ACTN3 genotype predicts metabolic, anthropometric and cardiovascular phenotypes in a young, healthy population (711.8)
Bibliographic record
Abstract
Exercise‐related polymorphisms have played an important role in shaping human evolution. One such polymorphism, ACTN3 R577X, is overrepresented in endurance athletes and centenarians suggesting an association with favorable metabolic health. As such, we examined the influence of ACTN3 genotype on health‐related phenotypes in young subjects (age 18‐35) from the Assessing Inherent Markers for Metabolic syndrome in the Young (AIMMY) study (n=188). Cardiovascular, anthropometric, metabolic and body composition characteristics were assessed. ACTN3 genotype was associated with BMI in a sex specific manner, with null (XX) females having higher scores, while male positive (RR/RX) allele carriers had greater scores compared to XX males (p<0.05). Similarly, body fat percentage and waist circumference measurements were higher in females of the XX genotype compared to RR/RX allele carriers (p<0.05). In males, body circumferences and waist:hip ratio were higher in RR/RX allele carriers compared to XX individuals. Interestingly, Male RR/RX allele carriers had higher blood glucose and diastolic blood pressure than XX males. It was also found that female RR/RX carriers had higher VO 2 peak scores than XX females (p<0.05). Metabolic and cardiovascular associations with ACTN3 genotype may offer novel insight into predicted athletic performance and disease risk.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".