Background:Evidence indicates substantial genetic overlap between psychiatric diagnoses. Accounting for these transdiagnostic effects can sharpen research on disorder-specific genetic architecture and patterns of comorbidity. Methods:We applied genomic structural equation modeling to genome-wide association study summary statistics from 11 major psychiatric disorders to isolate genetic effects shared across disorders (the genomic p factor) from residual genetic effects associated with each disorder (non-p). Using these non-p summary statistics, we examined SNP heritability, genetic correlations among psychiatric disorders, and genetic correlations with external biobehavioural traits spanning socio-demographic, anthropometric, health-related, and psychological domains. Results:After accounting for transdiagnostic effects, genetic associations between psychiatric disorders changed substantially, with many correlations attenuated and some showing marked shifts in magnitude and direction. Genetic correlations between psychiatric disorders and external biobehavioural traits showed greater specificity. Conclusion:Removing transdiagnostic effects provides a more nuanced view of the genetic architecture underlying psychiatric disorders and sharpens inference about genetic relationships between disorders and other comorbid traits. This may inform future work on psychiatric classification, prediction, and treatment research.

OBJECTIVE:Attention-deficit/hyperactivity disorder (ADHD) may lead to depression, but little is known about its underlying mechanisms. We examined whether clinical factors (irritability, anxiety), cognitive-affective processes (emotion recognition, response inhibition, working memory, sustained attention), and negative thought patterns (external locus of control, negative cognitive style) mediated ADHD-depression associations across development and whether these pathways differ by sex. METHOD:Analyses were performed in the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Twins Early Development Study (TEDS). In both samples, ADHD was assessed using the Strengths and Difficulties Questionnaire (SDQ) hyperactivity/inattention subscale at ages 7, 12/13, and 16/17 years. Depressive symptoms were assessed using the short Mood and Feelings Questionnaire at ages 12, 18/21, and 26/27. Mediators were assessed at ages 8-11, 16-17, and 21-25 years with counterfactual mediation models. RESULTS:Clinical factors were assessed and mediated the ADHD-depression effect in both cohorts across development. In ALSPAC, clinical mediators contributed most in childhood (30%) and young adulthood (29%), whereas in TEDS, they contributed most in adolescence (46%). In ALSPAC, negative thought patterns mostly contributed in adolescence (39%), whereas cognitive-affective factors did not show consistent evidence of mediating effects across development. All mediators combined explained 30%, 48%, and 34% of the total effect of ADHD on depression in childhood, adolescence, and young adulthood, respectively. In sex-stratified models, the relative contribution of mediators varied by sex and developmental stage. In childhood, mediators accounted for a greater proportion of the total effect in male (37%) than in female (25%) individuals, whereas a similar proportion of mediated effects was observed across sexes during adolescence (48% in female and 45% in male individuals). In young adulthood, the indirect effect via all mediators was evident only in female individuals (42%). CONCLUSION:Mechanisms linking ADHD and depression are developmental stage and sex specific. Irritability and anxiety in childhood and young adulthood (particularly for female individuals), and external locus of control and negative cognitive style in adolescence, might represent promising intervention targets for preventing depression in youth with ADHD. STUDY PREREGISTRATION INFORMATION:Study Preregistration: Clinical and Cognitive Mediators Underlying Subsequent Depression in Individuals With Attention-Deficit/Hyperactivity Disorder: A Developmental Approach; https://www.jaacap.org/article/S0890-8567(25)00171-6/fulltext.

STUDY OBJECTIVES:Chronotype has been linked to a wide variety of psychiatric conditions. In particular, evening chronotype could be a transdiagnostic risk factor for different mental health difficulties. In this study, we examine how chronotype relates to psychopathology and whether it can be conceptualized as a part of the global construct of psychopathology (p-factor) by studying the genetic and environmental overlap between these variables. We utilize data from a genetically informative design to study: (1) the association between chronotype and psychopathology; (2) the genetic and environmental overlap between chronotype and psychopathology; and (3) the predictive value of polygenic score (PGS) for chronotype for psychopathology. METHODS:Chronotype was measured using an abbreviated version of the Munich Chronotype Questionnaire. Measures of psychopathology included: depression, anxiety, alcohol use, and psychotic experiences among others. We used different psychopathology and chronotype-related polygenic scores. Association between chronotype and psychopathology were examined with three approaches: (1) phenotypic associations; (2) genetic and environmental associations using the twin design; and (3) genetic associations using PGS. RESULTS:There were small, though largely significant, associations between chronotype and psychopathology with significant genetic and environmental overlap. Chronotype PGS significantly predicted a very small proportion of the variance for some measures of psychopathology (e.g. symptoms of attention deficit hyperactivity disorder). However, overall, our results also suggest that the majority of genetic/environmental influences (96 per cent) on chronotype do not overlap with those on the psychopathology factor. CONCLUSIONS:Results from this study highlight existence of significant associations between chronotype and certain psychopathology traits. However, the very small associations do not support the idea that chronotype is a core element of the general "p-factor."

Background: Posttraumatic stress disorder (PTSD) occurs following traumatic experiences, but not everyone who experiences trauma develops PTSD. Genetic factors play an important role in shaping how individuals respond to trauma, a form of gene-environment interaction. An open question in PTSD genetics research is the extent to which gene-environment interactions vary across specific traumas. Objective: We aimed to compare gene-environment interaction effects across a broad range of self-reported traumatic experiences across the lifespan. Method: We analysed existing data from two large UK cohorts: the UK Biobank and GLAD-EDGI-COPING (N=144,702). PTSD symptoms were assessed using the six-item abbreviated PTSD Checklist. We examined eleven self-reported trauma exposures, including five childhood traumas and six adulthood traumas. We conducted gene-environment interaction analyses for each trauma at three levels of genetic specificity: polygenic risk scores, specific genes, and specific genetic variants. Results: Childhood traumas had stronger associations with PTSD symptoms and greater gene-environment interactions than adulthood traumas on average. Childhood emotional and physical neglect also had gene-environment greater interactions than childhood abuse. Interaction patterns varied across genes and variants, with several leading PTSD-associated genes (e.g. ANAPC, FAM120A, SGCD ) having particularly great interactions with certain traumas. Several genes ( DTX4, PSMD12, TYW3, ZNF660 ) demonstrated consistently stronger interactions with all childhood or all adulthood traumas. Differences in gene-environment interactions across traumas were not explained by variation in exposure rates, associations with PTSD, or gene-environment correlations. Conclusions: Genetic influences on PTSD risk vary by trauma type and are most pronounced for childhood traumas. To account for the moderating role of trauma type, genetic research on PTSD should incorporate detailed trauma exposure information.

Gene-environment interactions are critical for understanding the genetics of PTSD, although it remains unclear how they differ across traumas. Using data from the UK Biobank and GLAD-EDGI-COPING (N=144,702), we conducted gene-environment interaction analyses incorporating eleven trauma measures. We analysed polygenic risk scores, specific genes, and specific genetic variants. Childhood traumas had stronger associations with PTSD symptoms and greater gene-environment interactions than adulthood traumas on average. Interaction patterns varied across genes and variants, with many of the leading genes for PTSD (e.g. ANAPC, FAM120A, SGCD) having particularly great interactions with certain traumas. Several genes (DTX4, PSMD12, TYW3, ZNF660) demonstrated stronger interactions with all childhood or all adulthood traumas. Our results suggest genetic influences on PTSD risk vary by trauma type and are most pronounced for childhood traumas. To accommodate the moderating effect of trauma type, genomic research on PTSD should incorporate trauma exposure information.

The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder and phobias) are highly prevalent, often onset early and cause substantial global disability. Although distinct in their clinical presentations, they probably 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 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 out of the 58 associations 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 implicated in ANX genetic risk. These results advance our understanding of the genetic architecture of ANX and prioritize genes for functional follow-up studies.

Importance: Major depressive disorder (MDD) is a complex psychiatric disorder influenced by genetic, social, and environmental factors. Family history, genome-wide polygenic scores, and childhood trauma are key predictors of MDD onset with distinct contributions. Objective: This study modelled the combined effects of family history of multiple psychiatric disorders, polygenic scores of multiple traits, and childhood trauma, alongside sociodemographic factors on MDD diagnosis and number of episodes. We aimed to build and externally validate predictive models for MDD risk and severity. Participants: We used data from the Genetic Links to Anxiety and Depression Study and other NIHR BioResource studies (GLAD+) and UK Biobank (UKB) collected between 2016 and 2023. Outcomes and measurements: MDD diagnosis followed DSM-5 criteria using online questionnaire data. Family history (Yes/No) was reported for up to 22 psychiatric disorders. Polygenic scores were calculated based on genome-wide association studies (n=22). Participants answered the five-item childhood trauma screener. We used elastic net regression with nested cross-validation to select the best predictors. Results: In GLAD+ (9,927 MDD cases, 4,452 controls), family history explained 17% of the MDD variance, followed by childhood trauma (11%), sociodemographics (10%), and polygenic scores (7%), resulting in 33% of the MDD variance (AUC-ROC=0.84). In UKB (40,667 MDD cases, 70,755 controls), family history explained 13% of the MDD variance, childhood trauma (7%), sociodemographics (6%), and polygenic scores (4%). Combined together, the predictors explained 23% of the variance (AUC-ROC=0.74). The top five individual predictors were family history of depression, childhood trauma, female sex, family history of anxiety, and the MDD polygenic score in both cohorts. The predictive models were externally well-validated across GLAD+ and UKB obtaining comparable predictive performance. Finally, when combined, the predictors explained 26% and 12% of the variance in the number of MDD episodes in GLAD+ and UKB respectively. Conclusions: Integrating family history, PRSs, ChT, and sociodemographic factors can predict risk of an MDD diagnosis and its recurrent course. This model may help identify individuals at high risk for depression in clinical settings, assess its severity, enable early diagnosis and potentially personalize treatment. ### Competing Interest Statement Prof Breen has received honoraria, research or conference grants and consulting fees from Illumina, Otsuka, and COMPASS Pathfinder Ltd. Prof Hotopf is the principal investigator of the RADAR-CNS consortium, an IMI public private partnership, and as such receives research funding from Janssen, UCB, Biogen, Lundbeck and MSD. Prof McIntosh has received research support from Eli Lilly, Janssen, and the Sackler Foundation, and has also received speaker fees from Illumina and Janssen. Prof Cleare has received honoraria for presentations from Janssen, Otsuka, COMPASS Pathways Plc., Viatris and Medscape, honoraria for consulting from Janssen, Otsuka and COMPASS Pathways Plc, research grant support from ADM Protexin Ltd and Beckley Psytech Ltd, and is President of the International Society for Affective Disorders (unpaid). Prof Zahn is a private psychiatrist service provider at The London Depression Institute, has collaborated with EMOTRA, EMIS PLC, Depsee Ltd, and Alloc Modulo Ltd. He has received honoraria from pharmaceutical companies (Lundbeck, Janssen) for scientific presentations and is a co-investigator on a Livanova-funded observational study of Vagus Nerve Stimulation for Depression. RZ is affiliated with the DOr Institute of Research and Education, Rio de Janeiro and advises the Scients Institute, USA. ### Funding Statement This work was supported by the National Institute for Health and Care Research (NIHR) BioResource [RG94028, RG85445], NIHR Biomedical Research Centre [IS-BRC-1215-20018], HSC R&D Division, Public Health Agency [COM/5516/18], MRC Mental Health Data Pathfinder Award (MC\_PC\_17,217), and the National Centre for Mental Health funding through Health and Care Research Wales. Johan Zvrskovec acknowledges funding from the National Institute for Health and Care Research (NIHR) Biomedical Research Centre and Guys and St Thomas NHS Foundation Trust. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The GLAD Study was approved by the London - Fulham Research Ethics Committee on 21st August 2018 (REC reference: 18/LO/1218) following a full review by the committee. The NIHR BioResource has been approved as a Research Tissue Bank by the East of England - Cambridge Central Committee (REC reference: 17/EE/0025). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Objective. Psychiatric conditions arise from a complex interplay of genetics and environment. Many people struggle to interpret genetic risk, leading to distress and inadequately informed decisions. Mental health professionals are often the first point of contact for patients with questions about psychiatric genetic risk. We aimed to uncover UK-based psychiatric professionals' knowledge and perceptions of psychiatric genetic risk, comparing those with and without a medical degree to identify training gaps. Methods. Healthcare professionals (n=152) were recruited via email and social media. An online survey assessed: 1) genetic knowledge using the 6-item International Genetic Literacy and Attitudes Survey (iGLAS), 2) confidence discussing genetic and environmental risk, 3) perceived contributions of genetic and environmental factors to psychiatric conditions, and 4) how often patients and relatives ask questions about genetic or environmental risk. We compared those with a medical degree (n=56) to those without (n=96) via linear regressions. Results. One-quarter indicated patients always or often asked about genetic risk for their psychiatric condition. Whilst participants' genetic knowledge was good (mean iGLAS score=4.36 out of 6), 10% believed at least one psychiatric condition was caused by only environmental or only genetic factors. Only 30% feel confident discussing genetic risk with patients and their relatives. Participants with a medical degree demonstrated significantly greater genetic knowledge (mean iGLAS score=5.02, SD=0.91) than those without (mean=3.97, SD=1.31; beta=1.05, 95% CI=0.64, 1.47, p<0.001), and were more confident discussing genetic risk (beta=0.60, 95% CI=0.20, 1.01, p=0.004), however this latter finding was non-significant after controlling for sex. Confidence discussing environmental risk was not linked to training background. Conclusions. Patients and their relatives are curious about genetic risk, yet professionals' confidence discussing this was low, especially among those without medical degrees. We highlight a specific training gap related to genetics and support calls for accessible psychiatric genetics education for mental health professionals. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement H.L.D was funded by the Economic Social Research Council. J.M was funded by the Lord Leverhulme Charitable Grant. G.B, T.C.E, M.R.D and E.V were funded by the National Institute for Health and Social Care Research (NIHR) Biomedical Research Centre (BRC) at the South London and Maudsley NHS Foundation Trust and King's College London. This paper represents independent research part-funded by the NIHR BRC. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2013. The PerPsych study was approved by the Psychiatry, Nursing, and Midwifery Research Ethics Subcommittee at King's College London on 24th June 2021 (HR/DP-20/21-22019). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes PerPsych study data are available via a data request application to the NIHR BioResource (https://bioresource.nihr.ac.uk/using-our-bioresource/academic-and-clinical-researchers/apply-for-bioresource-data/). The data are not publicly available due to restrictions outlined in the study protocol and specified to participants during the consent process.

Evidence-based psychological treatments for anxiety and depression are widely used, yet roughly half of those treated do not respond. Treatment response prediction could help to optimize patient outcomes and use of clinical resources. However, existing longitudinal studies with potentially valuable predictors are unlikely to include comprehensive, prospective measures of symptoms throughout therapy. Single-item patient ratings of helpfulness and improvement are a potentially cost-effective and efficient alternative, but their relationship with typically used change score measures is unknown. Data were analyzed from 135 participants (124 female sex; 120 female gender; 127 White) who received cognitive-behavioral therapy. Anxiety symptoms (Generalized Anxiety Disorder-7), depression symptoms (Patient Health Questionnaire-9), and impairment (Work and Social Adjustment Scale) questionnaire scores were obtained before therapy (assessment), before each session, and 1-month posttreatment (follow-up). Helpfulness (binary) and improvement (continuous) ratings were collected at follow-up. Linear regression models assessed the relationship between helpfulness and improvement ratings and questionnaire change scores from the first to the last session. Logistic regressions modeled the relationships between single-item measures and National Health Service Talking Therapies outcomes, derived from questionnaire change scores. Helpfulness and improvement showed significant associations with questionnaire change scores as well as National Health Service Talking Therapies outcomes. In a joint model, improvement retained significant associations while helpfulness became nonsignificant. Improvement, and to a lesser extent helpfulness, patient ratings may be a cost-effective alternative for establishing treatment efficacy and outcome. The items' wording and response scales may underlie observed differences. While not equivalent to change score-based measures, they may be adequate for studies requiring large sample sizes. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

We performed a genome-wide association meta-analysis of generalised anxiety symptom severity in 696,563 individuals of European ancestry from 14 cohorts. We identified 82 independent genome-wide significant variants within 76 loci, 41 of which were novel for anxiety. SNP-based heritability was 5.9% (SE = 0.19%). Polygenic scores were significantly associated with anxiety symptom severity and disorder in European, African, and South Asian ancestry samples (r2=1.2%-3.4%). Significant genetic correlations were estimated with numerous mental and physical health traits, including case-control anxiety, neuroticism and depression (rg=0.71-0.86), irritable bowel syndrome (rg=0.57), coronary artery disease, endometriosis, and migraine (rg=0.20-0.27). Gene-based and pathway analyses implicated synaptic and axonal processes, with enriched expression in the brain. These findings highlight the additional value of a dimensional approach in anxiety genetics.

Adolescent depression is a heritable psychiatric condition with rising global prevalence and severe long-term outcomes, yet its biological underpinnings remain poorly understood. We conducted the first genome-wide association study of adolescent-onset depression, comprising 102,428 cases (diagnosis or clinical symptom thresholds) and 286,911 controls, including diverse ancestries. Cross-ancestry meta-analysis identified 52 independent variants across 17 loci; European-only analysis found 61 variants at 29 loci, with a SNP-based heritability of 9.8%. Comparative analyses revealed two genes unique to adolescent-onset versus lifetime depression, enriched in neuronal subtypes, and two genes as potential drug repurposing targets. Polygenic scores were associated with adolescent-onset depression across ancestries, persistent depression trajectories, more severe outcomes, as well as reduced cortical volume, surface area and white matter integrity. Genetic correlation and Mendelian randomisation analyses support shared genetic liability and causal links with early puberty and modifiable health and behavioural risk factors. These findings uncover novel genetic loci and refine biological pathways underlying adolescent-onset depression, revealing age-specific mechanisms and early intervention opportunities.

Despite the widespread use of cognitive-behavioural therapy (CBT), only about half of patients respond favourably. Understanding whether relevant psychological processes are associated with treatment response could help identify patients at risk of non-response prior to treatment and improve their outcomes by enabling clinicians to tailor interventions accordingly. Fear conditioning tasks are a valuable tool for studying the learning processes associated with anxiety disorders and their treatment. This study examined associations between outcomes from a remote fear conditioning task and responses to internet-based CBT. Anxious adults (n=112) completed a fear conditioning task before receiving internet-based CBT. Participants rated their expectancy of an aversive noise (unconditioned stimulus; US) in response to a reinforced conditional stimulus (CS+) and a nonreinforced conditional stimulus (CS-) during acquisition, followed by extinction where neither stimulus was reinforced. Anxiety symptoms were assessed before each CBT session. Linear regression models indicated no significant association between mean US-expectancy ratings for 'safe' stimuli (acquisition CS- and extinction CS+) and change in anxiety across treatment. These findings contribute to the mixed literature on fear conditioning's role in treatment outcomes, highlighting the need for further research to elucidate the complex interplay between fear conditioning processes and response to CBT in anxiety disorders.

The population prediction of polygenic scores (PGS) was found to capture two distinct processes: within-family prediction (individual-specific genetic differences between family members, such as siblings) and between-family prediction (family-level genetic differences, including assortative mating and ancestry). We quantify between-family prediction as the extent to which population prediction exceeds within-family prediction. While between-family prediction was found to be substantial for cognitive traits, its magnitude for psychopathology remains underexplored. Using 3300 unrelated individuals and 1600 dizygotic twin pairs at age 26 in the UK-based Twins Early Development Study, we examined within-family and population-level PGS prediction for eight psychopathologies, assessed as dimensions and diagnoses. Despite limited statistical power, within-family prediction is broadly comparable to population prediction, accounting for 72.4% of population estimates for dimensions and 78.0% for diagnoses. Only anxiety dimensions showed a significant prediction difference, suggesting some between-family contributions. We conclude that, overall, population PGS for psychopathology primarily reflect within-family genetic effects.

BACKGROUND:This paper introduces the UK Biobank (UKB) second mental health questionnaire (MHQ2), describes its design, the respondents and some notable findings. UKB is a large cohort study with over 500,000 volunteer participants aged 40-69 years when recruited in 2006-2010. It is an important resource of extensive health, genetic and biomarker data. Enhancements to UKB enrich the data available. MHQ2 is an enhancement designed to enable and facilitate research with psychosocial and mental health aspects. METHODS:UKB sent participants a link to MHQ2 by email in October-November 2022. The MHQ2 was designed by a multi-institutional consortium to build on MHQ1. It characterises lifetime depression further, adds data on panic disorder and eating disorders, repeats 'current' mental health measures and updates information about social circumstances. It includes established measures, such as the PHQ-9 for current depression and CIDI-SF for lifetime panic, as well as bespoke questions. Algorithms and R code were developed to facilitate analysis. RESULTS:At the time of analysis, MHQ2 results were available for 169,253 UKB participants, of whom 111,275 had also completed the earlier MHQ1. Characteristics of respondents and the whole UKB cohort are compared. The major phenotypes are lifetime: depression (18%); panic disorder (4.0%); a specific eating disorder (2.8%); and bipolar affective disorder I (0.4%). All mental disorders are found less with older age and also seem to be related to selected social factors. In those participants who answered both MHQ1 (2016) and MHQ2 (2022), current mental health measure showed that fewer respondents have harmful alcohol use than in 2016 (relative risk 0.84), but current depression (RR 1.07) and anxiety (RR 0.98) have not fallen, as might have been expected given the relationship with age. We also compare lifetime concepts for test-retest reliability. CONCLUSIONS:There are some drawbacks to UKB due to its lack of population representativeness, but where the research question does not depend on this, it offers exceptional resources that any researcher can apply to access. This paper has just scratched the surface of the results from MHQ2 and how this can be combined with other tranches of UKB data, but we predict it will enable many future discoveries about mental health and health in general.

A combination of genetic and environmental factors working in interplay is thought to underlie differences in symptoms of psychopathology between adolescents. Yet, studies that have investigated gene-environment interaction in isolated aspects of developmental psychopathology lack robust effects, highlighting the need for a more comprehensive approach. We adopted a multivariable framework to investigate gene-environment interaction in internalising and externalising symptoms of psychopathology in a sample of 3,337 16-year-olds from the Twins Early Development Study. We used penalised regression models to examine the main effects of genetic factors (G), indexed by combining 13 polygenic scores for psychopathology, and environmental factors (E), measured by combining multiple environmental exposures during childhood and adolescence, on symptoms of psychopathology. We also examined their additive effects (G+E) and their interaction (G × E). Polygenic scores accounted for, on average, 2.7% of the variance in symptoms of psychopathology, with stronger predictions for externalising symptoms, while environmental measures alone accounted for an average of 7.1% of the variance. G+E accounted for an average of 9.1% of differences between adolescents in symptoms of psychopathology. We observed small G × E effects for internalising symptoms, accounting for an average of 1.1% of the variance. Children with a higher genetic risk showed higher levels of internalising symptoms, especially when exposed to more chaos at home and harsher parenting. A number of the detected interactions between the polygenic scores and environmental measures also exhibited significant indirect effects in genetic correlation analyses, highlighting the need to interpret G × E findings considering gene-environment correlation. Overall, our findings indicate that genetic and environmental influences contribute additively, underscoring the importance of jointly considering both factors to enhance our understanding of youth psychopathology. At the same time, our results highlight the persistent challenges involved in identifying robust G × E effects.Disclosure: Nothing to disclose.

Background Functional impairment in daily activities, such as work and socialising, is part of the diagnostic criteria for major depressive disorder (MDD) and most anxiety disorders. Despite evidence that symptom severity and functional impairment are partially distinct, functional impairment is often overlooked. To assess whether functional impairment captures diagnostically relevant genetic liability beyond that of symptoms, we aimed to estimate the heritability of, and genetic correlations between, key measures of current depression symptoms, anxiety symptoms and functional impairment. Methods In 17,130 individuals with lifetime depression or anxiety from the Genetic Links to Anxiety and Depression (GLAD) Study, we analysed total scores from the Patient Health Questionnaire-9 (PHQ-9; depression symptoms), Generalised Anxiety Disorder-7 (GAD-7; anxiety symptoms), and Work and Social Adjustment Scale (WSAS; functional impairment). Genome-wide association analyses were performed with REGENIE. Heritability was estimated using GCTA-GREML and genetic correlations with bivariate-GREML. Results Phenotypic correlations were moderate across the three measures (Pearson’s r = 0.50 - 0.69). All three scales were found to be under low but significant genetic influence (h2SNP = 0.11 - 0.19) with high genetic correlations between them (rg = 0.79 - 0.87). Conclusions Among individuals with lifetime depression or anxiety, the genetic variants that underlie symptom severity largely overlap with those influencing functional impairment. This suggests that self-reported functional impairment, while clinically relevant for diagnosis and treatment outcomes, does not reflect substantial additional genetic liability beyond that captured by symptom-based measures of depression or anxiety.

Peer problems in childhood and adolescence are associated with anxiety and depression in emerging adulthood. However, it remains unclear whether prosocial behaviours reduce this risk and whether these associations remain after adjusting for familial factors, including genetics. The present study examined how the development of peer problems and prosocial behaviours across childhood and adolescence were associated with anxiety and depression in emerging adulthood, and whether these associations remained when using a monozygotic twin difference design. The study included up to 31,016 participants (50.4 % female) from the Twins Early Development Study (TEDS; N = 19,758) and the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 11,258), with sample sizes varying across analyses based on data availability. Repeated data were collected from ages 4 to 26/28 (TEDS/ALSPAC). Results from latent growth curve and path analyses showed that higher initial levels of peer problems and prosocial behaviours in childhood, as well as more persistent peer problems and prosocial behaviours during childhood, increased risk for anxiety and depression in emerging adulthood. Associations with peer problems remained significant after adjusting for familial factors using monozygotic twin difference scores, suggesting that individual-specific experiences, like children's responses to peer problems, may explain why peer problems increase risk for later anxiety and depression. In contrast, associations with prosocial behaviours did not remain significant after adjusting for familial factors, indicating that whilst prosocial behaviours in childhood were associated with higher levels of anxiety and depression in emerging adulthood, this was largely explained by genetic or environmental factors shared within the family.