Uncovering the specific genetic architecture underpinning anxiety and mood disorders using a joint latent factor GWAS and a detailed LD score panel

Description

Genome-wide association (GWA) studies of single phenotypes and broad latent traits do not capture all genetic associations relevant for any investigated trait due to intricate interactions underpinning complex human traits and biases being introduced in the measurement and selection process of individual studies. Studies informed by GWA data, such as designs employing polygenic scores or genetic instrumental variables for mendelian randomisation, would at this moment not primarily gain from an increase in statistical power of the GWA data but rather from providing specific and precise genetic associations with more granularly defined phenotypes such as biomarkers to provide insights into either prevention or psychiatric treatment. We hypothesise that indicator variables describing a broad set of traits in a joint factor analysis of GWA study summary statistics can identify detailed latent genetic covariance patterns underpinning anxiety and mood disorders. Such patterns could in turn yield improved characterisations of the genetic constructs of the primary trait phenotypes or of endophenotypes. In this talk I will present preliminary results from performing a large joint GWA study using genomic structural equation modelling.

Period	17 Jun 2021
Held at	Social Genetic & Developmental Psychiatry
Degree of Recognition	Regional