Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study

Camilla Williams, Zhixiu Li, Nicholas Harvey, Rodney Lea, Brendon Gurd, Jacob Bonafiglia, Ioannis Papadimitriou, Macsue Jacques, Ilaria Croci, Dorthe Stensvold, Ulrik Wisloff, Jenna Taylor, Trishan Gajanand, Emily Cox, Joyce Ramos, Robert Fassett, Jonathan Little, Monique Francois, Christopher Hearon Jr, Satyam SarmaSylvan Jannsen, Emiline Craenenbroeck, Paul Beckers, Veronique Cornelissen, Erin Howden, Shelley Keating, Xu Yan, David Bishop, Anja Bye, Larisa Haupt, Lyn Griffiths, Kevin Ashton, Matthew Brown, Luciana Torquati, Nir Eynon, Jeff Coombes

    Research output: Contribution to journalArticlepeer-review

    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 2peak response following exercise training. Methods: Participant change in objectively measured V̇O 2peak 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 2peak 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 2peak , 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 2peak 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 2peak 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 2peak response variance, and whether genomic predictors for V̇O 2peak 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.

    Original languageEnglish
    Article number37
    Number of pages15
    JournalJournal of Biomedical Science
    Volume28
    Issue number1
    DOIs
    Publication statusPublished - 13 May 2021

    Keywords

    • GWAS
    • Genetics
    • Individual variability
    • Polygenic predictor score
    • V̇O peak training response

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