Biology subjects

Schlag, F.

Publications and source records attributed to Schlag, F..

3 recordsLinked to original sources

bioRxiv2025

Genome-wide analysis of social behaviour in context: a meta-regression approach across social domains, reporters and developmental stages

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). 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.

genomics↗

bioRxiv2025

Disentangling multivariate relationships between cognition, language and social traits: structures of G, E, and rGE

BackgroundCognitive, language, and social abilities are complex, heritable and intertwined traits shaping childrens 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 (rGE), investigating cognitive, language, and social behavioural/communication measures. MethodsData 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 DevelopmentSM (ABCD) Study (N[≤]4,412), and analyses were carried out implementing an extended data-driven genetic-relationship-matrix structural equation modelling (GRM-SEM) approach. ResultsIn 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 ({lambda}A and {lambda}E, respectively) for verbal IQ ({lambda}A=0.73(SE=0.05); {lambda}E=0.57(SE=0.07)). The second domain captured social difficulties, with the largest {lambda}A and {lambda}E for social communication measures ({lambda}A=0.39(SE=0.10); {lambda}E=0.82(SE=0.10)). We identified trait-specific rGE between pairs of A and E factors with different directions of effect (cognition/language rGE=0.89(SE=0.18), social rGE=-0.62(SE=0.17)). rGE 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. ConclusionsIn childhood, cognitive/language abilities versus social abilities are influenced by distinct genomic and/or environmental factors, potentially interlinked through trait-specific rGE, suggesting differences in developmental processes.

genomics↗

bioRxiv2022

Genomic contributions to infant and toddler vocabulary scores: Implications for association with health-, cognition- and behaviour-related outcomes

BackgroundThe 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. MethodsWe 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-h2), genetic correlations (rg) and modelled underlying genetic factor structures with multivariate models. ResultsContributions of common genetic variation to early-life vocabulary were modest (SNP-h2: 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 (rg=0.07(SE=0.10)), although both measures were genetically related to toddler expressive vocabulary (rg=0.69(SE=0.14) and rg=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: rg=0.36(SE=0.12)), despite comparable study power for infant measures. Furthermore, increased polygenic ADHD risk was associated with larger infant expressive vocabulary (rg=0.23(SE=0.08)), as confirmed by ADHD-symptom-based follow-up analyses in the Avon Longitudinal Study of Parents and Children (ALSPAC-rg=0.54(SE=0.26)). Genetic relationships with toddler receptive vocabulary were, however, opposite (ALSPAC-rg=-0.74(SE=0.23)), highlighting developmental changes in genetic architectures. ConclusionsMultiple genetic components contribute to early-life vocabulary development, shaping polygenic association patterns with later-life ADHD symptoms and cognition.

genomics↗