Meta-analysis of genome-wide studies identifies <i>WNT16</i> and <i>ESR1</i> SNPs associated with bone mineral density in premenopausal women
Bibliographic record
Abstract
Previous genome-wide association studies (GWAS) have identified common variants in genes associated with variation in bone mineral density (BMD), although most have been carried out in combined samples of older women and men. Meta-analyses of these results have identified numerous single-nucleotide polymorphisms (SNPs) of modest effect at genome-wide significance levels in genes involved in both bone formation and resorption, as well as other pathways. We performed a meta-analysis restricted to premenopausal white women from four cohorts (n = 4061 women, aged 20 to 45 years) to identify genes influencing peak bone mass at the lumbar spine and femoral neck. After imputation, age- and weight-adjusted bone-mineral density (BMD) values were tested for association with each SNP. Association of an SNP in the WNT16 gene (rs3801387; p = 1.7 × 10(-9) ) and multiple SNPs in the ESR1/C6orf97 region (rs4870044; p = 1.3 × 10(-8) ) achieved genome-wide significance levels for lumbar spine BMD. These SNPs, along with others demonstrating suggestive evidence of association, were then tested for association in seven replication cohorts that included premenopausal women of European, Hispanic-American, and African-American descent (combined n = 5597 for femoral neck; n = 4744 for lumbar spine). When the data from the discovery and replication cohorts were analyzed jointly, the evidence was more significant (WNT16 joint p = 1.3 × 10(-11) ; ESR1/C6orf97 joint p = 1.4 × 10(-10) ). Multiple independent association signals were observed with spine BMD at the ESR1 region after conditioning on the primary signal. Analyses of femoral neck BMD also supported association with SNPs in WNT16 and ESR1/C6orf97 (p < 1 × 10(-5) ). Our results confirm that several of the genes contributing to BMD variation across a broad age range in both sexes have effects of similar magnitude on BMD of the spine in premenopausal women. These data support the hypothesis that variants in these genes of known skeletal function also affect BMD during the premenopausal period.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".