# Exploring the Genetic Overlap Between Metabolic Traits and Anorexia Nervosa

## TL;DR

This study explores the genetic links between anorexia nervosa and metabolic traits, identifying shared genetic regions and potential biological mechanisms.

## Contribution

The study identifies specific genomic regions and shared genes that may explain the genetic overlap between anorexia nervosa and metabolic traits.

## Key findings

- Significant local genetic correlations were found across 60 regions between anorexia nervosa and metabolic traits.
- Three genomic regions showed strong evidence of colocalization with shared variants for high-density lipoprotein and body mass index.
- The study identified independent genomic regions and shared genes that may explain the biological link between anorexia nervosa and metabolic dysregulation.

## Abstract

Anorexia nervosa (AN) is an eating disorder with complex biology that remains largely uncharacterized. Recent genome-wide association studies have identified genetic associations between metabolic traits and AN that may relate to the underlying pathophysiology of the condition. Moreover, observational studies have identified evidence of dysregulated metabolic traits in AN, with emerging evidence suggesting that some of these findings are also observed in weight-restored individuals. While there is evidence for putative shared genetic factors linking metabolic traits and AN, the biology underpinning these genetic relationships has not been thoroughly investigated.

To further explore shared genetic architecture between metabolic traits and AN with regional specificity, we investigated spatially localized genetic correlation and Bayesian colocalization between 6 metabolic traits (body mass index, high-density lipoprotein, leptin, fasting insulin, insulin resistance, and type 2 diabetes) (n = 30,931–659,316) and AN (n = 72,517).

Significant local genetic correlation was identified across 60 regions, between genetic liability to AN and one of the 6 metabolic traits, after Benjamini-Hochberg correction. Three of these regions showed strong evidence of colocalization with a shared variant (posterior probability > 0.8), indicating potential functional mechanisms related to the trait associations for high-density lipoprotein and body mass index.

Using evidence of local genetic correlation and colocalization, we found independent regions of the genome that may determine the genome-wide genetic correlation between metabolic traits and AN and identified specific shared genes which may assist with our mechanistic understanding of the inherent biological link between AN and metabolites.

Anorexia nervosa is a psychiatric disorder influenced by both genetic and environmental components. Emerging evidence suggests that there may be underlying metabolic dysregulation present in the disorder rather than it solely being a consequence of food restriction. Genome-wide association studies are available that measure the association between genetic variants, metabolic traits, and anorexia nervosa, which can be used to investigate the relationship between these traits. Utilizing these data, we identified genetic variants and regions of the genome that are associated with both metabolic dysregulation and increased risk of anorexia nervosa. These variants may function through genes and explain the biological mechanisms through which these traits are associated.

Anorexia nervosa is a psychiatric disorder influenced by both genetic and environmental components. Emerging evidence suggests that there may be underlying metabolic dysregulation present in the disorder rather than it solely being a consequence of food restriction. Genome-wide association studies are available that measure the association between genetic variants, metabolic traits, and anorexia nervosa, which can be used to investigate the relationship between these traits. Utilizing these data, we identified genetic variants and regions of the genome that are associated with both metabolic dysregulation and increased risk of anorexia nervosa. These variants may function through genes and explain the biological mechanisms through which these traits are associated.