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

Background: Low cardiorespiratory fitness ((V) over dotO(2)peak) is highly associated with chronic disease and mortality from all causes. Whilst exercise training is recommended in health guidelines to improve (V) over dotO(2)peak, there is considerable inter-individual variability in the (V) over dotO(2)peak response to the same dose of exercise. Understanding how genetic factors contribute to (V) over dotO(2)peak 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 (V) over dotO(2)peak response following exercise training. Methods: Participant change in objectively measured (V) over dotO(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 x 10(-5)) with the magnitude of (V) over dotO(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 (V) over dotO(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 (V) over dotO(2)peak response that reached suggestive significance (P < 1 x 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 x 10(-7)). A PPS created from the 12 lead SNPs was unable to predict (V) over dotO(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 x 10(-4)) and the validation study (P < x 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 (V) over dotO(2)peak response variance, and whether genomic predictors for (V) over dotO(2)peak response trainability can inform evidence-based clinical practice.

Automated summary

This study identified 12 novel genetic loci with suggestive association with (V)over dotO(2)peak response following exercise training. However, a polygenic predictor score created from these loci failed to accurately predict the (V)over dotO(2)peak response. Significant correlations were found for beta coefficients of variants in the study and validation, suggesting that with higher statistical power, more significant genetic associations may become apparent.