Regular exercise and patterns of response across multiple cardiometabolic traits: the HERITAGE family study

Abstract

ObjectivesWe investigated whether high responsiveness or low responsiveness to exercise training aggregates in the same individuals across seven cardiometabolic traits.MethodsA total of 564 adults (29.2% black, 53.7% female) from the HERITAGE family study completed a 20-week endurance training programme (at 55%–75% of participants’ maximal oxygen uptake (VO2max)) with VO2max, per cent body fat, visceral adipose tissue, fasting levels of insulin, high-density lipoprotein cholesterol, small low-density lipoprotein particles and inflammatory marker GlycA measured before and after training. For each exercise response trait, we created ethnicity-specific, sex-specific and generation-specific quintiles. High responses were defined as those within the 20th percentile representing the favourable end of the response trait distribution, low responses were defined as the 20th percentile from the least favourable end, and the remaining were labelled as average responses.ResultsOnly one individual had universally high or low responses for all seven cardiometabolic traits. Almost half (49%) of the cohort had at least one high response and one low response across the seven traits. About 24% had at least one high response but no low responses, 24% had one or more low responses but no high responses, and 2.5% had average responses across all traits.ConclusionsInterindividual variation in exercise responses was evident in all the traits we investigated, and responsiveness did not aggregate consistently in the same individuals. While adherence to an exercise prescription is known to produce health benefits, targeted risk factors may not improve.

The HERITAGE Family Study: A Review of the Effects of Exercise Training on Cardiometabolic Health, with Insights into Molecular Transducers

“…For instance, the correlation coefficients between the gains in V̇O 2max and the changes in cardiometabolic traits are less than 0.10. Similarly, the coefficients among several cardiometabolic trait changes are generally about 0.20 or less, except for the changes between percent body fat and AVF, which reached 0.35 ( 283 ). Thus, the response levels across traits do not aggregate in any given individual, indicating that there is a high degree of trait specificity in responsiveness to an endurance training program.…”

“…One important question is whether the HERITAGE findings on V̇O 2max trainability apply to the training-induced changes in other traits of interest. Individual differences in response level have been observed for a panel of seven cardiometabolic and cardiorespiratory fitness traits ( 44 , 283 ). Changes in V̇O 2max were shown to be independent of the changes in adiposity, visceral adipose tissue, insulin, lipid and lipoprotein, and inflammatory phenotype changes (Table 16 ).…”

“… Fasting insulin, fasting plasma insulin; GlycA, plasma inflammatory marker; AVF, abdominal visceral fat; fasting plasma insulin; LDL-P, low-density lipoprotein particle, plasma inflammatory marker GlycA. Adapted with permission from Barber et al ( 283 ). …”

Multiomics Approach to Precision Sports Nutrition: Limits, Challenges, and Possibilities

“…Hereditability estimates for cardiorespiratory fitness or VO2max are relatively high (about 50%) (27,28). Nonetheless, studies linking genotype and SNPs to cardiorespiratory fitness and other related attributes such as exercise training responses and exercise-induced changes in cardiometabolic risk factors have failed to produce definitive panels that could be used by DTC companies (27,(29)(30)(31). The use of global metabolomics and proteomics profiling as correlates of cardiorespiratory fitness has only recently been explored and these are best described as preliminary studies (32,33).…”

A Systematic Review Examining the Approaches Used to Estimate Interindividual Differences in Trainability and Classify Individual Responses to Exercise Training

“…With respect to classifying individual responses, labeling someone as a “non-responder” to exercise should be avoided because individuals can: (1) demonstrate individual patterns of response across a range of outcomes [e.g., the VO 2 max of an individual may “respond” positively while their body fat percentage may “not respond” ( Barber et al, 2021 )], (2) respond differently following different exercise doses ( Bonafiglia et al, 2016 ; Montero and Lundby, 2017 ; Marsh et al, 2020 ), or (3) respond differently to repeated exposure to the same training intervention ( Del Giudice et al, 2020 ). Further, given the difficulty in delineating changes caused by exercise vs. behavioral or environmental factors, “responders” and “non-responders” should not be interpreted as individuals who responded or did not respond to exercise per se ( Swinton et al, 2018 ).…”