Although cardiovascular (CV) risks have been reported in prehypertension, their link to sympathovagal imbalance (SVI) has not been investigated. In the present study, we have assessed the factors contributing to SVI and the prediction of CV risk by SVI in prehypertensives. Body mass index, CV parameters such as heart rate, systolic blood pressure (BP), diastolic BP, mean arterial pressure, rate-pressure product (RPP), stroke volume, left ventricular ejection time, cardiac output, total peripheral resistance, baroreflex sensitivity recorded by continuous blood pressure variability monitoring using Finapres, autonomic function tests recorded by spectral analysis of heart rate variability (HRV), and heart rate and BP responses to standing, deep breathing, and isometric handgrip, and biochemical parameters such as homeostatic model assessment of insulin resistance, lipid risk factors, inflammatory markers, thyroid profile, and renin and oxidative stress parameters were analyzed in young normotensives (n = 118) and prehypertensives (n = 58). Contribution of CV risks to low-frequency/high-frequency (LF/HF) ratio of HRV, the marker of SVI, was determined by multiple regression analysis, and prediction of SVI to RPP, a known CV risk, was assessed by logisitic regression adjusted for body mass index. BP variability, HRV, and autonomic function test parameters were significantly altered in prehypertensives and these parameters were correlated with LF/HF. Insulin resistance, dyslipidemia, inflammation, and oxidative stress contributed to SVI in prehypertensives. LF/HF and baroreflex sensitivity had significant prediction of RPP in prehypertensives. In conclusion, SVI in young prehypertensives is due to both increased sympathetic and decreased vagal tone. CV risks are linked to SVI and SVI predicts cardiac risk in prehypertensives.
Recently, prehypertension has been reported to be associated with adverse cardiovascular (CV) events. Although the exact mechanisms involved in the causation of prehypertension have not yet been clearly explained, recent reports from our laboratory have demonstrated the association of sympathovagal imbalance (SVI) in the form of sympathetic overactivity and vagal withdrawal with prehypertension status in prehypertension. We have reported that decreased vagal modulation of cardiac functions and decreased heart rate variability (HRV) are major CV risks in prehypertensives. Family history, male gender, salt intake, obesity, diabetes mellitus, psychosocial stress, and dyslipidemia have been reported as the risk factors for prehypertension and hypertension. Low-grade inflammation, insulin resistance, hyperlipidemia, and oxidative stress have been reported in prehypertension, and all these factors are known CV risks. Chronic SVI due to any cause has been reported to be associated with CV morbidity and mortality. However, to the best of our knowledge, no study has been conducted till date to assess the role of SVI in prediction of CV risks in prehypertension. As prehypertension is reported to be quite prevalent in younger age group, in the present study, we have assessed CV and autonomic functions by HRV analysis, baroreflex sensitivity (BRS) assessed by blood pressure variability (BPV) monitoring, and conventional autonomic function tests (AFT) and analyzed the link of CV risks such as inflammation, insulin resistance, dyslipidemia, and oxidative stress to SVI in young prehypertensives.
Methods
After obtaining the approval of Research Advisory Council and Institutional Ethics Committee of Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India, 176 student volunteers were recruited from medical and paramedical streams of JIPMER and students of central school of JIPMER campus, Puducherry. All the subjects were clinically examined to rule out the presence of any acute or chronic illness. Informed written consent was obtained from all of them before the recordings.
After 20 minutes rest in sitting posture in AFT laboratory, blood pressure (BP) was recorded using automatic BP monitor (Omron Healthcare, Kyoto, Japan). Systolic BP (SBP) and diastolic BP (DBP) were noted from the display screen of the equipment. For each subject, BP was recorded in each arm and on 2 occasions with an interval of 1 day between the recordings. For both SBP and DBP, the mean of the 4 recordings was considered. The subjects were classified into 2 groups based on their level of SBP and DBP as per JNC-7 classification.
- 1
Normotensives (n = 118, men 52, women 66): healthy subjects having SBP of 100 to 119 mm Hg and DBP of 60 to 79 mm Hg.
- 2
Prehypertensives (n = 58; men 31, women 27): healthy subjects having SBP of 120 to 139 mm Hg and DBP of 80 to 89 mm Hg.
Subjects with a history of smoking and/or alcoholism, acute or chronic ailments, and known cases of diabetes, hypertension, cardiac diseases, kidney disease, or any endocrinal disorder were excluded from the present study. As the level of physical fitness is a major determinant of vagal tone and HRV, subjects performing regular athletic activities were excluded from the study.
Subjects were asked to report to AFT laboratory of physiology department at about 8 a.m. after overnight fast. The temperature of the laboratory was maintained at 25°C for all recordings. Their age, height, body weight, and body mass index (BMI) were recorded.
After 15 minutes of supine rest, electrocardiogram (ECG) was recorded for short-term HRV analysis following the procedures recommended by Task Force, using BIOPAC MP-100 data acquisition system (BIOPAC Inc., Goleta, California). For the purpose, electrocardiographic electrodes were connected and lead II ECG was acquired at a rate of 1,000 samples/s during supine rest using BIOPAC MP-100, continuously for 10 minutes. The data were transferred from BIOPAC to a Windows-based PC with AcqKnowledge software, version 3.8.2 (BIOPAC Inc., Goleta, California). Ectopics and artifacts were removed from the recorded ECG. The RR tachogram was extracted from the edited ECG using the R-wave detector in the AcqKnowledge software. HRV analysis was done using the HRV analysis software, version 1.1 (Bio-signal Analysis group, Kuopio, Finland). Frequency-domain indexes of HRV such as total power (TP), normalized low-frequency power (LFnu), normalized high-frequency power (HFnu), ratio of low-frequency/high-frequency power (LF/HF ratio) and time-domain indexes such as the square root of the mean of the sum of the squares of the differences between adjacent NN intervals (RMSSD), SD of normal-to-normal interval, number of interval differences of successive NN intervals >50 ms (NN50), and the proportion derived by dividing NN50 by the total number of NN intervals (pNN50) were recorded.
The CV parameters were measured by continuous BP variability (BPV) method using Finapres (Finometer, version 1.22a; Finapres Medical Systems BV, Amsterdam, The Netherlands), a noninvasive, continuous, hemodynamic CV monitor based on the principle of measurement of finger arterial pressure with the volume clamp technique of Penaz and the Physiocal criteria of Wesseling. In this method, the brachial artery pressure measured was the reconstructed pressure from the finger pressure estimated through generalized waveform inverse modeling and generalized level correction. The subjects were asked to lie down and the brachial cuff of Finapres was tied around the midarm about 2 cm above the cubital fossa, and the finger cuff of small, medium, or large size were tied around the middle phalanx of the middle finger depending on the finger width. For the height correction, 2 sensors were placed, one at the heart level and another at the finger level. The recordings were obtained after connection of cables of the cuffs to the Finometer, after 10 minutes of supine rest. The “return to flow calibration and the Physiocal” was done for the level correction between the brachial and finger pressure during the initial 5 minutes of the recordings. After this, continuous BP recording was done for a period of 10 minutes.
The reconstructed brachial pressure was acquired through a PC-based data acquisition system (Finapres Medical Systems BV, Amsterdam, The Netherlands). The parameters recorded from the reconstructed brachial pressure tachogram were heart rate (HR), SBP, DBP, mean arterial pressure, rate-pressure product (RPP), interbeat interval, left ventricular ejection time, stroke volume, cardiac output, total peripheral resistance (TPR), and BRS.
Three conventional AFT were performed following the standard procedures. For HR and BP response to standing, BP and ECG were recorded in the supine position. The subject was instructed to attain the standing posture in 3 seconds. The ECG was continuously recorded during the procedure. BP was recorded every 40 seconds by an automatic BP monitor (Omron, SEM-1, Kyoto, Japan) till fifth minute. The 30:15 ratio (ratio of maximum RR interval at thirtieth beat to minimum RR interval at fifteenth beat after standing) was calculated.
For HR response to deep breathing, the subject was in sitting posture and HR and respiration monitoring was done from electrocardiographic recording and stethographic respiratory tracings recorded on the multichannel polygraph (Nihon-Kohden, Tokyo, Japan), respectively. A baseline recording of ECG and respiration was taken for 30 seconds. The subject was asked to take slow and deep inspiration followed by slow and deep expiration such that each breathing cycle lasted for 10 seconds, consisting of 6 breathing cycles/min. E/I ratio (ratio of average RR interval during expiration to average RR interval during inspiration in 6 cycles of deep breathing) was calculated from electrocardiographic tracing.
For BP response to isometric handgrip, baseline BP was recorded. The subject was asked to press handgrip dynamometer at 30% of maximum voluntary contraction for 2 minutes. BP was recorded at the first and second minutes of contraction. ΔDBP IHG (maximum increase in DBP above baseline) was noted.
Five milliliter of fasting blood sample was collected. The serum was separated from blood samples of all the subjects for estimation of biochemical parameters. Fasting blood glucose was estimated by glucose oxidase method using glucometer (LifeScan Inc, Milpitas, California). For determination of insulin resistance, homeostatic model assessment of insulin resistance (HOMA-IR) was calculated using the formula: HOMA-IR = fasting blood sugar (mmol) × insulin (μIU/L)/22.5.
Lipid profile parameters (total cholesterol [TC], triglycerides [TG], high-, low-, and very low-density lipoproteins) were assessed using fully automated chemistry analyzer (AU400; Olympus, Orlando, Florida). Atherogenic index (AI) was calculated using the formula: log 10 (TG/HDL). The high-sensitivity C-reactive protein (hs-CRP) was estimated by enzyme immunoassay method using enzyme-linked immunosorbent assay (ELISA) kit (DBC; Diagnostics Biochem Canada Inc, Ontario, Canada). Interleukin-6 (IL6) was measured by enzyme immunoassay method using ELISA kit (Ani Biotech Oy, Tiilitie, Finland). Tumor necrosis factor-α (TNFα) was estimated by enzyme immunoassay method using ELISA kit (Ani Biotech Oy, Tiilitie, Finland). Renin was estimated by enzyme immunoassay method using the ELISA kit of DRG Diagnostics (DRG Instruments GmbH, Frauenbergstr, Marburg, Germany). Oxidative stress was assessed by estimating thiobarbituric acid–reactive substance (TBARS) using ELISA kit (Cayman Chemical Co., Ann Arbor, Michigan).
SPSS, version 13 (SPSS Software Inc., Chicago, Illinois) was used for statistical analysis. All the data are expressed as mean ± SD. Normality of data was tested by Kolmogorov-Smirnov test. For parametric data, the level of significance between the groups was tested by Student unpaired t test, and for nonparametric data, Welch’s corrected t test was used. The association of LF/HF ratio with HRV, BPV, AFT, and biochemical parameters was assessed by Pearson correlation analysis. The independent contribution of various CV risk factors such as insulin resistance, AI, inflammatory markers, and oxidative stress to SVI (alteration in LF/HF ratio) was assessed by multiple regression analysis. Independent prediction of LF/HF and BRS to cardiac risk (increased RPP) in prehypertensives was assessed by multivariate logistic regression. A p value <0.05 was considered statistically significant.
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