The human skeletal form underlies our ability to walk on two legs, but unlike standing height, the genetic basis of limb lengths and skeletal proportions is less well understood. Here we applied a deep learning model to 31,221 whole body dual-energy X-ray absorptiometry (DXA) images from the UK Biobank (UKB) to extract 23 different image-derived phenotypes (IDPs) that include all long bone lengths as well as hip and shoulder width, which we analyzed while controlling for height. All skeletal proportions are highly heritable (~40-50%), and genome-wide association studies (GWAS) of these traits identified 179 independent loci, of which 102 loci were not associated with height. These loci are enriched in genes regulating skeletal development as well as associated with rare human skeletal diseases and abnormal mouse skeletal phenotypes. Genetic correlation and genomic structural equation modeling indicated that limb proportions exhibited strong genetic sharing but were genetically independent of width and torso proportions. Phenotypic and polygenic risk score analyses identified specific associations between osteoarthritis (OA) of the hip and knee, the leading causes of adult disability in the United States, and skeletal proportions of the corresponding regions. We also found genomic evidence of evolutionary change in arm-to-leg and hip-width proportions in humans consistent with striking anatomical changes in these skeletal proportions in the hominin fossil record. In contrast to cardiovascular, auto-immune, metabolic, and other categories of traits, loci associated with these skeletal proportions are significantly enriched in human accelerated regions (HARs), and regulatory elements of genes differentially expressed through development between humans and the great apes. Taken together, our work validates the use of deep learning models on DXA images to identify novel and specific genetic variants affecting the human skeletal form and ties a major evolutionary facet of human anatomical change to pathogenesis.

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.

BackgroundMusculoskeletal providers are increasingly recognizing the importance of social factors and their association with health outcomes as they aim to develop more comprehensive models of care delivery. Such factors may account for some of the unexplained variation between pathophysiology and level of pain intensity and incapability experienced by people with common conditions, such as persistent nontraumatic knee pain secondary to osteoarthritis (OA). Although the association of one’s social position (for example, income, employment, or education) with levels of pain and capability are often assessed in OA research, the relationship between aspects of social context (or unmet social needs) and such symptomatic and functional outcomes in persistent knee pain are less clear.Questions/purposes(1) Are unmet social needs associated with the level of capability in patients experiencing persistently painful nontraumatic knee conditions, accounting for sociodemographic factors? (2) Do unmet health-related social needs correlate with self-reported quality of life?MethodsWe performed a prospective, cross-sectional study between January 2021 and August 2021 at a university academic medical center providing comprehensive care for patients with persistent lower extremity joint pain secondary to nontraumatic conditions such as age-related knee OA. A final 125 patients were included (mean age 62 ± 10 years, 65% [81 of 125] women, 47% [59 of 125] identifying as White race, 36% [45 of 125] as Hispanic or Latino, and 48% [60 of 125] with safety-net insurance or Medicaid). We measured patient-reported outcomes of knee capability (Knee injury and Osteoarthritis Outcome Score for Joint Replacement), quality of life (Patient-Reported Outcome Measure Information System [PROMIS] Global Physical Health and PROMIS Global Mental Health), and unmet social needs (Accountable Health Communities Health-Related Social Needs Survey, accounting for insufficiencies related to housing, food, transportation, utilities, and interpersonal violence), as well as demographic factors.ResultsAfter controlling for demographic factors such as insurance status, education attained, and household income, we found that reduced knee-specific capability was moderately associated with experiencing unmet social needs (including food insecurity, housing instability, transportation needs, utility needs, or interpersonal safety) (standardized beta regression coefficient [β] = -4.8 [95% confidence interval -7.9 to -1.7]; p = 0.002 and substantially associated with unemployment (β = -13 [95% CI -23 to -3.8]; p = 0.006); better knee-specific capability was substantially associated with having Medicare insurance (β = 12 [95% CI 0.78 to 23]; p = 0.04). After accounting for factors such as insurance status, education attained, and household income, we found that older age was associated with better general mental health (β = 0.20 [95% CI 0.0031 to 0.39]; p = 0.047) and with better physical health (β = 0.004 [95% CI 0.0001 to 0.008]; p = 0.04), but effect sizes w...

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