Introduction
Sickle cell disease (SCD) is an inheritable genetic disorder of hemoglobin structure with variable clinical manifestations. Annually, about 312,000 people are born with hemoglobin SS genotype worldwide, with up to 236,000 of these in sub-Saharan Africa (1,2). Nigeria has the highest disease burden in the world (3). The prevalence of SCD across sub-Saharan Africa is between 10% and 45% (4,5).
The vascular endothelium performs endocrine, autocrine, and paracrine functions, and it is the largest organ in the body (being the one-cell-thick innermost layer lining of all blood vessels) (6). It helps to regulate vascular tone, maintain vascular homeostasis, and regulate blood flow, and it constitutes an antithrombotic surface for smooth passage of blood elements/constituents (6). Endothelial dysfunction (ED) is a known feature of SCD, which is present both in crisis and in steady state (7,8). It has been demonstrated in both children and adults with SCD (8,9), and it is more severe in patients with sickle cell anemia than in patients with sickle cell trait (10). Impaired (reduced) sonographic brachial artery flow-mediated dilation (FMD) is a recognized biomarker for ED in SCD (11). The assessment of FMD is a noninvasive approach to examining vasodilator function in vivo and has been used as a surrogate marker of vascular health. It can describe any vasodilation of an artery following an increase in luminal blood flow and internal wall shear stress (12).
We aimed at evaluating ED in SCD using sonographic brachial artery FMD, compared the FMD in patients with SCD with that of controls with HbAA genotype, and determined any possible association/relationship among the trio of ED and biomarkers of renal function along with indices of SCD severity in patients asymptomatic of renal disease. To the best of our knowledge, no study has shown the relationship between FMD and cystatin C (Cys-C) along with renal artery resistivity index (RARI).
Materials and Methods
We enrolled 44 patients with homozygous SCD (HbSS) in steady state on the basis of the criteria defined by Ballas (13) attending the hematology clinic of the local institution along with 33 age- and sex-matched controls (HbAA) in this cross-sectional comparative study. The study protocol was approved by the institutional review board, and informed written consent was obtained from all of the participants. The genotype of all of the participants had been confirmed previously by hemoglobin electrophoresis. We excluded subjects with risk factors for ED, such as hypertension, diabetes, obesity, hypercholesterolemia, stroke, and smoking. We also excluded the carrier state for thalassemia (α- and β-thalassemia traits) by considering their medical history, full blood count, and the red cell indices (MCV and MCH). None of the subjects were on hydroxyurea or nicosan.
Demographic and Clinical Characteristics
Demographic and clinical data were obtained using a structured data sheet. Systolic BP and diastolic BP were measured over the left arm brachial artery region in resting state using an analog mercury sphygmomanometer.
Laboratory Evaluation
An ELISA using quantitative competitive immunoassays was done to determine fetal hemoglobin (HbF), soluble P-selectin (sP-selectin), kidney injury molecule (KIM-1), homocysteine (HCY), and Cys-C levels according to the manufacturer’s instructions (assay kits were procured from Neobiolab, Cambridge, MA). Serum total cholesterol and LDL were assessed using cardiochek PA analyzer (PTS Diagnostics Headquarters, Indianapolis, IN). Hemoglobin concentration, platelet count, white blood cell count, peripheral capillary oxygen saturation levels, and fasting blood sugar along with serum creatinine were assayed. Creatinine assay along with Hb. conc., white blood cell, and platelet count were not done for the controls. The eGFR was done using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) creatinine equation (14).
Brachial Artery Sonographic FMD
The lead author, O. Chidiogo Chukwunweike performed the brachial artery FMD assessment on all of the subjects using a Doppler-enabled MINDRAY DC-7 ultrasound scanner (Shenzhen Mindray Bio-medical Electronics, Nanshan, Shenzhen, China) with a 7.5- to 12-MHz linear array transducer. The right brachial artery FMD protocol was the same as described previously (15,16). After a 10- to 15-minute rest at room temperature, the subjects were requested to lie supine, and their right arm was exposed and abducted to 15°C. Acoustic gel was applied proximal to the antecubital fossa, and the brachial artery was scanned in a longitudinal section 5–10 cm to get a clear view of both walls of the artery. After an optimal image was obtained, the surface of the skin was marked, and the arm was kept in the same position throughout the study. The brachial artery luminal diameter was measured as the distance between the anterior intima-lumen interface and the posterior intima-lumen interface and labeled as D1. A BP cuff was then applied to the forearm below the elbow and inflated to 50 mm Hg above the systolic BP for 5 minutes to elicit an endothelium-mediated response, and then, it was deflated after 5 minutes of cuff occlusion. The same brachial artery segment underneath the area of the skin marked was interrogated continuously for 30 seconds before and for 90 seconds after cuff deflation. The second arterial diameter (D2) was taken as the maximum diameter obtained between 60 and 90 seconds after cuff release.
All measurements were obtained during the systolic phase. The average of three measurements was used for FMD calculation.
FMD was calculated as the percentage change in diameter after reactive hyperemia relative to the baseline using the formulaTiming, room temperature, and experience of the examiner could affect the results obtained (15).
Renal Arterial Doppler Sonography
Doppler sonography of the right renal artery was done with the subject in the left lateral decubitus position to visualize the artery on greyscale imaging. Spectral Doppler of the interlobar or segmental arteries was then performed with a small sample volume (1 mm). Angle correction was not carried out because only the resistive index (RI) and pulsatility index are of interest.
Statistical analysis was done using the Statistical Package for Social Sciences software version 20 (SPSS Inc., Chicago, IL). Data normality was determined using the Kolmogorov–Smirnov test. Chi-squared test/Fisher’s exact test was used to compare proportions. An independent samples Mann–Whitney U test was used to compare the medians. An independent samples t test was used to compare the means, whereas Spearman’s Rho was used for correlational analysis. Statistical significance was set at P≤0.05.
Results
Forty-four subjects with HbSS SCD and a median age of 24.5 years old (interquartile range [IQR], 19.5–32.0 years old) were enrolled along with a control group with a median age of 24.0 years old (IQR, 21.0–27.0 years old). The subjects with SCD included 23 (52.3%) men and 21 (47.7%) women, whereas the control subjects included 17 (51.5%) men and 16 (48.5%) women. No significant difference was noted between the ages of the subjects in both groups (Table 1).
Table 1. -
Characteristics of subjects with sickle cell disease and controls
Variables |
SCD, n=44 |
Controls, n=33 |
P Value |
Age, yr |
24.5 (19.5–32.0) |
24.0 (21.0–27.0) |
0.31
a
|
Height, m |
1.6 (1.6–1.7) |
1.6 (1.5–1.7) |
0.90
a
|
Weight, kg |
49.1±10.0 |
61.3±12.3 |
<0.001
b
|
BMI, kg/m2
|
18.1 (16.8–20.4) |
21.6 (19.9–25.7) |
<0.001
a
|
SpO2, % |
95.0 (92.0–98.0) |
98.0 (96.0–98.5) |
<0.001
a
|
Hb conc., g/dl |
8.3 (7.3–8.7) |
|
|
WBC, 103/μl |
9.5 (7.3–11.7) |
|
|
Platelet, 103/μl |
295.5 (192.0–367.5) |
|
|
HbF, ng/ml |
373.3 (316.8–448.28) |
273.9 (212.2–335.7) |
<0.001
a
|
sP-selectin, ng/ml |
78.7 (68.9–84.0) |
72.7 (67.1–78.5) |
0.007
a
|
HCY, µmol/L |
16.4 (10.1–28.8) |
8.3 (5.0–19.3) |
0.008
a
|
Cys-C, mg/L |
4.8 (1.6–7.9) |
1.1 (0.5–1.6) |
<0.001
a
|
KIM-1, pg/ml |
445.0 (320.0–623.0) |
125.0 (120.0–184.0) |
<0.001
a
|
Creatinine, µmol/L |
87.5 (64.5–124.3) |
|
|
eGFRCKD-EPI, ml/min per 1.73 m2
|
87.5 (59.0–118.8) |
|
|
UACR, mg/g, n (%)
|
|
|
|
<30 |
26 (59.1) |
33 (100) |
<0.001
c
|
<30–300 |
14 (31.8) |
0 (0) |
|
>300 |
4 (9.1) |
0 (0) |
|
RARI |
0.70 (0.66–0.72) |
0.59 (0.54–0.64) |
<0.001
a
|
SCD, sickle cell disease; BMI, body mass index; SpO2, oxygen saturation; Hb conc., hemoglobin concentration; WBC, white blood cell count; HbF, hemoglobin F; sP-selectin, soluble P-selectin; HCY, homocysteine; Cys-C, cystatin C; KIM-1, kidney injury molecule-1; eGFRCKD-EPI, eGFRChronic Kidney Disease Epidemiology Collaboration; UACR, urine albumin-to-creatinine ratio; RARI, renal artery resistivity index.
aIndependent samples Mann–Whitney U test was used to compare the medians.
bIndependent samples t test was used to compare the means.
cChi-squared test/Fisher’s exact test statistic was used to compare proportions.
The median FMD of 3.44 (IQR, 0.00–7.08) in subjects with SCD was significantly lower than that of controls, which was 5.35 (IQR, 3.60–6.78; P=0.04) (Table 1). No significant sex difference was noted in the FMD among subjects with (P=0.98) and among control subjects (P=0.79).
There was significant modest negative correlation between FMD and serum Cys-C levels (r=−0.372; P=0.01) and between FMD and RARI (r=−0.307; P=0.04) (Table 2) in subjects with SCD. No significant correlation was noted between FMD and other biomarkers of SCD severity (Table 2), like HbF, sP-selectin, and HCY.
Table 2. -
Spearman correlation of percentage of flow-mediated dilation with other variables in subjects with SCD versus controls
Variables |
Subjects with SCD |
Control Subjects |
Correlation Coefficient |
P Value |
Correlation Coefficient |
P Value |
Age, yr |
0.153 |
0.32 |
0.079 |
0.31 |
Height, m |
0.117 |
0.45 |
−0.210 |
0.29 |
Weight, kg |
−0.063 |
0.68 |
−0.179 |
0.37 |
BMI, kg/m2
|
−0.088 |
0.5 |
0.014 |
0.94 |
SpO2, % |
0.127 |
0.410 |
0.147 |
0.42 |
Hb conc., g/dl |
0.125 |
0.42 |
|
|
WBC, 103/μl |
0.077 |
0.62 |
|
|
Platelet, 103/μl |
−0.182 |
0.24 |
|
|
HbF, ng/ml |
0.011 |
0.95 |
0.114 |
0.53 |
sP-selectin, ng/ml |
−0.182 |
0.24 |
0.003 |
0.99 |
HCY, µmol/L |
−0.204 |
0.18 |
−0.022 |
0.91 |
Cys-C, mg/L |
−0.372 |
0.01 |
0.020 |
0.91 |
KIM-1, pg/ml |
0.179 |
0.25 |
0.156 |
0.38 |
Creatinine, µmol/L |
−0.166 |
0.28 |
|
|
eGFRCKD-EPI, ml/min per 1.73 m2
|
0.111 |
0.47 |
|
|
UACR |
−0.074 |
0.63 |
−0.146 |
0.42 |
RARI |
−0.307 |
0.04 |
−0.017 |
0.92 |
Using an FMD cutoff of 5.35, which is the median value obtained in the control population, subjects with SCD were separated into two groups: the median Cys-C level in subjects with SCD and FMD<5.35 (4.9; IQR, 3.1–7.4) was significantly higher than that of subjects with SCD and FMD≥5.35 (1.6; IQR, 1.4–9.3) (Table 3). A significant difference was also noted in the KIM-1 values of both groups. Although RARI was slightly higher in subjects with SCD and FMD<5.35 than in those with FMD≥5.35, this was not statistically significant (Table 3).
Table 3. -
Categorization of subjects with SCD on the basis of flow-mediated dilation
Variables |
SCD FMD <5.35, n=29 |
SCD FMD ≥5.35, n=15 |
P Value |
Sex, n (%)
|
|
|
|
Men |
14 (48.3) |
9 (60.0) |
0.54
a
|
Women |
15 (51.7) |
6 (40.0) |
|
Age, yr |
24.0 (19.0–31.5) |
26.0 (21.0–32.0) |
0.64
b
|
Height, m |
1.6 (1.5–1.7) |
1.6 (1.6–1.8) |
0.10
b
|
Weight, kg |
48.5±11.1 |
50.3±7.7 |
0.59
c
|
BMI, kg/m2
|
18.1 (16.6–20.5) |
17.7 (16.8–20.2) |
0.79
b
|
SpO2, % |
94.0 (89.0–97.5) |
95.0 (93.0–98.0) |
0.18
b
|
Hb conc., g/dl |
8.1±1.3 |
8.3±1.1 |
0.50
c
|
WBC, 103/μl |
9.9±4.1 |
10.0±3.8 |
0.92
c
|
Platelet, 103/μl |
302.9±148.6 |
274.7±146.7 |
0.55
c
|
HbF, ng/ml |
383.6 (328.8–444.5) |
349.3 (260.3–472.6) |
0.42
b
|
sP-selectin, ng/ml |
79.4 (65.9–84.8) |
78.5 (76.0–82.5) |
0.92
b
|
HCY, µmol/L |
18.7 (11.9–32.7) |
14.4 (7.4–25.6) |
0.36
b
|
Cys-C, mg/L |
4.9 (3.1–7.4) |
1.6 (1.4–9.3) |
0.04
b
|
KIM-1, pg/ml |
420.0 (297.5–540.0) |
560.0 (380.0–798.0) |
0.04
b
|
Creatinine, µmol/L |
90.0 (69.0–105.5) |
78.0 (49.0–128.0) |
0.77
b
|
eGFRCKD-EPI ml/min per 1.73 m2
|
87.0 (60.5–115.0) |
92.0 (58.0–146.0) |
0.69
b
|
RARI |
0.70 (0.67–0.73) |
0.69 (0.62–0.71) |
0.16
b
|
FMD, flow-mediated dilation.
aChi-squared test/Fisher’s exact test statistic was used to compare proportions.
bIndependent samples Mann–Whitney U test was used to compare the median.
cIndependent samples t test was used to compare the means.
Among subjects with SCD and FMD<5.35, serum Cys-C levels were significantly higher in those with urine albumin-to-creatinine ratio (UACR) >300 mg/g (13.4; IQR, 1.6–13.4) than in those with UACR=30–300 mg/g (6.4; IQR, 5.6–10.5) and those with UACR<30 mg/g in that order (3.4; IQR, 2.1–5.0) (Figure 1) with P=0.006. In this subgroup, there was significant correlation between FMD and UACR (r=0.576; P=0.001), between FMD and serum creatinine levels (r=0.418; P=0.02), between FMD and eGFRCKD-EPI levels (17) (r=0.430; P=0.02), and between FMD and serum sP-selectin levels (r=0.389; P=0.04) (Table 4). However, in subjects with FMD≥5.35, there was no significant difference in serum Cys-C levels on the basis of their UACR values (Figure 1) (P=0.53). In addition, there was no significant correlation between FMD and UACR, serum creatinine levels, eGFRCKD-EPI, or sP-selectin (Table 4).
Figure 1.: Clustered box plot showing the distribution of cystatin C (Cys-C) levels in subjects with sickle cell disease (SCD) on the basis of the flow-mediated dilation (FMD) category and the urine albumin-to-creatinine ratio (UACR) category. Higher levels of Cys-C were shown in those with FMD <5.35 in the 3 UACR categories.
Table 4. -
Spearman correlation of Cys-C with other variables in the two groups of subjects with SCD
Groups |
UACR, mg/g |
Creatinine, µmol/L |
GFR, ml/min per 1.73 m2
|
sP-selectin, ng/ml |
RARI |
KIM-1, pg/ml |
Subjects with FMD<5.35
|
|
|
|
|
|
|
Spearman’s Rho |
0.576 |
0.418 |
0.430 |
0.389 |
0.129 |
0.032 |
P value |
0.001 |
0.02 |
0.02 |
0.04 |
0.51 |
0.87 |
Subjects with FMD≥5.35
|
|
|
|
|
|
|
Spearman’s Rho |
−0.232 |
−0.268 |
0.352 |
−0.396 |
−0.059 |
0.566 |
P value |
0.41 |
0.34 |
0.20 |
0.14 |
0.83 |
0.03 |
No significant correlation was observed between Cys-C and RARI in both subjects with FMD<5.35 and those with FMD≥5.35 (Table 4).
Discussion
ED has been implicated in the chronic arterial vasculopathy seen in patients with SCD, which is said to be responsible for diverse multiorgan pathologies (18). Ultrasonography has proven to be useful in assessing vasculopathic changes of the cerebral arteries (19,20), renal arteries (21,22), and femoral arteries (23) in SCD. In contrast to these arteries, which reflect changes to localized regions of the body, FMD of the brachial artery has the advantage of giving an overview of the overall vascular health of the body.
Several possible etiologies have been proposed for ED in SCD, including abnormal shear-stress–mediated vasodilation (24), adhesion, and interaction between sickled red blood cells (SRBCs) and endothelial cells; SRBC membrane stiffness; hypoxia; nitric oxide deficiency; blood hyperviscosity; and renal function (10,25262728–29).
FMD, from this study, was significantly lower in patients with SCD than in controls. This corroborates with the findings in Indians (6,10,30). The mean ages of the sample populations were similar to this study (25.39±6.14 years old; sample size =44). In the study by Raghuwanshi and Raghuvanshi (30), men =24.41±6.59 years old, and women =25.00±7.56 years old (sample size =25). In the study by Zawar et al. (10), mean age was 23.15±5.27 years old (sample size =37), and in the study by Al-Janabi et al. (6), mean age was27.0±8.9 years old (sample size =30). However, Hadeed et al. (9) in France studied 30 younger children with SCD (mean age of 12.3±4.5 years old) and found no significant difference in FMD between the patients with SCD and age- and sex-matched controls, concluding that manifestations of ED may be more evident in life as the disease progresses. However, their finding was at variance with that of an earlier French study (8) in children (mean age =10.4±3.3 years old; sample size =21), which reported that FMD was significantly lower in children with sickle cell anemia than in controls and that it did not correlate with age (8). Hadeed et al. (9) also reported, as we found in our study, no correlation between FMD and age. Given the mean age in all of these studies, it is conceivable to surmise that increasing age might play a role in the advent of ED in SCD, although further studies designed purposely to address that question are desirable.
Regarding the relationship among FMD, RARI, and biochemical parameters of renal function, we observed a statistically significant negative correlation between FMD and Cys-C along with RARI. Furthermore, Cys-C was significantly higher in subjects with SCD and FMD<5.35 than in those with FMD≥5.35. These findings suggest that patients with SCD and impaired FMD are more likely to have impaired renal function, buttressing similar observations by Tharaux (31) and Ataga et al. (29). Albuminuria, an early marker of renal injury, which was used by Ataga et al. (29), has several causes other than impaired renal function and may not be a reliable marker of renal function compared with the use of Cys-C, which was used in our study. Ataga et al. (29) examined the FMD in 23 subjects with SCD and varying degrees of albuminuria, and they found that UACR and serum endothelin-1 levels were inversely correlated with FMD. They concluded that their study established an association of albuminuria with ED in SCD and that elevated serum endothelin-1, by mediating ED, may be contributory to SCD-related glomerulopathy (29). We noted a strong positive correlation between UACR and serum Cys-C in subjects with FMD<5.35 and none in those with FMD≥5.35. To the best of our knowledge, our study is the first to report a significant relationship between FMD and Cys-C along with RARI in SCD. This finding may imply that, because biomarkers of renal function correlate with FMD in SCD, whereas other biomarkers of SCD disease severity do not, monitoring and management of renal function will be critical in SCD to preserve FMD and prevent ED. Although RARI is a proven tool for evaluating various renal diseases (3233–34), it should also be noted that RARI is also an indicator of cardiovascular outcome (35). In a study by Ikee et al (36), biochemical and histopathologic parameters showed statistically significant correlations with RI. However, stepwise multiple regression analysis showed that only atherosclerosis was chosen as an independent risk factor for increased RI. The consistent renal Doppler finding in SCD across the board has been a statistically significant elevated intrarenal arteries RI above those of HbAA controls, with a reported a sensitivity of 100% and a specificity of 66.7% for RI>0.70 in detecting increased resistance within the intrarenal arteries of patients with HbSS (21,37).
Our study did not demonstrate any relationship between serum creatinine, a biomarker of renal function, and FMD. The discordance in the relationship between Cys-C and creatinine with FMD, relating to glomerular filtration, may be because, although Cys-C is freely filtered by the glomerular membrane, it is neither reabsorbed nor secreted in the kidney tubular system, unlike creatinine (38). Similarly, no relationship was noted between eGFR and FMD. These findings may be because serum creatinine is less sensitive to renal function derangement than serum Cys-C (39). Additionally, Coll et al. (40) noted that serum creatinine started to increase above normal values when GFR was 75 ml/min per 1.73 m2 in contrast to serum Cys-C, which started to rise at a higher GFR value of 88 ml/min per 1.73 m2. In this study, the median eGFR was 87 ml/min per 1.73 m2.
KIM-1 is released by proximal tubular cells in response to acute ischemic or hypoxic injury to the kidney (41). In this study, it was significantly higher in the group with FMD≥5.35 than in those with FMD<5.35. This might reflect acute ischemic (or hypoxic) kidney injury that predates the more chronic ED.
Hypoxia, resulting from chronic anemia, in SCD has also been shown to be a marker of disease severity (42,43). Hemoglobin concentration, however, did not show any significant correlation with FMD (Table 2).
As renal impairment worsens, the prevalence of anemia increases, which affects nearly all patients with stage 5 CKD (44). Erythropoietin, which is produced by the kidneys and responsible for stimulation of erythropoiesis, is decreased in CKD and thus, accountable for anemia (Figure 2) (45). Sherwood et al. (46) confirmed that patients with SCD had reduced erythropoietin levels in comparison with a control population. Tissue ischemia and infarction resulting from vascular occlusion in SCD are primarily due to the microvascular obstruction by SRBC, although vasculopathic changes in larger vessels are also known to affect the kidneys (Figure 2) (23,47,48).
Figure 2.: A chart showing the relationship between renal impairment and sickle cell disease pathophysiologic processes.
Circulating microparticles found in patients with end stage renal failure have been associated with ED, which is a significant determinant of cardiovascular risk (49). Likewise, ED has been established in our study and others to be associated with SCD as a result of the endothelial damage and intima hyperplasia (6,10,47). As the disease progresses in SCD and ED worsens along with anemia, renal function depreciates, which further compounds on the degree of endothelial function in a vicious cycle (Figure 2).
Vasculopathy in SCD has been well documented, especially regarding the cerebral arteries. Because SCD, through its complex pathophysiologic processes, results in arterio-occlusive disease, which could result in renal failure due to ischemia, renal failure could also, in addition, contribute to the compromised blood flow by compromising substantial artery compliance (Figure 2) (50).
Other biomarkers of disease severity in subjects with SCD (Table 2) did not show any significant relationship with FMD. HbF is the most potent modulator of the clinical and hematologic features in SCD. Higher HbF levels were associated with a reduced rate of acute painful episodes and fewer leg ulcers along with reduced SCD severity (51). Endothelial sP-selectin plays a crucial role in leukocyte recruitment as well as the adhesion of SRBC to the endothelium, ultimately leading to an impairment of microvascular circulation involved in the development of painful vaso-occlusion (5253–54). HCY, which is elevated in SCD in this study (Table 1) and other studies (55), is a strong risk factor for atherosclerotic disease in the peripheral arteries along with arterial thromboembolism (56). HbF, sP-selectin, and HCY showed no correlation with FMD (Table 2).
Only subjects with homozygous SCD were recruited in this study in steady state. Further studies in subjects with heterozygous SCD and also, in subjects with SCD in vaso-occlusive crisis would add to the body of knowledge regarding FMD in the disease.
In conclusion, brachial artery FMD is an essential test in the management of patients with SCD for noninvasive assessment of the vascular endothelium status. There is a relationship between FMD, RARI, and Cys-C in patients with SCD such that impairment of FMD could also be a proxy marker for the onset of renal impairment in this group of patients. Even though our findings show relationships rather than causation, we believe that they are still a step forward in the ongoing quest to unravel the mysteries of this genetic disease. Determining the exact age at which FMD impairment sets in children with SCD could be the subject of a future study.
Disclosures
A. Aderibigbe, O. Ayoola, R. Bolarinwa, B. Idowu, and C. Onwuka have nothing to disclose.
Funding
We acknowledge the management of the Obafemi Awolowo University Teaching Hospital, Ile-Ife, Osun State, Nigeria, for partly funding this project.
Author Contributions
O. Ayoola conceptualized the study and was responsible for the investigation, methodology, and project administration; O. Ayoola, R. Bolarinwa, B. Idowu, and C. Onwuka were responsible for writing the original manuscript, and reviewed and edited the manuscript; R. Bolarinwa was responsible for investigation and methodology; C. Onwuka was responsible for the formal analysis; and A. Aderibigbe reviewed and edited the manuscript.
References
1. Saraf SL, Molokie RE, Nouraie M, Sable CA, Luchtman-Jones L, Ensing GJ, Campbell AD, Rana SR, Niu XM, Machado RF, Gladwin MT, Gordeuk VR: Differences in the clinical and genotypic presentation of sickle cell disease around the world. Paediatr Respir Rev 15: 4–12, 2014
2. Weatherall DJ, Clegg JB: Inherited haemoglobin disorders: An increasing global health problem. Bull World Health Organ 79: 704–712, 2001
3. Aloni MN, Ngiyulu RM, Gini-Ehungu JL, Nsibu CN, Ekila MB, Lepira FB, Nseka NM:
Renal function in children suffering from sickle cell disease: Challenge of early detection in highly resource-scarce settings. PLoS One 9: e96561, 2014
4. Mulumba LL, Wilson L: Sickle cell disease among children in Africa: An integrative literature review and global recommendations. Int J Afr Nurs Sci 3: 56–64, 2015
5. Piel FB, Patil AP, Howes RE, Nyangiri OA, Gething PW, Dewi M, Temperley WH, Williams TN, Weatherall DJ, Hay SI: Global epidemiology of sickle haemoglobin in neonates: A contemporary geostatistical model-based map and population estimates. Lancet 381: 142–151, 2013
6. Al-Janabi HO, Al-Saadi WI, Hamdani FB, Al-Tameemi WF:
Brachial artery diameter as a predictor of
endothelial dysfunction in sickle cell disease. Iraqi J Med Sci 14: 351–358, 2016
7. Blum A, Yeganeh S, Peleg A, Vigder F, Kryuger K, Khatib A, Khazim K, Dauerman H: Endothelial function in patients with sickle cell anemia during and after sickle cell crises. J Thromb Thrombolysis 19: 83–86, 2005
8. de Montalembert M, Aggoun Y, Niakate A, Szezepanski I, Bonnet D: Endothelial-dependent vasodilation is impaired in children with sickle cell disease. Haematologica 92: 1709–1710, 2007
9. Hadeed K, Hascoet S, Castex MP, Munzer C, Acar P, Dulac Y: Endothelial function and vascular properties in children with sickle cell disease. Echocardiography 32: 1285–1290, 2015
10. Zawar SD, Vyawahare MA, Nerkar M, Jawahirani AR: Non-invasive detection of
endothelial dysfunction in sickle cell disease by Doppler ultrasonography. J Assoc Physicians India 53: 677–680, 2005
11. Rees DC, Gibson JS:
Biomarkers in sickle cell disease. Br J Haematol 156: 433–445, 2011
12. Thijssen DH, Black MA, Pyke KE, Padilla J, Atkinson G, Harris RA, Parker B, Widlansky ME, Tschakovsky ME, Green DJ: Assessment of flow-mediated dilation in humans: A methodological and physiological guideline. Am J Physiol Heart Circ Physiol 300: H2–H12, 2011
13. Ballas SK: More definitions in sickle cell disease: Steady state v base line data. Am J Hematol 87: 338, 2012
14. Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, Kusek JW, Manzi J, Van Lente F, Zhang YL, Coresh J, Levey AS; CKD-EPI Investigators: Estimating glomerular filtration rate from serum
creatinine and
cystatin C. N Engl J Med 367: 20–29, 2012
15. Corretti MC, Anderson TJ, Benjamin EJ, Celermajer D, Charbonneau F, Creager MA, Deanfield J, Drexler H, Gerhard-Herman M, Herrington D, Vallance P, Vita J, Vogel R; International
Brachial Artery Reactivity Task Force: Guidelines for the ultrasound assessment of endothelial-dependent flow-mediated vasodilation of the
brachial artery: A report of the International
Brachial Artery Reactivity Task Force. J Am Coll Cardiol 39: 257–265, 2002
16. Bots ML, Westerink J, Rabelink TJ, de Koning EJ: Assessment of flow-mediated vasodilatation (FMD) of the
brachial artery: Effects of technical aspects of the FMD measurement on the FMD response. Eur Heart J 26: 363–368, 2005
17. Levey AS, Stevens LA: Estimating GFR using the CKD Epidemiology Collaboration (CKD-EPI)
creatinine equation: More accurate GFR estimates, lower CKD prevalence estimates, and better risk predictions. Am J Kidney Dis 55: 622–627, 2010
18. Hebbel RP, Vercellotti G, Nath KA: A systems biology consideration of the vasculopathy of sickle cell anemia: The need for multi-modality chemo-prophylaxsis. Cardiovasc Hematol Disord Drug Targets 9: 271–292, 2009
19. Adams R, McKie V, Nichols F, Carl E, Zhang D-L, McKie K, Figueroa R, Litaker M, Thompson W, Hess D: The use of transcranial ultrasonography to predict stroke in sickle cell disease. N Engl J Med 326: 605–610, 1992
20. Adams RJ, McKie VC, Carl EM, Nichols FT, Perry R, Brock K, McKie K, Figueroa R, Litaker M, Weiner S, Brambilla D: Long-term stroke risk in children with sickle cell disease screened with transcranial Doppler. Ann Neurol 42: 699–704, 1997
21. Taori KB, Chaudhary RS, Attarde V, Dhakate S, Sheorain V, Nimbalkar P, Wasnik PN: Renal Doppler indices in sickle cell disease: Early radiologic predictors of renovascular changes. AJR Am J Roentgenol 191: 239–242, 2008
22. Aikimbaev KS, Oğuz M, Güvenç B, Başlamişli F, Koçak R: Spectral pulsed Doppler sonography of renal vascular resistance in sickle cell disease: Clinical implications. Br J Radiol 69: 1125–1129, 1996
23. Ayoola OO, Bolarinwa RA, Onakpoya UU, Adedeji TA, Onwuka CC, Idowu BM: Intima-media thickness of the common femoral artery as a marker of leg ulceration in sickle cell disease patients. Blood Adv 2: 3112–3117, 2018
24. Belhassen L, Pelle G, Sediame S, Bachir D, Carville C, Bucherer C, Lacombe C, Galacteros F, Adnot S:
Endothelial dysfunction in patients with sickle cell disease is related to selective impairment of shear stress-mediated vasodilation. Blood 97: 1584–1589, 2001
25. Mosseri M, Bartlett-Pandite AN, Wenc K, Isner JM, Weinstein R: Inhibition of endothelium-dependent vasorelaxation by sickle erythrocytes. Am Heart J 126: 338–346, 1993
26. Aslan M, Ryan TM, Adler B, Townes TM, Parks DA, Thompson JA, Tousson A, Gladwin MT, Patel RP, Tarpey MM, Batinic-Haberle I, White CR, Freeman BA: Oxygen radical inhibition of nitric oxide-dependent vascular function in sickle cell disease. Proc Natl Acad Sci U S A 98: 15215–15220, 2001
27. Eberhardt RT, McMahon L, Duffy SJ, Steinberg MH, Perrine SP, Loscalzo J, Coffman JD, Vita JA: Sickle cell anemia is associated with reduced Nitric Oxide bioactivity in peripheral conduit and resistance vessels. Am J Hematol 74: 104–111, 2003
28. Akinsheye I, Klings ES: Sickle cell anemia and vascular dysfunction: The nitric oxide connection. J Cell Physiol 224: 620–625, 2010
29. Ataga KI, Derebail VK, Caughey M, Elsherif L, Shen JH, Jones SK, Maitra P, Pollock DM, Cai J, Archer DR, Hinderliter AL: Albuminuria is associated with
endothelial dysfunction and elevated plasma endothelin-1 in sickle cell anemia. PLoS One 11: e0162652, 2016
30. Raghuwanshi PK, Raghuvanshi SS: Vascular
endothelial dysfunction in sickle cell disease by
brachial artery flow mediated dilatation. Asian J Med Sci 5: 105–107, 2014
31. Tharaux PL: Endothelin in renal injury due to sickle cell disease. Contrib Nephrol 172: 185–199, 2011
32. Apoku IN, Ayoola OO, Salako AA, Idowu BM: Ultrasound evaluation of obstructive uropathy and its hemodynamic responses in southwest Nigeria. Int Braz J Urol 41: 556–561, 2015
33. Ogunmoroti OA, Ayoola OO, Makinde ON, Idowu BM: Maternal renal artery Doppler sonographic changes in pregnancy-induced hypertension in South West Nigeria. Niger Med J 56: 190–193, 2015
34. Abidoye IA, Ayoola OO, Idowu BM, Aderibigbe AS, Loto OM: Uterine artery Doppler velocimetry in hypertensive disorder of pregnancy in Nigeria. J Ultrason 17: 253–258, 2017
35. Ponte B, Pruijm M, Ackermann D, Vuistiner P, Eisenberger U, Guessous I, Rousson V, Mohaupt MG, Alwan H, Ehret G, Pechere-Bertschi A, Paccaud F, Staessen JA, Vogt B, Burnier M, Martin PY, Bochud M: Reference values and factors associated with renal resistive index in a family-based population study. Hypertension 63: 136–142, 2014
36. Ikee R, Kobayashi S, Hemmi N, Imakiire T, Kikuchi Y, Moriya H, Suzuki S, Miura S: Correlation between the resistive index by Doppler ultrasound and kidney function and histology. Am J Kidney Dis 46: 603–609, 2005
37. Shogbesan GA, Famurewa OC, Ayoola OO, Bolarinwa RA: Evaluation of renal artery Resistive and Pulsatility Index in steady state SCD patients and controls. West Afr J Ultrasound 18: 30–35, 2017
38. Cheuiche AV, Queiroz M, Azeredo-da-Silva ALF, Silveiro SP: Performance of
cystatin C-based equations for estimation of glomerular filtration rate in diabetes patients: A prisma-compliant systematic review and meta-analysis. Sci Rep 9: 1418, 2019
39. Dharnidharka VR, Kwon C, Stevens G: Serum
cystatin C is superior to serum
creatinine as a marker of kidney function: A meta-analysis. Am J Kidney Dis 40: 221–226, 2002
40. Coll E, Botey A, Alvarez L, Poch E, Quintó L, Saurina A, Vera M, Piera C, Darnell A: Serum
cystatin C as a new marker for noninvasive estimation of glomerular filtration rate and as a marker for early renal impairment. Am J Kidney Dis 36: 29–34, 2000
41. Han WK, Bailly V, Abichandani R, Thadhani R, Bonventre JV: Kidney Injury Molecule-1 (KIM-1): A novel biomarker for human renal proximal tubule injury. Kidney Int 62: 237–244, 2002
42. Hijmans CT, Grootenhuis MA, Oosterlaan J, Heijboer H, Peters M, Fijnvandraat K: Neurocognitive deficits in children with sickle cell disease are associated with the severity of anemia. Pediatr Blood Cancer 57: 297–302, 2011
43. Darbari DS, Wang Z, Kwak M, Hildesheim M, Nichols J, Allen D, Seamon C, Peters-Lawrence M, Conrey A, Hall MK, Kato GJ, Taylor JG 6th: Severe painful vaso-occlusive crises and mortality in a contemporary adult sickle cell anemia cohort study. PLoS One 8: e79923, 2013
44. KDOQI; National Kidney Foundation: KDOQI clinical practice guidelines and clinical practice recommendations for anemia in chronic kidney disease. Am J Kidney Dis 47[Suppl 3]: S11–S145, 2006
45. Erslev A: Humoral regulation of red cell production. Blood 8: 349–357, 1953
46. Sherwood JB, Goldwasser E, Chilcote R, Carmichael LD, Nagel RL: Sickle cell anemia patients have low erythropoietin levels for their degree of anemia. Blood 67: 46–49, 1986
47. Francis RB: Large-vessel occlusion in sickle cell disease: Pathogenesis, clinical consequences, and therapeutic implications. Med Hypotheses 35: 88–95, 1991
48. Manwani D, Frenette PS: Vaso-occlusion in sickle cell disease: Pathophysiology and novel targeted therapies. Blood 122: 3892–3898, 2013
49. Amabile N, Guérin AP, Leroyer A, Mallat Z, Nguyen C, Boddaert J, London GM, Tedgui A, Boulanger CM: Circulating endothelial microparticles are associated with vascular dysfunction in patients with end-stage renal failure. J Am Soc Nephrol 16: 3381–3388, 2005
50. London GM, Marchais SJ, Safar ME, Genest AF, Guerin AP, Metivier F, Chedid K, London AM: Aortic and large artery compliance in end-stage renal failure. Kidney Int 37: 137–142, 1990
51. Akinsheye I, Alsultan A, Solovieff N, Ngo D, Baldwin CT, Sebastiani P, Chui DHK, Steinberg MH:
Fetal hemoglobin in sickle cell anemia. Blood 118: 19–27, 2011
52. Gutsaeva DR, Parkerson JB, Yerigenahally SD, Kurz JC, Schaub RG, Ikuta T, Head CA: Inhibition of cell adhesion by anti-
P-selectin aptamer: A new potential therapeutic agent for sickle cell disease. Blood 117: 727–735, 2011
53. Embury SH, Matsui NM, Ramanujam S, Mayadas TN, Noguchi CT, Diwan BA, Mohandas N, Cheung AT: The contribution of endothelial cell
P-selectin to the microvascular flow of mouse sickle erythrocytes in vivo. Blood 104: 3378–3385, 2004
54. Matsui NM, Borsig L, Rosen SD, Yaghmai M, Varki A, Embury SH:
P-selectin mediates the adhesion of sickle erythrocytes to the endothelium. Blood 98: 1955–1962, 2001
55. Houston PE, Rana S, Sekhsaria S, Perlin E, Kim KS, Castro OL: Homocysteine in sickle cell disease: Relationship to stroke. Am J Med 103: 192–196, 1997
56. Refsum H, Ueland PM, Nygård O, Vollset SE: Homocysteine and cardiovascular disease. Annu Rev Med 49: 31–62, 1998