Genetic Insights into Head-to-Body Ratios Via Deep Learning-Based Image Segmentation and Implications for Common Diseases.

ABSTRACT: Head-to-body ratios (HBRs) are important anthropometric traits with direct relevance to human growth, development, and disease risk. However, the role of the proportions between head and body remains understudied, with the genetic basis of HBRs remaining largely unexplored. By applying deep learning models to 38,202 whole-body dual-energy X-ray absorptiometry images from the UK Biobank, we generated 10 distinct HBR phenotypes based on head (length/width) and various body dimensions. Our genome-wide association analyses identify 245 significant loci, with SNP-based heritability estimates ranging from 25% to 43%. Functional annotations show that genes prioritized for HBRs are enriched in chondrocytes in skeletal tissues and oligodendrocytes across multiple brain regions. Polygenic risk score

SUBMITTER: Shi W 

PROVIDER: S-EPMC12827411 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature