Genetic Associations With Acceleration, Change of Direction, Jump Height, and Speed in English Academy Football Players
Bibliographic record
Abstract
ABSTRACT: McAuley, ABT, Hughes, DC, Tsaprouni, LG, Varley, I, Suraci, B, Bradley, B, Baker, J, Herbert, AJ, and Kelly, AL. Genetic associations with acceleration, change of direction, jump height, and speed in English academy football players. J Strength Cond Res 38(2): 350-359, 2024-High-intensity movements and explosive actions are commonly assessed during athlete development in football (soccer). Although many environmental factors underpin these power-orientated traits, research suggests that there is also a sizeable genetic component. Therefore, this study examined the association of 22 single-nucleotide polymorphisms (SNPs) with acceleration, change of direction, jump height, and speed in academy football players. One hundred and forty-nine, male, under-12 to under-23 football players from 4 English academies were examined. Subjects performed 5-, 10-, 20-, and 30-m sprints, countermovement jumps (CMJs), and the 5-0-5 agility test. Simple linear regression was used to analyze individual SNP associations, whereas both unweighted and weighted total genotype scores (TGS; TWGS) were computed to measure the combined influence of all SNPs. To control for multiple testing, a Benjamini-Hochberg false discovery rate of 0.05 was applied to all genotype model comparisons. In isolation, the GALNT13 (rs10196189) G allele and IL6 (rs1800795) G/G genotype were associated with faster (∼4%) 5-, 10-, and 20-m sprints and higher (∼16%) CMJs, respectively (p < 0.001). Furthermore, the TGS and TWGS significantly correlated with all performance assessments, explaining between 6 and 33% of the variance (p < 0.001). This study demonstrates that some genetic variants are associated with power-orientated phenotypes in youth football players and may add value toward a future polygenic profile of physical performance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".