Increased Burden of Common Risk Alleles in Children With a Significant Fracture History
Bibliographic record
Abstract
ABSTRACT Extreme presentations of common disease in children are often presumed to be of Mendelian etiology, but their polygenic basis has not been fully explored. We tested whether children with significant fracture history and no osteogenesis imperfecta (OI) are at increased polygenic risk for fracture. A childhood significant fracture history was defined as the presence of low-trauma vertebral fractures or multiple long bone fractures. We generated a polygenic score of heel ultrasound-derived speed of sound, termed “gSOS,” which predicts risk of osteoporotic fracture. We tested if individuals from three cohorts with significant childhood fracture history had lower gSOS. A Canadian cohort included 94 children with suspected Mendelian osteoporosis, of which 68 had negative OI gene panel. Two Finnish cohorts included 59 children with significant fracture history and 22 with suspected Mendelian osteoporosis, among which 18 had no OI. After excluding individuals with OI and ancestral outliers, we generated gSOS estimates and compared their mean to that of a UK Biobank subset, representing the general population. The average gSOS across all three cohorts (n = 131) was −0.47 SD lower than that in UK Biobank (n = 80,027, p = 1.1 × 10−5). The gSOS of 78 individuals with suspected Mendelian osteoporosis was even lower (−0.76 SD, p = 5.3 × 10−10). Among the 131 individuals with a significant fracture history, we observed 8 individuals with gSOS below minus 2 SD from the mean; their mean lumbar spine DXA-derived bone mineral density Z-score was −1.7 (SD 0.8). In summary, children with significant fracture history but no OI have an increased burden of common risk alleles. This suggests that a polygenic contribution to disease should be considered in children with extreme presentations of fracture. © 2020 American Society for Bone and Mineral Research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".