The Human Gene Map for Performance and Health-Related Fitness Phenotypes
Bibliographic record
Abstract
This update of the human gene map for physical performance and health-related fitness phenotypes covers the research advances reported in 2006 and 2007. The genes and markers with evidence of association or linkage with a performance or a fitness phenotype in sedentary or active people, in responses to acute exercise, or for training-induced adaptations are positioned on the map of all autosomes and sex chromosomes. Negative studies are reviewed, but a gene or a locus must be supported by at least one positive study before being inserted on the map. A brief discussion on the nature of the evidence and on what to look for in assessing human genetic studies of relevance to fitness and performance is offered in the introduction, followed by a review of all studies published in 2006 and 2007. The findings from these new studies are added to the appropriate tables that are designed to serve as the cumulative summary of all publications with positive genetic associations available to date for a given phenotype and study design. The fitness and performance map now includes 214 autosomal gene entries and quantitative trait loci plus seven others on the X chromosome. Moreover, there are 18 mitochondrial genes that have been shown to influence fitness and performance phenotypes. Thus, the map is growing in complexity. Although the map is exhaustive for currently published accounts of genes and exercise associations and linkages, there are undoubtedly many more gene-exercise interaction effects that have not even been considered thus far. Finally, it should be appreciated that most studies reported to date are based on small sample sizes and cannot therefore provide definitive evidence that DNA sequence variants in a given gene are reliably associated with human variation in fitness and performance traits.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.022 |
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".