B3329 - Multivariate prediction of childhood psychopathology using polygenic scores - 24/06/2019

B number: 
B3329
Principal applicant name: 
Hannah Sallis | MRC IEU (UK)
Co-applicants: 
Omowonuola Akingbuwa, Professor Marcus Munafo, Professor Christel Middeldorp
Title of project: 
Multivariate prediction of childhood psychopathology using polygenic scores
Proposal summary: 

Childhood psychopathology traits are complex, being affected by a large number of genetic variants, each with a small effect. They are also associated with a number of other phenotypes, both psychiatric and non-psychiatric (Meinzer et al., 2013, Erickson et al., 2016). These associations may be explained by different mechanisms, e.g. shared biological pathways or pleiotropy, where the same genetic variant(s) influence multiple phenotypes. Either way, polygenic risk scores (PRS) – aggregate scores reflecting an individual’s liability for a trait based on multiple genetic variants – can, and have been used to investigate these associations (Nivard et al., 2017, Stergiakouli et al., 2017, Jansen et al., 2018). When PRS of one trait significantly predict another, we can conclude that the traits are genetically correlated.

Polygenic risk scores have been used to show genetic associations between childhood psychopathology and a range of adult traits including psychiatric disorders like major depressive disorder (MDD) and schizophrenia, functional outcomes like educational attainment, and other psychopathology related traits including insomnia, neuroticism, subjective wellbeing, and BMI, which are generally stable over age. However, it is unknown what the patterns of correlations or associations between adult traits and childhood psychopathology are and how they contribute to the associations between them, as well as the developmental trajectories of these associations. Taking a multivariate approach, we hope to understand the patterns of correlation/association between our traits of interest as well as investigate which adult traits show the biggest contribution to the association with childhood psychopathology.

Impact of research: 
This research has the potential to improve our understanding of the aetiology of childhood psychopathology, and how associations between traits may explain developmental trajectories in psychopathology.
Date proposal received: 
Monday, 24 June, 2019
Date proposal approved: 
Monday, 24 June, 2019
Keywords: 
Genetic epidemiology (including association studies and mendelian randomisation), Behaviour - e.g. antisocial behaviour, risk behaviour, etc., Mental health, Statistical methods, Genetic epidemiology