Abstract
Background Anorexia Nervosa (AN) is a complex and serious eating disorder, occurring in ~1% of individuals. Despite having the highest mortality rate of any psychiatric disorder, little is known about the aetiology of the AN, and few effective treatments exist. Global efforts to collect large samples from individuals with AN have been highly successful, and a recent study consequently identified the first genome-wide significant locus involved in AN, with significant genetic correlations with multiple metabolic indices. This result, coupled with other recent studies and epidemiological evidence, implies that previous characterizations of AN as a purely psychiatric disorder should be revisited. Rather, it seems that both psychiatric and metabolic systems may be involved. Methods In order to elucidate more of the system-specific aetiology of AN, we applied transcriptomic imputation methods to 3,495 cases and 10,982 controls, collected by the PGC-ED working group. Transcriptomic Imputation (TI) methods approaches use machine-learning methods to impute tissue-specific gene expression from large genotype data using curated eQTL reference panels. These offer an exciting opportunity to compare gene associations across neurological and metabolic tissues. Here, we applied CommonMind Consortium (CMC) and GTEx-derived gene expression prediction models for 12 brain tissues and 12 tissues with potential metabolic involvement (Adipose, Adrenal Gland, 2 Colon, 3 Esophagus, Liver, Pancreas, Small Intestine, Spleen, Stomach). In total, these analyses include 234,968 gene-tissue association tests. Results We identified 35 significant gene-tissue associations within the large chromosome 12 region described in the recent PGC-ED GWAS. We applied a forward-stepwise conditional analysis analogous to GCTA-CoJo in order to identify independent associations within this region and across tissues, and identified two independently associated genes, both in metabolic tissues; RPS26, in the Spleen (p=2.59e-08), and C12orf49, in the Thyroid (p=4.01e-06). We also identified two further regions with genome-wide significant gene-tissue associations, both in brain tissues; REEP5, in the DLPFC (p=8.52e-07), and CUL3, in the Caudate Basal Ganglia (p=1.8e-06). Discussion Our results support a model of AN risk influenced by both metabolic and psychiatric factors. We plan to follow these analyses with investigations of the overlap between AN and other psychiatric and metabolic phenotypes, as well as analysis of potentially implicated molecular pathways.
Published Version
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