Developmental changes within the genetic architecture of social communication behaviour: A multivariate study of genetic variance in unrelated individuals

Abstract

Background: Recent analyses of trait-disorder overlap suggest that psychiatric dimensions may relate to distinct sets of genes that exert their maximum influence during different periods of development. This includes analyses of social-communciation difficulties that share, depending on their developmental stage, stronger genetic links with either Autism Spectrum Disorder or schizophrenia. Here we developed a multivariate analysis framework in unrelated individuals to model directly the developmental profile of genetic influences contributing to complex traits, such as social-communication difficulties, during a ~10-year period spanning childhood and adolescence. Methods:Longitudinally assessed quantitative social-communication problems (N≤ 5,551) were studied in participants from a UK birth cohort (ALSPAC, 8 to 17 years). Using standardised measures, genetic architectures were investigated with novel multivariate genetic-relationship-matrix structural equation models (GSEM) incorporating whole-genome genotyping information. Analogous to twin research, GSEM included Cholesky decomposition, common pathway and independent pathway models. Results:A 2-factor Cholesky decomposition model described the data best. One genetic factor was common to SCDC measures across development, the other accounted for independent variation at 11 years and later, consistent with distinct developmental profiles in trait-disorder overlap. Importantly, genetic factors operating at 8 years explained only ~50% of the genetic variation at 17 years. Conclusion:Using latent factor models, we identified developmental changes in the genetic architecture of social-communication difficulties that enhance the understanding of ASD and schizophrenia-related dimensions. More generally, GSEM present a framework for modelling shared genetic aetiologies between phenotypes and can provide prior information with respect to patterns and continuity of trait-disorder overlap.

The development of autistic social traits across childhood and adolescence in males and females

“…Another key question is whether the SCDC‐measured traits we observed in adolescent girls are truly autistic in nature, or whether they represent a different type of social impairment, for example, arising from the onset of internalising problems, ADHD or psychosis risk (St Pourcain, Eaves, et al., ; St Pourcain, Robinson et al., ). Several strands of evidence support the notion that the female social variability we observed in adolescence is related to autism.…”

“…A related possibility is that a ‘two‐hit’ mechanism could be in operation, whereby pubertal influences interact with pre‐existing vulnerabilities (Picci & Scherf, ). Furthermore, there is evidence that some genetic influences on social behaviour only start to influence the phenotype in adolescence, and it will be important to investigate whether such time‐specific genetic effects are moderated by gender (St Pourcain, Eaves, et al., ; St Pourcain, Robinson et al., ).…”

“…This contradicts the idea that the rise in SCDC scores of females we observed is merely an epiphenomenon driven by a rise in internalising problems (in this case, social anxiety). Nevertheless, future work is needed to elucidate the nature and causes of adolescent onset social communication difficulties, including the extent to which they are influenced by nonautistic factors (St Pourcain, Eaves, et al., ; St Pourcain, Robinson et al., ). This should include investigation of their infant and early childhood precursors, co‐occurring psychopathology and early adult outcomes.…”

The developmental genetic architecture of vocabulary skills during the first three years of life: Capturing emerging associations with later-life reading and cognition

“…We model multivariate genetic architectures underlying these traits as directly captured by genome-wide information (based on genetic-relationship-matrices, GRMs) for up to 6,524 unrelated youth from the UK Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort (18,19). We apply GRM structural equation modelling (GSEM) (20), analogous to twin research-modelling techniques, and dissect the phenotypic variation into additive genetic and residual variance structures.…”

“…relationship-matrix Structural Equation Models (GSEMs)(20). This is a multivariate structural equation modelling technique, which combines multivariate analysis methodologies established in twin research(40,41) with estimates of genetic relationships between unrelated individuals, as captured by genomewide genetic markers (20) (S3 Appendix).…”