A GWAS for grip strength in cohorts of children – advantages of analysing young participants for this trait
Bibliographic record
Abstract
Abstract Grip strength (GS) is a proxy measure for muscular strength and a predictor for bone fracture risk among other diseases. Previous genome-wide association studies (GWAS) have been conducted in large cohorts of adults focusing on scores collected for the dominant hand, therefore increasing the likelihood of confounding effects by environmental factors. Here, we perform the first GWAS meta-analyses on maximal GS with the dominant (GSD) and non-dominant (GSND) hand in two cohorts of children (ALSPAC, N = 5,450; age range = 10.65 – 13.61; Raine Study, N = 1,162, age range: 9.42-12.38 years). We identified a novel significant association for GSND (rs9546244, LINC02465 , p = 3.43e-08 ) and replicated associations previously reported in adults including with a HOXB3 gene marker that shows an eQTL effect. Despite a much smaller sample (∼3%) compared to the UK Biobank we replicated correlation and polygenic risk score (PRS) analyses previously reported in this much larger adult cohort. Specifically, we observed genetic correlations with coronary artery disease and a PRS association with the risk of overall fracture. Furthermore, we observed a higher SNP-heritability (24-41%) compared to previous studies (4-24%) in adults. Our results suggest that cohorts of children might be better suited for genetic studies of grip strength, possibly due to the shorter exposure to confounding environmental factors compared to adults.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".