Silva et al. BMC Medical Genetics 2013, 14:108
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RESEARCH ARTICLE
Open Access
Genetic and biochemical markers of hydroxyurea
therapeutic response in sickle cell anemia
Danilo Grunig Humberto Silva1,4, Edis Belini Junior1, Gisele Cristine de Souza Carrocini1, Lidiane de Souza Torres1,
Octávio Ricci Júnior2, Clarisse Lopes de Castro Lobo3, Claudia Regina Bonini-Domingos1 and
Eduardo Alves de Almeida4*
Abstract
Background: Sickle cell anemia (SCA) presents a complex pathophysiology which can be affected by a number of
modifying factors, including genetic and biochemical ones. In Brazil, there have been no studies verifying
βS-haplotypes effect on oxidative stress parameters. This study evaluated βS-haplotypes and Hb F levels effects on
oxidative stress markers and their relationship with hydroxyurea (HU) treatment in SCA patients.
Methods: The studied group was composed by 28 SCA patients. Thirteen of these patients were treated with HU
and 15 of them were not. We used molecular methodology (PCR-RFLP) for hemoglobin S genotype confirmation
and haplotypes identification. Biochemical parameters were measured using spectrophotometric methods
(Thiobarbituric-acid-reactive substances and Trolox equivalent antioxidant capacity levels, catalase and GST activities)
and plasma glutathione levels by High-performance liquid chromatography coupled to electrochemical detection.
Results: We found the highest frequency of Bantu haplotype (48.2%) which was followed by Benin (32.1%). We
observed also the presence of Cameroon haplotype, rare in Brazilian population and 19.7% of atypical haplotypes.
The protective Hb F effect was confirmed in SCA patients because these patients showed an increase in Hb F levels
that resulted in a 41.3% decrease on the lipid peroxidation levels (r =−0.74, p=0.01). Other biochemical parameters
have not shown differential expression according to patient’s haplotypes. Bantu haplotype presence was related to
the highest lipid peroxidation levels in patients (p < 0,01), but it also conferred a differential response to HU
treatment, raising Hb F levels in 52.6% (p = 0.03) when compared with the group with the same molecular profile
without HU usage.
Conclusions: SCA patients with Bantu haplotype showed the worst oxidative status. However these patients also
demonstrated a better response to the treatment with HU. Such treatment seems to have presented a “haplotypedependent” pharmacological effect.
Keywords: Hemoglobin S, Beta-S-gene cluster haplotypes, Oxidative stress, Antioxidant capacity
Background
Sickle cell anemia (SCA) is a chronic and progressively debilitating medical condition featuring ongoing hemolytic
anemia and recurrent acute vaso-occlusive events [1]. It is
characterized by a clinical course highly variable, ranging
from death in early childhood [2] to a normal life span with
few complications [3]. This feature reflects the complex
pathophysiology of SCA which can be affected by a number
* Correspondence: ealmeida@ibilce.unesp.br
4
Department of Chemistry and Environmental Sciences, Sao Paulo State
University–UNESP, Sao Paulo, Brazil
Full list of author information is available at the end of the article
of modifying factors including haplotype of β-globin gene
cluster [4], coinheritance of polymorphisms associated with
clinical aspects [5,6] and treatment response [7],
hemoglobin fetal (Hb F) levels [8], chronic inflammation
and oxidative states [9,10] as well as gender [4].
There are five distinct haplotypes linked to the βS-mutation and they are known as Benin (Ben), Bantu or Central
African Republic, Senegal (Sen), Cameroon (Camer) and
Indian-Arab haplotypes. These ones are classified according
to the geographical region in which they were originally
identified [11,12]. Analysis of βS polymorphisms is of genetic and anthropologic interest, but it may also be related to
© 2013 Silva et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
Silva et al. BMC Medical Genetics 2013, 14:108
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disease severity as well as variations in drug response
[13,14]. Bantu haplotype has been associated with more severe disease outcome and a high organ damage incidence.
Benin haplotype has been associated with intermediate disease severity. On the other hand, Senegal and Indian-Arab
haplotypes have been associated with milder disease severity [13,15] due to their higher Hb F levels related to the
C → T mutation at position -158 XmnI in the Gγ-globin
gene promoter region [15].
Hydroxyurea (HU) administration seems to be the best
available treatment option for SCA patients [1,16,17]. HU
is an antineoplastic drug which its main pharmacological
action is to increase Hb F levels. It has other potentially
beneficial effects including improved nitric oxide (NO) metabolism, reduced red cell–endothelial interaction and decreased erythrocyte density [1]. Although highly effective
for most SCA patients, there is a considerable inter-patient
variability creating a broad spectrum of Hb F induction
[1,18]. HU mechanisms of action for Hb F induction remain incompletely understood. Hb F induction by HU has
been correlated to cell cycle inhibition leading to activation
of stress erythropoiesis [1,19-21]. Other studies have suggested that Hb F induction by HU is mediated more
specifically via nitric oxide-dependent transcriptional mechanisms [22,23] and cyclic nucleotides [24,25] and initial evidence for some epigenetic regulation [26].
Many studies have been carried out trying to establish
a relation between βS -haplotypes and SCA phenotype.
These haplotype-phenotype associations are not definitely established and no clear correlation has emerged
[6,27-29] to date, though. In Brazil, there have been no
studies verifying βS -haplotypes effect on oxidative stress
parameters. Therefore this work aimed at studying βS haplotype effects and Hb F levels on oxidative stress
markers and their relationship with HU treatment.
Methods
Patients
Eligible patients were 10 years or older at the beginning of
the study and they were diagnosed with SCA. They all had
access to the same medication protocol. The studied group
was composed by 28 SCA patients (11 males and 17 females; mean age: 27.7 years old; range: 10-65 years old) in
clinical follow-up in Sao Jose do Rio Preto (SP) and Rio de
Janeiro (RJ). All the patients are from the southeast region
of Brazil.
All SCA patients were screened using a questionnaire.
Pregnant, smokers or drinkers were excluded from the
study, as well as anyone who had had a stroke, pain and/or
hemolytic crisis or had received blood transfusion within
two months prior to the start of the study. The medications
used by SCA patients were previously checked and the ones
taking any other medication known to affect the parameters
analyzed (such as acetylsalicylic acid, antibiotics or
Page 2 of 9
vitamins) within 24 h of sample collection were also excluded. All subjects gave their informed consent and the
study was reviewed and ethically approved by the Data
Safety Monitoring Board (DSMB) according to Brazilian
Regulations and Ethical Committee of Sao Paulo State
University (0015.0.229.000-09).
Biological samples
Blood samples (11 mL) were collected through venipuncture
in heparinized and ethylenediamine tetraacetic acid (EDTA)
tubes. The heparinized blood (7 mL) was incubated for 20
min at 37°C and then centrifuged at 206 g for 20 min to
separate plasma for Thiobarbituric-acid-reactive substances
(TBARS) and Trolox equivalent antioxidant capacity
(TEAC) analysis. The EDTA sample fraction (4 mL) was
aliquoted: 2 mL used for the hemoglobinopathies tests,
genotypic determination and catalase (CAT) and glutathione
S-transferase (GST) enzymatic activities analysis and the
other 2 mL were submitted to centrifugation at 825 g for 10
min to obtain plasma and then were frozen at−80°C for
glutathione (GSH) levels determination.
Hemoglobin phenotypes, genotypes and βS-globin
haplotypes
Hb identification was performed using electrophoresis
on cellulose acetate pH 8.4 and agar electrophoresis at
pH 6.2. Hb fraction quantification was obtained using
high performance liquid chromatography (HPLC) by the
automated VARIANT™ equipment (Bio-Rad Laboratories,
CA, USA) [30]. Cell morphology microscopic analysis was
performed on the stained blood using May-GrünwaldGiemsa. In all patient samples, Hb S genotype was
developed by molecular analysis using PCR-RFLP. The
segment amplification that encodes βS gene was accomplished by specific primers and amplicon was
cleaved by the DdeI restriction endonuclease (New
England BioLabs, MA, USA) [31]. Beta globin haplotypes were determined through the PCR-RFLP analysis
of the following polymorphic restriction sites: γG
(Hind III), γA (Hind III), ψβ (Hinc II), 3′ψβ (Hinc II)
and 5′β (Hinf I), as previously described [32].
Biochemical analysis
Lipid peroxidation levels were assessed in heparinized
plasma using TBARS assay [33]. Antioxidant capacity
was also determined in heparinized plasma samples
according to their equivalence to Trolox (6-hydroxy2,5,7,8-tetramethychroman-2-carboxylic acid) [34]. For
total GST activity, blood samples were diluted in a 3.5
μM 2-mercaptoethanol 10 μM NADP 2.7 mM EDTA
hemolyzing solution (1:20, v/v) and then assayed using
1-chloro-2,4-dinitrobenzene (CDNB) as substrate at 340
nm. The assay was carried out in 0.2 M K-phosphate
buffer pH 6.5, 1 mM CDNB, 1 mM GSH (ε = 9.6 mM-1
Silva et al. BMC Medical Genetics 2013, 14:108
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cm-1) [35]. For CAT activity analysis, blood samples were
diluted in ultrapure water (1:50, v/v) and then 10 μL
were used to measure CAT activity, by the decrease in
absorbance at 240 nm (ε = 0.04 mM-1 cm-1) due to consumption of H2O2 (10 mM H2O2 in 1 M Tris–HCl buffer pH 8.0 containing 5 mM EDTA) [36].
GSH concentration was determined in EDTA
plasma samples using HPLC coupled to a coulometric
electrochemical detector (Coulochem III ESA, Bedford,
MA) [37]. Under these conditions, GSH clearly eluted
in ~ 6 min. GSH was extracted from the plasma samples by adding perchloric acid to the plasma sample
(10% final concentration). After vigorous stirring
and remaining 10 min on ice, the mixture was
centrifuged at 825 g for 10 min at 4°C. The extract
was then filtered through Millex syringe filter units
(0.22 μm) and directly injected into the HPLC system. The calculations were based on a calibration
curve previously constructed by injecting authentic
GSH standards into HPLC system.
Statistical analysis
Statistical analysis was performed in groups with at least
three individuals using the Statistica 9.0 software
(Statsoft Inc.). Data were tested regarding normality and
homogeneity of variances assumptions according to
Shapiro-Wilk test and Levene’s test, respectively. Groups
that met the assumptions (parametric data) were compared by applying t test or one-way ANOVA followed by
Fisher’s post hoc. Those groups that did not meet the
assumptions (non-parametric data) were compared by
Mann–Whitney test or Kruskal-Wallis followed by
Dunn’s post hoc test. In order to assess association degree between the studied variables, we used Pearson’s
correlation for parametric data and Spearman’s rank correlation for non-parametric data. In order to assess age
and gender influence on the values of oxidative stress
markers, we classified SCA patients into two age groups
(≤ 20 and > 20 years) and we applied factorial ANOVA.
Data were expressed as mean ± standard deviation and
p < 0.05 was considered statistically significant.
Table 1 Characterization of atypical βS-haplotypes alleles
Restriction sites
βS-Haplotypes
Xmn I
5′γ
G
Hind III
γ
G
Hinc II
γA
Ψβ
Hinf I
3′ψβ
5′ β
Atypical 1
-
-
-
-
-
-
Atypical 2
-
+
-
-
+
-
Atypical 3
-
-
+
-
+
-
Results
Through βS -haplotypes molecular analysis we found
nine different combinations of restriction sites, resulting
in the following specific combinations: Bantu, Benin,
Cameroon and three atypical. The atypical patterns were
classified by the numbers 1, 2 and 3, they do not fall into
any of the classifications previously reported in the
literature (Table 1).
We identified eight (28.5%) patients with haplotype
Bantu/Bantu, 10 (35.7%) Bantu/Benin, two (7.1%) Benin/
Benin, one (3.6%) Benin/Cameroon, one (3.6%) Bantu/
Atypical 1, one (3.6%) Benin/Atypical 1, one (3.6%) Benin/
Atypical 2, one (3.6%) Benin/Atypical 3 and three (10.8% )
Atypical 2/Atypical 2. From 56 chromosomes analyzed,
the allelic frequency observed was: 27 (48.2%) alleles
Bantu, 18 (32.1%) Benin, one (1.8%) Cameroon and 10
(19.7%) Atypical, from the atypical ones, two (3.6%) Atypical 1, seven (12.5%) Atypical 2 and one (1.8%) Atypical 3.
For biochemical parameters assessment, firstly we
checked whether age and gender could influence the
values of studied markers (TBARS and TEAC levels,
GST and CAT enzyme activities and plasma GSH levels)
to avoid biases. We found no statistically significant difference for any of the evaluated parameters, as shown in
Table 2.
The influence of haplotypes and HU treatment over Hb
F concentration and on biochemical markers was determined by subgroups formation - haplotype and HU use (+
HU) and haplotype without HU use (–HU). The values
and/or mean of ana\lyzed parameters according to subgroup are presented in Table 3.
Between the subgroups submitted to statistical comparisons, we assessed haplotypes effect on SCA phenotypic
Table 2 Analysis of the age and gender interference on the biochemical markers values in SCA patients
Age#
≤ 20 years n = 09
> 20 years n = 19
1452.94 ± 699.00
1577.07 ± 539.85
TEAC (mM)
1.97 ± 0.21
GST (U/mL)
1.77 ± 0.94
CAT (U/mL)
1660.80 ± 525.41
0.74 ± 0.49
TBARS (ng/mL)
GSH (μM)
Gender#
P values*
P values*
Male n = 11
Female n = 17
0.4950
1345.94 ± 413.13
1660.90 ± 655.72
0.0719
2.03 ± 0.15
0.6737
2.01 ± 0.23
2.01 ± 0.12
0.7292
1.51 ± 0.49
0.2394
1.50 ± 0.56
1.64 ± 0.72
0.3757
1912.16 ± 517.83
0.0957
1831.30 ± 634.04
1831.40 ± 461.03
0.7524
0.70 ± 0.39
0.3644
0.59 ± 0.52
0.79 ± 0.31
0.2791
*Comparisons were made by factorial ANOVA.
#
There were no significant interactions between independent variables: age and gender (p > 0.05).
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Table 3 Descriptive analysis of the βS-haplotypes interference in the phenotypic expression of SCA patients
Parameters
Hb F (%)
Haplotypes (+HU)
TBARS (ng/mL)
TEAC (mM)
GST (U/mL)
CAT (U/mL)
GSH (μM)
n
Bantu/Bantu
2
1.95
1201.18
2.17
1.26
1742.95
1.30
Bantu/Benin
6*
17.42
1066.26
2.03
1.50
2294.01
0.62
Benin/Benin
1
5.2
1616.62
2.17
1.44
2278.17
1.10
Benin/Camer
0
———
———
———
———
———
———
Bantu/Atp1
0
———
———
———
———
———
———
Benin/Atp1
1
1.8
1524.30
2.20
1.20
1531.69
0.19
Benin/Atp2
1
8.4
1012.00
2.01
2.00
1084.51
0.22
Benin/Atp3
1
7.3
1216.92
2.10
1.92
1880.28
0.88
Atp2/Atp2
1
11
1308.00
1.97
1.51
1866.20
0.37
Haplotypes (−HU)
Bantu/Bantu
6*
6.78
2284.33
1.93
2.03
1656.10
0.77
Bantu/Benin
4*
6.68
1815.50
2.09
1.27
1842.43
0.84
Benin/Benin
1
2.1
1222.00
2.09
1.65
2570.42
0.74
Benin/Camer
1
4.8
934.00
1.90
2.00
996.48
0.70
Bantu/Atp1
1
3.2
1287.00
1.95
1.18
2017.61
0.87
Benin/Atp1
0
———
———
———
———
———
———
Benin/Atp2
0
———
———
———
———
———
———
Benin/Atp3
0
———
———
———
———
———
———
Atp2/Atp2
2
7.45
1576.00
1.77
1.45
1248.24
0.32
(+HU): patients treated with HU; (−HU): patients not treated with HU; Camer: Cameroon; Atp: atypical.
*Subgroups subject to statistical comparisons.
expression markers, comparing Bantu/Bantu (–HU) with
Bantu/Benin (–HU) and we observed no statistical difference (Table 4). In order to prove the contribution of HU
use on these markers, according to haplotypes subgroups,
we compared Bantu/Benin (+HU) with Bantu/Benin
(–HU) and found an increase in Hb F levels in the treated
subgroup (p < 0.01) and consequent lipid peroxidation reduction (p = 0.03) (Table 5).
The association degree among the studied markers
showed that in patients with the same βS-haplotype (Bantu/
Benin), HU promoted an increase of 61.7% in Hb F values
Table 4 Influence of Bantu and Benin haplotypes on SCA
phenotypic expression
Modulators
Bantu/Bantu (−HU)
Bantu/Benin (−HU)
n = 06
n = 04
6.78 ± 3.60
6.67 ± 6.37
0.9731
2284.33 ± 435.50
1815.50 ± 334.80
0.1074
TEAC (mM)
1.92 ± 0.13
2.08 ± 0.18
0.1465
GST (U/mL)
2.03 ± 1.02
1.27 ± 0.63
0.2245
CAT (U/mL)
1656.10 ± 413.96
1842.42 ± 397.81
0.4993
0.77 ± 0.37
0.84 ± 0.62
0.8317
Hb F (%)
TBARS (ng/mL)
GSH (μM)
(−HU) patients not treated with HU. Mean ± standard deviation.
* Comparisons were made by Mann–Whitney test.
(Figure 1A) and a decrease of 41.3% in lipid peroxidation levels (Figure 1B), according to a negative correlation found between these markers (r =−0.74, p = 0.01)
(Figure 1C). The other evaluated biochemical parameters
showed no differential expression or association.
Bantu haplotype is associated with the worst clinical
outcomes in SCA. Therefore, to better address Bantu
haplotype influence on oxidative stress markers and HU
usage, we classified the patients into four sample groups:
Table 5 Influence of the HU use in SCA patients with the
Bantu/Benin haplotype
Modulators
Bantu/Benin (+HU)
Bantu/Benin (−HU)
n = 06
n = 04
17.41 ± 3.10
6.67 ± 4.37
0.0069#
1066.26 ± 495.09
1815.50 ± 334.80
0.0303#
TEAC (mM)
2.02 ± 0.16
2.08 ± 0.18
0.6124
GST (U/mL)
1.49 ± 0.62
1.27 ± 0.63
0.5925
CAT (U/mL)
2294.01 ± 297.29
1842.42 ± 397.81
0.0725
0.62 ± 0.37
0.84 ± 0.62
0.4981
P
values*
Hb F (%)
TBARS (ng/mL)
GSH (μM)
(−HU) patients not treated with HU. (+HU) patients treated with HU.
*Comparisons were made by Mann–Whitney test.
#
Indicates statistical difference (p < 0.05).
P
values*
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Figure 1 (See legend on next page.)
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Silva et al. BMC Medical Genetics 2013, 14:108
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(See figure on previous page.)
Figure 1 Hb F and lipid peroxidation levels in SCA patients with Bantu/Benin haplotype. A) Hb F levels were about 2.6 times higher in
patients under HU treatment compared to those not treated (p = 0.0069; Mann–Whitney test). B) Lipid peroxidation levels showed 1.7 times
lower in those patients on HU usage (p = 0.0303; Mann–Whitney test). C) Negative linear correlation between Hb F and lipid peroxidation levels
(r = −0.74; p = 0.0156; Spearman’s rank test).
on SCA patients hematological and clinical features
[13,27,38-41], but studies associating haplotypes with
oxidative stress markers are scarce. This study, to our
knowledge, yields a unique opportunity in which both
genetic factor (βS -haplotypes) and oxidative stress
markers were simultaneously measured and correlated
with Hb F levels and HU use in Brazilian SCA patients.
We found a higher frequency of Bantu haplotype
followed by Benin. This distribution of βS-haplotypes
was similar to other studies with Brazilian SCA patients
from southeast region [39-44]. The chromosomes majority with βS gene has one of the five common haplotypes,
although in every large series of SCA patients there is a
minority of chromosomes (5 ± 10%) usually referred as
“atypical” haplotypes [45]. We found 19.7% of atypical
haplotypes, higher frequency than it is expected. None
of the identified haplotypes during the study have had
presence of XmnI polymorphic site, neither those haplotypes already described in the literature nor the atypical
ones. Therefore, other genetic polymorphisms not
targeted in this study should be involved in high Hb F
levels obtained in SCA patients not treated with HU.
Bantu/Benin haplotype was the most frequent. Therefore in these patients, we confirmed Hb F protective effect provided by HU use. Once increasing Hb F levels
resulted in a decrease of the lipid peroxidation levels in
accordance with our recent publications [44,46]. The
protective effect is due to the increase in Hb F concentration that either inhibits or retards Hb S polymerisation [47], leading to a decreased intravascular sickling
and an increasing nitric oxide bioavailability [48]. These
alterations result in a decreased oxidative stress with
markedly decreased lipid peroxidation and increased
activity⁄levels of antioxidants (SOD, GPx, catalase, and
Group I. Patients with Bantu haplotype at least one
chromosome without HU treatment. The haplotypes
that comprised this group were Bantu/Bantu, Bantu/
Benin and Bantu/Atp1;
Group II. Patients with Bantu haplotype at least one
chromosome and under HU treatment. The
haplotypes were Bantu/Bantu and Bantu/Benin;
Group III. Patients without the Bantu haplotype a HU
usage. This group was composed by haplotypes
Benin/Benin, Benin/Camer, Atp2/Atp2;
Group IV. Patients without Bantu haplotype in any
chromosome, but under HU usage. The haplotypes
were Benin/Benin, Benin/Camer, Atp2/Atp2.
Table 6 summarizes obtained results from the
comparisons between such groups for all evaluated
parameters.
The haplotype sample group analysis also showed significant differences only in the Hb F and lipid peroxidation
markers. Bantu haplotype presence was related to the
highest lipid peroxidation levels in patients (p < 0.01)
(Figure 2A), but also, it conferred a differential response to
HU treatment, raising Hb F levels in 52.6% (p = 0.03) when
compared with the group with same molecular profile not
treated (Group I). This treatment response was not observed in patients without Bantu haplotype (Figure 2B).
Discussion
Although SCA is one of the first disorders to be clearly
defined at molecular level, genetic understanding of the
basis for disease expression variability is still unclear
[38]. Since βS -haplotypes discovery as genetic modulators of phenotypic expression in SCA, several studies
have been developed to determine haplotypes effect
Table 6 Relationship between the Bantu haplotype and HU treatment on SCA patients
Sample groups
Group I
Group II
n = 11
Hb F (%)
Group III
n = 08
a
n = 04
b
6.42 ± 4.45
5.45 ± 5.42
0.0388
1099.99 ± 455.70
1327.00 ± 463.9
1335.57 ± 241.94b
0.0009
TEAC (mM)
1.99 ± 0.16
2.06 ± 0.15
1.88 ± 0.27
2.09 ± 0.10
0.2296
GST (U/mL)
1.68 ± 0.90
1.44 ± 0.55
1.64 ± 0.53
1.61 ± 0.34
0.8974
CAT (U/mL)
1756.72 ± 385.98
2156.25 ± 540.32
1515.85 ± 759.98
1728.17 ± 446.54
0.1758
0.81 ± 0.44
0.79 ± 0.45
0.52 ± 0.24
0.55 ± 0.41
0.4987
GSH (μM)
b
6.74 ± 3.46a
2023.18 ± 490.74
TBARS (ng/mL)
b
P
values*
n = 05
a
13.55 ± 7.66
a
Gruop IV
*Different letters indicate statistical differences (ANOVA followed by Fisher’s post hoc test).
Group I: Bantu (−HU), Group II: Bantu (+ HU), Group III: any haplotype except Bantu (−HU), Group IV: any haplotype except Bantu (+ HU).
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Figure 2 Analysis of Bantu haplotype effect and HU use on SCA phenotypic expression modulators. A) Lipid peroxidation showed its
highest mean value in Group I compared to the others groups. B) Higher Hb F levels in patients of Group II compared to group with the same
molecular profile not treated (Group I) and to the others evaluated groups. *Indicates statistical difference (ANOVA followed by Fisher’s post hoc
test). Group I: Bantu (−HU), Group II: Bantu (+ HU), Group III: any haplotype except Bantu (−HU), Group IV: any haplotype except Bantu (+ HU).
GSH) [48]. This antioxidant response was not observed
though, according to the haplotype profile.
Bantu haplotype presence was related to the highest
lipid peroxidation levels in patients, corroborating with
the results obtained by Rusanova et al. [49]. The authors
showed that SCA patients with Senegal and Indian-Arab
alleles had the mild clinical outcomes associated with
low oxidative status, whereas high oxidative stress was
related to Benin and Bantu haplotypes, consequent severe phenotypes. On the other evaluated parameters
(TEAC levels, CAT and GST activities and plasma GSH
levels), we have not observed any significant haplotype
influence. Thus, oxidative stress biomarkers analysis may
be important in clinical condition evaluation of SCA patients, furthermore in therapeutic response monitoring
among SCA patients under HU use.
Currently, many researches aimed at identifying interindividual genetic variations, underlying different pharmacological responses to drug use [50]. In SCA, this paradigm
is being applied to elucidate vascular complications pathogenesis and to develop individualized therapies [6]. However, there is no stated relationship in the literature
between differential response to HU treatment according to
βS-haplotypes in SCA patients. Vicari et al. [51] showed, in
contrast to previous reports [52-54], a significant increase
in Hb F levels in SCA patients with Bantu haplotype after
HU use, similar HU pharmacological response that we
obtained in our studied group. As it is estimated that 40%
of the patients do not respond to HU treatment [55] and
Bantu haplotype is the most frequent in Brazilian SCA patients, this HU differential response should be carefully
interpreted, according to Vicari et al. [51].
We hypothesized that this “haplotype-dependent”
pharmacological effect of HU is due to the “highest
stress erythropoiesis stimulation” in SCA patients with
Bantu haplotype. The presence of Bantu haplotype is associated with a hyperoxidative status and consequent
higher hemolytic levels and lower Hb concentrations,
characteristics known to increase the circulating erythropoietin concentrations, which in turn stimulates erythropoiesis [56-58]. Based on HU cytotoxic effect which is
beneficial in many ways; it targets rapidly dividing cells,
which in red cells tend to be those ones with a high Hb
S levels and favors the production of red cells with a
high Hb F levels, as these levels tend to arise from red
cells that divide less rapidly [59]. This way, SCA patients
with Bantu haplotype under HU use would have higher
erythropoiesis stimulation, favoring production of red
cells with a high Hb F levels. This hypothesis agrees with
the observations from Gordeuk et al. [60]. The authors
confirmed by multiple linear regression that lower
hemoglobin concentration was correlated with higher
erythropoietin concentration and higher Hb F percentage among sickle cell disease patients. Therefore, even
with a small sample size, our results have left perspectives for further studies to better address this hypothesis.
Conclusion
We provided evidence that Bantu haplotype presence
seems to be an important predictor factor of oxidative
stress and of differential response to HU use in SCA patients. We confirmed a hyperoxidative status among
SCA patients. This status should be considered, at least
partially, on clinical manifestations variety of these patients. Thus, the use of oxidative stress biomarkers may
be important in the evaluation of clinical condition of
SCA patients, furthermore in therapeutic response monitoring among SCA patients under HU use. We also suggest that the development of therapies to improve the
redox status would be beneficial to reduce the severity
of SCA.
Competing interests
The authors declare no competing financial or other relationship with other
people or organizations interests.
Silva et al. BMC Medical Genetics 2013, 14:108
http://www.biomedcentral.com/1471-2350/14/108
Authors’ contributions
DGHS: data design, data acquisition, data analysis, statistical analysis, data
interpretation and manuscript preparation. EBJ: technical assistance on
molecular, biochemical and statistical analysis. GCSC: technical assistance in
the standardization of molecular biology analysis. LST: technical assistance on
biochemical analysis. ORJ: data provision and critical review of manuscript.
CLCL: data provision and critical review of manuscript. CRBD: study concept
and design and critical review of manuscript. EAA: study concept and
design, guidance on standardization of the biochemical methods and critical
review of the manuscript. All authors read and approved the final
manuscript.
Acknowledgments
The authors would like to thank the following Brazilian foundations:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
(grant 409691/2006-2), Fundação de Amparo à Pesquisa do Estado de São
Paulo (FAPESP) (2006/03873-1), Coordenação de Aperfeiçoamento de Pessoal
de Nível Superior (CAPES) and the Ministry of Health (grant MS 3072/2007)
for their financial support, and Carolina Grünig Humberto da Silva for
revising the English text.
Author details
1
Department of Biology, Hemoglobin and Hematologic Genetic Diseases
Laboratory, Sao Paulo State University–UNESP, Sao Paulo, Brazil. 2Department
of Medicine, Sao Jose do Rio Preto Medical School–FAMERP, Sao Paulo,
Brazil. 3Hematological State Institute “Arthur de Siqueira Cavalcanti”–
HEMORIO, Rio de Janeiro, Brazil. 4Department of Chemistry and
Environmental Sciences, Sao Paulo State University–UNESP, Sao Paulo, Brazil.
Received: 17 April 2012 Accepted: 2 October 2013
Published: 9 October 2013
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doi:10.1186/1471-2350-14-108
Cite this article as: Silva et al.: Genetic and biochemical markers of
hydroxyurea therapeutic response in sickle cell anemia. BMC Medical
Genetics 2013 14:108.
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