Evaluation of Physical Activity, Metabolic Markers, and Cardiovascular Disease Risk

Editor's Note: Commentary based on Pang Y, Kartsonaki C, Du H, et al. Physical activity, sedentary leisure time, circulating metabolic markers, and risk of major vascular diseases. Circ Genomic Precis Med 2019;12(9):386-396.1

Study Questions
What is the association of physical activity and leisure time with plasma lipoproteins, lipids, and other metabolic biomarkers, and how do these associations relate to cardiovascular disease (CVD) risks?

Methods
Data was obtained from the prospective China Kadoorie Biobank (CKB), a prospective cohort study of 512,713 adults aged 30-79 years from China.1 Investigators compared a subset of CVD cases to controls without prior coronary heart disease, stroke, transient ischemic attack (TIA) and cancer or statin use at baseline. At baseline, participants completed a questionnaire on socio-demographic characteristics, smoking, alcohol consumption, diet, physical activity, and medical history, and underwent a range of physical measurements including height, weight, hip and waist circumference, bio-impedance, lung function, blood pressure, and heart rate. All patients provided a non-fasting blood sample at baseline. Nuclear magnetic resonance (NMR) spectroscopy was used to measure 225 metabolic markers and derived traits from baseline plasma samples. Linear regression was applied to assess correlation between physical activity and leisure time and biomarkers, with adjustments for potential confounders including body mass index, diabetes mellitus, and dietary variables. These results were then related to association of biomarkers with occlusive CVD (defined by the authors in the supplementary material as myocardial infarction and ischemic stroke) risk. This nested case-control study of CVD subtypes included cases of myocardial infarction, ischemic stroke, and intracerebral hemorrhage.

Results
Participants were selected from the CKB cohort who were aged 30-79 at the baseline survey, did not report coronary heart disease, stroke, TIA, and cancer at baseline, and did not use statins. Included were 4660 participants, 3195 CVD cases (2057 occlusive CVD and 1138 intracerebral hemorrhage) and 1465 controls. Participants were a mean age of 46 years, 50% were women, and the mean total level of physical activity was 23 metabolic equivalent (MET)-h/day and mean sedentary leisure time was 3.16 h/day. Physical activity and leisure time were associated with more than 100 metabolic markers with patterns of associations generally as anticipated. In this cohort, there were inverse associations of physical activity with very low density lipoprotein (VLDL) and low density lipoprotein (LDL) particle concentrations. Inflammatory markers including high sensitivity C reactive protein, fibrinogen, and glycoprotein acetyls were also inversely associated with physical activity. The authors do not mention whether or not these associations were independent of weight loss. Moreover, there is a positive association of physical activity with high density lipoprotein (HDL) particle concentrations. The authors showed that the local difference in metabolic biomarkers related to higher physical activity conferred lower risk of occlusive CVD with approximately 70% of the protective association potentially explained by these metabolic markers. These metabolic markers also potentially explained ~50% of the harmful effect of sedentary leisure time on occlusive CVD. And there were inverse associations of physical activity with major vascular events after adjustment for age, sex, region, household income, education, alcohol consumption, smoking, fresh fruit intake, sedentary leisure time, and self-reported general health status. This study also demonstrated an inverse association of total physical activity with isoleucine, leucine, and valine, which are part of the branched-chain amino acid group, essential amino acids that play a key role in energy production and protein synthesis and whose circulating levels are associated with obesity, insulin resistance, metabolic disorders, type 2 diabetes, and CVD.

Conclusions
The investigators concluded that among Chinese adults, physical activity and sedentary behavior have opposing associations with a diverse range of circulating metabolites. The authors state that their results may potentially implicate lipids and lipoproteins as mediators of the beneficial effects of physical activity on risk of CVD.

Perspective
This study stands out from prior studies as it examines the associations of physical activity and sedentary behaviors with circulating metabolic biomarkers and disease risk. As the authors point out, these findings are of contemporary importance given recent guidelines for the primary prevention of cardiovascular disease (CVD) published by the American College of Cardiology/American Heart Association (ACC/AHA).2 A major strength of this study is the wealth of data collected in a prospective biobank. However, as the authors note, the study is limited by the subjective self-reporting of physical activity and leisure time. Additionally, while the authors controlled for many confounders, they do note the possibility of residual confounding because of unmeasured or sub-optimally measured factors. Unfortunately, as a cross sectional study, data were acquired at baseline and therefore the longitudinal relationship between physical activity and blood based lipid and metabolic biomarkers cannot be fully appreciated. Moreover, as the authors point out, it is difficult to fully disentangle which biomarkers, either individually or in combination, chiefly explained the effects of physical activity on CVD. It is not clear if perhaps physical activity results in weight loss which then reduced lipids. The authors do not present data on the independent association of lipids and activity. While the importance of physical activity and avoiding sedentary behaviors cannot be overstated, this study does not add novel clinical information. What needs to be sought in future studies is the predictive utility of specific metabolic biomarkers to explain the effects of physical activity/sedentary behavior in reducing the risk of CVD. In this age of big data, we need to embrace the great potential in biobanks such as CKB for predictive analytics. Still, given the results of this study, recommendations for increasing physical activity and reducing sedentary leisure time continue to be sound recommendations for patients and specifically appear to be associated with improved metabolic profiles.

References

  1. Pang Y, Kartsonaki C, Du H, et al. Physical activity, sedentary leisure time, circulating metabolic markers, and risk of major vascular diseases. Circ Genomic Precis Med 2019;12:386-96.
  2. Arnett DK, Blumehthal RS, Albert, MA, et al. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation 2019;140:596-646.

Clinical Topics: Diabetes and Cardiometabolic Disease, Dyslipidemia, Prevention, Hypertriglyceridemia, Lipid Metabolism, Nonstatins, Novel Agents, Statins, Diet, Exercise, Smoking

Keywords: Primary Prevention, Secondary Prevention, Body Mass Index, Waist Circumference, Ischemic Attack, Transient, Hydroxymethylglutaryl-CoA Reductase Inhibitors, C-Reactive Protein, Cross-Sectional Studies, Self Report, Metabolic Equivalent, Leucine, Weight Loss, Prospective Studies, Isoleucine, Blood Pressure, American Heart Association, Cardiovascular Diseases, Case-Control Studies, Heart Rate, Linear Models, Fibrinogen, Electric Impedance, Stroke, Amino Acids, Essential, Valine, Lipids, Insulin Resistance, Metabolome, Biological Specimen Banks, Brain Ischemia, Diabetes Mellitus, Type 2, Obesity, Cerebral Hemorrhage, Exercise, Myocardial Infarction, Leisure Activities, Lipoproteins, HDL, Magnetic Resonance Spectroscopy, Lipoproteins, LDL, Diet, Coronary Disease, Lipoproteins, VLDL, Primary Prevention, Health Status, Lipoproteins, Smoking, Alcohol Drinking, Neoplasms, Glycoproteins, Cohort Studies


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