Genome-wide Association Studies Reveal Novel Locus With Sex-/Therapy-Specific Fracture Risk Effects in Childhood Cancer Survivors
Bibliographic record
Abstract
ABSTRACT Childhood cancer survivors treated with radiation therapy (RT) and osteotoxic chemotherapies are at increased risk for fractures. However, understanding of how genetic and clinical susceptibility factors jointly contribute to fracture risk among survivors is limited. To address this gap, we conducted genome-wide association studies of fracture risk after cancer diagnosis in 2453 participants of European ancestry from the Childhood Cancer Survivor Study (CCSS) with 930 incident fractures using Cox regression models (ie, time-to-event analysis) and prioritized sex- and treatment-stratified genetic associations. We performed replication analyses in 1417 survivors of European ancestry with 652 incident fractures from the St. Jude Lifetime Cohort Study (SJLIFE). In discovery, we identified a genome-wide significant (p < 5 × 10−8) fracture risk locus, 16p13.3 (HAGHL), among female CCSS survivors (n = 1289) with strong evidence of sex-specific effects (psex-heterogeneity < 7 × 10−6). Combining discovery and replication data, rs1406815 showed the strongest association (hazard ratio [HR] = 1.43, p = 8.2 × 10−9; n = 1935 women) at this locus. In treatment-stratified analyses in the discovery cohort, the association between rs1406815 and fracture risk among female survivors with no RT exposures was weak (HR = 1.22, 95% confidence interval [CI] 0.95–1.57, p = 0.11) but increased substantially among those with greater head/neck RT doses (any RT: HR = 1.88, 95% CI 1.54–2.28, p = 2.4 × 10−10; >36 Gray only: HR = 3.79, 95% CI 1.95–7.34, p = 8.2 × 10−5). These head/neck RT-specific HAGHL single-nucleotide polymorphism (SNP) effects were replicated in female SJLIFE survivors. In silico bioinformatics analyses suggest these fracture risk alleles regulate HAGHL gene expression and related bone resorption pathways. Genetic risk profiles integrating this locus may help identify female survivors who would benefit from targeted interventions to reduce fracture risk. © 2020 American Society for Bone and Mineral Research (ASBMR).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".