Meta-analysis of genome-wide studies identifies MEF2C SNPs associated with bone mineral density at forearm
Bibliographic record
Abstract
Background Forearm fractures affect 1.7 million individuals worldwide each year and most occur earlier in life than hip fractures. While the heritability of forearm bone mineral density (BMD) and fracture is high, their genetic determinants are largely unknown. Aim To identify genetic variants associated with forearm BMD and forearm fractures. Methods BMD at distal radius, measured by dualenergy x-ray absorptiometry, was tested for association with common genetic variants. We conducted a metaanalysis of genome-wide association studies for BMD in 5866 subjects of European descent and then selected the variants for replication in 715 Mexican American samples. Gene-based association was carried out to supplement the single-nucleotide polymorphism (SNP) association test. We then tested the BMD-associated SNPs for association with forearm fracture in 2023 cases and 3740 controls. Results We found that five SNPs in the introns of MEF2C were associated with forearm BMD at a genome-wide significance level (p<5×10-8) in meta-analysis (lead SNP, rs11951031[T] -0.20 SDs per allele, p=9.01×10-9). The gene-based association test suggested an association between MEF2C and forearm BMD ( p=0.003). The association between MEF2C variants and risk of fracture did not achieve statistical significance (SNP rs12521522[A]: OR=1.14 (95% CI 0.92 to 1.35), p=0.14). Meta-analysis also revealed two genome-wide suggestive loci at CTNNA2 and 6q23.2. Conclusions These findings demonstrate that variants at MEF2C were associated with forearm BMD, implicating this gene in the determination of BMD at forearm.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".