Leveraging genome-wide data to understand the risk and treatment of common mental disorders

Abstract

Common mental disorders, including anxiety and depression, have a detrimental impact on global disease burden and quality of life. Both the risk and treatment of anxiety and depression are associated with the complex interplay between genetic, psychological, and socio-environmental factors. Integrating these factors has posed a challenge in research efforts aimed at improving the prevention and treatment of these disorders. The recent growth of genomic data and advancements in multi-trait methodology allows for the incorporation of genetics with psycho-social factors at an unprecedented level. This thesis applies statistical genetic approaches to further understand the genetic influences on the risk and resolution of common mental disorders. The first empirical study (Chapter 2) presents the largest genome wide association study (GWAS) meta-analysis of lifetime fear-based anxiety disorders (N total = 188,812; N cases =30,861) and examines the shared and distinct genetic relationship with generalised anxiety disorder (N total =172,248; N cases =54,928) and broad domains of other complex traits. Chapter 3 builds on previous research finding a genetic component of reported trauma, a major socio-environmental risk factor for anxiety and depression. By leveraging preexisting GWAS summary statistics, genetic correlations and genomic multiple regression analyses are used to identify heritable psychological and behavioural traits that capture the common genetic variant-based heritability of reported childhood maltreatment (N=185,414). Chapter 4 represents the largest GWAS meta-analysis of outcomes following psychological treatment for anxiety and depression (N total =15,131; N reported positive outcomes =11,408). The utility of genetic factors is also assessed by incorporating polygenic scores of complex traits into multivariable prediction models of psychological treatment outcomes alongside known clinical and demographic predictors. The final chapter discusses the implications of the findings from this thesis within the context of challenges emerging in anxiety and depression genomics. With the ongoing expansion of GWAS data, consideration should be taken into how phenotyping approaches influence downstream analyses, including the genetic structure observed across psychopathologies and the psycho-social components involved in gene environment interplay.

Date of Award	1 Jun 2023
Original language	English
Awarding Institution	King's College London
Supervisor	Thalia Eley (Supervisor) & Gerome Breen (Supervisor)