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Albuminuria, serum antioxidant enzyme levels and markers of hemolysis and inflammation in steady state children with sickle cell anemia

  • Karen E. Itokua1,
  • Jean Robert Makulo2, 4Email author,
  • François B. Lepira2,
  • Michel N. Aloni1,
  • Pépé M. Ekulu1,
  • Ernest K. Sumaili2,
  • Justine B. Bukabau2,
  • Vieux M. Mokoli2,
  • Augustin L. Longo2,
  • François M. Kajingulu2,
  • Chantal V. Zinga2,
  • Yannick M. Nlandu2,
  • Yannick M. Engole2,
  • Pierre Z. Akilimali3,
  • René M. Ngiyulu1,
  • Jean Lambert Gini1 and
  • Nazaire M. Nseka2
BMC NephrologyBMC series – open, inclusive and trusted201617:178

https://doi.org/10.1186/s12882-016-0398-0

Received: 25 February 2016

Accepted: 15 November 2016

Published: 17 November 2016

Abstract

Background

Oxidative stress is thought to be involved in the pathogenesis of microalbuminuria in Sickle cell anemia (SCA). Antioxidant enzymes such as glutathione peroxidase (GPx) and Cu-Zn superoxide dismutase (SOD) may play an important protective role. This study aimed to evaluate the association between albuminuria and these two antioxidant enzymes.

Methods

We consecutively recruited Steady state children aged between 2 and 18 years old with established diagnosis of homozygous SCA in two hospitals of Kinshasa/DR Congo. The relationship between Urinary Albumin Creatinine Ratio (UACR) and other variables of interest (age, systolic blood pressure, diastolic blood pressure, plasma GPx and Cu-Zn SOD, free plasmatic hemoglobin, LDH, indirect bilirubin, white blood cells (WBC), percentage of fetal hemoglobin, serum iron, ferritin, CRP) was analyzed by Bivariate correlation (Pearson’s correlation coefficient). Microalbuminuria was defined by urine albumin/creatinine ratio between 30 and 299 mg/g.

Results

Seventy Steady state Black African children with SCA (56% boys; average age 9.9 ± 4.3 years; 53% receiving hydroxyurea) were selected. Prevalence of microalbuminuria was 11.8%. LDH (r = 0.260; p = 0.033) and WBC count (r = 0.264; p = 0.033) were positively correlated with UACR whereas GPx (− 0.328; p = 0.007) and Cu-Zn SOD (− 0.210; p = 0.091) were negatively correlated with UACR.

Conclusions

Albuminuria is associated with decreased antioxidant capacity and increased levels of markers of hemolysis and inflammation. Therefore, strategies targeting the reduction of sickling and subsequent hemolysis, oxidative stress and inflammation could help preventing or at least delaying the progression of kidney disease in SCA children.

Keywords

Sickle cell anemia Albuminuria GPx Cu-Zn SOD Lactate dehydrogenase Inflammation

Background

Sickle cell anemia (SCA) is a hemoglobinopathy characterized by hemolytic anemia, increased susceptibility to infections and vaso-occlusion leading to a reduced patient’s quality of life and life expectancy [1]. Oxidative stress has been reported to play a significant role in the pathophysiology of hemolysis, vaso-occlusion and subsequent organ damage including the kidneys [13]. Sickling and subsequent hemolysis and anemia increase superoxide anion and other reactive oxygen species (ROS) production and impair ROS scavenging enzymes levels and activity in SCA patients [1]. Low ROS scavenging enzymes activity, due to either low intake of vitamins or impaired synthesis of enzymes because of cofactors deficiency [4], is thought to play the main role in the pathogenesis of oxidative stress-induced vascular complications and microalbuminuria [5]. Indeed, lower activities of superoxide dismutase (SOD), glutathione peroxidase (GPx) and catalase (CAT) as well as altered levels of enzyme cofactors such as zinc, copper, selenium and iron have been reported in SCA patients without and with microalbuminuria [5]. The knowledge of the association of microalbuminuria with oxidative stress could be of therapeutic interest. Although the use of antioxidants and supplementation of enzyme cofactors can be conceivably envisaged, the prominent renoprotective effect of angiotensin II type 1 receptor blocker (ARB) Telmisartan in type 2 diabetes, a condition associated with microalbuminuria as SCA has been reported to be mediated through enhancing antioxidant defense capacity and reducing oxidative stress [6]. Unfortunately, data on oxidative stress in SCA patients with and without microalbuminuria are very scare in Africa, a setting where SCA is prevailing [710]. In order to contribute to a better understanding of the physiopathology of glomerular damage in SCA, this work aimed to study the relationship between urinary albumin creatinine ratio (UACR) and enzymatic antioxidant status assessed using two markers: serum GPx and Cu-Zn SOD, in Steady state Black African children with SCA.

Methods

Subjects and study design

The design of this cross sectional study has been described elsewhere [11]. The study was conducted over a period of three months in two hospitals of Kinshasa/DR Congo: Monkole hospital and Saint-Crispin Medical Center. We consecutively recruited Steady state children aged between 2 and 18 years old with established diagnosis of homozygous SCA by isoelectric focusing method on the Capillaris 2® (SEBIA, France) after written informed consent provided by their legal guardians. Exclusion criteria included a recent history of blood transfusion, a current crisis or history of sickle cell crisis or acute illness two months prior to the study.

Data collection procedure and laboratory analysis

For each patient, anthropometric parameters, past medical history especially current medication were obtained and physical examination performed.

A venous blood sample was collected for the determination of the level of GPx and Cu-Zn SOD as well as other biochemical parameters of interest including Fetal hemoglobin (HbF), blood count, serum creatinine, total bilirubin and its fractions, lactate dehydrogenase (LDH), iron, ferritin, C reactive protein (CRP), plasma free Hb.

Cu-Zn SOD and GPx were assayed by double-sandwich Elisa method using biotin-streptavidin system [11]. For GPx and Cu-Zn SOD, the blood samples were centrifuged for 10 min at 3000 × g and the obtained plasma was separated, aliquoted to microtubes, and stored frozen at −80 °C until testing a few days later.

Single spot morning urine specimens were collected and urine samples containing blood (1+ or greater), white blood cells (1+ or greater) and/or nitrites were excluded. Both urine dipstick test and UACR measurement were performed. UACR was performed using an immunoassay method with DCA Bayer 2000 reagent (DCA Bayer analyzer®, Siemens Healthcare Diagnostics Pyt Ltd., 885 Mountain Highway, Australia). Normal albuminuria, microalbuminuria and macroalbuminuria were defined as UACR < 30 mg/g, 30 to 299 mg/g and ≥ 300 mg/g, respectively [12].

Ethical approval

Ethical approval for the study was granted by the institutional review boards of the Monkole hospital (006 CEFA-MONKOLE/2014) in line with the principles of the Declaration of Helsinki, second revision. The aim and study procedures were explained to the parents or legal guardians and they provided written consent before any of the subjects were included.

Data management and statistical analysis

Statistical analyses were performed using SPSS (version 21.0, SPSS Inc., Chicago, USA). The primary focus in the data analysis was to assess the relationship between UACR and the antioxidant status. For this purpose, bivariate correlation (Pearson’s correlation coefficient) analyses were performed to analyze the relationships between UACR and other numerical data. Analyses were carried out with Pearson’s correlation, simple and multiple linear regressions. Step-wise multivariate regression analysis was performed to determine the independent variables for UACR. For other results, numerical variables are presented as mean ± standard deviation (SD) for normally distributed values or as median with interquartile (IQ) range for nonparametric values and categorical variables are presented as percentage. Pearson chi-square or Fisher’s exact test were used to assess differences in categorical data between groups and Student t-test or Mann Whitney U test were used to assess numerical data as appropriate. Statistical significance was defined as p value of < 0.05.

Results

General characteristics of patients

Table 1 shows the general characteristics of the study population. Seventy children with SCA in steady state (56% boys) were selected among which 68 had UACR results. Their mean age was 9.9 ± 4.3 years. Macroalbuminuria was not found in this series. Prevalence of microalbuminuria was 11.8% in the whole group. Microalbuminuria was more prevalent among girls than boys, however, there was no statistically difference between the two groups (17.2% versus 7.7%; p = 0.293.
Table 1

General characteristics of the study population

 

Whole group n = 70

Boys n = 39

Girls n = 31

p

Age, years

9.9 ± 4.4

10.5 ± 4.3

9.0 ± 4.4

0.153

Hb, g/dl

8.2 ± 1.3

7.9 ± 1.3

8.6 ± 1.4

0.040

Leukocytes, elts/mm3

11618 ± 4621

11339 ± 4114

12011 ± 5113

0.568

Platelets, elts/mm3

380727 ± 154522

364.358 ± 132.846

401.884 ± 184.553

0.344

Reticulocytes, %

12.0 (8.5–17.6)

11,0 (7,0–15,5)

14,0 (9,6–19,8)

0.117

HbF, %

8.7 (3.5–16.9)

13.9 (6.9–21.4)

6.2 (2.1–9.7)

0.004

Patients receiving HU, %

37

21

16

0.552

HbF in patients receiving HU, %

14 (7–21)

11 (6–18)

19 (13–25)

0.081

Indirect Bilirubin, mg/dl

1.9 (0.9–3.5)

1.5 (0.9–3.8)

1.9 (1.1–3.5)

0.941

Total Bilirubin, mg/dl

2.5 (1.5–4.0)

2.2 (1.3–4.3)

2.6 (1.7–4.0)

0.632

Creatinine, mg/dl

0.38 ± 1.05

0.38 ± 0.12

0.37 ± 0.11

0.600

GFR, ml/min/1.73 m2

211 ± 54

209 ± 67

215 ± 35

0.691

LDH, UI/l

544 (400–771)

457 (338–761)

653 (490–788)

0.012

CPR, mg/l

3.4 (2.0–5.1)

3.0 (1.3–4.5)

3.9 (2.8–6.9)

0.151

Iron, micromol/l

16.2 (13.2–19.2)

16.3 (14.0–21.1)

15.5 (11.5–17.8)

0.892

Ferritin, ng/ml

209 (106–453)

301 (111–613)

184 (104–378)

0.396

Free plasmatic Hb, mg/l

168 (116–267)

140 (120–240)

210 (106–288)

0.278

Cu-Zn SOD, pg/ml

305 (112–556)

281 (96–426)

360 (130–657)

0.803

GPx, micromol/l

220 (100–476)

242 (107–549)

210 (93–466)

0.699

UACR, mg/g

12 (9–22)

10 (9–20)

18 (10–26)

0.058

Values are presented as means ± SD, median (IQ 25–75) or absolute frequency

CRP C reactive protein, HU hydroxyurea, GFR glomerular filtration rate, Hb hemoglobin, HbF fetal hemoglobin, LDH lactate deshydogenase, GPx Gluthation peroxidase, SOD Superoxide dismutase, UACR Urinary albumin creatinine ratio

In the study group, 37 patients (53%) received hydroxyurea (HU). Compared with the untreated patients, those who received HU had higher rates of GPx and Cu-SOD. They also had lower levels of UACR but the difference was not statistically significant (Table 2).
Table 2

Comparison of rates of antioxidants and albuminuria based on the HU treatment

 

Treated (37)

Untreated (33)

P

GPx, micromol/l

391 (199–678)

108 (65–220)

<0.001

Cu-Zn SOD, pg/ml

402 (96–694)

132 (53–407)

0.139

UACR, mg/g

10 (9–17)

19 (10–27)

0.094

Values are presented as median (IQ 25–75)

GPx Gluthation peroxidase, SOD Superoxide dismutase, UACR Urinary albumin creatinine ratio

Correlation between UACR and study variables

Table 3 shows correlation between UACR and study variables. LDH (r = 0.260; p = 0.033) and leucocytes levels (r = 0.264; p = 0.033) were positively correlated with UACR whereas GPx (− 0.328; p = 0.007) and Cu-Zn SOD (− 0.210; p = 0.091) were negatively correlated with UACR. There was no statistically correlation between UACR and age, systolic blood pressure, diastolic blood pressure, creatinine, glomerular filtration, fetal hemoglobin, plasma free hemoglobin, serum iron, ferritin, indirect bilirubin and CRP.
Table 3

Correlation between UACR and other variables in patients studied

Variables

UACR mg/g

r

p value

GPx, micromol/l

−0.328

0.007

Cu-Zn SOD, pg/ml

−0.210

0.091

Age, years

−0.135

0.271

SBP, mmHg

0.224

0.078

DBP, mmHg

0.110

0.389

Leucocytes/mm3

0.264

0.033

Fetal Hb, %

−0.011

0.931

LDH, UI/l

0.260

0.033

Free plasmatic hemoglobin, mg/dl

0.139

0.264

Indirect bilirubin, mg/dl

−0.016

0.898

CRP, mg/l

−0.002

0.988

Serum iron, micromol/l

−0.009

0.940

Ferritin, ng/ml

−0.104

0.397

Linear regression considering UACR as dependent variable

The results related to the linear regression are reported in Table 4 and Figs. 1 and 2. Simple linear regression indicates that GPx, leucocytes levels and LDH respectively explain 10.8, 7.0 and 6.8% of the variation of UACR. The Cu-Zn SOD influences the variation of UACR by about 4.4% without reaching statistical significance. In multivariate analysis, only GPx and LDH were associated with UACR. After adjustment, these two factors account for 14.4% of change in UACR.
Table 4

Simple and Multiple linear Regression of UACR according to other variables of interest in patients studied

Variables

constant

ß coefficient

P value

R 2

Simple linear regression

 GPx, micromol/l

20.955

−0.012

0.007

0.108

 Cu-Zn SOD, pg/ml

19.943

−0.008

0.091

0.044

 Leucocytes/mm3

9.802

0.001

0.033

0.070

 LDH, UI/l

10.917

0.011

0.033

0.068

Multiple linear regression

14.727

  

0.144

 GPx, micromol/l

 

−0.010

0.049

 

 LDH, UI/l

 

0.010

0.046

 
Fig. 1

UACR as a function of GPx

Fig. 2

UACR as a function of Cu-Zn SOD

Discussion

The main findings of the present cross-sectional study of Steady state SCA children can be summarized as follows. First, albuminuria was inversely correlated with antioxidant enzyme levels and positively to absolute white blood cell (WBC) count and LDH enzyme levels. Second, antioxidant enzyme glutathione peroxidase (GPx) and LDH levels emerged as the main independent multivariate determinants of albuminuria but the model explained only 14% of the variations of albuminuria. Third, patients receiving hydroxyurea appear to have improved antioxidant capacity and low UACR.

In our cohort, we found an inverse correlation between albuminuria and antioxidant enzyme GPx and Cu-Zn SOD. This observation is similar to previous reports from Nigeria [8], Egypt [9] and Qatar [5]. The decrease in antioxidant enzyme levels and activity could be explained by their susceptibility to ROS-induced oxidation [13, 14]. Reduced glutathione (GSH), a cofactor for GPx, is oxidized to glutathione disulfide (GSSG) through its reduction of free radicals and ROS and is an essential element to reduce hydrogen peroxide (H202). This finding may suggest that the overabundance of oxidative stress leads to consumption or inactivation this protective cofactor [13, 14]. Oxidative damage may alter both the structure and the function of the glomerulus due to its effects on mesangial and endothelial cells [8, 15]. Oxidative stress has been reported to oxidize angiotensinogen and convert it to angiotensin II (ATII) and to increase secondary angiotensin type 1 receptor (AT1R)-mediated generation of transforming growth factor-beta (TGFβ) in the kidney in SCA; excessive AT1R signaling causes SCA glomerulopathy [15, 16].

A Previous study reported the relationship between albuminuria and inflammation, and hemolysis [17]. This report has been confirmed by our results, albuminuria was positively correlated with leukocytes count and LDH level. These results suggest that the activation of vascular endothelial cells and the circulating blood cells represent the continual inflammation seen in SCA. Upon activation, circulating white blood cells and platelets express adhesion glycoproteins leading that will interact with endothelial cell adhesion molecules leading consequently to endothelial dysfunction [14].

The LDH is known to be a marker of hemolysis. The positive association between albuminuria and LDH suggest the central role of hemolysis as the starting point for many of the subsequent complications of SCA, including kidney damage [14, 18]. A Previous study has already reported a significant correlation between serum LDH levels and albuminuria [19]. Indeed, hemolysis through increased plasma-free hemoglobin concentrations can induce the generation of ROS by non-enzymatic (Fenton reaction) with subsequent oxidative stress, inflammation, endothelial dysfunction and tissue damage [14, 19]. However, the hemolytic origin of circulating LDH remains a matter of controversy. Indeed, Neely et al. found that the increase in serum LDL levels was not correlated with plasma-free hemoglobin level and suggested that the source of LDH is damaged tissue as this enzyme is an ubiquitous one and seen in nearly all living cells where it catalyzes the conversion of lactate to pyruvic acid [20].

In multivariate analysis, GPx and LDH levels were independent determinants of albuminuria but the model explained only 14% of the variation in albuminuria levels suggesting the non-inclusion in the model of other variables susceptible to influence this variation. Although an association between markers of oxidative stress and common secondary diseases in SCA have been reported, other factors such as diet, physical activity, and other comorbid diseases associated with SCA may interfere with the variations in albuminuria levels [14]. Some of these factors were not included in the present study and could explain the low determination coefficient of the multivariate model.

For decades, many studies worldwide have shown the benefit of HU in SCA [21, 22]. Although the difference did not reach statistical significance, patients who received HU had higher levels of Cu-Zn SOD and lower UACR. Unlike GPx in both groups (under HU patients and untreated patients) had reached statistical significance. The precise mechanism by which HU produces its varied effects is not fully elucidated. The efficacy of HU is generally attributed to its ability to boost the levels of HbF [23].

Our results should be interpreted within the limitations of the present work. First, the cross-sectional design of the study precludes the establishment of temporal relationships between study variables. Secondly, the small sample does not confer much power to statistics tests to identify additional associations between the study variables. Third, given the limited financial resources, we did not measure the cofactors of antioxidant enzymes and trace elements to better explain the alterations in enzymes levels. The assay of transferrin also was not done. However, we can mention that both ferritin (evaluated in present study) and transferrin prevent the iron to react with its immediate environment. Indeed, in healthy cells, the iron ions are chelated by transport proteins (transferrin) or storage proteins (ferritin). Fourth, in medical human literature, there are few data on reference values of each antioxidant or oxidative stress markers. It is known that, initially, the body will react in a moderate oxidative stress by overexpressing antioxidant enzymes (eg when exercise). If the stress persists and produces massively free radicals, SOD and GPx will be destroyed and its concentration drops. Paradoxically, a too high concentration of SOD can be dangerous because, in this case, it is the basis of a hydrogen peroxide overproduction (paradoxical effect of antioxidants) [24].

Conclusion

In the present study, albuminuria was associated with decreased antioxidant capacity and increased levels of markers of hemolysis and inflammation. Therefore, strategies targeting the reduction of Sickling and subsequent hemolysis and oxidative stress and inflammation could help preventing or at least delaying the progression of cardiovascular and kidney disease in SCA children.

Abbreviations

ARB: 

Angiotensin II type 1 receptor blocker

ATII: 

Angiotensin II

CAT: 

Catalase

CRP: 

C reactive protein

GPx: 

Glutathione peroxidase

HbF: 

Fetal hemoglobin

HU: 

Hydroxyurea

LDH: 

Lactate dehydrogenase

ROS: 

Reactive oxygen species

SCA: 

Sickle cell anemia

SOD: 

Super oxide dismutase

TGF β: 

Transforming growth factor beta

UACR: 

Urinary albumin creatinine ratio

WBC: 

White blood cell

Declarations

Acknowledgements

The authors gratefully thank the staff of the laboratories of Monkole hospital, Saint-Crispin Medical Center and Kinshasa School of Public Health.

Funding

This work received no financial assistance from any funding agency in the public, commercial or non-profit sectors.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

KEI wrote the first draft of the manuscript. KEI, FBL and JRM designed, acquired data, analyzed, interpreted data, drafted and revised the manuscript. MNA, PME, ESK, JBB, VMM, ALL, CVZ, FMK, YMN, YE, RN, JLG, PZA and NMN interpreted data and revised the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they do not have any financial interest with the information contained in this paper.

Consent for publication

Not applicable.

Ethics and consent to participate

The study protocol was approved by the ethical committee of Monkole Medical Center (006 CEFA-MONKOLE/2014). The aim and study procedures were explained to the parents or legal guardians and they provided written consent before any of the subjects where included.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Division of Hematology, Oncology and Nephrology, Department of Pediatric, University of Kinshasa Hospital, University of Kinshasa
(2)
Nephrology Unit, Department of Internal Medicine, University of Kinshasa Hospital, University of Kinshasa
(3)
Kinshasa School of Public Health, University of Kinshasa
(4)
Faculty of Medicine, University of Kinshasa Hospital

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Copyright

© The Author(s). 2016

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