Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study
Bibliographic record
Abstract
Abstract Background Low cardiorespiratory fitness (V̇O 2peak ) is highly associated with chronic disease and mortality from all causes. Whilst exercise training is recommended in health guidelines to improve V̇O 2peak , there is considerable inter-individual variability in the V̇O 2peak response to the same dose of exercise. Understanding how genetic factors contribute to V̇O 2peak training response may improve personalisation of exercise programs. The aim of this study was to identify genetic variants that are associated with the magnitude of V̇O 2 peak response following exercise training. Methods Participant change in objectively measured V̇O 2 peak from 18 different interventions was obtained from a multi-centre study (Predict-HIIT). A genome-wide association study was completed (n = 507), and a polygenic predictor score (PPS) was developed using alleles from single nucleotide polymorphisms (SNPs) significantly associated ( P < 1 × 10 –5 ) with the magnitude of V̇O 2 peak response. Findings were tested in an independent validation study (n = 39) and compared to previous research. Results No variants at the genome-wide significance level were found after adjusting for key covariates (baseline V̇O 2 peak , individual study, principal components which were significantly associated with the trait). A Quantile–Quantile plot indicates there was minor inflation in the study. Twelve novel loci showed a trend of association with V̇O 2 peak response that reached suggestive significance ( P < 1 × 10 –5 ). The strongest association was found near the membrane associated guanylate kinase, WW and PDZ domain containing 2 ( MAGI2 ) gene (rs6959961, P = 2.61 × 10 –7 ). A PPS created from the 12 lead SNPs was unable to predict V̇O 2 peak response in a tenfold cross validation, or in an independent (n = 39) validation study ( P > 0.1). Significant correlations were found for beta coefficients of variants in the Predict-HIIT ( P < 1 × 10 –4 ) and the validation study ( P < × 10 –6 ), indicating that general effects of the loci exist, and that with a higher statistical power, more significant genetic associations may become apparent. Conclusions Ongoing research and validation of current and previous findings is needed to determine if genetics does play a large role in V̇O 2 peak response variance, and whether genomic predictors for V̇O 2 peak response trainability can inform evidence-based clinical practice. Trial registration Australian New Zealand Clinical Trials Registry (ANZCTR), Trial Id: ACTRN12618000501246, Date Registered: 06/04/2018, http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374601&isReview=true .
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".