# Investigating the Sexual Dimorphism of Waist-to-Hip Ratio and Its Associations with Complex Traits

## TL;DR

This study explores how waist-to-hip ratio differs between sexes and how it relates to various health traits, revealing sex-specific genetic and biological patterns.

## Contribution

The study identifies sex-specific genetic markers and associations of waist-to-hip ratio with complex traits using large-scale genetic and health data.

## Key findings

- Sex-specific heritability of waist-to-hip ratio was identified, with genes like CCDC92 in females and UQCC1 in males.
- Genetic correlations revealed 23 sex-specific traits linked to waist-to-hip ratio and eight loci across five diseases.
- Regression analysis showed stronger associations with waist-to-hip ratio in females compared to males.

## Abstract

Background: Obesity significantly impacts disease burden, with waist-to-hip ratio (WHR) as a key obesity indicator, but the genetic and biological pathways underlying WHR, particularly its sex-specific differences, remain poorly understood. Methods: This study explored WHR’s sexual dimorphism and its links to complex traits using cross-sectional surveys and genetic data from Giant and UK Biobank (UKB). We analyzed WHR heritability, performed tissue-specific transcriptome-wide association studies (TWAS) using FUSION, and conducted genetic correlation analyses with linkage disequilibrium score regression (LDSC) and Local Analysis of [co]Variant Association (LAVA). Polygenic scores (PGS) for WHR were constructed using the clumping and thresholding method (CT), and associations with complex traits were assessed via logistic or linear models. Results: The genetic analysis showed sex-specific heritability for WHR, with TWAS identifying female-specific (e.g., CCDC92) and male-specific (e.g., UQCC1) genes. Global genetic correlation analysis revealed sex-specific associations between WHR and 23 traits, while local analysis identified eight sex-specific loci across five diseases. Regression analysis highlighted sex-specific associations for 70 traits with WHR and 45 traits with WHR PGS, with stronger effects in females. Predictive models also performed better in females. Conclusions: This study underscores WHR’s sexual dimorphism and its distinct associations with complex traits, offering insights into sex-specific biological differences, health management, and clinical advancements.