of schizophrenia and major depression and the development of thyroid cancer.

Nrg1 intracellular signaling regulates the development of interhemispheric callosal axons in mice.

Schizophrenia is associated with altered cortical circuitry. Although the schizophrenia risk gene NRG1 is known to affect the wiring of inhibitory interneurons, its role in excitatory neurons and axonal development is unclear. Here, we investigated the role of Nrg1 in the development of the corpus callosum, the major interhemispheric connection formed by cortical excitatory neurons. We found that deletion of Nrg1 impaired callosal axon development in vivo. Experiments in vitro and in vivo demonstrated that Nrg1 is cell-autonomously required for axonal outgrowth and that intracellular signaling of Nrg1 is sufficient to promote axonal development in cortical neurons and specifically in callosal axons. Furthermore, our data suggest that Nrg1 signaling regulates the expression of Growth Associated Protein 43, a key regulator of axonal growth. In conclusion, our study demonstrates that NRG1 is involved in the formation of interhemispheric callosal connections and provides a novel perspective on the relevance of NRG1 in excitatory neurons and in the etiology of schizophrenia.