Abstract
We aimed to elucidate the role of autonomic dysfunction in the context of complex metabolic and cardiovascular changes in subjects with prehypertension. We identified 556 asymptomatic subjects without hypertension who underwent comprehensive cardiovascular exams. We obtained heart rate recovery (HRR) after peak exercise to quantitatively measure autonomic dysfunction. Of the 556 participants, 279 individuals had prehypertension and the remaining 277 had optimal BP. HRR was significantly lower in the prehypertension group (36.0 ± 14.5 bpm) than in the optimal BP group (39.3 ± 14.7 bpm, P = .009). The prehypertension group more frequently demonstrated features of metabolic disturbances and subclinical target organ damage. Among the various baseline cardiovascular and metabolic factors assessed, resting systolic BP and high‐density lipoprotein cholesterol level were independent determinants of HRR (both P < .05). Autonomic dysfunction coexists with prehypertension and is closely linked to changes in systolic BP and lipid metabolism.
Keywords: autonomic nervous system, exercise test, heart rate, metabolic syndrome, prehypertension
1. INTRODUCTION
Prehypertension is a major public health concern affecting more than 1 out of every 4 adults worldwide.1, 2 A growing body of evidence indicates that prehypertension accompanies metabolic disturbances, leading to target organ damage and increased cardiovascular morbidity and mortality.1, 2, 3, 4 Although it is crucial to identify the cause of prehypertension and intervene early in the disease course, little is known about the pathophysiology of this condition. Autonomic dysfunction has been thought to play a causative role in the development of hypertension.5, 6 It is unclear, however, whether and how much autonomic dysfunction contributes to the precursor state of hypertension. Only limited data are available to support the association between prehypertension and autonomic dysfunction,7 partly due to the paucity of objective tools to measure autonomic dysfunction.
More recently, heart rate recovery (HRR) has been proposed as a marker of autonomic dysfunction that can be easily obtained during a treadmill test. HRR at 1 minute post‐exercise (HRR1), defined as the change in heart rate from peak to 1 minute after exercise, represents parasympathetic reactivation.8 To date, 2 studies have tested HRR in patients with prehypertension, and these studies were subject to limitations in the study design. The first study by Erdogan et al was limited by its small cohort size.9 The second study by Aneni et al had a study population that was predominantly male, included only a small number of individuals in the control group with optimal blood pressure (BP), and did not identify the determinants of autonomic dysfunction in subjects with prehypertension.10 Previous studies have separately investigated the effects of either autonomic dysfunction or metabolic dysfunction on prehypertension, although both conditions coexist and mutually contribute to the pathophysiology of prehypertension.11 In addition, the possible interplay between autonomic function and the cardiovascular system has not been clarified in prehypertensive subjects. To understand the role of autonomic dysfunction in the context of complex metabolic and cardiovascular changes in patients with prehypertension, we evaluated the autonomic, metabolic, and cardiovascular profiles of 277 individuals with prehypertension compared to 279 people with optimal BP.
2. METHODS
2.1. Study participants
This cross‐sectional study was conducted at a tertiary hospital in South Korea during 2009‐2015. Initially, 1230 asymptomatic subjects who underwent a cardiopulmonary exercise test as part of their health surveillance were identified. The medical records of patients were reviewed to collect demographic and clinical data. Among them, we included subjects aged 20‐80 years with complete data regarding both echocardiography and brachial‐ankle pulse wave velocity (baPWV). We excluded subjects with the following characteristics: (1) hypertension (BP ≥ 140/90 mm Hg or use of antihypertensive drugs), (2) diabetes (fasting glucose ≥126 mg/dL or use of anti‐diabetic drugs), (3) missing laboratory test data, (4) other combined diseases that might have affected the results of the exercise test (eg, significant structural heart disease and/or lung disease, anemia with hemoglobin <10 mg/dL), and (5) non‐Korean descent. Finally, the study population consisted of 556 subjects. The participants were categorized into 2 groups based on their BP levels according to the JNC 7 report: (1) the optimal BP group (systolic BP < 120 mm Hg and diastolic BP < 80 mm Hg, n = 277) and (2) the prehypertension group (systolic BP 120‐139 mm Hg and/or diastolic BP 80‐90 mm Hg, n = 279).12 The institutional ethics committee approved the study protocol (KC17RESE0373).
2.2. Measurements
BP was measured in a sitting position using an automated BP device (TM‐2665P, A&D Co. Ltd., Tokyo, Japan) with an appropriate‐sized cuff. Participants were required to rest at least 10 minutes before BP measurement. BP was measured for all the participants at least twice within an interval of 2 minutes.12 If a difference in BP of more than 5 mm Hg between the 2 measurements was noted, BP was measured a third time after 2 minutes and the average value was taken. The subject's height (cm) and weight (kg) were digitally measured while wearing lightweight clothing and their body mass index (BMI, kg/m2) was calculated. Blood samples were collected after a 12‐hour overnight fast. HbA1c was measured using a G8 HbA1c analyzer (Tosoh Corporation, Tokyo, Japan). Insulin resistance was assessed with homeostatic model assessment‐estimated insulin resistance (HOMA‐IR) using the online HOMA2 calculator, as previously described.3 Lipid profiles were enzymatically measured using the Hitachi 7600‐200. Echocardiographic data were obtained using standard ultrasound systems (Vivid 7, GE Healthcare, Milwaukee, WI, USA) according to the American Society of Echocardiography guidelines.13
A Colin waveform analyzer (VP1000, Colin Co. Ltd., Komaki, Japan) was used to measure the bilateral baPWV in all subjects. The subjects were examined in the supine position. Monitoring cuffs were placed around both arms at the brachialis muscles and both ankles and the pressure waveforms of the brachial and posterior tibial arteries were recorded. An electrocardiogram as well as BP and heart rate (HR) were simultaneously recorded. The PWV was calculated by measuring the time required for the pulse wave to travel between the brachial and posterior tibial arteries. The distance between the brachialis and posterior tibial arteries was estimated based on the height of the subject. The mean values of the right and left baPWV were used for the final analysis.
Participants underwent a symptom‐limited cardiopulmonary exercise test using a modified Bruce treadmill protocol. The first 2 stages of the modified Bruce protocol included a warm‐up period at 1.7 mph and 0% grade for 3 minutes followed by a period of 1.7 mph and 5% grade for 3 minutes. The third stage was the same as the first stage of the standard Bruce protocol, during which both speed and grade were increased every 3 minutes.14 Peak VO2 (mL/kg/min), which is representative of exercise capacity, was defined as the mean of the highest values over the last 10 seconds of exercise and was recorded during the test (Schiller, Baar, Switzerland). After maximal exercise, the participants underwent a passive recovery session in the supine position for 6 minutes. During the exercise and recovery phases, BP along with HR was monitored every minute. HRR1 was determined as follows: peak HR‐HR after 1 minute of recovery.
2.3. Data analysis
To identify the differences between the optimal BP and prehypertension groups, Student t test and the chi‐square test were performed. The data were presented as the mean ± standard deviation for continuous variables and as a number with the percentage for categorical variables. We further used analysis of covariance (ANCOVA) to estimate the HRR1 level, controlling for baseline clinical confounders (age and BMI), which corresponded to significant differences between the 2 groups. Correlations between HRR1 and possible cofactors were analyzed using Pearson's correlation test. Additionally, multivariate linear regression analysis was performed to identify the independent determinants of HRR1. Variables with a P‐value <.05 in the univariate analysis and the clinically relevant variable (age) were included in the multivariate analysis. All analyses were 2‐tailed and statistical significance was set at a P‐value of <.05. Statistical analyses were conducted using SPSS version 21.0 software (SPSS Inc., Chicago, IL, USA).
3. RESULTS
3.1. Baseline characteristics: cardiometabolic and autonomic function profiles
Table 1 shows the baseline characteristics of all participants. The prehypertension group was older in age, had higher BMI, HbA1c, and HOMA‐IR levels and lower high‐density lipoprotein (HDL) cholesterol than the optimal BP group. There was no significant difference in triglyceride and low‐density lipoprotein cholesterol levels between the 2 groups. The prehypertension group exhibited increased arterial stiffness (expressed as baPWV), decreased left ventricular (LV) systolic function, increased LV mass index, and increased E/e’ ratio compared to the individuals in the optimal BP group.
Table 1.
Baseline characteristics of the participants with prehypertension (Pre‐HT) and optimal blood pressure (Opt BP)
| Variable | All (n = 556) | Opt BP (n = 277) | Pre‐HT (n = 279) | P |
|---|---|---|---|---|
| Clinical variables | ||||
| Age, y | 52.9 ± 8.6 | 51.6 ± 8.3 | 54.1 ± 8.6 | .001 |
| Male, n (%) | 293 (52.7) | 135 (48.7) | 158 (56.6) | .074 |
| Body mass index, kg/m2 | 23.9 ± 3.1 | 23.2 ± 2.8 | 24.6 ± 3.2 | <.001 |
| Systolic BP, mm Hg | 119.1 ± 10.4 | 110.5 ± 6.5 | 127.7 ± 5.0 | <.001 |
| Diastolic BP, mm Hg | 71.4 ± 8.4 | 66.0 ± 6.5 | 76.9 ± 6.4 | <.001 |
| HR, bpm | 78.7 ± 11.6 | 79.0 ± 11.5 | 78.4 ± 11.6 | .548 |
| Laboratory findings | ||||
| HbA1c, % | 5.6 ± 0.6 | 5.5 ± 0.5 | 5.7 ± 0.7 | .009 |
| Fasting glucose, mg/dL | 98.7 ± 16.7 | 96.4 ± 15.6 | 101.0 ± 17.3 | .001 |
| HOMA‐IR | 1.09 ± 0.98 | 0.92 ± 0.85 | 1.26 ± 1.06 | <.001 |
| Creatinine, mg/dL | 0.87 ± 0.20 | 0.85 ± 0.18 | 0.89 ± 0.22 | .015 |
| Total cholesterol, mg/dL | 200.1 ± 37.4 | 200.1 ± 37.0 | 200.0 ± 37.9 | .973 |
| Triglyceride, mg/dL | 112.0 ± 71.8 | 107.6 ± 73.0 | 116.4 ± 70.4 | .149 |
| HDL‐cholesterol, mg/dL | 50.4 ± 13.1 | 52.4 ± 13.6 | 48.5 ± 12.2 | <.001 |
| LDL‐cholesterol, mg/dL | 124.4 ± 32.9 | 123.1 ± 31.7 | 125.3 ± 34.1 | .445 |
| Brachial‐ankle PWV, m/s | 13.85 ± 1.80 | 13.16 ± 1.43 | 14.54 ± 1.87 | <.001 |
| Echocardiographic findings | ||||
| LV ejection fraction, % | 67.1 ± 5.1 | 67.6 ± 5.0 | 66.5 ± 5.1 | .011 |
| LV mass index, g/m2 | 79.1 ± 15.2 | 75.7 ± 13.6 | 82.6 ± 15.9 | <.001 |
| E/e’ ratio | 8.5 ± 2.2 | 8.1 ± 2.0 | 8.8 ± 2.4 | <.001 |
| Cardiopulmonary exercise data | ||||
| Exercise time, s | 602 ± 143 | 612 ± 141 | 592 ± 144 | .107 |
| Peak systolic BP, mm Hg | 156.8 ± 24.4 | 148.2 ± 22.8 | 165.5 ± 22.9 | <.001 |
| Peak diastolic BP, mm Hg | 73.9 ± 12.0 | 70.5 ± 10.6 | 77.3 ± 12.3 | <.001 |
| Peak heart rate, bpm | 143.0 ± 11.1 | 144.0 ± 10.9 | 142.0 ± 11.2 | .042 |
| Peak VO2, mL/kg/min | 25.2 ± 7.3 | 25.2 ± 7.2 | 25.2 ± 7.4 | .941 |
| Recovery 1 min HR, bpm | 105.3 ± 14.4 | 104.7 ± 14.1 | 106.0 ± 14.6 | .271 |
| HRR1, bpm | 37.7 ± 14.6 | 39.3 ± 14.7 | 36.0 ± 14.5 | .009 |
Data are presented as a number (percentage) or mean ± standard deviation. Student's t‐test and the chi‐square test were used to compare the characteristics of the two BP groups. BP, blood pressure; HR, heart rate; HOMA‐IR, homeostatic model assessment‐estimated insulin resistance; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein; LV, left ventricular; PWV, pulse wave velocity; and HRR1, heart rate recovery at 1 min post‐exercise.
Although there was no significant difference in resting HR between the groups, HRR1 was significantly decreased in the prehypertension group (36.0 ± 14.5 vs 39.3 ± 14.7 bpm, P = .009, Figure 1). After adjustments for age and BMI, HRR1 remained significantly decreased in the prehypertension group (P = .048, Table S1). There were no significant differences in exercise duration and exercise capacity (peak VO2 level) between the 2 groups.
Figure 1.
Heart rate recovery at 1 min post‐exercise (HRR 1) was significantly delayed in the prehypertension group. This difference remained statistically significant after adjusting for age and body mass index (adjusted P = .048). Data are presented as the mean ± standard deviation
3.2. Determinants of autonomic dysfunction (HRR)
Correlations between HRR1 and possible cofactors are summarized in Table 2 and Figure 2. HRR1 was inversely correlated with resting systolic BP, resting HR, HOMA‐IR, and baPWV and was positively correlated with HDL‐cholesterol. However, neither echocardiographic parameters (LV ejection fraction, LV mass index, and the E/e’ ratio) nor exercise parameters (exercise duration and exercise capacity) were significantly correlated with HRR1.
Table 2.
Correlations between HRR1 and potential factors (n = 556)
| Variable | r | P |
|---|---|---|
| Age | −0.076 | .075 |
| Resting systolic blood pressure | −0.142 | .001 |
| Resting heart rate | −0.259 | <.001 |
| Body mass index | −0.090 | .035 |
| HOMA‐IR | −0.105 | .013 |
| HDL‐cholesterol | 0.133 | .002 |
| LDL‐cholesterol | 0.049 | .247 |
| Brachial‐ankle pulse wave velocity | −0.137 | .001 |
| LV ejection fraction | −0.046 | .281 |
| LV mass index | 0.020 | .637 |
| E/e’ ratio | 0.023 | .584 |
| Exercise time | 0.023 | .595 |
| Peak VO2 | 0.020 | .633 |
HRR1, heart rate recovery at 1 min post‐exercise; HOMA‐IR, homeostatic model assessment‐estimated insulin resistance; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein; and LV, left ventricular.
Figure 2.
The associations between heart rate recovery (HRR) and other cofactors are shown. HRR was inversely correlated with resting systolic blood pressure (A) and positively correlated with high‐density lipoprotein (HDL) cholesterol (B) in all participants (open circle denotes the optimal blood pressure group, and the closed square denotes the prehypertension group)
Multivariate linear regression analysis showed that age (β = −.163, P = .021), resting systolic BP (β = −.150, P = .010), resting HR (β = −.355, P < .001), and HDL‐cholesterol level (β = .151, P = .001) remained independent determinants of HRR1 after adjusting for BMI, baPWV, and HOMA‐IR (Table 3).
Table 3.
Determinants of HRR1 in all subjects (n = 556)
| Variable | Unadjusted | Adjusted | ||
|---|---|---|---|---|
| β | P | β | P | |
| Age | −0.129 | .075 | −0.163 | .021 |
| Resting systolic BP | −0.200 | .001 | −0.150 | .010 |
| Resting heart rate | −0.327 | <.001 | −0.355 | <.001 |
| Body mass index | −0.428 | .035 | ||
| baPWV | −0.011 | .001 | ||
| HOMA‐IR | −1.587 | .013 | ||
| HDL‐cholesterol | 0.149 | .002 | 0.151 | .001 |
HRR1, heart rate recovery at 1 min post‐exercise; BP, blood pressure; baPWV, brachial‐ankle pulse wave velocity; HOMA‐IR, homeostatic model assessment‐estimated insulin resistance; and HDL, high‐density lipoprotein.
4. DISCUSSION
The present study demonstrated the role of autonomic dysfunction in conjunction with metabolic dysfunction in the pathophysiology of prehypertension. The major findings are as follows: (1) individuals with prehypertension have autonomic dysfunction, metabolic disturbance, and target organ damage (such as increased arterial stiffness and altered LV structure and function); (2) autonomic dysfunction is related to BP level, adverse metabolic profile (increased insulin resistance and abnormal lipid metabolism), and increased arterial stiffness; and (3) the most important key factors of autonomic dysfunction are BP level and abnormal lipid profile. To the best of our knowledge, this is the first study to explore the role of autonomic dysfunction in the context of complex metabolic and cardiovascular changes in subjects with prehypertension.
4.1. Prehypertension as a pathologic condition: comorbid state with autonomic and metabolic dysfunction and subclinical target organ damage
Our study is in line with previous studies that have shown that prehypertension exhibits features of metabolic disturbance, such as obesity, insulin resistance, impaired fasting glucose, and abnormal lipid profile.3, 15 Our study also confirmed that prehypertension is associated with autonomic dysfunction, which was reflected by delayed HRR. A previous study showed that elevated sympathetic tone was associated with high normal BP states, and intriguingly, it was also coupled with metabolic alterations similar to those observed in our study.7 Other studies have also demonstrated that decreased parasympathetic tone, along with increased sympathetic activity, underlies the pathogenesis of prehypertension.9, 10, 16, 17, 18 Further, our observation reinforced the notion that prehypertension is associated with subclinical target organ damage, in aspects of “vascular” and “cardiac” structure and function. Collectively, our findings indicate that prehypertension is not a simple precursor state of hypertension with high normal BP. Rather, it is a pathologic condition with a spectrum of changes in autonomic and metabolic domains and target organ damage, which warrants increased clinical attention.
4.2. Complex interplay among BP level, autonomic function, and metabolic function
To effectively manage prehypertension, it is crucial to identify the relationship between the clustered risk factors. Our data demonstrated that prehypertension group displays autonomic dysfunction. In addition, 1 of the independent determinants of autonomic dysfunction in the present study was BP level. Thus, these findings indicate that the relationship between elevated BP and autonomic dysfunction might be a mutually affected relationship rather than a simple 1‐way causal relationship.9, 19 Further, our results demonstrated that elevated BP and abnormal lipid metabolism are key determinants of autonomic dysfunction, suggesting a complex relationship among BP status, autonomic function, and metabolic function. Previous reports have shown that autonomic nervous system function plays a role in both BP control and metabolism.7, 11, 20 Obesity (especially central obesity) contributes to sympathetic activation independent of BP.21, 22 Furthermore, obesity‐related sympathetic activation contributes to BP elevation.23 In addition, metabolic syndrome (characterized by glucose intolerance, dyslipidemia, central obesity, and elevated BP) can induce sympathetic activation, which may be further augmented by the presence of hypertension.24 In our study, individuals in the prehypertension group displayed greater insulin resistance, obesity, and abnormal lipid metabolism, all of which are metabolic factors associated with autonomic dysfunction, which is in line with previous studies. However, contrary to previous studies,7 insulin resistance was not a significant determinant of autonomic dysfunction after adjusting for other cofactors. This is probably due to different population characteristics and ethnicities between the previous study and the current study. Our study population represented healthy subjects who were not obese (BMI 23.9 ± 3.1 kg/m2), which presumably led to a reduced association with insulin resistance and an increased association with HDL‐cholesterol. In addition, we further adjusted for the effect of obesity (BMI), which is closely related to insulin resistance.25 Indeed, the differences in HRR1 between the prehypertension and optimal BP groups were considerably affected by BMI.
Several other findings need to be discussed. First, age was one of the independent determinants of autonomic dysfunction. It is well known that body fat increases with age,26 which might contribute to autonomic dysfunction. Second, increased arterial stiffness was associated with autonomic dysfunction, although its statistical significance was lost after adjusting for other confounding factors. This result implies that the association between autonomic dysfunction and vascular remodeling might be mediated by age, rapid baseline HR, and other metabolic factors. Indeed, a correlation between arterial stiffness and autonomic function (particularly abnormal parasympathetic tone) has been tested, especially in diabetes, which is closely associated with metabolic disturbance.27, 28 Impaired baroreceptor function induced by arterial wall stiffening is suggested as a possible mechanism for this relationship.27 Although the precise mechanism that mediates elevated BP, autonomic dysfunction, and increased arterial stiffness is unclear, an unbalanced sympathetic‐parasympathetic tone may presumably elevate BP by increasing vascular tone29, 30 and further increase BP levels by inducing vascular remodeling,27, 31 thus resulting in a vicious cycle. Third, unlike the previous study,9 an association between autonomic dysfunction and exercise capacity was not evident. In the present study, we directly measured exercise capacity via peak VO2 levels. Although exercise capacity is affected by basal autonomic tone,3 it seems to be unrelated to post‐exercise parasympathetic reactivation. However, this explanation is currently speculative and more studies are warranted to precisely determine the relationship between exercise capacity and autonomic function during resting, exercise, and post‐exercise periods.
4.3. Strengths
First, to avoid any potential confounding effects, we excluded patients with hypertension, diabetes, and ischemic/structural heart disease. Second, our study enrolled relatively large cohorts and included multiple parameters (clinical and laboratory data, vascular stiffness, and echocardiographic and exercise data) to explore the role of autonomic dysfunction in the context of complex metabolic and cardiovascular changes in subjects with prehypertension. Third, our results have clinical significance. It is noteworthy that 2 of the independent determinants of autonomic dysfunction—elevated BP and abnormal lipid profile—can be easily identified via physical exams and laboratory tests and, further, can be therapeutically modified. Future research can prospectively explore the clinical significance of such interventions using a reduction of HRR as a short‐term readout of efficacy and a reduction of cardiovascular morbidity as a long‐term outcome.
4.4. Limitations
Several limitations of our study should be acknowledged. First, this was a cross‐sectional study and therefore cannot clearly define causal relationships between prehypertension and autonomic‐metabolic dysfunction. Second, our data did not include any information regarding a family history of hypertension and the renin‐angiotensin‐aldosterone system, both of which might affect the sympathetic tone and metabolic state.16, 24 Third, HRR (an index used in our study) mainly reflects parasympathetic tone (not sympathetic activity) and is a rather indirect method for assessing autonomic function compared to other techniques (heart rate variability test, norepinephrine spillover, and muscle sympathetic nerve activity). However, it enabled the evaluation of autonomic dysfunction in a large population without increasing cost. Fourth, we did not perform out‐of‐office BP measurements (ambulatory BP monitoring and/or home BP monitoring), and thus, we could not exclude the effects of white coat hypertension and masked hypertension. Fifth, the numerical difference in HRR1 between optimal BP and prehypertension groups was minimal (about 3 bpm), despite the statistical significance. We believe additional studies regarding HRR for subjects without hypertension are needed to establish meaningful reference data for clinical and/or research purposes. Sixth, the coefficient of the determinant of the current regression analysis was low (r 2 = .113), which means that this regression analysis is inadequate to thoroughly explain the determinant of HRR, despite the fact that we examined the associated factors of HRR using multiple parameters. Seventh, the mean diastolic BP value of prehypertension group (76.9 mm Hg) was slightly lower than the other study group, which might have affected the results. However, we carefully rechecked if the participants were properly allocated to each group. Last, our study could not be directly applied to other ethnicities or patients with overt cardiovascular disease. Considering these limitations, our conclusions should be considered only as possible hypotheses generated based on the data collected herein and additional longitudinal and/or interventional studies are needed.
5. CONCLUSIONS
In summary, prehypertension is associated with autonomic dysfunction, metabolic disarray, and subclinical target organ damage, which warrants further clinical attention. In addition, autonomic function is closely linked to BP levels and metabolic alterations, which intricately interact with one another and, thus, promote or amplify each other. Considering the prevalence of prehypertension and its adverse effect on the cardiovascular system, active management of these clustered risk factors (elevated BP, autonomic dysfunction, arterial stiffness, obesity, and insulin resistance), all of which are closely interrelated, is essential in prehypertensive individuals. This study calls for a comprehensive approach when managing individuals with prehypertension.
CONFLICT OF INTEREST
None.
Supporting information
ACKNOWLEDGMENTS
We would like to thank Jungeun Baek (registered diagnostic cardiac sonographer) for her support and cooperation. We also wish to thank Dr. Inhye E Ahn for her comments on the manuscript.
Jung M‐H, Ihm S‐H, Lee D‐H, et al. Prehypertension is a comorbid state with autonomic and metabolic dysfunction. J Clin Hypertens. 2018;20:273–279. 10.1111/jch.13180
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