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Saudi Journal of Kidney Diseases and Transplantation
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Table of Contents   
ORIGINAL ARTICLE  
Year : 2018  |  Volume : 29  |  Issue : 4  |  Page : 785-792
Evaluation of endothelial progenitor cell (CD34) as a marker of cardiovascular risk in children on regular hemodialysis


1 Department of Pediatrics, Faculty of Medicine (for Girls), Al-Azhar University, Cairo, Egypt
2 Department of Clinical Pathology, National Heart Institute, Cairo, Egypt
3 Department of Radiology, Faculty of Medicine (for Girls), Al-Azhar University, Cairo, Egypt

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Date of Submission05-Jul-2017
Date of Acceptance16-Aug-2017
Date of Web Publication28-Aug-2018
 

   Abstract 

Endothelial progenitor cells (EPCs) CD34 are bone marrow-derived cells that decrease in chronic kidney disease (CKD) patients especially when they reach end-stage renal disease and may be a risk marker of cardiovascular (CV) diseases. The aim of our study is to investigate the endothelial progenitor cell CD 34 numbers in children with CKD on regular hemodialysis (HD) and detect their association with vascular stiffness. We recruited 25 children on regular HD, who were selected from the HD unit of Al-Zahraa Hospital, Al-Azhar University. Another group of 25 age and sex matched healthy children served as as controls. We investigated the number of EPC number (CD34) using flow cytometry, intima-media thickness (IMT), and the peak systolic velocity (PSV) of the main arteries including the (aorta, carotid, and femoral) arteries using Doppler ultrasound, this is in the same line with the routine and traditional investigations of the CV risk in the study groups. Children on regular HD have significantly lower EPC numbers (CD34 numbers) compared to their controls, the median and the inter equatorial range of CD34 was 57 (17–122) and five (3–6), respectively (P 0.001). Significant positive correlations were found between CD 34 and triglycerides serum level (r = 0.817, P = 0.001), also between CD34 with IMT and PSV of the aorta (r = 0.685, P = 0.000: r = 0.457, P = 0.022), respectively. CD34 is 88% sensitive and specific for the detection of CV risk in children on regular HD. EPC CD34 exhibited a higher predictive value for CV risk in children on regular HD. Reduced EPC numbers contribute to accelerated atherosclerosis.

How to cite this article:
Abdel-Salam M, Abd Elsalam R, Youssef N, Mamdouh F, Abdel-Salam T. Evaluation of endothelial progenitor cell (CD34) as a marker of cardiovascular risk in children on regular hemodialysis. Saudi J Kidney Dis Transpl 2018;29:785-92

How to cite this URL:
Abdel-Salam M, Abd Elsalam R, Youssef N, Mamdouh F, Abdel-Salam T. Evaluation of endothelial progenitor cell (CD34) as a marker of cardiovascular risk in children on regular hemodialysis. Saudi J Kidney Dis Transpl [serial online] 2018 [cited 2019 May 22];29:785-92. Available from: http://www.sjkdt.org/text.asp?2018/29/4/785/239640

   Introduction Top


Cardiovascular diseases (CVDs) are known to be the most important causes of morbidity and mortality in children with chronic kidney disease (CKD), particularly in those undergoing hemodialysis. Although conventional CV risk factors occurred less frequently in children, those related to uremia might be present.[1]

Manifestations of CVD in childhood CKD include arterial stiffening,[2] calcification,[3] premature atherosclerosis[4] and left ventricular hypertrophy.[5]

Over time, CKD developing in children was associated with increased CV mortality that markedly accelerated once dialysis was initiated.[6],[7]

Circulating endothelial progenitor cells (EPCs) are bone-marrow derived CD34+ mononuclear cells (MNCs) capable of new vessel formation in ischemic injury, a process termed postnatal vasculogenesis.[8]

The EPCs induce proliferation, migration, and adhesion, and further differentiate into fully functional endothelial cells to maintain vascular integrity. EPCs migrate from the bone marrow to the systemic circulation and damaged tissue, and then incorporate into the vascular endo-thelial cell monolayer after differentiating into mature endothelial cells.[8]

The number of circulating EPCs has been identified as a surrogate biologic marker for vascular function and cumulative CV risk in the general population.[9]

Increased risk of CVD in end-stage renal disease (ESRD) has been explained by accelerated atherosclerosis and impaired angiogenesis, in which EPCs may play key roles.[10]

Here, we proposed that circulating EPCs are associated with CV risk and to clarify the predictive values of circulating EPCs in CV calcification.

We aimed to investigate EPC CD34 numbers in children with CKD on regular HD and compare them with healthy controls and detect the association between EPC and vascular stiffness.


   Patients and Methods Top


This case–control study included 50 children with their ages ranging from 6 to 18 years, divided into 25 children with ESRD (glome-rular filtration rate 15 mL/min/1.73 m2) on regular HD for 4-h/setting, three times weekly; according to KDIGO (2012).[11] The most common cause of CKD in the study patients is acquired causes (36%) followed by unknown and congenital causes (32%) and (28%), respectively.

In addition, it included 25 healthy children who served as controls. Children with primary vascular disease and those with any acute and other chronic illness were excluded from the study.

All children included in the study were subjected to full history (etiology and duration of CKD, duration of dialysis, cardiac symptoms, and medications), general and local cardiac examination). Informed consent was obtained from the participating parents in adherence with the Ethical Committee of Al Zahraa Hospital Al-Azhar University. The study was conducted with the participation between pediatric nephrology and HD, radiology and clinical pathology departments.

Investigations

Laboratory

Sampling

Two milliliters were drawn and placed into a vacutainer tube containing ethylenediamine-tetraacetic acid (EDTA) for complete blood picture using automated cell counter model Sysmex KxN21.

Five milliliters were drawn and placed into a plain tube, centrifuged within 30 min of collection and serum was separated and divided into one portion for blood urea nitrogen (BUN), serum creatinine, Ca, ph, cholesterol, and triglyceride at the same day. Another portion of the sample taken in EDTA solution as anticoagulant was kept at room temperature (18°C–25°C). Detection of CD34 was done by a Beckman Coulter flow cytometry and EPIC XL software (Brocklebank and Sparrow, 2001).[12]

Radiology

Assessment of intimal-medial thickness (IMT) and peak systolic velocity (PSV) of the main arteries including the aorta, carotid, and femoral arteries.

Both IMT and PSV were measured using the Doppler U/S “Esaote My lab50Xvisioin” apparatus in Al-Zhraa university hospital. The IMT was calculated as the distance between the leading edge of the lumen–intima interface and the media-adventitia interface on the far wall of the artery [Figure 1].[13]
Figure 1: Demonstrates IMT of the common carotid artery.
IMT: Intimal-medial thickness.


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PSV was measured by grayscale ultrasound using 7.5 MHZ probe. Doppler examination was done through B-Mode, color mode, and peak systolic velocity was measured. In B-Mode, the vessel appears anechoic with hyper-echoic walls [Figure 2].[14]
Figure 2: Demonstrates PSV of the common carotid artery.
PSV: Peak systolic velocity.


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   Statistical Analysis Top


Data were collected, revised, coded, and entered to the Statistical Package for Social Science version 20.0 (IBM Corp., Armonk, NY). Qualitative data were presented as number and percentages and compared between groups using Chi-square test while quantitative data with parametric distribution were presented as mean, standard deviations and ranges and compared between groups using Independent t-test, also quantitative data with nonparametric distribution was presented as median with inter-quartile ranges and compared between groups using Mann–Whitney test. Spearman correlation coefficients were used to assess the correlation between two quantitative parameters in the same groups. Receiver operating characteristic curve (ROC) was used to assess the best cut off point with sensitivity and specificity. The confidence interval was set 95% so, the P value was considered statistically significant at the level of <0.05.


   Results Top


[Table 1] shows a comparison between dialysis children and healthy controls regarding demographic data and blood pressure (BP) measurements; it revealed a significant increase in BP (systolic and diastolic) in patients group compared to their controls.
Table 1: Comparison between patients group and controls regarding demographic data and blood pressure

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[Table 2] shows a comparison between dialysis children and healthy controls regarding laboratory data. As can be expected, it showed significant higher values of BUN, creatinine, cholesterol, triglyceride, Ph, PTH) serum levels in patients group than healthy controls, while there was significant low values of RBCs counts, hemoglobin level, serum Ca, albumin, and CD34 numbers in dialysis children than healthy controls.
Table 2: Comparison between patients group and controls regarding laboratory data.

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[Table 3] shows a comparison between dialysis children and healthy controls regarding Doppler ultrasound assessment of IMT and peak systolic velocities of the big arteries, it revealed a significant increase in the IMT and peak systolic velocities of the aorta in patients group compared to their controls.
Table 3: Comparison between patients group and the controls regarding intima medial thickness and peak systolic velocity of (aorta, carotid and femoral) arteries

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[Figure 3] demonstrates a significant positive correlation between CD34 and peak systolic velocity of the aorta. [Figure 4] demonstrates a significant positive correlation between CD34 and IMT of the aorta. [Figure 5] demonstrates the significant positive correlation between CD34 and triglyceride serum level.
Figure 3: Correlation between CD34 and peak systolic velocity of the aorta.

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Figure 4: Correlation between CD34 and intima-media thickness of the aorta.

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Figure 5: Correlation between CD34 and triglyceride serum level.

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[Table 4] and [Figure 6] show the cutoff point between cases and controls regarding CD34, sensitivity, and specificity of CD34 as an early marker for prediction of CV risk in children on HD; it revealed the cutoff point of CD34 between cases and controls is ≤10 with 88% sensitivity and specificity in the prediction of CV risks in children on HD.
Table 4: The cutoff point, area under the curve, sensitivity, and specificity of CD34 for prediction of cardiovascular risk in children on regular hemodialysis.

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Figure 6: Specificity and sensitivity of CD34 in the prediction of CV risk in children on hemodialysis.

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   Discussion Top


The low number of circulating EPCs has emerged as a biomarker of CV risk in adults. However, data regarding EPCs in pediatric populations with CV risk factors are limited. Children with CKD are considered in the highest of CV risk (NHLB, 2011).[15] Only a few studies have been conducted in children or young adults with present CV risk factors to examine whether a reduction of EPCs is present at early stages of disease and whether alterations in circulating progenitor subpopulations correlate with blood vessels structure and function.

The major concern of this study was not only to assess the number of EPCs (CD34) in children with (CKD) on regular HD as a nontraditional marker of CV risk but also to detect their relation to the vascular structure and function. It was interesting and unfortunate to find a significant decrease in CD34 numbers in children on regular HD in comparison to their controls. CD34+ are bone-marrow derived MNCs, and it is a special subtype of progenitor cells which can differentiate into mature endothelial cells, thus contributing to reendothelialization and neovascularization.[16] EPCs are not true endothelial progenitors, although they are likely to play a role in angiogenesis by virtue of the release of paracrine angiogenic factors.[17] Therefore, these patients with CKD low EPC counts are deprived of the function of these, and this is why they are more prone to the CV risk.

Several factors present in patients with CKD may have an effect on EPC number and function: hypertension, dyslipidemia, glucose intolerance, microinflammation and increased C-reactive protein, oxidative stress, low levels of erythropoietin, and uremic toxins,[18] according the study results patients included in the study were anemic, hypertensive, and dyslipidemic, in addition to hypoalbuminemia, altered albumin homeostasis in ESRD patients is caused by a systemic inflammatory state.[19]

Our study was in agreement with Krenning et al and Rabelink et al,[20],[21] they reported significant decrease in CD34 numbers in CKD patients. Vasa et al[22] also reported that EPC numbers correlated with CV risk. They showed that patients with coronary artery disease had substantially lower numbers of detectable EPC (circulating or colonies) than age-matched controls. Serum triglyceride level significantly and positively correlates with circulating CD34.

This suggests that serum triglyceride levels may constitute an efficient tool for estimating the risk of insufficient vascular homeostasis. This is in agreement with Shantsila et al 2007[23] who reported a similar finding. IMT and PSV of the aorta significantly and positively correlate with circulating CD34-this means that alterations in circulating progenitor subpopulations correlate blood vessels structure and function. EPCs are important for large vessel repair after injury or in atherosclerosis[24] and also in the endothelial regeneration, characterized by the expression of varying surface markers that adhere to the damaged endothelium promoting tissue repair.[25]

ROC curve analysis demonstrated that EPCs is highly sensitive and specific marker for early diagnosis of CV risks in children on HD with 88% sensitivity and specificity.

In conclusion, low values of CD34+ cell count is a risk factor with significant predictive value in addition to the traditional CV risk in children on HD due to impaired endogenous regenerative and repair capacity. Although the endo-thelial progenitor cell remains a research tool at the present time, it is our contention that this technology will figure prominently not only in risk assessment but also in the treatment strategies in the future.


   Limitations of the Study Top


The relatively low number of participants is the only limitation of the study.

Conflict of interest: None declared.

 
   References Top

1.
Scavarda VT, Pinheiro AC, Costa SD, et al. Children with chronic renal disease undergoing dialysis or conservative treatment-differences in structural and functional echocardiographic parameters. Echocardiography 2014;31:1131-7.  Back to cited text no. 1
    
2.
Shroff R, Dégi A, Kerti A, et al. Cardiovascular risk assessment in children with chronic kidney disease. Pediatr Nephrol 2013;28:875-84.  Back to cited text no. 2
    
3.
Shroff RC, McNair R, Figg Net al. Dialysis accelerates medial vascular calcification in part by triggering smooth muscle cell apoptosis. Circulation 2008;118:1748-57.  Back to cited text no. 3
    
4.
Dursun I, Poyrazoglu HM, Gunduz Z, et al. The relationship between circulating endothelial microparticles and arterial stiffness and atherosclerosis in children with chronic kidney disease. Nephrol Dial Transplant 2009;24: 2511-8.  Back to cited text no. 4
    
5.
Mitsnefes MM, Barletta GM, Dresner IG, et al. Severe cardiac hypertrophy and long-term dialysis: The Midwest pediatric nephrology consortium study. Pediatr Nephrol 2006;21: 1167-70.  Back to cited text no. 5
    
6.
McDonald SP, Craig JC; Australian and New Zealand Paediatric Nephrology Association. Long-term survival of children with end-stage renal disease. N Engl J Med 2004;350:2654-62.  Back to cited text no. 6
    
7.
Oh J, Wunsch R, Turzer M, et al. Advanced coronary and carotid arteriopathy in young adults with childhood-onset chronic renal failure. Circulation 2002;106:100-5.  Back to cited text no. 7
    
8.
Tilling L, Chowienczyk P, Clapp B. Progenitors in motion: Mechanisms of mobilization of endothelial progenitor cells. Br J Clin Pharmacol 2009;68:484-92.  Back to cited text no. 8
    
9.
Lu CL, Leu JG, Liu WC, et al. Endothelial progenitor cells predict long-term mortality in hemodialysis patients. Int J Med Sci 2016;13: 240-7.  Back to cited text no. 9
    
10.
Hickson LJ, Eirin A, Lerman LO. Challenges and opportunities for stem cell therapy in patients with chronic kidney disease. Kidney Int 2016;89:767-78.  Back to cited text no. 10
    
11.
KDIGO. KDIGO clinical practice guideline for anemia in chronic kidney disease. Kidney Int Suppl 2012;2:283-7.  Back to cited text no. 11
    
12.
Brocklebank AM, Sparrow RL. Enumeration of CD34+ cells in cord blood: A variation on a single-platform flow cytometric method based on the ISHAGE gating strategy. Cytometry 2001;46:254-61.  Back to cited text no. 12
    
13.
Sundholm J, Gustavsson T, Sarkola T. Semiautomatic border detection software for the quantification of arterial lumen, intima-media and adventitia layer thickness with very-high resolution ultrasound. Atherosclerosis 2014; 234:283-7.  Back to cited text no. 13
    
14.
Chavhan GB, Parra DA, Mann A, Navarro OM. Normal Doppler spectral waveforms of major pediatric vessels: Specific patterns. Radiographics 2008;28:691-706.  Back to cited text no. 14
    
15.
Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents, National Heart, Lung, and Blood Institute. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: Summary report. Pediatrics 2011 ;128 Suppl 5:S213-56.  Back to cited text no. 15
    
16.
Li Q, Wang Y, Liu H, et al. Leukocyte cells identification and quantitative morphometry based on molecular hyperspectral imaging technology. Comput Med Imaging Graph 2014;38:171-8.  Back to cited text no. 16
    
17.
Pearson JD. Endothelial progenitor cells – Hype or hope? J Thromb Haemost 2009;7:255-62.  Back to cited text no. 17
    
18.
Patel RS, Li Q, Ghasemzadeh N, et al. Circulating CD34+ progenitor cells and risk of mortality in a population with coronary artery disease. Circ Res 2015;116:289-97.  Back to cited text no. 18
    
19.
Haller C. Hypoalbuminemia in renal failure: Pathogenesis and therapeutic considerations. Kidney Blood Press Res 2005;28:307-10.  Back to cited text no. 19
    
20.
Krenning G, Dankers PY, Drouven JW, et al. Endothelial progenitor cell dysfunction in patients with progressive chronic kidney disease. Am J Physiol Renal Physiol 2009;296: F1314-22.  Back to cited text no. 20
    
21.
Rabelink TJ, de Boer HC, van Zonneveld AJ. Endothelial activation and circulating markers of endothelial activation in kidney disease. Nat Rev Nephrol 2010;6:404-14.  Back to cited text no. 21
    
22.
Vasa M, Fichtlscherer S, Aicher A, et al. Number and migratory activity of circulating endothelial progenitor cells inversely correlate with risk factors for coronary artery disease. Circ Res 2001;89:E1-7.  Back to cited text no. 22
    
23.
Shantsila E, Watson T, Lip GY. Endothelial progenitor cells in cardiovascular disorders. J Am Coll Cardiol 2007;49:741-52.  Back to cited text no. 23
    
24.
Griese DP, Ehsan A, Melo LG, et al. Isolation and transplantation of autologous circulating endothelial cells into denuded vessels and prosthetic grafts: Implications for cell-based vascular therapy. Circulation 2003;108:2710-5.  Back to cited text no. 24
    
25.
Glowiñska-Olszewska B, Moniuszko M, Hryniewicz A, et al. Relationship between circulating endothelial progenitor cells and endothelial dysfunction in children with type 1 diabetes: A novel paradigm of early atherosclerosis in high-risk young patients. Eur J Endocrinol 2013;168:153-61.  Back to cited text no. 25
    

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Correspondence Address:
Prof. Manal Abdel-Salam
Pediatrics Department, Faculty of Medicine (for Girls), Al-Azhar University, Cairo
Egypt
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DOI: 10.4103/1319-2442.239640

PMID: 30152413

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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

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