Genetic Factors Associated With Human Physical Activity: Are Your Genes Too Tight To Prevent You Exercising?
Bibliographic record
Abstract
The benefits of physical activity (PA) on health and fitness are well known. It has become apparent from studies of heritability that there is a considerable genetic component to PA. However, PA is such a complex phenotype that the measurement and quantification of it provide a challenge to a clearer understanding of its genetic basis. In this review, we assessed available evidence from family and twin studies that have estimated the heritability of PA. Heritability is greater when evaluated by accelerometry compared with questionnaires, and for questionnaires higher in twin than family studies. Accelerometry studies suggest heritability of PA is 51% to 56%. There have been many genome-wide linkage studies, candidate gene studies, and four genome-wide association studies that have highlighted specific genetic factors linked to different PA levels. These studies have generally failed to replicate identified loci, with the exception of the melanocortin 4 receptor, and this may be because of the variability in the measurement techniques used to characterize the behavior. Future work should aim to standardize the procedures used to measure PA in the context of trying to identify genetic causes. The link of genetics to physical exercise is not so tight that it prevents voluntary interventions.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".