Project description:Anorexia nervosa (AN) is a psychiatric disorder with an estimated heritability of around 70%. Although the largest genome-wide association study meta-analysis on AN identified independent loci-conferring risk to the disorder, the molecular mechanisms underlying the genetic basis of AN remains to be elucidated. To explore AN, we ran a transcriptome profiling in peripheral blood mononuclear cells of 15 AN subjects and 15 healthy controls. We validated our mean results in a mouse model of chronic food restriction mimicking several aspects of AN. Through this exploratory study we identified 673 significantly differentially expressed genes in AN. Among these genes, we identified the Vanin-1 (Vnn1) gene that appears to play a major role in the regulation of multiple metabolic pathways. We confirmed an underexpression of Vnn1, especially in the liver, in a mouse model of chronic food restriction. These results indicate that quantitative food restriction affects Vnn1 expression, suggesting that this gene may contribute to the anorexic phenotype in the chronic food restriction mouse model as well as in patients affected by AN. We believe that this report highlights promising candidate genes and gene pathways for AN and reveals Vnn1 as a biomarker that may be used as molecular targets to predict and/or to understand AN.
Project description:As part of the Genetic Consortium for Anorexia Nervosa (GCAN) and Wellcome Trust Case
Control Consortium 3 (WTCCC3), we have amassed the largest anorexia nervosa (AN)
sample in the world (~4,000). Following the WTCCC3 GWAS, we secured funding from the
Klarman Family Foundation to extend the genetic analyses to variants on the exome chip
(CoreExome array). This pre-lim relates to carrying out genotyping on the CoreExome array
on up to a maximum of 580 new samples.
Project description:Up until now, no study has looked specifically at epigenomic landscapes throughout twin samples, discordant for Anorexia nervosa (AN). Our goal was to find evidence to confirm the hypothesis that epigenetic variations play a key role in the aetiology of AN. In this study, we quantified genome-wide patterns of DNA methylation using the Infinium Human DNA Methylation EPIC BeadChip array (850K) in DNA samples isolated from whole blood collected from a group of 7 monozygotic twin pairs discordant for AN. Results were then validated performing a genome-wide DNA methylation profiling using DNA extracted from whole blood of a group of non-family related AN patients and a group of healthy controls. Our first analysis using the twin sample revealed 9 CpGs associated to a gene. The validation analysis showed two statistically significant CpGs with the rank regression method related to two genes associated to metabolic traits, PPP2R2C and CHST1. When doing beta regression, 6 of them showed statistically significant differences, including 3 CpGs associated to genes JAM3, UBAP2L and SYNJ2.Finally, the overall pattern of results shows genetic links to phenotypes which the literature has constantly related to AN, including metabolic and psychological traits. The genes PPP2R2C and CHST1 have both been linked to the metabolic traits type 2 diabetes through GWAS studies. The genes UBAP2L and SYNJ2 have been related to other psychiatric comorbidity.