Effects of physical inactivity in cardiovascular biomarkers

Introduction

It is well established the concept that regular physical exercise induces stable physiological and metabolic adaptations for several cells, tissues and organs, including the cardiovascular system. Exercise training has a relevant role in healthy growth and aging, a great beneficial effect on overall mortality and can prevent the occurrence of many chronic diseases, as extensively discussed in several excellent papers (1-4).

A physically active behavior is reported to increase 8–10 years of life free from chronic limiting illness in comparison to sedentary lifestyle (5) also for low-intensity programs: 92 minutes per week or 15 min a day of moderate-intensity endurance training have been reported to provide a 14% reduced risk of all-cause mortality and 3 years longer life expectancy (6). A light-intensity exercise program, such as fast walking, has provided good level of evidence to be adequate to improve blood pressure control in individual with essential hypertension (7), although in a different extent in relation to different patterns of nocturnal fall of blood pressure (8), may improve some metabolic parameters (9) and risk factors in type 2 diabetes (10), may help to control low-level systemic inflammation (3), a key factor linking physical inactivity (PI), unhealthy lifestyle and future development of multimorbidity (11-13).

Even a very low amount of exercise, quantified in 5 to 10 minutes of running/day also at slow speed (<6 miles/hour) has been associated with markedly reduced risk of death from all causes as well as cardiovascular disease (CVD) (14).

Unlike drug therapy, physical activity (PA) has few side effects and it is a cost-effective means for prevention and treatment (15), properly compared to a “polypill” (16,17).

The current enormous worldwide high prevalence of sedentary lifestyle is the consequence of progressive modernization and automation occurred during the last century, favoring the shift to more sedentary occupational tasks and lifestyle. This sedentariness has been described as a major mortality risk factor, independent of PA and ~5.3 million deaths are attributed to PI (1) which is, in fact, the fourth leading cause of death worldwide (18).

As suggested by Tremblay et al. in 2017, the social and economic burden created by these changes in our lifestyle, gives rise to the urgency for clear, common and accepted terminology and definitions (19). While the term PA has been well established in literature for many years and is currently still defined as Caspersen et al. suggested in 1985 as “any body movement generated by the contraction of skeletal muscles that raises energy expenditure above resting metabolic rate, and is characterized by its modality, frequency, intensity, duration, and context of practice” (19,20) the definition of both PI and sedentary behavior has seen some updates during the last years.

PI is defined as “the failure to meet a predefined moderate to vigorous-intensity PA threshold” (1) while sedentary behavior is defined as a “behavior characterized by an energy expenditure ≤1.5 METs, while in a sitting, reclining, or lying posture” (19).

As we can grasp from these definitions, it is important to underline that PA and sedentary behaviors are not the opposite of each other: individuals are considered to be active when they reach PA recommendations for their age, which does not prevent them from also devoting a significant part of their time to sedentary behaviors (1).

As for the difference between PI and sedentary behavior, even if in 2012 the Sedentary Behavior Research Network proposed a more accurate and widely accepted clarification there still remains a need for further consensus. In fact the standardized use of these key terms has had variable uptake across disciplines and medical subject headings continue to use PI when sedentary behavior would be more appropriate (19).

In conclusion, given the epidemiological importance of PI as a modifiable risk factor for morbidity and mortality and the consequential need for suitable diagnostic and follow-up tools, we aimed to review the effects of PI on cardiovascular biomarkers.

The concept of cardiovascular biomarker

Following the currently accepted definition, a biomarker is “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” (21).

According to this definition, a biomarker may be a metabolic indicator searched in a biological sample (urine, blood, or biopsy), but may be also derived by an instrumental examination (e.g., blood pressure measurement, electrocardiogram registration, 24-h Holter analysis, analysis of data obtained through echocardiogram or computed tomography scan) (22).

In several pathologic conditions the search for the “perfect” biomarker is still ongoing because an useful biomarker have to grant to the clinician different important characteristics: (I) accuracy; (II) reproducibility; (III) standardization; (IV) easiness to detect and to interpret by clinicians; (V) high sensitivity and specificity for the outcome it is expected to identify; (VI) well accepted by the patient; (VII) high positive predictive value independently of established predictors for the expected outcome (23).

Biomarkers are a powerful tool requiring rigorous and critical interpretation. Their use can help physicians to classify individuals into categories of disease or no disease, to determine the risk of an event or prognosis as well as to target interventions in clinical practice (24). In order to properly use biomarkers, distinction between a causal factor and a biomarker must be taken into consideration: to be useful, a biomarker need not contribute directly to the disease mechanism (24).

Considering the variety of uses, the desirable characteristics of a biomarker differ with their intended utilization: biomarkers of screening, high sensitivity and specificity, predictive value, large likelihood ratios, and low costs; yet, for biomarkers monitoring the response to therapy, features such as narrow intraindividual variation and association with disease outcome are critical (25). The search for the “perfect” biomarker is challenging in various scientific fields.

CVD is a leading cause of death worldwide and continues to increase in prevalence compared to previous decades, in part due to the aging of the world population (26,27). Identification of biomarkers with high sensitivity and specificity for assessing the prognosis of CVD is thus necessary for optimizing personalized treatment and reducing mortality (28,29). Although over the past 30 years advances in biomarker research and developments related to CVD have led to more sensitive screening methods, earlier diagnosis and improved treatments resulting in more favorable clinical outcomes in the community, the use of biomarkers for different purposes in cardiovascular remains an important area of research and many new developments are still underway (26). For example, in recent years, the physiological and pathological effects of exosomes on CVD have been extensively studied and accumulating evidence. It has been suggested that cardiomyocyte-derived exosomes not only play an important role in the progression of CVD (30) but have also been proved to be accessible in nearly all body fluids and reflect disease stage or progression (28).

In summary, there are numerous cardiovascular biomarkers that are currently available and that have clinical use as diagnostic, prognostic or predictive (26) and, although risk in CVD is still determined predominantly by clinical factors, biochemical, cellular and imaging parameters is steadily allowing for incrementally refined risk assessment and, over time, this is gradually moving us nearer to the paradigm of targeted, precision medicine (31).

A detailed review of both well-known and under study cardiovascular biomarkers is beyond the scope of this review. Nevertheless, given the extent of data at our disposal, an overview of the most important CV biomarkers used nowadays in clinical practice, seems necessary.

Biomarkers can be grouped following different criteria (e.g., disease-specificity, use in clinical practice, pathologic process) (26). Table 1 summarizes the main cardiovascular biomarkers used in clinical practice, grouped based on the pathologic process they represent.

As for instrumental biomarkers, the available data are fewer. In this field, instrumental risk markers that have shown promise in cardiovascular risk assessment are: coronary artery calcium (CAC) (35,36), carotid intima-media thickness (CIMT), ankle-brachial index (ABI), brachial flow-mediated dilation (FMD) (37).

Table 2 shows the main instrumental biomarkers according to available information.

Consequences of physical inactivity for human health

Regular exercise is without doubt a powerful and extraordinary simple way to treat and prevent a wide range of chronic pathological conditions, such as metabolic diseases related to obesity, atherosclerotic degeneration of vessels and related vascular events, other CVDs, neurodegeneration, cancer, and several others (12).

So, how does PA influence our body “well-being” and, consequently, how does the lack of it, influence its “malaise”? Exercise biology is complex, and it involves various metabolic and molecular changes that translate into changes in substrate utilization, enzyme activation, and improvement in exercise performance (43). Various mechanism underling these effects have been proposed and only partially understood: enhanced nitric oxide-mediated vasodilation and optimized shear stress are main benefits together with oxidative stress modulation and the putative anti-inflammatory effect of exercise (29,44).

Recently, it has been proposed that the protective effects of PA could also be attributed to the muscular production of peptide mediators called myokines, these, secreted during skeletal muscle contraction, may trigger specific metabolic pathways in different tissue and organs far from the muscle allowing the latter to communicate with many organs such as visceral fat, bone, liver, and nervous system, among others (29). As for the pathophysiology of this “communication”, accumulating data suggest that some myokines may work exerting specific endocrine effects on visceral fat or mediating direct anti-inflammatory effects and some other may work locally within the muscle via paracrine mechanisms, exerting their effects on signaling pathways involved in fat oxidation (45).

PI dysregulates molecular circuitry, thus influencing the development of the different pathologic conditions up to determine its clinical expression (2). The exact underlying biochemical and molecular mechanisms of PI are not well characterized. Yet, as asserted by Booth et al., it is important to remind that these mechanisms are not simply the converse of PA; instead, mechanisms of PI in some cases employ totally different pathways than PA uses (46,47).

PI interacts with other environmental factors to increase risk for many chronic conditions and represents an actual cause of premature death (47). PI impacts on the pathogenesis of so many diseases so much that, in order to indicate this cluster of diseases, Pedersen suggested the term “diseasome of PI” (48). In fact, PI appears to be an independent and strong risk factor for accumulation of visceral fat, which again is a source of systemic inflammation (48) and is recognized as one of the leading risk factors for developing of at least 35 chronic diseases/conditions (46).

Cardiovascular health and physical inactivity

PI increases the prevalence of all major CVDs (e.g., subclinical atherosclerosis, coronary heart disease (CHD), acute coronary syndrome, angina pectoris, cerebrovascular disease, high blood pressure, heart failure) (47).

Numerous studies have established the importance of PA and fitness for long-term cardiovascular health (49) and its importance on lowering morbidity and mortality from heart disease (50).

Regular moderate exercise (i.e., as recommended by U.S. PA Guidelines, 30 minutes of moderate exercise—like a brisk walk—for 5 days per week or more) has been shown to be helpful for both the primary and secondary prevention of CVD in both men and women as well as engaging in more strenuous exercise (like jogging) for shorter periods of time, such that 15 minutes of jogging done 5 days per week (50).

On the other side, there is evolving evidence that excessive endurance exercise (defined as from 60 to 90 min Exercise Training per session), high-volume and/or high-intensity long-term exercise training, may attenuate the health benefits of a physically active lifestyle as demonstrated by the findings of accelerated coronary artery calcification, exercise-induced cardiac biomarker release, myocardial fibrosis, atrial fibrillation, and even higher risk of sudden cardiac death in athletes (51).

The mechanisms that contribute to the relationship between CVD and PI and/or sedentary behavior are still under investigation and can be grouped as direct and indirect mechanisms. The “indirect-mechanisms hypothesis” relates to the demonstrated impact of sedentary behavior on traditional cardiovascular risk factors both in healthy volunteers (52,53) and in populations with CV risk and/or CVD (54,55).

Regarding the effects exerted by PA about CV system, regular training or exercise has direct structural and functional benefits in the vasculature, including cardiac preconditioning (56), and various indirect advantageous effects. In fact, regular PA has been demonstrated to reduce abdominal adiposity and improve weight control (57), improve lipid profile reducing triglyceride levels and increasing HDL cholesterol levels (58) improve insulin sensitivity and glycemic control in type 2 diabetes (10), grant a reduction of systolic and diastolic blood pressure both in normotensive and in hypertensive subjects (7,59), improve autonomic tone and sympatho-vagal balance (60), restore blood coagulation, fibrinolysis and platelet aggregation (61), augment coronary blood flow (62), and improve endothelial dysfunction (63). Some of these effects may be due to the muscle-derived myokines—already cited in this review, which induce a healthy anti-inflammatory milieu, and the promotion of a healthy gut microbiota (64).

Changes in cardiovascular biomarkers in sedentary subjects

Although the pathological pathways linking sedentary behavior and CVD are still unclear and under research, recently there has been an interest in understanding the biomarkers underlying the response to PA, focusing mainly on biomarker related to cardiovascular risk (65).

Numerous studies have taken under investigation the changes in cardiovascular biomarkers in sedentary subjects, sometimes with conflicting and unclear results.

Different types of biomarkers associated with CVD risk have been assessed in various studies.

Analyzing the data available (from RCT, POS and CSS), the majority of studies exploring the modification of some anthropometric-systemic markers (e.g., Body Mass Index, Waist Circumference, Systolic blood pressure, diastolic blood pressure), lipid-related biomarkers, glycemic biomarkers and sedentary behavior showed mixed evidence of association or no evidence for association: Qi et al. in 2015 reported that objectively measured data showed that sedentary time was not related to blood pressure or cholesterol levels or CRP levels; in 2017 Wirth et al. reported that the studies concerning the relationship between sedentary behavior and both systolic and diastolic blood pressure showed non-significant results (65,66).

Objectively measured data showed that sedentary time is also strongly associated with triglycerides, indices of insulin resistance, 2-hour plasma glucose (66) León-Latre et al. also showed a significant association between sitting time and all glycemic and insulin resistance-related parameters studied, with the exception of glycated hemoglobin (67). Sedentary time is thought to affect glucose homeostasis and lipid metabolism by reducing muscle GLUT4 content and insulin-stimulated glucose uptake while also reducing lipoprotein lipase activity, leading to impaired triglyceride and HDL cholesterol metabolism (68) and, consequently, to a greater cardiovascular risk.

As for inflammatory-related biomarkers (e.g., CRP, IL-6, and TNF-α), these are relatively stable and rarely affected by exercise behavior (69).

Apart from these more studied biomarkers, novel ones have also been taken under consideration focusing on their modification in response to PA.

Among the most promising “novel” cardiovascular biomarkers, both BNP and NT-proBNP apparently decrease in patients with ventricular heart dysfunction who undergo exercise training (70,71).

The exact mechanism remains unclear and these promising effects remind us that these biomarkers deserve further study (69).

Brierley et al., focused on how changes in sedentary behavior in workplace could positively modify cardiometabolic risk marker and, likely the cardiovascular risk; the study found that, in general, sedentary behavior workplace interventions showed promise for improving cardiometabolic risk markers, although there was no consistency in which cardiometabolic risk markers showed improvement across interventions (72).

Perspectives and conclusions

The strong association between PA and cardiovascular health has been well characterized and strongly established in many studies although the pathophysiology of this association is still partially unclear and worthy of further investigations. The exercise-induced changes in cardiovascular biomarkers require further studies through focused Randomized Clinical Trial to provide stronger and globally accepted pieces of evidence regarding this field. This could be helpful not only to establish more certainties regarding the biological pathways in which PA has a role but also to give the practitioner the instruments to better assess prognostically and to better outline the follow up of the individuals for whom the sedentariness has a major role in the deterioration of cardiovascular health and quality of life.

Furthermore, there is still the need to clarify the features of some cardiovascular risk biomarkers to have a univocal position on their actual use and utility for diagnostic, prognostic and follow-up purposes.

In conclusion, at present, the magnitude of data regarding this issue is still too “unshaped” and needs better characterization and homogenization to obtain a greater consensus and a practical application in clinical practice.

Acknowledgments

Funding: None.

Footnote

Provenance and Peer Review: This article was commissioned by the Guest Editor (Fabian Sanchis-Gomar) for the series “The effects of demographic factors on cardiovascular biomarkers” published in Journal of Laboratory and Precision Medicine. The article has undergone external peer review.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/jlpm-2019-edfcb-03). The series “The effects of demographic factors on cardiovascular biomarkers” was commissioned by the editorial office without any funding or sponsorship. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Thivel D, Tremblay A, Genin PM, et al. Physical Activity, Inactivity, and Sedentary Behaviors: Definitions and Implications in Occupational Health. Front Public Health 2018;6:288. [Crossref] [PubMed]
2. Di Raimondo D, Musiari G, Miceli G, et al. Preventive and Therapeutic Role of Muscle Contraction Against Chronic Diseases. Curr Pharm Des 2016;22:4686-99. [Crossref] [PubMed]
3. Pinto A, Di Raimondo D, Tuttolomondo A, et al. Effects of physical exercise on inflammatory markers of atherosclerosis. Curr Pharm Des 2012;18:4326-49. [Crossref] [PubMed]
4. Larson EB, Wang L, Bowen JD, et al. Exercise is associated with reduced risk for incident dementia among persons 65 years of age and older. Ann Intern Med 2006;144:73-81. [Crossref] [PubMed]
5. Brønnum-Hansen H, Juel K, Davidsen M, et al. Impact of selected risk factors on expected lifetime without long-standing, limiting illness in Denmark. Prev Med 2007;45:49-53. [Crossref] [PubMed]
6. Wen CP, Wai JP, Tsai MK, et al. Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study. Lancet 2011;378:1244-53. [Crossref] [PubMed]
7. Pinto A, Di Raimondo D, Tuttolomondo A, et al. Twenty-four hour ambulatory blood pressure monitoring to evaluate effects on blood pressure of physical activity in hypertensive patients. Clin J Sport Med 2006;16:238-43. [Crossref] [PubMed]
8. Di Raimondo D, Tuttolomondo A, Miceli S, et al. Aerobic physical activity based on fast walking does not alter blood pressure values in non-dipper essential hypertensives. Int Angiol 2012;31:142-9. [PubMed]
9. Di Raimondo D, Tuttolomondo A, Buttà C, et al. Metabolic and anti-inflammatory effects of a home-based programme of aerobic physical exercise. Int J Clin Pract 2013;67:1247-53. [Crossref] [PubMed]
10. Balducci S, Zanuso S, Cardelli P, et al. Effect of high- versus low-intensity supervised aerobic and resistance training on modifiable cardiovascular risk factors in type 2 diabetes; the Italian Diabetes and Exercise Study (IDES). PLoS One 2012;7:e49297 [Crossref] [PubMed]
11. Booth FW, Chakravarthy MV, Gordon SE, et al. Waging war on physical inactivity: using modern molecular ammunition against an ancient enemy. J Appl Physiol 1985;2002:3-30. [PubMed]
12. Di Raimondo D, Tuttolomondo A, Musiari G, et al. Are the Myokines the Mediators of Physical Activity-Induced Health Benefits? Curr Pharm Des 2016;22:3622-47. [Crossref] [PubMed]
13. Di Raimondo D. Editorial (Thematic Issue: Myokines and Exercise Training: More Shadows than Lights). Curr Pharm Des 2016;22:3619-21. [Crossref] [PubMed]
14. Lee DC, Pate RR, Lavie CJ, et al. Leisure-time running reduces all-cause and cardiovascular mortality risk. J Am Coll Cardiol 2014;64:472-81. [Crossref] [PubMed]
15. Vasankari V, Husu P, Vähä-Ypyä H, et al. Association of objectively measured sedentary behaviour and physical activity with cardiovascular disease risk. Eur J Prev Cardiol 2017;24:1311-8. [Crossref] [PubMed]
16. Fiuza-Luces C, Garatachea N, Berger NA, et al. Exercise is the real polypill. Physiology (Bethesda) 2013;28:330-58. [Crossref] [PubMed]
17. Pareja-Galeano H, Garatachea N, Lucia A. Exercise as a Polypill for Chronic Diseases. Prog Mol Biol Transl Sci 2015;135:497-526. [Crossref] [PubMed]
18. Kohl HW, Craig CL, Lambert EV, et al. The pandemic of physical inactivity: global action for public health. Lancet 2012;380:294-305. [Crossref] [PubMed]
19. Tremblay MS, Aubert S, Barnes JD, et al. SBRN Terminology Consensus Project Participants. Sedentary Behavior Research Network (SBRN) - Terminology Consensus Project process and outcome. Int J Behav Nutr Phys Act 2017;14:75. [Crossref] [PubMed]
20. Caspersen CJ, Powell KE, Christenson GM. Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public Health Rep 1985;100:126-31. [PubMed]
21. Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 2001;69:89-95. [Crossref] [PubMed]
22. Vasan RS. Biomarkers of cardiovascular disease: molecular basis and practical considerations. Circulation 2006;113:2335-62. [Crossref] [PubMed]
23. Manolio T. Novel risk markers and clinical practice. N Engl J Med 2003;349:1587-9. [Crossref] [PubMed]
24. Libby P, King K. Biomarkers: A Challenging Conundrum in Cardiovascular Disease. Arterioscler Thromb Vasc Biol 2015;35:2491-5. [Crossref] [PubMed]
25. Dadu RT, Nambi V, Ballantyne CM. Developing and assessing cardiovascular biomarkers. Transl Res 2012;159:265-76. [Crossref] [PubMed]
26. Dhingra R, Vasan RS. Biomarkers in cardiovascular disease: Statistical assessment and section on key novel heart failure biomarkers. Trends Cardiovasc Med 2017;27:123-33. [Crossref] [PubMed]
27. Della Corte V, Tuttolomondo A, Pecoraro R, et al. Inflammation, Endothelial Dysfunction and Arterial Stiffness as Therapeutic Targets in Cardiovascular Medicine. Curr Pharm Des 2016;22:4658-68. [Crossref] [PubMed]
28. Bei Y, Yu P, Cretoiu D, et al. Exosomes-Based Biomarkers for the Prognosis of Cardiovascular Diseases. Adv Exp Med Biol 2017;998:71-88. [Crossref] [PubMed]
29. Di Raimondo D, Miceli G, Musiari G, et al. New insights about the putative role of myokines in the context of cardiac rehabilitation and secondary cardiovascular prevention. Ann Transl Med 2017;5:300. [Crossref] [PubMed]
30. Yu H, Wang Z. Cardiomyocyte-Derived Exosomes: Biological Functions and Potential Therapeutic Implications. Front Physiol 2019;10:1049. [Crossref] [PubMed]
31. Thomas MR, Lip GY. Novel Risk Markers and Risk Assessments for Cardiovascular Disease. Circ Res 2017;120:133-49. [Crossref] [PubMed]
32. Silva D, Pais de Lacerda A. High-sensitivity C-reactive protein as a biomarker of risk in coronary artery disease. Rev Port Cardiol 2012;31:733-45. [Crossref] [PubMed]
33. Kaptoge S, Di Angelantonio E, Pennells LEmerging Risk Factors Collaboration, et al. C-reactive protein, fibrinogen, and cardiovascular disease prediction. N Engl J Med 2012;367:1310-20. [Crossref] [PubMed]
34. Duan J, Zhu B, Wu Y, et al. Myokines: An Available Biomarker to Evaluate Cardiac Functions? Cardiology 2019;142:211-2. [Crossref] [PubMed]
35. Knuuti J, Wijns W, Saraste A, et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J 2020;41:407-77. [Crossref] [PubMed]
36. Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2019;73:e285-e350. [Crossref] [PubMed]
37. Yeboah J, McClelland RL, Polonsky TS, et al. Comparison of novel risk markers for improvement in cardiovascular risk assessment in intermediate-risk individuals. JAMA 2012;308:788-95. [Crossref] [PubMed]
38. Mancia G, Verdecchia P. Clinical value of ambulatory blood pressure, evidence and limits. Circ Res 2015;116:1034-45. [Crossref] [PubMed]
39. Nambi V, Chambless L, Folsom AR, et al. Carotid intima-media thickness and presence or absence of plaque improves prediction of coronary heart disease risk: the ARIC (Atherosclerosis Risk In Communities) study. J Am Coll Cardiol 2010;55:1600-7. [Crossref] [PubMed]
40. Fowkes FG, Murray GD, Butcher I, et al. Ankle brachial index combined with Framingham Risk Score to predict cardiovascular events and mortality: a meta-analysis. JAMA 2008;300:197-208. [Crossref] [PubMed]
41. Fowkes FG, Murray GD, Butcher I, et al. Development and validation of an ankle brachial index risk model for the prediction of cardiovascular events. Eur J Prev Cardiol 2014;21:310-20. [Crossref] [PubMed]
42. Yeboah J, Folsom AR, Burke GL, et al. Predictive value of brachial flow-mediated dilation for incident cardiovascular events in a population-based study: the multi-ethnic study of atherosclerosis. Circulation 2009;120:502-9. [Crossref] [PubMed]
43. Huh JY. The role of exercise-induced myokines in regulating metabolism. Arch Pharm Res 2018;41:14-29. [Crossref] [PubMed]
44. Boccatonda A, Tripaldi R, Davì G, et al. Oxidative Stress Modulation Through Habitual Physical Activity. Curr Pharm Des 2016;22:3648-80. [Crossref] [PubMed]
45. Pedersen BK. Exercise-induced myokines and their role in chronic diseases. Brain Behav Immun 2011;25:811-6. [Crossref] [PubMed]
46. Booth FW, Roberts CK, Thyfault JP, et al. Role of Inactivity in Chronic Diseases: Evolutionary Insight and Pathophysiological Mechanisms. Physiol Rev 2017;97:1351-402. [Crossref] [PubMed]
47. Booth FW, Roberts CK, Laye MJ. Lack of exercise is a major cause of chronic diseases. Compr Physiol 2012;2:1143-211. [PubMed]
48. Pedersen BK. The diseasome of physical inactivity--and the role of myokines in muscle--fat cross talk. J Physiol 2009;587:5559-68. [Crossref] [PubMed]
49. Hershman SG, Bot BM, Shcherbina A, et al. Physical activity, sleep and cardiovascular health data for 50,000 individuals from the MyHeart Counts Study. Sci Data 2019;6:24. [Crossref] [PubMed]
50. Lavie CJ, O'Keefe JH, Sallis RE. Exercise and the heart --the harm of too little and too much. Curr Sports Med Rep 2015;14:104-9. [Crossref] [PubMed]
51. Eijsvogels TMH, Thompson PD, Franklin BA. The "Extreme Exercise Hypothesis": Recent Findings and Cardiovascular Health Implications. Curr Treat Options Cardiovasc Med 2018;20:84. [Crossref] [PubMed]
52. Stamatakis E, Hamer M, Tilling K, et al. Sedentary time in relation to cardio-metabolic risk factors: differential associations for self-report vs accelerometry in working age adults. Int. J. Epidemiol 2012;41:1328-37. [Crossref] [PubMed]
53. Huynh QL, Blizzard CL, Sharman JE, et al. The cross-sectional association of sitting time with carotid artery stiffness in young adults. BMJ Open 2014;4:e004384 [Crossref] [PubMed]
54. Gerage AM, Benedetti TR, Farah BQ, et al. Sedentary behavior and light physical activity are associated with brachial and central blood pressure in hypertensive patients. PLoS One 2015;10:e0146078 [Crossref] [PubMed]
55. King WC, Chen JY, Courcoulas AP, et al. Objectively-measured sedentary time and cardiometabolic health in adults with severe obesity. Prev. Med 2016;84:12-8. [Crossref] [PubMed]
56. Scott JM, Esch BT, Haykowsky MJ, et al. Effects of high intensity exercise on biventricular function assessed by cardiac magnetic resonance imaging in endurance trained and normally active individuals. Am J Cardiol 2010;106:278-83. [Crossref] [PubMed]
57. Paley CA, Johnson MI. Abdominal obesity and metabolic syndrome: exercise as medicine? BMC Sports Sci Med Rehabil 2018;10:7. [Crossref] [PubMed]
58. Wang Y, Xu D. Effects of aerobic exercise on lipids and lipoproteins. Lipids Health Dis 2017;16:132. [Crossref] [PubMed]
59. Di Raimondo D, Miceli G, Casuccio A, et al. Does sympathetic overactivation feature all hypertensives? Differences of sympathovagal balance according to night/day blood pressure ratio in patients with essential hypertension. Hypertens Res 2016;39:440-8. [Crossref] [PubMed]
60. Besnier F, Labrunée M, Pathak A, et al. Exercise training-induced modification in autonomic nervous system: An update for cardiac patients. Ann Phys Rehabil Med 2017;60:27-35. [Crossref] [PubMed]
61. van der Vorm LN, Huskens D, Kicken CH, et al. Effects of Repeated Bouts of Exercise on the Hemostatic System. Semin Thromb Hemost 2018;44:710-22. [Crossref] [PubMed]
62. Hambrecht R, Wolf A, Gielen S, et al. Effect of exercise on coronary endothelial function in patients with coronary artery disease. N Engl J Med 2000;342:454-60. [Crossref] [PubMed]
63. Kobayashi N, Tsuruya Y, Iwasawa T, et al. Exercise training in patients with chronic heart failure improves endothelial function predominantly in the trained extremities. Circ J 2003;67:505-10. [Crossref] [PubMed]
64. Fiuza-Luces C, Santos-Lozano A, Joyner M, et al. Exercise benefits in cardiovascular disease: beyond attenuation of traditional risk factors. Nat Rev Cardiol 2018;15:731-43. [Crossref] [PubMed]
65. Wirth K, Klenk J, Brefka SSITLESS consortium, et al. Biomarkers associated with sedentary behaviour in older adults: A systematic review. Ageing Res Rev 2017;35:87-111. [Crossref] [PubMed]
66. Qi Q, Strizich G, Merchant G, et al. Objectively Measured Sedentary Time and Cardiometabolic Biomarkers in US Hispanic/Latino Adults: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Circulation 2015;132:1560-9. [Crossref] [PubMed]
67. León-Latre M, Moreno-Franco B, Andrés-Esteban EM, et al. Sedentary lifestyle and its relation to cardiovascular risk factors, insulin resistance and inflammatory profile. Rev Esp Cardiol (Engl Ed) 2014;67:449-55. [Crossref] [PubMed]
68. Swindell N, Mackintosh K, McNarry M, et al. Objectively Measured Physical Activity and Sedentary Time Are Associated With Cardiometabolic Risk Factors in Adults With Prediabetes: The PREVIEW Study. Diabetes Care 2018;41:562-9. [Crossref] [PubMed]
69. Che L, Li D. The Effects of Exercise on Cardiovascular Biomarkers: New Insights, Recent Data, and Applications. Adv Exp Med Biol 2017;999:43-53. [Crossref] [PubMed]
70. Smart NA, Steele M. Systematic review of the effect of aerobic and resistance exercise training on systemic brain natriuretic peptide (BNP) and N-terminal BNP expression in heart failure patients. Int J Cardiol 2010;140:260-5. [Crossref] [PubMed]
71. Tuttolomondo A, Pinto A, Di Raimondo D, et al. Changes in natriuretic peptide and cytokine plasma levels in patients with heart failure, after treatment with high dose of furosemide plus hypertonic saline solution (HSS) and after a saline loading. Nutr Metab Cardiovasc Dis 2011;21:372-9. [Crossref] [PubMed]
72. Brierley ML, Chater AM, Smith LR, et al. The Effectiveness of Sedentary Behaviour Reduction Workplace Interventions on Cardiometabolic Risk Markers: A Systematic Review. Sports Med 2019;49:1739-67. [Crossref] [PubMed]