Polygenic analyses of childhood and adult psychopathology, and their overlap

Children with psychopathology have an increased risk of continued psychopathology in adulthood compared to the general population. Therefore an understanding of the genetic underpinnings of such traits could be crucial in identifying children most at risk of adverse outcomes, as well as in developing intervention or prevention strategies that may prove useful to them. In this thesis, studies were performed with the aim of investigating genetic mechanisms underlying the persistence of psychiatric traits in children and adolescents, as well as understanding how they develop into adulthood. Chapter 1 of this thesis serves as an introduction to the topics covered, as well as providing an overview of the state of the field up to the point of this undertaking. In chapter 2 we performed a systematic review of studies that used statistical genetic methods to evaluate the contribution of common genetic variants to psychiatric disorders and traits. We showed that larger sample sizes facilitate the discovery of trait-associated genetic variants, as well as provide evidence of heritability based on measured genetic variants, known as SNP-based heritability. Importantly, we observed abundant cross-trait associations across psychopathology traits, suggesting a role for pleiotropic genetic effects in the aetiology of psychopathology across development. In chapter 3 we investigated genetic associations between repeated measures of childhood psychopathology, and polygenic scores (PGS) of adult traits including major depression, bipolar disorder, subjective wellbeing, neuroticism, insomnia, educational attainment, and BMI. We showed a consistent pattern of mostly stable genetic associations between adult trait PGS and childhood psychopathology across age, indicating the existence of a set of genetic factors that influence psychopathology and related traits across the lifespan. Additionally, we showed differential associations between educational attainment and BMI PGS, and types of childhood psychopathology, providing evidence for pleiotropy not just within psychopathology, but across related health and socioeconomic indicators. In chapter 4 we used structural equation modelling to investigate the extent to which the genetic associations observed between childhood psychopathology and adult traits are explained by correlations between the adult trait PGS, as well as correlations between the childhood measures. Again, we observed differential associations between educational attainment and BMI PGS, and childhood psychopathology, i.e. educational attainment PGS was associated with ADHD symptoms, while BMI PGS was associated with ADHD symptoms and social problems. Only major depression PGS remained associated with all three childhood psychopathology measures, suggesting that while shared genetic factors have a role in our understanding of psychopathology, unique genetic factors are likely also important. In chapter 5 we combined genetic, environmental and psychosocial (risk) factors to produce a model for the prediction of adolescent intentional self-harm, aggression, or a combination of both. Our results suggested that aggressive symptoms in mid-adolescence as well as PGS of psychiatric disorders were important predictors of aggression and/or self-harm. We also showed that a combination of different types of predictors, including both genetic, environmental and psychosocial factors, provided the best model for predicting our outcome. Finally, in chapter 6 we investigated the extent to which common variant and rare variant gene-set enrichment analyses converge to similar results for schizophrenia. Results implicated genes likely to be under stringent selection, and suggests partial convergence across common and (ultra-)rare variants, indicating that the same biological mechanisms are implicated across the allele frequency spectrum. Chapter 7 summarises the main findings of the thesis, as well as discussing their implications and future perspectives with regards to field at large. I conclude that a move from genetic variation to disease mechanisms and biological pathways is crucial to further our understanding. The integration of information across the allele frequency spectrum also likely offers the best avenue for significant progress.