Abstract
Background and objectives
Inflammation is relevant in restenosis of atherosclerotic vascular diseases, but its role in dialysis arteriovenous fistula remains unknown. In animal studies, upregulation of monocyte chemoattractant protein-1 has been shown in venous segments of arteriovenous fistula. We, therefore, aimed to investigate serial changes in circulating monocyte chemoattractant protein-1 after percutaneous transluminal angioplasty of dialysis arteriovenous fistulas and its relation to restenosis.
Design, setting, participants, & measurements
Fifty-nine patients with dysfunctional arteriovenous fistulas that were referred for percutaneous transluminal angioplasty were enrolled prospectively between January of 2010 and July of 2012. Three of them were excluded due to percutaneous transluminal angioplasty failure or acute infection. Blood was sampled from arteriovenous fistulas at baseline, 2 days, 2 weeks, and 3 months after percutaneous transluminal angioplasty. Clinical follow-up was continued monthly for 3 months. Angiographic follow-up was arranged at the end of 3 months. Seventeen patients without significant stenosis were enrolled as the control group.
Results
Fifty-six patients completed clinical follow-up. Significant increases in monocyte chemoattractant protein-1 were observed at 2 days and 2 weeks (both P<0.001) after percutaneous transluminal angioplasty. Twenty-three (41%) patients had symptomatic restenosis. The restenosis group had a higher percentage change in monocyte chemoattractant protein-1 levels at 2 days (median =47%; interquartile range, 27%–65% versus median =17%; interquartile range, 10%–25%; P<0.001) after percutaneous transluminal angioplasty compared with the patent group. Fifty-two patients completed angiographic follow-up. A positive correlation between relative luminal loss and monocyte chemoattractant protein-1 increase at 2 days after percutaneous transluminal angioplasty was found (r=0.53; P<0.001). In multivariate analysis, postangioplasty monocyte chemoattractant protein-1 increase at 2 days was an independent predictor of restenosis. Using receiver operator characteristic analysis, >25% postangioplasty increase of monocyte chemoattractant protein-1 was significantly associated with restenosis after percutaneous transluminal angioplasty (hazard ratio, 5.36; 95% confidence interval, 1.81 to 15.8).
Conclusions
Circulating monocyte chemoattractant protein-1 levels were elevated 2 days and 2 weeks after percutaneous transluminal angioplasty. Early postangioplasty increase of monocyte chemoattractant protein-1 level was associated with restenosis of arteriovenous fistulas.
Keywords: angioplasty, arterioveous fistula, hemodialysis, monocyte chemoattractant protein-1, stenosis
Introduction
A well functioning hemodialysis vascular access greatly influences the survival and quality of life of patients with ESRD. A native arteriovenous fistula (AVF) is recommended as the preferred access of choice by the practice guidelines of the National Kidney Foundation Dialysis Outcomes Quality Initiative (NKF-DOQI) (1). Nonetheless, the primary unassisted patency rate of AVFs decreases to 75% after 2 years (2). The most common cause of AVF dysfunction is stenoses at the outflow veins (3). Percutaneous transluminal angioplasty (PTA) is an established therapy of stenoses in native AVFs. However, its benefits are attenuated by a high restenosis rate. Only 26%–58% of AVFs have no restenosis 1 year after PTA (4). Repeated interventions are usually required, and these impose a tremendous financial burden on the health care system (5).
The fundamental pathologic change of AVF stenosis is neointimal hyperplasia at venous segments, different from stenosis of atherosclerotic vascular diseases (3,6). The principle mechanism of PTA is disruption of stenotic lesions, which is inevitably accompanied by various degrees of vessel injury. The injured vessel initiates an inflammatory response that recruits mononuclear monocytes. They play a crucial role in vessel healing, remodeling, and cell proliferation (7). Monocyte chemoattractant protein-1 (MCP-1), the prototype of the C-C chemokine family, is broadly involved in the pathogenesis of atherosclerosis (8,9). An increase in MCP-1 is associated with restenosis after coronary angioplasty (10–12). Nonetheless, its role in restenosis of AVFs remains unclear.
Therefore, the aims of this study were to investigate (1) serial changes in circulating inflammatory markers, including high–sensitivity C–reactive protein (hs-CRP), IL-6, and MCP-1, after PTA of dialysis AVFs and (2) the association between inflammatory markers and restenosis.
Materials and Methods
Patients
Patients with dysfunctional hemodialysis AVFs referred for PTA were invited to participate in this study between January of 2010 and July of 2012. They were referred on the basis of one or more of the following criteria: (1) clinical signs suggesting vascular access dysfunction (decreased thrill, development of collateral veins, and increased pulsatility); (2) reduction of flow rate >25% from baseline; (3) total access blood flow rate <500 mL/min as measured by the ultrasound dilution method (Transonic Flow-QC; Transonic Systems, Ithaca, NY); or (4) increased venous pressure during dialysis (dynamic venous pressure exceeding threshold level measured three consecutive times). After diagnostic angiography, patients were included in the PTA group if they (1) received regular dialysis for >6 months; (2) had no history of infection, decompensated heart failure, or acute coronary syndrome requiring hospitalization within the past 3 months; and (3) showed >50% stenosis at the venous segment of the AVF with compatible clinical manifestations. Patients showing no significant stenosis were invited as the control group. Exclusion criteria were (1) failed PTA or (2) acute infection, decompensated heart failure, or acute coronary syndrome requiring hospitalization during the follow-up period. The study flow and design are illustrated in Figure 1. The study was on the basis of the Declaration of Helsinki (edition 6; revised 2000). Informed consent was obtained from all study participants, and the study was approved by the Institutional Research Board.
Figure 1.
Study flow and design for cohort and follow-up (F/U). BS, blood sampling; D, day; DSA, digitally subtracted angiography; HD, hemodialysis; M, month; PTA, percutaneous transluminal angioplasty; W, week.
Angiography, Angioplasty, and Quantitative Angiographic Analyses
Diagnostic angiography (Advantx; GE Healthcare, Waukesha, WI) was performed in the morning on a midweek dialysis day within 4 hours of the coming dialysis session. After diagnostic angiography, PTA was performed according to the NKF-DOQI guidelines (i.e., only for patients with a clinical indicator of dysfunction coupled with a minimum of 50% diameter stenosis) (1). The stenosis was treated with standard angioplasty techniques, and high-pressure or cutting balloons were used only for resistant stenosis (13,14). Stents, graft stents, or drug-eluting balloons were not used in this study. After the PTA procedure, aspirin was prescribed for 3 days. Medications for underlying cardiovascular disease or CKD were continued on the basis of the original indications.
A computer-based system (Digital DLX; GE Healthcare) was used for quantitative angiographic analysis. Measurement was performed by a physician who was blinded to data of inflammatory markers. The degree of stenosis was evaluated in two orthogonal planes, and the greatest degree of stenosis was used for subsequent anatomic measurements. Anatomic measurements were made using a calibrated reference marker with computer–assisted edge detection software within the angiographic imaging system. The reference vessel was defined as an adjacent segment of normal vein located upstream from the lesion. The degree of stenosis was reported as the maximum diameter reduction compared with the reference vessel diameter. The difference between the reference vessel and balloon diameters divided by reference vessel diameter was defined as oversizing. Angiographic restenosis was defined as >50% diameter reduction. Relative luminal loss was defined as the difference between stenosis after PTA and stenosis at follow-up angiogram, reflecting the degree of luminal renarrowing (15).
Follow-Up
Clinical Follow-Up.
After the PTA procedure, all patients received prospective clinical follow-up for 3 months under the same protocol at their respective hemodialysis centers. Clinical follow-up included physical examination and dynamic venous pressure monitoring at each hemodialysis session and transonic examination of access blood flow rate immediately after the intervention followed by monthly examination and telephone surveillance by a coordinating study nurse at monthly intervals. The referring nephrologists were blinded to participants’ data of inflammatory markers. When abnormal clinical or hemodynamic parameters were detected, patients were referred for repeat fistulography and PTA as appropriate.
Angiographic Follow-Up.
Participants were scheduled for a follow-up angiogram at the end of 3 months if no clinical restenosis developed. When symptom-driven PTA was performed before the end of 3 months, the angiogram before PTA was defined as the follow-up angiogram.
Laboratory Methods
Blood sampling for measurements of inflammatory markers was scheduled at baseline (after angiography but before PTA), 2 days, 2 weeks, and 3 months after PTA. The timing of sampling was standardized at a midweek hemodialysis session. Blood samples were drawn directly from AVFs before dialysis and immediately centrifuged at 3000 rpm for 10 minutes at 4°C. The plasma samples were then stored at −80°C until use. Plasma biochemical parameters, including cholesterol, triglyceride, calcium, phosphate, and albumin, were analyzed by standard laboratory procedures. Commercially available ELISA kits were used for measurement of hs-CRP (Dade Behring, Inc., Newark, NJ), IL-6, and MCP-1 (Quantikine HS; R&D Systems, Minneapolis, MN). The assay was performed by an independent laboratory, and staff were unaware of the patient’s clinical data. The intra– and interassay coefficients of variation were both <8%.
Statistical Analyses
Continuous variables were expressed as means±SD for normally distributed variables or medians (interquartile ranges [IQRs]) for non–normally distributed variables. An ANOVA for repeated measures with multiple comparison tests (Scheffe test) was performed to test changes in inflammatory markers measured over time. Categorical data were compared using the chi-squared test with Yates correction and Fisher exact test as appropriate. Univariate linear regression analyses were used to assess the relationships between MCP-1 levels and baseline variables. Differences between PTA and control groups or restenosis and patent groups at each time point were analyzed using t test or Mann–Whitney test. Changes in biomarker level were calculated as the difference from baseline level divided by the baseline level and are expressed as percentages. A cutoff number of circulating MCP-1 level and percentage change was determined by receiver operator characteristic analysis to maximize the power in predicting clinical restenosis. The restenosis-free patency was estimated using the Kaplan–Meier method, and differences between groups were compared by using the log-rank test. Univariate regression was performed to evaluate risk factors for restenosis. All variables with P<0.20 in univariate analysis were included in the multivariate regression model to determine independent predictors of restenosis. The estimated sample size with α=0.05, power =0.80, and expected MCP-1 difference of 160 pg/ml was 24 patients for each group (10). We further estimated the statistical power in this study to be 98.5% at 2 days, 52.5% at 2 weeks, and 30.9% at 3 months for a significant difference of MCP-1 between restenosis and patent groups. All P values were two tailed, and values of P<0.05 were considered statistically significant. Statistical analyses were conducted using SPSS, version 20.0. (SPSS Inc., Chicago, IL).
Results
Characteristics of Patients and AVFs
Fifty-nine patients were included initially. Three patients were excluded: one patient due to PTA failure and two due to acute infection during the follow-up period. No patient was transferred to peritoneal dialysis or kidney transplantation, and no patient died or was lost to clinical follow-up at the end of study. Four patients without clinical restenosis refused follow-up angiography. Consequently, 56 patients completed clinical follow-up, and 52 of them had angiographic follow-up (Figure 1).
Demographic characteristics, cardiovascular risk factors, biochemistry, and medications of the 56 patients at baseline are summarized in Table 1 stratified by the presence or absence of clinical restenosis. There were no differences in baseline clinical variables between the restenosis and patent groups, except that nitrate use was higher in the patent group. The AVF characteristics were comparable between restenosis and patent groups, except for longer lesion length in the restenosis group.
Table 1.
Baseline characteristics of study participants
| Characteristics | Control, n=17 | PTA, n=56 | ||
|---|---|---|---|---|
| Patent, n=33 | Restenosis, n=23 | P Value | ||
| Demographics | ||||
| Men | 12 (70%) | 18 (56%) | 10 (40%) | 0.59 |
| Age, yr | 63±13 | 66±12 | 65±14 | 0.80 |
| Dialysis vintage, mo | 98 (73–147) | 37 (23–53) | 44 (26–56) | 0.14 |
| Comorbidities | ||||
| Hypertension | 14 (82%) | 30 (91%) | 19 (83%) | 0.43 |
| Diabetes | 5 (29%) | 20 (61%) | 12 (52%) | 0.59 |
| Current smoker | 0 (0%) | 8 (24%) | 4 (17%) | 0.47 |
| Dyslipidemia | 1 (2%) | 12 (36%) | 10 (44%) | 0.78 |
| CAD | 1 (2%) | 18 (54%) | 12 (52%) | 0.99 |
| PAD | 0 (0%) | 7 (21%) | 8 (35%) | 0.16 |
| Biochemistry | ||||
| Cholesterol, mg/dl | 151±36 | 159±35 | 155±31 | 0.63 |
| Triglycerides, mg/dl | 121 (77–201) | 178 (110–304) | 174 (96–273) | 0.69 |
| Albumin, g/dl | 3.88±0.37 | 3.72±0.41 | 3.12±0.39 | 0.39 |
| Calcium, mg/dl | 9.72±1.11 | 9.59±1.15 | 9.60±0.95 | 0.99 |
| Phosphate, mg/dl | 5.33±1.99 | 4.73±1.44 | 4.95±1.90 | 0.70 |
| Hemoglobin, g/dl | 10.6±1.54 | 11.20±1.37 | 10.60±1.05 | 0.08 |
| Kt/V | 1.38±0.16 | 1.35±0.25 | 1.39±0.24 | 0.53 |
| Medications | ||||
| Antiplatelet | 4 (24%) | 13 (39%) | 11 (48%) | 0.59 |
| Calcium blocker | 6 (35%) | 19 (58%) | 8 (35%) | 0.11 |
| ACEI/ARB | 3 (18%) | 15 (46%) | 9 (39%) | 0.79 |
| β-Blocker | 6 (35%) | 10 (30%) | 7 (30%) | 0.99 |
| Lipid-lowering agents | ||||
| Statin | 1 (2%) | 4 (12%) | 3 (13%) | 0.99 |
| Nonstatin | 1 (2%) | 1 (3%) | 0 (0%) | 0.99 |
| Nitrate | 0 (0%) | 12 (36%) | 2 (9%) | 0.02 |
| Access and lesion | ||||
| Shunt age, mo | 91 (60–112) | 35 (22–47) | 51 (32–76) | 0.20 |
| Upper arm fistula | 0 (0%) | 11 (33%) | 13 (57%) | 0.10 |
| Right arm fistula | 6 (35%) | 6 (18%) | 4 (17%) | 0.99 |
| RV diameter, mm | — | 5.8±0.9 | 6.2±0.9 | 0.20 |
| Lesion length, cm | — | 3.4±1.5 | 4.5±2.0 | 0.03 |
| Pre-PTA stenosis, % | — | 73±14 | 78±14 | 0.17 |
| Post-PTA residual stenosis, % | — | 18±9 | 19±9 | 0.55 |
| Lesion location | — | |||
| Anastomosis | — | 3 (9%) | 2 (9%) | 0.99 |
| Outflow vein | — | 30 (91%) | 21 (91%) | 0.99 |
| Resistant stenosis | — | 4 (12%) | 4 (17%) | 0.70 |
| Procedures | ||||
| HPB-PTA | — | 2 (6%) | 4 (17%) | 0.22 |
| CB-PTA | — | 2 (6%) | 0 (0%) | 0.51 |
| Oversizing, % | — | 12±11 | 15±9 | 0.39 |
| Vessel complications | — | 1 (3%) | 2 (9%) | 0.56 |
Values are means±SD for normally distributed variables, medians (interquartile ranges) for non–normally distributed variables, and numbers (percentages) for dichotomous variables. Vessel complications include dissection and rupture of vessels. PTA, percutaneous transluminal angioplasty; CAD, coronary artery disease; PAD, peripheral artery disease; ACEI/ARB, angiotensin–converting enzyme inhibitor/angiotensinogen receptor blocker; RV, reference vessel; —, not applicable; HPB-PTA, high–pressure balloon percutaneous transluminal angioplasty; CB-PTA, cutting balloon percutaneous transluminal angioplasty.
Serial Change in Inflammatory Markers before and after PTA
Serial changes in plasma MCP-1 after PTA are shown in Figure 2. Compared with the control group, which received angiography only, patients receiving PTA had elevated plasma MCP-1 levels 2 days (25%; IQR, 15%–36% versus −2%; IQR, −6%–7%; P<0.001) and 2 weeks (14%; IQR, 5%–24% versus −6%; IQR, −11%–7%; P=0.04) after PTA. The elevation of MCP-1 was highest at 2 days and returned to baseline 3 months after PTA (Figure 2A). In contrast, hs-CRP and IL-6 levels were not significantly elevated during the follow-up in either the restenosis or the patent group (Table 2). When the PTA group was stratified by restenosis or no restenosis, plasma MCP-1 levels were significantly elevated at 2 days and 2 weeks after PTA in both the restenosis and patent groups (Figure 2B).
Figure 2.
Serial change of plasma monocyte chemoattractant protein-1 (MCP-1) levels before and at 2 days (2D), 2 weeks (2WK), and 3 months (3MO) after percutaneous transluminal angioplasty (PTA). (A) Control group (black circles) versus PTA group (white squares). (B) Restenosis group (white squares) versus patent group (black circles); data are means ±95% confidence intervals.
Table 2.
Inflammatory biomarkers before and after percutaneous transluminal angioplasty
| Biomarkers | Control, n=17 | PTA, n=56 | ||
|---|---|---|---|---|
| Patent, n=33 | Restenosis, n=23 | P Value | ||
| Absolute level | ||||
| hs-CRP, mg/L | ||||
| Before | 0.22 (0.12–0.61) | 0.54 (0.21–1.10) | 0.34 (0.23–0.76) | 0.32 |
| 2 d | 0.29 (0.10–0.49) | 0.59 (0.29–1.40) | 0.56 (0.36–0.86) | 0.99 |
| 2 wk | 0.22 (0.10–0.66) | 0.60 (0.19–1.35) | 0.39 (0.23–0.98) | 0.46 |
| 3 mo | 0.36 (0.11–0.62) | 0.43 (0.18–1.24) | 0.52 (0.25–0.72) | 0.66 |
| MCP-1, pg/ml | ||||
| Before | 425 (379–493) | 362 (268–425) | 303 (248–375) | 0.09 |
| 2 d | 442 (378–484) | 427 (310–505) | 437 (386–792) | 0.54 |
| 2 wk | 416 (368–510) | 389 (255–432) | 361 (300–446) | 0.37 |
| 3 mo | 381 (351–503) | 356 (255–432) | 321 (258–394) | 0.50 |
| IL-6, pg/ml | ||||
| Before | 4.9 (2.9–9.7) | 5.0 (3.0–8.3) | 3.6 (2.6–11.3) | 0.73 |
| 2 d | 5.5 (2.7–8.6) | 5.0 (2.9–8.8) | 6.1 (2.9–13.8) | 0.56 |
| 2 wk | 5.5 (3.2–7.1) | 5.5 (3.2–10.7) | 5.4 (3.0–16.4) | 0.70 |
| 3 mo | 4.7 (2.4–9.7) | 4.8 (3.1–6.9) | 3.9 (2.6–12.7) | 0.71 |
| Percentage change | ||||
| hs-CRP, % | ||||
| 2 d | −7 (−31–52) | 8 (−18–128) | 41 (−13–89) | 0.31 |
| 2 wk | −4 (−38–56) | 14 (−37–138) | 9 (−3–31) | 0.99 |
| 3 mo | −22 (−32–78) | −45 (−61–42) | 8 (−24–82) | 0.07 |
| MCP-1, % | ||||
| 2 d | −2 (−6–7) | 17 (10–25) | 47 (27–60) | <0.001 |
| 2 wk | −6 (−11–7) | 11 (−1–22) | 21 (9–36) | 0.05 |
| 3 mo | −6 (−11–5) | −1 (−4–5) | 6 (1–13) | 0.10 |
| IL-6, % | ||||
| 2 d | −10 (−23–19) | 19 (−41–69) | 32 (−12–97) | 0.26 |
| 2 wk | −10 (−22–18) | 4 (−25–98) | 42 (4–82) | 0.29 |
| 3 mo | 7 (−16–14) | −4 (−14–14) | 11 (−23–63) | 0.33 |
Values are expressed as medians (interquartile ranges); P values are patent versus restenosis. PTA, percutaneous transluminal angioplasty; hs-CRP, high–sensitivity C–reactive protein; MCP-1, monocyte chemoattractant protein-1.
Inflammatory Markers in Patients with and without Restenosis
Plasma levels of MCP-1, IL-6, and hs-CRP at baseline were not significantly different in the restenosis and patent groups (Table 2). Serially monitored IL-6 and hs-CRP levels at 2 days, 2 weeks, and 3 months after PTA were not significantly different between groups as well. The percentage changes of IL-6 and hs-CRP levels varied widely and did not differ between the restenosis and patent groups at any follow-up time point (Table 2). Compared with the patent group, the percentage changes in MCP-1 levels were significantly higher in the restenosis group at 2 days (47%; IQR, 27%–60% versus 17%; IQR, 10%–25%; P<0.001) and 2 weeks (21%; IQR, 9%–36% versus 11%; IQR, −1%–22%; P=0.05) after PTA (Figure 2B, Table 2).
Correlation between Inflammatory Markers and Relative Luminal Loss
Follow-up angiograms were performed in 52 patients, and their mean relative luminal loss was 34.8% (SD=22.4%). There was no correlation between relative luminal loss and absolute MCP-1 levels at any follow-up time point. A significant positive correlation was observed between relative luminal loss and percentage change in MCP-1 levels at 2 days (r=0.53; P<0.001) (Figure 3). In univariate linear regression analysis, the percentage increase in MCP-1 at 2 days was correlated with lesion length (β=9; 95% confidence interval [95% CI], 6 to 12; P<0.001), resistant stenosis (β=1; 95% CI, −0.05 to 39.1; P=0.05), and dilation with high-pressure balloons (β=27; 95% CI, 6 to 49; P=0.02) (Table 3). Stratification analysis by long or short lesions (classified by median of lesion length) was carried out to elucidate the association between luminal loss and MCP-1 increase at 2 days. We found that the association between relative luminal loss and MCP-1 increase was significant in both the long-lesion group (r=0.58; P=0.002) and the short-lesion group (r=0.41; P=0.03).
Figure 3.
Correlation between monocyte chemoattractant protein-1 (MCP-1) levels and relative luminal loss by follow-up angiography. (A) No correlation between baseline MCP-1 and relative luminal loss. (B) Positive correlation between percentage increase of MCP-1 at 2 days (48HR) after percutaneous transluminal angioplasty and relative luminal loss.
Table 3.
Results of univariate linear regression analysis between the lesion factors, therapeutic factors, and monocyte chemoattractant protein-1 levels
| Factors | MCP-1, Baseline, pg/ml | ΔMCP-1, 2 d, % | ||
|---|---|---|---|---|
| β (95% CI) | P Value | β (95% CI) | P Value | |
| Lesion factors | ||||
| Anastomosis involvement | −79 (−188 to 30) | 0.37 | −7 (−32 to 18) | 0.58 |
| Reference vessel diameter, mm | 25 (−10 to 60) | 0.21 | 4 (−3 to 12) | 0.27 |
| Lesion length, mm | −6 (−24 to 12) | 0.49 | 9 (6 to 12) | <0.001 |
| Pre-PTA stenosis, % | 2.1 (−0.1 to 4.3) | 0.06 | 0.07 (−0.43 to 0.58) | 0.77 |
| Residual stenosis after PTA, % | 2.5 (−0.9 to 5.9) | 0.15 | −0.22 (−0.99 to 0.56) | 0.58 |
| Resistant stenosis | −74 (−162 to 15) | 0.10 | 1 (−0.05 to 39.10) | 0.05 |
| Therapeutic factors | ||||
| Oversizing, % | −156 (−895 to 476) | 0.30 | 42 (−27 to 112) | 0.22 |
| High-pressure dilation | −83 (−184 to 16) | 0.10 | 27 (6 to 49) | 0.02 |
| Cutting balloon dilation | −31 (−201 to 141) | 0.72 | −6 (−45 to 32) | 0.74 |
| Vessel complications | 6 (−12 to 24) | 0.48 | −4 (−35 to 28) | 0.82 |
| Statin | −19 (−115 to 77) | 0.69 | 8 (−13 to 30) | 0.75 |
Vessel complications include dissection and rupture of vessels. MCP-1, monocyte chemoattractant protein-1; ΔMCP-1, percentage increase of monocyte chemoattractant protein-1 from baseline; 95% CI, 95% confidence interval; PTA, percutaneous transluminal angioplasty.
Prediction of Clinical Restenosis by the Increase in Postangioplasty MCP-1
On the basis of receiver operator characteristic analysis, 25% increase of MCP-1 level at 2 days after PTA was found to be the best cutoff value for predicting clinical restenosis (area under curve =0.86±0.05; P<0.001) (Figure 4A). Patients were divided into groups of high (>25%) versus low (<25%) percentage change in MCP-1. The Kaplan–Meier plot showed that the group with increases of MCP-1>25% had a lower restenosis–free patency rate compared with the group with a smaller percentage change in MCP-1 (<25%) (Figure 4B).
Figure 4.
Monocyte chemoattractant protein-1 increase predicts restenosis. (A) Receiver operator characteristic curve of postangioplasty monocyte chemoattractant protein-1 (MCP-1) increase for clinical restenosis. The area under receiver operator characteristic curve (AUC) was 0.86±0.05, which was significantly different from a random distribution (P<0.001). (B) Kaplan–Meier analyses showing the proportion of patients without clinical restenosis. Patients are divided according to a cutoff value of 25% postangioplasty MCP-1 increase. PTA, percutaneous transluminal angioplasty.
Univariate and Multivariate Analyses
Univariate regression analysis revealed that nitrate use, lesion length, and percentage change in MCP-1 at 48 hours were risk factors for restenosis (Table 4). Multivariate regression analysis showed hemoglobin, nitrate use, lesion length, and postangioplasty change in MCP-1 levels at 2 days to be independent predictors of restenosis (Table 4). Postangioplasty change in MCP-1 levels at 2 days remained a significant predictor of restenosis (hazard ratio, 1.22; 95% CI, 1.07 to 1.38; P<0.01), even after adjusting for demographic factors (dialysis vintage and hemoglobin), medication factors (use of calcium blocker and nitrate), and fistula factors (fistula location, predialysis stenosis, and lesion length).
Table 4.
Univariate and multivariate regressions for predictors of restenosis
| Predictors | Unit of Increase | Hazard Ratio | 95% CI | P Value |
|---|---|---|---|---|
| Univariate analysis | ||||
| Dialysis vintage | 1 mo | 1.01 | 0.96 to 1.03 | 0.15 |
| Hemoglobin | 1 g/dl | 0.66 | 0.41 to 1.18 | 0.10 |
| CCB | Use | 0.39 | 0.13 to 1.18 | 0.10 |
| Nitrate | Use | 0.17 | 0.03 to 0.84 | 0.03 |
| Fistula location | Upper | 2.60 | 0.87 to 7.79 | 0.09 |
| Lesion length | 1 cm | 1.42 | 1.02 to 1.16 | 0.04 |
| Stenosis, before PTA | 1% | 1.03 | 0.99 to 1.07 | 0.17 |
| MCP-1, baseline | 1 pg/ml | 0.99 | 0.99 to 1.00 | 0.08 |
| ΔMCP-1 at 2 d | 1% | 1.10 | 1.04 to 1.16 | <0.001 |
| ΔMCP-1 at 2 wk | 1% | 1.03 | 0.99 to 1.07 | 0.06 |
| Multivariate analysis | ||||
| Hemoglobin | 1 g/dl | 0.31 | 0.11 to 0.86 | 0.03 |
| Nitrate | Use | 0.03 | 0.01 to 0.65 | 0.03 |
| Lesion length | 1 cm | 1.60 | 1.07 to 2.42 | 0.02 |
| ΔMCP-1 at 2 day | 1% | 1.22 | 1.07 to 1.38 | 0.001 |
95% CI, 95% confidence interval; CCB, calcium channel blocker; PTA, percutaneous transluminal angioplasty; MCP-1, monocyte chemoattractant protein-1; ΔMCP-1, percentage increase of monocyte chemoattractant protein-1 from baseline.
Discussion
The results of this study show a serial change in circulating MCP-1 concentrations after PTA of dialysis AVFs. MCP-1 concentrations increased significantly 2 days after PTA and thereafter, declined to baseline by the end of the 3-month follow-up. The magnitude of the MCP-1 increase is correlated with late luminal loss. Patients with clinical restenosis had a more profound increase in MCP-1 levels early after PTA, independent of clinical, biochemical, angiographic, or procedural factors. To our knowledge, this study provides the first evidence in humans that an increase in MCP-1 is associated with restenosis of dialysis AVFs.
We found a small but significant increase in MCP-1 in peripheral blood early after PTA. MCP-1 is produced by monocytes, endothelial cells, and fibroblasts. Macrophages and smooth cells, the major cells present in tissue after balloon dilation, also elaborate MCP-1 (16,17). Activated platelets after angioplasty can also stimulate MCP-1 production in leukocytes (10). In vitro experiments have shown that MCP-1 expression in vascular smooth muscle is enhanced and peaks 48 hours after stimulation (17,18). Therefore, it is conceivable that MCP-1 is elaborated from the site of vessel injury after PTA. Previous studies in humans reveal an increase in MCP-1 in peripheral blood after coronary angioplasty. The elevation may persist for 3–6 months (10–12). Our study identified elevated MCP-1 in peripheral blood after PTA of dialysis AVFs. Nonetheless, MCP-1 levels declined 2 weeks later and returned to baseline at 3 months. The disparity may come from differences in pathology or therapy between atherosclerosis and dialysis AVFs. For example, stents were seldom used in dialysis AVFs but frequently used in arterial diseases (19). In animal studies, chemokine expression and leukocyte recruitment in response to balloon injury are less sustained than the response to stent injury (20).
There are two possible explanations for the association between the increase in MCP-1 and restenosis. First, MCP-1 is the major signal for the accumulation of mononuclear leukocytes after vessel injury (21). MCP-1 also enhances the generation of reactive oxygen species by monocytes, which evoke secondary cytokines and growth factors, in turn amplifying and sustaining the proliferative response (10). In animal studies, marked upregulation of MCP-1 has been shown in the venous segment of AVFs, and upregulation of MCP-1 gene expression accelerates intimal hyperplasia of vein grafts (7,22). A variety of anti–MCP-1 therapies prevent restenosis in animal studies (23–25). These data are consistent with our findings and support the concept that MCP-1 itself plays a relevant role in venous intimal hyperplasia of dialysis AVFs.
Second, the increase in MCP-1 was associated with the severity of lesions and devices of PTA, which were also predictors of restenosis (4,26,27). For example, lesion length was associated with an increase in MCP-1 and restenosis in our analysis. Consequently, the increase in MCP-1 may be a surrogate measurement for lesion or injury, not necessarily a direct mediator for restenosis. Nonetheless, the number of patients with resistant stenoses or special devices was small. It did not differ between patent and restenosis groups. In stratification analysis, an increase in MCP-1 was correlated with relative luminal loss in either the long- or short-lesion group. Furthermore, an increase in MCP-1 remained an independent predictor of restenosis after adjustment by lesion factors in multivariate analysis. These data suggest that an increase in MCP-1, at least to some extent, was not just a confounder of lesion or therapeutic devices.
Unlike atherosclerosis, baseline circulating inflammatory markers were not associated with restenosis of dialysis AVFs in our study. Baseline circulating inflammatory markers predict restenosis in patients with coronary artery diseases (13,28,29). Nonetheless, studies in dialysis AVFs reveal conflicting results (30–33). A dissimilar pathogenic process of dialysis AVFs may account for the disparity in some way. In other ways, baseline circulating MCP-1 is affected by a variety of nonvascular factors in patients who are uremic (34). Circulating MCP-1 does not necessarily parallel levels of MCP-1 at the tissue level or lesions of dialysis access (35). That may be the reason why baseline levels were not associated with restenosis.
In contrast, the most probable source of the MCP-1 increase after PTA is the disrupted lesions. Animal studies show peaking of MCP-1 mRNA within hours after angioplasty at the areas of balloon injury, which in turn, recruits more monocytes (20). In our analysis, the MCP-1 increase, rather than baseline levels, was correlated with lesion and procedural factors. Therefore, the MCP-1 increase may be a better measure of local inflammatory activation and better associated with restenosis than baseline levels.
In contrast to the widespread use of drug-eluting stents in coronary interventions, their use in AVFs is still uncommon. In animal studies, neutralization of MCP-1 before or immediately after arterial injury was effective in preventing intimal hyperplasia (24,36,37). Anti–MCP-1 gene therapy had been shown to inhibit smooth muscle cell proliferation and vein-graft thickening (23,25). On the basis of our findings, specific measures to suppress an elevation of MCP-1 may prevent intimal hyperplasia, especially in the early period after intervention. In addition, the inflammatory response triggered by interventions may be another predictor of restenosis. Consequently, modification of devices or techniques to limit vessel injury, such as cutting balloons or graft stents, may be beneficial in mitigating restenosis after PTA of AVFs (26,27,38,39).
The changes in circulating MCP-1 levels and its correlation coefficient with luminal loss were relatively small. Our sample size was small, and confirmation in a larger cohort is desirable. Tissue levels of MCP-1 were not assessed in this study and did not necessarily parallel circulating MCP-1 levels. The increase in MCP-1 may be a surrogate indicator for lesion or procedural factors and may not necessarily be a direct mediator.
Our study shows that circulating MCP-1 is elevated early after PTA, and an early increase of MCP-1 was associated with restenosis of dialysis AVFs. Whether modulating MCP-1 early after PTA can prevent restenosis deserves further investigation.
Disclosures
None.
Acknowledgments
This work was supported by grants from the National Science Council (NSC102-2811-B-010-027-MY3), the Novel Bioengineering and Technological Approaches to Solve Two Major Health Problems in Taiwan sponsored by the Taiwan Ministry of Science and Technology Academic Excellence Program (MOST 105-2633-B-009-003), Taipei Veterans General Hospital (V104C-050 and V104E4-001), the Ministry of Education’s Aim for the Top University Plan, and the Foundation for Poison Control. This study was supported, in part, by grants from the National Taiwan University Hospital, Hsinchu Branch (HCH103-1, HCH103-14, HCH103-67, HCH104-10, HCH104-11, HCH104-57, HCH104-58, HCH105-7, HCH105-14, and HCH105-24) and the National Science Council (NSC103-2314-B-002-183, NSC104-2314-B-002-206, and NSC105-2314-B-002).
The funders had no role in the study design; the collection, analysis, or interpretation of data; writing this report; or the decision to submit this report for publication.
Footnotes
Published online ahead of print. Publication date available at www.cjasn.org.
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