METHODS FOR UNDERSTANDING GENETIC CONTRIBUTIONS TO LIFECOURSE MENTAL DISORDERS

There has been substantial progress into the genetics of mental disorders, leading to the identification of key genomic loci, enhanced understanding of causal pathways and improved scope for drug targets. Much of this is based on cross-sectional work, ignoring the fact that mental disorders are not static and can change across the lifecourse. Emerging evidence now suggests that mental disorders, like depression, can have time specific genetic effects that influence the onset, course and persistence of mental disorders over time. However, the methods available to drive this research forward have rarely been applied to genetic and lifecourse studies.

In this symposium, we will highlight exciting new methods that demonstrate the utility of combining genomic and lifecourse methods for improved understanding of mental disorders. This integration of new methods, genetics and lifecourse data could shed light on when genetic and environmental factors are having their greatest effect, which could in turn lead to better preventions and interventions for mental disorders.

Pravesh Parekh (Oslo) will introduce the Fast and Efficient Mixed Effects Algorithm (FEMA), a novel mixed-modelling framework for performing large-scale longitudinal GWAS that allows discovery of non-linear interaction of SNPs, while allowing for time-varying heritability and random effects. The key methodological concepts of FEMA will be introduced, alongside novel opportunities and applications to mental disorders in the Norwegian Mother, Father and Child Cohort Study (MoBa) and Adolescent Brain Cognitive Development (ABCD) Study.

Esme Elsden (Edinburgh) will present longitudinal phenotyping of depressive symptoms and its applications to PRS prediction and GWAS. Using data from UK Biobank, trajectories of depressive symptoms can be derived which reveal key features that cross-sectional approaches miss. These key features include the cumulative total of exposure to depressive symptoms (Area Under the Curve). Results indicate that polygenic contributions significantly influence the severity and course of depression trajectories across the lifecourse and GWAS of these features also identify novel loci that can be more effectively captured through longitudinal designs.

Chris Rayner (King’s College London) will demonstrate the use of Empirical Bayes Estimates with Simultaneous Correction (SCEBE) for performing repeated measures GWAS of depression symptoms in mothers from MoBa. Repeated measures approaches to GWAS and polygenic scoring will be compared with traditional lifetime history approaches. The impacts of selective participation and attrition on repeated measures analyses will also be discussed.

Christel Middeldorp (Amsterdam) will focus on enduring mental health (EMH), a stable state of mental health over time. Previous research on EMH has primarily focused on the absence of mental health problems, neglecting the equally important dimension of presence of wellbeing. In this study, both the absence of mental health problems and the presence of higher wellbeing over time will be examined by using longitudinal data measured in twins, The heritability of EMH will be presented and the associations with polygenic scores as well as other variables, including educational attainment, personality traits, social variables.

Robyn Wootton (Bristol) will summarise these studies and provide a discussion on what lifecourse and genetic studies should do to facilitate future work.

Disclosure: Nothing to disclose. (Kwong, Parekh, Wootton)