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. 2018 Sep 10;20(10):1519–1526. doi: 10.1111/jch.13365

Kidney protective effects of baroreflex activation therapy in patients with resistant hypertension

Manuel Wallbach 1, Petra Zürbig 2, Hassan Dihazi 1, Gerhard A Müller 1, Rolf Wachter 3,4, Joachim Beige 5,6, Michael J Koziolek 1,✉, Harald Mischak 2,7
PMCID: PMC8030795  PMID: 30203514

Abstract

Baroreflex activation therapy (BAT) is approved for the treatment of resistant hypertension. In addition to blood pressure (BP) reduction, pilot studies suggested several organoprotective effects of BAT. Thirty‐two patients with resistant hypertension were prospectively treated with BAT. Besides office BP and 24‐hour ambulatory BP (ABP) measurements, detection of a urinary proteome‐based classifier (CKD273), which has been shown to predict chronic kidney disease (CKD) progression, was carried out at baseline and after 6 months of BAT. Office BP significantly decreased from 170 ± 25/90 ± 18 to 149 ± 29/82 ± 18 mm Hg. Analysis of CKD273 score and eGFR with CKD‐EPI equation at baseline revealed strong correlation (r = 0.568, P < 0.001). After 6 months of BAT, there was no significant change in CKD273 score (−0.061 [95% CI: −0.262 to 0.140], P = 0.601). However, by stratification of the data regarding ABP response, there was a statistically significant (P = 0.0113) reduction in the CKD273 score from a mean of 0.161 [95% CI: −0.093 to 0.414] to −0.346 [95% CI: −0.632 to −0.060] after BAT in patients with systolic ABP decrease of ≥5 mm Hg. These data emphasized potential nephroprotective effects of BAT in patients with sufficient BP response.

Keywords: baroreflex activation therapy, CKD273, resistant hypertension, urinary proteomic

1. INTRODUCTION

Kidney disease improving global outcomes (KDIGO) guidelines for the management of blood pressure (BP) in chronic kidney disease (CKD) recommend that both diabetic and nondiabetic patients without albuminuria with non‐dialysis‐dependent CKD should have an office BP controlled ≤ 140/90 mm Hg, whereas BP target for patients with significant albuminuria (microalbuminuria or macroalbuminuria) with or without diabetes should be ≤ 130/80 mm Hg.1 Furthermore, according to the current definition, hypertensive patients who reach the BP target by means of four or more drugs are considered resistant.2, 3, 4 Existence of CKD is frequently associated with resistant hypertension,5 and observational studies suggest a strong association between hypertension (HTN) or proteinuria and the risk for renal function decline or end‐stage renal disease (ESRD)6 as well as cardiovascular events.

A new surgically implantable device for the treatment of resistant hypertension has been developed to administer baroreflex activation therapy (BAT) via electrical stimulation of the carotid baroreceptors. BAT has been shown to chronically reduce blood pressure (BP) in patients with resistant hypertension.7, 8, 9 Furthermore, a first prospective study demonstrated potential nephroprotective effects of BAT in therapy‐resistant hypertension in CKD patients by a reduction in BP, proteinuria, and also a stabilization of estimated GFR.10 In addition to these observations, there was also an improvement in the parameters of vascular stiffness.11

A urinary proteome‐based classifier (CKD273) has been developed12 and validated in large clinical studies to assess and predict progression of CKD.13, 14, 15, 16, 17, 18, 19, 20 CKD273 is used as a tool for patient stratification in a multicentric randomized clinical trial (PRIORITY).21 The validity of the CKD273 classifier has been recently evaluated applying the Oxford EBM and SORT guidelines,22 and a letter of support for CKD273 was issued by the US Food and Drug Administration.23

The present proteomic study aims to investigate whether BAT leads to a urinary proteomic‐based change in chronic kidney disease (CKD) progression. Proteome analysis of 32 urine samples from patients with resistant hypertension undergoing BAT was performed using capillary electrophoresis coupled to mass spectrometry (CE‐MS) analysis. The samples were prospectively analyzed at baseline and after 6 months of BAT, and then, classification of the samples with the CKD273 classifier was performed.

2. METHODS

2.1. Patients’ characteristics and BAT

In Table 1, all relevant clinical data are listed. Patients fulfilling diagnosis of resistant HTN with BP above national and international targets were evaluated and treated as described previously.24 In brief, for BAT, the Barostim neo (CVRx, Minneapolis, MN) was used and patient selection was conducted according to the suggestion of the German BAT consensus group.25 BAT was initiated 4 weeks after implantation, and the stimulation was individually increased by adaption of programmed parameters (pulse amplitude (1‐20 mA), pulse width (15‐500 ms), and frequency 10‐100 pulses/s) during monthly follow‐up according to patients’ office BP and tolerance. All patients included provided written informed consent before study initiation. This study was approved by the Local Ethical Committee of Göttingen (19/9/2011). The investigation conforms to the principles outlined in the Declaration of Helsinki.

Table 1.

Clinical data; mean (±SD)

Parameter Baseline After 6 mo P‐value
Patient no. 32
Responder 14
Age (y) 56 (±11)
Sex (% male) 47
Diabetes (%) 34
Systolic ABP (mm Hg) 145.9 (± 16.1) 141.4 (± 20.9) 0.11
Number of antihypertensive drugs 6.6 (± 1.5) 6.6 (± 1.5) 0.76
Responder 6.6 (± 1.6) 6.3 (± 1.9) 0.41
Nonresponder 6.8 (± 1.4) 6.8 (± 1.0) 1.0
eGFR (CKD‐EPI creatinine) (mL/min) 76 (± 30) 76 (± 30) 0.66
eGFR (MDRD) (mL/min) 74 (± 29) 76 (± 32) 0.40
Office RRsys (mm Hg) 170 (± 25) 149 (± 29) <0.01
Office RRdia (mm Hg) 90 (± 18) 82 (± 18) <0.01
Albumin/creatinine (mg/g) 25.5 (12.5−174.7) 25.7 (11.4−69.3) 0.49
CKD273 −0.017 (± 0.533) −0.061 (± 0.558) 0.60
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CKD‐EPI, chronic kidney disease epidemiology collaboration; eGFR, estimated glomerular filtration rate; serum creatinine in mg/dl to mol/L × 88.4. Values are mean ± SD or median (IQR).

2.2. Office BP measurement and 24‐hour ABPM

At baseline, BP was measured at each arm, and the arm with the higher BP was used for all subsequent readings. Brachial BP of the arm was recorded after 10 min of supine rest using a semiautomatic oscillometric device (Bosch + Sohn GmbH, Jungingen, Germany) two times within a 3‐minute interval. The mean values out of these two measurements were averaged. Ambulatory blood pressure measurement (ABPM) was performed using an oscillometric Spacelabs Model 90207 Recorder (Spacelabs Healthcare, Nürnberg, Germany) with readings taken every 15 minutes in daytime and every 30 minutes at nighttime. Ambulatory blood pressure (ABP) readings were averaged for 24 hours, day (7 am to 10 pm), and night (10 pm to 7 am). Patients were assessed while adhering to their usual diurnal activity and nocturnal sleep routine. According to the European Society of Cardiology/European Society of Hypertension guidelines, only recordings with >70% valid measurements were included in the analysis.26

2.3. Sample preparation

Whereas clinical researcher had access to clinical data, the investigation of the urine sample was performed in an independent laboratory. The laboratory investigators were blinded to patient clinical information. Decoding and statistical analysis were performed by the clinical team. The blinded urine samples were prepared essentially as described previously.27 Briefly, for CE‐MS analysis 0.7 mL aliquot was thawed immediately before use and diluted with 0.7 mL 2 mol/L urea and 10 mmol/L NH4OH containing 0.02% SDS. In order to remove high molecular weight polypeptides, samples were filtered using Centrisart ultracentrifugation filter devices (20 kDa molecular weight cutoff; Sartorius, Göttingen, Germany) at 3000 g until 1.1 mL of filtrate was obtained. Subsequently, filtrate was desalted using PD‐10 column (GE Healthcare, Göteburg, Sweden) equilibrated in 0.01% NH4OH in HPLC‐grade water. Finally, samples were lyophilized and stored at −20°C. This procedure results in an average recovery of sample in the preparation procedure ~85%.28 Shortly before CE‐MS analysis, lyophilisates were resuspended in HPLC‐grade water to a final protein concentration of 0.8 µg/µL checked by BCA assay (Interchim, Montlucon, France).

2.4. CE‐MS analysis

CE‐MS analysis was performed as previously described.29, 30 The limit of detection was ~1 fmol, and mass resolution was above 8000 enabling resolution of monoisotopic mass signals for z ≤ 6. After charge deconvolution, mass deviation was <25 ppm for monoisotopic resolution and <100 ppm for unresolved peaks (z > 6). The analytical precision of the platform was assessed by (a) reproducibility achieved for repeated measurement of the same replicate and (b) by the reproducibility achieved for repeated preparation and measurement of the same urine sample; details on analytical precision were reported recently.12 To ensure high data consistency, a minimum of 800 peptides/proteins had to be detected with a minimal MS resolution of 8000 in a minimal migration time interval of 10 minutes.

2.5. Data processing

Mass spectral ion peaks representing identical molecules at different charge states were deconvoluted into single masses using MosaiquesVisu software.31 Both CE migration time and ion signal intensity (amplitude) showed variability, mostly due to different concentrations of ions in the sample, and were consequently normalized. Reference signals of 1770 urinary peptides were used for CE‐time calibration by local regression. For normalization of analytical and urine dilution variances, MS signal intensities were normalized relative to 29 internal standard peptides generally present in at least 90% of all urine samples with small relative standard deviation. For calibration, linear regression was performed.32 The obtained peak lists characterized each polypeptide by its molecular mass [Da], normalized CE migration time [min], and normalized signal intensity. All detected peptides were deposited, matched, and annotated in a Microsoft SQL database allowing further statistical analysis.

2.6. CKD273 classifier analysis

The CKD273 classifier is a SVM‐based classification model,33, 34, 35 which allows the classification of samples in the high dimensional parameter space using MosaCluster software (version 1.7.0).36 Applying the CKD273 classifier to CE‐MS data of unknown samples, MosaCluster calculated classification scores, based on the amplitudes of the 273 peptides making up the CKD biomarker. Classification is performed by determining the Euclidian distance (defined as the SVM classification score) of the 273‐dimensional vector to a 272‐dimensional maximal margin hyperplane, which was defined previously.12 The cutoff for CKD diagnosis (>0.343) of the classification score was determined with the result of the biomarker discovery cohort in Good and colleagues12 Furthermore, to increase the sensitivity of classifier with respect to a better CKD prognosis a lower cutoff (0.154) was used in a clinical trial.21 For the present study, patients were grouped based on their CKD273 score in patients at high risk (>0.343), medium risk (between 0.343 and 0.154), and low risk (<0.154).

Reproducibility of the CKD273 score was shown previously. The relative intra‐assay standard deviation for the CKD273 score was between 7% and 10%.12, 37

2.7. Statistical analysis

Graphically analysis as well as a Shapiro‐Wilk test was used to test whether data were normally distributed. To analyze the potential differences between baseline and month 6 in the investigated variables, depending on the shape of the data, nonparametric Wilcoxon test or a paired two‐sided t test was used without correction for multiple testing. Results with P < 0.05 were considered statistically significant. R‐based statistic software (version 2.15.3) (Centre for Statistics, Frederiksberg, Denmark) and Statistica 13 (StatSoft Europe GmbH, Hamburg, Germany) were used for statistical analysis. P‐values for the difference between responders and nonresponders were calculated with Mann‐Whitney test for independent samples and were carried out in MedCalc 12.7.5.0 (MedCalc Software, Mariakerke, Belgium) as well as the Box‐and‐Whisker plots. Data were reported as mean ± SD or mean (95% CI).

3. RESULTS

Out of the 36 patients in this cohort, data from four patients were not included, one patient with IgA nephritis, and all relevant data for the other three patients were not available. In the investigated group of patients (n = 32), seven patients presented with macroalbuminuria, eight with microalbuminuria, and 17 without albuminuria at baseline. Office BP was reduced from 170 ± 25/90 ± 18 mm Hg to 149 ± 29/82 ± 18 mm Hg after 6 months of BAT (both P < 0.005). ABPM was determined with all 32 patients showing a reduction in systolic ABP of −4.4 ± 15.4 mm Hg, though without reaching statistical significance (P = 0.17). However, 14 patients (44%) could be classified as responders in 24‐hour ABP (systolic ABP decrease ≥5 mm Hg). The number of antihypertensive medication did not change between baseline and month 6 (6.6 ± 1.5 vs. 6.6 ± 1.5, P = 0.76), and there was no difference in the number of antihypertensive medication between responder and nonresponder at baseline (P = 0.61) and month 6 (P = 0.31).

Among the 32 analyzed patients, there are 28 patients (88%) with CKD, whereas nine patients (28%) showed CKD stage ≥3. Data are summarized in Table 1.

For the 32 patient samples (n = 64), high‐quality CE‐MS data sets were obtained. All measurements passed the quality control and were used for further analysis. All data were calibrated and annotated using the mosaiques human urinary database.38 The application of the CKD273 classifier resulted in classification scores, which are listed in the Table S1.

At baseline, mean CKD273 score was −0.017 [95% CI: −0.209 to 0.176] with 22 patients showing CKD273 score <0.154, three patients showing CKD273 score between 0.154 and 0.343, and seven patients showing CKD273 score above 0.343. As depicted in Figure 1, correlation analysis of CKD273 score and eGFR with CKD‐EPI equation at baseline revealed strong correlation (r = −0.568, P < 0.01). After 6 months of BAT, there was no significant change in CKD273 score (−0.061 [95% CI: −0.262 to 0.140], P = 0.60). Moreover, correlation analysis of the changes between baseline and month 6 values for systolic 24 hours ABP values and the changes in CKD273 score showed only moderate correlation without reaching statistical significance (Figure 2).

Figure 1.

Figure 1

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Correlation analysis of baseline between CKD273 scores and estimated glomerular filtration rate (eGFR). Chronic kidney disease epidemiology collaboration (CKD‐EPI)

Figure 2.

Figure 2

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Correlation analysis of changes between baseline and follow‐up of systolic 24‐h ABP and CKD273 scores. Δ was calculated by baseline—month 6 data. Therefore, Δ indicates reduction

By stratification of the data regarding ABP responders and nonresponders (Figure 3), there was a statistically significant (P = 0.01) higher CKD273 score within nonresponder of 0.161 [95% CI: −0.093 to 0.414] compared to −0.436 [95% CI: −0.628 to −0.051] within responder after BAT. In contrast to this result, there are no significant changes in the albumin/creatinine ratio (P = 0.12). Within responder, there was a trend toward reduction in the CKD273 score without reaching statistical significance during follow‐up (baseline: −0.117 (95% CI −0.675 to 0.132) vs. month 6: −0.436 (95% CI −0.628 to 0.051), P = 0.15).

Figure 3.

Figure 3

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Box‐and‐Whisker plots of (A) CKD273 scores and (B) albumin/creatinine ratio. The patients are stratified in ABP responders (red line) and nonresponders (black line), and data of baseline and follow‐up are shown. Line indicates the median, boxes indicate the interquartile range, and whiskers indicate the extreme values

To investigate the potential use of proteomics, we also compared the individual peptides within the proteomic classifier to evaluate differences in single peptides between responders and nonresponders in the follow‐up. Twenty of these peptides showed significant difference (P < 0.05) between responders and nonresponders after 6 months of BAT, and most (n = 19) of the peptides originated from collagens, but one from CD99 (Figure 4). Most collagen fragments (90%) as well as the CD99 peptide had lower amplitudes in the nonresponder group compared with the responders. Furthermore, some peptides (collagen alpha‐1 (I) chain [432‐451] and [820‐835]; collagen alpha‐1 (III) chain [1168‐1195]) had the same sequence but a different molecular mass based on a different number of modifications (hydroxylation of proline).

Figure 4.

Figure 4

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The presented peptides showed significant difference (P < 0.05) between responders and nonresponders after 6 mo of BAT. Fold changes of significant peptides of CKD273 are shown. Peptide with # is identical to a peptide of a previous study dealing with the treatment effect of spironolactone15

4. DISCUSSION

Using proteomic analysis, previous studies were able to show the effects of different treatments on CKD.15, 39 Also in this study, we analyzed urine samples from patients, who suffer from resistant HTN with potential complications based on CKD. The observation of the patient's data in the follow‐up (after 6 months) resulted in significant differences in CKD273 scores between ABP responders and nonresponders. In contrast, the albumin/creatinine ratio was not able to distinguish between the two groups. This result is not surprising, as previous proteomic studies also showed that CKD273 outperforms albuminuria in the prediction of CKD.20, 40 The major advantage of the CKD273 classifier is the prediction of CKD at early stages as the majority of patients within the present study.17, 20, 40, 41

There is evidence that CKD273 can directly reflect early kidney damage, as it is associated with renal fibrosis.42 This was also demonstrated with the correlation analysis of the baseline data, where CKD273 scores have a strong and significant correlation with eGFR (Figure 1), superior to that of albuminuria (data are not shown). Therefore, it may be possible to show the beneficial effects of a specific treatment. This effect can also be demonstrated in Figure 3A, by comparing the CKD273 scores at baseline and follow‐up. In the ABP responder group, the scores tended to be decreased, while the nonresponder scores at month 6 tended to be increased and lay within the category of a medium risk (between 0.343 and 0.154). Although previous studies suggested vasoprotective effects of BAT,11 data on nephroprotection are so far not so robust.10, 43 In this study, a strong surrogate of CKD progression was lower after 6 months of BAT in at least so‐called responders suggesting nephroprotection. The proof of nephroprotection by controlled studies, however, is still pending.

The further in‐depth investigation of single peptides of the CKD273 classifier resulted in the identification of almost solely collagen peptides, which are significantly different between the ABP responders and nonresponders. This aspect also underlines the hypothesis that collagen peptides are able to show early minor changes in the kidneys, in contrast to blood‐derived peptides, like albumin, which are more functional parameters and therefore “react” slower and later. Also, the regulation of the collagen peptides is in the same direction as in previous studies,12, 20 pointing out that collagen turnover in treated responders is more related to that of more healthy individuals, because in this group, higher concentrations can be found.

The present findings might be of special clinical relevance as collagen fragments appear to be the major component of urinary peptides and likely reflect physiologic turnover of the extracellular matrix, whereas decreased activity of collagenases was observed in patients with CKD resulting in accumulation of extracellular matrix, which represent the fibrotic kidney.28, 44, 45, 46

In addition, one collagen alpha‐1 (I) chain (Figure 4, peptide with #) peptide was also identified in another study dealing with the prediction of albuminuria response to spironolactone treatment with urinary proteomics in patients with type 2 diabetes and hypertension.15 In this study, the patients were also stratified in responders and nonresponders. The regulation of this peptide in our study is similar to the regulation in the previous study, pointing out that this peptide is independent of the treatment, but specific for the regeneration of the kidney under treatment.

Our study has several limitations. Major limitations of the study are the small sample size, the open design without a control group and the post hoc analysis. Strictly speaking, analyzing of the CKD273 based on the stratification into responders and nonresponders was a post hoc analysis, so that the results must be interpreted with caution. Moreover, the patients in this study were mainly in moderate CKD stages. However, independently of the mean baseline values, the CKD273 classifier can significantly show differences between responders and nonresponders. In nonresponders, the mean CKD273 score is above the cutoff for CKD prediction. The CKD273 has, however, only been validated for assessing and predicting the progression of CKD from cross‐sectional assessments. Though the CKD273 classifier was also validated in longitudinal studies with respect to the prognostic value of the classifier 20, 40 and is had been suggested to be a potential surrogate markers of renoprotection,39 it has not been completely validated for the change of the peptide fragment within a certain time frame as a marker for reduction in progression of CKD. Assessment of the acute influence of frequently described antihypertensive drugs showed no significant in vivo effect on the CKD273 score.37 However, individual urinary peptides were investigated with respect to their changes during a specific time under pharmacologic nephroprotective treatment showing improvement of CKD273.47

In conclusion, between ABP responders and nonresponders there was a statistical significant difference in the CKD273 score at month 6, suggesting that target organ damage might be reduced in patients who respond to inhibition of the sympathetic nervous system. Furthermore, this hypothesis was underlined by the fact that the peptides, which are responsible for the significant changes in CKD273, are mostly collagen peptides. These peptides were reported as being involved in the extracellular matrix processes of the kidney during CKD.12, 20, 48

CONFLICT OF INTEREST

MW, MK, and RW have received speaking honoraria and research grant from CVRx. RW declares having received lecture fees and enumeration for including participants into clinical trials from CVRx. RW has received consultant fees from CVRx. MK is member of the CVRx Barostim Hypertension Registry Steering Committee.

Supporting information

 

Click here for additional data file. (26.5KB, xls)

Wallbach M, Zürbig P, Dihazi H, et al. Kidney protective effects of baroreflex activation therapy in patients with resistant hypertension. J Clin Hypertens. 2018;20:1519–1526. 10.1111/jch.13365

Manuel Wallbach, Petra Zürbig and Michael J. Koziolek, Harald Mischak equally contributed to this study.

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