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

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 sam...

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Autores principales: Williams, Camilla J., Li, Zhixiu, Harvey, Nicholas, Lea, Rodney A., Gurd, Brendon J., Bonafiglia, Jacob T., Papadimitriou, Ioannis, Jacques, Macsue, Croci, Ilaria, Stensvold, Dorthe, Wisloff, Ulrik, Taylor, Jenna L., Gajanand, Trishan, Cox, Emily R., Ramos, Joyce S., Fassett, Robert G., Little, Jonathan P., Francois, Monique E., Hearon, Christopher M., Sarma, Satyam, Janssen, Sylvan L. J. E., Van Craenenbroeck, Emeline M., Beckers, Paul, Cornelissen, Véronique A., Howden, Erin J., Keating, Shelley E., Yan, Xu, Bishop, David J., Bye, Anja, Haupt, Larisa M., Griffiths, Lyn R., Ashton, Kevin J., Brown, Matthew A., Torquati, Luciana, Eynon, Nir, Coombes, Jeff S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8117553/
https://www.ncbi.nlm.nih.gov/pubmed/33985508
http://dx.doi.org/10.1186/s12929-021-00733-7
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author Williams, Camilla J.
Li, Zhixiu
Harvey, Nicholas
Lea, Rodney A.
Gurd, Brendon J.
Bonafiglia, Jacob T.
Papadimitriou, Ioannis
Jacques, Macsue
Croci, Ilaria
Stensvold, Dorthe
Wisloff, Ulrik
Taylor, Jenna L.
Gajanand, Trishan
Cox, Emily R.
Ramos, Joyce S.
Fassett, Robert G.
Little, Jonathan P.
Francois, Monique E.
Hearon, Christopher M.
Sarma, Satyam
Janssen, Sylvan L. J. E.
Van Craenenbroeck, Emeline M.
Beckers, Paul
Cornelissen, Véronique A.
Howden, Erin J.
Keating, Shelley E.
Yan, Xu
Bishop, David J.
Bye, Anja
Haupt, Larisa M.
Griffiths, Lyn R.
Ashton, Kevin J.
Brown, Matthew A.
Torquati, Luciana
Eynon, Nir
Coombes, Jeff S.
author_facet Williams, Camilla J.
Li, Zhixiu
Harvey, Nicholas
Lea, Rodney A.
Gurd, Brendon J.
Bonafiglia, Jacob T.
Papadimitriou, Ioannis
Jacques, Macsue
Croci, Ilaria
Stensvold, Dorthe
Wisloff, Ulrik
Taylor, Jenna L.
Gajanand, Trishan
Cox, Emily R.
Ramos, Joyce S.
Fassett, Robert G.
Little, Jonathan P.
Francois, Monique E.
Hearon, Christopher M.
Sarma, Satyam
Janssen, Sylvan L. J. E.
Van Craenenbroeck, Emeline M.
Beckers, Paul
Cornelissen, Véronique A.
Howden, Erin J.
Keating, Shelley E.
Yan, Xu
Bishop, David J.
Bye, Anja
Haupt, Larisa M.
Griffiths, Lyn R.
Ashton, Kevin J.
Brown, Matthew A.
Torquati, Luciana
Eynon, Nir
Coombes, Jeff S.
author_sort Williams, Camilla J.
collection PubMed
description 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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spelling pubmed-81175532021-05-13 Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study Williams, Camilla J. Li, Zhixiu Harvey, Nicholas Lea, Rodney A. Gurd, Brendon J. Bonafiglia, Jacob T. Papadimitriou, Ioannis Jacques, Macsue Croci, Ilaria Stensvold, Dorthe Wisloff, Ulrik Taylor, Jenna L. Gajanand, Trishan Cox, Emily R. Ramos, Joyce S. Fassett, Robert G. Little, Jonathan P. Francois, Monique E. Hearon, Christopher M. Sarma, Satyam Janssen, Sylvan L. J. E. Van Craenenbroeck, Emeline M. Beckers, Paul Cornelissen, Véronique A. Howden, Erin J. Keating, Shelley E. Yan, Xu Bishop, David J. Bye, Anja Haupt, Larisa M. Griffiths, Lyn R. Ashton, Kevin J. Brown, Matthew A. Torquati, Luciana Eynon, Nir Coombes, Jeff S. J Biomed Sci Research 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. BioMed Central 2021-05-13 /pmc/articles/PMC8117553/ /pubmed/33985508 http://dx.doi.org/10.1186/s12929-021-00733-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Williams, Camilla J.
Li, Zhixiu
Harvey, Nicholas
Lea, Rodney A.
Gurd, Brendon J.
Bonafiglia, Jacob T.
Papadimitriou, Ioannis
Jacques, Macsue
Croci, Ilaria
Stensvold, Dorthe
Wisloff, Ulrik
Taylor, Jenna L.
Gajanand, Trishan
Cox, Emily R.
Ramos, Joyce S.
Fassett, Robert G.
Little, Jonathan P.
Francois, Monique E.
Hearon, Christopher M.
Sarma, Satyam
Janssen, Sylvan L. J. E.
Van Craenenbroeck, Emeline M.
Beckers, Paul
Cornelissen, Véronique A.
Howden, Erin J.
Keating, Shelley E.
Yan, Xu
Bishop, David J.
Bye, Anja
Haupt, Larisa M.
Griffiths, Lyn R.
Ashton, Kevin J.
Brown, Matthew A.
Torquati, Luciana
Eynon, Nir
Coombes, Jeff S.
Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study
title Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study
title_full Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study
title_fullStr Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study
title_full_unstemmed Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study
title_short Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study
title_sort genome wide association study of response to interval and continuous exercise training: the predict-hiit study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8117553/
https://www.ncbi.nlm.nih.gov/pubmed/33985508
http://dx.doi.org/10.1186/s12929-021-00733-7
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