A major role for common genetic variation in anxiety disorders

Association of Genetically Predicted Anxiety and Depression With Functional Outcome After Ischemic Stroke: A Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

Anxiety and depression have implications for ischemic stroke recovery. This study explored the association of genetically predicted anxiety and depression with functional outcome after ischemic stroke using Mendelian randomization (MR) approach.

METHODS

Independent genetic variants associated with anxiety and depression at genome-wide significance level (p < 5 × 10-8) were obtained from large-scale genome-wide association studies (Nmax = 1,306,354). Genetic results of poststroke outcome were obtained from Genetics of Ischemic Stroke Functional Outcome meta-analysis (N = 6,021). Three months after ischemic stroke event, the functional outcome was appraised with the modified Rankin Scale (mRS) score, and a mRS >2 was defined as worse functional outcome. Odds ratios (ORs) and 95% CIs are reported for the association of genetically predicted anxiety and depression with functional outcome after ischemic stroke. The inverse-variance weighted method was adopted to pool estimates. Alternative MR methods such as the weighted median and MR using the Robust Adjusted Profile Score were used as sensitivity analyses. The intercept of MR-Egger regression was also adopted to assess pleiotropy. The heterogeneity among variants was assessed by I2 and Q statistics.

RESULTS

Genetic liability to depression was associated with worse functional outcome after stroke (mRS 3-6, OR 2.30; 95% CI 1.18-4.49, p = 0.015). Sensitivity analyses produced consistent results. The bidirectional MR analysis indicates that poststroke outcome did not influence liability to depression (OR 1.01, 95% CI 0.99-1.03; p = 0.436). By comparison, genetic liability to anxiety was not related with poststroke outcome (OR 1.03; 95% CI 0.71-1.50; p = 0.869). Analyses in models without adjustment for stroke severity also indicated that genetic liability to depression was related with poor functional outcome after ischemic stroke (OR 2.54; 95% CI 1.41-4.58; p = 0.002). No evidence of heterogeneity or directional pleiotropy was observed (p > 0.05).

DISCUSSION

Our MR study provides evidence to support detrimental effects of depression on ischemic stroke functional outcome. Future studies are warranted to explore whether clinical intervention on depression can ameliorate functional outcome after ischemic stroke.

A Potential Role for MAGI-1 in the Bi-Directional Relationship Between Major Depressive Disorder and Cardiovascular Disease

PURPOSE OF REVIEW

Major Depressive Disorder (MDD) is characterized by persistent symptoms such as fatigue, loss of interest in activities, feelings of sadness and worthlessness. MDD often coexist with cardiovascular disease (CVD), yet the precise link between these conditions remains unclear. This review explores factors underlying the development of MDD and CVD, including genetic, epigenetic, platelet activation, inflammation, hypothalamic-pituitary-adrenal (HPA) axis activation, endothelial cell (EC) dysfunction, and blood-brain barrier (BBB) disruption.

RECENT FINDINGS

Single nucleotide polymorphisms (SNPs) in the membrane-associated guanylate kinase WW and PDZ domain-containing protein 1 (MAGI-1) are associated with neuroticism and psychiatric disorders including MDD. SNPs in MAGI-1 are also linked to chronic inflammatory disorders such as spontaneous glomerulosclerosis, celiac disease, ulcerative colitis, and Crohn's disease. Increased MAGI-1 expression has been observed in colonic epithelial samples from Crohn's disease and ulcerative colitis patients. MAGI-1 also plays a role in regulating EC activation and atherogenesis in mice and is essential for Influenza A virus (IAV) infection, endoplasmic reticulum stress-induced EC apoptosis, and thrombin-induced EC permeability. Despite being understudied in human disease; evidence suggests that MAGI-1 may play a role in linking CVD and MDD. Therefore, further investigation of MAG-1 could be warranted to elucidate its potential involvement in these conditions.

Polygenic Scores and Networks of Psychopathology Symptoms

Importance

Studies on polygenic risk for psychiatric traits commonly use a disorder-level approach to phenotyping, implicitly considering disorders as homogeneous constructs; however, symptom heterogeneity is ubiquitous, with many possible combinations of symptoms falling under the same disorder umbrella. Focusing on individual symptoms may shed light on the role of polygenic risk in psychopathology.

Objective

To determine whether polygenic scores are associated with all symptoms of psychiatric disorders or with a subset of indicators and whether polygenic scores are associated with comorbid phenotypes via specific sets of relevant symptoms.

Design, Setting, and Participants

Data from 2 population-based cohort studies were used in this cross-sectional study. Data from children in the Avon Longitudinal Study of Parents and Children (ALSPAC) were included in the primary analysis, and data from children in the Twins Early Development Study (TEDS) were included in confirmatory analyses. Data analysis was conducted from October 2021 to January 2024. Pregnant women based in the Southwest of England due to deliver in 1991 to 1992 were recruited in ALSPAC. Twins born in 1994 to 1996 were recruited in TEDS from population-based records. Participants with available genetic data and whose mothers completed the Short Mood and Feelings Questionnaire and the Strength and Difficulties Questionnaire when children were 11 years of age were included.

Main Outcomes and Measures

Psychopathology relevant symptoms, such as hyperactivity, prosociality, depression, anxiety, and peer and conduct problems at age 11 years. Psychological networks were constructed including individual symptoms and polygenic scores for depression, anxiety, attention-deficit/hyperactivity disorder (ADHD), body mass index (BMI), and educational attainment in ALSPAC. Following a preregistered confirmatory analysis, network models were cross-validated in TEDS.

Results

Included were 5521 participants from ALSPAC (mean [SD] age, 11.8 [0.14] years; 2777 [50.3%] female) and 4625 participants from TEDS (mean [SD] age, 11.27 [0.69] years; 2460 [53.2%] female). Polygenic scores were preferentially associated with restricted subsets of core symptoms and indirectly associated with other, more distal symptoms of psychopathology (network edges ranged between r = -0.074 and r = 0.073). Psychiatric polygenic scores were associated with specific cross-disorder symptoms, and nonpsychiatric polygenic scores were associated with a variety of indicators across disorders, suggesting a potential contribution of nonpsychiatric traits to comorbidity. For example, the polygenic score for ADHD was associated with a core ADHD symptom, being easily distracted (r = 0.07), and the polygenic score for BMI was associated with symptoms across disorders, including being bullied (r = 0.053) and not thinking things out (r = 0.041).

Conclusions and Relevance

Genetic associations observed at the disorder level may hide symptom-level heterogeneity. A symptom-level approach may enable a better understanding of the role of polygenic risk in shaping psychopathology and comorbidity.

Genetic influences on sibling bullying and mental health difficulties

BACKGROUND

Sibling bullying is associated with mental health difficulties; both in the short and long term. It is commonly assumed that sibling bullying leads to mental health difficulties but additional explanations for the relationship between the two are seldom investigated.

METHODS

To address this gap in knowledge, we used a genetically sensitive design with data from the Avon Longitudinal Study of Parents and Children (maximum N = 3,959, 53% female). At ages 11-13 years, individuals self-reported their involvement in sibling bullying, as a victim and perpetrator, and parents reported on their child's mental health difficulties. Polygenic scores, indices of genetic risk for psychiatric disorders (major depressive disorder and attention deficit hyperactivity disorder) were computed using children's genetic data. Regression and structural equation models were fitted to the data.

RESULTS

Sibling bullying, victimisation and perpetration, and polygenic scores both predicted mental health difficulties in an additive manner but there was no interaction between them. Polygenic scores for mental health difficulties were also associated with sibling bullying.

CONCLUSIONS

These findings suggest that sibling bullying, victimisation and perpetration, is associated with mental health difficulties, even after accounting for some genetic effects. Additionally, the relationship between sibling bullying and mental health difficulties may be, at least partly, due to shared genetic aetiology. One possibility is that genetic risk for mental health difficulties influences the onset of mental health difficulties which in turn make children more susceptible to sibling bullying.

Genetic Architectures of Adolescent Depression Trajectories in 2 Longitudinal Population Cohorts

Importance

Adolescent depression is characterized by diverse symptom trajectories over time and has a strong genetic influence. Research has determined genetic overlap between depression and other psychiatric conditions; investigating the shared genetic architecture of heterogeneous depression trajectories is crucial for understanding disease etiology, prediction, and early intervention.

Objective

To investigate univariate and multivariate genetic risk for adolescent depression trajectories and assess generalizability across ancestries.

Design, Setting, and Participants

This cohort study entailed longitudinal growth modeling followed by polygenic risk score (PRS) association testing for individual and multitrait genetic models. Two longitudinal cohorts from the US and UK were used: the Adolescent Brain and Cognitive Development (ABCD; N = 11 876) study and the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 8787) study. Included were adolescents with genetic information and depression measures at up to 8 and 4 occasions, respectively. Study data were analyzed January to July 2023.

Main Outcomes and Measures

Trajectories were derived from growth mixture modeling of longitudinal depression symptoms. PRSs were computed for depression, anxiety, neuroticism, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, and autism in European ancestry. Genomic structural equation modeling was used to build multitrait genetic models of psychopathology followed by multitrait PRS. Depression PRSs were computed in African, East Asian, and Hispanic ancestries in the ABCD cohort only. Association testing was performed between all PRSs and trajectories for both cohorts.

Results

A total sample size of 14 112 adolescents (at baseline: mean [SD] age, 10.5 [0.5] years; 7269 male sex [52%]) from both cohorts were included in this analysis. Distinct depression trajectories (stable low, adolescent persistent, increasing, and decreasing) were replicated in the ALSPAC cohort (6096 participants; 3091 female [51%]) and ABCD cohort (8016 participants; 4274 male [53%]) between ages 10 and 17 years. Most univariate PRSs showed significant uniform associations with persistent trajectories, but fewer were significantly associated with intermediate (increasing and decreasing) trajectories. Multitrait PRSs-derived from a hierarchical factor model-showed the strongest associations for persistent trajectories (ABCD cohort: OR, 1.46; 95% CI, 1.26-1.68; ALSPAC cohort: OR, 1.34; 95% CI, 1.20-1.49), surpassing the effect size of univariate PRS in both cohorts. Multitrait PRSs were associated with intermediate trajectories but to a lesser extent (ABCD cohort: hierarchical increasing, OR, 1.27; 95% CI, 1.13-1.43; decreasing, OR, 1.23; 95% CI, 1.09-1.40; ALSPAC cohort: hierarchical increasing, OR, 1.16; 95% CI, 1.04-1.28; decreasing, OR, 1.32; 95% CI, 1.18-1.47). Transancestral genetic risk for depression showed no evidence for association with trajectories.

Conclusions and Relevance

Results of this cohort study revealed a high multitrait genetic loading of persistent symptom trajectories, consistent across traits and cohorts. Variability in univariate genetic association with intermediate trajectories may stem from environmental factors. Multitrait genetics may strengthen depression prediction models, but more diverse data are needed for generalizability.

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.

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.

Causal relationships between psychological disorders and functional gastrointestinal disorders: a bidirectional two-sample Mendelian randomization study

BACKGROUND AND AIMS

Observational studies have shown bidirectional associations between psychological disorders (e.g. depression and anxiety) and functional gastrointestinal disorders. However, whether the relationships are causal is uncertain. Here, we used a bidirectional two-sample Mendelian randomization method to investigate the association between psychological disorders and functional gastrointestinal disorders (FGIDs).

METHODS

We obtained genome-wide association study summary statistics for two common psychological disorders: depression (170 756 cases) and anxiety (31 977 cases), as well as for three common FGIDs: functional dyspepsia with 6666 cases, constipation with 26 919 cases, and irritable bowel syndrome (IBS) with 7053 cases. These summary statistics were retrieved from several publicly available genome-wide association study databases. The inverse variance weighted method was used as the main Mendelian randomization method.

RESULTS

Inverse variance weighted Mendelian randomization analyses showed statistically significant associations between genetically predicted depression and risk of functional dyspepsia [odds ratio (OR): 1.40, 95% confidence interval (CI): 1.08-1.82], constipation (OR: 1.28, 95% CI: 1.13-1.44), and IBS (OR: 1.51, 95% CI: 1.37-1.67). Genetically predicted anxiety was associated with a higher risk of IBS (OR: 1.13, 95% CI: 1.10-1.17) instead of functional dyspepsia and constipation. In addition, genetically predicted IBS instead of functional dyspepsia and constipation was associated with a higher risk of depression (OR: 1.33, 95% CI: 1.12-1.57) and anxiety (OR: 2.05, 95% CI: 1.05-4.03).

CONCLUSION

Depression is a causal risk factor for three common FGIDs. A bidirectional causal relationship between IBS and anxiety or depression was also identified.

Genome-wide association study of major anxiety disorders in 122,341 European-ancestry cases identifies 58 loci and highlights GABAergic signaling

The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder, and phobias) are highly prevalent, often onset early, persist throughout life, and cause substantial global disability. Although distinct in their clinical presentations, they likely represent differential expressions of a dysregulated threat-response system. Here we present a genome-wide association meta-analysis comprising 122,341 European ancestry ANX cases and 729,881 controls. We identified 58 independent genome-wide significant ANX risk variants and 66 genes with robust biological support. In an independent sample of 1,175,012 self-report ANX cases and 1,956,379 controls, 51 of the 58 associated variants were replicated. As predicted by twin studies, we found substantial genetic correlation between ANX and depression, neuroticism, and other internalizing phenotypes. Follow-up analyses demonstrated enrichment in all major brain regions and highlighted GABAergic signaling as one potential mechanism underlying ANX genetic risk. These results advance our understanding of the genetic architecture of ANX and prioritize genes for functional follow-up studies.

Genetic analyses point to alterations in immune-related pathways underpinning the association between psychiatric disorders and COVID-19

Current literature suggests that people with psychiatric disorders have a higher risk of COVID-19 infection and a worse prognosis of the disease. We aimed to study the genetic contribution to these associations across seven psychiatric disorders as well as a general psychopathology factor (P-factor) and determine whether these are unique or shared across psychiatric disorders using statistical genetic techniques. Using the largest available genome-wide association studies (GWAS), we found a significant genetic overlap between depression, ADHD, PTSD, and the P-factor with both COVID-19 infection and hospitalization, and between anxiety and COVID-19 hospitalization. We used pairwise GWAS to examine this overlap on a fine-grained scale and identified specific regions of the genome shared between several psychiatric disorders, the P-factor, and COVID-19. Gene-based analysis in these genomic regions suggested possible links with immune-related pathways such as thyroid homeostasis, inflammation, and stress response. Finally, we show preliminary evidence for causal associations between depression, ADHD, PTSD, and the P-factor, and higher COVID-19 infection and hospitalization using Mendelian Randomization and Latent Causal Variable methods. Our results support the hypothesis that the relationship between psychiatric disorders and COVID-19 risk is likely due to shared alterations in immune-related pathways and is not a result of environmental factors alone, shedding light on potentially viable therapeutic targets.

Disentangling differing relationships between internalizing disorders and alcohol use

Both internalizing disorders and alcohol use have dramatic, wide-spread implications for global health. Previous work has established common phenotypic comorbidity among these disorders, as well as shared genetic variation underlying them both. We used genomic structural equation modeling to investigate the shared genetics of internalizing, externalizing, and alcohol use traits, as well as to explore whether specific domains of internalizing symptoms mediate the contrasting relationships with problematic alcohol use compared to alcohol consumption. We also examined patterns of genetic correlations between similar traits within additional Finnish and East Asian ancestry groups. When the shared genetic influence of externalizing psychopathology was accounted for, the genetic effect of internalizing traits on alcohol use was reduced, suggesting the important role of common genetic factors underlying multiple psychiatric disorders and their genetic influences on comorbidity of internalizing and alcohol use traits. Individual internalizing domains had contrasting effects on frequency of alcohol consumption, which demonstrate the complex system of pleiotropy that exists, even within similar disorders, and can be missed when evaluating only relationships among formal diagnoses. Future work must consider the broad effects of shared psychopathology along with the fine-scale effects of heterogeneity within disorders to more fully understand the biology underlying complex traits.

Evidence for strong genetic correlations among internalizing psychopathology and related self-reported measures using both genomic and twin/adoptive approaches

The internalizing construct captures shared variance underlying risk for mood and anxiety disorders. Internalizing factors based on diagnoses (or symptoms) of major depressive disorder (MDD) and generalized anxiety disorder (GAD) are well established. Studies have also integrated self-reported measures of associated traits (e.g., questionnaires assessing neuroticism, worry, and rumination) onto these factors, despite having not tested the assumption that these measures truly capture the same sets of risk factors. This study examined the overlap among both sets of measures using converging approaches. First, using genomic structural equation modeling, we constructed internalizing factors based on genome-wide association studies (GWASs) of internalizing diagnoses (e.g., MDD) and traits associated with internalizing (neuroticism, loneliness, and reverse-scored subjective well-being). Results indicated the two factors were highly (rg = .79) but not perfectly genetically correlated (rg < 1.0, p < .001). Second, we constructed similar latent factors in a combined twin/adoption sample of adults from the Colorado Adoption/Twin Study of Lifespan Behavioral Development and Cognitive Aging. Again, both factors demonstrated strong overlap at the level of genetic (rg = .76, 95% confidence interval [CI] [0.40, 0.97]) and nonshared environmental influences (re = .80, 95% CI [0.53, 1.0]). Shared environmental influences were estimated near zero for both factors. Our findings are consistent with current frameworks of psychopathology, though they suggest there are some unique genetic influences captured by internalizing diagnosis compared to trait measures, with potentially more nonadditive genetic influences on trait measures. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Using Alternative Definitions of Controls to Increase Statistical Power in GWAS

Genome-wide association studies (GWAS) are often underpowered due to small effect sizes of common single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the greatest statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.

Epigenetic signatures of social anxiety, panic disorders and stress experiences: Insights from genome-wide DNA methylation risk scores

Social anxiety disorder (SAD) and panic disorder (PD) are prevalent anxiety disorders characterized by a complex interplay of genetic and environmental factors. Both disorders share overlapping features and often coexist, despite displaying distinct characteristics. Childhood life adversity, overall stressful life events, and genetic factors contribute to the development of these disorders. DNA methylation, an epigenetic modification, has been implicated in the pathogenesis of these diseases. In this study, we investigated whether whole-genome DNA methylation risk scores (MRSs) for SAD risk, severity of social anxiety, childhood life adversity, PD risk, and overall stressful life events were associated with SAD or PD case‒control status. Preliminary epigenome-wide association studies (EWASs) for SAD risk, severity of social anxiety, and childhood life adversity were conducted in 66 SAD individuals and 77 healthy controls (HCs). Similarly, EWASs for PD risk and overall stressful life events were performed in 182 PD individuals and 81 HCs. MRSs were calculated from these EWASs. MRSs derived from the EWASs of SAD risk and severity of social anxiety were greater in PD patients than in HCs. Additionally, MRSs derived from the EWASs of overall stressful life events, particularly in PD individuals, were lower in SAD individuals than in HCs. In contrast, MRSs for childhood life adversity or PD risk were not significantly associated with PD or SAD case‒control status. These findings highlight the epigenetic features shared in both disorders and the distinctive epigenetic features related to social avoidance in SAD patients, helping to elucidate the epigenetic basis of these disorders.

Cross-continental environmental and genome-wide association study on children and adolescent anxiety and depression

Anxiety and depression in children and adolescents warrant special attention as a public health concern given their devastating and long-term effects on development and mental health. Multiple factors, ranging from genetic vulnerabilities to environmental stressors, influence the risk for the disorders. This study aimed to understand how environmental factors and genomics affect children and adolescents anxiety and depression across three cohorts: Adolescent Brain and Cognitive Development Study (US, age of 9-10; N=11,875), Consortium on Vulnerability to Externalizing Disorders and Addictions (INDIA, age of 6-17; N=4,326) and IMAGEN (EUROPE, age of 14; N=1888). We performed data harmonization and identified the environmental impact on anxiety/depression using a linear mixed-effect model, recursive feature elimination regression, and the LASSO regression model. Subsequently, genome-wide association analyses with consideration of significant environmental factors were performed for all three cohorts by mega-analysis and meta-analysis, followed by functional annotations. The results showed that multiple environmental factors contributed to the risk of anxiety and depression during development, where early life stress and school support index had the most significant and consistent impact across all three cohorts. In both meta, and mega-analysis, SNP rs79878474 in chr11p15 emerged as a particularly promising candidate associated with anxiety and depression, despite not reaching genomic significance. Gene set analysis on the common genes mapped from top promising SNPs of both meta and mega analyses found significant enrichment in regions of chr11p15 and chr3q26, in the function of potassium channels and insulin secretion, in particular Kv3, Kir-6.2, SUR potassium channels encoded by the KCNC1, KCNJ11, and ABCCC8 genes respectively, in chr11p15. Tissue enrichment analysis showed significant enrichment in the small intestine, and a trend of enrichment in the cerebellum. Our findings provide evidences of consistent environmental impact from early life stress and school support index on anxiety and depression during development and also highlight the genetic association between mutations in potassium channels, which support the stress-depression connection via hypothalamic-pituitary-adrenal axis, along with the potential modulating role of potassium channels.

Combining Transdiagnostic and Disorder-Level GWAS Enhances Precision of Psychiatric Genetic Risk Profiles in a Multi-Ancestry Sample

The etiology of substance use disorders (SUDs) and psychiatric disorders reflects a combination of both transdiagnostic (i.e., common) and disorder-level (i.e., independent) genetic risk factors. We applied genomic structural equation modeling to examine these genetic factors across SUDs, psychotic, mood, and anxiety disorders using genome-wide association studies (GWAS) of European- (EUR) and African-ancestry (AFR) individuals. In EUR individuals, transdiagnostic genetic factors represented SUDs (143 lead single nucleotide polymorphisms [SNPs]), psychotic (162 lead SNPs), and mood/anxiety disorders (112 lead SNPs). We identified two novel SNPs for mood/anxiety disorders that have probable regulatory roles on FOXP1, NECTIN3, and BTLA genes. In AFR individuals, genetic factors represented SUDs (1 lead SNP) and psychiatric disorders (no significant SNPs). The SUD factor lead SNP, although previously significant in EUR- and cross-ancestry GWAS, is a novel finding in AFR individuals. Shared genetic variance accounted for overlap between SUDs and their psychiatric comorbidities, with second-order GWAS identifying up to 12 SNPs not significantly associated with either first-order factor in EUR individuals. Finally, common and independent genetic effects showed different associations with psychiatric, sociodemographic, and medical phenotypes. For example, the independent components of schizophrenia and bipolar disorder had distinct associations with affective and risk-taking behaviors, and phenome-wide association studies identified medical conditions associated with tobacco use disorder independent of the broader SUDs factor. Thus, combining transdiagnostic and disorder-level genetic approaches can improve our understanding of co-occurring conditions and increase the specificity of genetic discovery, which is critical for psychiatric disorders that demonstrate considerable symptom and etiological overlap.

Phenotypic and Genetic Associations Between Preschool Fine Motor Skills and Later Neurodevelopment, Psychopathology, and Educational Achievement

BACKGROUND

Fine motor skills are heritable and comprise important milestones in development, and some evidence suggests that impairments in fine motor skills are associated with neurodevelopmental conditions, psychiatric disorders, and poor educational outcomes.

METHODS

In a preregistered study of 9625 preschool children from TEDS (Twins Early Development Study), fine motor assessments (drawing, block building, folding, and questionnaires) were conducted at 2, 3, and 4 years of age. A cross-age fine motor score was derived using principal component analysis. Multivariate regression analysis was used to examine the relationships between the fine motor score and neurodevelopmental traits, psychopathology, and educational outcomes at 3 later ages (7-8, 12, and 16 years) and cross-age psychopathology composite scores. Polygenic scores (PGSs) were created for attention-deficit/hyperactivity disorder (ADHD), autism, schizophrenia, anxiety, major depressive disorder, obsessive-compulsive disorder, and years of education. We ran single-PGS models and a multi-PGS model.

RESULTS

Fine motor skills were negatively associated with neurodevelopmental traits and psychopathology across childhood and adolescence and positively associated with educational achievement in adolescence (β = 0.25, p < .001). Superior fine motor skills were associated with a higher years-of-education PGS (β = 0.07, p < .001), a lower ADHD PGS (β = -0.04, p = .011), and a higher anxiety PGS (β = 0.03, p = .040). Similarly, the multi-PGS model retained the PGSs for years of education (β = 0.07), ADHD (β = -0.03), and anxiety (β = 0.01). A non-preregistered analysis in an independent preschool sample replicated the ADHD PGS association, but not the years of education or anxiety PGS associations.

CONCLUSIONS

Fine motor skills are linked genetically and phenotypically to later neurodevelopment, psychopathology, and educational outcomes. Future work should investigate the mechanisms that underlie the role of fine motor development in later outcomes.

Examining Differences in the Genetic and Functional Architecture of Attention-Deficit/Hyperactivity Disorder Diagnosed in Childhood and Adulthood

Background

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder with diagnostic criteria requiring symptoms to begin in childhood. We investigated whether individuals diagnosed as children differ from those diagnosed in adulthood with respect to shared and unique architecture at the genome-wide and gene expression level of analysis.

Methods

We used genomic structural equation modeling (SEM) to investigate differences in genetic correlations (rg) of childhood-diagnosed (ncases = 14,878) and adulthood-diagnosed (ncases = 6961) ADHD with 98 behavioral, psychiatric, cognitive, and health outcomes. We went on to apply transcriptome-wide SEM to identify functional annotations and patterns of gene expression associated with genetic risk sharing or divergence across the ADHD subgroups.

Results

Compared with the childhood subgroup, adulthood-diagnosed ADHD exhibited a significantly larger negative rg with educational attainment, the noncognitive skills of educational attainment, and age at first sexual intercourse. We observed a larger positive rg for adulthood-diagnosed ADHD with major depression, suicidal ideation, and a latent internalizing factor. At the gene expression level, transcriptome-wide SEM analyses revealed 22 genes that were significantly associated with shared genetic risk across the subtypes that reflected a mixture of coding and noncoding genes and included 15 novel genes relative to the ADHD subgroups.

Conclusions

This study demonstrated that ADHD diagnosed later in life shows much stronger genetic overlap with internalizing disorders and related traits. This may indicate the potential clinical relevance of distinguishing these subgroups or increased misdiagnosis for those diagnosed later in life. Top transcriptome-wide SEM results implicated genes related to neuronal function and clinical characteristics (e.g., sleep).

Assessing the Role of Cortisol in Anxiety, Major Depression, and Neuroticism: A Mendelian Randomization Study Using SERPINA6/SERPINA1 Variants

Background

Previous evidence informed by the toxic stress model suggests that higher cortisol causes anxiety and major depression, but clinical success is lacking. To clarify the role of cortisol, we used Mendelian randomization to estimate its associations with anxiety, major depression, and neuroticism, leveraging the largest available genome-wide association studies including from the Psychiatric Genomics Consortium, the UK Biobank, and FinnGen.

Methods

After meta-analyzing 2 genome-wide association studies on morning plasma cortisol (n = 32,981), we selected single nucleotide polymorphisms (SNPs) at p < 5 × 10-8 and r2 < 0.3 in the SERPINA6/SERPINA1 gene region encoding proteins that influence cortisol bioavailability. We applied these SNPs to summary genetic associations with the outcomes considered (n = 17,310-449,484), and systolic blood pressure as a positive outcome, using inverse-variance weighted meta-analysis accounting for correlation. Sensitivity analyses addressing SNP correlation and confounding by childhood maltreatment and follow-up analyses using only SNPs that colocalized with SERPINA6 expression were conducted.

Results

Cortisol was associated with anxiety (pooled odds ratio [OR] 1.16 per cortisol z score; 95% CI, 1.04 to 1.31), but not major depression (pooled OR 1.02, 95% CI, 0.95 to 1.10) or neuroticism (β -0.025; 95% CI, -0.071 to 0.022). Sensitivity analyses yielded similar estimates. Cortisol was positively associated with systolic blood pressure, as expected. Using rs9989237 and rs2736898, selected using colocalization, cortisol was associated with anxiety in the UK Biobank (OR 1.32; 95% CI, 1.01 to 1.74) but not with major depression in FinnGen (OR 1.14; 95% CI, 0.95 to 1.37).

Conclusions

Cortisol was associated with anxiety and may be a potential target for prevention. Other targets may be more relevant to major depression and neuroticism.

Heterogeneity analysis provides evidence for a genetically homogeneous subtype of bipolar-disorder

Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. One way to assess this heterogeneity is to look for patterns in the subphenotype data, identify a more phenotypically homogeneous set of subjects, and perform a genome-wide association-study (GWAS) and subsequent secondary analyses restricted to this homogeneous subset. Because of the variability in how phenotypic data was collected by the various BD studies over the years, homogenizing the phenotypic data is a challenging task, and so is replication. As members of the Psychiatric Genomics Consortium (PGC), we have access to the raw genotypes of 18,711 BD cases and 29,738 controls. This amount of data makes it possible for us to set aside the intricacies of phenotype and allow the genetic data itself to determine which subjects define a homogeneous genetic subgroup. In this paper, we leverage recent advances in heterogeneity analysis to look for distinct homogeneous genetic BD subgroups (or biclusters) that manifest the broad phenotype we think of as Bipolar Disorder. As our data was generated by 27 studies and genotyped on a variety of platforms (OMEX, Affymetrix, Illumina), we use a biclustering algorithm capable of covariate-correction. Covariate-correction is critical if we wish to distinguish disease-related signals from those which are a byproduct of ancestry, study or genotyping platform. We rely on the raw genotyped data and do not include any data generated through imputation. We first apply this covariate-corrected biclustering algorithm to a cohort of 2524 BD cases and 4106 controls from the Bipolar Disease Research Network (BDRN: OMEX). We find evidence of genetic heterogeneity delineating a statistically significant bicluster comprising a subset of BD cases which exhibits a disease-specific pattern of differential-expression across a subset of SNPs. This pattern replicates across the remaining data-sets collected by the PGC containing 5781/8289 (OMEX), 3581/7591 (Illumina), and 6825/9752(Affymetrix) cases/controls, respectively. This bicluster includes subjects diagnosed with bipolar type-I, as well as subjects diagnosed with bipolar type-II. However, the bicluster is enriched for bipolar type-I over type-II and may represent a collection of correlated genetic risk-factors. By investigating the bicluster-informed polygenic-risk-scoring (PRS), we find that the disease-specific pattern highlighted by the bicluster can be leveraged to eliminate noise from our GWAS analyses and improve not only risk prediction, particularly when using only a relatively small subset (e.g., ~ 1%) of the available SNPs, but also SNP replication. Though our primary focus is only the analysis of disease-related signal, we also identify replicable control-related heterogeneity. Covariate-corrected biclustering of raw genetic data appears to be a promising route for untangling heterogeneity and identifying replicable homogeneous genetic subtypes of complex disease. It may also prove useful in identifying protective effects within the control group. This approach circumvents some of the difficulties presented by subphenotype data collected by meta-analyses or 23 andMe, e.g., missingness, assessment variation, and reliance on self-report.

A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra

There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable fit. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.

Identification of Novel Genomic Loci for Anxiety and Extensive Genetic Overlap with Psychiatric Disorders

Background

Anxiety disorders are prevalent and anxiety symptoms co-occur with many psychiatric disorders. We aimed to identify genomic risk loci associated with anxiety, characterize its genetic architecture, and genetic overlap with psychiatric disorders.

Methods

We used the GWAS of anxiety symptoms, schizophrenia, bipolar disorder, major depression, and attention deficit hyperactivity disorder (ADHD). We employed MiXeR and LAVA to characterize the genetic architecture and genetic overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of genomic loci associated with anxiety and those shared with psychiatric disorders. Gene annotation and gene set analyses were conducted using OpenTargets and FUMA, respectively.

Results

Anxiety was polygenic with 12.9k estimated genetic risk variants and overlapped extensively with psychiatric disorders (4.1-11.4k variants). MiXeR and LAVA revealed predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 114 novel loci for anxiety by conditioning on the psychiatric disorders. We also identified loci shared between anxiety and major depression (n = 47), bipolar disorder (n = 33), schizophrenia (n = 71), and ADHD (n = 20). Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways and differential tissue expression in more diverse tissues than those annotated to the shared loci.

Conclusions

Anxiety is a highly polygenic phenotype with extensive genetic overlap with psychiatric disorders. These genetic overlaps enabled the identification of novel loci for anxiety. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified genetic loci implicate molecular pathways that may lead to potential drug targets.

A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra

There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable t. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.

Patterns of stressful life events and polygenic scores for five mental disorders and neuroticism among adults with depression

The dominant ('general') version of the diathesis-stress theory of depression views stressors and genetic vulnerability as independent risks. In the Australian Genetics of Depression Study (N = 14,146; 75% female), we tested whether polygenic scores (PGS) for major depression, bipolar disorder, schizophrenia, anxiety, ADHD, and neuroticism were associated with reported exposure to 32 childhood, past-year, lifetime, and accumulated stressful life events (SLEs). In false discovery rate-corrected models, the clearest PGS-SLE relationships were for the ADHD- and depression-PGSs, and to a lesser extent, the anxiety- and schizophrenia-PGSs. We describe the associations for childhood and accumulated SLEs, and the 2-3 strongest past-year/lifetime SLE associations. Higher ADHD-PGS was associated with all childhood SLEs (emotional abuse, emotional neglect, physical neglect; ORs = 1.09-1.14; p's < 1.3 × 10-5), more accumulated SLEs, and reported exposure to sudden violent death (OR = 1.23; p = 3.6 × 10-5), legal troubles (OR = 1.15; p = 0.003), and sudden accidental death (OR = 1.14; p = 0.006). Higher depression-PGS was associated with all childhood SLEs (ORs = 1.07-1.12; p's < 0.013), more accumulated SLEs, and severe human suffering (OR = 1.17; p = 0.003), assault with a weapon (OR = 1.12; p = 0.003), and living in unpleasant surroundings (OR = 1.11; p = 0.001). Higher anxiety-PGS was associated with childhood emotional abuse (OR = 1.08; p = 1.6 × 10-4), more accumulated SLEs, and serious accident (OR = 1.23; p = 0.004), physical assault (OR = 1.08; p = 2.2 × 10-4), and transportation accident (OR = 1.07; p = 0.001). Higher schizophrenia-PGS was associated with all childhood SLEs (ORs = 1.12-1.19; p's < 9.3-8), more accumulated SLEs, and severe human suffering (OR = 1.16; p = 0.003). Higher neuroticism-PGS was associated with living in unpleasant surroundings (OR = 1.09; p = 0.007) and major financial troubles (OR = 1.06; p = 0.014). A reversed pattern was seen for the bipolar-PGS, with lower odds of reported physical assault (OR = 0.95; p = 0.014), major financial troubles (OR = 0.93; p = 0.004), and living in unpleasant surroundings (OR = 0.92; p = 0.007). Genetic risk for several mental disorders influences reported exposure to SLEs among adults with moderately severe, recurrent depression. Our findings emphasise that stressors and diatheses are inter-dependent and challenge diagnosis and subtyping (e.g., reactive/endogenous) based on life events.

Loss of mGlu5 receptors in somatostatin-expressing neurons alters negative emotional states

Subtype 5 metabotropic glutamate receptors (mGlu5) are known to play an important role in regulating cognitive, social and valence systems. However, it remains largely unknown at which circuits and neuronal types mGlu5 act to influence these behavioral domains. Altered tissue- or cell-specific expression or function of mGlu5 has been proposed to contribute to the exacerbation of neuropsychiatric disorders. Here, we examined how these receptors regulate the activity of somatostatin-expressing (SST+) neurons, as well as their influence on behavior and brain rhythmic activity. Loss of mGlu5 in SST+ neurons elicited excitatory synaptic dysfunction in a region and sex-specific manner together with a range of emotional imbalances including diminished social novelty preference, reduced anxiety-like behavior and decreased freezing during retrieval of fear memories. In addition, the absence of mGlu5 in SST+ neurons during fear processing impaired theta frequency oscillatory activity in the medial prefrontal cortex and ventral hippocampus. These findings reveal a critical role of mGlu5 in controlling SST+ neurons excitability necessary for regulating negative emotional states.

Examining intergenerational risk factors for conduct problems using polygenic scores in the Norwegian Mother, Father and Child Cohort Study

The aetiology of conduct problems involves a combination of genetic and environmental factors, many of which are inherently linked to parental characteristics given parents' central role in children's lives across development. It is important to disentangle to what extent links between parental heritable characteristics and children's behaviour are due to transmission of genetic risk or due to parental indirect genetic influences via the environment (i.e., genetic nurture). We used 31,290 genotyped mother-father-child trios from the Norwegian Mother, Father and Child Cohort Study (MoBa), testing genetic transmission and genetic nurture effects on conduct problems using 13 polygenic scores (PGS) spanning psychiatric conditions, substance use, education-related factors, and other risk factors. Maternal or self-reports of conduct problems at ages 8 and 14 years were available for up to 15,477 children. We found significant genetic transmission effects on conduct problems for 12 out of 13 PGS at age 8 years (strongest association: PGS for smoking, β = 0.07, 95% confidence interval = [0.05, 0.08]) and for 4 out of 13 PGS at age 14 years (strongest association: PGS for externalising problems, β = 0.08, 95% confidence interval = [0.05, 0.11]). Conversely, we did not find genetic nurture effects for conduct problems using our selection of PGS. Our findings provide evidence for genetic transmission in the association between parental characteristics and child conduct problems. Our results may also indicate that genetic nurture via traits indexed by our polygenic scores is of limited aetiological importance for conduct problems-though effects of small magnitude or effects via parental traits not captured by the included PGS remain a possibility.

Childhood correlates and young adult outcomes of trajectories of emotional problems from childhood to adolescence

BACKGROUND

Emotional problems, especially anxiety, have become increasingly common in recent generations. Few population-based studies have examined trajectories of emotional problems from early childhood to late adolescence or investigated differences in psychiatric and functional outcomes.

METHODS

Using the Avon Longitudinal Study of Parents and Children (ALSPAC, n = 8286, 50.4% male), we modeled latent class growth trajectories of emotional problems, using the parent-reported Strength and Difficulties Questionnaire emotional scale (SDQ-E) on seven occasions (4-17 years). Psychiatric outcomes in young adulthood (21-25 years) were major depressive disorder (MDD), generalized anxiety disorder (GAD), and self-harm. Functional outcomes were exam attainment, educational/occupational status, and social relationship quality.

RESULTS

We identified four classes of emotional problems: low (67.0%), decreasing (18.4%), increasing (8.9%), and persistent (5.7%) problems. Compared to those in the low class, individuals with decreasing emotional problems were not at elevated risk of any poor adult outcome. Individuals in the increasing and persistent classes had a greater risk of adult MDD (RR: 1.59 95% CI 1.13-2.26 and RR: 2.25 95% CI 1.49-3.41) and self-harm (RR: 2.37 95% CI 1.91-2.94 and RR: 1.87 95% CI 1.41-2.48), and of impairment in functional domains. Childhood sleep difficulties, irritability, conduct and neurodevelopmental problems, and family adversity were associated with a persistent course of emotional problems.

CONCLUSIONS

Childhood emotional problems were common, but those whose symptoms improved over time were not at increased risk for adverse adult outcomes. In contrast, individuals with persistent or adolescent-increasing emotional problems had a higher risk of mental ill-health and social impairment in young adulthood which was especially pronounced for those with persistent emotional problems.

A Developmentally-Informative Genome-wide Association Study of Alcohol Use Frequency

Contemporary genome-wide association study (GWAS) methods typically do not account for variability in genetic effects throughout development. We applied genomic structural equation modeling to combine developmentally-informative phenotype data and GWAS to create polygenic scores (PGS) for alcohol use frequency that are specific to developmental stage. Longitudinal cohort studies targeted for gene-identification analyses include the Collaborative Study on the Genetics of Alcoholism (adolescence n = 1,118, early adulthood n = 2,762, adulthood n = 5,255), the National Longitudinal Study of Adolescent to Adult Health (adolescence n = 3,089, early adulthood n = 3,993, adulthood n = 5,149), and the Avon Longitudinal Study of Parents and Children (ALSPAC; adolescence n = 5,382, early adulthood n = 3,613). PGS validation analyses were conducted in the COGA sample using an alternate version of the discovery analysis with COGA removed. Results suggest that genetic liability for alcohol use frequency in adolescence may be distinct from genetic liability for alcohol use frequency later in developmental periods. The age-specific PGS predicts an increase of 4 drinking days per year per PGS standard deviation when modeled separately from the common factor PGS in adulthood. The current work was underpowered at all steps of the analysis plan. Though small sample sizes and low statistical power limit the substantive conclusions that can be drawn regarding these research questions, this work provides a foundation for future genetic studies of developmental variability in the genetic underpinnings of alcohol use behaviors and genetically-informed, age-matched phenotype prediction.

Inter- and transgenerational heritability of preconception chronic stress or alcohol exposure: Translational outcomes in brain and behavior

Chronic stress and alcohol (ethanol) use are highly interrelated and can change an individual's behavior through molecular adaptations that do not change the DNA sequence, but instead change gene expression. A recent wealth of research has found that these nongenomic changes can be transmitted across generations, which could partially account for the "missing heritability" observed in genome-wide association studies of alcohol use disorder and other stress-related neuropsychiatric disorders. In this review, we summarize the molecular and behavioral outcomes of nongenomic inheritance of chronic stress and ethanol exposure and the germline mechanisms that could give rise to this heritability. In doing so, we outline the need for further research to: (1) Investigate individual germline mechanisms of paternal, maternal, and biparental nongenomic chronic stress- and ethanol-related inheritance; (2) Synthesize and dissect cross-generational chronic stress and ethanol exposure; (3) Determine cross-generational molecular outcomes of preconception ethanol exposure that contribute to alcohol-related disease risk, using cancer as an example. A detailed understanding of the cross-generational nongenomic effects of stress and/or ethanol will yield novel insight into the impact of ancestral perturbations on disease risk across generations and uncover actionable targets to improve human health.

Nightmares share genetic risk factors with sleep and psychiatric traits

Nightmares are vivid, extended, and emotionally negative or negative dreams that awaken the dreamer. While sporadic nightmares and bad dreams are common and generally harmless, frequent nightmares often reflect underlying pathologies of emotional regulation. Indeed, insomnia, depression, anxiety, or alcohol use have been associated with nightmares in epidemiological and clinical studies. However, the connection between nightmares and their comorbidities are poorly understood. Our goal was to examine the genetic risk factors for nightmares and estimate correlation or causality between nightmares and comorbidities. We performed a genome-wide association study (GWAS) in 45,255 individuals using a questionnaire-based assessment on the frequency of nightmares during the past month and genome-wide genotyping data. While the GWAS did not reveal individual risk variants, heritability was estimated at 5%. In addition, the genetic correlation analysis showed a robust correlation (rg > 0.4) of nightmares with anxiety (rg = 0.671, p = 7.507e-06), depressive (rg = 0.562, p = 1.282e-07) and posttraumatic stress disorders (rg = 0.4083, p = 0.0152), and personality trait neuroticism (rg = 0.667, p = 4.516e-07). Furthermore, Mendelian randomization suggested causality from insomnia to nightmares (beta = 0.027, p = 0.0002). Our findings suggest that nightmares share genetic background with psychiatric traits and that insomnia may increase an individual's liability to experience frequent nightmares. Given the significant correlations with psychiatric and psychological traits, it is essential to grow awareness of how nightmares affect health and disease and systematically collect information about nightmares, especially from clinical samples and larger cohorts.

The structure of psychiatric comorbidity without selection and assortative mating

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

The genetic architecture of youth anxiety: a study protocol

BACKGROUND

Anxiety disorders are the most common psychiatric problems among Canadian youth and typically have an onset in childhood or adolescence. They are characterized by high rates of relapse and chronicity, often resulting in substantial impairment across the lifespan. Genetic factors play an important role in the vulnerability toward anxiety disorders. However, genetic contribution to anxiety in youth is not well understood and can change across developmental stages. Large-scale genetic studies of youth are needed with detailed assessments of symptoms of anxiety disorders and their major comorbidities to inform early intervention or preventative strategies and suggest novel targets for therapeutics and personalization of care.

METHODS

The Genetic Architecture of Youth Anxiety (GAYA) study is a Pan-Canadian effort of clinical and genetic experts with specific recruitment sites in Calgary, Halifax, Hamilton, Toronto, and Vancouver. Youth aged 10-19 (n = 13,000) will be recruited from both clinical and community settings and will provide saliva samples, complete online questionnaires on demographics, symptoms of mental health concerns, and behavioural inhibition, and complete neurocognitive tasks. A subset of youth will be offered access to a self-managed Internet-based cognitive behavioral therapy resource. Analyses will focus on the identification of novel genetic risk loci for anxiety disorders in youth and assess how much of the genetic risk for anxiety disorders is unique or shared across the life span.

DISCUSSION

Results will substantially inform early intervention or preventative strategies and suggest novel targets for therapeutics and personalization of care. Given that the GAYA study will be the biggest genomic study of anxiety disorders in youth in Canada, this project will further foster collaborations nationally and across the world.

Gene Discovery and Biological Insights into Anxiety Disorders from a Multi-Ancestry Genome-wide Association Study of >1.2 Million Participants

We leveraged information from more than 1.2 million participants to investigate the genetics of anxiety disorders across five continental ancestral groups. Ancestry-specific and cross-ancestry genome-wide association studies identified 51 anxiety-associated loci, 39 of which are novel. Additionally, polygenic risk scores derived from individuals of European descent were associated with anxiety in African, Admixed-American, and East Asian groups. The heritability of anxiety was enriched for genes expressed in the limbic system, the cerebral cortex, the cerebellum, the metencephalon, the entorhinal cortex, and the brain stem. Transcriptome- and proteome-wide analyses highlighted 115 genes associated with anxiety through brain-specific and cross-tissue regulation. We also observed global and local genetic correlations with depression, schizophrenia, and bipolar disorder and putative causal relationships with several physical health conditions. Overall, this study expands the knowledge regarding the genetic risk and pathogenesis of anxiety disorders, highlighting the importance of investigating diverse populations and integrating multi-omics information.

Causal effect of systemic lupus erythematosus on psychiatric disorders: A two-sample Mendelian randomization study

BACKGROUND

This study aims to investigate the association between systemic lupus erythematosus (SLE) and the risk of seven psychiatric disorders through the application of Mendelian randomization (MR) analysis due to previous observational studies that have suggested a potential link between SLE and psychiatric disorders.

METHODS

We collected genetic instruments for SLE from a genome-wide association study (GWAS) involving 23,210 individuals. Seven psychiatric traits were enrolled from the recent largest GWAS, including major depression disorder (MDD), generalized anxiety disorder (GAD), schizophrenia (SCZ), bipolar disorder (BID), autism spectrum disorder (ASD), attention deficit/hyperactivity disorder (ADHD), and insomnia. Summary statistics for psychiatric disorders were obtained from different GWAS meta-analysis studies. The inverse variance weighted (IVW) method was used as the main MR analysis.

RESULTS

The IVW method indicated that SLE is associated with a higher risk of GAD (OR = 1.072, 95 % CI [1.017-1.129], P = 0.008) and SCZ (OR = 3.242, 95 % CI [1.578-6.660], P = 0.007). However, no evidence was found for the causal associations between SLE and other psychiatric disorders. Further analyses found no evidence of pleiotropy and heterogeneity.

CONCLUSIONS

This two-sample MR analysis provides evidence that genetically predicted SLE may increase the risk of GAD and SCZ in a European population. Future studies are needed to elucidate and investigate the mechanisms underlying these causal relationships. Considering the existence of racial genomic heterogeneity, our findings must be viewed with caution.

A psychometric evaluation of the 16-item PHQ-ADS concomitant anxiety and depression scale in the UK biobank using item response theory

BACKGROUND

The Patient Health Questionnaire Anxiety and Depression Scale (PHQ-ADS) provides a reliable and valid measure of concomitant depression and anxiety. However, research on its psychometric efficiency and optimal scale length using item-response theory (IRT) has not been reported. This study aimed to optimize the length of the PHQ-ADS scale without losing information by discarding items that were a poor fit to the IRT model.

METHODS

The UK Biobank is a large cohort study designed to investigate risk factors for a broad range of disease. PHQ-ADS data were available from n = 152,826 participants (age = 55.87 years; SD = 7.73; 56.4 % female), 30.4 % of the entire UK Biobank sample. Psychometric properties of the PHQ-ADS were investigated using a 2-parameter IRT and Mokken analysis. Item statistics included discrimination, difficulty and Loevinger H coefficients of monotonicity.

RESULTS

In the entire 16-item scale, item discrimination ranged from 1.40 to 4.22, with the item 'worrying' showing the highest level of discrimination and the item 'sleep disturbance' showing the lowest. Mokken analysis showed that the 16-item PHQ-ADS scale could be reduced to a 7-item scale without loss of test information. The reduced scale comprised mainly items measuring cognitive-affective symptoms of anxiety/depression, whereas items measuring somatic symptoms were discarded. The revised scale showed high discrimination and scalability.

LIMITATIONS

Findings are limited by the use of cross-sectional data that only included the baseline online questionnaire, but not other waves.

CONCLUSIONS

IRT is a useful technique for scale reductions which serve the clinical and epidemiological need to optimize screening questionnaires to reduce redundancy and maximize information. A reduced-item 7-item PHQ-ADS scale reduces the response burden on participants in epidemiological research settings, without loss of information.

Effects of sex and gender on the etiologies and presentation of select internalizing psychopathologies

The internalizing spectrum encompasses a subset of psychopathologies characterized by emotional liability, anhedonia, anxiousness, distress, and fear, and includes, among others, diagnoses of major depressive disorder (MDD), generalized anxiety disorder (GAD), and posttraumatic stress disorder (PTSD). In this review, we describe the vast body of work highlighting a role for sex and gender in the environment, symptom onset, genetic liability, and disorder progression and comorbidities of MDD, GAD, and PTSD. We also point the reader to different language used in diverse fields to describe sexual and gender minorities that may complicate the interpretation of emerging literature from the social sciences, psychiatric and psychological sciences, and genetics. Finally, we identify several gaps in knowledge that we hope serve as launch-points for expanding the scope of psychiatric studies beyond binarized sex-stratification. Despite being under-represented in genomics studies, placing emphasis on inclusion of sexual and gender diverse participants in these works will hopefully improve our understanding of disorder etiology using genetics as one tool to inform how biology (e.g., hormone concentration) and environmental variables (e.g., exposure to traumatic events) contribute to differences in symptom onset, pattern, and long-term trajectory.

Genome-wide meta-analysis, functional genomics and integrative analyses implicate new risk genes and therapeutic targets for anxiety disorders

Anxiety disorders are the most prevalent mental disorders. However, the genetic etiology of anxiety disorders remains largely unknown. Here we conducted a genome-wide meta-analysis on anxiety disorders by including 74,973 (28,392 proxy) cases and 400,243 (146,771 proxy) controls. We identified 14 risk loci, including 10 new associations near CNTNAP5, MAP2, RAB9BP1, BTN1A1, PRR16, PCLO, PTPRD, FARP1, CDH2 and RAB27B. Functional genomics and fine-mapping pinpointed the potential causal variants, and expression quantitative trait loci analysis revealed the potential target genes regulated by the risk variants. Integrative analyses, including transcriptome-wide association study, proteome-wide association study and colocalization analyses, prioritized potential causal genes (including CTNND1 and RAB27B). Evidence from multiple analyses revealed possibly causal genes, including RAB27B, BTN3A2, PCLO and CTNND1. Finally, we showed that Ctnnd1 knockdown affected dendritic spine density and resulted in anxiety-like behaviours in mice, revealing the potential role of CTNND1 in anxiety disorders. Our study identified new risk loci, potential causal variants and genes for anxiety disorders, providing insights into the genetic architecture of anxiety disorders and potential therapeutic targets.

Genetic correlations between suicide attempts and psychiatric and intermediate phenotypes adjusting for mental disorders

BACKGROUND

Suicide attempts are a moderately heritable trait, and genetic correlations with psychiatric and related intermediate phenotypes have been reported. However, as several mental disorders as well as major depressive disorder (MDD) are strongly associated with suicide attempts, these genetic correlations could be mediated by psychiatric disorders. Here, we investigated genetic correlations of suicide attempts with psychiatric and related intermediate phenotypes, with and without adjusting for mental disorders.

METHODS

To investigate the genetic correlations, we utilized large-scale genome-wide association study summary statistics for suicide attempts (with and without adjusting for mental disorders), nine psychiatric disorders, and 15 intermediate phenotypes.

RESULTS

Without adjusting for mental disorders, suicide attempts had significant positive genetic correlations with risks of attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, MDD, anxiety disorders and posttraumatic stress disorder; higher risk tolerance; earlier age at first sexual intercourse, at first birth and at menopause; higher parity; lower childhood IQ, educational attainment and cognitive ability; and lower smoking cessation. After adjusting for mental disorders, suicide attempts had significant positive genetic correlations with the risk of MDD; earlier age at first sexual intercourse, at first birth and at menopause; and lower educational attainment. After adjusting for mental disorders, most of the genetic correlations with psychiatric disorders were decreased, while several genetic correlations with intermediate phenotypes were increased.

CONCLUSIONS

These findings highlight the importance of considering mental disorders in the analysis of genetic correlations related to suicide attempts and suggest that susceptibility to MDD, reproductive behaviors, and lower educational levels share a genetic basis with suicide attempts after adjusting for mental disorders.

Estimating the impact of transmitted and non-transmitted psychiatric and neurodevelopmental polygenic scores on youth emotional problems

Anxiety and depression (emotional disorders) are familial and heritable, especially when onset is early. However, other cross-generational studies suggest transmission of youth emotional problems is explained by mainly environmental risks. We set out to test the contribution of parental non-transmitted genetic liability, as indexed by psychiatric/neurodevelopmental common polygenic liability, to youth emotional problems using a UK population-based cohort: the Millennium Cohort Study. European (N = 6328) and South Asian (N = 814) ancestries were included, as well as a subset with genomic data from both parents (European: N = 2809; South Asian: N = 254). We examined the association of transmitted (PGST) and non-transmitted polygenic scores (PGSNT) for anxiety, depression, bipolar disorder and neurodevelopmental disorders (attention-deficit/hyperactivity disorder [ADHD], autism spectrum disorder [ASD], schizophrenia) with youth emotional disorder and symptom scores, measured using the parent- and self-reported Strengths and Difficulties Questionnaire emotional subscale at 6 timepoints between ages 3-17 years. In the European sample, PGST for anxiety and depression, but not bipolar disorder, were associated with emotional disorder and symptom scores across all ages, except age 3, with strongest association in adolescence. ADHD and ASD PGST also showed association across ages 11-17 years. In the South Asian sample, evidence for associations between all PGST and outcome measures were weaker. There was weak evidence of association between PGSNT for anxiety and depression and age 17 symptom scores in the South Asian sample, but not in the European sample for any outcome. Overall, PGST for depression, anxiety, ADHD and ASD contributed to youth emotional problems, with stronger associations in adolescence. There was limited support for non-transmitted genetic effects: these findings do not support the hypothesis that parental polygenic psychiatric/neurodevelopmental liability confer risk to offspring emotional problems through non-transmitted rearing/nurture effects.

Using Alternative Definitions of Controls to Increase Statistical Power in GWAS

Genome-wide association studies (GWAS) are underpowered due to small effect sizes of single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the most statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.

Genetic associations and potential mediators between psychiatric disorders and irritable bowel syndrome: a Mendelian randomization study with mediation analysis

Objective

Potential causal associations between psychiatric disorders and irritable bowel syndrome have been demonstrated in observational studies; however, these studies are susceptible to underlying confounding and reverse causation biases. We aimed to assess the causal effects of psychiatric disorders on irritable bowel syndrome (IBS) and the potential mediators from a genetic perspective by conducting a Mendelian randomization (MR) study with mediation analysis.

Method

Genetic instruments associated with psychiatric disorders, potential mediators, and IBS were obtained from large-scale genome-wide association studies (GWAS). Three MR methods - the inverse-variance weighted (IVW) method, MR-Egger method, and weighted median method, were used to investigate causal association estimates. Heterogeneity among different genetic instrumental variables (IVs) was assessed using Q tests. Additionally, the MR-PRESSO and MR-Pleiotropy methods were used to verify horizontal pleiotropy and detect outliers that might bias the results, which were removed from further analysis. Consequently, we used MR mediation analysis to investigate potential mediators in the causal associations between psychiatric disorders and IBS.

Results

MR provided evidence of the causal effects of genetically predicted broad depression, major depressive disorder (MDD), anxiety disorder, post-traumatic stress disorder (PTSD), and schizophrenia on IBS. The results of MR mediation analysis demonstrated that the reduction in acetate levels mediated 12.6% of the effects of broad depression on IBS; insomnia mediated 16.00%, 16.20%, and 27.14% of the effects of broad depression, MDD, and PTSD on IBS, respectively; and the increase in blood β-hydroxybutyrate levels mediated 50.76% of the effects of schizophrenia on IBS.

Conclusion

Our study confirmed the brain-gut axis involvement and potential modulators in the pathophysiology of psychiatric disorder-induced IBS from a genetic perspective, and suggests potential therapeutic targets for the disrupted brain-gut axis.

Genetics of psycho-emotional well-being: genome-wide association study and polygenic risk score analysis

Background

Psycho-emotional well-being is essential for living a life of satisfaction and fulfillment. However, depression and anxiety have become the leading mental health issues worldwide, according to the World Health Organization. Both disorders have been linked to stress and other psychological factors. Their genetic basis remains understudied.

Methods

In 2020-2021, the psycho-emotional well-being of 30,063 Russians with no known psychiatric history was assessed using the Hospital Anxiety and Depression Scale (HADS) for general mental health and the HADS subscale A (anxiety) for anxiety. Following the original instructions, an anxiety score of ≥11 points was used as the anxiety threshold. A genome-wide association study was performed to find associations between anxiety and HADS/HADS-A scores using linear and logistic regressions based on HADS/HADS-A scores as binary and continuous variables, respectively. In addition, the links between anxiety, sociodemographic factors (such as age, sex, and employment), lifestyle (such as physical activity, sleep duration, and smoking), and markers of caffeine and alcohol metabolism were analyzed. To assess the risk of anxiety, polygenic risk score modeling was carried out using open-access software and principal component analysis (PCA) to simplify the calculations (ROC AUC = 89.4 ± 2.2% on the test set).

Results

There was a strong positive association between HADS/HADS-A scores and sociodemographic factors and lifestyle. New single-nucleotide polymorphisms (SNPs) with genome-wide significance were discovered, which had not been associated with anxiety or other stress-related conditions but were located in genes previously associated with bipolar disorder, schizophrenia, or emotional instability. The CACNA1C variant rs1205787230 was associated with clinical anxiety (a HADS-A score of ≥11 points). There was an association between anxiety levels (HADS-A scores) and genes involved in the activity of excitatory neurotransmitters: PTPRN2 (rs3857647), DLGAP4 (rs8114927), and STK24 (rs9517326).

Conclusion

Our results suggest that calcium channels and monoamine neurotransmitters, as well as SNPs in genes directly or indirectly affecting neurogenesis and synaptic functions, may be involved in the development of increased anxiety. The role of some non-genetic factors and the clinical significance of physiological markers such as lifestyle were also demonstrated.

To Each His Own Fear: Gender-Related Association of Anxiety, Substance Use, and Eating Disorders in a Representative Birth Cohort Sample of Young Adults with Either COMT Val158Met allele

INTRODUCTION

The role of catechol-O-methyltransferase (COMT) in catecholamine neurotransmitter metabolism has led to the investigation of variants of the corresponding gene in the etiology of different psychiatric disorders, but the results are inconclusive.

METHODS

We have examined the relationship between COMT Val158Met single nucleotide polymorphism (rs4680) and the occurrence of psychiatric disorders in a highly representative birth cohort sample of young adults in the Estonian Children Personality Behaviour and Health Study (original n = 1,238). The lifetime occurrence of psychiatric disorders at the age of 25 years was assessed with the Mini-International Neuropsychiatric Interview.

RESULTS

Both Val- and Met-alleles of the COMT Val158Met were associated with specific psychiatric disorders. Met-allele carriers had a significantly higher occurrence of agoraphobia (3.2% vs. 0.5%; χ2 = 4.10; p < 0.05) compared to Val/Val homozygotes. Also, the occurrence of panic disorder was significantly higher in female Met-allele carriers than in Val/Val homozygote females (10.2% vs. 3.6%; χ2 = 4.62 p = 0.03). In contrast, the occurrence of generalized anxiety disorder was higher in Val/Val females when compared to Met-allele carriers (12.7% vs. 6.8%; χ2 = 4.16; p = 0.04). Also, female Val/Val homozygotes (15.5%) had a higher occurrence of eating disorders than Met-allele carriers (6.1%) of the COMT Val158Met polymorphism (χ2 = 10.39; p = 0.002). In the whole sample, Met-allele homozygotes had a higher occurrence of alcohol use and substance use disorders than Val-allele carriers (χ2 = 3.62 and 3.68, respectively; p < 0.05).

CONCLUSION

In a regional highly birth cohort representative sample, either COMT rs4680 variant was observed in association with specific psychiatric disorders.

An evolutionary perspective on complex neuropsychiatric disease

The forces of evolution-mutation, selection, migration, and genetic drift-shape the genetic architecture of human traits, including the genetic architecture of complex neuropsychiatric illnesses. Studying these illnesses in populations that are diverse in genetic ancestry, historical demography, and cultural history can reveal how evolutionary forces have guided adaptation over time and place. A fundamental truth of shared human biology is that an allele responsible for a disease in anyone, anywhere, reveals a gene critical to the normal biology underlying that condition in everyone, everywhere. Understanding the genetic causes of neuropsychiatric disease in the widest possible range of human populations thus yields the greatest possible range of insight into genes critical to human brain development. In this perspective, we explore some of the relationships between genes, adaptation, and history that can be illuminated by an evolutionary perspective on studies of complex neuropsychiatric disease in diverse populations.

Exploring genetic risk for catatonia in a genome wide association study and polygenic risk score analysis

BACKGROUND

Catatonia is an under-recognized disorder characterized by psychomotor (increased, decreased, or abnormal) changes, affective symptoms, and disturbance of volition, which may arise in the setting of decompensated psychiatric or non-psychiatric medical disorders. Genetic studies of catatonia are limited, and to the best of our knowledge no prior genome wide association studies of catatonia have been performed to date.

METHODS

First we performed a genome wide association study of catatonia regardless of etiology (psychiatric or non-psychiatric). Secondarily we evaluated whether there was an elevated genetic risk profile for predisposing psychiatric disorders (schizophrenia spectrum disorder, bipolar affective disorder, etc.) in patients with catatonia. We used a matched case control design and applied polygenic risk scores to evaluate for a shared polygenetic contribution to catatonia from common psychiatric phenotypes that show a high prevalence of catatonia in their decompensated states.

RESULTS

Anxiety, bipolar affective disorder, schizophrenia spectrum disorder and cross disorder polygenic risk scores were significantly associated with catatonia case status in both unadjusted and adjusted logistic regression models for the European Ancestry set even after correcting for multiple comparisons. Depression, Alzheimer's, Autism Spectrum Disorder and Obsessive Disorder polygenic risk scores were not significantly associated with catatonia status in participants of European Ancestry. In the African Ancestry set, no psychiatric polygenic risk scores were significantly associated with catatonia status in either the unadjusted or adjusted regression models.

CONCLUSIONS

Even after controlling for relevant covariates, anxiety, bipolar affective disorder, schizophrenia spectrum disorder and cross disorders were significantly associated with catatonia status suggesting that there might be a shared genetic risk for those disorders amongst patients with catatonia.

Multi-polygenic scores in psychiatry: From disorder specific to transdiagnostic perspectives

The dense co-occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder-specific and a transdiagnostic framework. The study sample (n = 513) was deeply phenotyped, consisting of 452 patients from tertiary care with mood disorders, anxiety disorders (ANX), attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders, and/or substance use disorders (SUD) and 61 unaffected comparison individuals. We computed subject-specific polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross-disorder behavioral dimensions derived from a rich battery of psychopathology assessments. High PRSs for depression were unselectively associated with the diagnosis of SUD, ADHD, ANX, and mood disorders (p < 1e-4). In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems (R2  = 0.041, p = 5e-4) but not others. This study adds evidence to the ongoing discussion about the misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.

Persistent thinness and anorexia nervosa differ on a genomic level

Thinness and anorexia nervosa are both characterised by persistent low weight. Individuals with anorexia nervosa concurrently report distorted perceptions of their body and engage in weight-loss behaviours, whereas individuals with thinness often wish to gain weight. Both conditions are heritable and share genomics with BMI, but are not genetically correlated with each other. Based on their pattern of genetic associations with other traits, we explored differences between thinness and anorexia nervosa on a genomic level. In Part 1, using publicly available data, we compared genetic correlations of persistent thinness/anorexia nervosa with eleven psychiatric disorders. In Part 2, we identified individuals with adolescent persistent thinness in the Avon Longitudinal Study of Parents and Children (ALSPAC) by latent class growth analysis of measured BMI from 10 to 24 years (n = 6594) and evaluated associations with psychiatric and anthropometric polygenic scores. In Part 1, in contrast to the positive genetic correlations of anorexia nervosa with various psychiatric disorders, persistent thinness showed negative genetic correlations with attention deficit hyperactivity disorder (rgAN = 0.08 vs. rgPT = -0.30), alcohol dependence (rgAN = 0.07 vs. rgPT = -0.44), major depressive disorder (rgAN = 0.27 vs. rgPT = -0.18) and post-traumatic stress disorder (rgAN = 0.26 vs. rgPT = -0.20). In Part 2, individuals with adolescent persistent thinness in the ALSPAC had lower borderline personality disorder polygenic scores (OR = 0.77; Q = 0.01). Overall, results suggest that genetic variants associated with thinness are negatively associated with psychiatric disorders and therefore thinness may be differentiable from anorexia nervosa on a genomic level.

Stratifying early-onset emotional disorders: using genetics to assess persistence in young people of European and South Asian ancestry

BACKGROUND

Depression and anxiety are the most common mental health problems in young people. Currently, clinicians are advised to wait before initiating treatment for young people with these disorders as many spontaneously remit. However, others develop recurrent disorder but this subgroup cannot be identified at the outset. We examined whether psychiatric polygenic scores (PGS) could help inform stratification efforts to predict those at higher risk of recurrence.

METHODS

Probable emotional disorder was examined in two UK population cohorts using the emotional symptoms subscale of the Strengths and Difficulties Questionnaire (SDQ). Those with emotional disorder at two or more time points between ages 5 and 25 years were classed as 'recurrent emotional disorder' (n = 1,643) and those with emotional disorder at one time point as having 'single episode emotional disorder' (n = 1,435, controls n = 8,715). We first examined the relationship between psychiatric PGS and emotional disorders in childhood and adolescence. Second, we tested whether psychiatric PGS added to predictor variables of known association with emotional disorder (neurodevelopmental comorbidity, special educational needs, family history of depression and socioeconomic status) when discriminating between single-episode and recurrent emotional disorder. Analyses were conducted separately in individuals of European and South Asian ancestry.

RESULTS

Probable emotional disorder was associated with higher PGS for major depressive disorder (MDD), anxiety, broad depression, ADHD and autism spectrum disorder (ASD) in those of European ancestry. Higher MDD and broad depression PGS were associated with emotional disorder in people of South Asian ancestry. Recurrent, compared to single-episode, emotional disorder was associated with ASD and parental psychiatric history. PGS were not associated with episode recurrence, and PGS did not improve discrimination of recurrence when combined with clinical predictors.

CONCLUSIONS

Our findings do not support the use of PGS as a tool to assess the likelihood of recurrence in young people experiencing their first episode of emotional disorder.