Background: Polygenic scores (PGSs) are increasingly used to investigate the genetic architecture of complex traits. In genetics, family study designs are often used to adjust for confounders such as population structure and shared environment. However, family studies may also be particularly vulnerable to to non-random ascertainment, for example when individual case status affects the probability of inclusion, leading to differential representation of sibling pairs. In sibling samples, PGS associations can be decomposed into within-family and between-family components, where the within-family estimate captures associations between sibling differences in PGS and differences in outcome, thereby providing an estimate that is less affected by shared familial confounding. In this study, we examined the impact of non-random sampling on estimated genetic effects in family-based studies using both simulations and real-world data. Further, we leveraged the iPSYCH study design to estimate within-family PGS effects for six common mental health outcomes and whether accounting for these can improve prediction accuracy. Methods: We conducted simulations and applied the same framework to real-world data to evaluate the impact of selection bias on within- and between-family PGS estimates. Selection bias was modelled through differential sampling of sibling pairs based on case status, and inverse probability weighting (IPW) was applied to adjust for known heterogeneous inclusion probabilities. Analyses were replicated in the iPSYCH cohort using registry-based sampling weights and PGSs for six major psychiatric disorders. Predictive performance of models was assessed using five-fold cross-validation. Results: In simulation studies, biased sampling led to deviations in estimated PGS effects, with greater distortion observed for between-family components. IPW adjustment reduced the discrepancy between estimates obtained from biased and true underlying data. In the iPSYCH cohort, between-family estimates from unweighted models were larger than within-family estimates across traits. IPW weighted attenuated several of these estimates. Prediction analyses comparing models using total PGS versus decomposed within- and between-family components showed minimal differences in area under the curve and scaled R2 in the iPSYCH data, while modest gains were observed in selected simulation scenarios. Conclusions: Non-random ascertainment distorts effect estimates in family-based models, with particular sensitivity when estimating between-family effects. Incorporating IPWs derived from known or estimable inclusion probabilities can reduce this bias. Our findings highlight the importance of accounting for selection bias in family studies when estimating genetic effects

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.

Eating disorders-including anorexia nervosa (AN), bulimia nervosa and binge-eating disorder-are clinically distinct but exhibit symptom overlap and diagnostic crossover. Genomic analyses have mostly examined AN. Here we conducted a genomic meta-analysis of case-control studies of binge-eating behavior (BE; 39,279 cases, 1,227,436 controls), alongside analyses of AN (24,223 cases, 1,243,971 controls) and its subtypes (all European ancestries). We identified six BE-associated loci, including loci associated with a higher body mass index and impulse-control behaviors. AN genome-wide association studies yielded eight loci, validating six loci. Subsequent polygenic risk score analysis demonstrated an association with AN in two East Asian ancestry studies. BE and AN exhibited similar positive genetic correlations with psychiatric disorders but opposing genetic correlations with anthropometric traits. Most of the genetic signal in BE and AN was not shared with body mass index. We have extended eating disorder genomics beyond AN; future work will incorporate multiple diagnoses and global ancestries.

BACKGROUND:Relative risk estimates of familial aggregation of many types of mental disorders are available, but absolute risk estimates of familial aggregation of mental disorders remain sparse. The proportion of individuals who develop a mental disorder in the absence of the same disorder in a relative (non-familial cases) has not been examined. We aimed to create comprehensive risk estimates of the familial aggregation of mental disorders. METHODS:In this prospective cohort study, we followed people of Danish origin between Jan 1, 1970, and Dec 31, 2021. We used Danish population-based registers to link individuals and their mental health across extended family pedigrees. These registers include the Danish Civil Registration System, the Danish Multi Generation Register, the Danish Psychiatric Central Research Register, and the Danish National Patient Register. Mental disorders investigated were substance use disorder, cannabis use disorder, alcohol use disorder, schizophrenia and related disorders, schizophrenia, schizoaffective disorder, mood disorders, bipolar disorder, single and recurrent depressive disorders (depression), personality disorder, borderline personality disorder, and antisocial personality disorder. We estimated lifetime risk (risk up to age 60 years), age-specific absolute risk, and relative risk for each mental disorder and type of affected relative (eg first, second, or third-degree relatives). We calculated heritability estimates and the proportion of non-familial cases. We involved people with related lived experience in the study design and implementation. FINDINGS:A total of 3 048 583 individuals (1 486 132 [48·75%] females and 1 562 451 [51·25%] males) were followed up for 80 425 971 person-years. Individuals with a family member with a specific type of mental disorder had higher lifetime and relative risks of developing the same type of mental disorder. Both lifetime and relative risks were higher the closer the affected kinship. For example, the lifetime risk of depression was 15·48% (95% CI 15·31-15·65) in individuals with affected first-degree relatives, 13·50% (13·25-13·75) in individuals with affected second-degree relatives, 7·80% (7·76-7·84) in the general population, and 4·68% (4·65-4·71) in individuals without affected first-degree and second-degree relatives. The heritability for depression was 45·4% (95% CI 44·8-46·0) and the proportion of non-familial cases constituted 60·0% (95% CI 59·8-60·2). INTERPRETATION:Individuals with family members with a mental disorder face increased risks of the same disorder. From a population perspective, most mental disorders occur in individuals without affected close relatives, thus highlighting the need for prevention strategies which target the entire population. FUNDING:Novo Nordisk Foundation. TRANSLATION:For the Danish translation of the abstract see Supplementary Materials section.

Eating disorders -including anorexia nervosa (AN), bulimia nervosa, and binge eating disorder-are clinically distinct but exhibit symptom overlap and diagnostic crossover. Genomic analyses have mostly examined AN. We conducted the first genomic meta-analysis of binge eating behaviour (BE; 39,279 cases, 1,227,436 controls), alongside new analyses of AN (24,223 cases, 1,243,971 controls) and its subtypes (all European ancestries). We identified six loci associated with BE, including loci associated with higher body mass index (BMI) and impulse-control behaviours. AN GWAS yielded eight loci, validating six loci. Subsequent polygenic risk score analysis demonstrated an association with AN in two East Asian ancestry cohorts. BE and AN exhibited similar positive genetic correlations with psychiatric disorders, but opposing genetic correlations with anthropometric traits. Most of the genetic signal in BE and AN was not shared with BMI. We have extended eating disorder genomics beyond AN; future work will incorporate multiple diagnoses and global ancestries.

Background:Psychiatric disorders represent a significant global health burden with complex etiologies involving both genetic and environmental factors. However, while the main effects of genetic and environmental factors are frequently studied, their interplay in shaping psychiatric disorder risk remains poorly understood. This study investigates the interaction between polygenic scores (PGS) as proxies for genetic risk and environmental factors in the risk of psychiatric disorders. Method:This study utilized the iPSYCH case-cohort sample (n = 141,265). Environmental factors, including region, urbanicity, parental socioeconomic status, parental age, parental psychiatric history and early-life exposures: autoimmune disease, brain injury, and central nervous system (CNS) infections, were obtained from Danish nationwide registers. Logistic regression was used to examine the effects of targeted disorder-specific PGSs, environmental factors and their interactions on psychiatric disorders. Analyses were adjusted for age, sex and ancestral principal components to account for population stratification. Results:Both PGS and environmental factors were associated with psychiatric disorders. We found limited evidence of gene-environment interactions across the investigated psychiatric disorders. Most interaction terms were small and not statistically significant, but a few remained significant. These included a smaller PGS association with attention deficit hyperactivity disorder in Southern Denmark compared with the Capital Region, a reduced PGS association with bipolar disorder in the medium and lowest parental income groups compared with the highest income group, and a weaker PGS association with major depressive disorder in individuals with parental psychiatric history compared with those without such history. In contrast, a larger PGS association with schizophrenia was observed in the paternal age group 31-35 years compared with the 26-30 years reference group, and a stronger PGS association with anorexia nervosa in North Denmark compared with the Capital Region. Conclusion:Genetic liability for psychiatric disorders, captured through PGS, was associated with mental disorder risk across environmental contexts. Only a few gene-environment interactions were significant, and these were modest and mental disorder-specific. Overall, the findings highlight the difficulty of detecting robust gene-environment interactions and the need for studies of sufficient scale and statistical power to identify subtle gene-environment effects and improve understanding of psychiatric disorder etiology.

Attention deficit hyperactivity disorder (ADHD) is a childhood-onset neurodevelopmental disorder with a large genetic component1. It affects around 5% of children and 2.5% of adults2, and is associated with several severe outcomes3-11. Common genetic variants associated with the disorder have been identified12,13, but the role of rare variants in ADHD is mostly unknown. Here, by analysing rare coding variants in exome-sequencing data from 8,895 individuals with ADHD and 53,780 control individuals, we identify three genes (MAP1A, ANO8 and ANK2; P < 3.07 × 10-6; odds ratios 5.55-15.13) that are implicated in ADHD. The protein-protein interaction networks of these three genes were enriched for rare-variant risk genes of other neurodevelopmental disorders, and for genes involved in cytoskeleton organization, synapse function and RNA processing. Top associated rare-variant risk genes showed increased expression across pre- and postnatal brain developmental stages and in several neuronal cell types, including GABAergic (γ-aminobutyric-acid-producing) and dopaminergic neurons. Deleterious variants were associated with lower socioeconomic status and lower levels of education in individuals with ADHD, and a decrease of 2.25 intelligence quotient (IQ) points per rare deleterious variant in a sample of adults with ADHD (n = 962). Individuals with ADHD and intellectual disability showed an increased load of rare variants overall, whereas other psychiatric comorbidities had an increased load only for specific gene sets associated with those comorbidities. This suggests that psychiatric comorbidity in ADHD is driven mainly by rare variants in specific genes, rather than by a general increased load across constrained genes.

BACKGROUND:There is growing evidence linking neonatal vitamin D deficiency to an increased risk of schizophrenia, ADHD, and autism spectrum disorder (ASD). The aim of this study was to examine the association between two vitamin D biomarkers (25 hydroxyvitamin D [25(OH)D] and vitamin D-binding protein [DBP], and their related genetic correlates) and the risk of six mental disorders. METHODS:We used a population-based, case-cohort sample of all individuals born in Denmark between 1981 and 2005. Using Danish health registers with follow-up to Dec 31, 2012, we identified individuals diagnosed with major depressive disorder, bipolar disorder, schizophrenia, ADHD, ASD, and anorexia nervosa based on ICD-10 criteria. Additionally, a random subcohort from the general population was selected. Based on neonatal dried blood spots, we measured concentrations of 25(OH)D and DBP. Our primary analyses were based on hazard ratios (HR) with 95% CI and absolute risks for the six mental disorders according to measured concentrations of 25(OH)D and DBP. As secondary analyses, we examined the association between genetic predictors of 25(OH)D and DBP, and the six mental disorders, and Mendelian randomisation analyses based on published summary statistics for 25(OH)D, DBP, and the six mental disorders. People with lived experience contributed to the development of the guiding hypothesis. FINDINGS:We used the total population from the iPSYCH2012 design (n=88 764), which included individuals who developed the six mental disorders, major depressive disorder (n=24 240), bipolar disorder (n=1928), schizophrenia (n=3540), ADHD (n=18 726), ASD (n=16 146), anorexia nervosa (n=3643), and the randomly sampled subcohort (n=30 000). Among those who met a range of inclusion criteria (eg, measured 25[OH]D, DBP or genotype, and predominantly European ancestry), we measured 25(OH)D or DBP in 71 793 individuals (38 118 [53·1%] male and 33 675 [46·9%] female); 65 952 had 25(OH)D and 66 797 the DBP measurements. Significant inverse relationships were found between 25(OH)D and schizophrenia (HR 0·82, 95% CI 0·78-0·86), ASD (HR 0·93, 95% CI 0·90-0·96), and ADHD (HR 0·89, 95% CI 0·86-0·92). A significant inverse relationship was found between DBP and schizophrenia (HR 0·84, 95% CI 0·80-0·88). Based on polygenic risk scores, higher concentrations of 25(OH)D (adjusted for DBP) were significantly associated with a reduced risk of both ASD and schizophrenia. Analyses based on Mendelian randomisation provided support for a causal association between both lower 25(OH)D and DBP concentrations and an increased risk of ADHD. INTERPRETATION:Convergent evidence finds that neonatal vitamin D status is associated with an altered risk of mental disorders. Our study supports the hypothesis that optimising neonatal vitamin D status might reduce the incidence of a range of neurodevelopmental disorders. FUNDING:The Danish National Research Foundation.

We conducted a genome-wide association study on income among individuals of European descent (N = 668,288) to investigate the relationship between socio-economic status and health disparities. We identified 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes (the Income Factor). Our polygenic index captures 1-5% of income variance, with only one fourth due to direct genetic effects. A phenome-wide association study using this index showed reduced risks for diseases including hypertension, obesity, type 2 diabetes, depression, asthma and back pain. The Income Factor had a substantial genetic correlation (0.92, s.e. = 0.006) with educational attainment. Accounting for the genetic overlap of educational attainment with income revealed that the remaining genetic signal was linked to better mental health but reduced physical health and increased risky behaviours such as drinking and smoking. These findings highlight the complex genetic influences on income and health.

Genetic variants linked to autism are thought to change cognition and behaviour by altering the structure and function of the brain. Although a substantial body of literature has identified structural brain differences in autism, it is unknown whether autism-associated common genetic variants are linked to changes in cortical macro- and micro-structure. We investigated this using neuroimaging and genetic data from adults (UK Biobank, N = 31,748) and children (ABCD, N = 4928). Using polygenic scores and genetic correlations we observe a robust negative association between common variants for autism and a magnetic resonance imaging derived phenotype for neurite density (intracellular volume fraction) in the general population. This result is consistent across both children and adults, in both the cortex and in white matter tracts, and confirmed using polygenic scores and genetic correlations. There were no sex differences in this association. Mendelian randomisation analyses provide no evidence for a causal relationship between autism and intracellular volume fraction, although this should be revisited using better powered instruments. Overall, this study provides evidence for shared common variant genetics between autism and cortical neurite density.

Obsessive-compulsive disorder (OCD) affects ~1% of children and adults and is partly caused by genetic factors. We conducted a genome-wide association study (GWAS) meta-analysis combining 53,660 OCD cases and 2,044,417 controls and identified 30 independent genome-wide significant loci. Gene-based approaches identified 249 potential effector genes for OCD, with 25 of these classified as the most likely causal candidates, including WDR6, DALRD3 and CTNND1 and multiple genes in the major histocompatibility complex (MHC) region. We estimated that ~11,500 genetic variants explained 90% of OCD genetic heritability. OCD genetic risk was associated with excitatory neurons in the hippocampus and the cortex, along with D1 and D2 type dopamine receptor-containing medium spiny neurons. OCD genetic risk was shared with 65 of 112 additional phenotypes, including all the psychiatric disorders we examined. In particular, OCD shared genetic risk with anxiety, depression, anorexia nervosa and Tourette syndrome and was negatively associated with inflammatory bowel diseases, educational attainment and body mass index.

Socioeconomic status gaps in academic achievement are well documented. We show that a very similar gap exists with respect to genetic differences measured by a polygenic score for educational attainment. The genetic gap increases during elementary school, but only among low-socioeconomic-status children. Consequently, high-polygenic-score children experience the largest achievement growth over the school years, even if they are born in socioeconomic disadvantage. While the socioeconomic status gap is partly explained by selection into different neighbourhoods and schools, the polygenic score gap is not. However, a higher polygenic score is related to higher conscientiousness and a better subjective learning environment, even conditional on family fixed effects. These findings contribute to our understanding of how genetic and socioeconomic factors interact throughout the educational journey, offering insights for developing more targeted and effective educational interventions.

Bipolar disorder is a leading contributor to the global burden of disease1. Despite high heritability (60-80%), the majority of the underlying genetic determinants remain unknown2. We analysed data from participants of European, East Asian, African American and Latino ancestries (n = 158,036 cases with bipolar disorder, 2.8 million controls), combining clinical, community and self-reported samples. We identified 298 genome-wide significant loci in the multi-ancestry meta-analysis, a fourfold increase over previous findings3, and identified an ancestry-specific association in the East Asian cohort. Integrating results from fine-mapping and other variant-to-gene mapping approaches identified 36 credible genes in the aetiology of bipolar disorder. Genes prioritized through fine-mapping were enriched for ultra-rare damaging missense and protein-truncating variations in cases with bipolar disorder4, highlighting convergence of common and rare variant signals. We report differences in the genetic architecture of bipolar disorder depending on the source of patient ascertainment and on bipolar disorder subtype (type I or type II). Several analyses implicate specific cell types in the pathophysiology of bipolar disorder, including GABAergic interneurons and medium spiny neurons. Together, these analyses provide additional insights into the genetic architecture and biological underpinnings of bipolar disorder.

Background: Immune mechanisms are associated with adverse outcomes in schizophrenia; however, the predictive value of various peripheral immune biomarkers has not been collectively investigated in a large cohort before. Objective: To investigate how white blood cell (WBC) counts, ratios, and C-Reactive Protein (CRP) levels influence the long-term outcomes of individuals with schizophrenia spectrum disorder (SSD). Methods: We identified all adults in the Central Denmark Region during 1994-2013 with a measurement of WBC counts and/or CRP at first diagnosis of SSD. WBC ratios were calculated, and both WBC counts and ratios were quartile-categorized (Q4 upper quartile). We followed these individuals from first diagnosis until outcome of interest (death, treatment resistance and psychiatric readmissions), emigration or December 31, 2016, using Cox regression analysis to estimate adjusted hazard ratios (aHRs). Results: Among 6,845 participants, 375(5.5 %) died, 477 (6.9 %) exhibited treatment resistance, and 1470 (21.5 %) were readmitted during follow-up. Elevated baseline levels of leukocytes, neutrophils, monocytes, LLR, NLR, MLR, and CRP increased the risk of death, whereas higher levels of lymphocytes, platelets, and PLR were associated with lower risk. ROC analysis identified CRP as the strongest predictor for mortality (AUC=0.84). Moreover, elevated levels of leukocytes, neutrophils, monocytes, LLR, NLR and MLR were associated with treatment resistance. Lastly, higher platelet counts decreased the risk of psychiatric readmissions, while elevated LLR increased this risk. Conclusions: Elevated levels of WBC counts, ratios, and CRP at the initial diagnosis of SSD are associated with mortality, with CRP demonstrating the highest predictive value. Additionally, certain WBC counts and ratios are associated with treatment resistance and psychiatric readmissions.

Background Psychiatric disorders and type 2 diabetes mellitus (T2DM) are heritable, polygenic, and often comorbid conditions, yet knowledge about their potential shared familial risk is lacking. We used family designs and T2DM polygenic risk score (T2DM-PRS) to investigate the genetic associations between psychiatric disorders and T2DM.Methods We linked 659 906 individuals born in Denmark 1990-2000 to their parents, grandparents, and aunts/uncles using population-based registers. We compared rates of T2DM in relatives of children with and without a diagnosis of any or one of 11 specific psychiatric disorders, including neuropsychiatric and neurodevelopmental disorders, using Cox regression. In a genotyped sample (iPSYCH2015) of individuals born 1981-2008 (n = 134 403), we used logistic regression to estimate associations between a T2DM-PRS and these psychiatric disorders.Results Among 5 235 300 relative pairs, relatives of individuals with a psychiatric disorder had an increased risk for T2DM with stronger associations for closer relatives (parents:hazard ratio = 1.38, 95% confidence interval 1.35-1.42; grandparents: 1.14, 1.13-1.15; and aunts/uncles: 1.19, 1.16-1.22). In the genetic sample, one standard deviation increase in T2DM-PRS was associated with an increased risk for any psychiatric disorder (odds ratio = 1.11, 1.08-1.14). Both familial T2DM and T2DM-PRS were significantly associated with seven of 11 psychiatric disorders, most strongly with attention-deficit/hyperactivity disorder and conduct disorder, and inversely with anorexia nervosa.Conclusions Our findings of familial co-aggregation and higher T2DM polygenic liability associated with psychiatric disorders point toward shared familial risk. This suggests that part of the comorbidity is explained by shared familial risks. The underlying mechanisms still remain largely unknown and the contributions of genetics and environment need further investigation.