Genome-wide association study meta-analysis for quantitative ultrasound parameters of bone identifies five novel loci for broadband ultrasound attenuation
Bibliographic record
Abstract
Osteoporosis is a common and debilitating bone disease that is characterised by low bone mineral density, typically assessed using dual-energy X-ray absorptiometry. Quantitative ultrasound (QUS), commonly utilising the two parameters velocity of sound (VOS) and broadband ultrasound attenuation (BUA), is an alternative technology used to assess bone properties at peripheral skeletal sites. The genetic influence on the bone qualities assessed by QUS remains an under-studied area. We performed a comprehensive genome-wide association study (GWAS) including low-frequency variants (minor allele frequency ≥0.005) for BUA and VOS using a discovery population of individuals with whole-genome sequence (WGS) data from the UK10K project (n = 1268). These results were then meta-analysed with those from two deeply imputed GWAS replication cohorts (n = 1610 and 13 749). In the gender-combined analysis, we identified eight loci associated with BUA and five with VOS at the genome-wide significance level, including three novel loci for BUA at 8p23.1 (PPP1R3B), 11q23.1 (LOC387810) and 22q11.21 (SEPT5) (P = 2.4 × 10-8 to 1.6 × 10-9). Gene-based association testing in the gender-combined dataset revealed eight loci associated with BUA and seven with VOS after correction for multiple testing, with one novel locus for BUA at FAM167A (8p23.1) (P = 1.4 × 10-6). An additional novel locus for BUA was seen in the male-specific analysis at DEFB103B (8p23.1) (P = 1.8 × 10-6). Fracture analysis revealed significant associations between variation at the WNT16 and RSPO3 loci and fracture risk (P = 0.004 and 4.0 × 10-4, respectively). In conclusion, by performing a large GWAS meta-analysis for QUS parameters of bone using a combination of WGS and deeply imputed genotype data, we have identified five novel genetic loci associated with BUA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".