Background Parental genetics matters for children’s behavioural difficulties, but the extent to which this is due to direct genetic transmission versus environmentally mediated indirect genetic effects remains unclear. Methods We studied eight European birth cohorts with over 33,000 family-based trio samples. We analysed polygenic scores (PGSs) for 13 mental health and neurodevelopmental conditions and their composite indices (PC1 and mean) representing general neuropsychiatric liabilities, as well as educational attainment (EA) and alcohol and cigarette use, from children (PGSc), mothers (PGSm), and fathers. Child internalising, externalising, and total difficulties reported by mothers and/or fathers were examined at preschool and school ages. We then conducted multivariate meta-analyses to combine cohort-level results. Findings We observed several direct genetic effects on externalising difficulties, while indirect genetic influences were mainly identified for internalising difficulties. Specifically, child PGSs for attention-deficit/hyperactivity disorder (ADHD) and EA predicted higher and lower levels, respectively, of child externalising and total difficulties (all p FDR<0·001; for school-aged externalising difficulties, PGSc-ADHD: β=0·121 [95% CI 0·091 to 0·151], p FDR<0·0001; PGSc-EA: β=−0·095 [95% CI −0·127 to −0·063], p FDR<0·0001), whereas maternal PGSs for major depressive disorder (MDD) and general neuropsychiatric liabilities were associated with internalising and total difficulties across parental raters and child ages (all p FDR<0·05; for school-aged internalising difficulties, PGSm-MDD: β=0·049 [95% CI 0·017 to 0·081], p FDR=0·016; PGSm-PC1: β=0·056 [95% CI 0·022 to 0·091], p FDR=0·011). No statistically significant effects from paternal PGSs were identified. Interpretation In this multi-cohort study, findings across multiple traits, raters, and ages supported several direct genetic effects of ADHD and EA on child externalising difficulties and indirect genetic effects on internalising difficulties, especially maternal depression and general neuropsychiatric liabilities. These suggest that child internalising difficulties are not solely driven by direct genetic transmission. More comprehensive research is needed to better understand the mechanisms involved, and ultimately how to ameliorate child behavioural difficulties. Funding EU, ERC, RCN, RCF, UKRI, SERI, DFG Evidence before this study Indirect genetic effects (IGEs) refer to the influence of parental genotypes on offspring outcomes beyond direct genetic effects (DGEs), for example via environmental pathways. While IGEs on offspring cognitive traits are well-established for educational attainment, evidence for IGEs of parental liabilities to mental health and neurodevelopmental conditions remains limited. To assess the current state of evidence, we conducted a systematic search of published studies applying trio-based polygenic score (PGS) designs to child and adolescent mental health outcomes. We identified 141 primary studies in MEDLINE, Embase, PsycInfo, and Web of Science, by 6 March 2025, after removing duplicates; following screening, 12 studies met inclusion criteria (see supplement for a full description including results). Ten out of the 12 studies focused on externalising outcomes, with little or inconsistent support for IGEs. When observed, IGEs were mainly driven by maternal liabilities to autism, educational attainment, and cognitive performance on child outcomes. The current evidence was too limited and heterogeneous to synthesize findings quantitatively, therefore a qualitative synthesis was conducted. Many studies were statistically underpowered, and the observed IGEs were in all cases sample-specific. There were no published multi-cohort studies. Added value of this study We integrated information across over 33,000 mother-father-child trios from eight European cohorts, investigating 18 PGSs from parents and children, using maternal and paternal ratings of offspring’s internalising, externalising, and total difficulties as outcomes at both preschool and school age. We mainly observed DGEs on externalising difficulties, consistent with previous studies. Some evidence of IGEs was found for internalising and total difficulties. IGEs were often found to be maternally driven, with the most robust evidence across ages and raters emerging for maternal depression and general neuropsychiatric liabilities. Implications of all the available evidence The current evidence suggests that children’s behavioural difficulties, especially internalising difficulties, may be partly driven by the environment shaped by maternal neuropsychiatric liabilities. Ours and previous findings highlight a pressing need for more comprehensive studies across different cohorts, raters, outcomes, and time points to understand the true extent of IGEs in the intergenerational transmission of mental health. ### Competing Interest Statement O.A.A. is a consultant to CorTechs.ai and Precision Health, and has received speaker's honoraria from BMS, Lundbeck, Lilly, Janssen, Sunovion, and Otsuka, with no conflict of interest relevant to this work. The other authors declare no biomedical financial interests or potentially competing interests. ### Funding Statement This study was funded by the European Union's Horizon Europe Research and Innovation Programme, European Research Council, ERAnet Neuron, Academy of Finland (Council of Finland), Research Council of Norway, South-Eastern Norway Regional Health Authority, Horizon Europe, UK Research and Innovation, Swiss State Secretariat for Education, Research and Innovation, and German Research Foundation ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The PREDO study protocol was approved by the Ethics Committee of Obstetrics and Gynaecology and Women, Children and Psychiatry of the Helsinki and Uusimaa Hospital District and by the participating hospitals. All studies were approved by their institutional ethics review committees and all participants provided written informed consent (see supplement). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Correspondence and requests for materials should be addressed to: jari.lahti{at}helsinki.fi

Background:Cognitive, language, and social abilities are complex, heritable and intertwined traits shaping children's development and later mental health. To better understand cross-trait interrelationships, we model here the structures of shared genomic and shared non-genomic/residual (i.e. broadly environmental) influences, and their correlation ( r G E ), investigating cognitive, language, and social behavioural/communication measures. Methods:Data were obtained for unrelated children (8-13 years) from two population-based cohorts: the UK Avon Longitudinal Study of Parents and Children (ALSPAC, N≤6,543) and the US Adolescent Brain Cognitive Development℠ (ABCD) Study (N≤4,412), and analyses were carried out implementing an extended data-driven genetic-relationship-matrix structural equation modelling (GRM-SEM) approach. Results:In ALSPAC, we identified two independent phenotypic domains, each captured by a structurally matching pair consisting of a genomic (A) and a non-genomic/residual (E) factor. The first domain reflected cognitive/language difficulties, with the largest genomic and residual factor loadings ( λ A and λ E , respectively) for verbal IQ ( λ A = 0.73 ( S E = 0.05 ) ; λ E = 0.57 ( S E = 0.07 ) ). The second domain captured social difficulties, with the largest λ A and λ E for social communication measures ( λ A = 0.39 ( S E = 0.10 ) ; λ E = 0.82 ( S E = 0.10 ) ). We identified trait-specific r G E between pairs of A and E factors with different directions of effect (cognition/language r G E = 0.89 ( S E = 0.18 ) , social r G E = - 0.62 ( S E = 0.17 ) ). r G E patterns were linked to increased measurable A and E contributions for cognition/language difficulties, but decreased contributions for social problems. Analyses in ABCD confirmed the two domains for E and phenotypic structures, although genomic contributions were low. Conclusions:In childhood, cognitive/language abilities versus social abilities are influenced by distinct genomic and/or environmental factors, potentially interlinked through trait-specific r G E , suggesting differences in developmental processes.

Background: Rapid population-level identification of language disorders could help provide care to young children to improve their outcomes. Two previous studies identified and replicated up to six parent-reported items that predicted 11-year language outcome with ≥71% sensitivity and specificity. Here, we assess whether including genetic propensity for toddlerhood vocabulary improves predictive accuracy. Method: The Early Language in Victoria Study (ELVS) recruited 1,910 8-month-olds in Melbourne in 2003-2004. The Longitudinal Study of Australian Children (LSAC) recruited 5,107 0-1-year-olds across Australia in 2004. Both collected parent-reported items at 2-3 years, a comparable 11-year language outcome: the Clinical Evaluation of Language Fundamentals (CELF-4) Core Language score or Recalling Sentences subtest, and biospecimens for genotyping. We derived polygenic scores capturing participants’ genetic propensity for parent-reported 24-38-month vocabulary. We calculated univariate associations with continuous language outcomes. We used ensemble method SuperLearner to estimate how accurately the parent-reported predictors and polygenic scores predict low 11-year language outcome (more than 1.5 standard deviations below the mean) in each cohort. Results: Language outcome was available for 839 ELVS and 1,441 LSAC participants. Polygenic scores accounted for little variance in continuous language outcomes (R-squared less than 1.5%). Adding polygenic scores to the predictor sets increased accuracy of predicting language outcome by up to 7%, but inconsistently between analyses. Conclusions: Polygenic scores derived for toddlerhood vocabulary did not meaningfully predict late childhood language. Polygenic scores derived for later global language measures in larger samples may be better predictors. Presently, parent-reported measures or clinician observation appear best for predicting language outcome at this age.

BACKGROUND:Mastering gross motor abilities in early infancy and culturally defined actions (e.g. self-care routines) in late infancy can initiate cascading developmental changes that affect language learning. Here, we adopt a genetic perspective to investigate underlying processes, implicating either shared or "gateway" mechanisms, where the latter enable children to interact with their environment. METHODS:Selecting heritable traits (h2, heritability), we studied infant gross motor (6 months) and self-care/symbolic (15 months) skills as predictors of 10 language outcomes (15-38 months) in genotyped children from the Avon Longitudinal Study of Parents and Children (N ≤ 7,017). Language measures were combined into three interrelated language factors (LF) using structural equation modeling (SEM), corresponding to largely different age windows (LF15M, LF24M, LF38M, 51.3% total explained variance). Developmental genomic and non-genomic relationships across measures were dissected with Cholesky decompositions using genetic-relationship-matrix structural equation modeling (GRM-SEM) as part of a multivariate approach. RESULTS:Gross motor abilities at 6 months (h2 = 0.18 (SE = .06)) and self-care/symbolic actions at 15 months (h2 = 0.18 (SE = .06)) were modestly heritable, as well as the three derived language factor scores (LFS15M-h2 = 0.12 (SE = .05), LFS24M-h2 = 0.21 (SE = .06), LFS38M-h2 = 0.17 (SE = .05)), enabling genetic analyses. Developmental genetic models (GRM-SEM) showed that gross motor abilities (6 months) share genetic influences with self-care/symbolic actions (15 months, factor loading λ; λ = 0.22 (SE = .09)), but not with language performance (p ≥ .05). In contrast, genetic influences underlying self-care/symbolic actions, independent of early gross motor skills, were related to all three language factors (LFS15M-λ = 0.26 (SE = .09), LFS24M-λ = 0.28 (SE = .10), LFS38M-λ = 0.30 (SE = .10)). Multivariate models studying individual language outcomes provided consistent results, both for genomic and non-genomic influences. CONCLUSIONS:Genetically encoded processes linking gross motor behaviour in young infants to self-care/symbolic actions in older infants are different from those linking self-care/symbolic actions to emerging language abilities. These findings are consistent with a developmental cascade where motor control enables children to engage in novel social interactions, but children's social learning abilities foster language development.

Although autism has historically been conceptualized as a condition that emerges in early childhood1,2, many autistic people are diagnosed later in life3-5. It is unknown whether earlier- and later-diagnosed autism have different developmental trajectories and genetic profiles. Using longitudinal data from four independent birth cohorts, we demonstrate that two different socioemotional and behavioural trajectories are associated with age at diagnosis. In independent cohorts of autistic individuals, common genetic variants account for approximately 11% of the variance in age at autism diagnosis, similar to the contribution of individual sociodemographic and clinical factors, which typically explain less than 15% of this variance. We further demonstrate that the polygenic architecture of autism can be broken down into two modestly genetically correlated (rg = 0.38, s.e. = 0.07) autism polygenic factors. One of these factors is associated with earlier autism diagnosis and lower social and communication abilities in early childhood, but is only moderately genetically correlated with attention deficit-hyperactivity disorder (ADHD) and mental-health conditions. Conversely, the second factor is associated with later autism diagnosis and increased socioemotional and behavioural difficulties in adolescence, and has moderate to high positive genetic correlations with ADHD and mental-health conditions. These findings indicate that earlier- and later-diagnosed autism have different developmental trajectories and genetic profiles. Our findings have important implications for how we conceptualize autism and provide a model to explain some of the diversity found in autism.

Early-life abilities involved in perceiving, producing and engaging with music (musicality) may shape later (social) communication and language abilities. Here, we investigate phenotypic and genetic relationships linking musicality and communication abilities by studying information from preschool and school-aged children of the Avon Longitudinal Study of Parents and Children (N = 4169–6737 per measure, age 0.5–17 years). Using structural models, we identified relationships between latent musicality and speech- and cognition-related variables (r > 0.30). Consistently, polygenic scores for rhythmicity in adulthood (PGSrhythmicity) showed associations with preschool and school-age musicality (incremental-Nagelkerke-R2 = 0.006-0.011, p < 0.0025), as well as school-age communication and cognition-related measures (incremental-R2 = 0.04–1%, p < 0.0025). Studying the directionality of genetic effects using a mediation framework, we found evidence supporting a developmental pathway linking preschool musicality to school-age speech-/syntax-related abilities, as captured by PGSrhythmicity (shared effect: β = 0.0051(SE = 0.0021), p = 0.015). Associations were found conditional on general cognition and genetically unrelated to educational attainment, suggesting robust developmental links between early musicality and later speech-related communication performance.

Social behaviour is a heritable, context-dependent trait that changes across social settings and development, influencing wellbeing and mental health. We present the first genome-wide meta-regression study of social behaviour from infancy to early adulthood, leveraging 491,246 repeat measures of low prosocial behaviour and peer/social difficulties in European-ancestry cohorts (Neff=121,777, Nind=73,321). We modelled heterogeneity in genetic effects across social domains, informants, and ages (2–29 years), capturing social context through genomic influences. Six loci were identified, including variation within CADM2 ( p =2.51x10-[9][1]). The SNP-based heritability was modest (2–7%), and the genetic architecture of social behaviour multidimensional. Polygenic scores demonstrated predictability and accuracy in independent European-ancestry cohorts and, partially, in African-ancestry cohorts (Nind=16,305). Genetic correlations with later-life and mental health outcomes showed context-dependent patterns. Modelling predicted onsets of associations with social behaviour revealed distinct profiles, as observed for autism, ADHD, depression and schizophrenia, highlighting novel opportunities to genetically proxy developmental trajectories. ### Competing Interest Statement H.L. reports receiving grants from Shire Pharmaceuticals; personal fees from and serving as a speaker for Medice, Shire/Takeda Pharmaceuticals and Evolan Pharma AB; all outside the submitted work. H.L. is editor-in-chief of JCPP Advances. J.A.R-Q. was on the speakers bureau and/or acted as a consultant for Biogen, Idorsia, Casen-Recordati, Janssen-Cilag, Novartis, Takeda, Bial, Sincrolab, Neuraxpharm, Novartis, BMS, Medice, Rubio, Uriach, Technofarma and Raffo in the last 3 years. J.A.R-Q. also received travel awards (air tickets + hotel) for taking part in psychiatric meetings from Idorsia, Janssen-Cilag, Rubio, Takeda, Bial and Medice. The Department of Psychiatry, chaired by J.A.R-Q., received unrestricted educational and research support from the following companies in the last 3 years: Exeltis, Idorsia, Janssen-Cilag, Neuraxpharm, Oryzon, Roche, Probitas and Rubio. E.D.R. has served as a speaker for Shire Sweden AB, a Takeda Pharmaceutical Company, outside of this work. S.B. discloses that he has in the last 3 years acted as a consultant or lecturer for Medice, Takeda, and LinusBio. S.B. receives royalties for textbooks and diagnostic tools from Hogrefe, UTB, Ernst Reinhardt, Kohlhammer, and Liber. S.B. is a partner in NeuroSupportSolutions International AB. All other authors declare no conflict of interest. R2D2-MH, Horizon Europe, 101057385 R2D2-MH, UK Research and Innovation (UKRI), under the UK government’s Horizon Europe funding guarantee, 10039383 R2D2-MH, Swiss State Secretariat for Education, Research and Innovation (SERI), contract number: 22.00277 ZonMW, TOP 40–00812–98–11010 Horizon Europe Research and Innovation Programme, FAMILY, 101057529, HappyMums, 101057390 European Research Council, TEMPO, 101039672 Dutch Ministry of Education, Culture, and Science and the Netherlands Organisation for Scientific Research, 024.001.003, Consortium on Individual Development, NWO-VICI, NWO-ZonMW: 016.VICI.170.200 Horizon 2020 research and innovation program, Contract grant no. 633595, DynaHealth, LongITools, 874739, EarlyCause, 848158 China Scholarship Council, 201706990036 Max Planck Society Radboud University Donders RSF 2025 Ter Meulen Grant of the Royal Netherlands Academy of Arts and Sciences (KNAW) Strategic Research Council (SRC) established within the Academy of Finland, decision no. 352700 Instituto de Salud Carlos III, co-funded by the European Union Fund (Fondo Social Europeo Plus, FSE+), contract no. CP22/00026 Research Council of Norway (RCN), #274611, #336085, #274611, #274611, #288083, #336078 South-Eastern Norway Regional Health Authority (HSO), #2020022, #2018059, #2021045 MRC Integrative Epidemiology Unit, University of Bristol, Medical Research Council, University of Bristol, MC\_UU\_00032/1 European Union, 101045526, 818425 University of Oulu, Academy of Finland Profi6, decision number AF 336449 Research Council of Finland, STAGE [Grant N° 101137146], IHEN [Grant N° 101137317], OBELISK Grant [N° 101080465], OBCT [Grant N° 101080250], TRIGGER [Grant N° 101057739] Research Council of Finland, 356888 MRC Centre for Environment and Health, Medical Research Council, UK, MR/S019669/1 Simons Foundation, 724306 Sir Henry Wellcome Postdoctoral Fellowship, 213514/Z/18/Z Ministry of Science, Technology and Innovation, https://ror.org/012s3r374, State Research Agency grant RYC2022-038136-I, European Union FSE+, State Research Agency grant PID2022-143106OA-I00, European Union FEDER William H. Gates Sr. Fellowship from the Alzheimer’s Disease Data Initiative UK Medical Research Council, Grant Nos. MR/V012878/1 and previously MR/M021475/1 US National Institutes of Health, AG046938 European Research Council under the European Union's Seventh Framework Programme, FP7/2007-2013, grant agreement n° 602768 UK Research and Innovation, 10063472 EU-AIMS (European Autism Interventions) & AIMS-2-TRIALS, European Union FP7 & Horizon2020 Programmes, the European Federation of Pharmaceutical Industries and Associations (EFPIA), AUTISM SPEAKS, Autistica, SFARI,, Innovative Medicines Initiative Joint Undertaking Grant No. 115300 and 777394, Horizon2020 supported programme CANDY Grant No. 847818 [1]: #ref-9

Mastering developmental milestones such as infant motor and personal-social skills (including social routines and pretend-play) can initiate a cascade of developmental changes that may affect language learning. Specifically, motor development may represent an important, but little understood “gateway” enabling children to interact with their environment. Here, we investigate how infant motor and personal-social abilities link to infant and toddler language performance, using a genetic perspective. For this, we studied measures of motor and personal-social skills (6 and 15 months) as predictors of language development, captured by ten language phenotypes (15-38 months) in genotyped children from the Avon Longitudinal Study of Parents and Children (N≤7,017). Language measures were combined into language factor scores (LFS) using structural equation modelling. Developmental genomic and non-genomic (residual) relationships across phenotypes were modelled with a Cholesky decomposition using genetic-relationship-matrix structural equation modelling (GRM-SEM). The ten early language measures were captured by three interrelated language factors (F-15M, F-24M, F-38M, 51.3% explained variance), each corresponding to a different age window. Across infant predictors and derived language factor scores, common genetic variation accounted for a modest proportion of the phenotypic variance (known as heritability, h2: gross-motor-abilities-6M-h2=0.18(SE=0.06), personal-social-skills-15M-h2=0.18(SE=0.06), LFS-15M-h2=0.12(SE=0.05), LFS-24M-h2=0.21(SE=0.06), LFS-38M-h2=0.17(SE=0.05)). Fitting a Cholesky GRM-SEM across predictors and LFS showed that infant gross motor abilities shared genetic influences with personal-social skills (factor loading λ; personal-social-skills-15M-λ=0.22(SE=0.09)), but were unrelated to language performance (P≥0.05). In contrast, genetic influences underlying personal-social skills, independent of gross motor skills, were related to all three LFS (LFS-15M-λ=0.26(SE=0.09), LFS-24M-λ=0.28(SE=0.10), LFS-38M-λ=0.30(SE=0.10)). GRM-SEM analyses studying individual language outcomes provided consistent results, both for genomic and non-genomic structures. Thus, aetiological processes linking motor to personal-social skills differ from those linking personal-social to language abilities, consistent with a developmental cascade where motor control enables children to engage in novel social interactions, but children’s social learning abilities foster language development.

Early-life musical engagement is an understudied but developmentally important and heritable precursor of later (social) communication and language abilities. This study aims to uncover the aetiological mechanisms linking musical to communication abilities. We derived polygenic scores (PGS) for self-reported beat synchronisation abilities (PGSrhythmicity) in children (N≤6,737) from the Avon Longitudinal Study of Parents and Children and tested their association with preschool musical (0.5-5 years) and school-age (social) communication and cognition-related abilities (9-12 years). We further assessed whether relationships between preschool musicality and school-age communication are shared through PGSrhythmicity, using structural equation modelling techniques. PGSrhythmicity were associated with preschool musicality (Nagelkerke-R2=0.70-0.79%), and school-age communication and cognition-related abilities (R2=0.08-0.41%), but not social communication. We identified links between preschool musicality and school-age speech- and syntax-related communication abilities as captured by known genetic influences underlying rhythmicity (shared effect β=0.0065(SE=0.0021), p=0.0016), above and beyond general cognition, strengthening support for early music intervention programmes.

Common genetic variation has been associated with multiple phenotypic features in Autism Spectrum Disorder (ASD). However, our knowledge of shared genetic factor structures contributing to this highly heterogeneous phenotypic spectrum is limited. Here, we developed and implemented a structural equation modelling framework to directly model genomic covariance across core and non-core ASD phenotypes, studying autistic individuals of European descent with a case-only design. We identified three independent genetic factors most strongly linked to language performance, behaviour and developmental motor delay, respectively, studying an autism community sample (N = 5331). The three-factorial structure was largely confirmed in independent ASD-simplex families (N = 1946), although we uncovered, in addition, simplex-specific genetic overlap between behaviour and language phenotypes. Multivariate models across cohorts revealed novel associations, including links between language and early mastering of self-feeding. Thus, the common genetic architecture in ASD is multi-dimensional with overarching genetic factors contributing, in combination with ascertainment-specific patterns, to phenotypic heterogeneity.

Background The number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors, although mechanisms are not well understood. Here, we performed a meta-genome-wide association study within the EAGLE consortium and investigated polygenic overlap with later-life traits, including Attention-Deficit/Hyperactivity Disorder (ADHD) and cognition. Methods We studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months) and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated Single-Nucleotide Polymorphism heritability (SNP-h 2 ), genetic correlations (r g ) and modelled underlying genetic factor structures with multivariate models. Results Contributions of common genetic variation to early-life vocabulary were modest (SNP-h 2 : 0.08(SE=0.01) to 0.24(SE=0.03)) and multi-factorial. Genetic overlap between infant expressive and toddler receptive vocabulary was near zero (r g =0.07(SE=0.10)), although both measures were genetically related to toddler expressive vocabulary (r g =0.69(SE=0.14) and r g =0.67(SE=0.16), respectively). Consistently, polygenic association patterns with later-life traits differed: Genetic links with cognition emerged only in toddlerhood (e.g. toddler receptive vocabulary and intelligence: r g =0.36(SE=0.12)), despite comparable study power for infant measures. Furthermore, increased polygenic ADHD risk was associated with larger infant expressive vocabulary (r g =0.23(SE=0.08)), as confirmed by ADHD-symptom-based follow-up analyses in the Avon Longitudinal Study of Parents and Children (ALSPAC-r g =0.54(SE=0.26)). Genetic relationships with toddler receptive vocabulary were, however, opposite (ALSPAC-r g =-0.74(SE=0.23)), highlighting developmental changes in genetic architectures. Conclusions Multiple genetic components contribute to early-life vocabulary development, shaping polygenic association patterns with later-life ADHD symptoms and cognition.

Many complex psychiatric disorders are characterised by a spectrum of social difficulties. These symptoms lie on a behavioural dimension that is shared with social behaviour in the general population, with substantial contributions of genetic factors. However, shared genetic links may vary across psychiatric disorders and social symptoms. Here, we systematically investigate heterogeneity in shared genetic liabilities with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), bipolar disorder (BP), major depression (MD) and schizophrenia, across a spectrum of different social symptoms. Specifically, longitudinally assessed low-prosociality and peer-problem scores in two UK population-based/community-based cohorts (ALSPAC, N ≤ 6174, 4-17 years; TEDS, N ≤ 7112, 4-16 years; parent- and teacher-reports) were regressed on polygenic risk scores for ADHD, ASD, BP, MD, and schizophrenia, as informed by genome-wide summary statistics from large consortia, using negative binomial regression models. Across ALSPAC and TEDS, we replicated univariate polygenic associations between social behaviour and risk for ADHD, MD, and schizophrenia. Modelling univariate genetic effects across both cohorts with random-effect meta-regression revealed evidence for polygenic links between social behaviour and ADHD, ASD, MD, and schizophrenia risk, but not BP, where differences in age, reporter and social trait captured 45-88% in univariate effect variation. For ADHD, MD, and ASD polygenic risk, we identified stronger association with peer problems than low prosociality, while schizophrenia polygenic risk was solely associated with low prosociality. The identified association profiles suggest marked differences in the social genetic architecture underlying different psychiatric disorders when investigating population-based social symptoms across 13 years of child and adolescent development.

The use of spoken and written language is a capacity that is unique to humans. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30-80%, depending on the trait. The relevant genetic architecture is complex, heterogeneous, and multifactorial, and yet to be investigated with well-powered studies. Here, we present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures: word reading, nonword reading, spelling, phoneme awareness, and nonword repetition, with total sample sizes ranging from 13,633 to 33,959 participants aged 5-26 years (12,411 to 27,180 for those with European ancestry, defined by principal component analyses). We identified a genome-wide significant association with word reading (rs11208009, p=1.098 × 10 −8 ) independent of known loci associated with intelligence or educational attainment. All five reading-/language-related traits had robust SNP-heritability estimates (0.13–0.26), and genetic correlations between them were modest to high. Using genomic structural equation modelling, we found evidence for a shared genetic factor explaining the majority of variation in word and nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence and educational attainment. A multivariate GWAS was performed to jointly analyse word and nonword reading, spelling, and phoneme awareness, maximizing power for follow-up investigation. Genetic correlation analysis of multivariate GWAS results with neuroimaging traits identified association with cortical surface area of the banks of the left superior temporal sulcus, a brain region with known links to processing of spoken and written language. Analysis of evolutionary annotations on the lineage that led to modern humans showed enriched heritability in regions depleted of Neanderthal variants. Together, these results provide new avenues for deciphering the biological underpinnings of these uniquely human traits.

Disease-causing heterozygous variants in the ACTA2 gene cause an autosomal dominant heritable thoracic aortic disease (HTAD) with thoracic aortic aneurysm and dissection as main phenotype, and occasional extravascular abnormalities such as livedo reticularis. ACTA2-HTAD accounts for an important part of non-syndromic HTAD, with detection rates varying between 1.5-21% according to different studies. A consensus statement for the screening and management of patients with pathogenic ACTA2 variants has been recently published by the European reference network for rare vascular diseases (VASCERN). However, management of ACTA2 patients is often challenged by extremely variable inter- and intra-familial clinical courses of the disease. Here we report a family harboring a disease-causing ACTA2 variant. The proband and two siblings presented with acute type A aortic dissection and rupture involving nondilated aortic segments before the age of 30. Their mother died at 49 years-old from type B aortic dissection and rupture. Genetic testing revealed the heterozygous novel p.(Pro335Arg) variant in the ACTA2 gene in the proband and in the affected siblings. The clinical history of this family highlights the difficulty of adopting effective prevention strategies in ACTA2 patients.

Individual differences in early-life vocabulary measures are heritable and associated with subsequent reading and cognitive abilities, although the underlying mechanisms are little understood. Here, we (i) investigate the developmental genetic architecture of expressive and receptive vocabulary in toddlerhood and (ii) assess origin and developmental stage of emerging genetic associations with mid-childhood verbal and non-verbal skills. Studying up to 6,524 unrelated children from the population-based Avon Longitudinal Study of Parents and Children (ALSPAC) cohort, we dissected the phenotypic variance of longitudinally assessed early-life vocabulary measures (15-38 months) and later-life reading and cognitive skills (7-8 years) into genetic and residual components, by fitting multivariate structural equation models to genome-wide genetic-relationship matrices. Our findings show that the genetic architecture of early-life vocabulary is dynamic, involving multiple distinct genetic factors. Two of them are developmentally stable and contribute to genetic variation in mid-childhood skills: Genetic links with later-life verbal abilities (reading, verbal intelligence) emerged with expressive vocabulary at 24 months. The underlying genetic factor explained 10.1% variation (path coefficient: 0.32(SE=0.06)) in early language, but also 6.4% (path coefficient: 0.25(SE=0.12)) and 17.9% (path coefficient: 0.42(SE=0.13)) variation in mid-childhood reading and verbal intelligence, respectively. An independent stable genetic factor was identified for receptive vocabulary at 38 months, explaining 2.1% (path coefficient: 0.15(SE=0.07)) phenotypic variation. This genetic factor was also linked to both verbal and non-verbal cognitive abilities in mid-childhood, accounting for 24.7% of the variation in non-verbal intelligence (path coefficient: 0.50(SE=0.08)), 33.0% in reading (path coefficient: 0.57(SE=0.07)) and 36.1% in verbal intelligence (path coefficient: 0.60(0.10)), corresponding to the majority of genetic variance (≥66.4%). Thus, the genetic foundations of mid-childhood reading and cognition are diverse. They involve at least two independent genetic factors that emerge at different developmental stages during early language development and may implicate differences in cognitive processes that are already detectable during toddlerhood. Author summary Differences in the number of words young children produce (expressive vocabulary) and understand (receptive vocabulary) can be partially explained by genetic factors, and are related to reading and cognitive abilities later in life. Here, we studied genetic influences underlying word production and understanding during early development (15-38 months) and their genetic relationship with mid-childhood reading and cognitive skills (7-8 years), based on longitudinal phenotype measures and genome-wide genetic data from up to 6,524 unrelated children. We showed that vocabulary skills assessed at different stages during early development are influenced by distinct genetic factors, two of which also contribute to genetic variation in mid-childhood skills, suggesting developmental stability: Genetic sources emerging for word production skills at 24 months were linked to subsequent verbal abilities, including mid-childhood reading and verbal intelligence performance. A further independent genetic factor was identified that related to word comprehension at 38 months and also contributed to variation in later verbal as well as non-verbal abilities during mid-childhood. Thus, the genetic foundations of mid-childhood reading and cognition involve at least two independent genetic factors that emerge during early-life langauge development and may implicate differences in overarching cognitive mechanisms.