| Title: | Investigating the Sexual Dimorphism of Waist-to-Hip Ratio and Its Associations with Complex Traits |
| Journal: | Genes |
| Published: | 16 Jun 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40565603/ |
| DOI: | https://doi.org/10.3390/genes16060711 |
Publication 16273
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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.</p>
12 Keywords
- Cross-Sectional Studies
- Female
- Genome-Wide Association Study
- Humans
- Linkage Disequilibrium
- Male
- Middle Aged
- Multifactorial Inheritance
- Obesity
- Sex Characteristics
- Transcriptome
- Waist-Hip Ratio
8 Authors
- Haochang Li
- Shirong Hui
- Xuehong Cai
- Ran He
- Meijie Yu
- Yihao Li
- Rongbin Yu
- Peng Huang
1 Application
| Application ID | Title |
|---|---|
| 144904 | Integrative Deep Learning Analysis of UKBB Data: Bridging Genotypes, Medical Imaging, and Polygenic Scores for Precision Health Insights |
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