ARTICLE
Auteur(s) : Swapnil Sinha1, Tabish
Qidwai1, Kanika Kanchan1, Ganga N
Jha1, Prerna Anand2, Sudhanshu S
Pati3, Sanjib Mohanty3, Saroj K
Mishra3, Prajesh K Tyagi4, Surya K
Sharma4, Shally Awasthi2, Vimala
Venkatesh2, Saman
Habib1
1Division of Molecular and Structural
Biology, Central Drug Research Institute, Lucknow, India
2King George Medical University (KGMU), Lucknow,
India
3Ispat General Hospital, Rourkela, India
4Rourkela Field Station (National Institute
of Malaria Research), Rourkela, India
accepté le 31 Juillet 2010
The epidemiology of malaria caused by Plasmodium falciparum is
highly complex, and largely depends on the intensity of disease
transmission and level of acquired immunity. The human immune
response to P. falciparum infection involves a complex interaction
between different cell types and cytokine networks. The production
of pro- and anti-inflammatory cytokines, mainly by primed
CD4+- T-cell populations and macrophages, plays an
important role in host immune-effector mechanisms. However, the
balance between pro- and anti-inflammatory cytokines and their
contribution to the development of disease severity and clinical
immunity are poorly understood.
Blood-stage malaria parasite antigens trigger the early cytokine
response and release of endogenous pyrogens including TNF, IL-1β
and IFN-γ from macrophages [1-4]. Parasite-induced, early cytokine
production is necessary for both control of parasitaemia [5] and
priming of CD4+- T-cells (T helper cells) [6].
Pro-inflammatory cytokines, such as TNF, IL-6, IFN-γ and IL-1β have
been found to be elevated during severe malaria, and are also
related to severe disease manifestations [7-11]. At low levels, TNF
produced by activated macrophages and the Th1 subset of primed
CD4+- T-cells, initiates the pyrogenic response to
malaria infection and augments parasite clearance by circulating
monocytes [12]. IFN-γ, the production of which by natural killer
(NK) and Th1 cells, is stimulated by IL-12, triggers an effective
innate immune response by promoting phagocytosis of parasitized
erythrocytes by NK cells. IFN-γ also activates macrophages to
release other inflammatory cytokines, including IL-1β and IL-6,
which contribute to downstream, anti-parasitic, immune responses
[13, 14]. Both TNF and IFN-γ may act synergistically to resolve
malaria infection by assisting in effective clearance and killing
of the parasite. However, elevated levels of pro-inflammatory
cytokines, including both TNF and IFN-γ have been associated with
severe disease manifestations [9, 15]. Excessive TNF production may
lead to severe anemia, acute respiratory distress and upregulation
of endothelial adhesion molecule expression resulting in cerebral,
malaria-related complications [9, 16, 17]. Studies in mouse models
have implicated high levels of TNF in the impairment of dendritic
cell function, contributing to the immune suppression associated
with malaria [18].
It is widely known that anti-inflammatory cytokines are involved
in a feedback mechanism to regulate the expression of
pro-inflammatory cytokines, and prevent the pathological effects
that may result from their continuous secretion. IL-10, produced
primarily by Th2 cells and monocytes, is an important
anti-inflammatory cytokine that limits the secretion of
inflammatory cytokines and acts as a regulatory switch for Th1 and
macrophage cell function [19, 20]. Previous in vitro studies have
shown that IL-10 suppresses the expression of malaria
parasite-induced production of IL-1β, IL-6 and TNF by peripheral
blood mononuclear cells (PBMC) [21]. Elevated IL-10 levels have
been found in severe malaria patients [8, 22, 23], suggesting its
role in regulating Th1 cytokine-associated pathology.
The cytokine profile that regulates an individual's humoral and
cell-mediated immune responses, and their acquisition of clinical
immunity, may be a consequence of their relative exposure to
parasite infection. Populations living in malaria-endemic areas
develop acquired immunity against severe malaria as a result of
repeated infection and accumulation of malaria antigen-specific
antibodies [24]. A recent study in the mouse-malaria model has
shown regeneration of memory B cells to produce malaria-specific
antibodies after re-infection with P. chabaudi [25]. The
intensity of disease transmission, the severity of infection,
levels of control of peripheral parasitaemia and development of
clinical immunity that define the host immune response to malaria
infection in endemic populations, may not apply to those regions
where disease transmission is low. Most of the studies documenting
the relative amount of cytokines produced during various
manifestations of P. falciparum malaria infection, have been
carried out on subjects from regions where malaria is hyper-endemic
[7, 9, 22, 26]: there is little information on the cytokine profile
and immune response to infection in patients from regions where
falciparum malaria transmission is low.
In order to compare the cytokine production patterns and
consequent Th1/Th2 balance during falciparum malaria in patients
from areas of high or low disease transmission, we analyzed
circulating levels of TNF, IFN-γ, IL-12, IL-6 (pro-inflammatory)
and IL-4, IL-10 and IL-13 (anti-inflammatory) cytokines in control
and patient groups from a P. falciparum-endemic and non-endemic
region of India. Our results indicated differences between
individual cytokine responses, the Th1/Th2 balance, and a
cytokine-based distinction between severe and non-severe malaria
cases in the two regions.
Donors and methods
Patients and controls
Approval to carry out the case-control study was obtained from the
ethical committees of participating institutions. Informed consent
was obtained from each volunteer/guardian prior to collection of
blood from patients and controls. Patient samples were
collected from a P. falciparum-endemic (Antagarh, Chhattisgarh
and Sundargarh, Orissa), and a non-endemic (Lucknow and surrounding
areas of Uttar Pradesh) region of India. Diagnosis of P. falciparum
malaria was carried out as described elsewhere [10]. WHO guidelines
[27] were followed for the categorization of severe (S) and
non-severe (NS) cases [10]. Severe cases were further categorized
as cerebral (CM) or non-cerebral (NCM). A total of
74 patients (63 S and 13 NS) from the non-endemic region, and
101 patients (25 S and 76 NS) from the endemic region were
included in the study (table 1).
Control samples (C) (90 from the non-endemic region and
102 from the endemic region) were taken from
ethnically-matched, unrelated individuals (table 1) from both regions. All controls
recruited were healthy individuals with no reported history of any
obvious allergic manifestations. Diagnostic PCR was performed on
controls from the endemic regions to determine if any were
asymptomatic carriers. Patient plasma was separated immediately
after collection on the first day of entry into the hospital/health
centre. Plasma from control individuals was separated at the site
of collection. All of the plasma samples were transported to the
laboratory in liquid nitrogen and stored immediately at -70˚C.
Since clinical symptoms of malaria may resemble those of other
infectious illness, laboratory tests were generally ordered based
on clinical judgment, most commonly in our setting, an IgM ELISA
test for Japanese encephalitis, and serological tests for typhoid.
Because of the low HIV prevalence in these regions (< 1%),
malarial patients were not tested for HIV unless there were other
clinical indications. Only malaria-positive cases, with no obvious
co-infections, were included in the study.
Table 1 Demographic features of study
participants
|
Endemic region
|
Non-endemic region
|
|
Control
|
Non-severe
|
Severe
|
Control
|
Non-severe
|
Severe
|
|
No. of subjects
|
102
|
76
|
25
|
90
|
13
|
63
|
|
Female/Male
|
52/50
|
31/45
|
13/12
|
39/51
|
4/9
|
14/49
|
|
Mean age (years) (± SD)
|
38.9 (± 12.6)
|
28.02 (± 12.1)
|
34 (± 13.4)
|
28.7 (± 3.9)
|
29.7 (± 11.8)
|
24.3 (± 10.9)
|
Plasma cytokine estimation
Sandwich ELISA was performed for the estimation of plasma cytokine
levels in patients and controls. Plasma TNF, IL-4 and IL-13 levels
were determined using capture monoclonal anti-human antibody
(Pierce) and a paired, biotinylated, anti-human antibody (Pierce).
Briefly, microtitre plates were coated with 100 μL of capture
monoclonal antibody and incubated overnight at room temperature.
Plates were washed four times (50 mM Tris-Cl, 0.2% Tween-20) and
blocked with 200 μL of assay buffer (1X PBS with 4% BSA) for
2 h at room temperature, after which the plates were washed
thoroughly four times. Fifty μL of plasma sample or standards were
added, in duplicates, in each well and plates were incubated
overnight at 4˚C after which plates were washed six times.
Biotin-labeled detecting antibody was added and plates were
incubated at room temperature for about 2 h after which plates
were washed six times and then incubated for 30 min with
Streptavidin linked HRP enzyme (1:20,000 dilution). Plates were
washed eight times and 50 μL TMB of substrate solution were added.
The reactions were allowed to develop for about 30 min.
Reactions were stopped with 7% H2SO4. The
optical density (OD) was measured at a wavelength of 450 nm on
a BioTek Microplate reader. The limit of detection was defined as
two standard deviations above the mean optical density of eight
replicates of the zero standard. ELISAs for IL-6, IL-10, IL-12 and
IFN-γ were performed using OptEIA kits (BD Biosciences), according
to the manufacturer's instructions. Standards were included in
duplicates in each assay plate, and were used for the calculation
of the cytokine levels in the samples. The minimum detection limit
for all the assays was between 0.5-2 pg/mL.
Data analysis
Analysis was performed using GraphPad PRISM (v5.02) and an R
statistical computing environment. Cytokine response values were
normalized by log transformation (to the base 10), and adjusted for
age prior to analysis as we had observed statistically significant
differences among the three groups from both endemic and
non-endemic regions (mean age ± SD for endemic, C: 38.9 ± 12.6; NS:
28 ± 12.1; S: 34.0 ± 13.4, p = 0.001; non-endemic, C: 28.7 ± 3.9;
NS: 29.7 ± 11.8; S: 24.3 ± 10.9, p = 0.0022). When adjusted for
sex, we found no significant differences between the groups in our
study population. Means of plasma cytokine values for controls and
patients were compared using the Kruskal-Wallis test and
within-group comparison was performed using Dunn's multiple
comparison post-test. Coefficients of correlations between cytokine
levels were estimated using the Spearman rank test. Multiple
regression was performed using cytokine levels as the independent
variable and disease outcome (no disease, non-severe and severe
malaria) as the dependent variable. Stepwise multiple regression
(backward elimination) analysis was performed in order to compare
disease groups and to determine which cytokine best predicted
malaria severity. P-value of < 0.05 was considered to be
significant for all tests.
Results
Relative measurements of cytokines
and the Th1/Th2 balance in the malaria-endemic
and non-endemic regions
Basal levels of pro- and anti-inflammatory cytokines were compared
between controls of the two regions in order to analyze the Th1/Th2
balance. When individual pro- (TNF, IFN-γ, IL-6, IL-12) to
anti-inflammatory (IL-4, IL-10, IL-13) cytokine ratios were
compared, the endemic region controls exhibited a lower ratio (p
< 0.0001) (figure 1A) indicating
a shift towards a higher basal Th2 response in the endemic region.
Taking cytokine measurements as the independent variable, multiple
regression analysis was performed with the controls from both
regions. IL-10, IL-12 and IFN-γ contributed significantly to the
region-specific difference in cytokine response, with IL-10
contributing the most (p-values; IL-10: < 0.0001, IL-12: 0.004
and IFN-γ: 0.0003). We next estimated the IL-12/IL-10 and
IFN-γ/IL-10 ratios for both regions. The endemic region controls
exhibited significantly lower IL-12/IL-10 and IFN-γ/IL-10 ratios
when compared to non-endemic controls (p < 0.0001) (figure 1B, C),
indicating the predominance of the Th2 response over Th1 in regions
of high endemicity.
Comparative plasma cytokine levels in patient
and control groups from endemic and non-endemic
regions
Baseline plasma levels of individual cytokines were first compared
between control (C) and patient (severe: S, non-severe: NS) groups
from both regions. TNF levels were higher in patient groups when
compared with controls, although the difference was not significant
in the endemic region (table 2)
(non-endemic; C vs S: p < 0.001; C vs NS: p = 0.01). IL-6 levels
were elevated in severe patients when compared to non-severe
patients or controls (endemic, S vs NS: p < 0.01; non-endemic, S
vs NS: p = 0.0645) (table 2).
Levels of IL-12 and IFN-γ were found to be significantly higher in
non-severe patients when compared to severe malaria patients and
control groups for both regions (table 2).
Of the anti-inflammatory cytokines tested, levels of IL-10 were
found to be elevated in severe malaria patients when compared to
controls in both regions. However, the difference between severe
and non-severe patients was significant only in the endemic region
(table 2) (endemic; S vs C: p
< 0.0001, S vs NS: p < 0.05, non-endemic; S vs C: p
< 0.0001). Levels of IL13 were elevated in both patient groups
when compared to controls from the endemic region, but the
differences were not significant in the non-endemic region (table 2) (endemic; NS vs C: p <
0.0001, S vs C: p < 0.001). Consistent with a recent study on
malaria patients from India [11], no difference in cytokine levels
was observed when severe malaria patients were analyzed separately
as CM or NCM.
Table 2 Comparison of individual plasma cytokine
levels (pg/mL) in patient and control groups
|
Endemic region
|
Non-endemic region
|
|
Control n = 102
|
Non-severe n = 76
|
Severe n = 25
|
P-value
|
Control n = 90
|
Non-severe n = 13
|
Severe n = 63
|
P-value
|
|
TNF Median Range
|
12.02 1.3-136.8
|
8.76 2.4-257.81
|
20.37 1.2-141.74
|
0.4001a
|
12.27 0.28-98.2
|
26.12 1.1-257.52
|
25.4 1.76-433.17
|
0.0004a 0.01b < 0.001c
|
|
IL-12 Median Range
|
32.06 1.2-151.31
|
117.90 55.4-606.03
|
66.7 2.85-166.22
|
< 0.0001a < 0.0001b <
0.01c < 0.0001d
|
26.25 1.02-132.39
|
137.16 43.66-320.88
|
61.69 17.78-150.44
|
< 0.0001a < 0.0001b <
0.0001c < 0.01d
|
|
IFN-γ Median Range
|
44.89 4.89-248.05
|
68.84 3.32-980.16
|
41.21 8.05-765.95
|
0.0203a < 0.05b
|
14.89 2.63-128.58
|
49.11 6.84-464.37
|
28.92 8.56-194.89
|
< 0.0001a 0.0004b <
0.0001c
|
|
IL-6 Median Range
|
6.76 2.4-107.91
|
32.47 1.98-468.4
|
239.75 8.18-575.58
|
< 0.0001a < 0.0001b <
0.0001c < 0.01d
|
2.40 1.9-41.91
|
17.23 1.8-249.2
|
44 3.56-522.24
|
< 0.0001a < 0.0001b <
0.0001c
|
|
IL-10 Median Range
|
20.46 2.28-90.84
|
244.50 9.08-1984.29
|
671.29 7.4-1691.29
|
< 0.0001a < 0.0001b <
0.0001c < 0.05d
|
3.16 1.7-105.32
|
183.21 16.53-910.92
|
178.87 4.14-2594.76
|
< 0.0001a < 0.0001b <
0.0001c
|
|
IL-4 Median Range
|
5.6 1-43.2
|
7.3 1.3-68.8
|
2.5 1.2-30.51
|
0.0005a < 0.01c < 0.001d
|
3.2 1.3-25.8
|
7.45 1.86-127.38
|
5.1 1.2-14.18
|
0.0009a < 0.001b < 0.05c
< 0.05d
|
|
IL-13 Median Range
|
7.04 1.4-33.68
|
15.2 6.3-269.4
|
13.09 7.84-269.4
|
< 0.0001a < 0.0001b <
0.001c
|
8.66 1.86-46.86
|
22.9 4.6-556.2
|
10.4 2.4-251.4
|
0.2706a
|
Discrete patterns of cytokine profiles may define clinical
immunity to falciparum malaria in regions of varying
endemicity
To determine any functional association between cytokines, and
their contribution to malaria-related pathology, we performed
multiple regression considering cytokines as the independent
variable and disease outcome as the dependent variable. In the
endemic region, apart from TNF, IL-12 and IL-13, all other
cytokines contributed significantly to disease outcome, with IL-10
being the strongest predictor (table 3). However, in the non-endemic region,
IL-12, IL-10 and IL-6, were the significant predictors (table 3). To determine which cytokine best
predicted disease severity we performed stepwise multiple
regression using only non-severe and severe disease groups. IL-12
emerged as the most significant predictor of non-severe malaria
outcome in both regions (endemic; p: < 0.0001; non-endemic:
0.006).
To understand better the relative measurements of cytokine
production and Th1/Th2 balance, we compared the ratios of
pro-/anti-inflammatory cytokines that significantly contributed to
disease outcome in the regression analysis. Since IL-10 is known to
be an important regulator of the Th1 response and an inhibitor of
inflammatory cytokine production, we determined individual
IL-6/IL-10 and IFN-γ/IL-10 ratios for each control and patient
group in the endemic region, and IL-6/IL-10 and IL-12/IL-10 ratios
in the non-endemic region and then compared their means. In the
endemic region, the mean IFN-γ/IL-10 ratio was lower in patients
when compared to control groups (p < 0.0001 for all comparisons)
(figure 2A), while no
significant difference was observed between severe and non-severe
patients. In the non-endemic region, the mean IL12/IL10 ratio was
significantly lower in patients when compared to controls (p <
0.0001) (figure 2B). For both
regions, IL-6/IL-10 comparisons were non-significant. However, IL-6
and IL-10 showed positive correlations in severe patients from the
non-endemic region (Spearman's ρ:0.4; p: < 0.0001). Since TNF
and IFN-γ induce secretion of IL-6, we compared the relative
production of IL-6 to that of TNF and IFN-γ. Significantly higher
ratios of IFN-γ/IL-6 in non-severe patients from the endemic region
(p: 0.0001) were observed (figure 2C).
Interestingly, in the endemic region, IL-13 correlated negatively
with IFNγ in severe patients (Spearman's ρ: -0.49; p: 0.013),
while in the non-endemic region, IL-13 correlated negatively with
IL6 in severe malaria patients (Spearman's ρ: -0.485; p:
0.001).
Table 3 Multiple regression analysis to determine
relative contribution of cytokines to disease outcome.
Plasma cytokine values and disease outcome were taken
as independent and dependent variables, respectively
|
Regression coefficient
|
Standard error
|
P-value
|
|
Endemic region participants
|
|
TNF
|
0.020
|
0.0473
|
0.658
|
|
IL-12
|
0.028
|
0.0475
|
0.548
|
|
IFN-γ
|
0.255
|
0.0619
|
0.001
|
|
IL-6
|
0.251
|
0.0454
|
< 0.0001
|
|
IL-4
|
- 0.234
|
0.0827
|
0.005
|
|
IL-10
|
0.578
|
0.0545
|
< 0.0001
|
|
IL-13
|
- 0.202
|
0.0769
|
0.416
|
|
Non-endemic region participants
|
|
TNF
|
0.055
|
0.0625
|
0.373
|
|
IL-12
|
0.174
|
0.0626
|
0.006
|
|
IFN-γ
|
-0.068
|
0.1095
|
0.532
|
|
IL-6
|
0.249
|
0.0745
|
0.001
|
|
IL-4
|
-0.126
|
0.1041
|
0.225
|
|
IL-10
|
0.630
|
0.0599
|
< 0.0001
|
|
IL-13
|
0.021
|
0.0731
|
0.764
|
Discussion
The incidence of malaria in India is high and falciparum malaria
alone accounts for more than 80% of all cases of malaria in
specific areas, particularly regions in western, central, eastern
and north-eastern India [28, 29]. There are limited reports of
patterns of cytokine profiles and immune responses in Indian
populations, and those available refer to endemic regions [11, 22,
28, 29]. Mechanisms involved in the development of protective
immunity against malaria remain unclear, but criteria that define
clinical immunity in populations from malaria-endemic regions may
not apply to regions of low disease intensity and transmission. In
areas where P. falciparum malaria is endemic, people gradually
develop mechanisms to control severe inflammatory responses related
to the parasite as a consequence of repeated infection. When basal
level ratios of pro- to anti-inflammatory cytokines were compared
between controls from the two regions in this study, the endemic
region population exhibited lower ratios and higher levels of
anti-inflammatory cytokines. The half-life of most of the cytokines
is relatively short and they are rapidly cleared from the
circulation by the liver or kidneys. The level of circulating
cytokines depends on many factors including disease severity and
the level of immune challenge. It is believed that populations
living in malaria-endemic regions, control peripheral parasitaemia
in such a way that they do not show clinical symptoms, which
includes production of pro-inflammatory cytokines [24, 30]. Higher
basal levels of anti-inflammatory cytokines (lower Th1/Th2 ratio)
in controls from the malaria-endemic region indicate their
relevance in the development of acquired immunity. Among the
anti-inflammatory cytokines tested, IL-10 contributed the most to
the region-specific difference in basal cytokine levels, indicating
its role in controlling the stimulation of endogenous pyrogens and
the downstream immune effector cascade that are triggered due to
the presence of peripheral malaria antigens in the otherwise
asymptomatic endemic-region individuals.
Significantly elevated levels of TNF in non-endemic patients
validate its role in both the resolution of infection and induction
of the pyrogenic response. Although TNF levels do not vary
significantly between patients and control groups in the endemic
region, its positive correlation with IFN-γ in severe patients may
be associated with P. falciparum-related pathology. It was
interesting to note that cytokine levels, when compared
individually between controls and patient groups, did not exhibit
any region-specific patterns. However, when analyzed relatively, we
found that the cytokine response was region-specific indicating
that there exists a critical balance between cytokine production
and the immune response that may depend on the level of disease
transmission. IFN-γ, IL-10, IL-6, and IL-4 were predictors of
disease outcome in the endemic region. IFN-γ production has been
shown to be instrumental in controlling parasitaemia and activating
macrophages to produce endogenous pyrogens that mediate the
inflammatory cascade [14]. In endemic populations, primary
infection with the malaria parasite induces IFN-γ production
primarily by innate immune cells (NK cells, macrophages), and, at
the same time, T-cells are primed [31]. Upon reinfection, excessive
IFN-γ production is induced predominantly by malaria-specific
memory T-cells, along with NK cells and macrophages [3, 32], and is
potent for parasite killing and resolution of infection. Elevated
levels of IFN-γ relative to IL-6 in non-severe endemic patients,
suggest that IFN-γ production is optimized for evasion of acute
phase symptoms. Memory T-cell-derived IFN-γ can also contribute to
adaptive immunity in asymptomatic individuals since we observed
significantly higher levels of IFN-γ in control endemic populations
compared to controls from the non-endemic region. Early IFN-γ
production by NK cells is predominantly dependent on IL-12
secretion by activated macrophages and dendritic cells (DC). IL-12
has been shown to initiate a number of protective immune responses
to malaria including cell-mediated cytotoxicity (e.g. oxidative
burst, nitric oxide release and enhancement of phagocytosis),
up-regulation of IFNγ production by NK and T-cells, and
differentiation of CD+ T-cells towards a Th1 response
[33, 34]. Low levels of plasma IL-12 have been correlated with
severe forms of falciparum malaria in a number of studies [4, 35],
possibly due to down-regulation of the Th1 response. We also found
elevated levels of IL-12 in non-severe patients from both regions,
indicating the protective role of IL-12 against severe malaria.
A positive correlation between plasma IL-12 and IFN-γ
(Spearman's ρ: 0.46) was also seen in non-severe patients from the
non-endemic region, although the correlation was not significant
(probably due to the small sample size). IL-12 is regulated in a
negative feedback mechanism by IL-10 since uncontrolled IL-12
production leads to excessive production of pro-inflammatory
cytokines resulting in detrimental downstream effects [36]. High
IL-10 levels have been associated with severe falciparum malaria
[8, 22]. The low levels of P. falciparum-induced IL-12 relative to
IL-10 (low IL-12 /IL-10 ratio) in severe patients from
non-endemic regions suggest that IL-12 might be a very important
mediator of the Th1 response, with low levels resulting in
down-regulation of pro-inflammatory cytokines and their
anti-parasitic effects. Since early production of IFN-γ is also an
attribute of acquired immunity in endemic populations, the low
levels of IFN-γ, relative to IL-10 (low IFN-γ/IL-10 ratio) in
severe endemic region patients, indicate its indirect regulation by
IL-10, possibly due to deactivation of macrophage cell function by
IL-10 leading to low IL-12 production.
We observed an interesting correlation between plasma IL-13 and
other cytokines in both regions. IL-13 is a Th2, anti-inflammatory
cytokine and not much is known about its role in falciparum
malaria-induced immune responses. Since IL-13 is closely related to
IL-4 (~ 30% homology), and is also involved in IgE and IgG4
switching in human B cells [37], the negative correlation between
IL-13 and IFN-γ in severe patients from the endemic region may
indicate its counter-regulatory role and its possible involvement
in development of clinical immunity. However, in the non-endemic
region elevated levels of P. falciparum-induced IL-6, relative to
IL-13, may be associated with febrile illness.
The observed heterogeneity in the levels of individual cytokines
between patients and control groups could have been confounded by
some factors. All blood samples were collected at the time of
admission and since cytokine production varies with circadian
rhythm and the time course of the illness, the level of any
particular cytokine observed may not have been an exact reflection
of disease status. Thus, additional studies may be required to
explain the marked variations in individual cytokine measurements
within groups. Although the levels of various pro- and
anti-inflammatory cytokines are a consequence of the individual's
immunity and intensity of exposure, they may also be attributable
to his/her genetic makeup. The region-specific variations in the
cytokine profile observed in our dataset may also be explained by
genetic variants of the genes that encode these cytokines. Since
malaria is known to be one of the strongest forces of selection
[38], it will be interesting to understand the observed immune
response to malaria infection from the perspective of the genetic
background of populations from the two regions. Previously, we have
shown the correlation of TNF promoter variants with malaria
susceptibility and elevated TNF production [10]. Preliminary
results (unpublished) from our genetic study on the same endemic
and non-endemic populations have revealed significant,
region-specific differences in allele frequencies of some genetic
variants of several cytokine-encoding genes.
Taken together, our results are clearly indicative of the wide
variation in relative pro- and anti-inflammatory cytokine responses
to falciparum malaria infection in regions of varying disease
endemicity, and suggest that it is the overall ‘balance’ between
the two classes of cytokines that reflects how differently-exposed
populations may respond to P. falciparum-induced immune
challenge.
Acknowledgments
We are grateful to all donors and their families. We thank Shrawan
Mishra and Dr. Bheshaj K. Ramteke for help with sample collection.
Disclosure and financial support. This work was supported
by a grant to S.H. and V.V. from the Department of Biotechnology,
Government of India (BT/PR6065/MED/14/738/2005). This is CDRI
communication number 7605. None of the authors has any conflict of
interest to disclose.
References
1 Bate CA, Taverne J, Playfair JH. Malarial
parasites induce TNF production by macrophages. Immunology 1998;
64: 227.
2 Mshana RN, Boulandi J, Mshana NM,
Mayombo J, Mendome G. Cytokines in the pathogenesis of
malaria: levels of IL-I beta, IL-4, IL-6, TNF-alpha and IFN-gamma
in plasma of healthy individuals and malaria patients in a
holoendemic area. J Clin Lab Immunol 1991; 34: 131.
3 D'Ombrain MC, Robinson LJ, Stanisic DI,
et al. Association of early interferon-gamma production with
immunity to clinical malaria: a longitudinal study among Papua New
Guinean children. Clin Infect Dis 2008; 47: 1380.
4 Malaguarnera L, Pignatelli S, Musumeci M,
Simporè J, Musumeci S. Plasma levels of interleukin-18
and interleukin-12 in Plasmodium falciparum malaria. Parasite
Immunol 2002; 24: 489.
5 Kremsner PG, Winkler S, Brandts C, et al.
Prediction of Accelerated Cure in Plasmodium falciparum Malaria by
the Elevated Capacity of Tumor Necrosis Factor Production. Am J
Trop Med Hyg 1995; 53: 532.
6 Kern P, Hemmer CJ, Van Damme J, Gruss HJ,
Dietrich M. Elevated tumor necrosis factor alpha and
interleukin-6 serum levels as markers for complicated Plasmodium
falciparum malaria. Am J Med 1989; 87: 139.
7 Day NPJ, Hien TT, Schollaardt T, Loc PP,
Chuong LV, Chau TTH. The prognostic and pathophysiologic
role of pro- and anti-inflammatory cytokines in severe malaria. J
Infect Dis 1999; 180: 1288.
8 Lyke KE, Burges R, Cissoko Y, et al. Serum
levels of the proinflammatory cytokines interleukin-1 beta
(IL-1beta), IL-6, IL-8, IL-10, tumor necrosis factor alpha, and
IL-12(p70) in Malian children with severe Plasmodium falciparum
malaria and matched uncomplicated malaria or healthy controls.
Infect Immun 2004; 72: 5630.
9 Clark IA, Cowden WB, Butcher GA, Hunt NH.
Possible roles of tumor necrosis factor in the pathology of
malaria. Am J Pathol 1987; 129: 192.
10 Sinha S, Mishra SK, Sharma S, et al.
Polymorphisms of TNF-enhancer and gene for FcγRIIa correlate with
the severity of falciparum malaria in the ethnically diverse Indian
population. Malar J 2008; 7: 13.
11 Jain V, Armah HB, Tongren JE, et al.
Plasma IP-10, apoptotic and angiogenic factors associated with
fatal cerebral malaria in India. Malar J 2008; 7: 83.
12 Sedegah M, Finkelman F, Hoffman SL.
Interleukin-12 induction of Interferon gamma-dependent protection
against malaria. Proc Natl Acad Sci USA 1994; 91: 10700.
13 Taylor-Robinson AW, Looker M. Sensitivity of
malaria parasite to nitric oxide at low oxygen tension. Lancet
1998; 351: 1630.
14 Deloron P, Chougnet C, Lepers JP,
Tallet S, Coulanges P. Protective value of elevated
levels of gamma interferon in serum against exoerythrocytic stages
of Plasmodium falciparum. J Clin Microbiol 1991; 29: 1757.
15 Udomsangpetch R, Chivapat S, Viriyavejakul P,
et al. Involvement of cytokines in the histopathology of
cerebral malaria. Am J Trop Med Hyg 1997; 57: 501.
16 Clark IA. Along a TNF-paved road from dead parasites in
red cells to cerebral malaria, and beyond. Parasitology 2009; 136:
1457.
17 Lucas R, Lou J, Morel DR, Ricou B,
Suter PM, Grau GE. TNF receptors in the microvascular
pathology of acute respiratory distress syndrome and cerebral
malaria. J Leukoc Biol 1997; 61: 551.
18 Wykes MN, Liu XQ, Jiang S,
Hirunpetchara C, Good MF. Systemic tumor necrosis factor
generated during lethal Plasmodium infections impairs dendritic
cell function. J Immunol 2007; 179: 3982.
19 Bogdan C, Vodovotz Y, Nathan C. Macrophage
Deactivation by Interleukln 10. J Exp Med 1991; 174: 1549.
20 Ho M, Sexton MM, Tongtawe S,
Looareesuwan S, Suntharasami P, Webster HK.
Interleukin-10 inhibits tumor necrosis factor production but not
anigen-specific lymphoproliferation in acute Plasmodium falciparum
malaria. J Infect Dis 1995; 172: 838.
21 Ho M, Schollaardt T, Snape S,
Looareesuwan S, Suntharasami P, White NJ. Endogenous
interleukin-10 modulates proinflammatory response in Plasmodium
falciparum malaria. J Infect Dis 1998; 178: 520.
22 Prakash D, Fesel C, Jain R, Cazenave P,
Mishra GC, Pied S. Clusters of cytokines determine
malaria severity in Plasmodium falciparum-infected patients from
endemic areas of central India. J Infect Dis 2006; 194: 198.
23 Hugosson E, Montgomery SM, Premji Z,
Troye-Blomberg M, Björkman A. Higher IL-10 levels are
associated with less effective clearance of Plasmodium falciparum
parasites. Parasite Immunol 2004; 26: 111.
24 Rhee MSM, Akanmori BD, Waterfall M,
Riley EM. Changes in cytokine production associated with
acquired immunity to Plasmodium falciparum malaria. Clin Exp
Immunol 2001; 126: 503.
25 Ndungu FM, Cadman ET, Coulcher J, et al.
Functional memory B cells and long-lived plasma cells are generated
after a single Plasmodium chabaudi infection in mice. PLoS Pathog
2009; 5: e1000690.
26 Iriemenam NC, Okafor CM, Balogun HA,
et al. Cytokine profiles and antibody responses to Plasmodium
falciparum malaria infection in individuals living in Ibadan,
southwest Nigeria. Afr Health Sci 2009; 9: 66.
27 World Health Organization. Severe falciparum malaria. Trans R
Soc Trop Med Hyg 2000; 94 (Suppl. 1).
28 Singh N, Mishra AK, Shukla MM, Chand SK.
Forest malaria in Chhindwara, Madhya pradesh, central India: a case
study in a tribal community. Am J Trop Med Hyg 2003; 68: 602.
29 Sharma SK, Chattopadhyay R, Chakrabarti K,
et al. Epidemiology of malaria transmission and development of
natural immunity in a malaria-endemic village, San Dulakudar, in
Orissa state, India. Am J Trop Med Hyg 2004; 71: 457.
30 Bull PC, Marsh K. The role of antibodies to
Plasmodium falciparum-infected-erythrocytes surface antigens in
naturally acquired immunity to malaria. Trends Microbiol 2002; 10:
55.
31 Riley EM. Is T-cell priming required for initiation of
pathology in malaria infections? Immun Today 1999; 20: 228.
32 D'Ombrain MC, Hansen DS, Simpson KM,
Schofield L. γδ-T cells expressing NK receptors predominate
over NK cells and conventional T-cells in the innate IFN-γ response
to Plasmodium falciparum malaria. Eur J Immunol 2007; 37: 1864.
33 Chan SH, Perussia B, Gupta JW, et al.
Induction of IFN-γ production by NK cell stimulatory factor (NKSF):
characterization of the responder cells and synergy with other
inducers. J Exp Med 1991; 173: 869.
34 Aste-Amezaga M, D'Andrea A, Kubin M,
Trinchieri G. Cooperation of natural killer cell stimulatory
factor/interleukin-12 with other stimuli in the induction of
cytokines and cytotoxic cell-associated molecules in human T and NK
cells. Cell Immunol 1994; 156: 480.
35 Luty AJF, Perkins DJ, Lell B, et al. Low
Interleukin-12 Activity in Severe Plasmodium falciparum Malaria.
Infect Immun 2000; 68: 3909.
36 Aste-Amezaga M, Ma X, Sartori A,
Trinchieri G. Molecular Mechanisms of the Induction of IL-12
and Its Inhibition by IL-10. J Immunol 1998; 160: 5936.
37 Punnonen J, Aversa G, Cocks BG, et al.
Interleukin 13 induces interleukin 4-independent IgG4 and IgE
synthesis and CD23 expression by human B cells. Proc Natl Acad Sci
USA 1993; 90: 3730.
38 Kwaitkowski D. How malaria has affected the human genome
and what human genetics can teach us about malaria. Am J Hum Genet
2005; 77: 171.
|
Printable version
Version PDF
