Cross-Disorder Group of the Psychiatric Genomics Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis

Identification of a Predictive Model for Schizophrenia Based on SNPs in a Chinese Population

Background

Schizophrenia is a devastating mental disease with high heritability. A growing number of susceptibility genes associated with schizophrenia, as well as their corresponding SNPs loci, have been revealed by genome-wide association studies. However, using SNPs as predictors of disease and diagnosis remains difficult. Here, we aimed to uncover susceptibility SNPs in a Chinese population and to construct a prediction model for schizophrenia.

Methods

A total of 210 participants, including 70 patients with schizophrenia, 70 patients with bipolar disorder, and 70 healthy controls, were enrolled in this study. We estimated 14 SNPs using published risk loci of schizophrenia, and used these SNPs to build a model for predicting schizophrenia via comparison of genotype frequencies and regression. We evaluated the efficacy of the diagnostic model in schizophrenia and control patients using ROC curves and then used the 70 patients with bipolar disorder to evaluate the model's differential diagnostic efficacy.

Results

5 SNPs were selected to construct the model: rs148415900, rs71428218, rs4666990, rs112222723 and rs1716180. Correlation analysis results suggested that, compared with the risk SNP of 0, the risk SNP of 3 was associated with an increased risk of schizophrenia (OR = 13.00, 95% CI: 2.35-71.84, p = 0.003). The ROC-AUC of this prediction model for schizophrenia was 0.719 (95% CI: 0.634-0.804), with the greatest sensitivity and specificity being 60% and 80%, respectively. The ROC-AUC of the model in distinguishing between schizophrenia and bipolar disorder was 0.591 (95% CI: 0.497-0.686), with the greatest sensitivity and specificity being 60% and 55.7%, respectively.

Conclusion

The SNP risk score prediction model had good performance in predicting schizophrenia. To the best of our knowledge, previous studies have not applied SNP-based models to differentiate between cases of schizophrenia and other mental illnesses. It could have several potential clinical applications, including shaping disease diagnosis, treatment, and outcomes.

Metabolic Insights into Neuropsychiatric Illnesses and Ketogenic Therapies: A Transcriptomic View

The disruption of brain energy metabolism, leading to alterations in synaptic signaling, neural circuitry, and neuroplasticity, has been implicated in severe mental illnesses such as schizophrenia, bipolar disorder, and major depressive disorder. The therapeutic potential of ketogenic interventions in these disorders suggests a link between metabolic disturbances and disease pathology; however, the precise mechanisms underlying these metabolic disturbances, and the therapeutic effects of metabolic ketogenic therapy, remain poorly understood. In this study, we conducted an in silico analysis of transcriptomic data to investigate perturbations in metabolic pathways in the brain across severe mental illnesses via gene expression profiling. We also examined dysregulation of the same pathways in rodent or cell culture models of ketosis, comparing these expression profiles to those observed in the disease states. Our analysis revealed significant perturbations across all metabolic pathways, with the greatest perturbations in glycolysis, the tricarboxylic acid (TCA) cycle, and the electron transport chain (ETC) across all three disorders. Additionally, we observed some discordant gene expression patterns between disease states and ketogenic intervention studies, suggesting a potential role for ketone bodies in modulating pathogenic metabolic changes. Our findings highlight the importance of understanding metabolic dysregulation in severe mental illnesses and the potential therapeutic benefits of ketogenic interventions in restoring metabolic homeostasis. This study provides insights into the complex relationship between metabolism and neuropsychiatric disorders and lays the foundation for further experimental investigations aimed at appreciating the implications of the present transcriptomic findings as well as developing targeted therapeutic strategies.

Association between twin status with cognitive, behavioral development and brain structure in early adolescence: a retrospective cohort analysis based on the Adolescent Brain Cognitive Development Study

Twin births are related with maternal and fetal adverse outcomes. Little was known about the comparability of the cognitive, behavioral development and brain structure between twins and singletons in early adolescence. This retrospective cohort study was based on data from the United States population-based, prospective, longitudinal observational Adolescent Brain Cognitive Development study. Children with complete twin status information were enrolled, and the exposure variable was twin status. Primary outcomes were cognitive, behavioral development and brain structure in early adolescence. Cognitive and behavioral outcomes were assessed by using the NIH Toolbox and Child Behavioral Checklist, respectively. Brain structure was evaluated by the cortical thickness, area, and volume extracted from the magnetic resonance imaging (MRI) data. Subgroup analyses were conducted by prematurity, birth weight, with sibling, genetic profiles, and twin types (zygosity). From 1st September 2016 to 15th November 2018, 11545 children (9477 singletons and 2068 twins) aged 9-10 years were enrolled. Twins showed mildly lower cognitive performance (|t|> 5.104, P-values < 0.001, False Discovery Rate [FDR] < 0.001), better behavioral outcome (|t|> 2.441, P-values < 0.015, FDR < 0.042), such as lower scores for multiple psychiatric disorders and behavioral issues, and smaller cortical volume (t = - 3.854, P-values < 0.001, FDR < 0.001) and cortical area (t = - 3.872, P-values < 0.001, FDR < 0.001). The observed differences still held when stratified for prematurity, birth weight, presence of siblings, genetic profiles, and twin types (zygosity). Furthermore, analyses on the two-year follow-up data showed consistent results with baseline data. Twin status is associated with lower cognitive and better behavioral development in early adolescence accompanied by altered brain structure. Clinicians should be aware of the possible difference when generalizing results from adolescent twin samples to singletons.

Computational analysis of linguistic features in speech samples of first-episode bipolar disorder and psychosis

BACKGROUND

In recent years, automated analyses using novel NLP methods have been used to investigate language abnormalities in schizophrenia. In contrast, only a few studies used automated language analyses in bipolar disorder. To our knowledge, no previous research compared automated language characteristics of first-episode psychosis (FEP) and bipolar disorder (FEBD) using NLP methods.

METHODS

Our study included 53 FEP, 40 FEBD and 50 healthy control participants who are native Turkish speakers. Speech samples of the participants in the Thematic Apperception Test (TAT) underwent automated generic and part-of-speech analyses, as well as sentence-level semantic similarity analysis based on SBERT.

RESULTS

Both FEBD and FEP were associated with the use of shorter sentences and increased sentence-level semantic similarity but less semantic alignment with the TAT pictures. FEP also demonstrated reduced verbosity and syntactic complexity. FEP differed from FEBD in reduced verbosity, decreased first-person singular pronouns, fewer conjunctions, increased semantic similarity as well as shorter sentence and word length. The mean classification accuracy was 82.45 % in FEP vs HC, 71.1 % in FEBD vs HC, and 73 % in FEP vs FEBD. After Bonferroni correction, the severity of negative symptoms in FEP was associated with reduced verbal output and increased 5th percentile of semantic similarity.

LIMITATIONS

The main limitation of this study was the cross-sectional nature.

CONCLUSION

Our findings demonstrate that both patient groups showed language abnormalities, which were more severe and widespread in FEP compared to FEBD. Our results suggest that NLP methods reveal transdiagnostic linguistic abnormalities in FEP and FEBD.

Polygenic scores for psychiatric traits mediate the impact of multigenerational history for depression on offspring psychopathology

A family history of depression is a well-documented risk factor for offspring psychopathology. However, the genetic mechanisms underlying the intergenerational transmission of depression remain unclear. We used genetic, family history, and diagnostic data from 11,875 9-10 year-old children from the Adolescent Brain Cognitive Development study. We estimated and investigated the children's polygenic scores (PGSs) for 30 distinct traits and their association with a family history of depression (including grandparents and parents) and the children's overall psychopathology through logistic regression analyses. We assessed the role of polygenic risk for psychiatric disorders in mediating the transmission of depression from one generation to the next. Among 11,875 multi-ancestry children, 8,111 participants had matching phenotypic and genotypic data (3,832 female [47.2%]; mean (SD) age, 9.5 (0.5) years), including 6,151 [71.4%] of European ancestry). Greater PGSs for depression (estimate = 0.129, 95% CI = 0.070-0.187) and bipolar disorder (estimate = 0.109, 95% CI = 0.051-0.168) were significantly associated with higher family history of depression (Bonferroni-corrected P < .05). Depression PGS was the only PGS that significantly associated with both family risk and offspring's psychopathology, and robustly mediated the impact of family history of depression on several youth psychopathologies including anxiety disorders, suicidal ideation, and any psychiatric disorder (proportions mediated 1.39%-5.87% of the total effect on psychopathology; FDR-corrected P < .05). These findings suggest that increased polygenic risk for depression partially mediates the associations between family risk for depression and offspring psychopathology, showing a genetic basis for intergenerational transmission of depression. Future approaches that combine assessments of family risk with polygenic profiles may offer a more accurate method for identifying children at elevated risk.

Effects of CACNA1C and ANK3 on cognitive function in patients with bipolar disorder

Bipolar disorder (BD) is a complex, severe mental illness with cognitive impairment. Impairments in attention and memory are particularly evident. A large number of previous studies have identified CACNA1C and ANK3 gene variants as risk factors for BD and both affect cognitive function in people with BD. However, it is unclear whether there is an interaction effects between the two genes on cognitive impairment in patients. We used 153 Chinese Han Chinese patients with BD to explore the association of CACNA1C and ANK3 variants with attention and immediate memory using Plink software and and performed a epistatic interaction effects analysis. We found that CACNA1C and ANK3 gene variants respectively affected patients' scores on attention and memory tests. The significant SNP in the CACNA1C and ANK3 genes are rs73042126(P = 3.16 × 10-5,FDR = 0.0253) and rs2393640(P = 1.50 × 10-4,FDR = 0.0353) respectively. And they also interacted to affect cognitive functioning in BD patients (attention: P = 0.0289; immediate memory: P = 0.0398). Follow-up studies should increase the sample size, improve the assessment methods and experimental design, and further explore the pathogenic mechanisms of BD.

Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain

To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.

Understanding the link between different types of maternal diabetes and the onset of autism spectrum disorders

Autism spectrum disorders (ASD) encompass a collection of neurodevelopmental disorders that exhibit impaired social interactions and repetitive stereotypic behaviors. Although the exact cause of these disorders remains unknown, it is widely accepted that both genetic and environmental factors contribute to their onset and progression. Recent studies have highlighted the potential negative impact of maternal diabetes on embryonic neurodevelopment, suggesting that intrauterine hyperglycemia could pose an additional risk to early brain development and contribute to the development of ASD. This paper presents a comprehensive analysis of the current research on the relationship between various forms of maternal diabetes, such as type 1 diabetes mellitus, type 2 diabetes mellitus, and gestational diabetes mellitus, and the likelihood of ASD in offspring. The study elucidates the potential mechanisms through which maternal hyperglycemia affects fetal development, involving metabolic hormones, immune dysregulation, heightened oxidative stress, and epigenetic alterations. The findings of this review offer valuable insights for potential preventive measures and evidence-based interventions targeting ASD.

Multiomic profiling of transcription factor binding and function in human brain

Transcription factors (TFs) orchestrate gene expression programs crucial for brain function, but we lack detailed information about TF binding in human brain tissue. We generated a multiomic resource (ChIP-seq, ATAC-seq, RNA-seq, DNA methylation) on bulk tissues and sorted nuclei from several postmortem brain regions, including binding maps for more than 100 TFs. We demonstrate improved measurements of TF activity, including motif recognition and gene expression modeling, upon identification and removal of high TF occupancy regions. Further, predictive TF binding models demonstrate a bias for these high-occupancy sites. Neuronal TFs SATB2 and TBR1 bind unique regions depleted for such sites and promote neuronal gene expression. Binding sites for TFs, including TBR1 and PKNOX1, are enriched for risk variants associated with neuropsychiatric disorders, predominantly in neurons. This work, titled BrainTF, is a powerful resource for future studies seeking to understand the roles of specific TFs in regulating gene expression in the human brain.

Discrimination between healthy participants and people with panic disorder based on polygenic scores for psychiatric disorders and for intermediate phenotypes using machine learning

OBJECTIVE

Panic disorder is a modestly heritable condition. Currently, diagnosis is based only on clinical symptoms; identifying objective biomarkers and a more reliable diagnostic procedure is desirable. We investigated whether people with panic disorder can be reliably diagnosed utilizing combinations of multiple polygenic scores for psychiatric disorders and their intermediate phenotypes, compared with single polygenic score approaches, by applying specific machine learning techniques.

METHODS

Polygenic scores for 48 psychiatric disorders and intermediate phenotypes based on large-scale genome-wide association studies (n = 7556-1,131,881) were calculated for people with panic disorder (n = 718) and healthy controls (n = 1717). Discrimination between people with panic disorder and healthy controls was based on the 48 polygenic scores using five methods for classification: logistic regression, neural networks, quadratic discriminant analysis, random forests and a support vector machine. Differences in discrimination accuracy (area under the curve) due to an increased number of polygenic score combinations and differences in the accuracy across five classifiers were investigated.

RESULTS

All five classifiers performed relatively well for distinguishing people with panic disorder from healthy controls by increasing the number of polygenic scores. Of the 48 polygenic scores, the polygenic score for anxiety UK Biobank was the most useful for discrimination by the classifiers. In combinations of two or three polygenic scores, the polygenic score for anxiety UK Biobank was included as one of polygenic scores in all classifiers. When all 48 polygenic scores were used in combination, the greatest areas under the curve significantly differed among the five classifiers. Support vector machine and logistic regression had higher accuracy than quadratic discriminant analysis and random forests. For each classifier, the greatest area under the curve was 0.600 ± 0.030 for logistic regression (polygenic score combinations N = 14), 0.591 ± 0.039 for neural networks (N = 9), 0.603 ± 0.033 for quadratic discriminant analysis (N = 10), 0.572 ± 0.039 for random forests (N = 25) and 0.617 ± 0.041 for support vector machine (N = 11). The greatest areas under the curve at the best polygenic score combination significantly differed among the five classifiers. Random forests had the lowest accuracy among classifiers. Support vector machine had higher accuracy than neural networks.

CONCLUSIONS

These findings suggest that increasing the number of polygenic score combinations up to approximately 10 effectively improved the discrimination accuracy and that support vector machine exhibited greater accuracy among classifiers. However, the discrimination accuracy for panic disorder, when based solely on polygenic score combinations, was found to be modest.

Susceptibility to Treatment-Resistant Depression Within Families

Importance

Antidepressant responses and the phenotype of treatment-resistant depression (TRD) are believed to have a genetic basis. Genetic susceptibility between the TRD phenotype and other psychiatric disorders has also been established in previous genetic studies, but population-based cohort studies have not yet provided evidence to support these outcomes.

Objective

To estimate the TRD susceptibility and the susceptibility between TRD and other psychiatric disorders within families in a nationwide insurance cohort with extremely high coverage and comprehensive health care data.

Design, Setting, and Participants

This cohort study assessed data from the Taiwan national health insurance database across entire population (N = 26 554 001) between January 2003 and December 2017. Data analysis was performed from August 2021 to April 2023. TRD was defined as having experienced at least 3 distinct antidepressant treatments in the current episode, each with adequate dose and duration, based on the prescribing records. Then, we identified the first-degree relatives of individuals with TRD (n = 34 467). A 1:4 comparison group (n = 137 868) of first-degree relatives of individuals without TRD was arranged for the comparison group, matched by birth year, sex, and kinship.

Main Outcomes and Measures

Modified Poisson regression analyses were performed and adjusted relative risks (aRRs) and 95% CIs were calculated for the risk of TRD, the risk of other major psychiatric disorders, and different causes of mortality.

Results

This study included 172 335 participants (88 330 male and 84 005 female; mean [SD] age at beginning of follow-up, 22.9 [18.1] years). First-degree relatives of individuals with TRD had lower incomes, more physical comorbidities, higher suicide mortality, and increased risk of developing TRD (aRR, 9.16; 95% CI, 7.21-11.63) and higher risk of other psychiatric disorders than matched control individuals, including schizophrenia (aRR, 2.36; 95% CI, 2.10-2.65), bipolar disorder (aRR, 3.74; 95% CI, 3.39-4.13), major depressive disorder (aRR, 3.65; 95% CI, 3.44-3.87), attention-deficit/hyperactivity disorders (aRR, 2.38; 95% CI, 2.20-2.58), autism spectrum disorder (aRR, 2.26; 95% CI, 1.86-2.74), anxiety disorder (aRR, 2.71; 95% CI, 2.59-2.84), and obsessive-compulsive disorder (aRR, 3.14; 95% CI, 2.70-3.66). Sensitivity and subgroup analyses validated the robustness of the findings.

Conclusions and Relevance

To our knowledge, this study is the largest and perhaps first nationwide cohort study to demonstrate TRD phenotype transmission across families and coaggregation with other major psychiatric disorders. Patients with a family history of TRD had an increased risk of suicide mortality and tendency toward antidepressant resistance; therefore, more intensive treatments for depressive symptoms might be considered earlier, rather than antidepressant monotherapy.

Generation and transcriptomic characterization of MIR137 knockout miniature pig model for neurodevelopmental disorders

BACKGROUND

Neurodevelopmental disorders (NDD), such as autism spectrum disorders (ASD) and intellectual disorders (ID), are highly debilitating childhood psychiatric conditions. Genetic factors are recognized as playing a major role in NDD, with a multitude of genes and genomic regions implicated. While the functional validation of NDD-associated genes has predominantly been carried out using mouse models, the significant differences in brain structure and gene function between mice and humans have limited the effectiveness of mouse models in exploring the underlying mechanisms of NDD. Therefore, it is important to establish alternative animal models that are more evolutionarily aligned with humans.

RESULTS

In this study, we employed CRISPR/Cas9 and somatic cell nuclear transplantation technologies to successfully generate a knockout miniature pig model of the MIR137 gene, which encodes the neuropsychiatric disorder-associated microRNA miR-137. The homozygous knockout of MIR137 (MIR137-/-) effectively suppressed the expression of mature miR-137 and led to the birth of stillborn or short-lived piglets. Transcriptomic analysis revealed significant changes in genes associated with neurodevelopment and synaptic signaling in the brains of MIR137-/- miniature pig, mirroring findings from human ASD transcriptomic data. In comparison to miR-137-deficient mouse and human induced pluripotent stem cell (hiPSC)-derived neuron models, the miniature pig model exhibited more consistent changes in critical neuronal genes relevant to humans following the loss of miR-137. Furthermore, a comparative analysis identified differentially expressed genes associated with ASD and ID risk genes in both miniature pig and hiPSC-derived neurons. Notably, human-specific miR-137 targets, such as CAMK2A, known to be linked to cognitive impairments and NDD, exhibited dysregulation in MIR137-/- miniature pigs. These findings suggest that the loss of miR-137 in miniature pigs affects genes crucial for neurodevelopment, potentially contributing to the development of NDD.

CONCLUSIONS

Our study highlights the impact of miR-137 loss on critical genes involved in neurodevelopment and related disorders in MIR137-/- miniature pigs. It establishes the miniature pig model as a valuable tool for investigating neurodevelopmental disorders, providing valuable insights for potential applications in human research.

Neurophysiological profiles of patients with bipolar disorders as probed with transcranial magnetic stimulation: A systematic review

AIM

Bipolar disorder (BD) has a significant impact on global health, yet its neurophysiological basis remains poorly understood. Conventional treatments have limitations, highlighting the need for a better understanding of the neurophysiology of BD for early diagnosis and novel therapeutic strategies.

DESIGN

Employing a systematic review approach of the PRISMA guidelines, this study assessed the usefulness and validity of transcranial magnetic stimulation (TMS) neurophysiology in patients with BD.

METHODS

Databases searched included PubMed, MEDLINE, Embase, and PsycINFO, covering studies from January 1985 to January 2024.

RESULTS

Out of 6597 articles screened, nine studies met the inclusion criteria, providing neurophysiological insights into the pathophysiological basis of BD using TMS-electromyography and TMS-electroencephalography methods. Findings revealed significant neurophysiological impairments in patients with BD compared to healthy controls, specifically in cortical inhibition and excitability. In particular, short-interval cortical inhibition (SICI) was consistently diminished in BD across the studies, which suggests a fundamental impairment of cortical inhibitory function in BD. This systematic review corroborates the potential utility of TMS neurophysiology in elucidating the pathophysiological basis of BD. Specifically, the reduced cortical inhibition in the SICI paradigm observed in patients with BD suggests gamma-aminobutyric acid (GABA)-A receptor-mediated dysfunction, but results from other TMS paradigms have been inconsistent. Thus, complex neurophysiological processes may be involved in the pathological basis underlying BD. This study demonstrated that BD has a neural basis involving impaired GABAergic function, and it is highly expected that further research on TMS neurophysiology will further elucidate the pathophysiological basis of BD.

Analysis of clinical studies on clozapine from 2012-2022

Clozapine has been considered the "gold standard" in the treatment of schizophrenia for many years. Clozapine has a superior effect, particularly in the treatment of negative symptoms and suicidal behaviour. However, due to its numerous adverse reactions, clozapine is mainly used for treatment-resistant schizophrenia. The aim of this paper is to analyze the results of clinical studies on clozapine from 2012-2022. PubMed was used as the database. Sixty-four studies were included and categorised by topic. The pharmacokinetic properties of clozapine tablets and a clozapine suspension solution did not differ markedly. Clozapine was superior to olanzapine and risperidone in reducing aggression and depression. A long-term study showed that metabolic parameters changed comparably with olanzapine and clozapine after 8 years. Risperidone and ziprasidone can be used as an alternative to clozapine. Scopolamine, atropine drops, and metoclopramide are effective in the treatment of clozapine-induced hypersalivation. Eight drugs, including liraglutide, exenatide, metformin, and orlistat, are potentially effective in the treatment of clozapine-induced weight gain. Ziprasidone, haloperidol, and aripiprazole showed a positive effect on symptoms when added to clozapine. No investigated drug was superior to clozapine for the treatment of schizophrenia. Ziprasidone and risperidone can also be used well for the treatment of schizophrenia. In the treatment of clozapine-induced hypersalivation and weight gain, some drugs proved to be effective.

Rare and common variants associated with alcohol consumption identify a conserved molecular network

BACKGROUND

Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, genetic studies of alcohol consumption that use rare variants are still in their early stages. No prior studies of alcohol consumption have examined whether common and rare variants implicate the same genes and molecular networks, leaving open the possibility that the two approaches might identify distinct biology.

METHODS

To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N = 666,978) and whole exome sequencing data (Genebass, N = 393,099) to identify a set of common and rare variants for alcohol consumption. We used gene-based analysis to implicate genes from common and rare variant analyses, which we then propagated onto a shared molecular network using a network colocalization procedure.

RESULTS

Gene-based analysis of each dataset implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified in only the rare variant analysis, but have been associated with other neuropsychiatric traits. Network colocalization revealed significant network overlap between the genes identified via common and rare variants. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. Seventy-one of the genes in the shared network were previously implicated in neuropsychiatric or substance use disorders but not alcohol-related behaviors (e.g. EXOC2, EPM2A, and CACNG4). Differential gene expression analysis showed enrichment in the liver and several brain regions.

CONCLUSIONS

Genes implicated by network colocalization identify shared biology relevant to alcohol consumption, which also underlie neuropsychiatric traits and substance use disorders that are comorbid with alcohol use, providing a more holistic understanding of two disparate sources of genetic information.

Association Study of Serotonin 1A Receptor Gene, Personality, and Anxiety in Women with Alcohol Use Disorder

Alcohol use disorder is considered a chronic and relapsing disorder affecting the central nervous system. The serotonergic system, mainly through its influence on the mesolimbic dopaminergic reward system, has been postulated to play a pivotal role in the underlying mechanism of alcohol dependence. The study aims to analyse the association of the rs6295 polymorphism of the 5HTR1A gene in women with alcohol use disorder and the association of personality traits with the development of alcohol dependence, as well as the interaction of the rs6295, personality traits, and anxiety with alcohol dependence in women. The study group consisted of 213 female volunteers: 101 with alcohol use disorder and 112 controls. NEO Five-Factor and State-Trait Anxiety Inventories were applied for psychometric testing. Genotyping of rs6295 was performed by real-time PCR. We did not observe significant differences in 5HTR1A rs6295 genotypes (p = 0.2709) or allele distribution (p = 0.4513). The AUD subjects scored higher on the anxiety trait (p < 0.0001) and anxiety state (p < 0.0001) scales, as well as on the neuroticism (p < 0.0001) and openness (p = 0134) scales. Significantly lower scores were obtained by the AUD subjects on the extraversion (p < 0.0001), agreeability (p < 0.0001), and conscientiousness (p < 0.0001) scales. Additionally, we observed a significant effect of 5HTR1A rs6295 genotype interaction and alcohol dependency, or lack thereof, on the openness scale (p = 0.0016). In summary, this study offers a comprehensive overview of alcohol dependence among women. It offers valuable insights into this complex topic, contributing to a more nuanced understanding of substance use among this specific demographic. Additionally, these findings may have implications for developing prevention and intervention strategies tailored to individual genetic and, most importantly, personality and anxiety differences.

Understanding copy number variations through their genes: a molecular view on 16p11.2 deletion and duplication syndromes

Neurodevelopmental disorders (NDDs) include a broad spectrum of pathological conditions that affect >4% of children worldwide, share common features and present a variegated genetic origin. They include clinically defined diseases, such as autism spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD), motor disorders such as Tics and Tourette's syndromes, but also much more heterogeneous conditions like intellectual disability (ID) and epilepsy. Schizophrenia (SCZ) has also recently been proposed to belong to NDDs. Relatively common causes of NDDs are copy number variations (CNVs), characterised by the gain or the loss of a portion of a chromosome. In this review, we focus on deletions and duplications at the 16p11.2 chromosomal region, associated with NDDs, ID, ASD but also epilepsy and SCZ. Some of the core phenotypes presented by human carriers could be recapitulated in animal and cellular models, which also highlighted prominent neurophysiological and signalling alterations underpinning 16p11.2 CNVs-associated phenotypes. In this review, we also provide an overview of the genes within the 16p11.2 locus, including those with partially known or unknown function as well as non-coding RNAs. A particularly interesting interplay was observed between MVP and MAPK3 in modulating some of the pathological phenotypes associated with the 16p11.2 deletion. Elucidating their role in intracellular signalling and their functional links will be a key step to devise novel therapeutic strategies for 16p11.2 CNVs-related syndromes.

Factors that influence participation in physical activity for people with bipolar disorder: a synthesis of qualitative evidence

BACKGROUND

Mental health problems contribute significantly to the overall disease burden worldwide and are major causes of disability, suicide, and ischaemic heart disease. People with bipolar disorder report lower levels of physical activity than the general population, and are at greater risk of chronic health conditions including cardiovascular disease and obesity. These contribute to poor health outcomes. Physical activity has the potential to improve quality of life and physical and mental well-being.

OBJECTIVES

To identify the factors that influence participation in physical activity for people diagnosed with bipolar disorder from the perspectives of service users, carers, service providers, and practitioners to help inform the design and implementation of interventions that promote physical activity.

SEARCH METHODS

We searched MEDLINE, PsycINFO, and eight other databases to March 2021. We also contacted experts in the field, searched the grey literature, and carried out reference checking and citation searching to identify additional studies. There were no language restrictions.

SELECTION CRITERIA

We included qualitative studies and mixed-methods studies with an identifiable qualitative component. We included studies that focused on the experiences and attitudes of service users, carers, service providers, and healthcare professionals towards physical activity for bipolar disorder.

DATA COLLECTION AND ANALYSIS

We extracted data using a data extraction form designed for this review. We assessed methodological limitations using a list of predefined questions. We used the "best fit" framework synthesis based on a revised version of the Health Belief Model to analyse and present the evidence. We assessed methodological limitations using the CASP Qualitative Checklist. We used the GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative research) guidance to assess our confidence in each finding. We examined each finding to identify factors to inform the practice of health and care professionals and the design and development of physical activity interventions for people with bipolar disorder.

MAIN RESULTS

We included 12 studies involving a total of 592 participants (422 participants who contributed qualitative data to an online survey, 170 participants in qualitative research studies). Most studies explored the views and experiences of physical activity of people with experience of bipolar disorder. A number of studies also reported on personal experiences of physical activity components of lifestyle interventions. One study included views from family carers and clinicians. The majority of studies were from high-income countries, with only one study conducted in a middle-income country. Most participants were described as stable and had been living with a diagnosis of bipolar disorder for a number of years. We downgraded our confidence in several of the findings from high confidence to moderate or low confidence, as some findings were based on only small amounts of data, and the findings were based on studies from only a few countries, questioning the relevance of these findings to other settings. We also had very few perspectives of family members, other carers, or health professionals supporting people with bipolar disorder. The studies did not include any findings from service providers about their perspectives on supporting this aspect of care. There were a number of factors that limited people's ability to undertake physical activity. Shame and stigma about one's physical appearance and mental health diagnosis were discussed. Some people felt their sporting skills/competencies had been lost when they left school. Those who had been able to maintain exercise through the transition into adulthood appeared to be more likely to include physical activity in their regular routine. Physical health limits and comorbid health conditions limited activity. This included bipolar medication, being overweight, smoking, alcohol use, poor diet and sleep, and these barriers were linked to negative coping skills. Practical problems included affordability, accessibility, transport links, and the weather. Workplace or health schemes that offered discounts were viewed positively. The lack of opportunity for exercise within inpatient mental health settings was a problem. Facilitating factors included being psychologically stable and ready to adopt new lifestyle behaviours. There were positive benefits of being active outdoors and connecting with nature. Achieving balance, rhythm, and routine helped to support mood management. Fitting physical activity into a regular routine despite fluctuating mood or motivation appeared to be beneficial if practised at the right intensity and pace. Over- or under-exercising could be counterproductive and accelerate depressive or manic moods. Physical activity also helped to provide a structure to people's daily routines and could lead to other positive lifestyle benefits. Monitoring physical or other activities could be an effective way to identify potential triggers or early warning signs. Technology was helpful for some. People who had researched bipolar disorder and had developed a better understanding of the condition showed greater confidence in managing their care or providing care to others. Social support from friends/family or health professionals was an enabling factor, as was finding the right type of exercise, which for many people was walking. Other benefits included making social connections, weight loss, improved quality of life, and better mood regulation. Few people had been told of the benefits of physical activity. Better education and training of health professionals could support a more holistic approach to physical and mental well-being. Involving mental health professionals in the multidisciplinary delivery of physical activity interventions could be beneficial and improve care. Clear guidelines could help people to initiate and incorporate lifestyle changes.

AUTHORS' CONCLUSIONS

There is very little research focusing on factors that influence participation in physical activity in bipolar disorder. The studies we identified suggest that men and women with bipolar disorder face a range of obstacles and challenges to being active. The evidence also suggests that there are effective ways to promote managed physical activity. The research highlighted the important role that health and care settings, and professionals, can play in assessing individuals' physical health needs and how healthy lifestyles may be promoted. Based on these findings, we have provided a summary of key elements to consider for developing physical activity interventions for bipolar disorder.

Dynamic structure-function coupling across three major psychiatric disorders

BACKGROUND

Convergent evidence has suggested atypical relationships between brain structure and function in major psychiatric disorders, yet how the abnormal patterns coincide and/or differ across different disorders remains largely unknown. Here, we aim to investigate the common and/or unique dynamic structure-function coupling patterns across major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ).

METHODS

We quantified the dynamic structure-function coupling in 452 patients with psychiatric disorders (MDD/BD/SZ = 166/168/118) and 205 unaffected controls at three distinct brain network levels, such as global, meso-, and local levels. We also correlated dynamic structure-function coupling with the topological features of functional networks to examine how the structure-function relationship facilitates brain information communication over time.

RESULTS

The dynamic structure-function coupling is preserved for the three disorders at the global network level. Similar abnormalities in the rich-club organization are found in two distinct functional configuration states at the meso-level and are associated with the disease severity of MDD, BD, and SZ. At the local level, shared and unique alterations are observed in the brain regions involving the visual, cognitive control, and default mode networks. In addition, the relationships between structure-function coupling and the topological features of functional networks are altered in a manner indicative of state specificity.

CONCLUSIONS

These findings suggest both transdiagnostic and illness-specific alterations in the dynamic structure-function relationship of large-scale brain networks across MDD, BD, and SZ, providing new insights and potential biomarkers into the neurodevelopmental basis underlying the behavioral and cognitive deficits observed in these disorders.

Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach

Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.

Massively parallel characterization of regulatory elements in the developing human cortex

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.

Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Polygenic architecture of brain structure and function, behaviors, and psychopathologies in children

The human brain undergoes structural and functional changes during childhood, a critical period in cognitive and behavioral development. Understanding the genetic architecture of the brain development in children can offer valuable insights into the development of the brain, cognition, and behaviors. Here, we integrated brain imaging-genetic-phenotype data from over 8,600 preadolescent children of diverse ethnic backgrounds using multivariate statistical techniques. We found a low-to-moderate level of SNP-based heritability in most IDPs, which is lower compared to the adult brain. Using sparse generalized canonical correlation analysis (SGCCA), we identified several covariation patterns among genome-wide polygenic scores (GPSs) of 29 traits, 7 different modalities of brain imaging-derived phenotypes (IDPs), and 266 cognitive and psychological phenotype data. In structural MRI, significant positive associations were observed between total grey matter volume, left ventral diencephalon volume, surface area of right accumbens and the GPSs of cognition-related traits. Conversely, negative associations were found with the GPSs of ADHD, depression and neuroticism. Additionally, we identified a significant positive association between educational attainment GPS and regional brain activation during the N-back task. The BMI GPS showed a positive association with fractional anisotropy (FA) of connectivity between the cerebellum cortex and amygdala in diffusion MRI, while the GPSs for educational attainment and cannabis use were negatively associated with the same IDPs. Our GPS-based prediction models revealed substantial genetic contributions to cognitive variability, while the genetic basis for many mental and behavioral phenotypes remained elusive. This study delivers a comprehensive map of the relationships between genetic profiles, neuroanatomical diversity, and the spectrum of cognitive and behavioral traits in preadolescence.

Disease burden of mental disorders among children and adolescents considering both co-morbidities and suicide in Northeastern China

BACKGROUND

Few studies have assessed the burden of mental disorders among children and adolescents considering the impact of co-morbidities and suicide on disability adjusted life years (DALYs).

METHODS

This was a multicenter cross-sectional study. Our survey data in Liaoning Province (LN) were used to estimate the burden of six mental disorders, supplemented with data from other investigative studies conducted in China to assess four other disorders. DALYs were derived from the sum of years lived with a disability (YLDs) adjusted for co-morbidities, and the years of life lost (YLLs) adjusted for suicide. The changes in DALYs, YLDs, and YLLs were compared with and without adjustment for co-morbidities and suicide.

RESULTS

The DALYs rate of mental disorders among children and adolescents in LN decreased from 1579.6/105 to 1391.4/105, after adjusting for both co-morbidities and suicide (-11.9%). The DALYs rate for major depression, anxiety disorder, and conduct disorder (-80.8/105, -75.0/105 and  -30.2/105, respectively) were the top three contributors to the DALYs reduction (-188.2/105). The YLDs decreased from 72724.8 to 62478.5 after co-morbidity adjustment (-17.8%), mainly due to the reduction by major depression (-35.3%) and attention deficit/hyperactivity disorder [ADHD] (-34.2%). The YLLs increased from 130 to 1697.8 after adjusting for suicides (+ 56.9% of all suicide YLLs), mainly due to the contribution of major depression (+ 32.4%) and anxiety disorder (+ 10.4%). Compared to GBD 2010, the estimated DALY rate for mental disorders in LN was to be about 80%, with the proportion of DALYs and DALY rates explained by major depressive disorder accounted for only approximately one-third (14.6% vs. 41.9% and 202.6 vs. 759.9, respectively). But the proportion and absolute level of DALY rates explained by anxiety disorders were approximately 2-fold higher (39.7% vs. 19.6% and 552.2 vs. 323.3, respectively).

CONCLUSIONS

The DALYs of mental disorders among Chinese children and adolescents were approximately 80% of the global level, with anxiety disorders imposing about 2 times the global level. Co-morbidity and suicide must be adjusted when calculating DALYs.

Asian-European differentiation of schizophrenia-associated genes driven by admixture and natural selection

The European-centered genome-wide association studies of schizophrenia (SCZ) may not be well applied to non-European populations. We analyzed 1,592 reported SCZ-associated genes using the public genome data and found an overall higher Asian-European differentiation on the SCZ-associated variants than at the genome-wide level. Notable examples included 15 missense variants, a regulatory variant SLC5A10-rs1624825, and a damaging variant TSPAN18-rs1001292. Independent local adaptations in recent 25,000 years, after the Asian-European divergence, could have contributed to such genetic differentiation, as were identified at a missense mutation LTN1-rs57646126-A in Asians, and a non-risk allele ZSWIM6-rs72761442-G in Europeans. Altai-Neanderthal-derived alleles may have opposite effects on SCZ susceptibility between ancestries. Furthermore, adaptive introgression was detected on the non-risk haplotype at 1q21.2 in Europeans, while in Asians it was observed on the SCZ risk haplotype at 3p21.31 which is also potentially ultra-violet protective. This study emphasizes the importance of including more representative Asian samples in future SCZ studies.

Ahnak in the prefrontal cortex mediates behavioral correlates of stress resilience and rapid antidepressant action in mice

The prefrontal cortex (PFC) is a key neural node mediating behavioral responses to stress and the actions of ketamine, a fast-acting antidepressant. The molecular mechanisms underlying these processes, however, are not fully understood. Our recent study revealed a pivotal role of hippocampal Ahnak as a regulator of cellular and behavioral adaptations to chronic stress. However, despite its significant expression in the PFC, the contribution of cortical Ahnak to behavioral responses to stress and antidepressants remains unknown. Here, using a mouse model for chronic social stress, we find that Ahnak expression in the PFC is significantly increased in stress-resilient mice and positively correlated with social interaction after stress exposure. Conditional deletion of Ahnak in the PFC or forebrain glutamatergic neurons facilitates stress susceptibility, suggesting that Ahnak is required for behavioral resilience. Further supporting this notion, Ahnak expression in the PFC is increased after the administration of ketamine or its metabolite (2R, 6R)-hydroxynorketamine (HNK). Moreover, Ahnak deletion in forebrain glutamatergic neurons blocks the restorative behavioral effects of ketamine or HNK in stress-susceptible mice. This forebrain excitatory neuron-specific Ahnak deletion reduces the frequency of mini excitatory postsynaptic currents in layer II/III pyramidal neurons, suggesting that Ahnak may induce its behavioral effects via modulation of glutamatergic transmission in the PFC. Altogether, these data suggest that Ahnak in glutamatergic PFC neurons may be critical for behavioral resilience and antidepressant actions of ketamine or HNK in chronic social stress-exposed mice.

Clinical and personal predictors of functioning in affective disorders: Exploratory results from baseline and 6-month follow-up of a randomised controlled trial

Comprehensive knowledge of factors causing and sustaining functional impairment in patients with affective disorders is warranted. The aim is to investigate associations between clinical factors (such as affective symptoms) and personal factors (such as personality traits, coping strategies, and childhood trauma experiences) on functioning and improvement of functioning in patients with affective disorders. This exploratory study includes data from 103 patients with bipolar disorder and unipolar depressive disorder. Clinician-rated functioning was assessed at baseline using the Functioning Assessment Short Test (FAST), and performance-based functioning was assessed at baseline and 6-month follow-up using the Assessment of Motor and Process Skills (AMPS). Data on clinical and personal factors were collected at baseline. Personal factors were measured by the Eysenck Personality Inventory (EPQ), Coping Inventory for Stressful Situations (CISS) and Childhood Trauma Questionnaire (CTQ). Pearson correlations and multiple linear regression models were used to analyse the association of clinical and personal factors with baseline functioning (FAST) and to identify predictors of improvement in functioning (AMPS) from baseline to follow-up. At baseline, greater depressive symptom severity, the personality trait neuroticism, emotional coping, and childhood trauma all correlated with poorer functioning (higher FAST scores). In multiple linear regression models, depression severity, emotional coping and childhood trauma were significant predictors of poorer functioning. More childhood trauma was a predictor of less functional improvement measured by AMPS at 6-month follow-up. In conclusion, maladaptive coping styles and depressive symptoms contribute to functional impairment in patients with affective disorders, while childhood trauma has a negative impact on long-term functional outcomes.

Structural characterization of a polymorphic repeat at the CACNA1C schizophrenia locus

Genetic variation within intron 3 of the CACNA1C calcium channel gene is associated with schizophrenia and bipolar disorder, but analysis of the causal variants and their effect is complicated by a nearby variable-number tandem repeat (VNTR). Here, we used 155 long-read genome assemblies from 78 diverse individuals to delineate the structure and population variability of the CACNA1C intron 3 VNTR. We categorized VNTR sequences into 7 Types of structural alleles using sequence differences among repeat units. Only 12 repeat units at the 5' end of the VNTR were shared across most Types, but several Types were related through a series of large and small duplications. The most diverged Types were rare and present only in individuals with African ancestry, but the multiallelic structural polymorphism Variable Region 2 was present across populations at different frequencies, consistent with expansion of the VNTR preceding the emergence of early hominins. VR2 was in complete linkage disequilibrium with fine-mapped schizophrenia variants (SNPs) from genome-wide association studies (GWAS). This risk haplotype was associated with decreased CACNA1C gene expression in brain tissues profiled by the GTEx project. Our work suggests that sequence variation within a human-specific VNTR affects gene expression, and provides a detailed characterization of new alleles at a flagship neuropsychiatric locus.

Shared and distinct electroencephalogram microstate abnormalities across schizophrenia, bipolar disorder, and depression

BACKGROUND

Microstates of an electroencephalogram (EEG) are canonical voltage topographies that remain quasi-stable for 90 ms, serving as the foundational elements of brain dynamics. Different changes in EEG microstates can be observed in psychiatric disorders like schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD). However, the similarities and disparatenesses in whole-brain dynamics on a subsecond timescale among individuals diagnosed with SCZ, BD, and MDD are unclear.

METHODS

This study included 1112 participants (380 individuals diagnosed with SCZ, 330 with BD, 212 with MDD, and 190 demographically matched healthy controls [HCs]). We assembled resting-state EEG data and completed a microstate analysis of all participants using a cross-sectional design.

RESULTS

Our research indicates that SCZ, BD, and MDD exhibit distinct patterns of transition among the four EEG microstate states (A, B, C, and D). The analysis of transition probabilities showed a higher frequency of switching from microstates A to B and from B to A in each patient group compared to the HC group, and less frequent transitions from microstates A to C and from C to A in the SCZ and MDD groups compared to the HC group. And the probability of the microstate switching from C to D and D to C in the SCZ group significantly increased compared to those in the patient and HC groups.

CONCLUSIONS

Our findings provide crucial insights into the abnormalities involved in distributing neural assets and enabling proper transitions between different microstates in patients with major psychiatric disorders.

Cortical gradient perturbation in attention deficit hyperactivity disorder correlates with neurotransmitter-, cell type-specific and chromosome- transcriptomic signatures

AIMS

This study aimed to illuminate the neuropathological landscape of attention deficit hyperactivity disorder (ADHD) by a multiscale macro-micro-molecular perspective from in vivo neuroimaging data.

METHODS

The "ADHD-200 initiative" repository provided multi-site high-quality resting-state functional connectivity (rsfc-) neuroimaging for ADHD children and matched typically developing (TD) cohort. Diffusion mapping embedding model to derive the functional connectome gradient detecting biologically plausible neural pattern was built, and the multivariate partial least square method to uncover the enrichment of neurotransmitomic, cellular and chromosomal gradient-transcriptional signatures of AHBA enrichment and meta-analytic decoding.

RESULTS

Compared to TD, ADHD children presented connectopic cortical gradient perturbations in almost all the cognition-involved brain macroscale networks (all pBH <0.001), but not in the brain global topology. As an intermediate phenotypic variant, such gradient perturbation was spatially enriched into distributions of GABAA/BZ and 5-HT2A receptors (all pBH <0.01) and co-varied with genetic transcriptional expressions (e.g. DYDC2, ATOH7, all pBH <0.01), associated with phenotypic variants in episodic memory and emotional regulations. Enrichment models demonstrated such gradient-transcriptional variants indicated the risk of both cell-specific and chromosome- dysfunctions, especially in enriched expression of oligodendrocyte precursors and endothelial cells (all pperm <0.05) as well enrichment into chromosome 18, 19 and X (pperm <0.05).

CONCLUSIONS

Our findings bridged brain macroscale neuropathological patterns to microscale/cellular biological architectures for ADHD children, demonstrating the neurobiologically pathological mechanism of ADHD into the genetic and molecular variants in GABA and 5-HT systems as well brain-derived enrichment of specific cellular/chromosomal expressions.

A Systematic Review and Meta-analysis: Paternal Anxiety and the Emotional and Behavioral Outcomes in Their Offspring

OBJECTIVE

Anxiety disorders are highly prevalent worldwide; however, the literature lacks a meta-analytic quantification of the risk posed by fathers' anxiety for offspring development. This systematic review and meta-analysis aimed to provide a comprehensive estimate of the magnitude of the association between paternal anxiety and emotional and behavioral problems of offspring.

METHOD

In February 2022, Web of Science, Ovid (Embase, MEDLINE, PsycINFO), Trip Database, and ProQuest were searched to identify all quantitative studies that measured anxiety in fathers and emotional and/or behavioral outcomes in offspring. No limits were set for offspring age, publication language, or publication year. Summary estimates were extracted from the primary studies. Meta-analytic random-effects 3-level models were used to calculate correlation coefficients. Quality was assessed using the Newcastle-Ottawa Scale. The study protocol was preregistered with PROSPERO (CRD42022311501) and adhered to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) reporting guidelines.

RESULTS

Of 11,746 records identified, 98 were included in the meta-analysis. Small but significant associations were found between paternal anxiety and offspring emotional and behavioral problems overall (r = 0.16, 95% CI [0.13, 0.19]) and behavioral (r = 0.19, 95% CI [0.13, 0.24]), emotional (r = 0.15, 95% CI [0.12, 0.18]), anxiety (r = 0.13, 95% CI [0.11, 0.16]), and depression (r = 0.13, 95% CI [0.03, 0.23]) problems. Some significant moderators were identified.

CONCLUSION

Paternal mental health is associated with offspring development, and the offspring of fathers with anxiety symptoms or disorders are at increased risk of negative emotional and behavioral outcomes, in line with the principles of multifinality and pleiotropy. The substantial heterogeneity among studies and the overrepresentation of White European American groups in this literature highlight the need for further research.

DIVERSITY & INCLUSION STATEMENT

While citing references scientifically relevant for this work, we also actively worked to promote inclusion of historically underrepresented racial and/or ethnic groups in science in our reference list.

Differentially Altered Metabolic Pathways in the Amygdala of Subjects with Schizophrenia, Bipolar Disorder and Major Depressive Disorder

Background and hypothesis

A growing number of studies implicate a key role for metabolic processes in psychiatric disorders. Recent studies suggest that ketogenic diet may be therapeutically effective for subgroups of people with schizophrenia (SCZ), bipolar disorder (BPD) and possibly major depressive disorder (MDD). Despite this promise, there is currently limited information regarding brain energy metabolism pathways across these disorders, limiting our understanding of how brain metabolic pathways are altered and who may benefit from ketogenic diets. We conducted gene expression profiling on the amygdala, a key region involved in in the regulation of mood and appetitive behaviors, to test the hypothesis that amygdala metabolic pathways are differentially altered between these disorders.

Study Design

We used a cohort of subjects diagnosed with SCZ, BPD or MDD, and non-psychiatrically ill control subjects (n=15/group), together with our bioinformatic 3-pod analysis consisting of full transcriptome pathway analysis, targeted pathway analysis, leading-edge gene analysis and iLINCS perturbagen analysis.

Study Results

We identified differential expression of metabolic pathways in each disorder. Subjects with SCZ displayed downregulation of mitochondrial respiration and nucleotide metabolism pathways. In comparison, we observed upregulation of mitochondrial respiration pathways in subjects with MDD, while subjects with BPD displayed enrichment of pathways involved in carbohydrate metabolism. Several pathways associated with brain metabolism including immune system processes and calcium ion transport were also differentially altered between diagnosis groups.

Conclusion

Our findings suggest metabolic pathways are differentially altered in the amygdala in these disorders, which may impact approaches for therapeutic strategies.

Interleukin-23 levels in umbilical cord blood are associated with neurodevelopmental trajectories in infancy

Our previous study, which aimed to understand the early neurodevelopmental trajectories of children with and without neurodevelopmental disorders, identified five classes of early neurodevelopmental trajectories, categorized as high normal, normal, low normal, delayed, and markedly delayed. This investigation involved measurement using the Mullen Scale of Early Learning in a representative sample of Japanese infants followed up from the age of 0 to 2 years (Nishimura et al., 2016). In the present study, we investigated the potential association between cytokine concentrations in umbilical cord serum with any of the five classes of neurodevelopmental trajectories previously assigned, as follows: high normal (N = 85, 13.0%), normal (N = 322, 49.1%), low normal (N = 137, 20.9%), delayed (N = 87, 13.3%), and markedly delayed (N = 25, 3.8%) in infancy. Decreased interleukin (IL)-23 levels in the cord blood were associated with the markedly delayed class, independent of potential confounders (odds ratio, 0.44; 95%confidence interval: 0.26-0.73). Furthermore, IL-23 levels decreased as the developmental trajectory became more delayed, demonstrating that IL-23 plays an important role in development, and is useful for predicting the developmental trajectory at birth.

Unique transcriptional signatures correlate with behavioral and psychological symptom domains in Alzheimer's disease

Despite the significant burden, cost, and worse prognosis of Alzheimer's disease (AD) with behavioral and psychological symptoms of dementia (BPSD), little is known about the molecular causes of these symptoms. Using antemortem assessments of BPSD in AD, we demonstrate that individual BPSD can be grouped into 4 domain factors in our cohort: affective, apathy, agitation, and psychosis. Then, we performed a transcriptome-wide analysis for each domain utilizing bulk RNA-seq of post-mortem anterior cingulate cortex (ACC) tissues. Though all 4 domains are associated with a predominantly downregulated pattern of hundreds of differentially expressed genes (DEGs), most DEGs are unique to each domain, with only 22 DEGs being common to all BPSD domains, including TIMP1. Weighted gene co-expression network analysis (WGCNA) yielded multiple transcriptional modules that were shared between BPSD domains or unique to each domain, and NetDecoder was used to analyze context-dependent information flow through the biological network. For the agitation domain, we found that all DEGs and a highly associated transcriptional module were functionally enriched for ECM-related genes including TIMP1, TAGLN, and FLNA. Another unique transcriptional module also associated with the agitation domain was enriched with genes involved in post-synaptic signaling, including DRD1, PDE1B, CAMK4, and GABRA4. By comparing context-dependent changes in DEGs between cases and control networks, ESR1 and PARK2 were implicated as two high-impact genes associated with agitation that mediated significant information flow through the biological network. Overall, our work establishes unique targets for future study of the biological mechanisms of BPSD and resultant drug development.

Behaviour-correlated profiles of cerebellar-cerebral functional connectivity observed in independent neurodevelopmental disorder cohorts

The cerebellum, through its connectivity with the cerebral cortex, plays an integral role in regulating cognitive and affective processes, and its dysregulation can result in neurodevelopmental disorder (NDD)-related behavioural deficits. Identifying cerebellar-cerebral functional connectivity (FC) profiles in children with NDDs can provide insight into common connectivity profiles and their correlation to NDD-related behaviours. 479 participants from the Province of Ontario Neurodevelopmental Disorders (POND) network (typically developing = 93, Autism Spectrum Disorder = 172, Attention Deficit/Hyperactivity Disorder = 161, Obsessive-Compulsive Disorder = 53, mean age = 12.2) underwent resting-state functional magnetic resonance imaging and behaviour testing (Social Communication Questionnaire, Toronto Obsessive-Compulsive Scale, and Child Behaviour Checklist - Attentional Problems Subscale). FC components maximally correlated to behaviour were identified using canonical correlation analysis. Results were then validated by repeating the investigation in 556 participants from an independent NDD cohort provided from a separate consortium (Healthy Brain Network (HBN)). Replication of canonical components was quantified by correlating the feature vectors between the two cohorts. The two cerebellar-cerebral FC components that replicated to the greatest extent were correlated to, respectively, obsessive-compulsive behaviour (behaviour feature vectors, rPOND-HBN = -0.97; FC feature vectors, rPOND-HBN = -0.68) and social communication deficit contrasted against attention deficit behaviour (behaviour feature vectors, rPOND-HBN = -0.99; FC feature vectors, rPOND-HBN = -0.78). The statistically stable (|z| > 1.96) features of the FC feature vectors, measured via bootstrap re-sampling, predominantly comprised of correlations between cerebellar attentional and control network regions and cerebral attentional, default mode, and control network regions. In both cohorts, spectral clustering on FC loading values resulted in subject clusters mixed across diagnostic categories, but no cluster was significantly enriched for any given diagnosis as measured via chi-squared test (p > 0.05). Overall, two behaviour-correlated components of cerebellar-cerebral functional connectivity were observed in two independent cohorts. This suggests the existence of generalizable cerebellar network differences that span across NDD diagnostic boundaries.

Pleiotropy, epistasis and the genetic architecture of quantitative traits

Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.

A splice acceptor variant in RGS6 associated with intellectual disability, microcephaly, and cataracts disproportionately promotes expression of a subset of RGS6 isoforms

Intellectual disability (ID) is associated with an increased risk of developing psychiatric disorders, suggesting a common underlying genetic factor. Importantly, altered signaling and/or expression of regulator of G protein signaling 6 (RGS6) is associated with ID and numerous psychiatric disorders. RGS6 is highly conserved and undergoes complex alternative mRNA splicing producing ~36 protein isoforms with high sequence similarity historically necessitating a global approach in functional studies. However, our recent analysis in mice revealed RGS6 is most highly expressed in CNS with RGS6L(+GGL) isoforms predominating. A previously reported genetic variant in intron 17 of RGS6 (c.1369-1G>C), associated with ID, may provide further clues into RGS6L(+GGL) isoform functional delineation. This variant was predicted to alter a highly conserved canonical 3' acceptor site creating an alternative branch point within exon 18 (included in a subset of RGS6L(+GGL) transcripts) and a frameshift forming an early stop codon. We previously identified this alternative splice site and demonstrated its use generates RGS6Lζ(+GGL) isoforms. Here, we show that the c.1369-1G>C variant disrupts the canonical, preferred (>90%) intron 17 splice site and leads to the exclusive use of the alternate exon 18 splice site, inducing disproportionate expression of a subset of isoforms, particularly RGS6Lζ(+GGL). Furthermore, RGS6 global knockout mice do not exhibit ID. Thus, ID caused by the c.1369-1G>C variant likely results from altered RGS6 isoform expression, rather than RGS6 isoform loss. In summary, these studies highlight the importance of proper RGS6 splicing and identify a previously unrecognized role of G protein signaling in ID.

Schizophrenia risk proteins ZNF804A and NT5C2 interact in cortical neurons

The zinc finger protein 804A (ZNF804A) and the 5'-nucleotidase cytosolic II (NT5C2) genes are amongst the first schizophrenia susceptibility genes to have been identified in large-scale genome-wide association studies. ZNF804A has been implicated in the regulation of neuronal morphology and is required for activity-dependent changes to dendritic spines. Conversely, NT5C2 has been shown to regulate 5' adenosine monophosphate-activated protein kinase activity and has been implicated in protein synthesis in human neural progenitor cells. Schizophrenia risk genotype is associated with reduced levels of both NT5C2 and ZNF804A in the developing brain, and a yeast two-hybrid screening suggests that their encoded proteins physically interact. However, it remains unknown whether this interaction also occurs in cortical neurons and whether they could jointly regulate neuronal function. Here, we show that ZNF804A and NT5C2 colocalise and interact in HEK293T cells and that their rodent homologues, ZFP804A and NT5C2, colocalise and form a protein complex in cortical neurons. Knockdown of the Zfp804a or Nt5c2 genes resulted in a redistribution of both proteins, suggesting that both proteins influence the subcellular targeting of each other. The identified interaction between ZNF804A/ZFP804A and NT5C2 suggests a shared biological pathway pertinent to schizophrenia susceptibility within a neuronal cell type thought to be central to the neurobiology of the disorder, providing a better understanding of its genetic landscape.

Epilepsy and psychiatric comorbidities: A bidirectional mendelian randomization study

STUDY OBJECTIVES

Psychiatric comorbidities are relatively common among patients with epilepsy; however, the underlying mechanisms of this association remain largely unknown. The objective of this Mendelian randomization (MR) study was to analyze the genetic correlations and causality underlying these reciprocal associations.

METHODS

Single-nucleotide polymorphisms associated with epilepsy (29,677 controls and 15,212 cases) and seven psychiatric comorbidities (485,436 controls and 269,495 cases) were identified from genome-wide association studies. Causal significance was estimated using inverse variance weighting. Sensitivity analyses included the weighted median, MR-Egger, and MR-PRESSO. The psychiatric comorbidities analyzed in this study included attention deficit hyperactivity disorder (ADHD), autism spectrum disorder, major depressive disorder, bipolar disorder, schizophrenia, obsessive-compulsive disorder (OCD), and anorexia nervosa.

RESULTS

Both forward and reverse genetic associations were observed for the selected psychiatric disorders. Notably, ADHD was significantly associated with an increased risk of generalized epilepsy (odds ratio [OR], 1.09; 95 % confidence interval [CI], 1.01-1.18; p = 0.013). However, MR-PRESSO detected the existence of pleiotropy (p = 0.001). Additionally, focal epilepsy was significantly associated with a higher risk of OCD (OR, 1.44; 95 % CI, 1.08-1.92; p = 0.013), and all sensitivity tests yielded favorably nonsignificant results. There was no significant genetic association between epilepsy and other examined psychiatric disorders. However, due to the detection of pleiotropy by MR-Egger and considerations related to the threshold for genetic instruments, a cautious approach is warranted in interpreting some of the results.

CONCLUSIONS

This study revealed significant genetic causality between focal epilepsy and OCD, as well as between ADHD and generalized epilepsy. However, no casual significance was observed with other psychiatric comorbidities examined. Considering the inherent limitations of MR studies, further research is warranted to definitively clarify these genetic causal associations.

Polygenic risk scores mediating functioning outcomes through cognitive and clinical features in youth at family risk and controls

Schizophrenia and bipolar disorder exhibit substantial clinical overlap, particularly in individuals at familial high risk, who frequently present sub-threshold symptoms before the onset of illness. Severe mental disorders are highly polygenic traits, but their impact on the stages preceding the manifestation of mental disorders remains relatively unexplored. Our study aimed to examine the influence of polygenic risk scores (PRS) on sub-clinical outcomes over a 2-year period in youth at familial high risk for schizophrenia and bipolar disorder and controls. The sample included 222 children and adolescents, comprising offspring of parents with schizophrenia (n = 38), bipolar disorder (n = 80), and community controls (n = 104). We calculated PRS for psychiatric disorders, neuroticism and cognition using the PRS-CS method. Linear mixed-effects models were employed to investigate the association between PRS and cognition, symptom severity and functioning. Mediation analyses were conducted to explore whether clinical features acted as intermediaries in the impact of PRS on functioning outcomes. SZoff exhibited elevated PRS for schizophrenia. In the entire sample, PRS for depression, neuroticism, and cognitive traits showed associations with sub-clinical features. The effect of PRS for neuroticism and general intelligence on functioning outcomes were mediated by cognition and symptoms severity, respectively. This study delves into the interplay among genetics, the emergence of sub-clinical symptoms and functioning outcomes, providing novel evidence on mechanisms underpinning the continuum from sub-threshold features to the onset of mental disorders. The findings underscore the interplay of genetics, cognition, and clinical features, providing insights for personalized early interventions.

Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Nuclear microRNA-mediated transcriptional control determines adult microglial homeostasis and brain function

Microglia are versatile regulators in brain development and disorders. Emerging evidence links microRNA (miRNA)-mediated regulation to microglial function; however, the exact underlying mechanism remains largely unknown. Here, we uncover the enrichment of miR-137, a neuropsychiatric-disorder-associated miRNA, in the microglial nucleus, and reveal its unexpected nuclear functions in maintaining the microglial global transcriptomic state, phagocytosis, and inflammatory response. Mechanistically, microglial Mir137 deletion increases chromatin accessibility, which contains binding motifs for the microglial master transcription factor Pu.1. Through biochemical and bioinformatics analyses, we propose that miR-137 modulates Pu.1-mediated gene expression by suppressing Pu.1 binding to chromatin. Importantly, we find that increased Pu.1 binding upregulates the target gene Jdp2 (Jun dimerization protein 2) and that knockdown of Jdp2 significantly suppresses the impaired phagocytosis and pro-inflammatory response in Mir137 knockout microglia. Collectively, our study provides evidence supporting the notion that nuclear miR-137 acts as a transcriptional modulator and that this microglia-specific function is essential for maintaining normal adult brain function.

The detect consensus report on Attention Deficit/Hyperactivity Disorder and its management among Turkish children and adolescents (Detect: consensus report on ADHD among Turkish youth)

Attention Deficit/Hyperactivity Disorder (ADHD) is one of the most common and heritable neurodevelopmental disorders which may last through the life-span. A consensus report on diagnosis and management of ADHD among Turkish youth was prepared previously. However, the participants as well as the management options were rather limited and developments in the past decade necessitated a revision and update of the consensus. Therefore, this review aims to summarize the consensus among Child and Adolescent Psychiatrists from Türkiye on the nature and management of pediatric ADHD. For those aims, the etiology of ADHD, diagnostic and evaluation process, epidemiology, developmental presentations, differential diagnoses and comorbidities, course/outcome and pharmacological as well as non-pharmacological management options were reviewed and suggestions for clinical practice are presented. Since ADHD is a chronic disorder with wide-ranging effects on functionality that is frequently accompanied by other mental disorders, a multidimensional therapeutic approach is recommended. However, since the disorder has neurobiological basis, pharmacotherapy represents the mainstay of treatment. Additional therapies may include psychosocial therapy, behavioral therapy, school-based therapeutic approaches, and family education. This review provides recommendations for ADHD at the national and global levels. It contains information about ADHD that will contribute to and facilitate clinicians' decision-making processes. It is advisable to consider this guideline in clinical practice.

Exploring functional dysconnectivity in schizophrenia: alterations in eigenvector centrality mapping and insights into related genes from transcriptional profiles

Schizophrenia is a mental health disorder characterized by functional dysconnectivity. Eigenvector centrality mapping (ECM) has been employed to investigate alterations in functional connectivity in schizophrenia, yet the results lack consistency, and the genetic mechanisms underlying these changes remain unclear. In this study, whole-brain voxel-wise ECM analyses were conducted on resting-state functional magnetic resonance imaging data. A cohort of 91 patients with schizophrenia and 91 matched healthy controls were included during the discovery stage. Additionally, in the replication stage, 153 individuals with schizophrenia and 182 healthy individuals participated. Subsequently, a comprehensive analysis was performed using an independent transcriptional database derived from six postmortem healthy adult brains to explore potential genetic factors influencing the observed functional dysconnectivity, and to investigate the roles of identified genes in neural processes and pathways. The results revealed significant and reliable alterations in the ECM across multiple brain regions in schizophrenia. Specifically, there was a significant decrease in ECM in the bilateral superior and middle temporal gyrus, and an increase in the bilateral thalamus in both the discovery and replication stages. Furthermore, transcriptional analysis revealed 420 genes whose expression patterns were related to changes in ECM, and these genes were enriched mainly in biological processes associated with synaptic signaling and transmission. Together, this study enhances our knowledge of the neural processes and pathways involved in schizophrenia, shedding light on the genetic factors that may be linked to functional dysconnectivity in this disorder.

Clustering Schizophrenia Genes by Their Temporal Expression Patterns Aids Functional Interpretation

BACKGROUND

Schizophrenia is a highly heritable brain disorder with a typical symptom onset in early adulthood. The 2-hit hypothesis posits that schizophrenia results from differential early neurodevelopment, predisposing an individual, followed by a disruption of later brain maturational processes that trigger the onset of symptoms.

STUDY DESIGN

We applied hierarchical clustering to transcription levels of 345 genes previously linked to schizophrenia, derived from cortical tissue samples from 56 donors across the lifespan. We subsequently calculated clustered-specific polygenic risk scores for 743 individuals with schizophrenia and 743 sex- and age-matched healthy controls.

STUDY RESULTS

Clustering revealed a set of 183 genes that was significantly upregulated prenatally and downregulated postnatally and 162 genes that showed the opposite pattern. The prenatally upregulated set of genes was functionally annotated to fundamental cell cycle processes, while the postnatally upregulated set was associated with the immune system and neuronal communication. We found an interaction between the 2 scores; higher prenatal polygenic risk showed a stronger association with schizophrenia diagnosis at higher levels of postnatal polygenic risk. Importantly, this finding was replicated in an independent clinical cohort of 3233 individuals.

CONCLUSIONS

We provide genetics-based evidence that schizophrenia is shaped by disruptions of separable biological processes acting at distinct phases of neurodevelopment. The modeling of genetic risk factors that moderate each other's effect, informed by the timing of their expression, will aid in a better understanding of the development of schizophrenia.

Identification of novel rare variants for anxiety: an exome-wide association study in the UK Biobank

BACKGROUND

Rare variants are believed to play a substantial role in the genetic architecture of mental disorders, particularly in coding regions. However, limited evidence supports the impact of rare variants on anxiety.

METHODS

Using whole-exome sequencing data from 200,643 participants in the UK Biobank, we investigated the contribution of rare variants to anxiety. Firstly, we computed genetic risk score (GRS) of anxiety utilizing genotype data and summary data from a genome-wide association study (GWAS) on anxiety disorder. Subsequently, we identified individuals within the lowest 50% GRS, a subgroup more likely to carry pathogenic rare variants. Within this subgroup, we classified individuals with the highest 10% 7-item Generalized Anxiety Disorder scale (GAD-7) score as cases (N = 1869), and those with the lowest 10% GAD-7 score were designated as controls (N = 1869). Finally, we conducted gene-based burden tests and single-variant association analyses to assess the relationship between rare variants and anxiety.

RESULTS

Totally, 47,800 variants with MAF ≤0.01 were annotated as non-benign coding variants, consisting of 42,698 nonsynonymous SNVs, 489 nonframeshift substitution, 236 frameshift substitution, 617 stop-gain and 40 stop-loss variants. After variation aggregation, 5066 genes were included in gene-based association analysis. Totally, 11 candidate genes were detected in burden test, such as RNF123 (PBonferroni adjusted = 3.40 × 10-6), MOAP1(PBonferroni adjusted = 4.35 × 10-4), CCDC110 (PBonferroni adjusted = 5.83 × 10-4). Single-variant test detected 9 rare variants, such as rs35726701(RNF123)(PBonferroni adjusted = 3.16 × 10-10) and rs16942615(CAMTA2) (PBonferroni adjusted = 4.04 × 10-4). Notably, RNF123, CCDC110, DNAH2, and CSKMT gene were identified in both tests.

CONCLUSIONS

Our study identified novel candidate genes for anxiety in protein-coding regions, revealing the contribution of rare variants to anxiety.

Rare and Common Variants Associated with Alcohol Consumption Identify a Conserved Molecular Network

Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, rare variants have only begun to be studied for their role in alcohol consumption. No studies have examined whether common and rare variants implicate the same genes and molecular networks. To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N=666,978) and whole exome sequencing data (Genebass, N=393,099) to identify a set of common and rare variants for alcohol consumption. Gene-based analysis of each dataset have implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified only by rare variant analysis, but have been associated with related psychiatric traits. We then used a network colocalization procedure to propagate the common and rare gene sets onto a shared molecular network, revealing significant overlap. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. 74 of the genes in the network were previously implicated in comorbid psychiatric or substance use disorders, but had not previously been identified for alcohol-related behaviors, including EXOC2, EPM2A, CACNB3, and CACNG4. Differential gene expression analysis showed enrichment in the liver and several brain regions supporting the role of network genes in alcohol consumption. Thus, genes implicated by common and rare variants identify shared functions relevant to alcohol consumption, which also underlie psychiatric traits and substance use disorders that are comorbid with alcohol use.

Using Dispositions to Understand Otherwise Intractable Causal Pathways to Psychological Problems During Childhood and Adolescence

Studies of the genetic and environmental factors that make children more or less likely to develop distressing and impairing psychological problems, and studies of the psychobiological pathways through which these causal factors operate, have the goal of improving our understanding of the basic nature of psychological problems to develop better methods of prevention and treatment. For this reason, we have long had our eye on the prize of discovering the causes and psychobiological mechanisms underlying each dimension of psychological problems. There are compelling reasons, however, to seek a different and more achievable prize to understand psychological problems. Dimensions of psychological problems are both far too heterogeneous and too highly correlated to line up with distinct causal pathways. In contrast, a small number of orthogonal cognitive and socioemotional dispositional dimensions are correlated with psychological problems in revealing cross-cutting patterns. Each of these dispositions shares its independent causal pathways with psychological problems and help us understand the complex shared and heterogeneous nature of their causal processes. I outline a strategy for understanding the causes and mechanisms of psychological problems using studies of independently measured dispositions.

Genetic risk for hospitalization of African American patients with severe mental illness reveals HLA loci

Background

Mood disorders such as major depressive and bipolar disorders, along with posttraumatic stress disorder (PTSD), schizophrenia (SCZ), and other psychotic disorders, constitute serious mental illnesses (SMI) and often lead to inpatient psychiatric care for adults. Risk factors associated with increased hospitalization rate in SMI (H-SMI) are largely unknown but likely involve a combination of genetic, environmental, and socio-behavioral factors. We performed a genome-wide association study in an African American cohort to identify possible genes associated with hospitalization due to SMI (H-SMI).

Methods

Patients hospitalized for psychiatric disorders (H-SMI; n=690) were compared with demographically matched controls (n=4467). Quality control and imputation of genome-wide data were performed following the Psychiatric Genetic Consortium (PGC)-PTSD guidelines. Imputation of the Human Leukocyte Antigen (HLA) locus was performed using the HIBAG package.

Results

Genome-wide association analysis revealed a genome-wide significant association at 6p22.1 locus in the ubiquitin D (UBD/FAT10) gene (rs362514, p=9.43x10-9) and around the HLA locus. Heritability of H-SMI (14.6%) was comparable to other psychiatric disorders (4% to 45%). We observed a nominally significant association with 2 HLA alleles: HLA-A*23:01 (OR=1.04, p=2.3x10-3) and HLA-C*06:02 (OR=1.04, p=1.5x10-3). Two other genes (VSP13D and TSPAN9), possibly associated with immune response, were found to be associated with H-SMI using gene-based analyses.

Conclusion

We observed a strong association between H-SMI and a locus that has been consistently and strongly associated with SCZ in multiple studies (6p21.32-p22.1), possibly indicating an involvement of the immune system and the immune response in the development of severe transdiagnostic SMI.

The structure of psychiatric comorbidity without selection and assortative mating

The widespread comorbidity observed across psychiatric disorders may be the result of processes such as assortative mating, gene-environment correlation, or selection into population studies. Between-family analyses of comorbidity are subject to these sources of bias, whereas within-family analyses are not. Because of Mendelian inheritance, alleles are randomly assigned within families, conditional on parental alleles. We exploit this variation to compare the structure of comorbidity across broad psychiatric polygenic scores when calculated either between-family (child polygenic scores) or within-family (child polygenic scores regressed on parental polygenic scores) in over 25,000 genotyped parent-offspring trios from the Norwegian Mother Father and Child Cohort study (MoBa). We fitted a series of factor models to the between- and within-family data, which consisted of a single genetic p-factor and a varying number of uncorrelated subfactors. The best-fitting model was identical for between- and within-family analyses and included three subfactors capturing variants associated with neurodevelopment, psychosis, and constraint, in addition to the genetic p-factor. Partner genetic correlations, indicating assortative mating, were not present for the genetic p-factor, but were substantial for the psychosis (b = 0.081;95% CI [0.038,0.124]) and constraint (b = 0.257;95% CI [0.075,0.439]) subfactors. When average factor levels for MoBa mothers and fathers were compared to a population mean of zero we found evidence of sex-specific participation bias, which has implications for the generalizability of findings from cohort studies. Our results demonstrate the power of the within-family design for better understanding the mechanisms driving psychiatric comorbidity and their consequences on population health.