Establishing behavioural networks in psychiatric genetics
: polygenic scoring, cross-trait prediction, mediation, and Mendelian randomisation

Student thesis: Doctoral ThesisDoctor of Philosophy

Abstract

Quantitative genetics research utilising an array of sophisticated statistical techniques and methods has clearly demonstrated that genetics have a pervasive influence on human behavioural traits (Polderman et al, 2015, Bulik-Sullivan, et al, 2015; Krapohl et al, 2016; Socrates et al, 2017; Richardson, Harrison, Hemani & Smith, 2019). In the last few years, largely due to advances in genotyping large biobank cohorts with detailed phenotypic data, these types of studies have culminated in demonstrating that human behavioural traits and health outcomes form complex networks of relationships, with multiple causal pathways.However, due to the nature of these types of traits and with regards to human behaviour in general, the mechanisms that drive these association have not been easy to ascertain. Human behaviour is often not well defined, measured or understood. With the complications of strong and complex environmental influences, disentangling the role of genetics is challenging. The genetics underpinning these traits often consist of the small effects of many thousands of genetic variants, which can be difficult to quantify. Despite these obstacles, the technological progress in genotyping and subsequent sample size expansions, combined with the recent development of more advanced statistical genetics methods, have made mapping and understanding these networks achievable.The overarching aims of this thesis are to firstly utilise big data and large cohorts to identify genetic associations between traits and diseases, contrasting and comparing their relative effects, before interrogating these further to expose direct causal effects between behavioural traits and disease. The key objective is to elucidate the role of genetically influenced human behaviour and environmental effects on psychiatric and cognitive outcomes.

This PhD was funded by a studentship from the Institute of Psychiatry, Psychology and Neuroscience at King’s College London. This thesis used genotype and phenotype data from the Northern Finland Birth Cohort (NFBC1966) collected at age 31, which received financial support from University of Oulu Grant no. 65354, Oulu University Hospital Grant no. 2/97, 8/97, Ministry of Health and Social Affairs Grant no. 23/251/97, 160/97, 190/97, National Institute for Health and Welfare, Helsinki Grant no. 54121, Regional Institute of Occupational Health, Oulu, Finland Grant no. 50621, 54231. + researchers’ own funding. Genotype and phenotype data was also used from the UK Biobank, which is funded primarily by the Wellcome charity and the Medical Research Council (MRC). A comprehensive list of funding awards can be found on the UK Biobank website (https://www.ukbiobank.ac.uk/wp-content/uploads/2018/10/Funding-UK-Biobank-summary.pdf). I acknowledge the use of the research computing facility at King’s College London, Rosalind (https://rosalind.kcl.ac.uk).
Date of Award1 Jul 2021
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorPaul O'Reilly (Supervisor) & Jean-Baptiste Pingault (Supervisor)

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