Background:Genetic epidemiological analyses of child and adolescent mental health often use data from prospective longitudinal cohorts. Missingness due to selective attrition is therefore an important potential source of bias in such analyses. Informatively reporting on missingness and taking appropriate steps to handle it in analyses can mitigate this potential bias. Here, we aim to systematically assess how researchers report and address missingness in genetic epidemiological studies of child and adolescent mental health-related outcomes using cohort data. Methods:We systematically searched the Ovid Medline database for studies published between August 2012 and August 2025, reporting polygenic score, genome-wide association, or Mendelian randomization analyses, of data on children or adolescents participating in cohort studies. We extracted information from eligible studies based on criteria adapted from the strengthening and reporting of observational studies in epidemiology (STROBE) guidelines. Results:A total of 133 eligible studies were included, of which 125 (93.98%) reported the number of complete cases in all waves, while 84 (63.16%) detailed the amount of missingness on all key variables. Most studies used complete case analysis, while 39 studies explicitly reported applying other methods to handle missingness, with multiple imputation (n = 20, 15.04%) being the most common, followed by full information maximum likelihood 10 (8.1%). Only 18 studies (13.53%) reported an assumed missing mechanism along with the method used to address missingness. Full reporting of both the extent and handling of missingness at the item level was rare, occurring in only 5 (3.76%) and 15 (11.28%) studies, respectively, among the 123 studies that used multi-item instruments. Conclusion:Best practice recommendations for reporting on missing data handling emphasize the importance of detailing the proportion of missingness, types of mechanisms underpinning missingness, and details of approaches used. Based on this review, these recommendations for proper reporting of missing data are rarely followed in full.

Importance:A narrow range of food consumption and/or restricted eating is a core feature of avoidant/restrictive food intake (ARFI) disorder. However, there is limited knowledge of developmental characteristics of children with ARFI and its etiological influences, which constrains research, prevention, and intervention efforts. Objective:To estimate the prevalence of ARFI phenotypes in a population-based sample, examine developmental characteristics across childhood, and investigate the genetic architecture of ARFI using genome-wide association analyses. Design, Setting, and Participants:This preregistered study used data from children born from 1999 to 2009 in the population-based Norwegian Mother, Father, and Child Cohort Study (MoBa), with mother-reported data on ARFI symptoms at 3 and 8 years and linkage with diagnostic data from population health registries. Data were analyzed from March 2024 to May 2025. Exposures:Multiple items were used to identify children with broad ARFI. These children were subclassified into 3 groups based on symptom persistence: ARFI-broad transient (only at age 3 years), emergent (only at age 8 years), and persistent (ages 3 and 8 years). Children in these groups with 1 or more indicators of clinical significance (eg, nutritional deficiency) were further classified into ARFI-clinical subgroups. Main Outcomes and Measures:ARFI groups were compared across developmental characteristics from 6 months to 14 years. Genome-wide methods were used to examine single-nucleotide variant (SNV) heritability (SNV-h2), conduct genetic association analyses, and quantify genetic correlations with other phenotypes. Results:Of 35 751 children with available ARFI assessments at 3 and 8 years (18 236 male [51%]), the prevalence of ARFI-broad persistent, transient, and emergent was 2129 (6.0%), 6338 (17.7%), and 3001 (8.4%), respectively. The prevalence of ARFI-clinical persistent, transient, and emergent was 624 (1.8%), 1157 (3.2%), and 484 (1.4%), respectively (2265 [6.3%] overall). Children with ARFI-broad persistent exhibited more developmental difficulties compared with children with no ARFI. SNV-h2 ranged from 8% to 16%. Two independent genome-wide significant loci were identified. For ARFI-clinical, a significant association was identified with ADCY3 (z = 5.42; P = 3.03 × 10-8). Small to moderate genetic correlations were observed for ARFI-broad, ARFI-clinical and mental health, cognitive/educational, anthropometric, food-associated, and gastrointestinal disorder phenotypes. Conclusions and Relevance:This cohort study found that the prevalence of ARFI in the general pediatric population was substantial, and affected children had an associated elevated risk of developmental difficulties across multiple domains. Findings suggest a need for broad support interventions and advance understanding of the genetic underpinnings of ARFI.

BACKGROUND:Attention-deficit/hyperactivity disorder (ADHD) symptoms and emotional problems frequently co-occur. Longitudinal data provide opportunities to understand how and why they co-develop. METHODS:Data were drawn from the Twins Early Development Study, which included 27,890 participants. Emotional problems and ADHD symptoms were parent-reported using the Strengths and Difficulties Questionnaire and Conners' Parent Rating scales. We modeled the co-development of ADHD symptoms and emotional problems from ages 4 to 21 using joint trajectory analysis. The predictors included polygenic scores (PGSs) for multiple psychiatric symptoms, maternal depression, family chaos, and socioeconomic status (SES). The outcomes included SES, lifetime psychiatric diagnoses, undergraduate diploma attainment, and entry into parenthood at age 26. RESULTS:A four-class joint trajectory model was selected as best fitting and included: 'Low ADHD, Low emotional problems', 'High-decreasing ADHD, Low emotional problems', 'Mid-decreasing ADHD, Increasing emotional problems', and 'Increasing ADHD, Increasing emotional problems'. The consistently low-symptom group reported lower ADHD and had lower externalizing PGSs, lower maternal depression, higher SES, and less home chaos at baseline, and higher educational attainment and fewer lifetime depression/anxiety diagnoses at 26 than groups with higher symptom levels. Those with high ADHD symptoms in childhood or increasing ADHD symptoms from childhood to adulthood had the lowest educational attainment and SES in adulthood. CONCLUSIONS:Groups characterized by increasing ADHD symptoms also tended to show increases in emotional problems, whereas increases in emotional problems did not necessarily coincide with increases in ADHD symptoms. The trajectories had distinct early-life predictors and adult outcomes, highlighting potential intervention targets.

Early temperament, such as socio-emotional development and activity level, varies widely, yet its underlying biological associations are not understood. We identified genetic variation associated with infant and toddler temperament using genome-wide association meta-analyses. We studied parent-rated emotionality, activity, shyness and sociability (n = 43,963-72,663) in the second and third postnatal years and a cross-age average. Cross-age single nucleotide polymorphism heritabilities for emotionality, activity, shyness and sociability were 6.79% (95% confidence interval (CI), (4.71%, 8.87%)), 9.55% (95% CI, (7.04%, 12.06%)), 15.26% (95% CI, (12.24%, 18.28%)) and 3.42% (95% CI, (1.30%, 5.54%)), respectively. Ten genome-wide significant loci were discovered. Two loci colocalized with expression quantitative trait loci in the adult cortex: RHEBL1 (posterior probability, 0.93; associated with activity) and MR1 (posterior probability, 0.99; with emotionality). Genetic correlations were observed between early temperament and later outcomes, such as emotionality and adult neuroticism, activity and attention deficit/hyperactivity disorder (ADHD), sociability and autism, and shyness and adult extraversion. Multi-ancestry (n = 56,083-78,894) and European-ancestry analyses gave similar results. Infant and toddler temperament is associated with genetic variation and shows genetic continuity with later outcomes.

Background: Selective participation in research studies hampers researchers’ ability to draw valid and generalizable inferences from analyses. Quantifying and adjusting for selective participation is desirable, but can be challenging given the paucity of data for non-participants. Methods: We used individual-level information from population registers to predict baseline and continued participation in the Norwegian Mother, Father and Child Cohort Study (MoBa). Inverse probability weights were computed from logistic regression models with elastic-net regularization. We predicted selective participation and attrition in 296,987 mothers, of whom 29% returned the first MoBa questionnaire, and 12.5% who returned a follow-up questionnaire eight years later. To quantify bias we computed sample characteristics and outcome-exposure associations in the target population and stratified samples. To compare approaches for adjusting for bias, we computed weighted sample estimates using three sets of weights. Results: Unweighted sample estimates were systematically different from target population values, indicating bias due to selective participation. Baseline participation weights substantially reduced the impact of selection bias on mean values (93%) and associations (75%). Attrition weights performed similarly in reducing attrition bias (78% and 50%), but were less effective for reducing participation bias (22% and 14%). Discussion: Sample characteristics and effect estimates are substantially different from target population values. Participation weights were relatively effective at reducing bias due to selective participation, but attrition weights were not. Estimates from studies that use attrition weights may still contain non-negligible selection bias - particularly if the baseline sample is not representative of the target population. Future studies should prioritise opportunities for deriving sampling weights for participation as well as attrition.

In observational studies, an unhealthy dietary pattern during pregnancy is associated with an increased likelihood of offspring ADHD. We investigated whether such associations may be partly attributable to genetic confounding. Polygenic scores (PGSs) for a healthy dietary pattern were calculated for mother, father, and child trios in the COPSAC2010 cohort. Diagnoses and trait scores of ADHD were assessed in the children at age 10. Using trio models, we tested whether the association between maternal genetic liability to a healthy dietary pattern and offspring ADHD could be accounted for by genetic confounding. In COPSAC2010 trio models (N-trio=437), a maternal healthy dietary pattern PGS was associated with reduced ADHD trait score after adjustment for child and paternal dietary pattern PGS, suggesting indirect genetic effects consistent with causal effects from maternal diet. However, this was not replicated in MoBa (N-trio=41 580) or ALSPAC (N-trio=1 211), where direct genetic effect estimates implied an important role for genetic confounding. Collectively, these genetic results indicate a potential pathway by which genetic confounding can inflate observed associations between maternal dietary pattern in pregnancy and offspring ADHD, and do not provide any robust evidence consistent with a causal pathway between the two. These findings should be interpreted in the light of both the limited predictive power of the dietary pattern PGS, which accounted for only a small proportion of pregnancy diet variance, and the multi-faceted nature of diet as an exposure.

Lockdowns and social restrictions imposed in response to the Covid-19 pandemic intensified the proximity and reciprocal exposure among members of nuclear families. It is unclear how variation in mental distress during this period is attributed to potential influences of family members. This study used genetic data from adolescents (n = 4 388), mothers (n = 27 852) and fathers (n = 25 953), to disentangle the contributions of parent-driven, child-driven, and partner-driven components to mental distress during the first two months of the Covid-19 lockdown. Separate models also included adolescents’ non-pandemic mental distress as outcomes (n = 13 484). Trio genome-wide complex trait analyses separated two types of genetic components; direct–how an individual’s genotype is associated with their own mental distress, and indirect–how an individual’s genotype is associated with the mental distress of family members. A trio polygenic score (PGS) design was used to investigate associations of specific genetic liability factors with mental distress, and whether these changed over time (PGS×time). Results suggest that family-level genetic factors contribute to mental distress; variance components capturing indirect genetic effects accounted for 10% of adolescent mental distress (mother-driven), 2–3% of maternal (partner-driven), and 5% of paternal mental distress (child-driven). Mothers’ depression and ADHD PGS were positively associated with fathers’ mental distress. No PGS×time interactions were found. Direct genetic effects accounted for 9–10% variance in mental distress across family members, partly explained by genetic variants associated with anxiety, depression, ADHD and neuroticism. These findings highlight the importance of family dynamics and emphasize the potential value of including family members in mental health interventions.

Background: Genetic variants in family members may exert environmentally mediated indirect genetic effects on children’s attention-deficit hyperactivity disorder (ADHD) traits. We set out to quantify the indirect genetic effects of parents’ genotypes on children’s ADHD traits as measured in early and mid-childhood. Methods: We analyzed data from genotyped trios of children, mothers, and fathers of European ancestry from the Norwegian Mother, Father and Child Cohort Study (MoBa) birth cohort. Child ADHD data were available for analytic subsamples of 12,374 trios at age 5 (children 50.5% male), and 12,714 trios at age 8 (children 50.9% male). We quantified direct genetic effects of children’s genotype and indirect effects of mothers’ and fathers’ genotypes on children’s ADHD traits at each age. Results: At age 5, maternal indirect genetic effects explained roughly twice as much variance in children’s ADHD traits as did child direct genetic effects. At age 8, maternal indirect genetic effects and child direct genetic effects explained roughly equal portions of variance in child ADHD traits. However, issues with power were evident throughout analyses and precluded confident interpretation of indirect genetic effects. Conclusions: We find tentative evidence for heritable parental traits exerting environmental effects on child ADHD traits in early and mid-childhood, suggesting that maternal genotypes exert indirect effects on children’s traits after accounting for the direct effects of children’s own genotype. However, future studies with larger samples are needed to enable clear inferences on the importance of indirect genetic effects for children’s ADHD traits.

Abstract Polygenic scores are imperfect measures of the additive genetic effects of common genetic variants. The resulting measurement error biases estimates of quantities of interest in epidemiological analyses integrating polygenic scores. For example, how much of an exposure-outcome association is genetically confounded can be substantially underestimated when using polygenic scores alone. Here we present extensions to Gsens , a genetic sensitivity analysis, which aims to correct for such measurement error using both polygenic scores and heritability estimates. Gsens now allows for multiple exposures and estimates several quantities of interest, i.e. genetic confounding, adjusted residual association (net of genetic confounding), genetic overlap and environmentally mediated genetic effects. We present derivations and simulations showing how Gsens accounts for measurement error in the polygenic score; we also show how estimation may be affected by misspecifications of the causal structure between exposures. Applying Gsens in the Norwegian Mother, Father and Child Cohort Study (MoBa), we uncover, among other results, substantial genetic confounding in the associations between multiple known risk factors for attention deficit hyperactivity disorder (ADHD), such as low birth weight and temperament, and measures of ADHD in childhood. The updated Gsens R package offers multiple options, including for missing data handling and customisable syntax. Our extended version of Gsens is applicable to a broad range of substantive questions in multiple disciplines.

Anxiety is heritable and exists on a continuum, with symptoms ranging from adaptive threat response to clinical disorder. Here we performed a genome-wide association meta-analysis of generalized anxiety symptom severity in 693,869 individuals of European ancestry from 14 cohorts. We identified 80 independent genome-wide significant variants within 74 loci, 39 of which were newly associated with anxiety. SNP-based heritability was 5.9% (posterior s.d. = 0.15%). Polygenic scores were significantly associated with anxiety symptom severity and disorder in European, African and South Asian ancestry samples (R2 = 1.2-2.9%). Significant genetic correlations (rg) were estimated with mental and physical health traits, including case-control anxiety, neuroticism and depression (rg = 0.71-0.85), 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 discovery power gained from analysing a quantitative trait rather than a case-control phenotype in anxiety genetics.

BACKGROUND:The intergenerational transmission of obesity-related traits could propagate an accelerating cycle of obesity, if parental adiposity causally influences offspring adiposity. The extent to which intergenerational obesity associations are due to such causal effects, as opposed to genetic confounding (inheritance), is unclear. We aimed to establish whether associations between parental peri-pregnancy body mass index (BMI) and offspring birth weight (BW), BMI until 8 years of age, and 8-year-old eating behaviour are due to genetic confounding. METHODS AND FINDINGS:Data were from the Norwegian Mother, Father and Child Cohort Study, a prospective population-based birth cohort born between 1999 and 2009 at 50 out of 52 hospital maternity units in Norway. We compared the strength of the associations of maternal pre-pregnancy BMI versus paternal BMI during pregnancy, with offspring outcomes including birth weight and BMI assessed between age 6 months and 8 years of age, and appetite-related eating behaviour traits assessed at age 8 years via the Child Eating Behaviour Questionnaire (CEBQ), adjusting for potential confounders including parity, parental/grandparental language group and parental age, smoking, education and income). We then used an extended children of twins structural equation model (SEM) to quantify the extent to which associations were due to genetic confounding. Up to 85,866 children (51.3% male) were included in linear regression models, whereas SEM models included up to 50,999 children. Maternal BMI was more strongly associated than paternal BMI with offspring BW, but the maternal-paternal difference decreased for offspring BMI after birth. Greater parental BMI was associated with obesity-related offspring eating behaviours. SEM results indicated that genetic confounding did not explain the association between parental BMI and offspring BW, but explained the majority of the association with offspring BMI from 6 months onwards. For 8-year BMI, genetic confounding explained 79% (95% CI [62, 95]; p = 1.9 × 10-12) of the covariance with maternal BMI and 94% (95% CI [72, 113]; p = 2.7 × 10-14) of the covariance with paternal BMI. Limitations of this study include selective recruitment and attrition, potential bias due to parental assortative mating, and that findings may not generalise beyond high-income country settings with high obesity prevalence. CONCLUSIONS:We found strong evidence that parent-child BMI associations may primarily be due to genetic confounding. When considered alongside prior evidence, this finding may argue against a strong causal effect of maternal or paternal adiposity on childhood adiposity via intrauterine or periconceptional mechanisms.

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.

BACKGROUND:Inflammation in pregnancy induced by chronic disease, infection, or environmental exposures has been associated with neurodevelopmental conditions in observational study designs. OBJECTIVE:To investigate causal effects of pregnancy inflammation on offspring neurodevelopment in the Norwegian Mother, Father and Child Cohort Study (MoBa) using a genetically informed design. METHODS:In pre-registered analyses, we tested potential causal effects of increased C-reactive protein (CRP), interleukin-6 (IL-6), and glycoprotein acetyls (GlycA) in pregnancy on neurodevelopmental outcomes using trio polygenic score (PGS) and intergenerational Mendelian randomization (MR) analyses. PGS and MR genetic instruments were used to predict neurodevelopmental outcomes in the MoBa cohort, which included mother-reported neurodevelopmental traits registered from age 3 to 8 years and diagnoses of ADHD and autism. In both the trio PGS and intergenerational MR analyses, simultaneous inclusion of mothers', fathers', and children's genotypes allowed for effects consistent with the hypothesized causal pathway (maternal inflammation) to be estimated independent of familial confounding factors. RESULTS:Validation analyses of genetic instruments only showed strong predictive value for CRP. Trio PGS in 41,531 complete trios did not reveal maternal indirect effects of genetic liability to higher CRP on offspring neurodevelopmental outcomes. The results of the trio MR also failed to support a causal link between maternal inflammation, proxied by higher CRP, during pregnancy and offspring neurodevelopment. CONCLUSION:This study provided no evidence consistent with causal effects of higher CRP in pregnancy on offspring neurodevelopment. This may imply that observational links are driven by genetic confounding, though other factors - such as selective participation in MoBa - cannot be ruled out as alternative explanations for our null findings.

Background: Genetic and environmental factors contribute to eating disorder risk, yet their interplay is poorly understood. We examined whether childhood maltreatment and polygenic scores for anorexia nervosa (PGS-AN) and binge-eating broad (PGS-BEB) are associated with eating disorders. We also examined the interactions between childhood maltreatment and PGSs in predicting eating disorders. Methods: This nested case-control study used data from up to 63,989 mothers in the MoBa (Norwegian Mother, Father and Child Cohort Study). Mothers reported on their own experiences of 4 childhood maltreatment types: long-term humiliation or degradation, threats to self or someone close, physical abuse, and sexual abuse. Diagnoses of AN, bulimia nervosa (BN), binge-eating disorder (BED), purging disorder (PD), and binge-eating spectrum disorders (BESP) were obtained using self-report data from 5 time points and population health registers. Results: The prevalence of AN, BN, BED, PD, and BESP was 2.19%, 4.15%, 10.39%, 0.60%, and 12.96%, respectively. All childhood maltreatment types were strongly associated with elevated eating disorder likelihood (with odds ratios [ORs] ranging from 1.71 to 3.29) as were eating disorder PGSs (with ORs ranging from 1.05 to 1.31). There were no multiplicative interaction effects between childhood maltreatment and PGSs. Small additive interactions were observed between PGS-AN and PGS-BEB and degradation/humiliation for BN and BESP in exploratory analyses. Conclusions: Eating disorder PGSs and childhood maltreatment are associated with higher odds of eating disorders. Furthermore, we found tentative evidence of small additive interaction effects between polygenic liability and childhood maltreatment, suggesting that their combined influence further elevates the risk of some eating disorders.

Genome-wide association studies using large, population-based samples of unrelated individuals have discovered thousands of genetic associations with health and disease1. These studies can help explain genetic and environmental risks. However, increasing evidence suggests that population-based estimates, while precise, can also reflect confounding that affects their use and interpretation. This confounding can be overcome using data from genotyped family members, such as nuclear mother-father-child trios2,3. However, samples of genotyped families are rare4-11. Here we illustrate some of the advantages of familial data using the Norwegian Mother, Father and Child Cohort Study (MoBa), a population-based cohort of parents and offspring with extensive genotype data (n ≈ 230,000) (ref. 3), along with broad and longitudinal phenotyping of health and functioning. We provide an overview of MoBa and describe the quality control of genotype data tailored to this extensively related sample. We then use trio data to illustrate how family-based genomic designs can identify distinct direct and indirect sources of genetic influence and structural confounding. As examples, we analyse children's height, educational achievement, depressive symptoms and sleep duration. These demonstrations highlight MoBa as a broadly valuable resource for advancing understanding of health and functioning across the lifecourse and generations.

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.

Early in life, behavioural and cognitive traits associated with risk for developing a psychiatric condition are broad and undifferentiated. As children develop, these traits differentiate into characteristic clusters of symptoms and behaviours that ultimately form the basis of diagnostic categories. Understanding this differentiation process - in the context of genetic risk for psychiatric conditions, which is highly generalised - can improve early detection and treatment. We modelled the differentiation of behavioural and emotional problems from age 1.5-5 years (behavioural problems – emotional problems = differentiation score) in a pre-registered study of ~79 000 children from the population-based Norwegian Mother, Father, and Child Cohort Study. We used genomic structural equation modelling to identify genetic signal in differentiation and the total level of behavioural and emotional problems, investigating their links with 11 psychiatric and neurodevelopmental conditions. We examined associations of polygenic scores (PGS) with differentiation and total problems and assessed the relative contributions of direct and indirect genetic effects in over 33 000 family trios. Differentiation exhibited detectable common variant heritability ( h 2 SNP = 0.023 [0.017, 0.029]), and was primarily genetically correlated with psychiatric conditions via a “neurodevelopmental” factor. PGS analyses revealed a substantial association between polygenic liability to ADHD and differentiation (β = 0.09 [0.08, 0.11]), and a weaker association with total problems (β = 0.05 [0.04, 0.06]). Trio-PGS analyses indicated predominantly direct genetic effects on both outcomes. We uncovered systematic genomic signal in the differentiation process, mostly related to common variants associated with neurodevelopmental conditions. Investigating the co-occurrence and differentiation of behavioural and emotional problems may enhance our ability to detect and eventually prevent the emergence of psychiatric conditions.

Background:Postpartum depression (PPD) affects 18% of postpartum women globally. PPD is a heterogeneous condition with diverse presentations, which may differ in underlying etiology, potential outcomes, and optimal treatment. This study aimed to identify and validate PPD subtypes using comprehensive phenotypic and genetic data from a large, nationwide cohort. Methods:In this population-based cohort study, we used data from the Norwegian Mother, Father, and Child Cohort Study and Medical Birth Registry of Norway (MoBa), and applied unsupervised clustering (Uniform Manifold Approximation and Projection [UMAP] + Density-Based Spatial Clustering of Applications with Noise [DBSCAN]) to identify PPD subtypes among 7859 women with PPD (training set n = 5239). All pregnant women in Norway were eligible to enroll in MoBa between Jun 1, 1999 and Dec 31, 2008. Among women with their first recorded pregnancies in MoBa, they were considered to have clinically significant PPD if they scored ≥8 on the 6-item version of the Edinburgh Postnatal Depression Scale (EPDS) (equivalent to ≥11 on the full EPDS) administered at six months after birth. Input variables included psychiatric symptom severity, psychiatric history, trauma history, pain, and substance use. We then characterized clusters and tested associations with perinatal-relevant auxiliary variables and polygenic scores (PGS) for eight psychiatric and neurodevelopmental conditions. Findings were validated in a reserved test set (n = 2620). Findings:Nine clusters were identified in the training set (n = 5239), with seven replicating in the independent test set (n = 2620). Clusters were differentiated by symptom severity, onset timing, trauma history, and pain during pregnancy. In the training set, the cluster with the most severe symptoms was characterized by depression + trauma and comprised 28% [1483/5239] of training sample. This cluster showed marked socioeconomic adversity and elevated genetic risk for psychiatric conditions compared to other clusters (ADHD PGS OR 1.19, 95% CI 1.12-1.28; major depression PGS OR 1.15, 95% CI 1.07-1.23; PTSD PGS OR 1.09, 95% CI 1.02-1.17). In the test set, this cluster also comprised 28% [729/2620] and showed consistent associations with ADHD (OR 1.23, 95% CI 1.12-1.35), major depression (OR 1.09, 95% CI 0.99-1.20), and PTSD (OR 1.17, 95% CI 1.06-1.29). Conversely, the mild PPD cluster (10% [498/5239] of training sample) showed a protective profile (ADHD PGS OR 0.81, 95% CI 0.73-0.90; major depression PGS OR 0.85, 95% CI 0.77-0.94). In the test set, it represented 10% (263/2620), with consistent protective associations for ADHD (OR 0.84, 95% CI 0.72-0.96) and major depression (OR 0.77, 95% CI 0.67-0.89). Two early-onset clusters demonstrated distinct profiles despite similar symptom severity. The cluster characterized as early-onset PPD + pain (6% of training set [310/5239] and 7% of test set [178/2620]) had the highest prevalence of somatic conditions, including migraines (19% [58/310] training; 15% [26/178] test), nausea (47% [144/310] training; 53% [94/178] test), prenatal hospitalization (41% [128/310] training; 35% [62/178] test), and birth by caesarean section (10% [31/310] training; 8% [14/178] test), whereas the cluster characterized as early-onset PPD + anger (6% [307/5239] of training sample; 6% [158/2620] of test sample) showed many fewer physical health burdens. The clusters in the training and testing set had moderate to high concordance (ARI = 0.76 [95% CI 0.74, 0.77], FMI = 0.79 [95% CI 0.77, 0.81]). Interpretation:This study identifies clinically relevant PPD subtypes with distinct genetic and obstetric profiles, highlighting the importance of trauma-informed care, pain management, and holistic obstetric approaches in PPD prevention and treatment. Limitations of this study include reliance on self-reported data, lack of diversity in the genetically homogeneous Norwegian sample, and genetic analyses subject to power constraints, which may limit generalizability and reduce precision of results. Despite these limitations, identification of reproducible subtypes with different risk factors and outcomes provides a framework for developing targeted interventions and advancing precision psychiatry in maternal mental health. Funding:National Institute of Mental Health; National Institute of Child Health and Human Development; MRC Integrative Epidemiology Unit, University of Bristol; European Research Council; Marie Skłodowska-Curie Actions; South-Eastern Norway Regional Health Authority; Research Council of Norway; NordForsk; European Union Horizon 2020; Novo Nordisk Foundation.

BACKGROUND:The prevalence of youth anxiety and depression has increased globally, with limited causal explanations. Long-term physical health conditions (LTCs) affect 20-40% of youth, with rates also rising. LTCs are associated with higher rates of youth depression and anxiety; however, it is uncertain whether observed associations are causal or explained by unmeasured confounding or reverse causation. METHODS:Using data from the Norwegian Mother, Father, and Child Cohort Study (MoBa) and Norwegian National Patient Registry, we investigated phenotypic associations between childhood LTCs, and depression and anxiety diagnoses in youth (<19 years), defined using ICD-10 diagnoses and self-rated measures. We then conducted two-sample Mendelian Randomization (MR) analyses using SNPs associated with childhood LTCs from existing genome-wide association studies (GWAS) as instrumental variables. Outcomes were: (i) diagnoses of major depressive disorder (MDD) and anxiety disorders or elevated symptoms in MoBa, and (ii) youth-onset MDD using summary statistics from a GWAS in iPSYCH2015 cohort. RESULTS:Having any childhood LTC phenotype was associated with elevated youth MDD (OR = 1.48 [95% CIs 1.19, 1.85], p = 4.2×10-4) and anxiety disorder risk (OR = 1.44 [1.20, 1.73], p = 7.9×10-5). Observational and MR analyses in MoBa were consistent with a causal relationship between migraine and depression (IVW OR = 1.38 [1.19, 1.60], pFDR = 1.8x10-4). MR analyses using iPSYCH2015 did not support a causal link between LTC genetic liabilities and youth-onset depression or in the reverse direction. CONCLUSIONS:Childhood LTCs are associated with depression and anxiety in youth, however, little evidence of causation between LTCs genetic liability and youth depression/anxiety was identified from MR analyses, except for migraine.