Evaluating historical candidate genes for schizophrenia

Bistable Perception Discriminates Between Depressive Patients, Controls, Schizophrenia Patients, and Their Siblings

BACKGROUND AND HYPOTHESIS

Individuals with schizophrenia have less priors than controls, meaning they rely less upon their prior experiences to interpret the current stimuli. These differences in priors are expected to show as higher alternation rates in bistable perception tasks like the Structure-from-Motion (SfM) paradigm. In this paradigm, continuously moving dots in two dimensions are perceived subjectively as traveling along a three-dimensional sphere, which results in a direction of motion (left or right) that shifts approximately every few seconds.

STUDY DESIGN

Here, we tested healthy controls, patients with schizophrenia, siblings of patients with schizophrenia, and patients with depression with both the intermittent and continuous variants of the SfM paradigm.

STUDY RESULTS

In the intermittent variant of the SfM paradigm, depressive patients exhibited the lowest alternation rate, followed by unaffected controls. In contrast, patients with schizophrenia and their unaffected siblings displayed significantly higher alternation rates. In the continuous variant of the SfM paradigm, patients with schizophrenia showed the lowest mean percept durations, while there were no differences between the other three groups.

CONCLUSIONS

The intermittent SfM paradigm is a candidate endophenotype for schizophrenia. The aberrant processing in the patients may stem from alterations in adaptation and/or cross-inhibition mechanisms leading to changes in priors, as suggested by current models in the field. The intermittent SfM paradigm is, hence, a trait marker that offers the great opportunity to investigate perceptual abnormalities across the psychiatry spectrum, ranging from depression to psychosis.

Genetic Associations of Persistent Opioid Use After Surgery Point to OPRM1 but Not Other Opioid-Related Loci as the Main Driver of Opioid Use Disorder

Persistent opioid use after surgery is a common morbidity outcome associated with subsequent opioid use disorder, overdose, and death. While phenotypic associations have been described, genetic associations remain unidentified. Here, we conducted the largest genetic study of persistent opioid use after surgery, comprising ~40,000 non-Hispanic, European-ancestry Michigan Genomics Initiative participants (3198 cases and 36,321 surgically exposed controls). Our study primarily focused on the reproducibility and reliability of 72 genetic studies of opioid use disorder phenotypes. Nominal associations (p < 0.05) occurred at 12 of 80 unique (r2 < 0.8) signals from these studies. Six occurred in OPRM1 (most significant: rs79704991-T, OR = 1.17, p = 8.7 × 10-5), with two surviving multiple testing correction. Other associations were rs640561-LRRIQ3 (p = 0.015), rs4680-COMT (p = 0.016), rs9478495 (p = 0.017, intergenic), rs10886472-GRK5 (p = 0.028), rs9291211-SLC30A9/BEND4 (p = 0.043), and rs112068658-KCNN1 (p = 0.048). Two highly referenced genes, OPRD1 and DRD2/ANKK1, had no signals in MGI. Associations at previously identified OPRM1 variants suggest common biology between persistent opioid use and opioid use disorder, further demonstrating connections between opioid dependence and addiction phenotypes. Lack of significant associations at other variants challenges previous studies' reliability.

The Promise and Challenges of Integrating Biological and Prevention Sciences: A Community-Engaged Model for the Next Generation of Translational Research

Beginning with the successful sequencing of the human genome two decades ago, the possibility of developing personalized health interventions based on one's biology has captured the imagination of researchers, medical providers, and individuals seeking health care services. However, the application of a personalized medicine approach to emotional and behavioral health has lagged behind the development of personalized approaches for physical health conditions. There is potential value in developing improved methods for integrating biological science with prevention science to identify risk and protective mechanisms that have biological underpinnings, and then applying that knowledge to inform prevention and intervention services for emotional and behavioral health. This report represents the work of a task force appointed by the Board of the Society for Prevention Research to explore challenges and recommendations for the integration of biological and prevention sciences. We present the state of the science and barriers to progress in integrating the two approaches, followed by recommended strategies that would promote the responsible integration of biological and prevention sciences. Recommendations are grounded in Community-Based Participatory Research approaches, with the goal of centering equity in future research aimed at integrating the two disciplines to ultimately improve the well-being of those who have disproportionately experienced or are at risk for experiencing emotional and behavioral problems.

Schizophrenia genomics: genetic complexity and functional insights

Determining the causes of schizophrenia has been a notoriously intractable problem, resistant to a multitude of investigative approaches over centuries. In recent decades, genomic studies have delivered hundreds of robust findings that implicate nearly 300 common genetic variants (via genome-wide association studies) and more than 20 rare variants (via whole-exome sequencing and copy number variant studies) as risk factors for schizophrenia. In parallel, functional genomic and neurobiological studies have provided exceptionally detailed information about the cellular composition of the brain and its interconnections in neurotypical individuals and, increasingly, in those with schizophrenia. Taken together, these results suggest unexpected complexity in the mechanisms that drive schizophrenia, pointing to the involvement of ensembles of genes (polygenicity) rather than single-gene causation. In this Review, we describe what we now know about the genetics of schizophrenia and consider the neurobiological implications of this information.

New discoveries in the genetics and genomics of systemic juvenile idiopathic arthritis

INTRODUCTION

Systemic juvenile idiopathic arthritis (sJIA) is a severe inflammatory condition with onset in childhood. It is sporadic, but elements of its stereotypical innate immune responses are likely genetically encoded by both common variants with small effect sizes and rare variants with larger effects.

AREAS COVERED

Genomic investigations have defined the unique genetic architecture of sJIA. Identification of the class II HLA locus as the strongest sJIA risk factor for the first time brought attention to T lymphocytes and adaptive immune mechanisms in sJIA. The importance of the human leukocyte antigen (HLA) locus was reinforced by recognition that HLA-DRB1*15 alleles are strongly associated with development of drug reactions and sJIA-associated lung disease (sJIA-LD). At the IL1RN locus, genetic variation relates to both risk of sJIA and may also predict non-response to anakinra. Finally, rare genetic variants may have critical roles in disease complications, such as homozygous LACC1 mutations in families with an sJIA-like illness, and hemophagocytic lymphohistiocytosis (HLH) gene variants in some children with macrophage activation syndrome (MAS).

EXPERT OPINION

Genetic and genomic analysis of sJIA holds great promise for both basic discovery of the course and complications of sJIA, and may help guide personalized medicine and therapeutic decision-making.

The genetics of trichotillomania and excoriation disorder: A systematic review

BACKGROUND

Trichotillomania (TTM) and excoriation disorder (ED) are impairing obsessive-compulsive related disorders that are common in the general population and for which there are no clear first-line medications, highlighting the need to better understand the underlying biology of these disorders to inform treatments. Given the importance of genetics in obsessive-compulsive disorder (OCD), evaluating genetic factors underlying TTM and ED may advance knowledge about the pathophysiology of these body-focused repetitive behaviors.

AIM

In this systematic review, we summarize the available evidence on the genetics of TTM and ED and highlight gaps in the field warranting further research.

METHOD

We systematically searched Embase, PsycInfo, PubMed, Medline, Scopus, and Web of Science for original studies in genetic epidemiology (family or twin studies) and molecular genetics (candidate gene and genome-wide) published up to June 2023.

RESULTS

Of the 3536 records identified, 109 studies were included in this review. These studies indicated that genetic factors play an important role in the development of TTM and ED, some of which may be shared across the OCD spectrum, but there are no known high-confidence specific genetic risk factors for either TTM or ED.

CONCLUSIONS

Our review underscores the need for additional genome-wide research conducted on the genetics of TTM and ED, for instance, genome-wide association and whole-genome/whole-exome DNA sequencing studies. Recent advances in genomics have led to the discovery of risk genes in several psychiatric disorders, including related conditions such as OCD, but to date, TTM and ED have remained understudied.

The choice-wide behavioral association study: data-driven identification of interpretable behavioral components

Behavior contains rich structure across many timescales, but there is a dearth of methods to identify relevant components, especially over the longer periods required for learning and decision-making. Inspired by the goals and techniques of genome-wide association studies, we present a data-driven method-the choice-wide behavioral association study: CBAS-that systematically identifies such behavioral features. CBAS uses a powerful, resampling-based, method of multiple comparisons correction to identify sequences of actions or choices that either differ significantly between groups or significantly correlate with a covariate of interest. We apply CBAS to different tasks and species (flies, rats, and humans) and find, in all instances, that it provides interpretable information about each behavioral task.

Antipsychotic-induced epigenomic reorganization in frontal cortex of individuals with schizophrenia

Genome-wide association studies have revealed >270 loci associated with schizophrenia risk, yet these genetic factors do not seem to be sufficient to fully explain the molecular determinants behind this psychiatric condition. Epigenetic marks such as post-translational histone modifications remain largely plastic during development and adulthood, allowing a dynamic impact of environmental factors, including antipsychotic medications, on access to genes and regulatory elements. However, few studies so far have profiled cell-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects, or the effect of antipsychotic treatment on such epigenetic marks. Here, we conducted ChIP-seq analyses focusing on histone marks indicative of active enhancers (H3K27ac) and active promoters (H3K4me3), alongside RNA-seq, using frontal cortex samples from antipsychotic-free (AF) and antipsychotic-treated (AT) individuals with schizophrenia, as well as individually matched controls (n=58). Schizophrenia subjects exhibited thousands of neuronal and non-neuronal epigenetic differences at regions that included several susceptibility genetic loci, such as NRG1, DISC1, and DRD3. By analyzing the AF and AT cohorts separately, we identified schizophrenia-associated alterations in specific transcription factors, their regulatees, and epigenomic and transcriptomic features that were reversed by antipsychotic treatment; as well as those that represented a consequence of antipsychotic medication rather than a hallmark of schizophrenia in postmortem human brain samples. Notably, we also found that the effect of age on epigenomic landscapes was more pronounced in frontal cortex of AT-schizophrenics, as compared to AF-schizophrenics and controls. Together, these data provide important evidence of epigenetic alterations in the frontal cortex of individuals with schizophrenia, and remark for the first time on the impact of age and antipsychotic treatment on chromatin organization.

Did the human genome project affect research on Schizophrenia?

The Human Genome Project was undertaken primarily to discover genetic causes and better treatments for human diseases. Schizophrenia was targeted since three of the project`s principal architects had a personal interest and also because, based on family, adoption, and twin studies, schizophrenia was widely believed to be a genetic disorder. Extensive studies using linkage analysis, candidate genes, genome wide association studies [GWAS], copy number variants, exome sequencing and other approaches have failed to identify causal genes. Instead, they identified almost 300 single nucleotide polymorphisms [SNPs] associated with altered risks of developing schizophrenia as well as some rare variants associated with increased risk in a small number of individuals. Risk genes play a role in the clinical expression of most diseases but do not cause the disease in the absence of other factors. Increasingly, observers question whether schizophrenia is strictly a genetic disorder. Beginning in 1996 NIMH began shifting its research resources from clinical studies to basic research based on the promise of the Human Genome Project. Consequently, three decades later NIMH's genetics investment has yielded almost nothing clinically useful for individuals currently affected. It is time to review NIMH`s schizophrenia research portfolio.

Parkinson's disease and schizophrenia interactomes contain temporally distinct gene clusters underlying comorbid mechanisms and unique disease processes

Genome-wide association studies suggest significant overlaps in Parkinson's disease (PD) and schizophrenia (SZ) risks, but the underlying mechanisms remain elusive. The protein-protein interaction network ('interactome') plays a crucial role in PD and SZ and can incorporate their spatiotemporal specificities. Therefore, to study the linked biology of PD and SZ, we compiled PD- and SZ-associated genes from the DisGeNET database, and constructed their interactomes using BioGRID and HPRD. We examined the interactomes using clustering and enrichment analyses, in conjunction with the transcriptomic data of 26 brain regions spanning foetal stages to adulthood available in the BrainSpan Atlas. PD and SZ interactomes formed four gene clusters with distinct temporal identities (Disease Gene Networks or 'DGNs'1-4). DGN1 had unique SZ interactome genes highly expressed across developmental stages, corresponding to a neurodevelopmental SZ subtype. DGN2, containing unique SZ interactome genes expressed from early infancy to adulthood, correlated with an inflammation-driven SZ subtype and adult SZ risk. DGN3 contained unique PD interactome genes expressed in late infancy, early and late childhood, and adulthood, and involved in mitochondrial pathways. DGN4, containing prenatally-expressed genes common to both the interactomes, involved in stem cell pluripotency and overlapping with the interactome of 22q11 deletion syndrome (comorbid psychosis and Parkinsonism), potentially regulates neurodevelopmental mechanisms in PD-SZ comorbidity. Our findings suggest that disrupted neurodevelopment (regulated by DGN4) could expose risk windows in PD and SZ, later elevating disease risk through inflammation (DGN2). Alternatively, variant clustering in DGNs may produce disease subtypes, e.g., PD-SZ comorbidity with DGN4, and early/late-onset SZ with DGN1/DGN2.

Pre-Pulse Inhibition of an escape response in adult fruit fly, Drosophila melanogaster

Pre-Pulse Inhibition (PPI) is a neural process where suppression of a startle response is elicited by preceding the startling stimulus (Pulse) with a weak, non-startling one (Pre-Pulse). Defective PPI is widely employed as a behavioural endophenotype in humans and mammalian disorder-relevant models for neuropsychiatric disorders. We have developed a user-friendly, semi-automated, high-throughput-compatible Drosophila light-off jump response PPI paradigm, with which we demonstrate that PPI, with similar parameters measured in mammals, exists in adults of this model organism. We report that Drosophila PPI is affected by reduced expression of Dysbindin and both reduced and increased expression of Nmdar1 (N-methyl-D-aspartate receptor 1), perturbations associated with schizophrenia. Studying the biology of PPI in an organism that offers a plethora of genetic tools and a complex and well characterized connectome will greatly facilitate our efforts to gain deeper insight into the aetiology of human mental disorders, while reducing the need for mammalian models.

Psychosomatic Disorder: The Current Implications and Challenges

In recent years, there has been increasing global concern about the rising prevalence and rapid progression of psychosomatic disorders (PD). This surge can be attributed to irregular biological conditions and the increasingly stressful lifestyles that individuals lead, ultimately resulting in functional impairments of vital organs. PD arises from intricate interactions involving the central nervous, endocrine, and immune systems. Notably, the hypothalamic-pituitaryadrenal (HPA) axis plays an essential role, as its dysregulation is influenced by prolonged stress and psychological distress. Consequently, stress hormones, including cortisol, exert detrimental effects on immunological function, inflammation, and homeostatic equilibrium. It emerges as physical symptoms influenced by psychological factors, such as persistent pain, gastrointestinal disturbances, or respiratory complications, and is pertinent to highlight that excessive and chronic stress, anxiety, or emotional distress may engender the onset or exacerbation of cardiovascular disorders, namely hypertension and heart disease. Although several therapeutic strategies have been proposed so far, the precise etiology of PD remains elusive due to the intricate nature of disease progression and the underlying modalities of action. This comprehensive review seeks to elucidate the diverse classifications of psychosomatic disorders, explicate their intricate mechanisms, and shed light on their impact on the human body, which may act as catalysts for the development of various other diseases. Additionally, it explores the inherent medico-clinical challenges posed by PD and also explores the cutting-edge technologies, tools, and data analytics pipelines that are being applied in the contemporary era to effectively analyze psychosomatic data.

A novel heterozygous truncating variant in the AGO1 gene in an Iranian family with schizophrenia as an unreported symptom

Intellectual disability (ID) and autism spectrum disorders (ASDs) are the most common developmental disorders in humans. Combined, they affect between 3% and 5% of the population. Although high-throughput genomic methods are rapidly increasing the pool of ASD genes, many cases remain idiopathic. AGO1 is one of the less-known genes related to ID/ASD. This gene encodes a core member protein of the RNA-induced silencing complex, which suppresses mRNA expression through cleavage, degradation, and/or translational repression. Generally, patients with defects in the AGO1 gene manifest varying degrees of ID, speech delay, and autistic behaviors. Herein, we used whole-exome sequencing (WES) to investigate an Iranian family with two affected members one of whom manifested ID and autism and the other showed borderline ID and schizophrenia. WES analysis identified a novel heterozygous truncating variant (NM_012199.5:c.1298G > A, p.Trp433Ter) in the AGO1 gene that co-segregated with the phenotypes using Sanger sequencing. Moreover, the structural analysis showed that due to this variant, two critical domains (Mid and PIWI) of the AGO1 protein have been lost, which has a detrimental effect on the protein's function and structure. To the best of our knowledge, schizophrenia has not been reported in patients with AGO1 deficiency, which is a novel phenotypic finding that expands the AGO1-related behavioral disorders. Moreover, this study's findings determined that patients with the same variant in the AGO1 gene may show heterogeneity in manifested phenotypes.

Long non-coding RNAs in schizophrenia: Genetic variations, treatment markers and potential targeted signaling pathways

Schizophrenia (SZ), a complex and debilitating spectrum of psychiatric disorders, is now mainly attributed to multifactorial etiology that includes genetic and environmental factors. Long non-coding RNAs (lncRNAs) are gaining popularity as a way to better understand the comprehensive mechanisms beneath the clinical manifestation of SZ. Only in recent years has it been elucidated that mammalian genomes encode thousands of lncRNAs. Strikingly, roughly 30-40% of these lncRNAs are extensively expressed in different regions across the brain, which may be closely associated with SZ. The therapeutic and adverse effects of atypical antipsychotic drugs (AAPDs) are partially reflected by their role in the regulation of lncRNAs. This begs the question directly, do any lncRNAs exist as biomarkers for AAPDs treatment? Furthermore, we comprehend a range of mechanistic investigations that have revealed the regulatory roles for lncRNAs both involved in the brain and the periphery of SZ. More crucially, we also combine insights from a variety of signaling pathways to argue that lncRNAs probably play critical roles in SZ via their interactive downstream factors. This review provides a thorough understanding regarding dysregulation of lncRNAs, corresponding genetic alternations, as well as their potential regulatory roles in the pathology of SZ, which might help reveal useful therapeutic targets in SZ.

Human microglia maturation is underpinned by specific gene regulatory networks

Microglia phenotypes are highly regulated by the brain environment, but the transcriptional networks that specify the maturation of human microglia are poorly understood. Here, we characterized stage-specific transcriptomes and epigenetic landscapes of fetal and postnatal human microglia and acquired corresponding data in induced pluripotent stem cell (iPSC)-derived microglia, in cerebral organoids, and following engraftment into humanized mice. Parallel development of computational approaches that considered transcription factor (TF) co-occurrence and enhancer activity allowed prediction of shared and state-specific gene regulatory networks associated with fetal and postnatal microglia. Additionally, many features of the human fetal-to-postnatal transition were recapitulated in a time-dependent manner following the engraftment of iPSC cells into humanized mice. These data and accompanying computational approaches will facilitate further efforts to elucidate mechanisms by which human microglia acquire stage- and disease-specific phenotypes.

Gene-by-Environment Interaction Effects of Social Adversity on Externalizing Behavior in ABCD Youth

This study tested whether multiple domains of social adversity, including neighborhood opportunity/deprivation and life stress, moderate genetic (A), common environmental (C), and unique environmental (E) influences on externalizing behaviors in 760 same-sex twin pairs (332 monozygotic; 428 dizygotic) ages 10-11 from the ABCD Study. Proportion of C influences on externalizing behavior increased at higher neighborhood adversity (lower overall opportunity). A decreased and C and E increased at lower levels of educational opportunity. A increased at lower health-environment and social-economic opportunity levels. For life stress, A decreased and E increased with number of experienced events. Results for educational opportunity and stressful life experiences suggest a bioecological gene-environment interaction pattern such that environmental influences predominate at higher levels of adversity, whereas limited access to healthcare, housing, and employment stability may potentiate genetic liability for externalizing behavior via a diathesis-stress mechanism. More detailed operationalization of social adversity in gene-environment interaction studies is needed.

Gene and schizophrenia in the pregenome and postgenome-wide association studies era: a bibliometric analysis and network visualization

This study aimed to perform a bibliometric analysis on genetic studies in schizophrenia in the pregenome-wide association studies (GWAS) and post-GWAS era. We searched the literature on genes and schizophrenia using the Scopus database. The documents increased with time, especially after the human genome project and International HapMap Project, with the highest citation in 2008. The top occurrence author keywords were discovered to be different in the pre-GWAS and post-GWAS eras, reflecting the progress of genetic studies connected to schizophrenia. Emerging keywords highlighted a trend towards an application of precision medicine, showing an interplay of environmental exposures as well as genetic factors in schizophrenia pathogenesis, progression, and response to therapy. In conclusion, the gene and schizophrenia literature has grown rapidly after the human genome project, and the temporal variation in the author keywords pattern reflects the trend of genetic studies related to schizophrenia in the pre-GWAS and post-GWAS era.

Treatment-Resistant Schizophrenia, Clozapine Resistance, Genetic Associations, and Implications for Precision Psychiatry: A Scoping Review

Treatment-resistant schizophrenia (TRS) is often associated with severe burden of disease, poor quality of life and functional impairment. Clozapine is the gold standard for the treatment of TRS, although it is also known to cause significant side effects in some patients. In view of the burgeoning interest in the role of genetic factors in precision psychiatry, we conducted a scoping review to narratively summarize the current genetic factors associated with TRS, clozapine resistance and side effects to clozapine treatment. We searched PubMed from inception to December 2022 and included 104 relevant studies in this review. Extant evidence comprised associations between TRS and clozapine resistance with genetic factors related to mainly dopaminergic and serotoninergic neurotransmitter systems, specifically, TRS and rs4680, rs4818 within COMT, and rs1799978 within DRD2; clozapine resistance and DRD3 polymorphisms, CYP1A2 polymorphisms; weight gain with LEP and SNAP-25 genes; and agranulocytosis risk with HLA-related polymorphisms. Future studies, including replication in larger multi-site samples, are still needed to elucidate putative risk genes and the interactions between different genes and their correlations with relevant clinical factors such as psychopathology, psychosocial functioning, cognition and progressive changes with treatment over time in TRS and clozapine resistance.

Discovery of genomic loci associated with sleep apnea risk through multi-trait GWAS analysis with snoring

STUDY OBJECTIVES

Despite its association with severe health conditions, the etiology of sleep apnea (SA) remains understudied. This study sought to identify genetic variants robustly associated with SA risk.

METHODS

We performed a genome-wide association study (GWAS) meta-analysis of SA across five cohorts (NTotal = 523 366), followed by a multi-trait analysis of GWAS (multi-trait analysis of genome-wide association summary statistics [MTAG]) to boost power, leveraging the high genetic correlation between SA and snoring. We then adjusted our results for the genetic effects of body mass index (BMI) using multi-trait-based conditional and joint analysis (mtCOJO) and sought replication of lead hits in a large cohort of participants from 23andMe, Inc (NTotal = 1 477 352; Ncases = 175 522). We also explored genetic correlations with other complex traits and performed a phenome-wide screen for causally associated phenotypes using the latent causal variable method.

RESULTS

Our SA meta-analysis identified five independent variants with evidence of association beyond genome-wide significance. After adjustment for BMI, only one genome-wide significant variant was identified. MTAG analyses uncovered 49 significant independent loci associated with SA risk. Twenty-nine variants were replicated in the 23andMe GWAS adjusting for BMI. We observed genetic correlations with several complex traits, including multisite chronic pain, diabetes, eye disorders, high blood pressure, osteoarthritis, chronic obstructive pulmonary disease, and BMI-associated conditions.

CONCLUSION

Our study uncovered multiple genetic loci associated with SA risk, thus increasing our understanding of the etiology of this condition and its relationship with other complex traits.

Transcriptomic analyses reveal neuronal specificity of Leigh syndrome associated genes

Leigh syndrome is a rare, inherited, complex neurometabolic disorder with genetic and clinical heterogeneity. Features present in affected patients range from classical stepwise developmental regression to ataxia, seizures, tremor, and occasionally psychiatric manifestations. Currently, more than 100 monogenic causes of Leigh syndrome have been identified, yet the pathophysiology remains unknown. Here, we sought to determine the cellular specificity within the brain of all genes currently associated with Leigh syndrome. Further, we aimed to investigate potential genetic commonalities between Leigh syndrome and other disorders with overlapping clinical features. Enrichment of our target genes within the brain was evaluated with co-expression (CoExp) network analyses constructed using existing UK Brain Expression Consortium data. To determine the cellular specificity of the Leigh associated genes, we employed expression weighted cell type enrichment (EWCE) analysis of single-cell RNA-Seq data. Finally, CoExp network modules demonstrating enrichment of Leigh syndrome associated genes were then utilised for synaptic gene ontology analysis and heritability analysis. CoExp network analyses revealed that Leigh syndrome associated genes exhibit the highest levels of expression in brain regions most affected on MRI in affected patients. EWCE revealed significant enrichment of target genes in hippocampal and somatosensory pyramidal neurons and interneurons of the brain. Analysis of CoExp modules enriched with our target genes revealed preferential association with pre-synaptic structures. Heritability studies suggested some common enrichment between Leigh syndrome and Parkinson disease and epilepsy. Our findings suggest a primary mitochondrial dysfunction as the underlying basis of Leigh syndrome, with associated genes primarily expressed in neuronal cells.

Behaviour genetics and sleep: A narrative review of the last decade of quantitative and molecular genetic research in humans

During the last decade quantitative and molecular genetic research on sleep has increased considerably. New behavioural genetics techniques have marked a new era for sleep research. This paper provides a summary of the most important findings from the last ten years, on the genetic and environmental influences on sleep and sleep disorders and their associations with health-related variables (including anxiety and depression) in humans. In this review we present a brief summary of the main methods in behaviour genetic research (such as twin and genome-wide association studies). We then discuss key research findings on: genetic and environmental influences on normal sleep and sleep disorders, as well as on the association between sleep and health variables (highlighting a substantial role for genes in individual differences in sleep and their associations with other variables). We end by discussing future lines of enquiry and drawing conclusions, including those focused on problems and misconceptions associated with research of this type. In this last decade our knowledge about genetic and environmental influences on sleep and its disorders has expanded. Both, twin and genome-wide association studies show that sleep and sleep disorders are substantially influenced by genetic factors and for the very first time multiple specific genetic variants have been associated with sleep traits and disorders.

Molecular Landscape of Tourette's Disorder

Tourette's disorder (TD) is a highly heritable childhood-onset neurodevelopmental disorder and is caused by a complex interplay of multiple genetic and environmental factors. Yet, the molecular mechanisms underlying the disorder remain largely elusive. In this study, we used the available omics data to compile a list of TD candidate genes, and we subsequently conducted tissue/cell type specificity and functional enrichment analyses of this list. Using genomic data, we also investigated genetic sharing between TD and blood and cerebrospinal fluid (CSF) metabolite levels. Lastly, we built a molecular landscape of TD through integrating the results from these analyses with an extensive literature search to identify the interactions between the TD candidate genes/proteins and metabolites. We found evidence for an enriched expression of the TD candidate genes in four brain regions and the pituitary. The functional enrichment analyses implicated two pathways ('cAMP-mediated signaling' and 'Endocannabinoid Neuronal Synapse Pathway') and multiple biological functions related to brain development and synaptic transmission in TD etiology. Furthermore, we found genetic sharing between TD and the blood and CSF levels of 39 metabolites. The landscape of TD not only provides insights into the (altered) molecular processes that underlie the disease but, through the identification of potential drug targets (such as FLT3, NAALAD2, CX3CL1-CX3CR1, OPRM1, and HRH2), it also yields clues for developing novel TD treatments.

Systematic analysis to identify novel disease indications and plausible potential chemical leads of glutamate ionotropic receptor NMDA type subunit 1, GRIN1

Schizophrenia is a mental illness affecting the normal lifestyle of adults and early adolescents incurring major symptoms as jumbled speech, involvement in everyday activities eventually got reduced, patients always struggle with attention and memory, reason being both the genetic and environmental factors responsible for altered brain chemistry and structure, resulting in schizophrenia and associated orphan diseases. The network biology describes the interactions among genes/proteins encoding molecular mechanisms of biological processes, development, and diseases. Besides, all the molecular networks, protein-protein Interaction Networks have been significant in distinguishing the pathogenesis of diseases and thereby drug discovery. The present meta-analysis prioritizes novel disease indications viz. rare and orphan diseases associated with target Glutamate Ionotropic Receptor NMDA Type Subunit 1, GRIN1 using text mining knowledge-based tools. Furthermore, ZINC database was virtually screened, and binding conformation of selected compounds was performed and resulted in the identification of Narciclasine (ZINC04097652) and Alvespimycin (ZINC73138787) as potential inhibitors. Furthermore, docked complexes were subjected to MD simulation studies which suggests that the identified leads could be a better potential drug to recuperate schizophrenia.

Visual masking deficits in schizophrenia: a view into the genetics of the disease through an endophenotype

Schizophrenia is a severe psychiatric disorder determined by a complex mixture of genetic and environmental factors. To better understand the contributions of human genetic variations to schizophrenia, we performed a genome-wide association study (GWAS) of a highly sensitive endophenotype. In this visual masking endophenotype, two vertical bars, slightly shifted in the horizontal direction, are briefly presented (vernier offset). Participants are asked to indicate the offset direction of the bars (either left or right). The bars are followed by a grating mask, which makes the task both spatially and temporally challenging. The inter-stimulus interval (ISI) between the vernier and the mask was determined in 206 patients with schizophrenia, 109 first-order relatives, and 143 controls. Usually, in GWAS studies, patients are compared to controls (i.e., a binary task) without considering the large differences in performance between patients and controls, as it occurs in many paradigms. The masking task allows for a particularly powerful analysis because the differences in ISI within the patient population are large. We genotyped all participants and searched for associations between human polymorphisms and the masking endophenotype using a linear mixed model. We did not identify any genome-wide significant associations (p < 5 × 10^-8), indicating that common variants with strong effects are unlikely to contribute to the large inter-group differences in visual masking. However, we found significant differences in polygenetic risk scores (PRS) between patients and controls, and relatives and controls.

Pharmacogenetics and Schizophrenia-Can Genomics Improve the Treatment with Second-Generation Antipsychotics?

Schizophrenia (SCZ) is a complex psychiatric disorder of multifactorial origin, in which both genetic and environmental factors have an impact on its onset, course, and outcome. Large variability in response and tolerability of medication among individuals makes it difficult to predict the efficacy of a chosen therapeutic method and create universal and precise guidelines for treatment. Pharmacogenetic research allows for the identification of genetic polymorphisms associated with response to a chosen antipsychotic, thus allowing for a more effective and personal approach to treatment. This review focuses on three frequently prescribed second-generation antipsychotics (SGAs), risperidone, olanzapine, and aripiprazole, and aims to analyze the current state and future perspectives in research dedicated to identifying genetic factors associated with antipsychotic response. Multiple alleles of genes involved in pharmacokinetics (particularly isoenzymes of cytochrome P450), as well as variants of genes involved in dopamine, serotonin, and glutamate neurotransmission, have already been identified as ones of significant impact on antipsychotic response. It must, however, be noted that although currently obtained results are promising, trials with bigger study groups and unified protocols are crucial for standardizing methods and determining objective antipsychotic response status.

Current progress in understanding schizophrenia using genomics and pluripotent stem cells: A meta-analytical overview

Schizophrenia (SCZ) is a complex, heritable and polygenic neuropsychiatric disease, which disables the patients as well as decreases their life expectancy and quality of life. Common and rare variants studies on SCZ subjects have provided >100 genomic loci that hold importance in the context of SCZ pathophysiology. Transcriptomic studies from clinical samples have informed about the differentially expressed genes (DEGs) and non-coding RNAs in SCZ patients. Despite these advancements, no causative genes for SCZ were found and hence SCZ is difficult to recapitulate in animal models. In the last decade, induced Pluripotent Stem Cells (iPSCs)-based models have helped in understanding the neural phenotypes of SCZ by studying patient iPSC-derived 2D neuronal cultures and 3D brain organoids. Here, we have aimed to provide a simplistic overview of the current progress and advancements after synthesizing the enormous literature on SCZ genetics and SCZ iPSC-based models. Although further understanding of SCZ genetics and pathophysiological mechanisms using these technological advancements is required, the recent approaches have allowed to delineate important cellular mechanisms and biological pathways affected in SCZ.

How can we obtain truly translational mouse models to improve clinical outcomes in schizophrenia?

Schizophrenia is a serious mental illness affecting 0.7% of the world's population. Despite over 50 years of schizophrenia drug identification and development, there have been no fundamental advances in the treatment of schizophrenia since the 1980s. Complex genetic aetiology and elusive pathomechanisms have made it difficult for researchers to develop models that sufficiently reflect pathophysiology to support effective drug discovery. However, recent large-scale, well-powered genomic studies have identified risk genes that represent tractable entry points to decipher disease mechanisms in heterogeneous patient populations and develop targeted treatments. Replicating schizophrenia-associated gene variants in mouse models is an important strategy to start understanding their pathogenicity and role in disease biology. Furthermore, longitudinal studies in a wide range of genetic mouse models from early postnatal life are required to assess the progression of this disease through developmental stages to improve early diagnostic strategies and enable preventative measures. By expanding and refining our approach to schizophrenia research, we can improve prevention strategies and treatment of this debilitating disease.

Brain-wide versus genome-wide vulnerability biomarkers for severe mental illnesses

Severe mental illnesses (SMI), including major depressive (MDD), bipolar (BD), and schizophrenia spectrum (SSD) disorders have multifactorial risk factors and capturing their complex etiopathophysiology in an individual remains challenging. Regional vulnerability index (RVI) was used to measure individual's brain-wide similarity to the expected SMI patterns derived from meta-analytical studies. It is analogous to polygenic risk scores (PRS) that measure individual's similarity to genome-wide patterns in SMI. We hypothesized that RVI is an intermediary phenotype between genome and symptoms and is sensitive to both genetic and environmental risks for SMI. UK Biobank sample of N = 17,053/19,265 M/F (age = 64.8 ± 7.4 years) and an independent sample of SSD patients and controls (N = 115/111 M/F, age = 35.2 ± 13.4) were used to test this hypothesis. UKBB participants with MDD had significantly higher RVI-MDD (Cohen's d = 0.20, p = 1 × 10-23 ) and PRS-MDD (d = 0.17, p = 1 × 10-15 ) than nonpsychiatric controls. UKBB participants with BD and SSD showed significant elevation in the respective RVIs (d = 0.65 and 0.60; p = 3 × 10-5 and .009, respectively) and PRS (d = 0.57 and 1.34; p = .002 and .002, respectively). Elevated RVI-SSD were replicated in an independent sample (d = 0.53, p = 5 × 10-5 ). RVI-MDD and RVI-SSD but not RVI-BD were associated with childhood adversity (p < .01). In nonpsychiatric controls, elevation in RVI and PRS were associated with lower cognitive performance (p < 10-5 ) in six out of seven domains and showed specificity with disorder-associated deficits. In summary, the RVI is a novel brain index for SMI and shows similar or better specificity for SMI than PRS, and together they may complement each other in the efforts to characterize the genomic to brain level risks for SMI.

Rare variants implicate NMDA receptor signaling and cerebellar gene networks in risk for bipolar disorder

Bipolar disorder is an often-severe mental health condition characterized by alternation between extreme mood states of mania and depression. Despite strong heritability and the recent identification of 64 common variant risk loci of small effect, pathophysiological mechanisms remain unknown. Here, we analyzed genome sequences from 41 multiply-affected pedigrees and identified variants in 741 genes with nominally significant linkage or association with bipolar disorder. These 741 genes overlapped known risk genes for neurodevelopmental disorders and clustered within gene networks enriched for synaptic and nuclear functions. The top variant in this analysis - prioritized by statistical association, predicted deleteriousness, and network centrality - was a missense variant in the gene encoding D-amino acid oxidase (DAOG131V). Heterologous expression of DAOG131V in human cells resulted in decreased DAO protein abundance and enzymatic activity. In a knock-in mouse model of DAOG131, DaoG130V/+, we similarly found decreased DAO protein abundance in hindbrain regions, as well as enhanced stress susceptibility and blunted behavioral responses to pharmacological inhibition of N-methyl-D-aspartate receptors (NMDARs). RNA sequencing of cerebellar tissue revealed that DaoG130V resulted in decreased expression of two gene networks that are enriched for synaptic functions and for genes expressed, respectively, in Purkinje neurons or granule neurons. These gene networks were also down-regulated in the cerebellum of patients with bipolar disorder compared to healthy controls and were enriched for additional rare variants associated with bipolar disorder risk. These findings implicate dysregulation of NMDAR signaling and of gene expression in cerebellar neurons in bipolar disorder pathophysiology and provide insight into its genetic architecture.

New drug targets in psychiatry: Neurobiological considerations in the genomics era

After a period of withdrawal, pharmaceutical companies have begun to reinvest in neuropsychiatric disorders, due to improvements in our understanding of these disorders, stimulated in part by genomic studies. However, translating this information into disease insights and ultimately into tractable therapeutic targets is a major challenge. Here we consider how different sources of information might be integrated to guide this process. We review how an understanding of neurobiology has been used to advance therapeutic candidates identified in the pre-genomic era, using catechol-O-methyltransferase (COMT) as an exemplar. We then contrast with ZNF804A, the first genome-wide significant schizophrenia gene, and draw on some of the lessons that these and other examples provide. We highlight that, at least in the short term, the translation of potential targets for which there is orthogonal neurobiological support is likely to be more straightforward and productive than that those relying solely on genomic information. Although we focus here on information from genomic studies of schizophrenia, the points are broadly applicable across major psychiatric disorders and their symptoms.

A Re-evaluation of Candidate Gene Studies for Well-Being in Light of Genome-Wide Evidence

Ever since twin-family studies found that a substantial amount (± 40%) of the variation in well-being can be explained by genetic variation, several candidate genes have been proposed explaining this variation. However, these candidate gene and candidate gene-by-environment interaction studies have been surrounded by controversy regarding the validity and replication of their results. In the present study, we review the existing candidate gene literature for well-being. First, we perform a systematic literature search that results in the inclusion of 41 studies. After describing the results of the included studies, we evaluated the included candidate polymorphisms by (1) looking up the results for the studied candidate SNPs in a large well-being genome-wide association study, (2) performing association analyses in UK biobank (UKB) data for the candidate variable number tandem repeats (VNTR) and the APOE ε4 allele, and (3) studying possible candidate interactions with positive and negative environmental moderators using UKB data. We find no support for any of the candidate genes or candidate gene-environment interactions for well-being, with the exception of two SNPs that were chosen based on genome-wide evidence. While the generalizability of our findings is limited by our phenotype and environment definitions, we strongly advise well-being researchers to abandon the candidate gene approach in the field of well-being and move toward genome-wide approaches.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10902-022-00538-x.

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.

Longitudinal Temperament Pathways to ADHD Between Childhood and Adolescence

The current investigation extended prior cross-sectional mapping of etiological factors, transdiagnostic effortful and affective traits, and ADHD symptoms to longitudinal pathways extending from two etiological domains: polygenic and prenatal risk. Hypotheses were (1) genetic risk for ADHD would be related to inattentive ADHD symptoms in adolescence and mediated by childhood effortful control; (2) prenatal smoking would be related to hyperactive-impulsive ADHD symptoms during childhood and mediated by childhood surgency; and (3) there would be age-related variation, such that mediation of genetic risk would be larger for older than younger ages, whereas mediation of prenatal risk would be larger in earlier childhood than at later ages. Participants were 849 children drawn from the Oregon ADHD-1000 Cohort, which used a case control sample and an accelerated longitudinal design to track development from childhood (at year 1 ages 7-13) through adolescence (at year 6 ages 13-19). Results showed the mediational pathway from prenatal smoking through surgency to hyperactivity-impulsivity at Year 1 was significant (indirect effect estimate = .053, p < .01). The mediational pathway from polygenic risk through effortful control to inattention at Year 6 was also significant (indirect effect estimate = .084, p < .01). Both results were independent of the association between inattention and hyperactivity-impulsivity and control for the alternative etiological input and held across parent- and teacher-report of ADHD symptoms. In line with dual pathway models of ADHD, early prenatal risk for hyperactivity-impulsivity appears to operate through surgency, while polygenic genetic risk for inattention appears mediated by effortful control.

Dysregulation of GABAergic Signaling in Neurodevelomental Disorders: Targeting Cation-Chloride Co-transporters to Re-establish a Proper E/I Balance

The construction of the brain relies on a series of well-defined genetically and experience- or activity -dependent mechanisms which allow to adapt to the external environment. Disruption of these processes leads to neurological and psychiatric disorders, which in many cases are manifest already early in postnatal life. GABA, the main inhibitory neurotransmitter in the adult brain is one of the major players in the early assembly and formation of neuronal circuits. In the prenatal and immediate postnatal period GABA, acting on GABA_A receptors, depolarizes and excites targeted cells via an outwardly directed flux of chloride. In this way it activates NMDA receptors and voltage-dependent calcium channels contributing, through intracellular calcium rise, to shape neuronal activity and to establish, through the formation of new synapses and elimination of others, adult neuronal circuits. The direction of GABA_A-mediated neurotransmission (depolarizing or hyperpolarizing) depends on the intracellular levels of chloride [Cl⁻]_i, which in turn are maintained by the activity of the cation-chloride importer and exporter KCC2 and NKCC1, respectively. Thus, the premature hyperpolarizing action of GABA or its persistent depolarizing effect beyond the postnatal period, leads to behavioral deficits associated with morphological alterations and an excitatory (E)/inhibitory (I) imbalance in selective brain areas. The aim of this review is to summarize recent data concerning the functional role of GABAergic transmission in building up and refining neuronal circuits early in development and its dysfunction in neurodevelopmental disorders such as Autism Spectrum Disorders (ASDs), schizophrenia and epilepsy. In particular, we focus on novel information concerning the mechanisms by which alterations in cation-chloride co-transporters (CCC) generate behavioral and cognitive impairment in these diseases. We discuss also the possibility to re-establish a proper GABA_A-mediated neurotransmission and excitatory (E)/inhibitory (I) balance within selective brain areas acting on CCC.

What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

Separating Clinical and Subclinical Depression by Big Data Informed Structural Vulnerability Index and Its impact on Cognition: ENIGMA Dot Product

Big Data neuroimaging collaborations including Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) integrated worldwide data to identify regional brain deficits in major depressive disorder (MDD). We evaluated the sensitivity of translating ENIGMA-defined MDD deficit patterns to the individual level. We treated ENIGMA MDD deficit patterns as a vector to gauge the similarity between individual and MDD patterns by calculating ENIGMA dot product (EDP). We analyzed the sensitivity and specificity of EDP in separating subjects with (1) subclinical depressive symptoms without a diagnosis of MDD, (2) single episode MDD, (3) recurrent MDD, and (4) controls free of neuropsychiatric disorders. We compared EDP to the Quantile Regression Index (QRI; a linear alternative to the brain age metric) and the global gray matter thickness and subcortical volumes and fractional anisotropy (FA) of water diffusion. We performed this analysis in a large epidemiological sample of UK Biobank (UKBB) participants (N=17,053/19,265 M/F). Group-average increases in depressive symptoms from controls to recurrent MDD was mirrored by EDP (r2=0.85), followed by FA (r2=0.81) and QRI (r2=0.56). Subjects with MDD showed worse performance on cognitive tests than controls with deficits observed for 3 out of 9 cognitive tests administered by the UKBB. We calculated correlations of EDP and other brain indices with measures of cognitive performance in controls. The correlation pattern between EDP and cognition in controls was similar (r2=0.75) to the pattern of cognitive differences in MDD. This suggests that the elevation in EDP, even in controls, is associated with cognitive performance - specifically in the MDD-affected domains. That specificity was missing for QRI, FA or other brain imaging indices. In summary, translating anatomically informed meta-analytic indices of similarity using a linear vector approach led to better sensitivity to depressive symptoms and cognitive patterns than whole-brain imaging measurements or an index of accelerated aging.

A summary-statistics-based approach to examine the role of serotonin transporter promoter tandem repeat polymorphism in psychiatric phenotypes

In genetic studies of psychiatric disorders in the pre-genome-wide association study (GWAS) era, one of the most commonly studied loci is the serotonin transporter (SLC6A4) promoter polymorphism, a 43-base-pair insertion/deletion polymorphism in the promoter region (5-HTTLPR). The genetic association signals between 5-HTTLPR and psychiatric phenotypes, however, have been inconsistent across many studies. Since the polymorphism cannot be tested via available SNP arrays, we had previously proposed an efficient machine learning algorithm to predict the genotypes of 5-HTTLPR based on the genotypes of eight nearby SNPs, which requires access to individual-level genotype and phenotype data. To utilize the advantage of publicly available GWAS summary statistics obtained from studies with very large sample sizes, we develop a GWAS summary-statistics-based approach for testing the variable number of tandem repeat (VNTR) associations with various phenotypes. We first cross-verify the accuracy of the summary-statistics-based approach for 61 phenotypes in the UK Biobank. Since we observed a strong similarity between the predicted individual-level 5-HTTLPR genotype-based approach and the summary-statistics-based approach, we applied our method to the available neurobehavioral GWAS summary statistics data obtained from large-scale GWAS. We found no genome-wide significant evidence for association between 5-HTTLPR and any of the neurobehavioral traits. We did observe, however, genome-wide significant evidence for association between this locus and human adult height, BMI, and total cholesterol. Our summary-statistics-based approach provides a systematic way to examine the role of VNTRs and related types of genetic polymorphisms in disease risk and trait susceptibility of phenotypes for which large-scale GWAS summary statistics data are available.

Astrocyte Bioenergetics and Major Psychiatric Disorders

Ongoing research continues to add new elements to the emerging picture of involvement of astrocyte energy metabolism in the pathophysiology of major psychiatric disorders, including schizophrenia, mood disorders, and addictions. This review outlines what is known about the energy metabolism in astrocytes, the most numerous cell type in the brain, and summarizes the recent work on how specific perturbations of astrocyte bioenergetics may contribute to the neuropsychiatric conditions. The role of astrocyte energy metabolism in mental health and disease is reviewed on the organism, organ, and cell level. Data arising from genomic, metabolomic, in vitro, and neurobehavioral studies is critically analyzed to suggest future directions in research and possible metabolism-focused therapeutic interventions.

American psychiatry in the new millennium: a critical appraisal

This article casts a critical eye over the development of American psychiatry from 1980 to the present. It notes the rapid decline of psychoanalysis that followed the publication of DSM III; the rising influence of genetics and neuroscience; the re-emphasis on the biology of mental illness; and the collapse of public psychiatry that accompanied deinstitutionalization. It argues that while genetics and neuroscience have made scientific progress, the clinical utility of their findings to date has been very limited. The fifth edition of the DSM was supposed to base itself on this new science but that proved impossible. Diagnosis remains purely phenomenological and controversial. One of the ironies of research on psychiatric genetics is that has failed to find either a Mendelian origin of schizophrenia and depression or to validate the importance of hypothesized candidate genes. Genome-wide association studies have instead uncovered risk factors for major mental illnesses, but these overlap considerably, and the genetic associations are not dispositive. Most of those who carry these genetic variants do not develop mental illness. The status of psychopharmacology since the mid-1950s is scrutinized, as is the influence of the pharmaceutical industry on contemporary psychiatry, and the implications of its recent decision to abandon work in this arena. The paper concludes with an assessment of the crisis that it contends confronts contemporary American psychiatry: its overemphasis on biology; the urgent questions that persist about diagnosis and therapeutics; concerns about the directions of future research; and its inability to reduce the excess mortality that plagues the mentally ill.

The genetic basis of major depression

Major depressive disorder (MDD) is a common, debilitating, phenotypically heterogeneous disorder with heritability ranges from 30% to 50%. Compared to other psychiatric disorders, its high prevalence, moderate heritability, and strong polygenicity have posed major challenges for gene-mapping in MDD. Studies of common genetic variation in MDD, driven by large international collaborations such as the Psychiatric Genomics Consortium, have confirmed the highly polygenic nature of the disorder and implicated over 100 genetic risk loci to date. Rare copy number variants associated with MDD risk were also recently identified. The goal of this review is to present a broad picture of our current understanding of the epidemiology, genetic epidemiology, molecular genetics, and gene-environment interplay in MDD. Insights into the impact of genetic factors on the aetiology of this complex disorder hold great promise for improving clinical care.

Twin studies to GWAS: there and back again

The field of human behavioral genetics has come full circle. It began by using twin/family studies to estimate the relative importance of genetic and environmental influences. As large-scale genotyping became cost-effective, genome-wide association studies (GWASs) yielded insights about the nature of genetic influences and new methods that use GWAS data to estimate heritability and genetic correlations invigorated the field. Yet these newer GWAS methods have not replaced twin/family studies. In this review, we discuss the strengths and weaknesses of the two approaches with respect to characterizing genetic and environmental influences, measurement of behavioral phenotypes, and evaluation of causal models, with a particular focus on cognitive neuroscience. This discussion highlights how twin/family studies and GWAS complement and mutually reinforce one another.

Genetic and functional analysis reveals TENM4 contributes to schizophrenia

TENM4, encoding a member of the teneurin protein family, is a risk gene shared by many types of mental diseases and is implicated in neuronal plasticity and signaling. However, the role and the mechanisms of TENM4 in schizophrenia (SCZ) remain unclear. We identified possible pathogenic mutations in the TENM4 gene through target sequencing of TENM4 in 68 SCZ families. We further demonstrated that aberrant expression of Ten-m leads to lower learning ability, sleep reduction, and increased aggressiveness in animal models. RNA sequencing showed that aberrant expression of Ten-m was related to stimulus perception and metabolic process, and Gene Ontology enrichment terms were neurogenesis and ATPase activity. This study provides strong evidence that TENM4 contributes to SCZ, and its functional mutations might be responsible for the impaired neural circuits and behaviors observed in SCZ.

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Possible pathogenic rare missense mutations in TENM4 gene contribute to SCZ

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Aberrant expression of Ten-m leads to behavioral disturbances related to SCZ symptoms

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Ten-m affects stimulation, metabolic process, neurogenesis, and ATPase activity

A genetic risk score using human chromosomal-scale length variation can predict schizophrenia

Studies indicate that schizophrenia has a genetic component, however it cannot be isolated to a single gene. We aimed to determine how well one could predict that a person will develop schizophrenia based on their germ line genetics. We compared 1129 people from the UK Biobank dataset who had a diagnosis of schizophrenia to an equal number of age matched people drawn from the general UK Biobank population. For each person, we constructed a profile consisting of numbers. Each number characterized the length of segments of chromosomes. We tested several machine learning algorithms to determine which was most effective in predicting schizophrenia and if any improvement in prediction occurs by breaking the chromosomes into smaller chunks. We found that the stacked ensemble, performed best with an area under the receiver operating characteristic curve (AUC) of 0.545 (95% CI 0.539-0.550). We noted an increase in the AUC by breaking the chromosomes into smaller chunks for analysis. Using SHAP values, we identified the X chromosome as the most important contributor to the predictive model. We conclude that germ line chromosomal scale length variation data could provide an effective genetic risk score for schizophrenia which performs better than chance.

Mitochondrial Miro GTPases coordinate mitochondrial and peroxisomal dynamics

Mitochondria and peroxisomes are highly dynamic, multifunctional organelles. Both perform key roles for cellular physiology and homoeostasis by mediating bioenergetics, biosynthesis, and/or signalling. To support cellular function, they must be properly distributed, of proper size, and be able to interact with other organelles. Accumulating evidence suggests that the small atypical GTPase Miro provides a central signalling node to coordinate mitochondrial as well as peroxisomal dynamics. In this review, I summarize our current understanding of Miro-dependent functions and molecular mechanisms underlying the proper distribution, size and function of mitochondria and peroxisomes.

Alteration of NMDA receptor trafficking as a cellular hallmark of psychosis

A dysfunction of the glutamatergic transmission, especially of the NMDA receptor (NMDAR), constitutes one of the main biological substrate of psychotic disorders, such as schizophrenia. The NMDAR signaling hypofunction, through genetic and/or environmental insults, would cause a neurodevelopmental myriad of molecular, cellular, and network alterations that persist throughout life. Yet, the mechanisms underpinning NMDAR dysfunctions remain elusive. Here, we compared the membrane trafficking of NMDAR in three gold-standard models of schizophrenia, i.e., patient's cerebrospinal fluids, genetic manipulations of susceptibility genes, and prenatal developmental alterations. Using a combination of single nanoparticle tracking, electrophysiological, biochemical, and behavioral approaches in rodents, we identified that the NMDAR trafficking in hippocampal neurons was consistently altered in all these different models. Artificial manipulations of the NMDAR surface dynamics with competing ligands or antibody-induced receptor cross-link in the developing rat brain were sufficient to regulate the adult acoustic startle reflex and compensate for an early pathological challenge. Collectively, we show that the NMDAR trafficking is markedly altered in all clinically relevant models of psychosis, opening new avenues of therapeutical strategies.

Dissecting autism and schizophrenia through neuroimaging genomics

Neuroimaging genomic studies of autism spectrum disorder and schizophrenia have mainly adopted a 'top-down' approach, beginning with the behavioural diagnosis, and moving down to intermediate brain phenotypes and underlying genetic factors. Advances in imaging and genomics have been successfully applied to increasingly large case-control studies. As opposed to diagnostic-first approaches, the bottom-up strategy begins at the level of molecular factors enabling the study of mechanisms related to biological risk, irrespective of diagnoses or clinical manifestations. The latter strategy has emerged from questions raised by top-down studies: why are mutations and brain phenotypes over-represented in individuals with a psychiatric diagnosis? Are they related to core symptoms of the disease or to comorbidities? Why are mutations and brain phenotypes associated with several psychiatric diagnoses? Do they impact a single dimension contributing to all diagnoses? In this review, we aimed at summarizing imaging genomic findings in autism and schizophrenia as well as neuropsychiatric variants associated with these conditions. Top-down studies of autism and schizophrenia identified patterns of neuroimaging alterations with small effect-sizes and an extreme polygenic architecture. Genomic variants and neuroimaging patterns are shared across diagnostic categories suggesting pleiotropic mechanisms at the molecular and brain network levels. Although the field is gaining traction; characterizing increasingly reproducible results, it is unlikely that top-down approaches alone will be able to disentangle mechanisms involved in autism or schizophrenia. In stark contrast with top-down approaches, bottom-up studies showed that the effect-sizes of high-risk neuropsychiatric mutations are equally large for neuroimaging and behavioural traits. Low specificity has been perplexing with studies showing that broad classes of genomic variants affect a similar range of behavioural and cognitive dimensions, which may be consistent with the highly polygenic architecture of psychiatric conditions. The surprisingly discordant effect sizes observed between genetic and diagnostic first approaches underscore the necessity to decompose the heterogeneity hindering case-control studies in idiopathic conditions. We propose a systematic investigation across a broad spectrum of neuropsychiatric variants to identify putative latent dimensions underlying idiopathic conditions. Gene expression data on temporal, spatial and cell type organization in the brain have also considerable potential for parsing the mechanisms contributing to these dimensions' phenotypes. While large neuroimaging genomic datasets are now available in unselected populations, there is an urgent need for data on individuals with a range of psychiatric symptoms and high-risk genomic variants. Such efforts together with more standardized methods will improve mechanistically informed predictive modelling for diagnosis and clinical outcomes.

Smartphones and the Neuroscience of Mental Health

Improvements in understanding the neurobiological basis of mental illness have unfortunately not translated into major advances in treatment. At this point, it is clear that psychiatric disorders are exceedingly complex and that, in order to account for and leverage this complexity, we need to collect longitudinal data sets from much larger and more diverse samples than is practical using traditional methods. We discuss how smartphone-based research methods have the potential to dramatically advance our understanding of the neuroscience of mental health. This, we expect, will take the form of complementing lab-based hard neuroscience research with dense sampling of cognitive tests, clinical questionnaires, passive data from smartphone sensors, and experience-sampling data as people go about their daily lives. Theory- and data-driven approaches can help make sense of these rich data sets, and the combination of computational tools and the big data that smartphones make possible has great potential value for researchers wishing to understand how aspects of brain function give rise to, or emerge from, states of mental health and illness.

Progression of behavioral deficits during periadolescent development differs in female and male DISC1 knockout rats

Mutations in the disrupted in schizophrenia-1 (DISC1) gene are associated with an increased risk of developing psychological disorders including schizophrenia, bipolar disorder, and depression. Assessing the impact of knocking out genes, like DISC1, in animal models provides valuable insights into the relationship between the gene and behavioral outcomes. Previous research has relied on mouse models to assess these impacts, however these may not yield as reliable or rich a behavioral analysis as can be obtained using rats. Thus, the goal of the present study was to characterize the behavioral effects of a biallelic functional deletion of the DISC1 gene in the Sprague Dawley rat. Female and male wild type and DISC1 knockout rats were assessed beginning just prior to weaning and during the post-weaning periadolescent period. The primary outcomes evaluated were activity, anxiety, responses to novel objects and conspecifics, and prepulse inhibition. These behaviors were selected as analogous indices of psychological dysfunction in humans. The DISC1 knockout had significant effects on behavior, although the kind and magnitude of deficits was different for females and males: in females, effects included hyperactivity, aversion to novelty, and a modest prepulse inhibition deficit; in males, effects in anxiety and neophobia were mild but their prepulse inhibition deficit was large. These data confirm that the DISC1 knockout rat model is an excellent way to reproduce and study symptoms of psychological disorders and provides compelling evidence for differential consequences of its dysfunction for females and males in the progression and emergence of specific behavioral deficits.

Weak Association Between the Glutamate Decarboxylase 1 Gene (GAD1) and Schizophrenia in Han Chinese Population

Objectives

Schizophrenia (SZ) is a complex psychiatric disorder with high heritability, and genetic components are thought to be pivotal risk factors for this illness. The glutamate decarboxylase 1 gene (GAD1) was hypothesized to be a candidate risk locus for SZ given its crucial role in the GABAergic neurotransmission system, and previous studies have examined the associations of single nucleotide polymorphisms (SNPs) spanning the GAD1 gene with SZ. However, inconsistent results were obtained. We hence examined the associations between GAD1 SNPs and SZ in two independent case-control samples of Han Chinese ancestry.

Materials and Methods

Two Han Chinese SZ case-control samples, referred as the discovery sample and the replication sample, respectively, were recruited for the current study. The discovery sample comprised of 528 paranoid SZ cases (with age of first onset ≥ 18) and 528 healthy controls; the independent replication sample contained 1,256 early onset SZ cases (with age of first onset < 18) and 2,661 healthy controls. Logistic regression analysis was performed to examine the associations between GAD1 SNPs and SZ.

Results

Ten SNPs covering GAD1 gene were analyzed in the discovery sample, and two SNPs showed nominal associations with SZ (rs2241165, P = 0.0181, OR = 1.261; rs2241164, P = 0.0225, OR = 1.219). SNP rs2241164 was also nominally significant in the independent replication sample (P = 0.0462, OR = 1.110), and the significance became stronger in a subsequent meta-analysis combining both discovery and replication samples (P = 0.00398, OR = 1.138). Nevertheless, such association could not survive multiple corrections, although the effect size of rs2241164 was comparable with other SZ risk loci identified in genome-wide association studies (GWAS) in Han Chinese population. We also examined the associations between GAD1 SNPs and SZ in published datasets of SZ GWAS in East Asians and Europeans, and no significant associations were observed.

Conclusion

We observed weak associations between GAD1 SNPs and risk of SZ in Han Chinese populations. Further analyses in larger Han Chinese samples with more detailed phenotyping are necessary to elucidate the genetic correlation between GAD1 SNPs and SZ.