| Literature DB >> 33149225 |
Caian L Vinhaes1,2,3, Rozana S Teixeira4,5, Jay A S Monteiro-Júnior4, Rafael Tibúrcio1,2,5, Juan M Cubillos-Angulo1,2,5, María B Arriaga1,2,5, Adrielle G Sabarin4, Amâncio J de Souza4, Jacqueline J Silva1,4, Isa M Lyra6, Ana Marice Ladeia4,7, Bruno B Andrade8,9,10,11,12,13.
Abstract
Sickle cell anemia (SCA) is the most common inherited hemolytic anemia worldwide. Here, we performed an exploratory study to investigate the systemic oxidative stress in children and adolescents with SCA. Additionally, we evaluated the potential impact of hydroxyurea therapy on the status of oxidative stress in a case-control study from Brazil. To do so, a panel containing 9 oxidative stress markers was measured in plasma samples from a cohort of 47 SCA cases and 40 healthy children and adolescents. Among the SCA patients, 42.5% were undertaking hydroxyurea. Multidimensional analysis was employed to describe disease phenotypes. Our results demonstrated that SCA is associated with increased levels of oxidative stress markers, suggesting the existence of an unbalanced inflammatory response in peripheral blood. Subsequent analyses revealed that hydroxyurea therapy was associated with diminished oxidative imbalance in SCA patients. Our findings reinforce the idea that SCA is associated with a substantial dysregulation of oxidative responses which may be dampened by treatment with hydroxyurea. If validated by larger prospective studies, our observations argue that reduction of oxidative stress may be a main mechanism through which hydroxyurea therapy attenuates the tissue damage and can contribute to improved clinical outcomes in SCA.Entities:
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Year: 2020 PMID: 33149225 PMCID: PMC7642412 DOI: 10.1038/s41598-020-76075-5
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Characteristics of the clinical groups.
| Parameter | Unit | Healthy control (n = 40) | SCA No HU (n = 27) | SCA HU (n = 20) | |
|---|---|---|---|---|---|
| SpO2 | % | 98 (97–98) | 93.5 (88.2–96.0) | 94.5 (93.0–97.0) | |
| BMI | Kg/m2 | 17.2 (14.8–20.2) | 17.3 (15.1–19.0) | 16.1 (14.6–17.6) | 0.34 |
| Hemoglobin | mg/dL | 12.4 (11.7–14.2) | 8.0 (7.5–8.5) | 8.0 (6.9–8.5) | |
| Hematocrit | % | 38.8 (35.5–41.7) | 22.6 (21.7–25.0) | 23.9 (22.0–27.0) | |
| MCV | fL | 84.3 (78.2–89.4) | 88.8 (80.1–92.4) | 96.9 (90.5–101.4) | |
| MCHC | pg | 33.1 (32.0–34.2) | 33.8 (30.9–35.5) | 33.9 (33.3–35.5) | 0.24 |
| Leukocytes | 109/L | 7.0 (6.2–8.0) | 13.0 (10.3–14.9) | 11.5 (9.6–15.4) | |
| Platelet | 109/L | 284.0 (248.5–338.3) | 440.0 (339.5–531.5) | 494.0 (444.0–582.0) | |
| Reticulocytes | % | 0.8 (0.7–6.1) | 5.9 (3.2–9.1) | 5.9 (2.8–11.0) | |
| AST | U/L | 22.0 (15.0–29.5) | 52.0 (40.6–69.1) | 48.0 (29.3–68.0) | |
| ALT | U/L | 15.0 (12.0–18.0) | 24.5 (16.5–34.3) | 21.0 (15.5–35.5) | |
| Total bilirubin | mg/dL | 0.48 (0.22–0.83) | 2.8 (2.4–5.0) | 3.6 (1.6–3.8) | |
| Direct bilirubin | mg/dL | 0.08 (0.04–0.24) | 0.64 (0.5–0.93) | 0.32 (0.28–0.5) | |
| Indirect bilirubin | mg/dL | 0.35 (0.2–0.5) | 2.0 (1.6–4.5) | 3.1 (1.4–3.5) | |
| Total cholesterol | mg/dL | 149.0 (128.1–174.8) | 123.5 (105.9–135.8) | 109.5 (97.4–129.0) | |
| LDL-c | mg/dL | 83.2 (74.1–92.4) | 73.1 (54.0–84.3) | 60.6 (50.9–69.0) | |
| HDL-c | mg/dL | 43.3 (37.7–56.1) | 30.4 (22.2–36.0) | 30.2 (28.3–36.9) | |
| Triglycerides | mg/dL | 67.8 (49.7–85.9) | 101.6 (86.1–139.2) | 94.5 (73.8–115.6) | |
| CRP | mg/L | 0.8 (0.22–2.0) | 2.2 (0.9–3.7) | 2.0 (1.1–8.4) |
Data represents median and interquartile range (IQR) and were compared using the Kruskal–Wallis test.
aMarkers presented significant P-value in the Mann–Whitney U test between SCA with and without hydroxyurea therapy. (appear order) SpO2 Oxygen saturation, BMI Body Mass Index, MCV Mean Corpuscular Volume, MCHC Corpuscular hemoglobin concentration, AST Aspartate aminotransferase, ALT Alanine aminotransferase, LDL-c Low density lipoprotein-cholesterol, HDL-c High density lipoprotein-cholesterol, CRP C Reactive Protein, HO-1 Heme oxygenase-1, SOD Superoxide Dismutase, GSH Glutathione, MDA Malondialdehyde, LDH Lactate dehydrogenase, VEGF Vascular endothelial growth factor, sCD14 Soluble CD14.
Figure 1Principal component analysis using oxidative stress related markers can distinguish SCA patients from the healthy controls. A PCA model was employed to test whether combination of the markers evaluated could cluster SCA patients separately from controls. A vector analysis (biplot rays) was utilized to illustrate the influence of each biochemical parameter in the distribution of the data of the PCA model.
Figure 2Sickle cell anemia is linked to a distinct profile of oxidative stress. (A) An unsupervised, two-way hierarchical cluster analysis (Ward’s method with 100 × bootstrap) was employed to depict the overall expression of plasma markers associated with oxidative stress in study population. Two major clusters of markers were observed and are highlighted in red and green boxes on the right. (B) Average fold-difference values in plasma markers for subgroups of SCA participants based on use of hydroxyurea therapy and healthy controls. Differences that reached statistical significance (Mann–Whitney U test) after adjustment for multiple comparisons (adjusted P-value < 0.05) are represented in color bars. Red bars indicate higher values whereas blue bars denote lower values in the comparison group as indicated. (Order of appearance) HO-1 Heme oxygenase-1, HU hydroxyurea, LDH Lactate dehydrogenase, sCD14 Soluble CD14, GSH Glutathione, MDA Malondialdehyde, VEGF Vascular endothelial growth factor, SOD Superoxide Dismutase.
Figure 3Hydroxyurea treatment is associated with reduced degree of oxidative perturbation in Sickle Cell Anemia. (A) (Left panel) Histograms show the single sampe degree of oxidative perturbation (DOP) according the clinical group or helthy controls as indacted. (Right panel) Violin box plots represent the distribution of the DOP score values between study groups. Values were compared using the One-Way ANOVA test with Tukey’s post test, after observing a Gausian distribution of values using the D’Agostino-Pearson test (P-value < 0.001). (B) Speraman correlation analysis was performed between the values of DOP and of indicated markers. HU hydroxyurea.
Figure 4Hydroxyurea therapy is associated with coordinated changes in relationships between oxidative stress markers in SCA. Network analysis of the biomarker correlation matrices was performed with bootstrap (100 ×). The graphs show significant correlations (P < 0.05), and the Spearman rank (rho) threshold was ± 0.5. Each node represents a different parameter. The size of each circle (node) is proportional to the number of significant correlations involving such node. Connecting lines represent the Spearman rank coefficient (rho) values. Red color infers positive correlation, whereas blue color denotes negative correlations. Color maps on the right of each network denote the number of significant correlations per parameter (node) per clinical group as indicated. Heatmaps on the right panels rank the markares in each network based on number of statistically significant correlations involving each individual marker. HO-1 Heme oxygenase-1, HU hydroxyurea, LDH Lactate dehydrogenase, sCD14 Soluble CD14, GSH Glutathione, MDA Malondialdehyde, VEGF Vascular endothelial growth factor, SOD Superoxide Dismutase.