Aerobic exercise training improves endothelial function and attenuates blood pressure reactivity during maximal exercise in chronic kidney disease

Abstract

Patients with chronic kidney disease (CKD) have exaggerated increases in blood pressure during exercise that are associated with endothelial dysfunction. We hypothesized that aerobic exercise training would improve endothelial function and attenuate blood pressure reactivity during exercise in CKD. Sedentary individuals with CKD stages III–IV underwent 12 wk of aerobic cycling exercise (n = 26) or nonaerobic exercise (n = 22, control). Both interventions were performed 3 days/wk and matched for duration. Endothelial function was measured via peripheral arterial tonometry and quantified as reactive hyperemia index (RHI). Peak oxygen uptake (V̇o_2peak) was assessed via maximal treadmill exercise testing with concomitant blood pressure monitoring. All measurements were performed at baseline and after the 12-wk intervention. A linear mixed model was used to compare the rate of increase in blood pressure during the test. RHI improved with exercise (Pre = 1.78 ± 0.10 vs. Post = 2.01 ± 0.13, P = 0.03) with no change following stretching (Pre = 1.73 ± 0.08 vs. Post = 1.67 ± 0.10, P = 0.69). Peak systolic blood pressure during the maximal treadmill exercise test was lower after exercise training (Pre = 186 ± 5 mmHg, Post = 174 ± 4 mmHg, P = 0.003) with no change after stretching (Pre = 190 ± 6 mmHg, Post = 190 ± 4 mmHg, P = 0.12). The rate of increase in systolic blood pressure during the V̇o_2peak test tended to decrease after training for both groups (−2 mmHg/stage) with no differences between groups (P = 0.97). There was no change in V̇o_2peak after either intervention. In conclusion, aerobic exercise training improves endothelial function and attenuates peak blood pressure reactivity during exercise in CKD.

NEW & NOTEWORTHY Patients with chronic kidney disease (CKD) exhibit increased blood pressure reactivity during exercise that is associated with endothelial dysfunction. Twelve weeks of structured, aerobic, exercise training improves endothelial function and attenuates peak blood pressure responses during exercise in CKD stages III–IV.

INTRODUCTION

Patients with chronic kidney disease (CKD) exhibit exaggerated blood pressure reactivity during exercise that is independently associated with an elevated risk of cardiovascular mortality (1, 2). This heightened blood pressure reactivity is present during submaximal exercise utilizing small muscle mass (i.e., handgrip) (3, 4) and during whole body maximal treadmill exercise (5). Exaggerated blood pressure reactivity during exercise not only decreases exercise efficiency and increases cardiovascular risk during physical activity but also holds prognostic significance as it predicts greater risk of adverse cardiovascular events including stroke (6) and myocardial infarction (7). This is of particular clinical relevance in CKD, since cardiovascular disease is the primary cause of death in this population (8–10).

One mechanism that may contribute to exaggerated blood pressure reactivity during exercise in CKD is endothelial dysfunction. The endothelium plays a critical role in the production of nitric oxide (NO), which opposes sympathetically mediated vasoconstriction to skeletal muscles during exercise via local vasodilation in response to shear stress (11–13), and acts centrally to attenuate sympathetic outflow (14, 15). Both endothelial dysfunction and reduced NO bioavailability are present in CKD and increase in severity with disease progression (16–18). Endothelial dysfunction has previously been associated with exaggerated blood pressure responses during exercise in healthy individuals (19, 20), and we have recently extended these findings to CKD (5). Collectively, these observations suggest that the endothelium may be a viable target for improving blood pressure regulation during exercise in CKD.

Aerobic exercise training improves endothelial function in healthy individuals (21–23); however, these findings have not conclusively been extended to CKD. Although several animal studies report improvements in endothelial function in response to exercise training (24, 25), these findings have not always translated into human studies (26). One recent study did report improvements in microvascular function in CKD following 12 wk of aerobic exercise training, but blood pressure reactivity was not assessed (27). The purpose of this study was to evaluate endothelial function and blood pressure reactivity following 12 wk of aerobic exercise training compared with a nonaerobic exercise control intervention in patients with CKD. We hypothesized that 12 wk of aerobic exercise training would improve endothelial function and attenuate blood pressure reactivity during maximal exercise in patients with CKD stages III and IV.

METHODS

Ethical Approval

This study was approved by the Atlanta Veterans Affairs (VA) Health Care System Research and Development Committee and the Emory University Institutional Review Board. Written informed consent was obtained for all study participants, and all study procedures conformed to the standards set forth by the Declaration of Helsinki. This study is registered at clinicaltrials.gov (NCT 02947750).

Participants

Sedentary individuals with CKD stages III or IV [estimated glomerular filtration rate (eGFR) between 15 and 59 mL/min/1.73 m²], as defined by the CKD-EPI equation (28), were recruited from Emory University clinics and the Atlanta Veterans Affairs (VA) Health Care System for participation in this study. All participants engaged in less than 20 min twice per week of self-reported physical activity and had stable renal function (no greater than a decline of eGFR of 1 mL/min/1.73 m²/mo over the prior 3 mo). Exclusion criteria included uncontrolled hypertension (BP > 160/90 mmHg), vascular disease, use of clonidine, clinical evidence of heart failure or active heart disease determined by history, electrocardiogram (ECG) or echocardiogram, ongoing illicit drug use, alcohol use >2 drinks/day within the past 12 mo, diabetic neuropathy, severe anemia (hemoglobin <10 mg/dL), and pregnancy or plans to become pregnant.

Experimental Design

Participants were randomly assigned to one of two structured, supervised interventions that took place at a frequency of 3 days/wk for the duration of 12 wk (36 sessions total). The aerobic exercise intervention (“spin”) was administered to test the effects of aerobic exercise training on cardiovascular health in CKD. The nonaerobic control intervention (stretching and balance) was administered in parallel as the active control intervention that was conducted within the same group-based environment. For assessments, Protocols 1 and 2 were performed before the first session of either intervention, separated by at least 24 h, and were repeated within 1 wk following completion of the final (36th) training session. Both exercise and stretching interventions were supervised by an exercise physiologist and were performed at the Movement Studies and Aerobic Exercise Laboratory at the Atlanta VA Health Care System.

Protocol 1: Maximal Exercise Testing

Participants reported to the Movement Studies and Aerobic Exercise Laboratory at the Atlanta VA Health Care System after abstaining from exercise for at least 24 h before the study. Participants on medications took their prescribed medications as scheduled. Participants were instrumented with a 12-lead ECG for assessment of heart rate (HR) and for monitoring by a licensed physician to ensure participant safety during the testing. Expired gases were collected via a metabolic cart (Cosmed Quark CPET, Concord, CA) for assessment of peak aerobic capacity (V̇o_2peak). After instrumentation, the exercise test commenced in accordance with the modified Balke protocol (29). Briefly, this protocol consisted of 2-min stages at a fixed speed (3.0 miles/h) whereas treadmill grade increased progressively with each stage. A single trained investigator performed manual blood pressure measurements during the treadmill test using an appropriately sized blood pressure cuff. One measurement was made during the last 30 s of each 2-min stage. This measurement started at exactly 1.5 min into each stage and was completed within the last 5 s. Testing was terminated when subjects reached volitional fatigue or if a plateau in V̇o₂ was achieved so that V̇o₂ did not increase further with increasing workloads.

Protocol 2: Assessment of Endothelial Function

Endothelial function was assessed via peripheral arterial tonometry using the EndoPAT2000 device (Itamar Medical Ltd., Caesarea, Israel). This method is reproducible and is commonly used method to assess endothelial function in healthy and clinical populations (30–32). Inflatable pressure cuffs were attached to the index fingers of both hands whereas the participants rested in the supine position. A blood pressure cuff was attached to the participant’s nondominant forearm. After a 10-min resting baseline, the blood pressure cuff was inflated to a suprasystolic pressure (>250 mmHg) for a period of 5 min, followed by rapid cuff deflation. Reactive hyperemia index (RHI) was calculated from the occluded arm and normalized to measurements obtained from the nonoccluded control arm to account for nonendothelium-dependent systemic effects. A higher RHI value reflects a greater degree of endothelial function (33, 34). Body composition was also assessed during this visit via bioelectric impedance (S10 Body Water Analyzer, InBody, Cerritos, CA).

Aerobic Exercise Intervention

This intervention consisted of group-based, progressive, “spin” exercise on a stationary bicycle three times per week for 12 wk (total of 36 sessions) and has been used previously in sedentary older adults (35). The duration of each session began at 20 min during week 1 and was progressively increased by 1–2 min as tolerated by the participant to a maximum of 45 min/session. The average length of time to reach an exercise duration of 45 min was 30 sessions. Each exercise session was supervised and directed by a trained exercise physiologist. Maximal heart rate was calculated as 220-age, and exercise intensity was individualized to each participant based on maximal heart rate reserve (HRR) as calculated by the Karvonen method (36) and was targeted to maximize the time that participants maintained HR between 50% and 85% of maximal HRR. Each session began with a 5-min warm up, followed by an interval-based, workout phase that included short bouts of high-intensity sprints and climbs as previously described (35). HR was continuously monitored via a wireless HR monitor (FT7 Polar Heart Rate Monitor) to ensure that all participants maintained their target HR range throughout the duration of each session.

Stretching and Balance Intervention

This control intervention consisted of balance and stretching exercise for 12 wk (36 sessions) and was matched to the exercise intervention for frequency (3 days/wk) and duration (20–45 min). Participants performed static and dynamic balance exercises and low-intensity core strengthening exercises using a combination of body weight exercises, light weights, and elastic bands. HR was monitored to gauge exercise intensity and maximize the time that heart was maintained below 50% of HRR.

Data Analysis

Because of the sedentary and clinical nature of our participants, V̇o_2max (evidenced by a plateau in V̇o₂ despite an increase in workload) was not achieved in the majority of participants; thus, V̇o_2peak was defined as the highest V̇o₂ value observed at any point during the test and reported as our index of exercise capacity. For endothelial function data, the tonometry waveform was manually inspected to ensure no cuff leaks and that complete occlusion was achieved and maintained during the entire 5-min occlusion. RHI was calculated via an automated algorithm from specialized software (EndoPAT). All data are presented as means ± SE.

Statistics

Statistical analysis was performed in R (v. R4.1.2). Demographic data between groups were compared via unpaired, two-tailed, t tests for continuous variables or χ² analysis for categorical variables. RHI, V̇o_2peak, exercise duration, body composition, and resting hemodynamic and laboratory parameters were compared between groups via a two-way repeated-measures ANOVA (group by time) followed by Tukey’s post hoc tests. Peak blood pressure responses during exercise were compared between groups via a linear mixed model. The following covariates were considered: change in RHI, BMI, and eGFR. The rate of increase (i.e., slope) in HR, systolic blood pressure, and diastolic blood pressure during exercise were compared via a linear mixed model with random slope assuming data are missing at random conditional on V̇o_2peak. The fixed effects part of the fitted linear mixed model is shown below:

E(Y_ij) = β0 + β1 · group + β2 · condition + β3 · group · condition + β4 · stage + β5 · V̇o_2peak + β6 · group · stage + β7 · condition · stage + β8 · group · condition · stage.

In this model, “Y_ij” represents the blood pressure or HR measurement of ith subject at jth stage point, “group” represents stretching or exercise, and “condition” represents pre- versus postintervention. Using this approach, the regression for each group can be presented as:

Stretching + Pre: β0 + β4 · stage,

Exercise + Pre: β0 + β1 + (β4 + β6) · stage,

Stretching + Post: β0 + β2 + (β4 + β7) · stage,

Exercise + Post: β0 + β1 + (β2 + β3 + (β4 + β6 + β7 + β8) · stage.

Based on our hypothesis that improvements in endothelial function would be associated with reductions in blood pressure reactivity, a subanalysis was performed to examine the correlation between the improvement in RHI and the reduction in blood pressure reactivity during exercise following training using linear regression.

RESULTS

Participants

A total of 48 participants were enrolled for study participation. Demographic data and baseline characteristics for these participants are presented in Table 1. The majority of participants in each group were Black males. There were no differences in age, sex, race, body mass index (BMI), smoking status, comorbidities, or medication use between groups.

Table 1.

Participant demographic data

Characteristic	Exercise	Stretching	P
n	26	22
Age, yr	65 ± 1	64 ± 2	0.49
Sex, M/F	20/6	18/4	0.68
Race, n (%)			0.05
Black	25 (96%)	17 (77%)
White	1 (4%)	5 (23%)
Body weight, kg	100.4 ± 3.2	96.8 ± 3.5	0.45
Body mass index, kg/m2	32.5 ± 1.3	31.9 ± 1.2	0.73
Diabetes, n, %	14 (54%)	9 (41%)	0.37
Hypertension, n, %	25 (96%)	20 (91%)	0.45
Anti-hypertensive medications, n, %
Calcium channel blockers, n, %	16 (62%)	14 (22%)	0.88
ACE inhibitors/ARBs, n, %	15 (58%)	13 (59%)	0.92
Diuretics, n, %	13 (50%)	6 (27%)	0.07
β-Blockers, n, %	11 (42%)	7 (32%)	0.45
α-Blockers, n, %	4 (15%)	3 (14%)	0.86
Hydralazine, n, %	1 (4%)	2 (9%)	0.45

ACE, angiotensin converting enzyme; ARB, angiotensin receptor blocker; F, female; M, male.

Adherence

Intervention adherence was high in both groups with no differences between groups (P = 0.25). Participants in the exercise group completed 86% ± 2% of prescribed sessions whereas those in the stretching group completed 89% ± 2% of sessions.

Endothelial Function

RHI was collected before (Pre) and after (Post) the 12-wk intervention in 34 of the 48 participants (n = 21 exercise, n = 13 stretching). RHI improved with exercise only (Pre = 1.78 ± 0.05 vs. Post = 2.01 ± 0.13, P = 0.03) with no change following stretching (Pre = 1.73 ± 0.08 vs. Post = 1.67 ± 0.10, P = 0.69, Fig. 1).

Figure 1.

Mean reactive hyperemia index (RHI) values “Pre” vs. “Post” intervention. n = 21 exercise (19 M/2F) and n = 13 stretching (11 M/2 F). RHI values were compared via a two-way repeated-measures ANOVA (factor 1: time, factor 2: group) followed by Tukey’s post hoc tests. Time, P = 0.26; Group, P = 0.09; Interaction, P = 0.08. *P = 0.03. F, female; M, male.

Maximal Aerobic Exercise Capacity

Data from a maximal treadmill exercise test were collected from n = 18 in the exercise group and n = 17 in the stretching group. A subset of participants (n = 13) was unable to complete the maximal exercise testing due to orthopedic or other limitations that precluded their ability to perform the exercise treadmill test. Of the participants that completed the test, V̇o_2peak data are missing for n = 2 in the exercise group due to technical issues with the metabolic cart, but blood pressure data were recorded. We observed no improvement in V̇o_2peak after either intervention (Exercise: Pre = 25.0 ± 1.3 mL/kg/min vs. Post = 25.9 ± 1.6 mL/kg/min; Stretching: Pre = 26.2 ± 1.8 mL/kg/min vs. Post = 26.0 ± 1.6 mL/kg/min, P = 0.55, Fig. 2). However, both groups exercised longer during the test after the intervention compared with baseline (Exercise: Pre = 642 ± 42 s vs. Post = 734 ± 53 s, P = 0.008; Stretching: Pre = 486 ± 56 s vs. Post = 554 ± 65 s, P = 0.001).

Figure 2.

Mean V̇o_2peak values “Pre” vs. “Post” intervention. n = 16 exercise (15 M/1 F) and n = 17 stretching (13 M/4 F). V̇o_2peak values were compared via a two-way repeated-measures ANOVA (factor 1: time, factor 2: group) followed by Tukey’s post hoc tests. Time, P = 0.70; Group, P = 0.92; Interaction, P = 0.55. F, female; M, male; V̇o_2peak, peak oxygen uptake; V̇o_2peak, peak oxygen uptake.

Body Composition, Hemodynamics, and Laboratory Data

There was no change in lean mass, fat mass, or body composition after training for either group. We also observed no change in resting HR or blood pressure after training in either group (Table 2). Of the 35 participants who completed the maximal exercise test, blood pressure data are missing for n = 2 stretching due to our inability to clearly auscultate the blood pressure measurements throughout exercise during one of the two tests. Peak systolic blood pressure was reduced after exercise training (Pre = 186 ± 5 mmHg, Post = 174 ± 4 mmHg, P = 0.003) with no change after stretching (Pre = 190 ± 6 mmHg, Post = 190 ± 4 mmHg, P = 0.12, Fig. 3A). Peak diastolic blood pressure decreased slightly after training for both groups (approximately −3 mmHg) with no differences between groups (Fig. 3B, P = 0.80). We observed no change in rate or magnitude of increase in HR after the intervention in either group (P = 0.99). Although the rate of increase in systolic blood pressure tended to decrease in both groups after training (−2 mmHg/stage, P ≤ 0.0.05), there were no differences in the magnitude of this reduction between groups (P = 0.97, Fig. 4A). We observed a small, but statistically significant, reduction in the rate of increase in diastolic blood pressure following exercise training in both groups (−1 mmHg/stage, P = 0.015), but there were no differences in the magnitude of this reduction between groups (P = 0.48, Fig. 4B). There was no relationship between the improvement in RHI and the reduction in peak systolic blood pressure reactivity during maximal exercise after exercise training (P = 0.99). There were no changes in laboratory measures including serum creatinine, estimated glomerular filtration rate, potassium, and bicarbonate after intervention in either group.

Table 2.

Body composition, hemodynamic, and laboratory parameters following training

Characteristic	Exercise		Stretching
Time:	Pre	Post	Pre	Post	P
Body composition, %	35.3 ± 2.2	34.6 ± 2.0	31.8 ± 2.1	31.9 ± 2.1	0.38
Lean mass, kg	64.9 ± 1.8	65.5 ± 1.8	65.4 ± 2.5	65.4 ± 2.4	0.75
Fat mass, kg	35.6 ± 2.9	36.0 ± 2.8	31.2 ± 2.6	31.4 ± 2.6	0.42
Resting heart rate, beats/min	70 ± 2	69 ± 2	75 ± 3	76 ± 3	0.78
Systolic blood pressure, mmHg	129 ± 2	126 ± 2	129 ± 4	126 ± 2	0.65
Diastolic blood pressure, mmHg	71 ± 2	68 ± 2	76 ± 2	75 ± 2	0.58
Serum creatinine, mg/dL	1.9 ± 0.1	2.3 ± 0.5	1.8 ± 0.1	1.5 ± 0.1	0.20
eGFR, cc/min/1.73 m2	44 ± 2	43 ± 2	47 ± 3	50 ± 2	0.55
Serum potassium, mmol/L	4.1 ± 0.1	4.3 ± 0.1	4.1 ± 0.1	4.1 ± 0.1	0.25
Serum CO2, mmol/L	25 ± 1	24 ± 1	25 ± 1	25 ± 1	0.37

eGFR, estimated glomerular filtration rate.

Figure 3.

Peak systolic (A) and diastolic blood pressure (B) responses during maximal exercise “Pre” vs. “Post” intervention. n = 18 exercise (15 M/3 F) and n = 15 stretching (12 M/3 F). Peak systolic and diastolic blood pressure values were compared via a linear mixed model (factor 1: time, factor 2: group) with change in RHI, BMI, and eGFR considered as covariates. Peak systolic blood pressure: Time, P = 0.12; Group, P = 0.93; Interaction, P = 0.006. Peak diastolic blood pressure: Time, P = 0.04; Group, P = 0.92; Interaction, P = 0.80. *P = 0.003. BMI, body mass index; eGFR, estimated glomerular filtration rate; F, female; M, male; RHI, reactive hyperemia index.

Figure 4.

Systolic (A) and diastolic blood pressure (B) responses during maximal exercise (mmHg/stage) “Pre” vs. “Post” intervention. n = 18 exercise (15 M/3 F) and n = 15 stretching (12 M/3 F). A linear mixed model was used to compare the increase in blood pressure over time and between groups. Regression lines for each group were fitted based on individual participant responses including all treadmill stages completed for each participant. The rate of increase in systolic blood pressure (A) was decreased following exercise (P = 0.02) and tended to decrease following stretching (P = 0.05) with no differences between groups (P = 0.97). The rate of increase in diastolic blood pressure (B) was reduced following exercise (P = 0.02) with no change following stretching (P = 0.22) and no differences between groups (P = 0.48). F, female; M, male.

DISCUSSION

In this investigation, we compared the effects of a 12-wk, supervised, aerobic exercise intervention versus stretching and balance (nonaerobic control intervention) on endothelial function, peak oxygen uptake, and blood pressure reactivity during maximal exercise in CKD. In support of our hypotheses, 12 wk of aerobic exercise training improved endothelial function in older, sedentary individuals with CKD stages III and IV. Although we did observe a reduction in peak blood pressure responses during exercise after aerobic exercise training, the rate of increase in blood pressure was attenuated similarly in both groups.

Heightened blood pressure reactivity during exercise is independently associated with future adverse cardiovascular events (6, 7). Patients with CKD exhibit exaggerated blood pressure reactivity during both submaximal (4) and maximal exercise (5), and this is driven by multiple mechanisms including increased sensitivity of the muscle mechanoreflex (4), metabolic acidosis (37), and endothelial dysfunction (5). In addition to the increased risk of future cardiovascular events that is associated with this response, short-term consequences also include safety concerns during physical activity and a reduction in exercise efficiency. All of these are undesirable and may limit the ability of patients with CKD to engage in exercise, further contributing to exercise intolerance.

Our primary finding that 12 wk of aerobic exercise training enhanced endothelial function in CKD stages III and IV is in contrast to a previous study by Van Craenenbroeck et al. (26), which reported no improvement in endothelial function after 3 mo of cycling training in CKD. These disparate results may be due to differences in the nature of the intervention. The previous study utilized a home-based intervention that consisted of short bouts (10 min) of high-intensity cycling exercise performed four times daily (26). Similarly, endothelial function was assessed via brachial artery flow-mediated dilation (FMD) in that investigation whereas we used peripheral arterial tonometry to assess endothelial function. Although both of these methods are well established and routinely used to measure endothelial function in humans, they likely reflect different aspects of vascular physiology (i.e., macro- vs. microvascular) (31), which may have conributed to the divergent results between studies. In that regard, our findings are consistent with a recent report by Kirkman et al., which also reports improvements in microcirculatory function after 12 wk of structured aerobic exercise training in CKD, likely due to an improvement in redox balance (27). Although we did not explore the mechanisms mediating the improvement in endothelial function observed in the present investigation, reductions in oxidative stress may have played a role and warrant further study in future investigations.

In contrast to our hypothesis, 12 wk of aerobic exercise training did not improve V̇o_2peak and resulted in only a slight attenuation in the rate of increase in systolic blood pressure during maximal exercise (−2 mmHg), which was equivalent to what we observed in our stretching control group. However, we did observe a reduction in peak systolic blood pressure during exercise following the aerobic exercise intervention with no change following stretching. Previous work has suggested that both the magnitude and rate of increase in systolic blood pressure during maximal exercise are important predictors of future cardiovascular risk (7). Thus, the reduction in peak blood pressure reactivity after training could correspond to a beneficial effect on future cardiovascular risk in CKD; however, the lack of an improvement in the rate of increase in systolic blood pressure suggests that perhaps a higher dose of exercise (e.g., higher frequency of exercise, longer duration than 12 wk) may be needed to fully realize this benefit. In addition, future longitudinal studies in CKD are needed to confirm that the reduction in peak blood pressure during exercise does indeed correspond to a reduction in future cardiovascular risk in this population.

One explanation as to why both interventions resulted in an attenuated rate of increase in blood pressure following training could be related to an order effect. All patients in both groups were previously sedentary, and for many of them, this was their first time on a treadmill. As such, the attenuation in the rate of increase in blood pressure during the second test may simply have been related to a conditioning effect of the testing procedure, rather than a physiological improvement in neurocirculatory control during exercise. Similarly, the reduction in blood pressure reactivity after stretching may have been amplified by the very sedentary nature of our participants. The group-based intervention necessitated that they leave their home and walk from a parking lot into a large hospital setting three times per week. This increased activity, in addition to the body weight exercises, light weights, and elastic band exercises during the control intervention itself, could have been sufficient to provide beneficial physiologic effects, given their very low fitness at baseline. This notion is supported by the observation that both groups exercised longer during the treadmill test following the intervention compared with baseline. Although we observed no discernable improvement in peak oxygen uptake, some small improvements in mobility and movement economy may have occurred following stretching. In that regard, it is possible that the stretching intervention itself may have induced some improvement in blood pressure reactivity. One recent investigation reported that an 8-wk intervention consisting of stretching 5 days a week improved resting blood pressure in an older population (38). Although we intended for our stretching intervention to serve as a control to account for the social interaction of the group-based exercise intervention, future work should explore the potential cardiovascular benefits of stretching and balance in CKD.

Methodological Considerations

There are a number of methodological considerations that should be mentioned as they relate to the interpretation of our findings. First, our participants were mostly male (∼80%) so we are unable to compare differences across sexes. In healthy aging, sex differences are known to be present in endothelial adaptations following exercise training (39). Thus, future work should examine if these sex differences are also present in CKD. In addition, RHI data are missing on a subset of participants (n = 5 exercise, n = 9 stretching) due to either technical issues with the device, or in some cases, participants being unable to tolerate the 5 min of suprasystolic arm cuff inflation that is required for this procedure. However, RHI improved in the majority of participants in the cycling group (∼60%) whereas the majority of the participants in the stretching group (∼60%) exhibited a slight reduction in RHI following the intervention (Fig. 1). Thus, although our sample size is limited, these findings are strengthened when considering the proportion of participants who responded to the intervention in each group. Similarly, vascular function was assessed with the Endopat device rather than FMD, which contrasts with our previous study that demonstrated an association between reduced FMD and exaggerated blood pressure reactivity during exercise in CKD (5). Although FMD and RHI do correlate (40), they may respond differently following training. In addition, maximal heart rate was calculated as 220-age, rather than through maximal exercise testing. Therefore, patients on β-blocker may have been working at a higher percentage of their actual achievable maximum heart rate during training sessions. Furthermore, although we chose to assess V̇o_2peak using a different modality of training than what was used during exercise (i.e., treadmill vs. bike) to limit the potential for bias resulting from increased familiarity with the testing procedure in the cycling group, we acknowledge that this may have also contributed to the lack of change in V̇o_2peak after the intervention. However, the observation that endothelial function was improved following exercise training despite no change in V̇o_2peak raises important questions regarding the mechanisms underlying this adaptation, which appear to be independent of improved peak oxygen uptake. We did not examine specific mechanisms underlying improvement in RHI in this study, but previous work has suggested that enhancements in microcirculatory function after aerobic exercise training in CKD may be mediated by an improvement in redox balance (27). Thus, it is plausible that oxidative stress may have been attenuated after the exercise intervention. In addition, we only assessed endothelial function in the upper extremities whereas the training intervention consisted of lower body exercise. Although speculative, it is possible that exercise training may have induced a systemic effect (e.g., increased nitric oxide bioavailability) that subsequently led to improved RHI. Other interventions such as remote ischemic preconditioning (41) or passive limb heating (42) have also shown improvements in vascular function in a different extremity from the one that was used in the intervention (i.e., contralateral limb, upper versus lower body). Other potential mechanisms may include a reduction in sympathetic activity or inflammation, and these should all be explored in future studies.

Conclusions

We demonstrated that 12 wk of aerobic exercise training improves endothelial function and attenuates peak blood pressure responsiveness during maximal exercise in CKD stages III and IV. However, these improvements are independent of an improvement in V̇o_2peak. The relationship between endothelial function, exercise training, and blood pressure reactivity during exercise in CKD warrants further exploration, particularly as it relates to future risk of cardiovascular disease.

Perspectives and Significance

Patients with CKD exhibit increased blood pressure reactivity during exercise that is associated with endothelial dysfunction. Twelve weeks of structured, aerobic, exercise training improves endothelial function and attenuates peak blood pressure responses during exercise in CKD stages III and IV. Future work should further interrogate the relationship between endothelial dysfunction and exaggerated blood pressure reactivity during exercise in CKD and longitudinally assess if the attenuation in peak blood pressure during exercise corresponds to a reduced risk of future adverse cardiovascular events in this population.

GRANTS

This work was supported by National Institutes of Health Grants R01HL135183 (to J.P.), R61AT010457, and F32HL147547 to (J.D.S.) as well as the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Clinical Studies Center (Decatur, GA).

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

J.D.S., J.J., J.R.N., and J.P. conceived and designed research; J.D.S., K.M., J.J., D.R.D., D.G.M., J.R.N., and J.P. performed experiments; J.D.S., K.M., J.J., Y.H., J.R.N., and J.P. analyzed data; J.D.S., J.J., Y.H., J.R.N., and J.P. interpreted results of experiments; J.D.S., J.J., Y.H., J.R.N., and J.P. prepared figures; J.D.S., J.J., J.R.N., and J.P. drafted manuscript; J.D.S., K.M., J.J., D.R.D., Y.H., D.G.M., J.R.N., and J.P. edited and revised manuscript; K.M., J.J., D.R.D., Y.H., D.G.M., J.R.N., and J.P. approved final version of manuscript.