AN TWAS have previously been performed and revealed some insights into the pathogenesis of the disorder (Chatzinakos et al., 2020; Cheng et al., 2020; Johnson et al., 2022). For example, TWAS using the S-PrediXcan approach (Barbeira et al., 2018), was previously performed in the study outlining the largest AN GWAS, uncovering 36 genes with predicted expression associated with the disorder using data from Genotype-Tissue Expression (GTEx) project brain and blood data (Watson et al., 2019). However, these studies in AN have only considered mRNA expression, which may miss effects mediated from alternative splicing or protein expression. Moreover, large sample size post-mortem brain datasets like the PsychENCODE consortium (NSamples > 1000) with expression and genetic data available present an opportunity to boost power to discover AN associated genes through TWAS. In this study, we utilise models of genetically predicted mRNA expression, protein expression, and alternative mRNA isoform abundance to prioritise genes involved in AN. These association signals were further refined through conditional analysis and finemapping to reveal several genes including WDR6 that may play a role in AN biology. Pathways analysis also implicated regulation of immune system process with gene set functional analysis including signal from MST1, TREX1, PRKAR2A and PROS1.
