@article {328780,
	title = {The genetic architecture and evolution of the human skeletal form},
	journal = {ScienceScience},
	volume = {381},
	year = {2023},
	note = {<p>doi: 10.1126/science.adf8009</p>
},
	pages = {eadf8009},
	abstract = {<p>The human skeletal form underlies bipedalism, but the genetic basis of skeletal proportions (SPs) is not well characterized. We applied deep-learning models to 31,221 x-rays from the UK Biobank to extract a comprehensive set of SPs, which were associated with 145 independent loci genome-wide. Structural equation modeling suggested that limb proportions exhibited strong genetic sharing but were independent of width and torso proportions. Polygenic score analysis identified specific associations between osteoarthritis and hip and knee SPs. In contrast to other traits, SP loci were enriched in human accelerated regions and in regulatory elements of genes that are differentially expressed between humans and great apes. Combined, our work identifies specific genetic variants that affect the skeletal form and ties a major evolutionary facet of human anatomical change to pathogenesis. Many skeletal changes occurred on the path to modern humans, resulting in bipedalism but also susceptibility to musculoskeletal diseases. Kun et al. used imaging data from more than 30,000 UK Biobank participants to characterize skeletal proportions, assessing the genetic basis of these features, as well as their relationships to each other. They found that limb proportions are uncorrelated with body width proportions, that there are associations between hip- and leg-related skeletal proportions and osteoarthritis, and that there is enrichment for loci associated with skeletal proportion in genomic regions associated with human-specific evolution. This study demonstrates the utility of using imaging data from biobanks to understand both disease-related and normal physical variation among humans. ?Corinne Simonti Applying deep learning models to x-ray imaging data elucidates relationships between and the genetic basis for skeletal proportions.The human skeletal form underlies bipedalism, but the genetic basis of skeletal proportions (SPs) is not well characterized. We applied deep-learning models to 31,221 x-rays from the UK Biobank to extract a comprehensive set of SPs, which were associated with 145 independent loci genome-wide. Structural equation modeling suggested that limb proportions exhibited strong genetic sharing but were independent of width and torso proportions. Polygenic score analysis identified specific associations between osteoarthritis and hip and knee SPs. In contrast to other traits, SP loci were enriched in human accelerated regions and in regulatory elements of genes that are differentially expressed between humans and great apes. Combined, our work identifies specific genetic variants that affect the skeletal form and ties a major evolutionary facet of human anatomical change to pathogenesis. Many skeletal changes occurred on the path to modern humans, resulting in bipedalism but also susceptibility to musculoskeletal diseases. Kun et al. used imaging data from more than 30,000 UK Biobank participants to characterize skeletal proportions, assessing the genetic basis of these features, as well as their relationships to each other. They found that limb proportions are uncorrelated with body width proportions, that there are associations between hip- and leg-related skeletal proportions and osteoarthritis, and that there is enrichment for loci associated with skeletal proportion in genomic regions associated with human-specific evolution. This study demonstrates the utility of using imaging data from biobanks to understand both disease-related and normal physical variation among humans. ?Corinne Simonti Applying deep learning models to x-ray imaging data elucidates relationships between and the genetic basis for skeletal proportions.</p>
},
	url = {https://doi.org/10.1126/science.adf8009},
	author = {Kun, Eucharist and Javan, Emily M. and Smith, Olivia and Gulamali, Faris and de la Fuente, Javier and Flynn, Brianna I. and Vajrala, Kushal and Trutner, Zoe and Jayakumar, Prakash and Tucker-Drob, Elliot M. and Sohail, Mashaal and Singh, Tarjinder and Narasimhan, Vagheesh M.}
}
