American Journal of Medical Genetics Part B: Neuropsychiatric Genetics

Obsessive compulsive disorder (OCD) is significantly heritable, but only a fraction of the contributory genetic variation has been identified, and the molecular etiology involved remains obscure. Identifying rare contributory variants of large effect would be an important milestone in helping to elucidate the mechanisms involved. Analysis of densely affected pedigrees is a potentially useful strategy to bypass the sample size challenges of standard case-control approaches. Here we performed whole genome sequencing (WGS) of 25 individuals across two multiplex OCD pedigrees. We prioritised rare variants using a Bayesian inference approach which incorporates variant pathogenicity and co-segregation with OCD. In the first pedigree, we identified a highly deleterious missense variant in NPY5R, carried by the majority of affected individuals. This gene is brain-expressed and has previously been implicated in panic disorder and internet addiction GWAS studies. In the second pedigree, we identified a large deletion of DLGAP1 and a missense variant in MAPK8IP3, that perfectly co-segregated in a specific branch of the family: both genes have previously been implicated in OCD and autism. Both genes contribute to a protein interaction network including ERBB4 and RAPGEF1 which we had previously identified in a large Tourette Syndrome pedigree. Our analysis suggests that both energy homeostasis and downstream signalling from the post-synaptic density may both be important avenues for future research.

Abstract Background Gene dosage disorders impact cognition and psychopathology, but outcomes vary widely amongst carriers of the same variant. Recent work has sought to better predict proband outcomes using measures of corresponding traits in family members. However, family-based models have not yet been prospectively quantified across several traits in different genetic disorders, nor evaluated for the precision they afford: both crucial issues for clinical implementation. Methods In a first test case for these questions, we apply regression analyses to quantify and compare family-based prediction of 12 traits (including IQ, autism- and ADHD-related traits) in 433 individuals from families including a proband with XXY or XYY syndrome (N=93 and 58, respectively). Results The 12 traits vary substantially in their proband-family associations (0.001<|r|<0.55) - with differences emerging between XXY and XYY syndrome. Only two traits also show significant and similar proband-family associations in both aneuploidies, with the greatest concordance found for IQ. A family-based model for IQ prediction in male sex chromosome trisomies significantly reduces error vs. a group mean IQ model (F = 7.4, p = 0.006), but only in 65% of probands, and with mean error reduction of ~2 IQ points. Conclusions Family-based prediction of neuropsychiatric traits in genetic syndromes likely requires trait- and syndrome- specific models. Family models can significantly improve outcome prediction for IQ, but to variable degrees across individuals and with a small mean improvement. By mapping and quantifying these limits, our work helps draft a roadmap for refinement of family-based prediction of proband outcomes in gene dosage disorders.

BackgroundCognitive-behavioral therapy (CBT) is a widely used treatment for mental disorders, yet the biological mechanisms underlying its effects, and the factors contributing to response, remain poorly understood. DNA methylation, an epigenetic mechanism shaped by both genetic and environmental factors, may offer insights into individual differences in psychotherapy outcomes. MethodsSaliva samples were collected before treatment, after treatment, and three months post-treatment from individuals with OCD undergoing the Bergen 4-Day Treatment (n = 889). DNA methylation was measured using the Illumina EPIC v02 array, followed by epigenome-wide DNA methylation analyses of CBT response. ResultsWe identified ten differentially methylated regions (DMRs) associated with treatment response at baseline, 23 DMRs showing consistent associations with response across multiple time points, and three DMRs displaying longitudinal methylation changes associated with response. These loci were annotated to genes with roles in neuroplasticity, stress response, immune function, mitochondrial processes, and gene regulation. Baseline and stable methylation signals were largely influenced by genetic variation, whereas all longitudinal associations appeared to be confounded by psychoactive medication use and psychiatric comorbidities. In addition, changes in monocyte and CD4+T cell proportions were associated with treatment response. ConclusionsWe identified DNA methylation markers associated with CBT response in OCD at baseline. Stable methylation patterns associated with treatment response are likely driven by genetic factors. Longitudinal methylation analyses should be interpreted cautiously, as medication and comorbidities can exert substantial effects - even when they remain unchanged over time. Baseline methylation profiles may ultimately help predict treatment outcomes, thereby advancing precision psychiatry.

Hoarding disorder (HD) affects approximately 2-3% of adults and is associated with substantial functional disability and limited access to evidence-based care. The aim of the current analysis was to examine the naturalistic effectiveness of therapist-delivered video cognitive-behavioral therapy (CBT) for HD in a large real-world sample, and to characterize individual-level treatment response, time-to-response, and moderators of outcome. This retrospective, observational analysis examined clinical data from 305 adults diagnosed with HD who received therapist-delivered video CBT through an online specialty therapy platform between September 2021 and February 2026. Hoarding symptom severity was assessed using the Hoarding Rating Scale-Self Report (HRS-SR). Linear mixed models examined symptom change from baseline to three timepoints: session 10, session 20, and each patient's final session. HRS-SR scores decreased from M = 22.4 (SD = 7.6) at baseline to M = 16.4 (SD = 8.2) at final session (Hedges' g = 0.81, 95% CI: 0.68-0.94). By the final session, median percent improvement was 25.0% [IQR: 3.0-46.7%]. A total of 39.3% of patients achieved [&ge;]35% HRS-SR reduction, 27.4% of patients who began above the clinical threshold achieved remission, 36.4% demonstrated reliable improvement, and 22.9% of eligible patients achieved clinically significant change. Among patients who achieved and maintained [&ge;]35% reduction through their final session (n = 120), median time to first response was session 9, with 54.2% responding within 10 sessions. Analyses of secondary outcomes showed significant improvements in clutter severity, depressive and anxiety symptoms, stress, quality of life, and functional disability (Hedges' g = 0.21-0.47). Greater baseline severity, more sessions, and longer treatment duration significantly moderated outcomes; prior OCD treatment history did not. Findings suggest that therapist-delivered video CBT for HD, delivered remotely in a real-world setting, produces outcomes consistent with controlled trials and may be a clinically effective and scalable approach for a condition historically underserved by mental health systems.

ObjectiveTo characterize the familial patterns of misophonia and other commonly co-occurring neuropsychiatric conditions. MethodsWe examined cross-sectional survey responses from 101 probands with misophonia and their biological parents enrolled in a genetics study. ResultsProbands had a mean age of 24.6 {+/-} 11.6 years (8-64 years), were predominantly female (88%), and had high rates of co-occurring neuropsychiatric conditions, including anxiety (70%), depression (38%), ADHD (31%), and OCD (25%). Among probands, 39% had a first-degree relative with misophonia, and 48% had at least one any-degree relative with misophonia. In addition, many probands had at least one first-degree relative with anxiety (65%), depression (57%), ADHD (40%), OCD (20%), and autism (13%). Comparing rates of neuropsychiatric conditions reported by parents, mothers had significantly higher rates of misophonia (29% maternal vs. 9% paternal, p = 0.001) and anxiety (44% maternal vs. 26% paternal, p = 0.02) than fathers. ConclusionThese findings provide new insight into the familial patterns of misophonia and co-occurring neuropsychiatric conditions. Future research on underlying genetic and environmental factors is needed to shed light on the observed shared predispositions for misophonia and other neuropsychiatric conditions in families.

ObjectiveObsessive-compulsive disorder (OCD) frequently co-occurs with bipolar disorder (BD) or schizophrenia (SCZ), and, importantly, can often precede their onset. However, the genetic architecture and directionality underlying these relationships remain unclear. We leveraged large-scale genome-wide association study (GWAS) data to examine shared genetic architecture and directional relationships among OCD, BD and SCZ, and used major depressive disorder (MDD) as a comparator. MethodsUsing linkage disequilibrium score regression (LDSC), MiXeR, and Generalized Summary-data-based Mendelian Randomization (GSMR) as well as complementary Mendelian randomization approaches, we characterized genetic correlations, polygenic overlap (Dice coefficient), and effect direction concordance ({rho}{beta}) across disorders. ResultsWe observed substantial genetic correlations between OCD and BD (rg=0.37), BD type 2 (BD2) (rg=0.54), and SCZ (rg=0.39), with a large proportion of shared causal variants between OCD and both BD (Dice=0.85) and SCZ (Dice=0.84). MiXeR analyses indicated that OCD and BD2 share a smaller proportion of causal variants (Dice=0.57) but there is a high concordance of effect directions amongst these causal variants ({rho}{beta}=0.96), whereas OCD and MDD showed minimal overlap but strong concordance among shared variants (Dice=0.09, {rho}{beta}=1). Directional GSMR and complementary TwoSampleMR analyses supported a causal effect of genetic risk to OCD on liability to BD (b=0.20, p=1.5x10{square}{square}), SCZ (b=0.52, p=9.5x10{square}{superscript 2}{superscript 1}), and MDD (b=0.24, p=1.06x10{square}{square}), with little evidence for reverse causal effects. ConclusionsTogether, these findings indicate that genetic liability to OCD can represent an early component of transdiagnostic psychiatric risk, with implications for understanding and potentially predicting the emergence of broader psychopathology across the life course.

Meiotic recombination is an important means of increasing genetic diversity by generating novel haplotypes in a population. Recombination separates linked loci extremely slowly in some regions, therefore genetic variants in high linkage disequilibrium may become co-adapted. Reciprocal recombination that separates co-adapted variants may generate a deleterious de novo haplotype that contributes to disease. We developed statistical methods to detect genomic regions of recombination excess in two different family-based study designs. We identified recombination in the Simons Simplex Collection in 273 simplex families with one child with autism spectrum disorder (ASD) and at least two unaffected children, in which recombinations can be mapped to the proband and contrasted with the recombination counts in unaffected siblings; and in 1,802 families with two children, where the number of recombinations identified can be contrasted with the expectation from a reference recombination map. Both strategies revealed a tail of low p-values for loci of interest that contrasted with the rest of the distribution. Permutation and bootstrap tests did not identify genome-wide primary findings in either cohort, but the most significant three-child cohort locus of recombination excess (between cadherin genes CDH4 and CDH26) replicated in the two-child cohort (p=0.01). While this replication strategy was not defined a priori, five of the most recombination enriched bins identified candidate ASD genes (p=0.02; WWOX, ADAMTS16, INSR, ADARB2, and HS6ST1). Since the six identified loci were not identified as regions of high de novo copy number variation in the study cohort and no CNVs were detected in any of the recombinant probands in the identified regions, they represent candidates for reciprocal recombinations generating unfavourable haplotypes for these genes. This study highlights a previously unidentified source of clinical genetic variability contributing to the molecular aetiology of ASD. AUTHOR SUMMARYAutism spectrum disorder (ASD) is a constellation of neurodevelopmental disabilities characterised by deficits in social communication and repetitive patterns of behaviour. While ASD is highly heritable, its genetic basis is complex and poorly understood. While some highly penetrant types of genetic variation have been identified, most people with ASD carry a large number of variants that each contribute a small amount to their overall phenotype. In addition to mutations in individual genes, changes in the configuration of genes along a chromosome may contribute to ASD. Here, we describe a method for identifying regions where such new configurations have occurred through recombination and attempt to find regions where such changes are more common in autistic children than in their non-autistic siblings. We explore recombination as a source of genetic variation contributing to autism, which has potential to inform clinicians in providing services to autistic people and their families.

Background Major Depressive Disorder (MDD) is clinically and biologically heterogeneous. Here, we leveraged the genetics of individual depressive symptoms to dissect the disorder's underlying heterogeneity. Methods We utilized the BIObanks Netherlands Internet Collaboration (BIONIC). A series of genome-wide association studies (effective-N range: 14,407-47,110) compared controls (N=48,286) with partially different subsets of lifetime MDD cases (range: 3,892-15,577), each endorsing one of 12 individual DSM-based depressive symptoms. Results were combined in genetic correlations that informed factor analyses with Genomic Structural Equation Modeling, decomposing underlying MDD liability dimensions. The identified factors were assessed and further characterized using multivariate regression of neurodevelopmental/psychiatric and cardiometabolic traits. Results All symptoms demonstrated substantial SNP-based heritability (h2SNP:0.088-0.127). Despite high between-symptom genetic correlations, factor analyses yielded two highly correlated (rg=0.85) but still distinct latent factors: factor 1 (F1), capturing appetite/weight loss, insomnia, guilt/worthlessness, psychomotor slowing and suicidality, and factor 2 (F2), reflecting concentration problems, anhedonia, depressed mood, appetite/weight gain and fatigue. Overall, F1 had a stronger genetic overlap with neurodevelopmental/psychiatric phenotypes (e.g., autism: standardized estimate {beta}=0.45, p=4.49 x10-; schizophrenia: {beta}=0.40, p=1.73x10-), while F2 significantly overlapped with cardiometabolic traits (e.g., metabolic syndrome: {beta}=0.44, p=8.69x10-; coronary artery disease: {beta}=0.31, p=0.009). Conclusions We identified two genetic dimensions of MDD, each linked to partially distinct clinical manifestations and underlying biology, with one reflecting neurodevelopmental/psychiatric liabilities and the other capturing a strong cardiometabolic vulnerability. Disentangling such distinct dimensions may help guide patient stratification and targeted treatment, thereby advancing precision psychiatry.

Background: Bipolar disorder (BD) is increasingly conceptualized as a heterogeneous condition with a neurodevelopmental phenotype (NDP) identifying a subgroup with early neurodevelopmental vulnerability and poorer clinical outcomes. Sensory processing (SP) abnormalities are a core feature of neurodevelopmental disorders but remain poorly characterized in BD and may reflect underlying neurodevelopmental liability. We examined whether NDP load is associated with specific SP alterations in euthymic BD patients and whether NDP-based stratification explains SP variability better than conventional BD subtype (BD 1/2). Methods: We assessed 102 euthymic BD patients and 45 healthy controls (HC) using the Adolescent/Adult Sensory Profile (AASP). NDP load (0-3) was computed from nine clinical variables grouped into neonatal, comorbidity, and neurodevelopmental clusters; a median split defined BD without NDP (BD) and BD with NDP (BD-ND). Associations between NDP load and AASP quadrants were analyzed using Spearman correlations with FDR correction. Group differences (BD, BD-ND, HC) were assessed using Welch ANOVA and post-hoc tests. Nested and multivariable linear regressions examined whether NDP classification explained SP variance beyond BD subtype, adjusting for age, sex, anxiety, and residual mood symptoms. Results: Higher NDP load correlated with greater low registration (rho=0.35, p<0.001, q=0.004), sensory sensitivity (rho=0.30, p=0.001, q=0.004), and sensation avoiding (rho=0.23, p=0.014, q=0.040), but not sensation seeking. BD-ND showed higher low registration, sensory sensitivity, and sensation avoiding than BD and HC (all qs<0.01). NDP classification explained more SP variance than BD subtype; with robust associations after adjustment. Conclusions: Sensory processing alterations in BD are dimensionally associated with neurodevelopmental load and more accurately captured by NDP-based stratification than diagnostic subtype. SP alterations may represent a transdiagnostic marker of neurodevelopmental liability within BD, supporting biologically informed stratification approaches.

Attention-deficit/hyperactivity disorder (ADHD) is associated with impairments in sustained attention and inhibitory control. Neurofeedback (NFB) is a widely used non-pharmacological treatment for ADHD and is generally well tolerated, but evidence for its efficacy remains mixed. Here we report results from secondary analysis of a randomized controlled trial of NFB training for adult ADHD, analysing behaviour and neural data from attention testing in both test-retest and treatment-vs-waiting list control group contrasts. We used electroencephalography (EEG) to investigate event-related cortical dynamics during the Test of Variables of Attention (TOVA), administered before and after NFB treatment. 44 adults with ADHD (NFB treatment, ADHD-T: n = 23; waitlist control, ADHD-W: n = 21) completed the TOVA before and after the NFB training period, while 128-channel EEG was recorded. Treatment-related change was examined through analyses based on behavioural TOVA performance, power spectral density, and event-related potentials, analysed with Bayesian linear mixed models. We found no meaningful evidence for NFB-specific improvements in TOVA behavioural performance over time, and no evidence that NFB modulated ERP or spectral indices relative to the ADHD-W group. Overall, we found no evidence that NFB treatment meaningfully benefited sustained attention or inhibitory control in adults with ADHD.

Suicidal ideation in obsessive-compulsive disorder (OCD) is common and clinically significant, yet much of the existing literature conceptualizes suicide risk through the lens of comorbid depressive symptomatology. The present study examined whether other clinical features can identify clinically meaningful patterns associated with SI. Participants included 231 individuals with clinically significant OCD symptoms. SI was operationalized using Item 9 of the Beck Depression Inventory-II and binarized to reflect the presence or absence of suicidal thoughts. Depression severity scores were intentionally excluded from the predictive feature set, and three machine learning models (ElasticNet, Random Forest, and Explainable Boosting Machines) were evaluated using repeated nested cross-validation. All three algorithms showed comparable predictive performance. Given this overlap, the EBM was selected for interpretation due to its ability to model nonlinear relationships and interaction effects transparently. The model identified quality of life, obsessive-compulsive trait severity, somatic burden, and conscientiousness as prominent predictors of SI. Risk functions suggested nonlinear increases in estimated suicide risk at elevated levels of obsessive-compulsive traits and reduced quality of life. Additionally, interaction analyses indicated that severe obsessive-compulsive traits combined with elevated somatic burden were associated with higher estimated suicide risk than either factor alone. These findings suggest that interpretable machine learning can support clinically relevant phenotypic hypothesis generation. They also highlight somatic burden, functional impairment, obsessive-compulsive trait severity, and conscientiousness as potentially underappreciated targets for SI risk assessment in OCD, beyond the traditional focus on depressive comorbidity.

Polygenic risk scores (PRS) have shown increasing utility for risk stratification across complex diseases, but for psychiatric disorders such as bipolar disorder (BD), current PRS explain only a fraction of disorder liability (~1-9%), with predictive performance further diminished in non-European populations and real-world clinical cohorts. To explore the potential of integrating social and environmental risk factors alongside genetic liability to improve risk prediction, we evaluated the relationship between a PRS for BD (PRSBD) and six social risk measures - perceived stress, discrimination in medical settings, neighborhood social cohesion, perceived neighborhood disorder, cost-related medication nonadherence, and adverse childhood experiences - to BD case status in 115,275 participants (7,000 cases; 108,275 controls) from the All of Us Research Program. PRSBD was associated with BD case status across ancestry groups, though liability-scale variance explained was attenuated relative to what has been reported for curated research cohorts (R2 = 1.86% in European, 0.60% in African, 1.65% in Latino/Admixed American ancestries). Each social risk factor tested exhibited a larger effect size than PRSBD, with perceived stress (OR = 2.05 per SD) and adverse childhood experiences (OR = 2.68 for [&ge;]4 ACEs) demonstrating the strongest associations. Individuals in the lowest genetic risk decile with high social burden exhibited BD prevalence comparable to or exceeding those in the highest genetic risk decile with low social burden. These findings demonstrate the substantial explanatory power of social risk factors and support the development of integrated genetic-social risk frameworks for more accurate and equitable psychiatric risk prediction.

ObjectiveCognitive behavioral therapy (CBT) is an effective first-line treatment for obsessive-compulsive disorder (OCD), yet it remains difficult to predict who will respond to this intervention. This study investigates associations between neural activity during inhibitory control tasks and CBT outcomes, and whether task-based fMRI data could serve as a predictive marker of individual CBT response. MethodsUsing fMRI data from individuals performing an inhibitory control task across five samples (n=130, age range=8-57, 54% female) of the ENIGMA-OCD consortium, univariate associations were analyzed between activity during response inhibition and error processing and three CBT outcomes: response, remission, and pre-post treatment change in symptom severity. Random forest and support vector machine models using leave-one-sample-out cross-validation were used for prediction of CBT response and remission from fMRI activity and clinical data. ResultsRemission after CBT was associated with weaker activity in default mode regions during response inhibition and in the right supramarginal gyrus during error processing. Greater symptom reduction was linked to weaker pre-treatment activity across frontoparietal, dorsal attention, visual, and subcortical regions during response inhibition, but to stronger default mode activity during error processing. Despite these robust group-level effects, machine learning models failed to predict individual outcomes above chance level with either neuroimaging or clinical data. ConclusionWeaker activity during response inhibition in a widespread network, as well as stronger activity in default mode regions during error processing before treatment, appear beneficial to CBT response. However, these findings cannot yet be translated into individually predictive markers of CBT outcome.

Alternative-splicing events (ASE) increase transcriptomic variability and play key roles in biological functions. The contribution of ASE to bipolar disorder (BD) remains largely unexplored. We performed a Transcriptome-Wide Alternative-Splicing Analysis (TWASA) to identify ASEs and genes potentially involved in BD. The study comprised 635 individuals: a discovery sample (DS) of 31 individuals from eight multiplex BD families (16 BD cases; 15 unaffected relatives), and a replication sample (RS) of 604 subjects (372 BD cases; 232 controls). Sequencing was conducted on RNA from lymphoblastoid cell lines (DS) and whole blood (RS). TWASA was performed using VAST-TOOLS (VT), rMATS (RM), and MAJIQ/MOCCASIN (MCC). Gene-set association analyses of genes containing ASEs were performed across six psychiatric disorders. Novel ASE (nASE) were investigated in the DS using FRASER. Limited gene overlap was observed across TWASA tools. MCC identified 2,031 complex ASEs involving 1,508 genes, showing the strongest genetic association with BD across psychiatric phenotypes. Prioritization of MCC-identified ASE genes yielded 441 candidates, including DOCK2 as top candidate from the DS. Replication was obtained for 98 genes, five with an identical ASE, and four (RBM26, QKI, ANKRD36, and TATDN2) showing a concordant percentage-spliced-in direction with the DS. Finally, 578 nASE were identified in the DS, with no evidence of familial segregation or differences in ASE types. This first TWASA in BD reveals tool-specific variability, complex ASE for genes specifically associated with BD, and novel candidate genes for BD. Alternative transcript isoform abundance may represent a mechanism contributing to BD pathophysiology.

Adult ADHD is increasingly recognized across the lifespan, yet the psychometric equivalence of the Adult ADHD Self-Report Scale (ASRS) remains unverified for older populations. This study examined age-related Differential Item Functioning (DIF) in 600 adults (n = 100 per decade, ages 20-80) who completed the 18-item ASRS. Using a bi-factor Graded Response Model, we extracted latent ADHD trait scores ({omega}H = .895) and assessed DIF via ordinal logistic regression with adaptive age modeling. Five of 18 items exhibited significant uniform DIF. At equivalent latent severity, older adults were less likely to endorse hyperactivity symptoms in Part A (fidgeting, feeling "driven by a motor") but more likely to endorse specific symptoms in Part B (careless mistakes, misplacing items, interrupting). From ages 20 to 80, expected Part A scores decreased by 1.36 points (~0.27 per decade), while Part B scores increased by 1.15 points (~0.23 per decade). These findings indicate a phenotypic redistribution of ADHD symptoms as individuals age. Because the 6-item Part A screener serves as the primary clinical gatekeeper, its concentration of negative DIF suggests standard screening practice may systematically underestimate ADHD severity in older adults. We recommend using the full 18-item ASRS when screening older populations and suggest that developing age-adjusted norms would improve diagnostic accuracy.

Pediatric bipolar disorder is challenging to diagnose accurately due to symptom heterogeneity. More standardized and data-driven approaches are needed to enhance diagnostic reliability. We evaluated a clinical decision tool (nomogram), statistical methods (logistic regression, LASSO), machine learning (support vector machine, random forest, k-nearest neighbors, extreme gradient boosting), and deep learning model (multilayer perceptron) for pediatric bipolar disorder prediction across two datasets collected in academic (N=550) and community (N=511) clinical settings. We compared three modeling strategies: cross-dataset validation, cross-dataset with interaction terms, and mixed-dataset. We assessed model performance using discrimination ability, calibration, and predictor importance ranking. In the baseline cross-dataset approach, all models showed good internal discrimination in the academic dataset; but external discrimination in the community dataset substantially declined. Interaction-enhanced models slightly improved internal discrimination but not external performance or calibration. Recalibration prominently improved cross-dataset calibration without compromising discrimination, indicating that transportability problems were largely driven by probability scaling. Models trained on mixed datasets exhibited much stronger external discrimination and calibration. Across models and training strategies, family risk and PGBI-10M were consistently ranked as the most important predictors. Predictive models for pediatric bipolar disorder showed strong internal performance but limited cross-setting generalizability due to dataset shift and miscalibration. Increasing model complexity did not improve external performance, whereas training on pooled data substantially improved both discrimination and calibration. Findings suggest that sampling diversity, rather than model complexity, is more valuable for developing clinically useful and generalizable psychiatric prediction models, underscoring the importance of open and collaborative datasets.

ImportanceEating disorders (EDs) are heritable, yet the developmental pathways through which genetic liability manifests in early life remain unclear. ObjectiveTo investigate the associations between genetic liability for anorexia nervosa (AN) and binge eating (BE) and disordered eating behaviors (DEB) across childhood, and to identify the mediating roles of metabolic and psychosocial traits. Design, Setting, and ParticipantsThis longitudinal observational study used genomic and behavioral data from the Adolescent Brain Cognitive Development SM (ABCD(R)) Study, a multisite, population-based cohort of children recruited between 2016 and 2018 at ages 9 to 10 years from 21 research centers across the United States. A three-wave temporal design was employed, utilizing data from baseline (T0), Year 1 (T1), and Year 2 (T2) follow-ups. Primary analyses focused on 5,618 participants of genetically inferred European (EUR) ancestry, with exploratory analyses conducted in a diverse sample of 9,132 participants. ExposuresPolygenic scores (PGS) for AN and BE were calculated using summary statistics from the most recent genome-wide association studies. Mediators included BMI, ADHD, anxiety/depression, and social problems from the Child Behavioral Checklist assessed at Year 1 follow-up (T1). Main Outcomes and MeasuresParent reported DEB symptoms via the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS). For longitudinal association analyses, DEB were pooled across T0, T1 and T2 to assess the relationship between genetic liability and childhood symptom severity. For mediation analyses, DEB at T2 follow-up were used to ensure a clear temporal sequence between mediators at T1 and the outcomes. ResultsAmong 5,618 EUR participants (mean [SD] age, 9.91 [0.62] years; 47% female), longitudinal association models revealed that higher AN-PGS was associated with increased AN symptoms, while BE-PGS was associated with increased BE and AN symptoms. These patterns were largely consistent in exploratory cross-ancestry analyses. Mediation analyses showed that BMI mediated genetic risks across sexes, while ADHD and anxiety/depression symptoms emerged as additional mediators in females. Conclusions and RelevanceGenetic liabilities to AN and BE contribute to childhood DEB through sex-dependent pathways, highlighting the developmental continuity of ED risk from childhood. Integrating genetic profiles with behavioral markers may facilitate early identification and support multifaceted interventions. Key points QuestionDo genetic risks for anorexia nervosa (AN) and binge eating (BE) contribute to childhood disordered eating behaviors, and what mechanisms mediate these effects? FindingsIn this longitudinal study of 5,618 children of European ancestry, AN polygenic scores (AN-PGS) were associated with early AN symptoms, while BE-PGS showed transdiagnostic associations with both AN and BE symptoms. These links were mediated by BMI and psychosocial traits, including sex-specific pathways through ADHD and anxiety/depression symptoms in females. MeaningOur findings suggest that genetic liability to eating disorders manifests early in life through distinct metabolic and psychosocial pathways, highlighting a window for sex-specific targeted prevention.

Objective: ADHD has been associated with obesity indicators, including BMI, across the lifespan. A possible mechanism linking ADHD and BMI is binge eating. Previous research has found associations between ADHD, binge eating and BMI. However, the role of genetic and environmental influences on these associations remains unclear. Method: We utilized data from the Twins Early Development Study (TEDS), comprising 3,675 monozygotic and 7,063 dizygotic twin pairs. ADHD symptoms in childhood and adolescence were assessed using parent-reported questionnaires. Adult ADHD symptoms were measured using both self-report and parent-report questionnaires. Phenotypic mediation models examined whether binge eating mediated the association between ADHD and BMI, without controlling for genetic confounding. Subsequently, the etiological architecture underlying the associations among the three traits across childhood, adolescence, and adulthood were investigated by incorporating genetic and environmental influences into the models. Results: Binge eating significantly mediated the association between ADHD symptoms and BMI in both adolescence and adulthood. However, these mediation effects were no longer present once genetic and environmental influences were incorporated into the models. The best-fitting model in childhood, adolescence and adulthood was Cholesky decomposition models, where covariance between traits was explained by shared aetiology. Conclusions: This twin study reveals shared liability across ADHD, binge eating, and BMI. The mediating role of binge eating in the relationship between ADHD symptoms and BMI was largely confounded by shared genetic influences. Intervention strategies could focus more on common underlying behavioural and self-regulatory mechanisms across these traits, as well as placing more emphasis on symptom patterns within families.

BackgroundA range of rare chromosomal micro-deletions or -duplications (Copy Number Variants - CNVs) are associated with high risk of neurodevelopmental and mental health conditions (ND-CNVs). There is great individual variability in outcomes, but we lack insights into the contributing social factors, including family functioning. MethodsCaregivers of 598 children and young people (CYP) with a range of 16 ND-CNVs and 222 siblings without ND-CNVs (controls) completed questionnaires on overall family climate (cohesion and conflict) as well as caregiver-CYP relationship warmth and hostility and took part in a research diagnostic interview about CYPs psychiatric symptoms. CYPs intelligence quotient (IQ) was also measured. ResultsComparisons with published data from neurotypical families indicated that families affected by ND-CNVs are characterised by higher family cohesion and conflict as well as lower caregiver-CYP warmth and hostility. Symptoms of oppositional defiant disorder reduced more steeply in CYP with ND-CNVs compared to controls with increasing family cohesion (interaction effect: {beta} = -0.14, p = 4.65 x 10-{superscript 2}). In contrast, they rose more steeply with increasing family conflict (interaction effect: {beta} = 0.18, p = 1.05 x 10-{superscript 2}). Furthermore, symptoms of mood disorder increased more steeply with increased caregiver-CYP hostility in CYP with ND-CNVs (interaction effect: {beta} = 0.15, p = 4.55 x 10-{superscript 2}). ConclusionsRaising a CYP with a rare genetic condition is challenging. Timely access to interventions that support caregivers in fostering a positive family environment may reduce behavioural difficulties in CYP, with subsequent benefits for family functioning.

Objective: To test whether two brief mania measures, the Parent General Behavior Inventory-10 Mania form (PGBI-10M) and 7-Up, retain useful psychometric properties in a large population cohort, and to evaluate whether the PGBI-10M can identify Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS)-defined bipolar spectrum disorders in that setting. Method: Analyses used 11,000+ youths across late childhood and early adolescence from the Adolescent Brain Cognitive Development (ABCD) Study. For both PGBI-10M and 7-Up, we estimated descriptive statistics, internal consistency, confirmatory factor models, graded response models, and measurement-based care benchmarks (minimally important difference, reliable change, and clinical cutpoints). For the PGBI-10M, receiver operating characteristic (ROC) analyses estimated concurrent classification accuracy for bipolar diagnoses at baseline and 2-year follow-up and compared area under the curve (AUC) values with prior outpatient and community mental health samples. Results: Scores were lower than in clinical samples, but both measures remained psychometrically sound. The PGBI-10M showed alpha=.87-.88 and omega=.88; the 7-Up showed alpha=.78 and omega=.79. Longitudinal analyses indicated threshold differences across waves, likely reflecting caregiver recalibration and developmental changes, with modest impact on estimates. ABCD-based benchmarks supported meaningful and reliable change. The PGBI-10M discriminated bipolar cases (AUC=0.68 baseline; 0.77 follow-up), though performance was lower than in clinical samples. Positive predictive values were low in this population. Conclusion: The PGBI-10M and 7-Up support monitoring of manic and mixed symptoms, but the PGBI-10M alone is insufficient for universal bipolar screening. Brief mania scales are best used for targeted assessment and longitudinal monitoring within multi-informant workflows.