Innovation to Reduce Cardiovascular Complications of Diabetes at the Intersection of Discovery, Prevention and Knowledge Exchange

Can J Diabetes 37 (2013) 282e293

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Canadian Journal of Diabetes journal homepage: www.canadianjournalofdiabetes.com

Original Research

Innovation to Reduce Cardiovascular Complications of Diabetes at the Intersection of Discovery, Prevention and Knowledge Exchange Earl Noble PhD a, Jamie Melling PhD a, b, Kevin Shoemaker PhD a, Heikki Tikkanen MD, PhD c, d, Juha Peltonen PhD d, Melanie Stuckey PhD a, e, Robert J. Petrella MD, PhD a, e, f, * a

School of Kinesiology, Faculty of Health Sciences, University of Western Ontario, London, Ontario, Canada Health Studies, Faculty of Health Sciences, University of Western Ontario, London, Ontario, Canada c Department of Sports and Exercise Medicine, Institute of Clinical Medicine, University of Helsinki, Helsinki, Finland d Foundation for Sports and Exercise Medicine, Clinic for Sports and Exercise Medicine, Helsinki, Finland e Lawson Health Research Institute, University of Western Ontario, London, Ontario, Canada f Departments of Family Medicine and Medicine (Division of Cardiology), Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ontario, Canada b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 6 May 2013 Received in revised form 27 July 2013 Accepted 29 July 2013

This article describes selected primary outcomes from a series of linked, collaborative projects among multidisciplinary investigators from Canada and Finland dedicated to quantifying the benefits and detriments of prescriptive exercise in the prevention and control of the cardiovascular complications (CVCs) of diabetes along the continuum of disease risk. Ó 2013 Canadian Diabetes Association

Keywords: cardiovascular complications diabetes exercise international team multidisciplinary Mots clés : complications cardiovasculaires diabète exercice équipe internationale multidisciplinaire

r é s u m é Cet article décrit certains résultats principaux d’une série de projets de collaboration liés des investigateurs multidisciplinaires du Canada et de la Finlande voués à la quantification des avantages et des inconvénients de la prescription d’exercices dans la prévention et la maîtrise des complications cardiovasculaires (CCV) liées au diabète dans le continuum de risque de maladie. Ó 2013 Canadian Diabetes Association

Introduction Cardiovascular diseases are the leading source of morbidity and mortality among Canadians. In those with diabetes, cardiovascular complications (CVCs) result in >70% of deaths. While there is intense interest in identifying and modifying risk factors at the onset of CVCs in diabetes, the exact biological mechanisms, their measurements and broader social determinants governing CVCs of diabetes, including optimal ways to prevent or manage them, are still poorly understood. In the context of preventing or reversing CVCs, there is unequivocal evidence that increased physical activity and regular exercise can prevent diabetes and many risk factors that give rise to CVCs of diabetes. However, implementation of this

* Address for correspondence: Robert J. Petrella, MD, PhD, Lawson Health Research Institute and Western University, London, Ontario N6C 5J1, Canada. E-mail address: [email protected]. 1499-2671/$ e see front matter Ó 2013 Canadian Diabetes Association http://dx.doi.org/10.1016/j.jcjd.2013.07.061

knowledge at the point of care is alarmingly poor, as there is a significant gap in our understanding of how to target, deliver and prescribe the most beneficial type of exercise to patients at risk in the community. With funding from CIHR, HSFC, CDA, Pfizer and Tekes, we postulated that establishing early markers of CVCs in the context of diabetes requires a continuum of CVCs risk in preclinical animal models as well as “at risk” human models, including childhood metabolic disorders, individuals with metabolic syndrome and patients with overt diabetes and cardiovascular events. Using emerging and new technologies, we investigated microand macrovascular structure and function in representative animal models and human populations. As a major endpoint of this initiative, we determined the feasibility of measuring the early markers with new technologies and to implement new methods for application in clinical and community practice. Our Canada-Finland team partnership was leveraged using a knowledge integration form of governance for the group, where we identified precise

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strategies, within our capacity, to address important, emerging issues of CVCs of diabetes. Our team chose the name ARTEMIS for our collaboration as a metaphor which symbolized our collaborative efforts to search (“hunt”) for underlying causes of CVCs of diabetes, and to find innovative ways to promote the longevity of those affected and those at risk. We identified 2 major goals for our research: 1) to identify and then to prevent and treat early markers of CVCs in patients at risk for, or with, diabetes; and 2) to develop best practices for delivery of CVCs prevention and reversal at the point of care. This article describes selected primary outcomes from a series of linked, collaborative projects among multidisciplinary investigators from Canada and Finland dedicated to quantifying the benefits and detriments of prescriptive exercise in the prevention and control of the CVCs of diabetes along the continuum of diseased risk. Experimental evidence from rodent studies suggests a beneficial role of regular exercise in streptozotocin (STZ)-induced hyperglycemic animals (1e3) as regular exercise reduces hyperglycemiarelated plasma triglycerides, mean arterial blood pressure and plasma blood glucose values (4). In the majority of these studies, however, STZ-induced diabetic rodents with high blood glucose values (greater than 20 mM) are exercised. Given that type 1 diabetes mellitus (T1DM) patients are unlikely to have such severe hyperglycemia, experimental studies examining the effects of regular exercise in which blood glucose is poorly controlled would better represent the at-risk human T1DM population. Although more frequently associated with type 2 diabetes mellitus (T2DM), insulin resistance affects approximately 20% of individuals with T1DM (5). While the etiology of insulin resistance has not been established in the T1DM patient, it is clear that it does not parallel other insulin resistant states (i.e. T2DM or obesity), as T1DM patients are often asymptomatic for associated factors, such as obesity, reduced physical activity levels and visceral fat content (6). While aerobic exercise has historically been considered the most suitable exercise to improve insulin sensitivity, it is not clear whether the intensity, duration or frequency are factors to consider when prescribing an aerobic exercise program. Although less frequently prescribed, resistance exercise can produce favourable changes in muscle mass, increasing glucose storage capacity and glucose clearance from the blood (7). In a recent study, Bacchi et al reported that 4 months of resistance training in T2DM patients led to reductions in visceral and subcutaneous adiposity and HbA1c, and improvements in lean limb mass and insulin sensitivity to a similar extent as aerobic training (8). Our laboratory and others have shown that increases in Hsp70 can protect the myocardium against ischemia reperfusion injury (9e12). However, it has been demonstrated that Hsp70 protein levels in several tissues, including the heart, are reduced in unmanaged STZ-induced rodents (13). Furthermore, the increased expression of myocardial Hsp70 seen in nondiabetic rodents following 8 weeks of moderate intensity aerobic exercise training is suppressed in STZ-treated animals (13). However, discrepancies exist in the literature with regards to the suppressive effects of diabetes on Hsp70, which might be related to the severity and duration of the diabetes condition (14). Therefore, it was of interest to determine if this previously reported Hsp70 response is present in our model of combined insulin and exercise. Indeed, Li et al demonstrated that insulin treatment alone can increase Hsp70 expression as well as enhance myocardial recovery of contractile function postischemic injury (15). The purpose of these experiments was to examine the combined role of exercise training program coupled with insulin therapy to alleviate many of the well-known complications associated with diabetes progression, including insulin resistance, cardiovascular

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complications (16) and bone health (17). By maintaining blood glucose values in the 9 to 15 mM range utilizing insulin treatment, our studies attempt to examine the effects of regular exercise in a model that represents a moderate hyperglycemic T1DM patient with conventional insulin therapy (18). Although even moderate hyperglycemia would result in detectable pathology when chronically present, it was hypothesized that the combination of regular exercise and insulin therapy, regardless of training modality, would alleviate many of these diabetes-related complications. Our objectives were to: 1) develop a relevant model of type I diabetes; 2) determine the mode and intensity of exercise most effective in ameliorating the metabolic and cardiovascular effects of type I diabetes; 3) examine the effects of exercise on cardiac and vascular dynamics in diabetic animals; and 4) examine potential markers (Hsp70) that align with exerciseinduced alterations in the cardiovascular system that may be associated with improved function or protection. Methods Diabetes induction T1DM was induced over 5 consecutive days by daily intraperitoneal injections of 20 mg/kg streptozotocin (STZ; Sigma-Aldrich, St. Louis, MO, USA) dissolved in a citrate buffer (0.1 M, pH 4.5). The low-dose STZ-induced T1DM rodent model has been shown to elicit an inflammatory-mediated destruction of pancreatic islet b-cell, similar to the actual etiology of T1DM. Following the confirmation of diabetes, insulin pellets (1 pellet; 2U insulin/day; Linplant, Linshin Canada, Inc., Toronto, Ontario, Canada) were implanted subcutaneously in the abdominal region. Insulin dosages were continuously monitored and adjusted to sustain blood glucose concentrations within a 9 to 15 mmol/L range. Exercise protocol Both aerobic exercise groups ran 1 hour per day, 5 days a week, for 10 weeks on a motorized treadmill with a 6% grade incline. Following the familiarization, high-intensity trained (DH) rats ran consistently at a speed of 27 m/min while low-intensity aerobic exercise trained (DL) rats ran consistently at 15 m/min. DH and DL rats exercised at approximately 70% to 80% and 50% to 60% of their VO2 max, respectively (19). Resistance trained rats were required to climb a ladder with weight secured to the proximal portion of their tail. This protocol was originally developed as an animal model of resistance exercise that closely resembles exercise parameters and physiological adaptations observed in humans who resistance train (20). Following familiarization, DR rats underwent high-intensity progressive resistance training 5 days a week for 10 weeks. The resistance training protocol was adapted from Hornerberger and Farrar (20) as follows. Pre-training maximal carrying capacity was determined by initially loading rats with 75% of their body weight and then adding 30 g per climb until they were unable to successfully climb the ladder. For the first 4 ladder climbs, rats were loaded with 50%, 75%, 90% and 100% of their pre-training maximal carrying capacity. Subsequently, rats continued to climb at 100% maximal carrying capacity until exhaustion (unwillingness to climb despite tactile stimulation on their haunches). Every 3 days, a new maximal carrying capacity was determined. Results and Discussion Results from our first series of experiments indicated that sedentary diabetic animals, maintained within a moderate hyperglycemic range (9 to 15 mM) through a convention insulin treatment regime, demonstrated diabetes-related complications

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associated with cardiovascular function (echocardiography) and bone and body composition (microCT) (21). Diabetes-related complications were improved in the myocardium and bone following a 10-week moderate-intensity exercise program. Second, the animals maintained in the 9 to 15 mM blood glucose range also demonstrated improvements in blood glucose metabolism with exercise. Glucose tolerances (IVGTTs) were significantly improved in animals following the training program compared to sedentary diabetic controls. Furthermore, in keeping with recently emerging data in humans, we detected significant insulin resistance in these “poorly controlled” diabetic animals. Exercise rescued this insulinresistant phenotype such that the insulin requirement had to be significantly reduced in the exercise trained animals. Lastly, concomitant with changes in cardiac function, exercised trained rats demonstrated improvement in the biochemical properties of the heart as exercise training significantly elevated the constitutive Hsp70 levels to levels similar to nondiabetic animals (Figure 1B). The lack of Hsp70 expression suppression in the STZ animals is in contrast to previously reported data, and is likely due to having insulin present in these animals (22). Interestingly, Hsp70 not only enhances protection against myocardial ischemia-reperfusion injury, this protein has also been demonstrated to rescue insulin sensitivity in diabetic animals (23). This could also be a factor in the improved insulin sensitivity noted above. A recently published manuscript using a novel kinetic analysis demonstrates that diabetic rats exhibit impaired vascular function (24). Moreover, these observations were noted in the more peripheral arteries (iliac and femoral) as well as the aorta. This is one of the few studies that has examined vessels other than the aorta for this kind of analysis. Work submitted from our laboratory has further examined the effect of different exercise modalities in our “poorly controlled” insulin-supplemented model. This work was performed to determine if other exercise modalities lead to differential cardiovascular benefits. Hence, we initiated a study using low-intensity exercise (a brisk walk), high-intensity exercise (a brisk jog) and resistance exercise (weight lifting). The resistance exercise condition represents, to our knowledge, the first use of resistance training in a diabetic rodent model. This work demonstrated that all exercise modalities increased in insulin sensitivity (as assessed by IVGTTs; Figure 1A) while only aerobic exercise led to a lower insulin dose requirement. Importantly, high-intensity exercise demonstrated the greatest changes in both parameters. GLUT4 protein content was elevated in selected skeletal muscles in response to both resistance- and high-intensity exercise, while a low-intensity

exercise condition did not rescue the low GLUT4 protein content noted in the diabetic controls. Of the exercise training modalities, the high-intensity aerobic training was the most effective in normalizing (and, in fact, improving beyond normal) the responsiveness of the vascular system. These data suggest that changes in the vasoresponsiveness seem to be endothelium dependent as evidenced by the greater e-NOS content in the high-intensity trained animals and the greater normalized e-NOS content in the smaller, more responsive vessels. Taken together, these results suggest that all exercise modalities have some benefits including improved glucose tolerance. However, each mode of exercise training leads to differential improvements in insulin requirements, vascular dynamics and protein content of glucose handling proteins. Vascular disease is a hallmark of metabolic disorders and represents a major cardiovascular complication in diabetes. However, many features of cardiovascular disease (CVD) in metabolic disorders are not fully understood. For example, the site of initiation of vascular pathology represents 1 major uncertainty. In recent thinking, the microvascular bed has been implicated as the site of initiation of the disease process with subsequent progression to large vessel disease (25). In contrast to the hypothesis that CVD risk begins in the microcirculation, recent studies in older patients (26,27), and those with primary hypertension (28) and controlled T2DM (29), have suggested that left ventricular diastolic dysfunction (LVDD) is present early and acts as a function of improved or worsening of clinical parameters. Diminished LVDD has been linked to congestive heart failure, a relationship that raises the importance of understanding just where CVD risk begins in metabolic disorders. To date, concurrent measures of the vascular tree, including central conduit arteries, more distal muscular conduit arteries and the microvascular portion of the vascular tree, have not been assessed in a comprehensive model. Moreover, the variables to measure to detect vascular pathology are not clear. In our view, the mechanical properties of the vessels, namely stiffness, distensibility and viscoelastic properties represent functional outcomes that are sensitive to altered adrenergic and structural changes. While the location of vascular risk development during metabolic disorders remains uncertain, the mechanistic bases of such changes are also unknown. Earlier studies from our group demonstrated little impact of metabolic syndrome on forearm endothelial function (30). Otherwise, elevated baseline sympathetic nerve activity (SNA) may represent on important risk factor for vascular pathology. Using current approaches in analysis of sympathetic nerve activity (SNA), sympathetic hyperactivity occurs

Figure 1. (A) At week 6, all diabetic groups had significantly lower glucose clearance rates compared to C, while CD had a significantly lower glucose clearance rate compared to all other diabetic groups based on the interaction effect shown by the two way ANOVA (p<0.05). Nondiabetic sedentary control, (CD) diabetic sedentary control, (DH) diabetic highintensity aerobic exercise, (DL) diabetic low-intensity aerobic exercise or (DR) diabetic resistance exercise. (B) Hsp70 protein content in cardiac tissue following exercise training. There was a significant main effect of exercise training on cardiac Hsp70 levels (p<0.05). SED sedentary rodents, TRAIN exercise-trained rodents, DIA-SED sedentary STZ-induced diabetic rodents, DIA-TRAIN exercise-trained STZ-induced diabetic rodents. Data are mean þ SE.

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in metabolic syndrome (31,32). Chronically elevated SNA exerts deleterious effects on vascular (33,34) and cardiac (33,35e39) tissue. The information regarding sympathetic activation on vascular disease largely is correlative or based on rodent studies. Furthermore, uncertainty surrounds the time course of disordered autonomic outflow during the progression of T2DM, its consequent involvement in cardiovascular complications or how these neurovascular endpoints are affected by preventive/reversal strategies. Little information has been published regarding the impact of metabolic syndrome without diabetes on autonomic dysregulation. The major hypotheses tested in this portion of the ARTEMIS project were as follows: 1) Cardiovascular complications in metabolic syndrome individuals begin in the peripheral microvasculature and progress towards the heart with severity of MetS risk factors, 2) Advanced risk in MetS patients would be associated with disturbed autonomic function marked by heightened sympathetic outflow and 3) A 52-week monitored exercise intervention would improve CVCs in MetS patients. Our objectives were to first adapt the Windkessel modelling approach to study the mechanical properties of the forearm vascular bed so that they could be used in a comprehensive model that quantified vascular mechanics in the central and peripheral conduit vessels as well as the forearm vascular bed that contains a high proportion of microvessels. These measures would be combined with echocardiographic assessments of cardiac structure and function and measures of sympathetic outflow that included muscle sympathetic nerve activity and catecholamines. These measures were then made in obese children and in adults with >3 risk factors for metabolic syndrome (MetSþ) or similarly aged adults with <2 risk factors for MetS (MetS). Our second objective was to assess sympathetic drive in MetSþ and MetS participants using both plasma catecholamines as well as microneurographic (40) techniques. Lastly, we looked to quantify the vascular mechanics, cardiac function and sympathetic responses in MetSþ and MetS participants before and following a 52-week exercise intervention. Methods The developmental aspects of our research were carried out at the fundamental level, seeking mechanisms of control over vascular mechanics and efferent sympathetic discharge patterns. Subsequently, cross-sectional studies were performed to examine how vascular and neural properties were affected by CVD risk in metabolic disorders, followed by interventional studies in MetS participants to study the malleability of the vascular and neural patterns. Interventional study: population studied Studies of people at risk for diabetes and CVD involved examining individuals with metabolic syndrome (MetS) and obesity. MetS represents a cluster of risk factors for diabetes and requires three of the following to be classified as one with Mets: high blood pressure, high glucose, high triglycerides, low HDL levels, overweight and/or large waist circumference. By intent, we did not recruit individuals with high blood pressure or high plasma glucose to avoid the independent effects of these features on vascular health. Individuals with 3 or more of these factors were considered to have MetS (MetSþ), whereas those with fewer than 2 or less were not (MetS). A total of 85 community-dwelling adults, aged 45 to 75 years, were screened, of which 69 met the inclusion criteria and were assigned to an exercise intervention group (n¼39) and a usual care group (n¼30). These participants provided signed consent to the experimental protocols on a form that had been approved by University of Western Ontario’s Health Sciences

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Research Ethics Board. These ethics conformed to the Helsinki Accord. Exercise intervention The exercise group came to the exercise centre 3 times per week and performed a monitored exercise training program for 52 weeks in accordance with guidelines provided by the American College of Sports Medicine which prescribed a combination of aerobic and strength training based on exercise heart rate patterns. The levels of exercise intensity were adjusted every 2 weeks to sustain exercise stimulus. The participants were encouraged to continue their exercise program for 2 days/week without supervision. The usual care group received instructions regarding the exercise program and was encouraged to participate at home on their own volition. Throughout the training program, 34/36 exercise participants performed period testing every 3 months and completed the 52 week program. Of the usual care group, 29/30 completed the yearlong program. Results and Discussion Vascular mechanics and cardiac function A lumped Windkessel model was developed to measure forearm vascular bed mechanics, emphasizing a high proportion of microvascular content (41). To study the impact of hypertension on forearm vascular properties, this model was applied to young healthy individuals as well as uncontrolled hypertensive patients and age-matched controls (42). In contrast to expectations, forearm vascular compliance was similar across groups. However, viscoelastic properties of the forearm vascular bed were elevated in the hypertensive patients relative to the other groups. Regardless, the dynamic responsiveness of the vascular system (i.e., the ability to return pressure/flow patterns to baseline with a perturbation) was normal in all groups. Thus altered vascular viscoelasticity appeared to preserve overall dynamic vascular properties. To study the neural control of forearm vascular properties of vascular resistance, compliance, viscoelasticity and inertance, concurrent measures of brachial artery blood flow and pressure were measured in young individuals during infusions of a-agonist norepinephrine when the myogenic aspect of the forearm was manipulated by positioning the arm above or below the heart (43). Both forearm vascular compliance and viscoelasticity were affected by the myogenic load. Forearm vascular compliance was affected by baseline a-adrenergic control at a low, but not high, myogenic load. However, viscoelasticity was not affected by sympathetic activation. To see if these parameters would reflect early changes in vascular health and whether they changed quickly with a lifestyle intervention, young female smokers were studied before and following a 12-week smoking cessation program that included exercise (44). Forearm vascular compliance was low and viscoelasticity high in smokers compared to non-smoking controls. Following the intervention, forearm vascular compliance was restored to normal levels but viscoelasticity remained elevated above normal (unpublished results). Together, these data indicate that forearm vascular mechanical properties are dynamic variables and that viscoelastic properties appear to be most indicative of vascular dysregulation. This observation remains notable because it suggests that viscoelastic vascular properties may form an important variable of interest for measurement in clinical settings. To study vascular properties across a continuum of risk for CVD, carotid, brachial and forearm vascular variables were assessed in groups of obese but otherwise healthy teenagers, and adults with MetSþ (n¼29) or their age-matched controls (n¼45), and in a

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group of patients with coronary artery disease (T. Gimon and J. Corkall, unpublished data). No differences were observed in any vascular parameter amongst the young, healthy control and MetS participants. Subsequently, the comprehensive model examining central and peripheral vascular mechanics and cardiac function was applied to participants with (MetSþ; n¼29) and without (MetS; n¼45) participants (45). In contrast to the hypothesis that cardiovascular complications are exhibited earliest in peripheral vascular beds in metabolic disorders, we observed that the left ventricular E/A ratio, reflective of LVDD, was reduced in MetSþ participants; whereas all of the carotid, brachial and forearm vascular mechanics were similar between groups. Overall, no evidence was found of significant alterations in vascular properties either within the central elastic conduit arteries, the brachial artery or the forearm vascular bed across a continuum of risk for CVD unless the patients were hypertensive. However, the presence of vascular disease (e.g. coronary artery disease) exposed considerable alterations in the compliance and viscoelastic properties of the central and peripheral vasculature. With no evidence that risk for CVD affected vascular mechanics, our attention turned to the LVDD apparent in the MetSþ participants noted above. To study the impact exercise training on LVDD, these individuals performed the 52-week exercise intervention (46). Exercise training reduced SBP and increased estimated VO2 peak and HDL cholesterol in individuals with MetS. Importantly, 14 individuals with MetSþ (3 risk factors) decreased the number of risk factors below 2 with exercise training, with two individuals reducing their number of risk factors to only 1. This decrease in SBP was not affected by removal from the analysis of the 9 individuals who had either began or increased treatment dose of angiotensin receptor blockers during the course of the study. In addition to the improvements in risk factor profile, exercise training induced a prolongation of IVRT and a decrease in the early diastolic relaxation (E’) variable of the MetSþ group. However, the 52-week exercise intervention did not induce any detectable improvement in E/A ratio of the MetSþ group. Even a sub-analysis of individuals with a pre-intervention E/A ratio <1 (n¼19), exposed little benefit of the exercise intervention (weeks 0: 0.850.09, 12: 0.880.17, 24: 0.910.17, 52: 0.900.19, p¼0.12). Individuals with E/A ratio <1 at the start of training were older (614 vs. 566 years, p¼0.02), and experienced a decrease in SBP (13115 to 12011 mm Hg, p<0.01) as well as an increase in estimated VO2 peak (26.43.8 to 31.15.2 mL/kg/min, p<0.01) from week 0 to week 52 of training. Individuals with an E/A ratio >1 at the start of training had an increase in HDL cholesterol levels (0.960.20 to 1.130.29 mmol/L, p¼0.05) and estimated VO2 peak (35.36.3 to 38.16.7 mL/kg/min, p¼0.02) with exercise training. Therefore, benefits of exercise were observed, but did not include marked improvements in E/A. Autonomic nervous system Methods of assessing autonomic nervous system function in humans rely on analysis of heart rate variability from R-R interval time series, blood pressure variability, cardiovagal baroreflex sensitivity as an analogue of cardiovagal control and markers of sympathetic outflow, such as sympathetic nerve activity (microneurography) and plasma catecholamines. Kiviniemi et al (47) determined the power and the oscillating frequency of lowfrequency (0.04<0.15 Hz) oscillations in systolic blood pressure (SBP) and R-R interval (RRi), as well as cardiovagal baroreflex sensitivity (sequence method) to study autonomic control in groups of healthy YOUNG (333 years), OLDER healthy subjects (625 years), older patients with hypertension (HT, 615 years) and older patients with coronary artery disease without (CAD, 625 years) and with type 2 diabetes (CADþDM, 624 years, n¼28

for all groups). Power (Power [LF]) and median frequency (Med [LF]) of LF oscillations were calculated by power spectral analysis after removing respiratory effects by least-mean-square adaptive filtering. The results indicated that age represents a dominant risk factor for alterations in the spectral power of the LF SBP oscillations, but that the actual oscillating frequency can be modified further by the presence of coronary artery disease. Similarly, cardiovagal baroreflex gain was highest in the young individuals but depressed similarly across all older adult groups regardless of disease risk or coronary artery disease. Therefore, cardiovagal BRS and blood pressure variability stood out as markers of age but were not present in those with a risk for CVD. Oscillations in blood pressure are indirect measures of sympathetic outflow. Measures of sympathetic nerve activity, directed toward skeletal muscle (MSNA), provide direct access to the central nervous system. The limitations of this method in humans can include a lower success rate in obtaining data and regional variations in sympathetic nerve activity, whereby the discharges measured in the leg cannot be used to study sympathetic cardiac activation. Nonetheless, the technique of microneurgraphy can provide powerful information of sympathetic recruitment. To enhance information extraction from the neurograms of MSNA, we developed a wavelet-based template approach (48) and applied this new algorithm to human sympathetic nerve activity (SNA) recordings. The new approach enabled, for the first time, the ability to quantify the number of action potentials contributing to a sympathetic burst and their groupings based on shape. New results from fundamental studies indicated that a) as many as 40 action potentials can be observed per burst of neural activity, and b) a subpopulation of larger and faster-conducting axons exists, reserved for high stress scenarios, such as high chemoreflex or baroreflex stress (49e51). With this algorithm, we have investigated to some extent the impact of metabolic disease risk on efferent sympathetic discharge patterns in groups (n¼7 each) of young individuals and older groups of healthy, MetS, coronary artery disease (CAD) and congestive heart failure (CHF) (Brewer, Zubin, Edgell, Dujic, Shoemaker; unpublished results). Assessing the pattern of bursts in the integrated neurogram (e.g. bursts/min or bursts/100 heart beats), sympathetic outflow increased as a function of age and, with burst/ 100 heart beats as the metric, MetS increases MSNA above the effect of age per se. However, when the raw action potentials/burst and total action potentials per minute were used as the metric, the conclusions change. Specifically, compared with young individuals, action potentials/burst are diminished somewhat in all groups of older adults, except CHF patients, compensating for the higher burst frequency, so that total action potentials/mindarguably a more accurate indicator of sympathetic outflowddoes not change with age or disease risk. In fact, only CHF patients with excessive disease demonstrated excessive sympathetic outflow relative to young controls using action potential analysis. In other words, the action potential analysis approach indicates that neither age nor CVD risk appears to affect overall efferent sympathetic nerve activity, just its discharge pattern. We know very little about the nature or impact of sympathetic discharge patterns. These observations require verification and further analysis, but they have important implications for existing interpretations regarding the effects of age on MSNA, and the role that such patterns have in basic and clinical vascular and cardiac biology as well as the central nervous system changes with age and disease. As with the indices of autonomic outflow based on pressure oscillations and cardiovagal baroreflex analyses, these preliminary findings lead to the hypothesis that age is a dominant determinant of alterations in MSNA discharge and additional risk conferred by MetS is not clear. The requirement for high-quality neural signals represents a limitation of the action potential analysis approach outlined above, limiting the number of data points that can be obtained in a

E. Noble et al. / Can J Diabetes 37 (2013) 282e293 Table 1 Description of sympathetic activity at baseline and after 12 weeks of either an athome or in-lab exercise protocol

n Burst latency (s) Burst frequency (bursts/min) Burst incidence (bursts/100 heart beats) Average burst size (% of max) Median burst size (% of max) Baroreflex sensitivity intercept (bursts/100hb) Resting Norepinephrine (nmol/L) (n¼24)

Baseline

12 weeks

9 1.260.07 4012 6219 499 4710 508350 1.80.8

1.250.06 369 5512* 507 489 331216* 1.81.4

Values are mean  standard deviation. * Significant main effect of time.

longitudinal study. We were able to obtain repeated measurements of MSNA in 9 participants before, and following, 12 weeks of monitored, in-lab, exercise instruction. The results (Table 1) suggest that such hyperadrenergic activity, at least when assessed as sympathetic bursts/100 heart beats, can be attenuated with effect exercise interventions. We warrant caution, however, because the low effect size of these results (0.42) resulted in a low statistical power (31%). Clearly, additional data are needed to test this hypothesis. An additional observation was that cardiovagal baroreflex slope was increased in 21 MetSþ patients following 12 weeks of exercise (Figure 2). In this way, exercise training confers benefit to individuals at risk for CVD by reducing overall risk profile (45,46) and by improving the sympathetic and parasympathetic profile. Interesting to note is that in our interventional study, the MetS groups did not lose weight; their improved risk profile was due largely to improved cholesterol and triglyceride profiles.

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As with vascular indices, the net conclusions of the work in autonomic indices suggests that autonomic nervous system markers are not suitable early markers of CVD in patients at risk for CVD. Rather, age confers the greatest risk. However, these variables are plastic and do improve in response to exercise training. Nonetheless, important new information regarding subpopulations of sympathetic axons, alterations in recruitment patterns and the idea that discharge patterns can be altered in aged individuals (and perhaps disease) provides a new window of opportunity to understand the impact of age and disease on autonomic neural outflow. Cardiovascular disease is the leading cause of death worldwide (52) and T2DM is an independent risk factor for CVD. Central obesity, high blood pressure (BP), dysglycemia and dyslipidemia are some of the major cardiometabolic risk factors implicated in the development of CVD and T2D (53). Clustering of these risk factors, termed metabolic syndrome (MetS), increases the risk of disease progression more in combination that additive risk (53). Each of these disorders by itself is a risk factor for other diseases; however, in combination with each other, they dramatically increase the risk of developing cardiovascular disease and diabetes. Furthermore, although each of the aforementioned disorders in the MetS cluster can be treated individually, the contemporary thinking is to treat MetS, and prevent cardiovascular disease, by targeting risk factors through lifestyle interventions, as the common causes of MetS are poor diet and inadequate physical activity (54). Considering that the prevalence for cardiovascular disease increases with age, the proportion of older adults presenting with MetS will also likely increase steadily as the population ages. Meanwhile, individuals with MetS are 61% more likely to develop cardiovascular disease when compared to individuals without MetS (55). Complications from MetS can develop in less than 15 years, a rate of progression

Figure 2. Varying levels of measured muscle sympathetic nerve activity (MSNA) variables across Young, Older, MET, CAD and CHF groups. Figures 2A and 2B detail differences in measured integrated parameters. Figure 2C and 2D detail differences in measured action potential (AP) content parameters. A significant MANOVA for all parameters measured (see methods) F(32,104)¼2.168, p<0.05, h2¼0.91 suggested that the cannonically combined measured MSNA variables were different between groups. Univariate analysis with Tukey’s HSD post hoc suggested significant differences pictured in plots 1A-D. *, significantly different from Young. z, significantly different from CHF, all p<0.05.

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with significant implications for both public health and clinical interventions directed at high-risk individuals. Adoption of aerobic exercise training in healthy and sedentary middle-aged adults with MetS has also been shown to be an effective strategy to reduce prevalence of MetS (54). Hence, an urgent need to develop comprehensive efforts directed at lifestyle management with a significant emphasis on improving physical activity patterns in this population. Unfortunately for patients with MetS, and for those at risk, the optimal form of exercise and the means of maintaining long-term adoption of exercise intervention is not yet known. A Cochrane review on exercise or exercise and diet for preventing type 2 diabetes (56) demonstrated that interventions aimed at increasing exercise combined with diet are able to decrease the incidence of type 2 diabetes in high-risk groups (i.e. people with impaired glucose tolerance or MetS). Additionally, the authors suggested that there is a need for studies exploring exercise only interventions and studies exploring the effect of exercise and diet on quality of life, morbidity and mortality, with special focus on cardiovascular outcomes. Consequently, our group conducted a systematic review (57) of the evidence supporting the impact of different modes of exercise (aerobic, resistance and combined) on cardiovascular risk factors, to determine the key components for an optimal exercise prescription for patients with MetS in terms of clinical measures (blood pressure, glucose and lipids) as well as markers of CVCs of diabetes. The findings from this review indicated that aerobic exercise alone or combined with resistance training improves glycemic control, systolic blood pressure, triglycerides and waist circumference; however, the impact of resistance exercise alone on cardiovascular risk markers in type 2 diabetes remains unclear (57). Although evidence suggests that exercise can prevent the risk factors and treat the complications of MetS, community-based exercise programs are difficult to administer in a patient population, and success may vary in different settings. We had previously demonstrated the effectiveness and efficacy of an aerobic exercise prescription delivered by family physicians in a community setting (58). One continuing barrier is the availability of family physicians to deliver this prescription, despite their best intentions. There is a growing body of evidence suggesting that with the growth and availability of new technologies, chronic disease management can be delivered using remote monitoring technologies and allied health providers (59). We postulate that these technologies may be ideal to reach patients without ready access to family physicians or to those who live in rural settings without access to health providers and organized health facilities. Consequently, we will investigate exercise prescription by allied health professionals, overseen by a primary care physician, in both an institutional and rural community clinic setting. Rural Ontario has the second highest mortality rates from cardiac causes in Canada, and the Huron-Perth-Grey-Bruce region represents one of the highest cardiac death rates within the province. The percentage of people with type 2 diabetes is 8.0% in GreyBruce and 6.3% in Huron County, as compared to 4.8% reported for all of Canada (54). Mechanisms associated with the progression from MetS to T2D and CVD are poorly understood. Hence, in addition to our objective to implement an evidence-based exercise prescription for patients with METs in primary care, we were also interested in the underlying physiological determinants of CVCs. One such candidate is autonomic dysfunction which has been hypothesized to be an important component of disease progression (60,61). Heart rate variability (HRV) is a noninvasive measurement of autonomic cardiac regulation, which has important prognostic value. Low HRV is associated with increased all-cause and cardiovascular mortality in post-myocardial infarction patients (62,63) and with the development of T2D in a general population (64). Furthermore, in a

population with T2D, those with low HRV were more likely to develop CVD than those with normal HRV values (65). Low HRV is also characteristic of MetS populations (66). Autonomic dysfunction is consistently reported in females with MetS, while findings are more controversial in males (67e69). Studies have used regression models and Pearson correlations to examine associations between HRV parameters and individual MetS components in an effort to determine which MetS risk factors have the greatest effects on HRV. A systematic review showed that MetS risk factors are associated with different HRV parameters and suggested that impaired autonomic function, or low HRV, may be an important mechanism in the continuum of CV risk. However, to date, studies are cross-sectional and associations between longitudinal changes in MetS and HRV have not been examined. Physical activity is recommended as a first-line treatment for MetS (54). Lifestyle changes has proved to reduce disease progression (70,71), and long-term follow up has determined that lifestyle changes are more effective than metformin in reducing the incidence of T2D (71). Exercise also improves HRV in the general population (72) and in T2D (73). These concomitant improvements in MetS risk factors and HRV in response to exercise suggest that they may be linked mechanistically; however, longitudinal associations have not been examined. Despite the well-known health benefits of physical activity, accelerometer data has shown that 85% of Canadians (74) and 90% of Americans (75) do not meet national physical activity guidelines. Electronic health (eHealth) is a relatively new field in which electronic medium is used to support health. While studies are still in their infancy, some successes have been noted (59). Mobile health (mHealth) is a branch of ehealth that has the potential to be better than general eHealth interventions because of the portability. With many people carrying mobile phones and a growing number buying smartphones, mHealth interventions allow for the potential to act as a trigger for a behaviour or to provide information at the time that it is needed. We recently showed that an mHealth supported exercise intervention increased activity and improved MetS risk factors in a rural population (76). Additionally, participants found the technology acceptable and motivational (77). Despite a small sample size and short follow-up period, improvements in HRV were apparent (unpublished data). However, due to the single group design of the pilot study, it is unknown whether the mHealth component had added benefit compared to the exercise intervention alone. Similar to project 2, we hypothesized that an evidence-based exercise prescription aided by mHealth delivery in primary care would improve the reach and impact of our intervention on components of METs, and that this would be implicated by early markers of CVCs risk such that components of the METs would independently predict changes in HRV parameters. Our objectives were to: 1) compare a usual care exercise prescription previously utilized by our group and delivered in urban family practice settings, to delivery using mHealth remote monitoring and electronic counselling, in rural Ontario patients with METs where the rates of CVCs are highest; and 2) to isolate the underlying contribution of HRV on proposed improvement in components of METs and CVCs. Methods This study was part of a randomized controlled trial, in which 149 participants from rural Southwestern Ontario were block randomized to either the prescriptive exercise þ mHealth technology intervention group (INT; n¼75) or a prescriptive exercise control group (CTL; n¼74). To be included in the study, participants were required at screening to have a minimum of 2 of 5 MetS risk factors according to NCEP-ATPIII criteria e waist circumference  88 cm (women) or 102 cm (men); systolic blood pressure (SBP) 135 mm Hg and/or diastolic BP (DBP)  85 mm Hg; fasting plasma glucose

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(FPG)  6.1 mmol/L; fasting triglycerides (TG) 1.7 mmol/L; fasting high-density lipoprotein cholesterol (HD) 1.29 mmol/L (women) or 1.02 mmol/L (men) (ATPIII, 2002). Exclusion criteria were: systolic blood pressure (SBP) >180 mmHg and/or diastolic blood pressure >110 mm Hg; uncontrolled hypertension; type 1 diabetes; history of myocardial infarction, angioplasty, coronary artery bypass or cerebrovascular ischemia/stroke; symptomatic congestive heart failure; atrial flutter; unstable angina; unstable pulmonary disease; use of medications known to affect heart rate (HR) (such as beta blockers), or use of other medication that may interfere with study objectives; second or third degree heart block; pacemaker; unstable metabolic disease and orthopedic or rheumatologic problems that could impair the ability to exercise. The study was approved by the University of Western Ontario research ethics board and participants provided informed consent to participate. Participants reported to the Gateway Rural Health Research Institute (Seaforth, Ontario) at baseline (V0), 12 weeks (V1), 24 weeks (V2) and 52 weeks (V3). This paper reports findings up to V2. Automated BP was measured in the supine position (BPTruÔ) and the average of the last 2 of 3 measures was used to determine clinic BP. WC was measured as the midpoint between the lower rib and iliac crest (cm). Blood was drawn and sent to a central laboratory for measurement of FPG, triglycerides and HDL. Autonomic testing Following a light, standardized snack, participants were instrumented for collection of a lead II ECG recording. A respiratory belt (Pneumotrace II; ADInstruments, Dunedin, New Zealand) was secured around the thorax for collection of respiratory rate. RR intervals (RRI) were collected during 10 minutes of supine rest. External stimuli, such as light and noise, were controlled to ensure signal stability. Participants were instructed to remain still and awake. All measures were sampled at 1000 Hz, input into a data acquisition board (PowerLab ML795; ADInstruments) for analogueto-digital signal conversion with LabChart7Pro software (ADInstruments) and stored for offline analysis. Exercise testing and prescription Fitness (VO2max; ml/kg/min) was estimated with the Step Test Exercise Prescription (STEPÔ) tool, which has been validated in adults aged 18 to 85 (78) (Knight et al, in preparation). The full protocol has been published elsewhere (79). Briefly, participants were instructed to step up and down a set of 2 steps 20 times at a comfortable pace. Heart rate was measured immediately following the test by palpation of the radial artery. The following equation was used to estimate VO2max:

VO2max ¼ 3:9 þ ð1511=timeÞ$ðO2 pulse$0:124Þ  ðage$0:032Þ  ðsex$0:633Þ; where VO2max is predicted maximal oxygen uptake (L/min), time is the time to complete the stepping test (s); O2pulse is calculated as body mass (kg) divided by HR (bpm) palpated immediately upon completion of the stepping test; age is the patient’s age (y) and sex is 1 for males and 2 for females. Absolute VO2max was converted to relative (ml/kg/min) for classification according to fitness level. A tailored exercise program including target HR based on fitness level (70% to 85% maximum age-predicted HR) was prescribed based on the results of STEPÔ and an exercise specialist helped participants set SMART (specific, measurable, attainable, realistic, timed) goals. For INT, goals included increasing steps per day with pedometer monitoring, with the overall goal of achieving 10,000 steps per day. The exercise program and goals were updated at each visit.

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Mobile health intervention Participants received a Smartphone (Blackberry Curve 8300 or 8530; Blackberry, Waterloo, Ontario Canada) equipped with Healthanywhere (IgeaCare) health monitoring software, a Bluetooth enabled BP monitor (UA-767PBT; A & D Medical, Tokyo, Japan), a glucometer (Lifescan One Touch Ultra2Ô; Lifescan, Milpitas, California) with Polymap wireless Bluetooth adapter (PWR08-03) and a pedometer (HJ-150; Omron, Shimogyo-ku, Kyoto, Japan). A group training session (approximately 2-hour duration) was delivered at V0, during which participants were instructed on proper use of devices and techniques to get proper measurements. FPG and BP measures were to be submitted thrice weekly upon waking and pedometer steps were to be input nightly. Real-time measurements were sent to a secure central database that was monitored regularly by researchers. Limits were set for SBP at 60 mm Hg and 210 mm Hg; DBP at 40 mm Hg and 120 mm Hg; fasting glucose at 3 mmol/L and 15 mmol/L. Readings that were outside of these limits triggered alarms that automatically sent a message to the study physician’s smartphone to follow up with the participant. Details of database security are reported elsewhere (77). Heart rate variability analysis LabChart files were converted to text files for analysis with HRV software (Hearts v7; Heart Signal Co., Oulu, Finland). The HR time series was edited by a single investigator. All ECG signals were manually scanned for ectopic or non-sinus beats, which were deleted from the time series. Datasets were excluded from analysis when more than 10% of beats were edited. Time domain HRV analyses included HR, SDNN and the root square mean of successive differences (RMSSD). The HRV spectrum was computed with the nonparametric fast Fourier transform method. Very low frequency (VLF: 0.003-0.04Hz), low frequency (LF: 0.04-0.15Hz), high frequency (HF: 0.15-0.4Hz), LF/HF and total power (TP: 0.003-0.4Hz) were examined. Each RRi against the following one to create a Poincaré plot. The standard deviation of the width (SD1) and length (SD2) were calculated. Statistical analysis Baseline characteristics were compared between groups with unpaired t tests for outcome measures with normal distribution or a two-sample Wilcoxon test for outcome measures that were not normally distributed. Repeated measures analysis of variance (ANOVA) were used to observe group and time differences between MetS risk factors, fitness and HRV parameters that were normally distributed, and ANOVA on ranks was used for nonparametric outcomes (Sigma Plot v. 11.0; Sigma-Aldrich). Multiple linear regression models were used to investigate how changes in MetS components predicted changes in HRV, while adjusting for other variables and baseline values. All results are shown as mean  standard deviation for normally distributed data, median (interquartile range; IQR) for nonparametric data, and multiple linear regression results are presented as estimate (95% confidence interval; CI), unless otherwise specified. R statistical software was used for analysis. Results and Discussion Participant characteristics After removal of incomplete data, 116 participants were included in the final analysis (Table 2). FPG (p¼0.008) was higher in the intervention group compared to the control group, but groups were otherwise similar.

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Longitudinal changes in metabolic syndrome risk factors and heart rate variability parameters At V1, systolic BP was reduced in both groups but significantly more in the control group (difference in mean change: 5.68; 95% CI: 10.86, 0.50, p¼0.03), and CRPhs was also significantly reduced in the control group (difference in mean change: 0.45; 95% CI: 0.88, 0.01, p¼0.04). There were no differences between groups at V1 for other outcomes. Across the follow-up period, systolic BP, diastolic BP, waist circumference, total cholesterol, LDL and HbA1c were decreased, and VO2max was increased for the entire study population (p<0.001), with no difference in rate of change between groups. There were no changes in triglycerides or HDL. FG, insulin and CRPhs were significantly higher in the intervention group, compared to the control group, across the entire follow-up period (p<0.05) and FG increased over time for the entire study population (p¼0.01). HR was reduced at V1 compared to V0 (p¼0.016), but returned to baseline at V2. RMSSD and SD1 were reduced at V2 compared to V0 (p¼0.020 and 0.006, respectively), but there were no other significant changes in HRV parameters over time. Associations between changes in metabolic syndrome risk factors and heart rate variability Multiple linear regression (Table 3) showed that the change in HR and SDNN were independently predicted by the change in WC (p¼0.033) and FPG (p¼0.048), respectively. The change in VLF was independently predicted by the change in WC (p¼0.014) and FPG was included in the model to improve the fit (p¼0.07), though it did not have predictive value. The change in a1 was independently predicted by the change in SBP (p¼0.045) and TG was included in the model to improve the fit (p¼0.066). The change in MetS risk factors over the intervention period did not predict the change in HRV parameters RMSSD, LF, HF, TP, LF/HF, SD1 or SD2. The main findings of this study were that: 1) cardio-metabolic risk factors improved with both standard and mHealth supported prescriptive exercise interventions; 2) WC, SBP and FPG were the only MetS components that independently predicted changes in HRV, and only changes in HR, SDNN, VLF and a1 were associated with MetS component changes; 3) HR was transiently reduced and rMSSD and SD1 were reduced following the intervention period with no other changes in HRV; and 4) SBP and DBP were reduced following the 24-week intervention with no change in other MetS risk factors and no differences between treatment groups. Previous studies have examined associations between HRV parameters and MetS risk factors in cross-sectional studies. To our knowledge, this was the first study to examine these associations over a longitudinal intervention period. Interestingly, associations with changes in HRV and MetS risk factors overtime were different than cross-sectional associations. Changes in the HRV parameters that are traditionally considered to be reflective of vagal activity Table 2 Participant characteristics

n Age (y) WC (cm) SBP (mm Hg) DBP (mm Hg) FPG (mmol/L) TG (mmol/L) HDL (mmol/L) HOMA-IR VO2max (mL/kg/min) *

indicates p<0.05.

Intervention

Control

p

62 58.0 (14.0) 105.212.6 14120 8613 5.1 (0.9) 1.42 (0.76) 1.34 (0.57) 1.90 (1.66) 30.006.34

54 59.5 (11.8) 101.713.8 14219 8710 4.9 (0.5) 1.31 (1.05) 1.45 (0.47) 1.37 (1.01) 31.406.25

0.482 0.151 0.926 0.690 0.013* 0.791 0.312 0.010* 0.236

Table 3 Multiple linear regression examining contribution of change in metabolic syndrome risk factors to change in heart rate variability parameters Estimate HR WC SDNN FPG VLF WC FPG

a1 SBP TG *

95% Confidence Interval

p

(0.011, 0.247)

0.033*

3.332

(6.629, 0.035)

0.048*

0.021 0.114

(0.004, 0.038) (0.239, 0.011)

0.014* 0.074

0.003 0.038

(0.006, 7.0x105) (0.078, 2.5x103)

0.045* 0.066

0.129

F-statistic

Adjusted R2

5.786

0.224

6.075

0.2314

5.945

0.3211

16.58

0.541

indicates p<0.05.

during supine rest (rMSSD, HF, SD1) were not independently predicted by change in MetS risk factors, though in cross-sectional analyses, these HRV parameters were independently predicted by WC and FPG. On the other hand, parameters with sympathetic influence, were associated with changes in MetS risk factors. The change in HR was independently predicted by changes in WC. In the Diabetes Prevention Program, a higher baseline HR was related to incident diabetes (80). Preliminary results have suggested that HR may be reflective of sympathetic activity in MetS population (81) and may be responsible for normalization of sympathetic activity seen as a reduction in HR. Previous studies have shown that exercise improves HRV; however, in some studies, resting HRV was not a sensitive enough measure to detect subtle changes in autonomic function. Our recent meta-analysis of exercise effects on cardiovascular risk factors in T2D showed that aerobic exercise resulted in reduced glycated hemoglobin (a measure of glycemic control over the past 12 weeks), SBP and TG, with no changes in HDL or WC (57). Our prescriptive exercise intervention may have failed to change FPG, as the mean was within healthy limits and only seven individuals (6%) had a FPG >6.1 mmol/L to qualify as a risk factor. Similarly, the mean TG was also within healthy range. On the other hand, both SBP and DBP were elevated outside normal ranges (>135/85) at V0 and, therefore, had greatest potential for improvement. This intervention used the STEP tool for exercise counselling, which has proved to effectively increase fitness and improve MetS risk factors (79). Indeed, the 7% and 6% reductions in SBP and DBP, respectively, are similar to changes that have been seen with other interventions using STEP (79) and in line with changes in BP with exercise in hypertensive populations (82)dreduced by 6.9/4.9 mm Hg compared to our 10/5 mm Hg). The 7% increase in VO2max was lower than other studies employing the STEP intervention (79), which suggests that exercise goals may not have been met and may explain in part lack of change of some MetS risk factors. It is also salient that the study population hailed from rural communities with limited support for structured exercise venues which may impact the magnitude expected changes. Regardless and contrary to our hypothesis, there were no differences between mHealth and standard prescriptive exercise. Two systematic reviews have had conflicting results regarding the effectiveness of eHealth on physical activity and weight loss (59,83). Hence, mHealth may be more effective than other types of eHealth interventions due to their portability and convenience and their ability trigger behaviours or provide support at the appropriate time. Since the participants in our intervention primarily used their smartphone as a data portal for submitting measures, the full potential of the smartphonebased intervention may not have been realized. In conclusion, this 6-month interim report showed that changes in MetS components were common to mHealth and standard prescriptive exercise, while HR, VLF, SDNN and a1 were associated with changes in

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MetS risk factors but HRV parameters indicative of vagal activity were not. Type 1 diabetes (T1D) arises from autoimmune destruction of pancreatic beta cells, leading to a complete dependence on exogenous insulin for the regulation of blood glucose level. Although T1D is a significant medical problem all over the world, the geographic variation in its incidence is noticeable, with exceptionally high rate observed in Finland (83). The substantial increase in the incidence of T1D over recent decades cannot be the consequence only of enhanced genetic disease susceptibility in the population, but must be caused largely by changes in lifestyle and environment. After 20 to 25 years, 20% to 30% of T1D patients develop diabetic nephropathy, characterized by increased arterial blood pressure, a relentless decline in renal function and a 40-fold increased risk of early death due to cardiovascular disease (84,85). In T1D, elevated blood glucose is treated by delivering of exogenous insulin in a controlled setting and by controlling diet and energy consumption (e.g. physical activity). Determination of exercise and aerobic capacity (V_ O2peak) is of special interest in populations with chronic diseases, as V_ O2peak is a strong predictor of the risk for cardiovascular complications (86). In T1D patients, previous studies have reported similar (87) and lower (88) exercise capacity and V_ O2peak than in healthy controls. The mechanism(s) related to O2 delivery by which T1D can alter responses to exercise and lead to reduced V_ O2peak have been reported to include lower ventilation (89), impaired lung diffusion capacity (90), restrictions of cardiac output and stroke volume (91), and impaired hyperemic response in the muscle (92). The existence and severity of these impairments in O2 delivery cascade, however, are reported to be dependent on diabetic complications and longterm blood glucose levels (93). In the ARTEMIS-Helsinki study, we examined previously uncovered factors that might provide new insights on the possible mechanisms for impaired exercise capacity and increased risk for cardiovascular complications in T1D. We were especially interested in blood O2 carrying capacity and tissue oxygenation during incremental exercise. Additionally, impaired cardiovascular autonomic nervous system (ANS) function has been reported in T1D patients (94). We examined cardiovascular autonomic nervous system function (ANS) at rest during orthostatic and handgrip tests. Here, we will summarize our novel findings (95e98) in T1D patients. Methods Patients with T1D had normal urinary albumin excretion rate, normal estimated glomerular filtration ratio and no diagnosed diabetes-related complications. Healthy control subjects were matched by age, anthropometry and self-reported physical activity. The experimental protocol consisted of two visits to the laboratory, as previously reported (95e98). Briefly, pre-exercise measurements (questionnaires on leisure-time physical activity, anthropometry, spirometry, ECG) and a cardiopulmonary exercise test on a cycle ergometer were performed on the first visit. On the second visit, cardiovascular ANS function at rest and during function tests were recorded, followed by blood O2 carrying capacity measurement, to determine total hemoglobin mass (tHb-mass), erythrocyte volume (EV), plasma volume (PV) and blood volume (BV) (98). Results and Discussion Type 1 diabetes patients had w25% lower exercise capacity and aerobic capacity than healthy controls, despite being matched for similar age, anthropometric data and self-reported physical activity (95e98). Despite similar and normal hemoglobin concentration and hematocrit, T1D patients had 14% (126 g) lower tHb-mass and

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PV, resulting in 14% (913 ml) lower blood volume (BV) than healthy controls (96). Our results suggest that tHb mass together with BV are more sensitive variables to indicate early changes in blood O2 carrying capacity than hemoglobin concentration alone, providing additional information also for the clinical status in T1D. The relationship between V_ O2peak and blood O2 carrying capacity was different in T1D patients and controls. In patients compared to controls, the increase in V_ O2peak was approximately 33% and 50% smaller for a given increase in tHb-mass and BV, respectively. In addition to blood O2 carrying capacity, our results indicate other factors being involved in reduced aerobic capacity in T1D patients. Especially, enhanced deoxygenation rate in diabetic leg muscle during incremental cycling suggests increased dependence on O2 extraction in providing adequate V_ O2 at a given work rate (97). This finding may also suggest lower cardiac output and/or impaired peripheral vascular function at a given and at peak work rate in patients than controls, and potentially offers one explanation for the observed difference in V_ O2peak. At peak exercise, however, leg muscle deoxygenation proceeded to a similar level, suggesting equivalent O2 delivery/O2 utilization mismatching in both groups. Cerebral deoxygenation was similar in patients and controls (97). Previously, cardiovascular ANS function, evaluated by heart rate variability (HRV), systolic blood pressure variability (SBPV) and baroreflex sensitivity (BRS) have been linked to aerobic capacity in healthy subjects; but this relationship is unknown in T1D. We found that in HRV analysis of detrended fluctuation (DFA), the increase of alpha1 during both active standing and the handgrip test was smaller in T1D patients than in controls. This could indicate attenuated responsiveness of sympathetic function in T1D patients. Interestingly, parasympathetic cardiac ANS variables at rest were associated with V_ O2peak in controls, but not in T1D patients. Our results (95) suggest that T1D patients had weaker HRV response to manoeuvres, but not impaired cardiovascular ANS function at rest compared with controls, and that the alpha1 parameter of DFA method in connection with these manoeuvres may be one of the most sensitive indicators of early ANS function changes in T1D. In summary, T1D patients have low aerobic capacity, which may be an early marker of the risk for cardiovascular complications in these patients. Measuring total Hb mass, blood volume and tissue oxygenation, we have been able to add new information on early markers of reduced exercise capacity and potential risk factors for cardiovascular complications. We also observed that young T1D patients do not have impaired cardiovascular ANS function at rest compared with controls, but they may have weaker HRV response to different manoeuvres measuring ANS. Therefore, it is vital not only study T1D patients at rest but during exercise and common everyday challenges. Conclusion This article has described selected collaborative project products from our team in Canada and Finland along the continuum of CVCs of diabetes risk, from the laboratory to the point of care. Specifically, our key findings suggest the following: 1. During the course of our experiments in animals, it became apparent that a sedentary lifestyle may lead to diabetes. This is largely a function of aging. Furthermore, severe diabetes appears to act negatively upon cardiovascular responses to exercise. As such, further studies will examine vascular deterioration and the effect of exercise in aging individuals. 2. Vascular compliance (stiffness) appears to be regulated independently from the better-known variable of vascular resistance so that in the populations studied, the dynamic responsiveness of the vascular bed, as expressed in the pattern of compliance and resistance variables, is sustained in vascular

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disease. The assessment of postganglionic recruitment strategies is a major missing element in understanding neural and vascular control and health in humans, whereby our data suggest that there is more than one “population” of postganglionic sympathetic neuron and that an additional latent population of postganglionic sympathetic neurons exists and recruitment of this group is reserved for stressful circumstances. Thus this model will be extremely important in establishing the changes in neuronal discharge patterns along the continuum of risk for vascular disease in our project. 3. Preliminary evidence from our RCT (ARTEMIS RCT) support the implementation of prescriptive exercise at the point of care including the primary care setting using expertise of allied health team members, as well as leveraging health technologybased or mHealth tools in high risk populations in rural and remote regions. Improvement in MetS components were observed, but interestingly, at 24 weeks, mHealth supported prescriptive exercise did not improve upon our standard primary care exercise intervention. Heart rate variability, as an underlying mechanism of prescriptive exercise in this population, was associated with changes in MetS risk factors, but HRV parameters indicative of vagal activity were not. 4. The mechanism(s) related to O2 delivery by which T1D can alter responses to exercise and suggest that tHb-mass together with BV are more sensitive variables to indicate early changes in blood O2 carrying capacity than hemoglobin concentration alone, and would thus provide additional information also for the clinical status in T1D. HRV could indicate attenuated responsiveness of sympathetic function in T1D patients. We observed that parasympathetic cardiac ANS variables at rest were associated with V_ O2peak in controls but not in T1D patients, suggesting that T1D patients had weaker HRV response but not impaired cardiovascular ANS function at rest compared with controls. Acknowledgements The authors wish to acknowledge Arlene Fleischauer and Sheree Shapiro for their technical assistance. This research was supported by the Canadian Institute for Health Research (Team Grant #83030). Author Disclosure All authors as well as those acknowledged in this manuscript, do not have any conflicts of interest to disclose. References 1. Chakraphan D, Sridulyakul P, Thipakorn B, et al. Attenuation of endothelial dysfunction by exercise training in STZ-induced diabetic rats. Clin Hemorheol Microcirc 2005;32:217e26. 2. De Angelis KL, Oliveira AR, Dall’Ago P, et al. Effects of exercise training on autonomic and myocardial dysfunction in streptozotocin-diabetic rats. Braz J Med Biol Res 2000;33:635e41. 3. Paulson DJ, Kopp SJ, Peace DG, et al. Improved postischemic recovery of cardiac pump function in exercised trained diabetic rats. J Appl Physiol 1988;65:187e93. 4. Gava NS, Veras-Silva AS, Negrao CE, et al. Low-intensity exercise training attenuates cardiac beta-adrenergic tone during exercise in spontaneously hypertensive rats. Hypertension 1995;26:1129e33. 5. Pang TT, Narendran P. Addressing insulin resistance in Type 1 diabetes. Diabet Med 2008;25:1015e24. 6. Bergman BC, Howard D, Schauer IE, et al. Features of hepatic and skeletal muscle insulin resistance unique to type 1 diabetes. J Clin Endocrinol Metab 2012;97:1663e72. 7. Ivy JL. Role of exercise training in the prevention and treatment of insulin resistance and non-insulin-dependent diabetes mellitus. Sports Med 1997;24: 321e36. 8. Bacchi E, Negri C, Zanolin ME, et al. Metabolic effects of aerobic training and resistance training in type 2 diabetic subjects: a randomized controlled trial (the RAED2 study). Diabetes Care 2012;35:676e82.

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