Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis

GenomicSEM Modelling of Diverse Executive Function GWAS Improves Gene Discovery

Previous research has supported the use of latent variables as the gold-standard in measuring executive function. However, for logistical reasons genome-wide association studies (GWAS) of executive function have largely eschewed latent variables in favour of singular task measures. As low correlations have traditionally been found between individual executive function (EF) tests, it is unclear whether these GWAS have truly been measuring the same construct. In this study, we addressed this question by performing a factor analysis on summary statistics from eleven GWAS of EF taken from five studies, using GenomicSEM. Models demonstrated a bifactor structure consistent with previous research, with factors capturing common EF and working memory- specific variance. Furthermore, the GWAS performed on this model identified 20 new genomic risk loci for common EF and 4 for working memory reaching genome-wide significance beyond what was found in the constituent GWAS, together resulting in 29 newly mapped EF genes. These results help to clarify the underlying genetic structure of EF and support the idea that EF GWAS are capable of measuring genetic variance related to latent EF constructs even when not using factor scores. Furthermore, they demonstrate that GenomicSEM can combine GWAS with divergent and non-ideal measures of the same phenotype to improve statistical power.

Genetic Correlates of Treatment-Resistant Depression

Importance

Treatment-resistant depression (TRD) is a major challenge in mental health, affecting a significant number of patients and leading to considerable burdens. The etiological factors contributing to TRD are complex and not fully understood.

Objective

To investigate the genetic factors associated with TRD using polygenic scores (PGS) across various traits and explore their potential role in the etiology of TRD using large-scale genomic data from the All of Us (AoU) Research Program.

Design, Setting, and Participants

This study was a cohort design with observational data from participants in the AoU Research Program who have both electronic health records and genomic data. Data analysis was performed from March 27 to October 24, 2024.

Exposures

PGS for 61 unique traits from 7 domains.

Main Outcomes and Measures

Logistic regressions to test if PGS was associated with treatment-resistant depression (TRD) compared with treatment-responsive major depressive disorder (trMDD). Cox proportional hazard model was used to determine if the progressions from MDD to TRD were associated with PGS.

Results

A total of 292 663 participants (median [IQR] age, 57 (41-69) years; 175 981 female [60.1%]) from the AoU Research Program were included in this analysis. In the discovery set (124 945 participants), 11 of the selected PGS were found to have stronger associations with TRD than with trMDD, encompassing PGS from domains in education, cognition, personality, sleep, and temperament. Genetic predisposition for insomnia (odds ratio [OR], 1.11; 95% CI, 1.07-1.15) and specific neuroticism (OR, 1.11; 95% CI, 1.07-1.16) traits were associated with increased TRD risk, whereas higher education (OR, 0.88; 95% CI, 0.85-0.91) and intelligence (OR, 0.91; 95% CI, 0.88-0.94) scores were protective. The associations held across different TRD definitions (meta-analytic R2 >83%) and were consistent across 2 other independent sets within AoU (the whole-genome sequencing Diversity dataset, 104 388, and Microarray dataset, 63 330). Among 28 964 individuals followed up over time, 3854 developed TRD within a mean of 944 days (95% CI, 883-992 days). All 11 previously identified and replicated PGS were found to be modulating the conversion rate from MDD to TRD.

Conclusions and Relevance

Results of this cohort study suggest that genetic predisposition related to neuroticism, cognitive function, and sleep patterns had a significant association with the development of TRD. These findings underscore the importance of considering psychosocial factors in managing and treating TRD. Future research should focus on integrating genetic data with clinical outcomes to enhance understanding of pathways leading to treatment resistance.

Recent advances in understanding how compulsivity is related to behavioural addictions over their timecourse

Purpose of Review

Behavioural addictions involve loss of control over initially rewarding behaviours, which continue despite adverse consequences. Theoretical models suggest that these patterns of behaviour evolve over time, with compulsive and habitual behaviours held to reflect a loss of behavioural control. Compulsivity can be broadly described as a propensity for (or engagement in) repetitive behaviours that are not aligned with overall goals. Here, we consider whether compulsivity is associated with behavioural addictions at different stages of their development, based on self-report and neurocognitive measures.

Recent Findings

This review found that there is initial evidence that compulsive traits might predispose individuals to engage in problematic behaviours, and that self-report and neurocognitive measures of compulsivity are associated with severity of problematic behaviours even in the early stages of behavioural addictions. In the later stages of behavioural addiction, there is strong evidence for an association of gambling disorder with cognitive inflexibility, but less evidence for an association between compulsivity and other types of behavioural addiction.

Summary

Moving forwards, well-powered longitudinal studies, including studies using ecological momentary assessment (EMA), will be important in robustly developing our understanding of how compulsivity is related to behavioural addictions over their timecourse.

Incorporating polygenic liability and family history for predicting psychiatric diseases in the Taiwan biobank

BACKGROUND

This study investigated the interplay between molecular measures of polygenic risk score (PRS) and conventional measures of family history (FH) on the risk of four psychiatric disorders: schizophrenia (SCZ), bipolar disorder (BPD), major depressive disorder (MDD), and obsessive-compulsive disorder (OCD) in community samples of East Asian populations. We examined the individual and joint associations and relative contributions of PRS and FH and evaluated the potential of combining transdiagnostic PRSs and FHs to improve risk prediction.

METHODS

The genotyping of 106,581 unrelated participants from the Taiwan Biobank was linked to the National Health Insurance Research Database to retrieve information on ICD-defined diseases and FH. A logistic regression model was used to examine the association between PRS and FH in fathers, mothers, and siblings with a risk of psychiatric disorders.

RESULTS

The PRS for SCZ, BPD, MDD, and OCD explained 2.0%, 0.4%, 0.6%, and 0.6%, respectively, and FH explained 1.3%, 1.4%, 2.3%, and 3.4%, respectively, of the variance in the corresponding disease. Incorporating PRS and FH increased the explained variances in SCZ, BPD, MDD, and OCD by 3.2%, 1.7%, 2.8%, and 4.1%, respectively. The effect sizes for PRS and FH in the PRS/FH alone and PRS-FH combined models were generally similar. Simultaneously incorporating the four PRSs and FHs increased the explained variances of SCZ, BPD, MDD, and OCD to 4.7%, 4.7%, 3.3%, and 7.3%, respectively.

CONCLUSIONS

PRS and FH provide independent and complementary information for the identification of psychiatric disorders. The incorporation of transdiagnostic PRSs and FHs improved risk identification.

iPSCs and iPSC-derived cells as a model of human genetic and epigenetic variation

Understanding the interaction between genetic and epigenetic variation remains a challenge due to confounding environmental factors. We propose that human induced Pluripotent Stem Cells (iPSCs) are an excellent model to study the relationship between genetic and epigenetic variation while controlling for environmental factors. In this study, we have created a comprehensive resource of high-quality genomic, epigenomic, and transcriptomic data from iPSC lines and three iPSC-derived cell types (neural stem cell (NSC), motor neuron, monocyte) from three healthy donors. We find that epigenetic variation is most strongly associated with genetic variation at the iPSC stage, and that relationship weakens as epigenetic variation increases in differentiated cells. Additionally, cell type is a stronger source of epigenetic variation than genetic variation. Further, we elucidate a utility of studying epigenetic variation in iPSCs and their derivatives for identifying important loci for GWAS studies and the cell types in which they may be acting.

Genetic evidence of the causal relationships between psychiatric disorders and cardiovascular diseases

OBJECTIVE

Our primary objective is to investigate the causal relationships between 12 psychiatric disorders (PDs) and atrial fibrillation (AF), coronary artery disease (CAD), myocardial infarction (MI), and heart failure (HF).

METHODS

Firstly, we used linkage disequilibrium score regression to calculate the genetic correlations between 12 PDs and 4 cardiovascular diseases (CVDs). Subsequently, we performed two-sample and bidirectional Mendelian randomization (MR) analyses of phenotypes with significant genetic correlations to explore the causal relationships between PDs and CVDs. Inverse variance weighted with modified weights (MW-IVW), Robust Adjusted Profile Score, Inverse Variance Weighted, weighted median and weighted mode were used to evaluate causal effects, with MW-IVW being the main analysis method. And to validate the MR results, we conducted the replicate analyses using data from the FinnGen database.

RESULTS

Conducting MR analyses in phenotypes with significant genetic correlations, we identified bidirectional causal relationships between depression (DEP) and MI (DEP as exposure: OR = 1.1324, 95 % confidence interval (CI): 1.0984-1.1663, P < 0.0001; MI as exposure: OR = 1.0268, 95 % CI: 1.0160-1.0375, P < 0.0001). Similar relationships were observed in Attention Deficit/Hyperactivity Disorder (ADHD) and HF (ADHD as exposure: OR = 1.0270, 95 % CI: 1.0144-1.0395, P < 0.0001; HF as exposure: OR = 1.0980, 95 % CI: 1.0502-1.1458, P < 0.0001).

CONCLUSIONS

In our study, we conducted the comprehensive analyses between 12 PDs and CVDs. By bidirectional MR analysis, we observed significant causal relationships between MI and DEP, HF and ADHD. These findings suggest possible complex causal relationships between PDs and CVDs.

Causal associations between immune cells and psychiatric disorders: a bidirectional mendelian randomization analysis

Extensive researches illuminate a potential interplay between immune traits and psychiatric disorders. However, whether there is the causal relationship between the two remains an unresolved question. We conducted a two-sample bidirectional mendelian randomization by utilizing summary data of 731 immune cell traits from genome-wide association studies (GCST90001391-GCST90002121)) and 11 psychiatric disorders including attention deficit/hyperactivity disorder (ADHD), anxiety disorder, autism spectrum disorder (ASD), bipolar disorder (BIP), anorexia nervosa (AN), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), Tourette syndrome (TS), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), and substance use disorders (cannabis) (SUD) from the Psychiatric Genomics Consortium (PGC). A total of four types of immune signatures (median fluorescence intensities [MFI], relative cell [RC], absolute cell [AC], and morphological parameters [MP]) were included. Effect estimates were obtained by using the inverse-variance-weighted (IVW), weighted median method, Mendelian randomization (MR)-Egger, and corrected by false discovery rate. Outliers were evaluated through the leave-one-out technique. Horizontal pleiotropy was assessed using the MR pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger intercept tests. MR analysis results suggested several immune cell subtypes were casually associated with psychiatric disorders. It was found that CD33br HLA DR + CD14 - AC (Myeloid cell, AC) may contribute to decreasing the risk of BIP (odds ratio [OR] = 0.9179, confidence interval [CI] = 0.8829-0.9542, PFDR = 7.06 × 10-3), and likewise, CD38 on transitional (B cell, MFI) also showed negative causal effect on SCZ risk (OR = 0.9551, CI = 0.9330-0.9776, PFDR = 0.0441). While IgD - CD27 - %lymphocyte (B cell, RC) has causal effect on increasing BIP risk (OR = 1.0184, CI = 1.0079-1.0291, PFDR = 0.0201). In addition, HLA DR + + monocyte %monocyte (TBNK, RC) is likely to increase AN onset (OR = 1.0746, CI = 1.0324-1.1186, PFDR = 0.0506), and CCR2 on CD14 - CD16 + monocyte (Monocyte, MFI) may contribute to PTSD (OR = 1.0591, CI = 1.0275-1.0917, PFDR = 0.0369). Sensitivity analysis revealed consistency of results. Our research elucidates there may be causal links between immune traits and the onset of psychiatric disorders, which established a groundwork for the prospective clinical utilization of immune cells as markers for the diagnosis and early intervention of psychiatric disorders.

Causal Impacts of Psychiatric Disorders on Cognition and the Mediating Effect of Oxidative Stress: A Mendelian Randomization Study

Many psychiatric disorders are associated with major cognitive deficits. However, it is uncertain whether these deficits develop as a result of psychiatric disorders and what shared risk factors might mediate this relationship. Here, we utilized the Mendelian randomization (MR) analysis to investigate the complex causal relationship between nine major psychiatric disorders and three cognitive phenotypes, while also examining the potential mediating role of oxidative stress as a shared biological underpinning. Schizophrenia (SZ), major depressive disorder (MDD), and attention deficit hyperactivity disorder (ADHD) showed a decreasing effect on cognitive performance, intelligence, and education, while bipolar disorder (BPD) increased educational attainment. MR-Clust results exhibit the shared genetic basis between SZ and other psychiatric disorders in relation to cognitive function. Furthermore, when oxidative stress was considered as a potential mediating factor, the associations between SZ and the three dimensions of cognition, as well as between MDD and intelligence and ADHD and intelligence, exhibited larger effect sizes than the overall. Mediation MR analysis also supported the causal effects between psychiatric disorders and cognition via oxidative stress traits, including carotene, vitamin E, bilirubin, and uric acid. Finally, summary-based MR identified 29 potential causal associations of oxidative stress genes with both cognitive performance and psychiatric disorders. Our findings highlight the importance of considering oxidative stress in understanding and potentially treating cognitive impairments associated with psychiatric conditions.

Genomic Analysis of Trichotillomania

Trichotillomania (TTM) is a psychiatric condition in which people feel an overwhelming urge to pull out their hair, resulting in noticeable hair loss and significant distress. Twin, family and candidate gene studies suggest that TTM is at least partly genetic, but no genome-wide analyses have been completed. To fill the gap in this field, we have conducted a case-control study of genotype array data from 101 European ancestry TTM cases and 488 ancestry-matched unaffected controls. TTM cases were ascertained in the USA through web-based recruitment, patient support groups, and conferences organized by the Trichotillomania Learning Center. Following clinical confirmation of a TTM diagnosis, patients completed self-report assessments of frequency and duration of hair pulling, other psychiatric symptoms, and family history. Unaffected controls were also ascertained in the USA and were matched to cases by ancestry. In the first formal genome-wide association study of TTM, we did not identify any common variants with a genome-wide significant (P < 5×10 -8 ) association level with case status. We found that TTM cases carry a higher load of common polygenic risk for psychiatric disorders than unaffected controls ( P = 0.008). We also detected copy number variants previously associated with neuropsychiatric disorders in TTM cases (specifically, deletions in NRXN1, CSMD1 , and 15q11.2). These results further support genetics' role in the etiology of TTM and suggest that larger studies are likely to identify risk variation and, ultimately, specific risk genes associated with the condition.

Causal associations between iron levels in subcortical brain regions and psychiatric disorders: a Mendelian randomization study

Despite observational studies linking brain iron levels to psychiatric disorders, the exact causal relationship remains poorly understood. This study aims to examine the relationship between iron levels in specific subcortical brain regions and the risk of psychiatric disorders. Utilizing two-sample Mendelian randomization (MR) analysis, this study investigates the causal associations between iron level changes in 16 subcortical nuclei and eight major psychiatric disorders, including schizophrenia (SCZ), major depressive disorder (MDD), autism spectrum disorders (ASD), attention-deficit/hyperactivity disorder, bipolar disorder, anxiety disorders, obsessive-compulsive disorder, and insomnia. The genetic instrumental variables linked to iron levels and psychiatric disorders were derived from the genome-wide association studies data of the UK Biobank Brain Imaging and Psychiatric Genomics Consortium. Bidirectional causal estimation was primarily obtained using the inverse variance weighting (IVW) method. Iron levels in the left substantia nigra showed a negative association with the risk of MDD (ORIVW = 0.94, 95% CI = 0.91-0.97, p < 0.001) and trends with risk of SCZ (ORIVW = 0.90, 95% CI = 0.82-0.98, p = 0.020). Conversely, iron levels in the left putamen were positively associated with the risk of ASD (ORIVW = 1.11, 95% CI = 1.04-1.19, p = 0.002). Additionally, several bidirectional trends were observed between subcortical iron levels and the risk for psychiatric disorders. Lower iron levels in the left substantia nigra may increase the risk of MDD, and potentially increase the risk of SCZ, indicating a potential shared pathogenic mechanism. Higher iron levels in the left putamen may lead to the development of ASD. The observed bidirectional trends between subcortical iron levels and psychiatric disorders, indicate the importance of the underlying biomechanical interactions between brain iron regulation and these disorders.

The genetic architecture of differentiating behavioral and emotional problems in early life

BACKGROUND

Early in life, behavioral and cognitive traits associated with risk for developing a psychiatric condition are broad and undifferentiated. As children develop, these traits differentiate into characteristic clusters of symptoms and behaviors that ultimately form the basis of diagnostic categories. Understanding this differentiation process - in the context of genetic risk for psychiatric conditions, which is highly generalized - can improve early detection and intervention.

METHODS

We modeled the differentiation of behavioral and emotional problems from age 1.5-5 years (behavioral problems - emotional problems = differentiation score) in a pre-registered study of ∼79,000 children from the population-based Norwegian Mother, Father, and Child Cohort Study. We used genomic structural equation modeling to identify genetic signal in differentiation and total problems, investigating their links with 11 psychiatric and neurodevelopmental conditions. We examined associations of polygenic scores (PGS) with both outcomes and assessed the relative contributions of direct and indirect genetic effects in ∼33,000 family trios.

RESULTS

Differentiation was primarily genetically correlated with psychiatric conditions via a "neurodevelopmental" factor. Total problems were primarily associated with the "neurodevelopmental" factor and "p"-factor. PGS analyses revealed an association between liability to ADHD and differentiation (β=0.11 [0.10,0.12]), and a weaker association with total problems (β=0.06 [0.04,0.07]). Trio-PGS analyses showed predominantly direct genetic effects on both outcomes.

CONCLUSIONS

We uncovered genomic signal in the differentiation process, mostly related to common variants associated with neurodevelopmental conditions. Investigating the differentiation of early life behavioral and emotional problems may enhance our understanding of the developmental emergence of different psychiatric and neurodevelopmental conditions.

Advancing Obsessive-Compulsive Disorder Research: Insights from Transgenic Animal Models and Innovative Therapies

Obsessive-compulsive disorder (OCD) is a prevalent, chronic, and severe neuropsychiatric disorder that leads to illness-related disability. Despite the availability of several treatments, many OCD patients respond inadequately, because the underlying neural mechanisms remain unclear, necessitating the establishment of many animal models, particularly mouse models, to elucidate disease mechanisms and therapeutic strategies better. Although the development of animal models is ongoing, there remain many comprehensive summaries and updates in recent research, hampering efforts to develop novel treatments and enhance existing interventions. This review summarizes the phenotypes of several commonly used models and mechanistic insights from transgenic models of OCD, such as knockout mouse models. In addition, we present the advantages and limitations of these models and discuss their future in helping further understand the pathophysiology and advanced treatment. Here, we highlight current frontline treatment approaches for OCD, including neuromodulation and surgical interventions, and propose potential future directions. By studying gene mutations and observing phenotypes from available OCD animal models, researchers have classified the molecular signatures of each model reminiscent of changes in brain areas and neural pathways, with the hope of guiding the future selection of the most appropriate models for specific research in the OCD field.

Eating Problems Among Adolescent Boys and Girls Before and During the Covid-19 Pandemic

OBJECTIVE

Studies suggest that adolescents reported more eating problems during the pandemic. Using a population-based sample, we compared eating problems-and how they associate with a range of personal characteristics and genetic factors-among adolescents before (June 2017-April 2020) versus during (April 2020-December 2022) the pandemic.

METHOD

Based on a preregistered analysis plan, we used cross-sectional data collected from 22,706 14-16-year-olds over 6 years (55% during the pandemic) in the Norwegian Mother, Father, and Child Cohort. We used measurement invariance analyses to compare the level of eating restraint and body concern before and during the pandemic, and multi-group structural equation models to estimate pre-pandemic and pandemic patterns of associations.

RESULTS

Pandemic responders generally reported more eating problems than pre-pandemic responders, specifically on dieting and body dissatisfaction. However, after adjusting for a general linear increase in eating problems across all 6 years of data collection, the pandemic itself seems to be associated with more eating problems only among girls, reporting more eating restraints (meanΔ = 0.14 [CI: 0.07, 0.20]) and body concern (meanΔ = 0.17 [CI: 0.11, 0.23]). Associations between eating problems and a range of other characteristics did not differ across the pandemic and pre-pandemic groups.

CONCLUSIONS

There was a general increase in eating problems among 14-16-year-olds over time. Adjusting for this trend, the pandemic seems to exacerbate problems among girls. Although the mechanisms are unclear, our results point to factors susceptible to change that could have been intensified during the pandemic (e.g., screen time, mental distress). Our results highlight the importance of recognizing sex-specific differences in eating problems.

Causal association between mitochondrial function and psychiatric disorders: Insights from a bidirectional two-sample Mendelian randomization study

BACKGROUND

Previous observational studies have suggested that there appears to be a close association between mitochondrial function and psychiatric disorders, but whether a causal role exists remains unclear.

METHODS

We extracted genetic instruments for 67 mitochondrial-related proteins and 10 psychiatric disorders from publicly available genome-wide association studies, and employed five distinct MR methods and false discovery rate correction to detect causal associations between them. Additionally, we conducted a series of sensitivity tests and additional model analysis to ensure the robustness of the results. For potential causal associations, we further performed reverse MR analyses to assess the impact of reverse causality.

RESULTS

We identified a total of 2 significant causal associations and 24 suggestive causal associations. Specifically, Phenylalanine-tRNA ligase was found to increase the risk of Alzheimer's disease, while Mitochondrial glutamate carrier 2 decreased the risk of autism spectrum disorder. Furthermore, there was no evidence of significant pleiotropy, heterogeneity, or reverse causality.

LIMITATIONS

This study was limited to individuals of European ancestry, and the conclusions drawn are merely revelatory.

CONCLUSION

This study provides novel insights into the relationship between mitochondria and psychiatric disorders, as well as the pathogenesis and treatment strategies for psychiatric disorders.

Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus

BACKGROUND

Increasing evidence suggests a complex interplay between psychiatric disorders and metabolic dysregulations. However, most research has been limited to specific disorder pairs, leaving a significant gap in our understanding of the broader psycho-metabolic nexus.

METHODS

This study leveraged large-scale cohort data and genome-wide association study (GWAS) summary statistics, covering 8 common psychiatric disorders and 43 metabolic traits. We introduced a comprehensive analytical strategy to identify shared genetic bases sequentially, from key genetic correlation regions to local pleiotropy and pleiotropic genes. Finally, we developed polygenic risk score (PRS) models to translate these findings into clinical applications.

FINDINGS

We identified significant bidirectional clinical risks between psychiatric disorders and metabolic dysregulations among 310,848 participants from the UK Biobank. Genetic correlation analysis confirmed 104 robust trait pairs, revealing 1088 key genomic regions, including critical hotspots such as chr3: 47588462-50387742. Cross-trait meta-analysis uncovered 388 pleiotropic single nucleotide variants (SNVs) and 126 shared causal variants. Among variants, 45 novel SNVs were associated with psychiatric disorders and 75 novel SNVs were associated with metabolic traits, shedding light on new targets to unravel the mechanism of comorbidity. Notably, RBM6, a gene involved in alternative splicing and cellular stress response regulation, emerged as a key pleiotropic gene. When psychiatric and metabolic genetic information were integrated, PRS models demonstrated enhanced predictive power.

INTERPRETATION

The study highlights the intertwined genetic and clinical relationships between psychiatric disorders and metabolic dysregulations, emphasising the need for integrated approaches in diagnosis and treatment.

FUNDING

The National Key Research and Development Program of China (2023YFC2506200, SHH). The National Natural Science Foundation of China (82273741, SY).

mFusion: a multiscale fusion method bridging neuroimages to genes through neurotransmissions in mental health disorders

Mental health disorders emerge from complex interactions among neurobiological processes across multiple scales, which poses challenges in uncovering pathological pathways from molecular dysfunction to neuroimaging changes. Here, we proposed a multiscale fusion (mFusion) method to evaluate the relevance of each gene to the neuroimaging traits of mental health disorders. We combined gene-neuroimaging associations with gene-positron emission tomography (PET) and PET-neuroimaging associations using protein-protein interaction networks, where various genes traced by PET maps are involved in neurotransmission. Compared with previous methods, the proposed algorithm identified more disease genes on both simulated and empirical data sets. Applying mFusion to eight mental health disorders, we found that these disorders formed three clusters with distinct associated genes. In summary, mFusion is a promising tool of prioritizing genes for mental health disorders by establishing gene-PET-neuroimaging pathways.

Ketogenic Diet as a Nutritional Metabolic Intervention for Obsessive-Compulsive Disorder: A Narrative Review

The substantial evidence supporting the ketogenic diet (KD) in epilepsy management has spurred research into its effects on other neurological and psychiatric conditions. Despite differences in characteristics, symptoms, and underlying mechanisms, these conditions share common pathways that the KD may influence. The KD reverses metabolic dysfunction. Moreover, it has been shown to support neuroprotection through mechanisms such as neuronal energy support, inflammation reduction, amelioration of oxidative stress, and reversing mitochondrial dysfunction. The adequate intake of dietary nutrients is essential for maintaining normal brain functions, and strong evidence supports the role of nutrition in the treatment and prevention of many psychiatric and neurological disorders. Obsessive-compulsive disorder (OCD) is a neuropsychiatric condition marked by persistent, distressing thoughts or impulses (obsessions) and repetitive behaviors performed in response to these obsessions (compulsions). Recent studies have increasingly examined the role of nutrition and metabolic disorders in OCD. This narrative review examines current evidence on the potential role of the KD in the treatment of OCD. We explore research on the KD's effects on psychiatric disorders to assess its potential relevance for OCD treatment. Additionally, we identify key gaps in the preclinical and clinical research that warrant further study in applying the KD as a metabolic therapy for OCD.

The Causal Relationships Between Inflammatory Proteins, Brain Structure, and Psychiatric Disorders: A Two-Step Mendelian Randomization Analysis

BACKGROUND AND HYPOTHESIS

Inflammatory proteins are implicated in psychiatric disorders, but the causality and underlying mechanisms remain unclear.

STUDY DESIGN

We conducted bidirectional Mendelian randomization (MR) using genetic variants from genome-wide association studies (GWAS) for 91 inflammatory proteins (N = 14 824) and 11 psychiatric disorders (N = 9725 to 1 035 760). The primary analysis used the inverse variance weighted (IVW) method, with additional sensitivity analyses to confirm robustness. A two-step MR approach assessed whether brain imaging-derived phenotypes (IDPs) mediated the observed effects.

STUDY RESULTS

Forward MR analysis found the protective effect of CD40 on schizophrenia (SCZ) (IVW OR = 0.90, P = 5.29 × 10-6) and bipolar disorder (BD) (IVW OR = 0.89, P = 5.08 × 10-6). Reverse MR demonstrated that increased genetic risk of Tourette's syndrome (TS) was associated with reduced Fms-associated tyrosine kinase 3 ligand (Flt3L) levels (Flt3L) (Wald Ratio beta = -0.42, P = 1.99 × 10-7). The protective effect of CD40 on SCZ was partially mediated by the modulation of fractional anisotropy (FA) values in the right and left superior frontal occipital fasciculus, with mediation proportions of 9.6% (P = .025) and 11.5% (P = .023), respectively.

CONCLUSION

CD40 exerts an immunoprotective effect on SCZ and BD, and the effect of CD40 on SCZ was partially mediated through modulation of FA values in the superior frontal occipital fasciculus. These findings enhance comprehension of the etiology of these psychiatric conditions and underscore the promise of therapeutic strategies aimed at inflammatory proteins.

Neurobiology of Obsessive-Compulsive Disorder from Genes to Circuits: Insights from Animal Models

Obsessive-compulsive disorder (OCD) is a chronic, severe psychiatric disorder that has been ranked by the World Health Organization as one of the leading causes of illness-related disability, and first-line interventions are limited in efficacy and have side-effect issues. However, the exact pathophysiology underlying this complex, heterogeneous disorder remains unknown. This scenario is now rapidly changing due to the advancement of powerful technologies that can be used to verify the function of the specific gene and dissect the neural circuits underlying the neurobiology of OCD in rodents. Genetic and circuit-specific manipulation in rodents has provided important insights into the neurobiology of OCD by identifying the molecular, cellular, and circuit events that induce OCD-like behaviors. This review will highlight recent progress specifically toward classic genetic animal models and advanced neural circuit findings, which provide theoretical evidence for targeted intervention on specific molecular, cellular, and neural circuit events.

Transcriptomic Evaluation of a Stress Vulnerability Network Using Single-Cell RNA Sequencing in Mouse Prefrontal Cortex

BACKGROUND

Increased vulnerability to stress is a major risk factor for several mood disorders, including major depressive disorder. Although cellular and molecular mechanisms associated with depressive behaviors following stress have been identified, little is known about the mechanisms that confer the vulnerability that predisposes individuals to future damage from chronic stress.

METHODS

We used multisite in vivo neurophysiology in freely behaving male and female C57BL/6 mice (n = 12) to measure electrical brain network activity previously identified as indicating a latent stress vulnerability brain state. We combined this neurophysiological approach with single-cell RNA sequencing of the prefrontal cortex to identify distinct transcriptomic differences between groups of mice with inherent high and low stress vulnerability.

RESULTS

We identified hundreds of differentially expressed genes (padjusted < .05) across 5 major cell types in animals with high and low stress vulnerability brain network activity. This unique analysis revealed that GABAergic (gamma-aminobutyric acidergic) neuron gene expression contributed most to the network activity of the stress vulnerability brain state. Upregulation of mitochondrial and metabolic pathways also distinguished high and low vulnerability brain states, especially in inhibitory neurons. Importantly, genes that were differentially regulated with vulnerability network activity significantly overlapped (above chance) with those identified by genome-wide association studies as having single nucleotide polymorphisms significantly associated with depression as well as genes more highly expressed in postmortem prefrontal cortex of patients with major depressive disorder.

CONCLUSIONS

This is the first study to identify cell types and genes involved in a latent stress vulnerability state in the brain.

Association between blood mitochondrial DNA copy number and mental disorders: A bidirectional two-sample mendelian randomization study

BACKGROUND

Mitochondria is essential for cellular energy production, oxidative stress, and apoptosis. Mitochondrial DNA (mtDNA) encodes essential proteins for mitochondrial function. Although several studies have explored the association between changes in mtDNA copy number (mtDNA-CN) and risk of mental disorders, the results remain debated. This study used a bidirectional two-sample Mendelian randomization (MR) analysis to examine the genetic causality between mtDNA-CN and mental disorders.

METHODS

Genome-wide association study (GWAS) data for mtDNA-CN were sourced from UK biobank, involving 383,476 European cases. GWAS data for seven mental disorders-attention deficit/hyperactivity disorder, autism spectrum disorder (ASD), schizophrenia, bipolar disorder, major depressive disorder, anxiety, and obsessive-compulsive disorder-were primarily obtained from the Psychiatric Genomics Consortium. Causal associations were assessed using inverse variance weighting, with sensitivity analyses via the weighted median and MR-Egger methods. Reverse MR considered the seven mental disorders as exposures. All analyses were replicated with additional mtDNA-CN GWAS data from 465,809 individuals in the Heart and Ageing Research in Genomic Epidemiology consortium and the UK Biobank.

RESULTS

Forward MR observed a 27 % decrease in the risk of ASD per standard deviation increase in genetically determined blood mtDNA-CN (OR = 0.73, 95%CI: 0.58-0.92, p = 0.002), with no causal effects on other disorders. Additionally, reverse MR did not indicate a causal association between any of the mental disorders and mtDNA-CN. Validation analyses corroborated these findings, indicating their robustness.

CONCLUSIONS

Our study supports the potential causal association between mtDNA-CN and the risk of ASD, suggesting that mtDNA-CN could serve as a promising biomarker for early screening of ASD.

Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and somatic traits

Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and somatic traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and somatic traits were calculated in European-ancestry (EUR; n = 5691) participants and, when discovery datasets were available, for African-ancestry (AFR; n = 4918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGSMDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGSBMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and somatic traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.

Convergent molecular signatures across eating disorders and obsessive-compulsive disorder in the human brain

Eating disorders (ED) and obsessive-compulsive disorder (OCD) exhibit significant clinical and genetic overlap, yet their shared molecular mechanisms remain unclear. We conducted a transcriptomic investigation of the dorsolateral prefrontal cortex (DLPFC) and caudate from 86 controls, 57 ED, and 27 OCD cases. ED was associated with robust differentially expressed genes (DEGs): 102 DEGs the DLPFC and 222 in the caudate (FDR < 1%) and replicated in an independent cohort. For OCD, no DEGs reached significance; however, meta-analysis with extant data identified 57 DEGs in the caudate. High concordance in transcriptomic changes was observed between ED and OCD in both regions (DLPFC r=0.67, caudate r=0.75). A combined ED+OCD analysis uncovered 233 DEGs in the DLPFC and 816 in the caudate, implicating disrupted GABAergic neuron function, neuroendocrine pathways, metabolism, and synaptic processes. Genetically regulated expression analysis identified nine genes with strong evidence for increasing ED risk, further validating these pathways. These findings reveal a shared molecular basis for ED and OCD, offering new insights into their pathobiology and potential therapeutic targets.

DNA methylation as a possible mechanism linking childhood adversity and health: results from a 2-sample mendelian randomization study

Childhood adversity is an important risk factor for adverse health across the life course. Epigenetic modifications, such as DNA methylation (DNAm), are a hypothesized mechanism linking adversity to disease susceptibility. Yet, few studies have determined whether adversity-related DNAm alterations are causally related to future health outcomes or if their developmental timing plays a role in these relationships. Here, we used 2-sample mendelian randomization to obtain stronger causal inferences about the association between adversity-associated DNAm loci across development (ie, birth, childhood, adolescence, and young adulthood) and 24 mental, physical, and behavioral health outcomes. We identified particularly strong associations between adversity-associated DNAm and attention-deficit/hyperactivity disorder, depression, obsessive-compulsive disorder, suicide attempts, asthma, coronary artery disease, and chronic kidney disease. More of these associations were identified for birth and childhood DNAm, whereas adolescent and young adulthood DNAm were more closely linked to mental health. Childhood DNAm loci also had primarily risk-suppressing relationships with health outcomes, suggesting that DNAm might reflect compensatory or buffering mechanisms against childhood adversity rather than acting solely as an indicator of disease risk. Together, our results suggest adversity-related DNAm alterations are linked to both physical and mental health outcomes, with particularly strong impacts of DNAm differences emerging earlier in development.

A burden of rare copy number variants in obsessive-compulsive disorder

Current genetic research on obsessive-compulsive disorder (OCD) supports contributions to risk specifically from common single nucleotide variants (SNVs), along with rare coding SNVs and small insertion-deletions (indels). The contribution to OCD risk from rare copy number variants (CNVs), however, has not been formally assessed at a similar scale. Here we describe an analysis of rare CNVs called from genotype array data in 2248 deeply phenotyped OCD cases and 3608 unaffected controls from Sweden and Norway. Cases carry an elevated burden of CNVs ≥30 kb in size (OR = 1.12, P = 1.77 × 10-3). The excess rate of these CNVs in cases versus controls was around 0.07 (95% CI 0.02-0.11, P = 2.58 × 10-3). This signal was largely driven by CNVs overlapping protein-coding regions (OR = 1.19, P = 3.08 × 10-4), particularly deletions impacting loss-of-function intolerant genes (pLI >0.995, OR = 4.12, P = 2.54 × 10-5). We did not identify any specific locus where CNV burden was associated with OCD case status at genome-wide significance, but we noted non-random recurrence of CNV deletions in cases (permutation P = 2.60 × 10-3). In cases where sufficient clinical data were available (n = 1612) we found that carriers of neurodevelopmental duplications were more likely to have comorbid autism (P < 0.001), and that carriers of deletions overlapping neurodevelopmental genes had lower treatment response (P = 0.02). The results demonstrate a contribution of rare CNVs to OCD risk, and suggest that studies of rare coding variation in OCD would have increased power to identify risk genes if this class of variation were incorporated into formal tests.

Genomic structural equation modeling reveals latent phenotypes in the human cortex with distinct genetic architecture

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs, although sensitivity analyses indicated that other structures were plausible. The multivariate GWASs of the GIBNs identified 74 genome-wide significant (GWS) loci (p < 5 × 10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed between attention deficit hyperactivity disorder (ADHD) and major depressive disorder (MDD). CT GIBNs displayed a negative genetic correlation with alcohol dependence. Even though we observed model instability in our application of genomic SEM to high-dimensional data, jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across neuroimaging phenotypes offers new insights into the genetics of cortical structure and relationships to psychopathology.

Experience-dependent grooming microstructure alterations and gastrointestinal dysfunction in the SAPAP3 knockout mouse model of compulsive behaviour

BACKGROUND

Compulsive- and anxiety-like behaviour can be efficiently modelled in SAPAP3 knockout (KO) mice, a preclinical model of relevance to obsessive-compulsive disorder (OCD). Although there is emerging evidence in the clinical literature of gastrointestinal dysfunction in OCD, no previous studies have investigated gut function in preclinical models of relevance to OCD. Similarly, the effects of voluntary exercise (EX) or environmental enrichment (EE) have not yet been explored in this context.

METHOD

We comprehensively phenotyped the SAPAP3 KO mouse model, including the assessment of grooming microstructure, anxiety- and depressive-like behaviour, and gastrointestinal function. Mice were exposed to either standard housing (SH), exercise (EX, provided by giving mice access to running wheels), or environmental enrichment (EE) for 4 weeks to investigate the effects of enriched housing conditions in this animal model relevant to OCD.

FINDINGS

Our study is the first to assess grooming microstructure, perseverative locomotor activity, and gastrointestinal function in SAPAP3 KO mice. We are also the first to report a sexually dimorphic effect of grooming in young-adult SAPAP3 KO mice; along with changes to grooming patterning and indicators of gut dysfunction, which occurred in the absence of gut dysbiosis in this model. Overall, we found no beneficial effects of voluntary exercise or environmental enrichment interventions in this mouse model; and unexpectedly, we revealed a deleterious effect of wheel-running exercise on grooming behaviour. We suspect that the detrimental effects of experimental housing in our study may be indicative of off-target effects of stress-a conclusion that warrants further investigation into the effects of chronic stress in this preclinical model of compulsive behaviour.

Neuroticism and posttraumatic stress disorder: A Mendelian randomization analysis

OBJECTIVE

Epidemiological studies revealed an unestablished association between neuroticism and posttraumatic stress disorder (PTSD) and we conducted mendelian randomization (MR) analyses to examine whether neuroticism clusters of worry, depressed affect, and sensitivity to environmental stress and adversity (SESA) were involved in the development of PTSD.

METHOD

We obtained data on three neuroticism clusters, PTSD, and nine other psychiatric disorders from genome-wide association studies summary statistics and employed univariable, multivariable, and mediation MR analyses to explore causal associations among them.

RESULTS

Neuroticism clusters were linked with PTSD (depressed affect (odds ratio [OR]: 2.94 [95% confidence interval: 2.21-3.92]); SESA (2.69 [1.95-3.71]; worry (1.81 [1.37-2.99])). Neuroticism clusters were also associated with psychiatric disorders, with the depressed effect on panic disorder (PD) (2.60 [1.14-5.91]), SESA on anorexia nervosa (AN) (2.77 [1.95-3.94]) and schizophrenia (2.55 [1.99-3.25]), worry on major depressive disorder (MDD) (2.58 [2.19-3.05]). In multivariable MR, only the SESA-PTSD association remained (2.60 [2.096, 3.107]) while worry-PTSD and depressed affect-PTSD associations attenuated to nonsignificance. Mediation MR analyses suggested that PD mediated 3.76% of the effect of depressed effect on PTSD and AN mediated 10.33% of the effect of SESA on PTSD.

CONCLUSION

Delving deeper into neuroticism clusters, we comprehensively understand the role of neuroticism in PTSD.

Mendelian Randomization Study Supports Genetic Liability to Obsessive-Compulsive Disorder Associated With the Risk of Alzheimer's Disease

BACKGROUND

Observational studies have suggested that obsessive-compulsive disorder (OCD) may be associated with Alzheimer's disease (AD). However, whether OCD is a causal risk factor for AD remains unclear. This study aimed to assess the causal effect of OCD on AD risk by performing a two-sample Mendelian randomization (MR) analysis.

METHODS

Genome-wide association summary statistics were obtained for OCD, comprising 2688 cases and 7037 controls, as well as for AD, including 21,982 cases and 41,944 controls from Kunkle et al.'s study, and 39,918 cases and 358,140 controls from Wightman et al.'s study. On the basis of two diverse thresholds, OCD-associated genetic variants were screened as instrumental variables (IVs) for subsequent MR analyses. Inverse variance weighed was the primary MR method. MR-Egger, weighted median, and weighted mode were used as supplementary MR methods. Various sensitivity tests assessed the reliability of MR results.

RESULTS

On the basis of strict IV selecting thresholds, inverse-variance weighted (IVW) identified significant causal associations between genetic liability to OCD and increased risk of AD in two different sources ((i) Kunkle et al.: odds ratio [OR] = 1.070, 95% confidence interval [CI]: 1.015-1.127, p = 0.012; (ii) Wightman et al. 0.012; (iii) Wightman et al.: OR = 1.051, 95% CI: 1.014-1.090, p = 0.007). Three other supplementary MR methods yielded similar results to IVWs (OR > 1). Furthermore, all results were replicated in MR analyses based on lenient IV selecting thresholds. The sensitivity tests indicated that MR results were stable and not affected by significant horizontal pleiotropy.

CONCLUSIONS

This comprehensive MR study suggests that genetic liability to OCD is a causal risk factor for AD. Early intervention in patients with OCD may be beneficial in preventing future AD progression.

Nine Neuroimaging-AI Endophenotypes Unravel Disease Heterogeneity and Partial Overlap across Four Brain Disorders: A Dimensional Neuroanatomical Representation

Disease heterogeneity poses a significant challenge for precision diagnostics. Recent work leveraging artificial intelligence has offered promise to dissect this heterogeneity by identifying complex intermediate brain phenotypes, herein called dimensional neuroimaging endophenotypes (DNEs). We advance the argument that these DNEs capture the degree of expression of respective neuroanatomical patterns measured, offering a dimensional neuroanatomical representation for studying disease heterogeneity and similarities of neurologic and neuropsychiatric diseases. We investigate the presence of nine such DNEs derived from independent yet harmonized studies on Alzheimer's disease (AD1-2)1, autism spectrum disorder (ASD1-3)2, late-life depression (LLD1-2)3, and schizophrenia (SCZ1-2)4, in the general population of 39,178 participants in the UK Biobank study. Phenome-wide associations revealed prominent associations between the nine DNEs and phenotypes related to the brain and other human organ systems. This phenotypic landscape aligns with the SNP-phenotype genome-wide associations, revealing 31 genomic loci associated with the nine DNEs (Bonferroni corrected P-value < 5×10-8/9). The DNEs exhibited significant genetic correlations, colocalization, and causal relationships with multiple human organ systems and chronic diseases. A causal effect (odds ratio=1.25 [1.11, 1.40], P-value=8.72×10-4) was established from AD2, characterized by focal medial temporal lobe atrophy, to AD. The nine DNEs, along with their polygenic risk scores, significantly enhanced the predictive accuracy for 14 systemic disease categories, particularly for conditions related to mental health and the central nervous system, as well as mortality outcomes. These findings underscore the potential of the nine DNEs to capture the expression of disease-related brain phenotypes in individuals of the general population and to relate such measures with genetics, lifestyle factors, and chronic diseases. All results are publicly available at https://labs-laboratory.com/medicine/.

Assortative mating across nine psychiatric disorders is consistent and persistent over cultures and generations

Emerging evidence has shown that assortative mating (AM) is a key factor that shapes the landscape of complex human traits. It can increase the overall prevalence of disorders, influence occurrences of comorbidities, and bias estimation of genetic architectures. However, there is lack of large-scale studies to examine the cultural differences and the generational trends of AM for psychiatric disorders. Here, using national registry datasets, we conduct the largest scale of AM analyses on nine psychiatric disorders, with up to 1.4 million mated cases and 6 million matched controls. We performed meta-analyses on AM estimates from Taiwan, Denmark, and Sweden, to examine the potential impact of cultural differences. Generational changes for people born after 1930s were investigated as well. We found that AM of psychiatric disorders are consistent across nations and persistent over generations, with a small proportion of disorders showing generational changes of AM. Our results provide additional insight into the mechanisms of AM across psychiatric disorders and have evident implications on the estimation of the genetic architectures of psychiatric disorders.

Phenome-Wide Association Study of Latent Autoimmune Diabetes from a Southern Mexican Population Implicates rs7305229 with Plasmatic Anti-Glutamic Acid Decarboxylase Autoantibody (GADA) Levels

Latent autoimmune diabetes in adults (LADA) is characterized by the presence of glutamate decarboxylase autoantibodies (GADA). LADA has intermediate features between type 1 diabetes and type 2 diabetes. In addition, genetic risk factors for both types of diabetes are present in LADA. Nonetheless, evidence about the genetics of LADA in non-European populations is scarce. This study aims to perform a genome-wide association study with a phenome-wide association study of LADA in a southeastern Mexican population. We included 59 patients diagnosed with LADA from a previous study and 3121 individuals without diabetes from the MxGDAR/ENCODAT database. We utilized the GENESIS package in R to perform the genome-wide association study (GWAS) of LADA and PLINK for the phenome-wide association study (PheWAS) of LADA features. Nine polymorphisms reach the nominal association level (1 × 10-5) in the GWAS. The PheWAS showed that rs7305229 is genome-wide and associated with serum GADA levels in our sample (p = 1.84 × 10-8). rs7305229 is located downstream of the FAIM2 gene; previous reports associate FAIM2 variants with childhood obesity, body mass index, body adiposity measures, lymphocyte CD8+ activity, and anti-thyroid peroxidase antibodies. Our findings reveal that rs7305229 affects the GADA levels in patients with LADA from southeastern Mexico. More studies are needed to determine if this risk genotype exists in other populations with LADA.

A population-based study of familial coaggregation and shared genetic etiology of psychiatric and gastrointestinal disorders

BACKGROUND

It has been proposed that having a psychiatric disorder could increase the risk of developing a gastrointestinal disorder, and vice versa. The role of familial coaggregation and shared genetic loading between psychiatric and gastrointestinal disorders remains unclear.

METHODS

This study used the Taiwan National Health Insurance Research Database; 4,504,612 individuals born 1970-1999 with parental information, 51,664 same-sex twins, and 3,322,959 persons with full-sibling(s) were enrolled. Genotyping was available for 106,796 unrelated participants from the Taiwan Biobank. A logistic regression model was used to examine the associations of individual history, affected relatives, and polygenic risk scores (PRS) for schizophrenia (SCZ), bipolar disorder (BPD), major depressive disorder (MDD), and obsessive-compulsive disorder (OCD), with the risk of peptic ulcer disease (PUD), gastroesophageal reflux disease (GERD), irritable bowel syndrome (IBS), and inflammatory bowel disease (IBD), and vice versa.

RESULTS

Here we show that parental psychiatric disorders are associated with gastrointestinal disorders. Full-siblings of psychiatric cases have an increased risk of gastrointestinal disorders except for SCZ/BPD and IBD; the magnitude of coaggregation is higher in same-sex twins than in full-siblings. The results of bidirectional analyses mostly remain unchanged. PRS for SCZ, MDD, and OCD are associated with IBS, PUD/GERD/IBS/IBD, and PUD/GERD/IBS, respectively. PRS for PUD, GERD, IBS, and IBD are associated with MDD, BPD/MDD, SCZ/BPD/MDD, and BPD, respectively.

CONCLUSIONS

There is familial coaggregation and shared genetic etiology between psychiatric and gastrointestinal comorbidity. Individuals with psychiatric disorder-affected relatives or with higher genetic risk for psychiatric disorders should be monitored for gastrointestinal disorders, and vice versa.

Blood metabolites, neurocognition and psychiatric disorders: a Mendelian randomization analysis to investigate causal pathways

BACKGROUND

Neurocognitive dysfunction is observationally associated with the risk of psychiatric disorders. Blood metabolites, which are readily accessible, may become highly promising biomarkers for brain disorders. However, the causal role of blood metabolites in neurocognitive function, and the biological pathways underlying their association with psychiatric disorders remain unclear.

METHODS

To explore their putative causalities, we conducted bidirectional two-sample Mendelian randomization (MR) using genetic variants associated with 317 human blood metabolites (nmax = 215,551), g-Factor (an integrated index of multiple neurocognitive tests with nmax = 332,050), and 10 different psychiatric disorders (n = 9,725 to 807,553) from the large-scale genome-wide association studies of European ancestry. Mediation analysis was used to assess the potential causal pathway among the candidate metabolite, neurocognitive trait and corresponding psychiatric disorder.

RESULTS

MR evidence indicated that genetically predicted acetylornithine was positively associated with g-Factor (0.035 standard deviation units increase in g-Factor per one standard deviation increase in acetylornithine level; 95% confidence interval, 0.021 to 0.049; P = 1.15 × 10-6). Genetically predicted butyrylcarnitine was negatively associated with g-Factor (0.028 standard deviation units decrease in g-Factor per one standard deviation increase in genetically proxied butyrylcarnitine; 95% confidence interval, -0.041 to -0.015; P = 1.31 × 10-5). There was no evidence of associations between genetically proxied g-Factor and metabolites. Furthermore, the mediation analysis via two-step MR revealed that the causal pathway from acetylornithine to bipolar disorder was partly mediated by g-Factor, with a mediated proportion of 37.1%. Besides, g-Factor mediated the causal pathway from butyrylcarnitine to schizophrenia, with a mediated proportion of 37.5%. Other neurocognitive traits from different sources provided consistent findings.

CONCLUSION

Our results provide genetic evidence that acetylornithine protects against bipolar disorder through neurocognitive abilities, while butyrylcarnitine has an adverse effect on schizophrenia through neurocognition. These findings may provide insight into interventions at the metabolic level for risk of neurocognitive and related disorders.

Inhibitory neuron links the causal relationship from air pollution to psychiatric disorders: a large multi-omics analysis

Psychiatric disorders are severe health challenges that exert a heavy public burden. Air pollution has been widely reported as related to psychiatric disorder risk, but their casual association and pathological mechanism remained unclear. Herein, we systematically investigated the large genome-wide association studies (6 cohorts with 1,357,645 samples), single-cell RNA (26 samples with 157,488 cells), and bulk-RNAseq (1595 samples) datasets to reveal the genetic causality and biological link between four air pollutants and nine psychiatric disorders. As a result, we identified ten positive genetic correlations between air pollution and psychiatric disorders. Besides, PM2.5 and NO2 presented significant causal effects on schizophrenia risk which was robust with adjustment of potential confounders. Besides, transcriptome-wide association studies identified the shared genes between PM2.5/NO2 and schizophrenia. We then discovered a schizophrenia-derived inhibitory neuron subtype with highly expressed shared genes and abnormal synaptic and metabolic pathways by scRNA analyses and confirmed their abnormal level and correlations with the shared genes in schizophrenia patients in a large RNA-seq cohort. Comprehensively, we discovered robust genetic causality between PM2.5, NO2, and schizophrenia and identified an abnormal inhibitory neuron subtype that links schizophrenia pathology and PM2.5/NO2 exposure. These discoveries highlight the schizophrenia risk under air pollutants exposure and provide novel mechanical insights into schizophrenia pathology, contributing to pollutant-related schizophrenia risk control and therapeutic strategies development.

Graphical Abstract

Multitrait Analysis to Decipher the Intertwined Genetic Architecture of Neuroanatomical Phenotypes and Psychiatric Disorders

BACKGROUND

There is increasing evidence of shared genetic factors between psychiatric disorders and brain magnetic resonance imaging (MRI) phenotypes. However, deciphering the joint genetic architecture of these outcomes has proven to be challenging, and new approaches are needed to infer the genetic structures that may underlie those phenotypes. Multivariate analyses are a meaningful approach to reveal links between MRI phenotypes and psychiatric disorders missed by univariate approaches.

METHODS

First, we conducted univariate and multivariate genome-wide association studies for 9 MRI-derived brain volume phenotypes in 20,000 UK Biobank participants. Next, we performed various complementary enrichment analyses to assess whether and how univariate and multitrait approaches could distinguish disorder-associated and non-disorder-associated variants from 6 psychiatric disorders: bipolar disorder, attention-deficit/hyperactivity disorder, autism, schizophrenia, obsessive-compulsive disorder, and major depressive disorder. Finally, we conducted a clustering analysis of top associated variants based on their MRI multitrait association using an optimized k-medoids approach.

RESULTS

A univariate MRI genome-wide association study revealed only negligible genetic correlations with psychiatric disorders, while a multitrait genome-wide association study identified multiple new associations and showed significant enrichment for variants related to both attention-deficit/hyperactivity disorder and schizophrenia. Clustering analyses also detected 2 clusters that showed not only enrichment for association with attention-deficit/hyperactivity disorder and schizophrenia but also a consistent direction of effects. Functional annotation analyses of those clusters pointed to multiple potential mechanisms, suggesting in particular a role of neurotrophin pathways in both MRI phenotypes and schizophrenia.

CONCLUSIONS

Our results show that multitrait association signature can be used to infer genetically driven latent MRI variables associated with psychiatric disorders, thereby opening paths for future biomarker development.

Cognitive processing speed and accuracy are intrinsically different in genetic architecture and brain phenotypes

Since the birth of cognitive science, researchers have used reaction time and accuracy to measure cognitive ability. Although recognition of these two measures is often based on empirical observations, the underlying consensus is that most cognitive behaviors may be along two fundamental dimensions: cognitive processing speed (CPS) and cognitive processing accuracy (CPA). In this study, we used genomic-wide association studies (GWAS) data from 14 cognitive traits to show the presence of those two factors and revealed the specific neurobiological basis underlying them. We identified that CPS and CPA had distinct brain phenotypes (e.g. white matter microstructure), neurobiological bases (e.g. postsynaptic membrane), and developmental periods (i.e. late infancy). Moreover, those two factors showed differential associations with other health-related traits such as screen exposure and sleep status, and a significant causal relationship with psychiatric disorders such as major depressive disorder and schizophrenia. Utilizing an independent cohort from the Adolescent Brain Cognitive Development (ABCD) study, we also uncovered the distinct contributions of those two factors on the cognitive development of young adolescents. These findings reveal two fundamental factors underlying various cognitive abilities, elucidate the distinct brain structural fingerprint and genetic architecture of CPS and CPA, and hint at the complex interrelationship between cognitive ability, lifestyle, and mental health.

Distinct cognitive and functional connectivity features from healthy cohorts can identify clinical obsessive-compulsive disorder

Improving diagnostic accuracy of obsessive-compulsive disorder (OCD) using models of brain imaging data is a key goal of the field, but this objective is challenging due to the limited size and phenotypic depth of clinical datasets. Leveraging the phenotypic diversity in large non-clinical datasets such as the UK Biobank (UKBB), offers a potential solution to this problem. Nevertheless, it remains unclear whether classification models trained on non-clinical populations will generalise to individuals with clinical OCD. This question is also relevant for the conceptualisation of OCD; specifically, whether the symptomology of OCD exists on a continuum from normal to pathological. Here, we examined a recently published "meta-matching" model trained on functional connectivity data from five large normative datasets (N=45,507) to predict cognitive, health and demographic variables. Specifically, we tested whether this model could classify OCD status in three independent clinical datasets (N=345). We found that the model could identify out-of-sample OCD individuals. Notably, the most predictive functional connectivity features mapped onto known cortico-striatal abnormalities in OCD and correlated with genetic brain expression maps previously implicated in the disorder. Further, the meta-matching model relied upon estimates of cognitive functions, such as cognitive flexibility and inhibition, to successfully predict OCD. These findings suggest that variability in non-clinical brain and behavioural features can discriminate clinical OCD status. These results support a dimensional and transdiagnostic conceptualisation of the brain and behavioural basis of OCD, with implications for research approaches and treatment targets.

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

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

Executive Function and Impulsivity Predict Distinct Genetic Variance in Internalizing Problems, Externalizing Problems, Thought Disorders, and Compulsive Disorders: A Genomic Structural Equation Modeling Study

Individual differences in self-control predict many health and life outcomes. Building on twin literature, we used genomic structural equation modeling to test the hypothesis that genetic influences on executive function and impulsivity predict independent variance in mental health and other outcomes. The impulsivity factor (comprising urgency, lack of premeditation, and other facets) was only modestly genetically correlated with low executive function (rg =.13). Controlling for impulsivity, low executive function was genetically associated with increased internalizing (βg =.15), externalizing (βg =.13), thought disorders (βg =.38), compulsive disorders (βg =.22), and chronotype (βg =.11). Controlling for executive function, impulsivity was positively genetically associated with internalizing (βg =.36), externalizing (βg =.55), body mass index (βg =.26), and insomnia (βg =.35), and negatively genetically associated with compulsive disorders (βg = -.17). Executive function and impulsivity were both genetically correlated with general cognitive ability and educational attainment. This work suggests that executive function and impulsivity are genetically separable and show independent associations with mental health.

Investigating the impact of poverty on mental illness in the UK Biobank using Mendelian randomization

It is unclear whether poverty and mental illness are causally related. Using UK Biobank and Psychiatric Genomic Consortium data, we examined evidence of causal links between poverty and nine mental illnesses (attention deficit and hyperactivity disorder (ADHD), anorexia nervosa, anxiety disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, obsessive-compulsive disorder, post-traumatic stress disorder and schizophrenia). We applied genomic structural equation modelling to derive a poverty common factor from household income, occupational income and social deprivation. Then, using Mendelian randomization, we found evidence that schizophrenia and ADHD causally contribute to poverty, while poverty contributes to major depressive disorder and schizophrenia but decreases the risk of anorexia nervosa. Poverty may also contribute to ADHD, albeit with uncertainty due to unbalanced pleiotropy. The effects of poverty were reduced by approximately 30% when we adjusted for cognitive ability. Further investigations of the bidirectional relationships between poverty and mental illness are warranted, as they may inform efforts to improve mental health for all.

Genome-Wide Association Study of Obsessive-Compulsive Symptoms including 33,943 individuals from the general population

While 1-2% of individuals meet the criteria for a clinical diagnosis of obsessive-compulsive disorder (OCD), many more (~13-38%) experience subclinical obsessive-compulsive symptoms (OCS) during their life. To characterize the genetic underpinnings of OCS and its genetic relationship to OCD, we conducted the largest genome-wide association study (GWAS) meta-analysis of parent- or self-reported OCS to date (N = 33,943 with complete phenotypic and genome-wide data), combining the results from seven large-scale population-based cohorts from Sweden, the Netherlands, England, and Canada (including six twin cohorts and one cohort of unrelated individuals). We found no genome-wide significant associations at the single-nucleotide polymorphism (SNP) or gene-level, but a polygenic risk score (PRS) based on the OCD GWAS previously published by the Psychiatric Genetics Consortium (PGC-OCD) was significantly associated with OCS (Pfixed = 3.06 × 10-5). Also, one curated gene set (Mootha Gluconeogenesis) reached Bonferroni-corrected significance (Ngenes = 28, Beta = 0.79, SE = 0.16, Pbon = 0.008). Expression of genes in this set is high at sites of insulin mediated glucose disposal. Dysregulated insulin signaling in the etiology of OCS has been suggested by a previous study describing a genetic overlap of OCS with insulin signaling-related traits in children and adolescents. We report a SNP heritability of 4.1% (P = 0.0044) in the meta-analyzed GWAS, and heritability estimates based on the twin cohorts of 33-43%. Genetic correlation analysis showed that OCS were most strongly associated with OCD (rG = 0.72, p = 0.0007) among all tested psychiatric disorders (N = 11). Of all 97 tested phenotypes, 24 showed a significant genetic correlation with OCS, and 66 traits showed concordant directions of effect with OCS and OCD. OCS have a significant polygenic contribution and share genetic risk with diagnosed OCD, supporting the hypothesis that OCD represents the extreme end of widely distributed OCS in the population.

Shared Genetic Architecture Between Schizophrenia and Anorexia Nervosa: A Cross-trait Genome-Wide Analysis

BACKGROUND AND HYPOTHESIS

Schizophrenia (SCZ) and anorexia nervosa (AN) are 2 severe and highly heterogeneous disorders showing substantial familial co-aggregation. Genetic factors play a significant role in both disorders, but the shared genetic etiology between them is yet to be investigated.

STUDY DESIGN

Using summary statistics from recent large genome-wide association studies on SCZ (Ncases = 53 386) and AN (Ncases = 16 992), a 2-sample Mendelian randomization analysis was conducted to explore the causal relationship between SCZ and AN. MiXeR was employed to quantify their polygenic overlap. A conditional/conjunctional false discovery rate (condFDR/conjFDR) framework was adopted to identify loci jointly associated with both disorders. Functional annotation and enrichment analyses were performed on the shared loci.

STUDY RESULTS

We observed a cross-trait genetic enrichment, a suggestive bidirectional causal relationship, and a considerable polygenic overlap (Dice coefficient = 62.2%) between SCZ and AN. The proportion of variants with concordant effect directions among all shared variants was 69.9%. Leveraging overlapping genetic associations, we identified 6 novel loci for AN and 33 novel loci for SCZ at condFDR <0.01. At conjFDR <0.05, we identified 10 loci jointly associated with both disorders, implicating multiple genes highly expressed in the cerebellum and pituitary and involved in synapse organization. Particularly, high expression of the shared genes was observed in the hippocampus in adolescence and orbitofrontal cortex during infancy.

CONCLUSIONS

This study provides novel insights into the relationship between SCZ and AN by revealing a shared genetic component and offers a window into their complex etiology.

Dynamic convergence of autism disorder risk genes across neurodevelopment

Over a hundred risk genes underlie risk for autism spectrum disorder (ASD) but the extent to which they converge on shared downstream targets to increase ASD risk is unknown. To test the hypothesis that cellular context impacts the nature of convergence, here we apply a pooled CRISPR approach to target 29 ASD loss-of-function genes in human induced pluripotent stem cell (hiPSC)-derived neural progenitor cells, glutamatergic neurons, and GABAergic neurons. Two distinct approaches (gene-level and network-level analyses) demonstrate that convergence is greatest in mature glutamatergic neurons. Convergent effects are dynamic, varying in strength, composition, and biological role between cell types, increasing with functional similarity of the ASD genes examined, and driven by cell-type-specific gene co-expression patterns. Stratification of ASD genes yield targeted drug predictions capable of reversing gene-specific convergent signatures in human cells and ASD-related behaviors in zebrafish. Altogether, convergent networks downstream of ASD risk genes represent novel points of individualized therapeutic intervention.

Exploring the genetic and socioeconomic interplay between ADHD and anxiety disorders using Mendelian randomization

Background

ADHD and anxiety disorders often co-occur, sharing symptoms and dysfunctions, yet the underlying mechanisms remain elusive.

Methods

To explore the shared and distinct genetic variations between ADHD and anxiety disorders, we applied Mendelian randomization (MR) analysis to ADHD, anxiety disorders, and three socioeconomic factors: income, educational attainment (EA), and intelligence. MR analysis utilized genome-wide association study summary datasets (anxiety disorder: 7,016 cases and 14,745 controls; ADHD: 38,691 cases and 275,986 controls; EA: 766,345 participants; intelligence: 146,808 participants; household income: 392,422 participants), with inverse-variance weighting as the primary method.

Results

Our MR analysis revealed no discernible genetic-level causal effect between ADHD and anxiety disorders (p > 0.77). Additionally, the independent variables for ADHD (25 SNPs) and anxiety disorders (18 SNPs) did not overlap, highlighting the genetic distinction between the two conditions. Higher income (p < 0.002) and EA (p < 0.005) were found to serve as protective factors for both ADHD and anxiety disorders. Genetic predisposition to higher income (86 SNPs) and EA (457 SNPs) were identified as a potential common protective factors for both conditions. Lastly, genetic predisposition to higher intelligence was found to potentially guard against ADHD (p < 0.001) but not against anxiety disorders (p > 0.55).

Conclusion

Our findings indicate that the shared symptoms observed between ADHD and anxiety disorders are more likely influenced by genetic predispositions related to socioeconomic factors rather than by the genetic predispositions specific to the disorders themselves.

The genetics of trichotillomania and excoriation disorder: A systematic review

BACKGROUND

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

AIM

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

Gene × environment effects and mediation involving adverse childhood events, mood and anxiety disorders, and substance dependence

Adverse childhood events (ACEs) contribute to the development of mood and anxiety disorders and substance dependence. However, the extent to which these effects are direct or indirect and whether genetic risk moderates them is unclear. We examined associations among ACEs, mood/anxiety disorders and substance dependence in 12,668 individuals (44.9% female, 42.5% African American/Black, 42.1% European American/white). Using latent variables for each phenotype, we modelled direct and indirect associations of ACEs with substance dependence, mediated by mood/anxiety disorders (the forward or 'self-medication' model) and of ACEs with mood/anxiety disorders, mediated by substance dependence (the reverse or 'substance-induced' model). In a subsample, we tested polygenic scores for the substance dependence and mood/anxiety disorder factors as moderators in the mediation models. Although there were significant indirect paths in both directions, mediation by mood/anxiety disorders (the forward model) was greater than that by substance dependence (the reverse model). Greater genetic risk for substance use disorders was associated with a weaker direct association between ACEs and substance dependence in both ancestry groups (reflecting gene × environment interactions) and a weaker indirect association in European-ancestry individuals (reflecting moderated mediation). We found greater evidence that substance dependence reflects self-medication of mood/anxiety disorders than that mood/anxiety disorders are substance induced. Among individuals at higher genetic risk for substance dependence, ACEs were less associated with that outcome. Following exposure to ACEs, multiple pathways appear to underlie the associations between mood/anxiety disorders and substance dependence. Specification of these pathways could inform individually targeted prevention and treatment approaches.

Seven psychiatric traits and the risk of increased carotid intima-media thickness: a Mendelian randomization study

Background

Numerous observational studies have suggested an association between psychiatric traits and carotid intima-media thickness (cIMT). However, whether these associations have a causal relationship remains unknown, largely due to issues of reverse causality and potential confounders. This study aims to elucidate the potential causal role of psychiatric traits in the risk of arterial injury as measured by cIMT.

Methods

We utilized instrumental variables for attention deficit/hyperactivity disorder (ADHD, n = 226,534), bipolar disorder (n = 353,899), major depressive disorder (n = 142,646), post-traumatic stress disorder (n = 174,494), obsessive-compulsive disorder (n = 9,725), autism spectrum disorder (n = 173,773), and anxiety disease (n = 17,310), derived from the largest corresponding genome-wide association studies (GWAS). Summary statistics for cIMT associations were obtained from a meta-analysis combining GWAS data from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortia (n = 71,128) and the UK Biobank study (n = 45,185). The inverse-variance weighted method served as the primary analytical tool, supplemented by additional statistical methods in the secondary analyses to corroborate the findings. Adjustments were made according to the Bonferroni correction threshold.

Results

The Mendelian randomization analyses indicated a suggestive causal link between genetically predicted ADHD and cIMT (beta = 0.05; 95% confidence interval, 0.01-0.09; p = 0.018). Sensitivity analyses largely concurred with this finding. However, no significant associations were found between other psychiatric traits and cIMT.

Conclusions

This study provides insights into the risk effect of ADHD on cIMT, suggesting that arteriopathy and potential associated complications should be considered during the treatment and monitoring of patients with ADHD.

Examining the Genetic Links between Clusters of Immune-mediated Diseases and Psychiatric Disorders

Importance

Autoimmune and autoinflammatory diseases have been linked to psychiatric disorders in the phenotypic and genetic literature. However, a comprehensive model that investigates the association between a broad range of psychiatric disorders and immune-mediated disease in a multivariate framework is lacking.

Objective

This study aims to establish a factor structure based on the genetic correlations of immune-mediated diseases and investigate their genetic relationships with clusters of psychiatric disorders.

Design Setting and Participants

We utilized Genomic Structural Equation Modeling (Genomic SEM) to establish a factor structure of 11 immune-mediated diseases. Genetic correlations between these immune factors were examined with five established factors across 13 psychiatric disorders representing compulsive, schizophrenia/bipolar, neurodevelopmental, internalizing, and substance use disorders. We included GWAS summary statistics of individuals of European ancestry with sample sizes from 1,223 cases for Addison's disease to 170,756 cases for major depressive disorder.

Main Outcomes and Measures

Genetic correlations between psychiatric and immune-mediated disease factors and traits to determine genetic overlap. We develop and validate a new heterogeneity metric, Q Factor , that quantifies the degree to which factor correlations are driven by more specific pairwise associations. We also estimate residual genetic correlations between pairs of psychiatric disorders and immune-mediated diseases.

Results

A four-factor model of immune-mediated diseases fit the data well and described a continuum from autoimmune to autoinflammatory diseases. The four factors reflected autoimmune, celiac, mixed pattern, and autoinflammatory diseases. Analyses revealed seven significant factor correlations between the immune and psychiatric factors, including autoimmune and mixed pattern diseases with the internalizing and substance use factors, and autoinflammatory diseases with the compulsive, schizophrenia/bipolar, and internalizing factors. Additionally, we find evidence of divergence in associations within factors as indicated by Q Factor . This is further supported by 14 significant residual genetic correlations between individual psychiatric disorders and immune-mediated diseases.

Conclusion and Relevance

Our results revealed genetic links between clusters of immune-mediated diseases and psychiatric disorders. Current analyses indicate that previously described relationships between specific psychiatric disorders and immune-mediated diseases often capture broader pathways of risk sharing indexed by our genomic factors, yet are more specific than a general association across all psychiatric disorders and immune-mediated diseases.

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.