The Relationship between Heart Rate Variability and Serum Cytokines in

Prévia do material em texto

The Relationship between Heart Rate Variability
and Serum Cytokines in Chronic Chagasic
Patients with Persistent Parasitemia
MAURICIO LLAGUNO, M.D.,* LUIZ ANTONIO RODRIGUES DE RESENDE PERTILI, M.D.,*
MARCOS VINICIUS DA SILVA,‡ PABLO BUNAZAR, M.D.* ARIANE MARTIM REGES, M.D.,*
ANA CAROLINA GUIMARÃES FALEIROS, PH.D.,† ELIANE LAGES-SILVA, PH.D.,†
VIRMONDES RODRIGUES JUNIOR, M.D., PH.D.,‡ VALDO JOSÉ DIAS DA SILVA, M.D., PH.D.,§
and DALMO CORREIA FILHO, M.D., PH.D.*
From the *Internal Medicine Department, Infectious Division, Federal University of the Triângulo Mineiro,
Uberaba, Minas Gerais, Brazil; †Biological Science Department, Parasitology Division, Federal University of the
Triângulo Mineiro, Uberaba, Minas Gerais, Brazil; ‡Biological Science Department, Immunology Division, Federal
University of the Triângulo Mineiro, Uberaba, Minas Gerais, Brazil; and §Biological Science Department, Physiology
Division, Federal University of the Triângulo Mineiro, Uberaba, Minas Gerais, Brazil
Background: Persistent parasitemia, immunological, and autonomic nervous system impairments may
play an important role in the evolution and clinical outcome of the chronic phase of Chagas’ disease by
triggering functional cardiovascular changes.
Methods: Three groups were evaluated: 17 chronic chagasic patients with the indeterminate form
(IChD), 12 chronic chagasic patients with cardiac forms (ChHD), and 29 individuals as a healthy control
group. Parasitemia was assessed by polymerase chain reaction; hemoculture, heart rate variability by
linear and nonlinear methods, and interleukin (IL)-1β, IL-4, IL-6, IL-10, IL-12, IL-13, IL-17, and tumor
necrosis factor-α, and interferon (IFN)-γ serum cytokines were assessed by enzyme-linked immune assay.
Results: Twenty-nine chronic chagasic patients were positive for parasitemia (17 IChD and 12 ChHD).
Heart rate variability parameters in baseline condition and after cold face test were significantly decreased
in chagasic patients compared to controls. Tilt tests showed no alteration. However, using nonlinear
indices, ChHD patients presented lower values compared to IChD and controls. Differences in the
expression of serum cytokines were observed between chagasic patients and controls. However, among
the groups, ChHD presented higher median values of IL-10 and lower of IFN-γ compared to IChD.
Conclusion: Both chagasic groups present an autonomic impairment using linear methods. The
nonlinear methods revealed that the ChHD group had a higher cardiovascular risk. Serum cytokine
concentrations between chagasic patients were similar. However, ChHD showed higher concentrations
of IL-10 and lower of IFN-γ , suggesting some established process of immune regulation. (PACE 2011;
34:724–735)
Chagas disease, heart rate variability, dysautonomia, serum cytokines, parasitemia
Introduction
A century ago, Carlos Chagas identified the
etiologic agent (Trypanosoma cruzi), the main
vector (Reduviidae), and characterized the clinical
manifestations of a disease that would take his
name (Chagas, 1909). Despite being classified as
Financial Support: This work was supported by Fundação de
Amparo à Pesquisa do Estado de Minas Gerais – FAPEMIG
(PPM/08). The corresponding author is the recipient of a
Productivity Fellowship from CNPq (Conselho Nacional de
Desenvolvimento Cientı́fico e Tecnológico).
Address for reprints: Dalmo Correia Filho, M.D., Ph.D., Av
Getúlio Guaritá S/N P.O. Box, 118, Uberaba, MG 38030-440,
Brazil. Fax: 00553433185254; e-mail: dalmo@mednet.com.br
Received September 14, 2010; revised November 23, 2010;
accepted December 1, 2010.
doi: 10.1111/j.1540-8159.2010.03025.x
a disease exclusive to Latin America, human
migratory processes over the last few decades
have caused its globalization. However, its overall
incidence has decreased significantly due to vector
control and transfusioncampaigns.1–7
Chagas disease has two phases; in most cases,
the acute phase is oligosymptomatic, though in
some cases fatal severe myocarditis and encephali-
tis occur, while the chronic phase is generally the
indeterminate type, which represents up to 70% of
cases and can remain in a period of latency for 10–
30 years. However, persistent parasitism causes
immune system alterations, autonomic nervous
system (ANS) disorders, microvascular injury, and
other recurring mechanisms, from both the host
and the parasite, and can contribute to the genesis
of disease manifestations, with the cardiac form
being the leading cause of morbidity and mortality,
presenting an incidence of 20–30%, followed
C©2011, The Authors. Journal compilation C©2011 Wiley Periodicals, Inc.
724 June 2011 PACE, Vol. 34
AUTONOMICAL AND IMMUNOLOGICAL RELATIONSHIP IN CHAGAS DISEASE
by gastrointestinal symptoms. Among the factors
that can lead to different clinical outcomes and
influence the severity of the disease, the cardiac
forms are not yet fully understood and are a
challenge to understanding the pathophysiology
of the complex host-parasite relation.4,8–11
In the chronic phase, the coexistence of persis-
tent parasitism causes stimuli that activate specific
T cells by stimulating the secretion of inflamma-
tory cytokines, which are capable of producing
cardiac lesions and may release autoantigens, such
as myosin, that are recognized by another group of
reactive T cells and autoantibodies, contributing
to increased heart damage.11,12 This heart damage
favors the induction of costimulatory molecules
necessary for correct activation of autoreactive T
cells. At this point, a low parasite load would
activate the regulatory T cells (Treg) suppressing
an autoimmune pathogenic response. However, if
the parasite load or parasite antigens that mimic
molecules occur in high concentrations, they
stimulate the secretion of pathogenic autoreactive
T cells.13
It has been shown that Chagas disease
involvement in ANS compromise is a consequence
of inflammatory and degenerative processes of
variable intensity and length, which evolve
from an acute pattern to one involving fibrotic
ganglia and intrinsic neurons and in which
alterations may occur separately or in combination
with sympathetic and parasympathetic activities
related to the pathophysiological processes of the
heart.14–19 While some authors emphasize that
Chagas disease leads to inadequate modulation
of parasympathetic activity,20 others support
the theory that an attenuated sympathetic re-
sponse to stimuli occurs.21,22 Several methods
have verified these alterations in patients with
Chagas disease. However, the results are still
controversial.19,20,23–36
Computerized analysis of heart rate variability
(HRV) in time-frequency domains is a reliable,
noninvasive test that is easy to use, and permits
the characterization of absolute and relative
activities of the sympathetic and parasympathetic
components of the ANS, individualizing them
with relative precision.17,37–40 The decrease in
HRV parameters has been used as a predictor of
morbidity and mortality of cardiovascular disease
in healthy subjects and in patients with acute
ischemic disease, but its use as a prognostic
marker is still under discussion.41–44
The role of the immune system in the
development and prognosis of cardiovascular
diseases has been of great interest in recent years.
High concentrations of inflammatory cytokines,
such as TNF-α, interleukin (IL)-1b, IL-6, and
C-reactive protein, have been associated with
markers of cardiovascular mortality and morbidity
in the general population and as markers of
poor prognosis among survivors of acute coronary
events.45–48
Asymptomatic chronic Chagas disease pa-
tients or those with mild left ventricular dysfunc-
tion present a 15–30% risk of progressing to severe
forms of the disease. It is therefore extremely
important to elucidate patterns related to disease
progression. Thus, the recognition of recurring
inflammation due to persistent parasitism in
chronic Chagas disease patients could provide
relevant information, while distinct immune and
autonomicalterations could be used as prognostic
markers of cardiovascular risk. However, there
are currently no studies that have evaluated the
behavior of HRV analyzed by linear and nonlinear
methods and correlated these with serum cytokine
production in patients with the indeterminate
and cardiac forms of chronic Chagas disease and
persistent parasitemia.
Methods
Casuistic/Study Population
Following approval by the Ethics in Research
Committee of the Triangulo Mineiro Federal
University (Universidade Federal do Triângulo
Mineiro, UFTM), Uberaba, Minas Gerais, Brazil,
under protocol no. 1030, a prospective study was
developed between September 2007 and Decem-
ber 2008. Individuals with positive serology for
chronic stage Chagas disease attended by the
Chagas Disease Outpatient Clinic of the UFTM
and who were from the city of Uberaba and
surrounding region were examined. The study
population consisted of those who provided blood
samples that showed positive serology for T. cruzi,
who were referred by the Hemocenter and who
met the inclusion criteria: individuals aged 18–
60 years old, who agreed to participate in the study
after clarification and who showed blood culture
and polymerase chain reaction (PCR) positive for
T. cruzi at the time of intervention. The exclusion
criteria were individuals aged under 18 and over
60 years old, who had received treatment with
benznidazole within the previous 5 years, who
did not agree to participate in the study, and
who had negative blood culture or PCR, and
patients with the cardiac form of Chagas disease
(New York Heart Association functional class III
and IV) or the digestive form with megacolon or
megaesophagus grade III and IV; patients using
drugs (antiarrhythmic drugs, oral contraceptives,
hormone replacement, centrally acting antihyper-
tensive drugs) or diseases affecting HRV, such
as alcoholism, hypertension, diabetes mellitus,
PACE, Vol. 34 June 2011 725
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icense
LLAGUNO, ET AL.
kidney, liver, or thyroid disorders; and patients
with an artificial pacemaker.
Experimental Protocol of the Study
Clinical history and physical examination
were performed and followed the usual prelimi-
nary norms. During the selection and formation
of the groups, the following tests were performed:
cardiac autonomic function and exams to classify
the clinical forms (12-lead electrocardiogram
[ECG], echocardiogram, chest x-ray, esopha-
gogram, and barium enema), serology to diagnose
infection by T. cruzi (indirect immunofluores-
cence, indirect haemagglutination, ELISA), blood
culture, and PCR for T. cruzi. Carriers of T.
cruzi infection were established by seroposi-
tivity in at least two of the three techniques
used. Biochemical tests measuring blood glu-
cose, total cholesterol, high-density lipoprotein,
triglycerides, urea, creatinine, sodium, potassium,
alanine aminotransferase, aspartate aminotrans-
ferase, gamma glutamyl transferase, total and
indirect bilirubin, and hemogram were performed.
Using the biochemical results, patients were
characterized for the presence of other diseases
(diabetes, lipid disorders, thyroid disorders and
electrolyte imbalance, kidney and liver function
abnormalities).
Assessment of Cardiac Autonomic Function
A continuous ECG was recorded in deriva-
tion DII under three different conditions: basal
(supine), facial cooling, and passive standing.
Facial cooling was achieved by placing two bags
of ice water (4◦C, 39.2◦F) on the face of the
patient. The signal was recorded for 10 minutes
at baseline and 5 minutes in response to facial
cooling and passive standing, with a rest period
of 5 minutes between each examination. Data
were registered on a computer equipped with
an analog digital converter board (DI-194 starter
kit, Dataq Instruments, Akron, OH, USA) with
an acquisition rate of 240 samples per second.
The series analysis of interval between R waves
in electrocardiogram was corrected by the Linear
Analysis program (kindly ceded by Dr. Alberto
Porta of the University of Milan, Italy). These
were analyzed immediately using the Kubios
HRV program, version 2.0 (Biosignal Analysis
and Medical Imaging Group at the Department of
Physics, University of Kuopio, Kuopio, Finland),
which provided first-order temporal parametric
statistical indices, derivatives of the RR interval
periodogram, geometric indices, spectral indices
based on autoregressive modeling algorithm, and
nonlinear indices. Spectral analysis was tested
by removal of the first-order bias, using the
autoregressive method with a fixed-order model.
Very low frequency (VLF: 0.005–0.04 Hz),
low-frequency (LF: 0.04–0.15 Hz), and high-
frequency components (HF: 0.15–0.40 Hz) were
selected, expressed in peak frequencies (Hz), in
absolute power in millisecond2, in relative power
as a percentage (%), and in power in normalized
units (NUs), as well as the ratio of the frequencies
LF/HF.37,39,49 These measurements were related
to the activities of sympathetic (LF areas) and
parasympathetic subdivisions (HF fields) of the
ANS. Several temporal parametric, geometric,
spectral, and nonlinear statistical indices were
used, calculated relative to the variability of
the RR interval series considered. Regarding
the temporal indices,37 the mean RR interval
(millisecond), standard deviation of RR intervals
(SDNN), mean heart rate range (1/min), standard
deviation of heart rate (1/min), root mean square of
successive differences (RMSSD), and percentage
of successive RR intervals that differ by 50 ms
(pNN50) were used. Regarding the geometric
indices,50 the RR triangulation index (RRtri) and
triangulation and interpolation of RR intervals
(TINN) were used. The spectral indices37 used
were center frequency corresponding to the area
of the spectral profile or the frequency spectrum,
expressing the variance of the same (FreqLF,
FreqHF); absolute spectral area of each spectral
frequency bands, which expresses the variance
of the same (PowLF, PowHF); percentage of area
corresponding to the spectral bands of HF and
LF (LF%, HF%); area normalized spectral area
of the LF and HF bands (LFnu, HFnu); and the
ratio of absolute areas of the bands of LF and HF
spectrum (LF/HF). The nonlinear indices44 were
the measures of the Poincaré Plot (SD1, SD2),
approximate entropy (ApEn), sample entropy
(SampEn), Shannon entropy (ShEn), correlation
dimension (D2), percentage of recurrence (REC),
measurement of determinism (DET), measurement
of the length of the midline, and the line
maximum, as well as measurement of fluctua-
tion analysis without RR interval bias (alpha-1,
alpha-2).
Blood was cultured according to the tech-
nique described by Chiari et al.51 Plasma and
erythrocyte sediment was added to the liver infu-
sion tryptose (LIT) culture medium, as described
by Camargo.52 PCR was performed using the
technique described by Gomes et al.53 In the PCR,
the sequences of the constant region of minicircle
kDNA were the reaction target, amplifying a 330-
pb fragment with primers A121 and A122 as
described by Degrave et al.54
Statistical Analysis
After tabulation, the data were analyzed using
the software SigmaStat for Windows 3.5 (Jandel
726 June 2011 PACE, Vol. 34
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icenseAUTONOMICAL AND IMMUNOLOGICAL RELATIONSHIP IN CHAGAS DISEASE
Table I.
Distribution of Clinical and Ultrasonographic Parameters between the Patients in CT, IChD, and ChHD Groups
CT IChD ChHD
Indices ME P25 P75 ME P25 P75 ME P25 P75 P=
HR (bpm) 69.71 65.16 75.77 66.12 55.55 70.01 63.79 55.09 68.35 0.088
SBP (mmHg) 125.00 115.00 133.75 115.00 110.00 131.25 125.00 112.5 135.00 0.371
DBP (mmHg) 80.00 75.00 85.00 75.00 70.00 85.00 82.00 75.00 87.50 0.230
EF (%) 77.00 74.00 79.75 72.50 70.00 78.00 76.00 71.75 78.00 0.550
�D (%) 39.00 36.25 42.75 40.00 36.00 41.50 38.00 36.50 39.75 0.217
CT = control; IChD = indeterminate form; ChHD = cardiac clinical form; ME = median, P25 = 25th percentile; P75 = 75th percentile;
HR = heart rate in beats/min; SBP = systolic blood pressure; DBP = diastolic blood pressure; EF = ejection fraction; �D = left ventricle
fractional shortening. Kruskal-Wallis test.
Corporation, San Rafael, CA, USA). One-way
analysis of variance (ANOVA) tests followed by
the Tukey test or Kruskal-Wallis followed by
Dunn’s test were used as required. To calculate
differences between proportions, the χ2, Student’s
t-test, ANOVA, and Fisher exact tests were used
whenever necessary. Differences were considered
statistically significant when P < 0.05.
Results
The final sample was composed of three
groups: group I, 17 individuals with the indetermi-
nate clinical form (IChD); group II, 12 individuals
with the cardiac clinical form (ChHD); and group
III, the control group (CT), 29 patients without
Chagas disease. The IChD and ChHD groups
presented positive blood culture and PCR for
T. cruzi. In the Chagas disease group, the median
age was 49 years old,25–60 which was the same as
the control group, where the median age was also
49 years old.24–60 In both the infected and control
groups, predominance of women was verified, 17
(58.6%) and 18 (62.1%), respectively. However,
the distribution according to sex between the
two groups showed no significant difference (P =
1.000). The clinical and ultrasonographic data are
presented in Table I.
Evaluation of Cardiac Autonomic Function
The groups CT, IChD, and ChHD were
analyzed and compared at baseline to identify
their specific characteristics. The results were
divided according to types of indices (temporal,
geometric, spectral, and nonlinear) and were
analyzed by the percentage of variation in relation
to the same stimuli caused by facial cooling and
the Tilt test. Regarding the geometric and temporal
indices at baseline, significant differences in mean
duration of RR intervals occurred in the ChHD
group (P = 0.040), which showed a higher value
compared to groups IChD and CT. Regarding
SDNN, MHRi, RMSSD, pNN50, and RRtri, no
significant differences were observed between the
groups. However, a significant difference was
observed in the IChD group, which showed less
variation in SDHR (P = 0.011) and a lower value
for TINN (P = 0.034) compared to groups CT
and ChHD. Analysis of the spectral components
at baseline revealed no differences in the values
of FreqLF nor FreqHF in the groups studied;
however, the values of PowLF (P = 0.057) were
diminished both in the IChD (136.77 ms2) and
the ChHD groups (144.65 ms2) compared to the
CT group (329.16 ms2), though these differences
were not statistically significant. A significant
difference was observed in the median of PowHF
between the ChHD and CT groups (P = 0.042),
with values of 72.29 and 149.53 ms2, respectively.
The LF% component (P = 0.021) was also
diminished in the ChHD group compared to the CT
and IChD groups. Regarding median normalized
values, for both LF and HF and the LF/HF ratio,
no significant differences were verified between
the three groups. In the nonlinear analysis at
baseline, using measures of Poincaré plot, analysis
of fluctuations, and the dimension correlation, no
significant differences were determined. However,
ApEn was significantly lower (P = 0.021) in the
ChHD group compared with the other two groups.
Comparisons between SampEn and ShEn revealed
no differences between the three groups (Fig. 1).
Regarding the temporal indices in response to
facial cooling, less variation was observed in
response to facial cooling in groups IChD and
ChHD compared to CT; however, this was not
statistically significant. For the geometric indices,
the ChHD group showed a significant difference in
the triangulation rate of RR intervals (P = 0.014)
PACE, Vol. 34 June 2011 727
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icense
LLAGUNO, ET AL.
Figure 1. Box plot of median values of temporal, geometrical, spectral, and nonlinear indices at
baseline in the groups CT = control; IChD = indeterminate form; ChHD = cardiac clinical form.
The horizontal line represents the median, the bars the 25th and 75th percentiles, and the vertical
line 10–95%. *P ≤ 0.05 compared to control and P ≤ 0.05 for both groups. Kruskal-Wallis test.
compared to CT. In contrast, the other geometric
index studied, TINN, showed no significant
difference between the groups. While analyzing
the spectral components in response to facial
cooling, a significant difference was observed in
the ChHD group, which presented a negative
variation for FreqLF values (P = 0.001) compared
to CT. In the IChD group, a significant difference
was observed in the variation of PowLF (P = 0.047)
compared to CT. Despite no significant difference
in variation in groups IChD and especially
in ChHD, the HF% component presented an
entirely different response to that obtained in CT
(Table III). In the CT group, the change was slightly
negative (−2.14%) and the variation in IChD was
positive (27.79%) and in the ChHD group, this
positive change was even higher (101.69%). The
HFnu component and LF/HF ratio also showed a
negative variation in patients with Chagas disease,
both in the IChD and ChHD groups, in relation
to CT, but presented no significant difference.
Concerning nonlinear indices in response to facial
cooling, no differences were verified between the
groups.
Statistical analysis of temporal, geometrical,
spectral, and nonlinear indices during passive
standing revealed no significant differences be-
tween the three groups.
Analysis of Serum Cytokine Concentrations in
the Control Group and the Indeterminate and
Cardiac Clinical Forms of Chagas Disease
Plasma concentrations of IL-1β, IL-4, IL-5,
IL-6, IL-10, IL-12, IL-13, IFN-γ , and TNF-α were
analyzed in control subjects (CT) and Chagas dis-
ease patients according to clinical form (IChD and
728 June 2011 PACE, Vol. 34
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icense
AUTONOMICAL AND IMMUNOLOGICAL RELATIONSHIP IN CHAGAS DISEASE
Table II.
Distribution of Cytokine Values in pg/mL for the CT, IChD, and ChHD Groups
CT IChD ChHD
Interleukin ME P25 P75 ME P25 P75 ME P25 P75 P=
IL-1β 1.05 0.62 1.21 1.23 0.02 1.89 0.70 0.00 1.99 0.613
IL-4 10.66 6.99 12.24 *0.00 0.00 3.22 *1.25 0.10 2.59 <0.05
IL-5 7.25 5.25 8.85 6.07 4.76 6.87 7.19 5.88 8.43 0.254
IL-6 34.81 27.16 50.15 *18.61 9.96 33.04 23.69 17.28 29.53 0.003
IL-10 0.00 0.00 7.19 11.47 0.00 52.27 *22.22 13.82 34.52 0.001
IL-12 2.09 0.73 4.52 1.01 0.00 8.26 3.49 1.02 5.65 0.830
IL13 0.00 0.00 0.00 *115.49 46.04 182.65 *73.16 0.00 119.17 <0.001
IL-17 0.00 0.00 0.00 *32.34 0.00 176.59*44.53 0.00 98.67 <0.001
IFN-γ 45.79 8.65 93.55 143.65 0.00 209.43 0.00 0.00 132.26 0.329
TNF-α 0.00 0.00 111.38 *794.62 321.32 978.33 *370.41 308.76 591.21 <0.001
CT = control; IChD = indeterminate form; ChHD = cardiac clinical form; ME = median, P25 = 25th percentile; P75 = 75th percentile.
*P ≤ 0.05 by Kruskal-Wallis test.
ChHD) and the results were expressed as median
and percentiles 10–90 (Table II). Both groups of
Chagas disease patients showed increased serum
concentrations of TNF-α (P ≤ 0.001), IL-17 (P <
Table III.
Distribution of Values of Percentage Variation of Temporal, Spectral, and Geometric and Nonlinear Indices Observed in
Response to Facial Cooling between the Groups CT, ChHD, and IChD
CT IChD ChHD
Temporal
Indices ME P25 P75 ME P25 P75 ME P25 P75 P=
RRi (ms): 4.39 0.92 6.88 2.77 −1.08 5.12 0.77 −1.60 1.83 0.127
SDNN (ms): 12.64 0.45 35.35 4.40 −9.92 15.64 −1.06 −17.95 41.67 0.402
RMSSD (ms): 11.15 3.09 38.41 8.63 −3.69 26.75 7.48 −6.51 17.04 0.474
pNN50 (%): 30.79 0.00 95.81 −1.13 −34.02 40.49 0.00 −29.18 13.66 0.075
RRtri: 11.98 −2.75 23.22 *−12.45 −25.91 0.00 −4.51 −25.52 19.18 *0.014
FreqLF (Hz): 2.94 −6.45 12.50 *−24.38 −42.87 −11.08 −4.35 −30.00 8.33 0.001
FreqHF (Hz): −3.41 −9.21 4.76 −5.20 −11.99 3.27 0.00 −10.10 8.82 0.475
PowLF (ms2): 31.37 −30.39 132.51 −38.56 −43.39 129.80 *−17.76 −59.69 0.00 0.047
PowHF (ms2): 16.68 −3.64 95.01 62.17 30.12 143.38 5.84 −12.38 57.18 0.080
HF% (%): −2.14 −32.97 38.07 101.69 4.86 146.54 27.79 −18.30 96.75 0.052
LFnu (n.u.): −1.09 −22.50 13.14 −11.61 −25.53 0.22 −13.45 −29.54 0.39 0.355
HFnu (n.u.): 2.86 −24.60 49.05 29.61 1.19 139.63 33.01 −1.06 55.79 0.253
LF/HF: −3.84 −48.11 55.63 −35.55 −75.78 −0.89 −39.86 −68.12 1.47 0.176
ApEn: −18.47 −21.02 −15.11 −15.10 −21.68 −13.11 −17.32 −29.21 0.00 0.837
CT = control; IChD = indeterminate form; ChHD = cardiac clinical form; ME = median; P25 = 25th percentile; P75 = 75th percentile;
RRi = mean RR interval; SDNN = standard deviation of RR interval; MHRi = mean heart rate interval; SDHR = standard deviation of
heart rate; RMSSD = root mean square of the sum of the squares of differences between RR intervals; pNN50 = percentage of
differences and adjacent normal RR intervals that are greater than 50 ms; RRtri = RR interval triangulation index; TINN = triangular
interpolation of RR intervals, *= P < 0.05 compared to CT by Kruskal-Wallis test.
0.001), IL-13 (P < 0.001), and decreased IL-4 (P <
0.001) compared to controls. Besides these differ-
ences, the ChHD group showed greater production
of IL-10 (P < 0.05) and the IChD group showed
PACE, Vol. 34 June 2011 729
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icense
LLAGUNO, ET AL.
low concentrations of IL-6 (P < 0.001) compared
to control. Although not statistically significant,
the IChD group showed greater concentrations of
IFN-γ .
Correlation between Serum Concentrations
of Cytokines and HRV Parameters
Evaluation of HRV parameters in relation to
cytokines in the IChD group showed a positive
correlation between IL-1b and parameters RMSSD,
PowLF, PowHF, and SampEn (r = 0.48, P = 0.046;
r = 0.47, P = 0.055; r = 0.49, P = 0.040; and
r = 0.47, P = 0.055, respectively) and negative
with REC, DET, ShEn, and alpha-2 (r = −0.50,
P = 0.038; r = 0.49, P = 0.043; r = 0.47, P =
0.052; and r = 0.51, P = 0.038, respectively). A
negative correlation occurred between IL-4 and
the parameters PowLF and LF/HF (r = −0.49, P =
0.042; r = −0.46, P = 0.060) and positively with
alpha-2 (r = 0.50, P = 0.038). IL-10 correlated
positively with alpha-2 (r = 0.522, P = 0.031) and
negatively with SampEn (r = −0.532, P = 0.027).
Il-12 correlated positively with ApEn (r = 0.524,
P = 0.030) and negatively with REC, DET, ShEn,
and alpha-1 (r = −0.56, P = 0.018; r = −0.58, P =
0.014; r = −0.48, P = 0.051; and r = −0.56, P =
0.030, respectively).
Il-13 was positively correlated with LF% (r =
0.58, P = 0.015) and negatively with REC, DET,
and Shen (r = −0.52, P = 0.030; r = −0.47, P =
0.057; r = −0.52, P = 0.033, respectively). IL-17
correlated positively with LF/HF and LFnu (r =
0.73, P > 0.001; and r = 0.73, P > 0.001) and
negatively with HFnu (r = −0.73, P > 0.001). IFN-
γ was positively correlated with LF%, LF/HF (r =
0.64, P = 0.005; r = 0.58, P = 0.015) and negatively
with alpha-2 (r = −0.513, P = 0.035).
Regarding the ChHD group, a negative corre-
lation occurred between the values of IL-1b and
LF/HF (r = −0.59, P = 0.042) between IL-5 and the
values of SDNN, HRV, TINN, PowLF, PowHF, and
D2 (r = −0.60, P = 0.033; r = −0.76, P = 0.003; r =
−0.61, P = 0.033; r = −0.65, P = 0.020; r = −0.55,
P = 0.058; and r = 0.67, P = 0.015, respectively)
and between TNF-α and the parameters REC, DET,
and ShEn (r = −0.59, P = 0.042; r = −0.60, P =
0.033; and r = −0.61, P = 0.031, respectively). Il-
13 was positively correlated with HF% (r = 0.62,
P = 0.029) and a negative trend was observed
between IFN-γ and LF/HF (r = −0.55, P = 0.062)
and between IL-10 and PowHF (r = −0.57, P =
0.075).
Discussion
The compromise of the ANS on Chagas
disease is a consequence of inflammatory and
degenerative processes of variable range and
extension that evolve from an acute pattern to
a fibrotic one affecting intrinsic ganglia and
neurons, and an isolated or combined alterations
of the sympathetic and parasympathetic related
to the physiopathologic processes of the heart
may occur.14–19 The pathogenesis of this disease
involves various related mechanisms mainly to the
Parasitary persistence and the immunomediated
myocardial scarring.11
The scarcity of parasites and the intensity and
extension of the lesions, as well as the extended
latency period, has led several authors to evaluate
the involvement of autoimmune factors on the
pathogenesis of the Chagasic lesion related to the
existence of a cross reaction between the auto-
logous and antigens components of T. cruzi.
This response against the antigens present on the
cardiac tissue could favor the development of the
most severe forms of the Chagasic cardiopathy.
The coexistence of the Parasitary persistence
and autoimmune phenomena could cause the
activating stimuli of specific T cells, and once
secreted, the inflammatory cytokines would be
capable of producing a cardiac lesion. This would
release autoantigen (such as the myosin) that is
recognized by another group of reactive group of
T cells and autoantibodies, contributing to larger
cardiac damage.11,12
In this sense, a low Parasitary load would
activate the Tregs suppressing an autoim-
munopathogenic response, but if the Parasitary
load or molecules that mimic Parasitary anti-
gens have high concentrations, the secretion
of pathogenic autoreactive T cells would be
stimulated.13 Therefore, the importance of these
patients having positive Parasitemia is in the
potential that they would have to evolve either
to a determined form of the disease or progress to
more severe presentations of the disease. However,
in our study, we did not find a correlation between
the Parasitemia and the alterations of the ANS. Our
study is the first literature to explore the role of the
Parasitemia on the autonomic cardiac dysfunction
of chronic Chagasic patients.
ANS Compromise in Chagas Disease
Alterations in the vagal subunit have been
identified early in Chagas disease in individu-
als with and without cardiomyopathy, showing
abnormal responses in autonomous tests under
stimuli, such as the Valsalva maneuver, the sinus
arrhythmia test, and orthostatic stress, revealing
diminished HRV indices. These indices were
evaluated using temporal, spectral, nonlinear,
and turbulent heart methods and have been
used as markers of cardiacrisk in several other
diseases.25–27, 30, 32–34, 36, 55–57 However, in Chagas
disease, no consensus has been achieved regarding
their use. Methods involving time-domain and
730 June 2011 PACE, Vol. 34
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icense
AUTONOMICAL AND IMMUNOLOGICAL RELATIONSHIP IN CHAGAS DISEASE
frequency spectrum in HRV analysis have been
used to evaluate the effect of specific treatment
in Chagas disease,27 but studies evaluating the
correlation between cardiac autonomic function
and the quantification of serum cytokines do not
exist in the literature.
It has been demonstrated that patients with
the indeterminate form of Chagas disease can
present both dysautonomia and left ventricular
diastolic dysfunction, though both are indepen-
dent phenomena.17,20 In order to evaluate the
involvement of the ANS, the behavior of indices
that measure HRV were initially studied to
compare patients with Chagas disease in the IChD
and ChHD groups with control subjects.
The results were divided according to types
of index (temporal, geometric, spectral, and
nonlinear) and the percentage of variation thereof,
in relation to the stimuli caused by facial cooling
and the Tilt test. In the literature, the use of
temporal and spectral indices in the analysis of
HRV has been reported; however, few studies
link these indices to geometric and nonlinear
indices. It is known that temporal and spectral
indices can be influenced by several factors,
including oscillation due to the baroreflex system;
age; sex; the time an examination is performed,
in the case of certain temporal and extrasystole
indices; and arrhythmias and noise, in the case
of spectral indices.37 At baseline, patients in the
ChHD group presented longer duration of mean
RR intervals and lower values of mean heart rate,
PowLF, PowHF, LF%, and ApEn in relation to
the groups IChD and CT. Bradycardia, increased
mean RR intervals, can be explained by alterations
in conduction that can be observed in these
patients and are associated with disturbances of
the stimuli originating in the sinus node. This
fact has been described by several authors and
some studies indicate an association between
bradycardia and the presence of circulating
autoantibodies to neurotransmitter antireceptors;
such antibodies would be markers of immune-
mediated cardiac autonomic dysfunction.31,58 The
reduction in spectral components of both HF
and LF was associated with diminished total
sympathetic-vagal response, without affecting the
balance of the same, while low values of ApEn
were associated with greater heart rate regularity,
leading to lower oscillation of the heart rate. This
has been recognized as a marker of sudden cardiac
death for several other diseases. These findings
strongly suggest a global autonomic dysfunction
involving both divisions of the sympathetic and
parasympathetic ANS in patients with Chagas
cardiomyopathy, corroborating the findings of
numerous other authors.33,37,50,59–64
Considering the IChD group, a decrease was
observed in the standard deviation of heart rate at
baseline, together with a lower rate of triangular
interpolation of RR intervals and lower power
of LF component compared with ChHD and CT,
facts which could indicate some impairment of
the sympathetic-vagal balance in the IChD group
at baseline. This finding has been previously
described and was related to findings of intrinsic
denervation demonstrated in the early stages of
cardiac Chagas disease.15,20,26,32,33,35,63 Despite the
differences verified in the LF and HF components
at baseline, suggesting some disturbance in
sympathetic and parasympathetic modulation, the
overall variability remained unchanged, as has
been previously demonstrated.35
Evaluation of the effect triggered by facial
cooling in all groups revealed that the mean
duration of RR intervals increased in all patients
in the study. However, the ChHD group showed
the lowest variation of this index compared with
CT. The ChHD group also presented less variation
in the center frequency and in the power of LF
and HF% components. This low variation could
indicate diminished sympathetic and parasympa-
thetic modulation in these patients, as affirmed
by several studies; moreover, the decrease in
sympathetic modulation has been related to the
risk of sudden cardiac death in heart failure.
Regarding the IChD group, in response to
passive standing, no significant differences were
verified; however, previous studies have observed
variations in parasympathetic modulation under
this stimulus. It is possible that the small sample
size of the current group of indeterminate form
Chagas disease patients could explain the dis-
crepancy between the present findings and those
reported in literature.19,21,60 Evaluation of the
effect triggered by passive standing in the groups
studied showed that the average RR interval
decreased in all the patients studied; however,
despite all the different indices studied, no statis-
tical significance was observed. This finding is in
disagreement with previous observations reported
by Vasconcelos and Junquerira,35 in which they
verified a lower chronotropic response in patients
with cardiac Chagas disease.27,35 Oliverira et al.
and Vasconcelos and Junquerira also observed
this alteration; however, this occurred following
the use of benznidazole and was associated with
worsening of the sympathetic response, probably
due to drug-induced neurotoxicity.27,35 Thus,
the analysis of HRV in these patients showed
diminished capacity to activate the sympathetic
response and signs of vagal impairment in both
groups, which was more intense in the ChHD
group than in IChD.
PACE, Vol. 34 June 2011 731
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icense
LLAGUNO, ET AL.
Evaluation of Serum Cytokine Concentrations
Several aspects may influence the evolution of
Chagas disease in infected individuals, including
parasite load, exposure time, reexposure, and
genetic factors inherent to host and parasite and
the host immune response.65 Therefore, the im-
portance of studying the production of cytokines is
to determine characteristics of immune response
in individuals with Chagas disease that help to
elucidate why they manifest the disease or not and
to characterize a profile of cytokine production
in different clinical forms during treatment with
benznidazole. An immunological evaluation of
patients in the IChD and ChHD groups was
performed and compared to controls in order to
differentiate them.
Analysis of the serum concentrations of
proinflammatory cytokines revealed a significant
difference in IL-17, TNF-α, and IFN-γ concen-
trations in the IChD group, while ChHD showed
an increase in IL-17 compared to CT. Regarding
antiinflammatory cytokines, patients in group FI
showed low concentrations of IL-4, IL-6, and
increased IL-13 compared to CT. The ChHD subset
showed low values of IL-4 and increased IL-
10 compared to controls. Although the ChHD
group produced low concentrations of IFN-γ
and increased IL-10, the IChD group presented
greater TNF-α and IFN-γ production compared
to the ChHD; however, none of differences were
statistically significant.
Previous studies have shown that the pres-
ence of increased concentrations of IL-10 and
IL-13 favors parasiteescape and persistence.
Moreover, this exacerbated production of IL-10
inhibits IFN-γ , the cytokine responsible for
macrophage activation, and parasite control and
death. Together, an inefficient cellular immune
response with a “shift” to a standard type 2
response could have led to parasite escape and
survival and further development of the disease.
Moreover, the actual levels of IL-17 obtained from
these patients suggest some kind of inflammation
or autoimmunity. An important fact, since these
patients were characterized as belonging to the
ChHD group, while presenting mild signs and
apparently without progression.66,67
In the IChD group, the activation of the pre-
dominantly inflammatory immune system, char-
acterized by the presence of high concentrations
of TNF-α, IFN-γ , and IL-17, with concomitant
expression of IL-13 and low concentrations of IL-6
and IL4, could suggest the presence of a predomi-
nance of the Th1 response. This fact is of interest,
because in these patients, an imbalance in this
response could drive disease progression toward
a symptomatic/determinate form. Although the
present results are in agreement with previous
studies,68,69 the relation between IFN-γ , TNF-α,
IL-10, and IL-4 is controversial, because while
some studies showed high concentrations of IFN-γ
and TNF-α, with low concentrations of IL-10 and
Il-4 associated with ChHD,70–74 other studies have
reported no difference in cytokine production
between the chronic forms of the disease.75,76
The role of IFN-γ has been discussed regard-
ing both the control and the evolution of cardiomy-
opathy. Some authors have hypothesized that
patients with the indeterminate form producing
high concentrations of cytokines could develop
the symptomatic clinical form more quickly than
those presenting low production, while those pro-
ducing high concentrations of IL-10 might be less
likely to develop the symptomatic/determinate
form of the disease. Moreover, individuals already
expressing a symptomatic/determinate form who
developed high production of IL-10 with low
concentrations of IFN-γ would achieve immune
regulation status.
Correlation between Serum Concentrations
of Cytokines and HRV Parameters
The influences of autonomic control on the
vascular system has caused interest among many
researchers and analysis of HRV reflects the effect
of sympathetic and parasympathetic sinus node
cells, while alterations in these systems have been
observed in Chagas patients with and without
cardiomyopathy.
The nervous system can reduce the pro-
duction of cytokines of the parasympathetic
pathway. Stimulation of the vagus nerve in several
experimental models studying sepsis, myocardial
ischemia, and pancreatitis has demonstrated this
fact. The mechanism of this vagal inhibition
involves neurotransmitters, such as acetylcholine,
and their receptors in macrophages. Experimental
studies involving administration of the alpha-7
subunit of the nicotinic acetylcholine receptor
demonstrated the inhibition of TNF-α, IL-1, Il-6,
and Il-8. Given these results and other observa-
tions, the connection between the brain, immune
system, and the parasympathetic system has been
called the cholinergic antiinflammatory pathway.
In Chagas disease, the study of this pathway
in individuals with and without cardiomyopathy
could determine the risk of progression.
Analysis of the IChD group revealed direct
correlations between inflammatory cytokines (IL-
1β, IL-12, IL-13, IL-17, and IFN-γ ) and different
spectral parameters related to the sympathetic-
vagal balance and negatively with parameters
related to the nonlinear global cardiac function,
while the antiinflammatory cytokines (IL-4 and IL-
10) only showed an inverse correlation with total
spectral indices. The ChHD group showed similar
732 June 2011 PACE, Vol. 34
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icense
AUTONOMICAL AND IMMUNOLOGICAL RELATIONSHIP IN CHAGAS DISEASE
differences, with the added presence of TNF-α,
which was negatively correlated with nonlinear
parameters related to global cardiac function.
The presence of IL-5 was inversely related to
the majority of spectral and temporal parameters
associated with vagal system.
Peripheral cytokine release in response to
infection or signs of injury causes the brain
to release acetylcholine through several routes,
including a vagal pathway. This action would
inhibit the release of cytokines from macrophages
by promoting a certain degree of protection against
damage caused by the release of cytokines. This
release of acetylcholine from the vagal efferent
terminal reduces the heart rate and increases HRV,
promoting a link between these two pathways.
Immunological and autonomic control in different
clinical forms of Chagas disease appears to
work similarly; however, minimal disturbances
between these systems may contribute to the
onset of cardiac abnormalities. Although TNF-α
is a cytokine often associated with the prediction
of cardiac risk, in the patients studied here, it
was increased in both groups, though in the
ChHD group, it was positively correlated with
cardiac function. In addition,the presence of IL-
5 was evident in ChHD; this IL is associated with
neutrophilia and eosinophilia, which participate
in the pathophysiology of the disease.
The present study has several limitations,
including the small patient sample, because the
inclusion criteria had to be precise to avoid
confounding factors, such as comorbidities or
other factors that would influence the results.
Due to the study design, it was not possible to
determine whether the alterations that influenced
HRV were due to inflammation or vice versa and
bidirectional associations are plausible.
Conclusions
In conclusion, Chagas disease patients with
the indeterminate form and with the symp-
tomatic/determinate clinical forms both presented
a lower vagal response at baseline and for facial
cooling. However, the ApEn in Chagas disease
patients with the symptomatic/determinate form
was diminished and this index in other heart
diseases has been associated with increased
cardiovascular risk for ventricular fibrillation and
sudden death.
Significant differences between inflammatory
cytokines and HRV parameters were observed be-
tween the indeterminate form and cardiac clinical
form groups and the controls, and a negative
correlation was determined principally between
inflammatory cytokines and nonlinear parameters
of HRV. However, the results presented are not
sufficient to elucidate the cause-effect relation;
thus, new studies are required to further elucidate
current understanding of the factors that influence
the progression of cardiomyopathy in Chagas
disease.
References
1. Dias JC, Silveira AC, Schofield CJ. The impact of Chagas disease
control in Latin America: A review. Mem Inst Oswaldo Cruz 2002;
97:603–612.
2. Coura JR. Transmission of chagasic infection by oral route in the
natural history of Chagas disease. Rev Soc Bras Med Trop 2006;
39(Suppl 3):113–117.
3. Chagas C. Nova tripanozomiase humana. Estudos sobre a morfolojia
e o ciclo evolutivo do Schizotrypanum cruzi n.gen.,n. sp., ajente
etiolojico de nova entidade mórbida do homen. Mem Inst Oswaldo
Cruz 1909; I:5–61.
4. Prata A. Clinical and epidemiological aspects of Chagas disease.
Lancet infect Dis 2001; 1:92–100.
5. Rassi A Jr, Rassi A, Little WC, Xavier SS, Rassi SG, Rassi AG, Rassi
GG, et al. Development and validation of a risk score for predicting
death in Chagas’ heart disease. New Engl J Med 2006; 355:799–808.
6. Schmunis GA. The globalization of Chagas disease. ISBT Sci Ser
2007; 2:6–11.
7. Maguire JH. Chagas’ disease–can westop the deaths? New Engl J
Med 2006; 355:760–761.
8. Brener Z, Gazzinelli RT. Immunological control of Trypanosoma
cruzi infection and pathogenesis of Chagas’ disease. Int Arch
Allergy Immunol 1997; 114:103–110.
9. Morel CM, Lazdins J. Chagas disease. Nat Rev Microbiol 2003; 1:14–
15.
10. Higuchi Mde L, Benvenuti LA, Martins Reis M, Metzger M.
Pathophysiology of the heart in Chagas’ disease: Current status and
new developments. Cardiovasc Res 2003; 60:96–107.
11. Marin-Neto JA, Cunha-Neto E, Maciel BC, Simoes MV. Pathogenesis
of chronic Chagas heart disease. Circulation 2007; 115:1109–
1123.
12. Cunha-Neto E, Teixeira PC, Nogueira LG, Mady C, Lanni B,
Stolf N, Fiorelli A, et al. New concepts on the pathogenesis of
chronic Chagas cardiomyopathy: Myocardial gene and protein
expression profiles. Rev Soc Bras Med Trop 2006; 39(Suppl 3):59–
62.
13. Vray B, Camby I, Vercruysse V, Mijatovic T, Bovin NV, Ricciardi-
Castagnoli P, Kaltner H, et al. Up-regulation of galectin-3 and
its ligands by Trypanosoma cruzi infection with modulation of
adhesion and migration of murine dendritic cells. Glycobiology
2004; 14:647–657.
14. Köberle F. Pathology and pathological anatomy of Chagas’ disease.
Bol Oficina Sanit Panam 1961; 51:404–428.
15. Lopes ER, Chapadeiro E, Andrade ZA, Almeida HO, Rocha A.
Pathological anatomy of hearts from asymptomatic Chagas disease
patients dying in a violent manner. Mem Inst Oswaldo Cruz 1981;
76:189–197.
16. Köberle F. Chagas disease: A disease of the peripheral autonomic
nervous system. Wien Klin Wochenschr 1956; 68:333–339.
17. Miziara AN, Molina RJ, Ferreira BD, Barbosa CJ, Dias da Silva VJ,
Prata A, Correia D. Cardiac autonomic modulation in hypertensive
patients with Chagas’ disease. Acta tropica 2006; 97:188–195.
18. Natelson BH, Goldwater DJ, De Roshia C, Levin BE. Visceral
predictors of cardiovascular deconditioning in late middle-aged
men. Aviat Space Environ Med 1985; 56:199–203.
19. Junqueira LF Jr, Soares JD. Impaired autonomic control of heart
interval changes to Valsalva manoeuvre in Chagas’ disease without
overt manifestation. Auton Neurosci 2002; 97:59–67.
20. Marin-Neto JAB-M G, Pazin-Filho A, Simoes MV, Maciel BC.
Cardiac autonomic impairment and early myocardial damage
involving the right ventricle are independent phenomena in Chagas’
disease. Int J Cardiol 1998; 65:261–269.
21. Guzzetti S, Josa D, Pecis M, Bonura L, Prosdocimi M, Malliani A.
Effects of sympathetic activation on heart rate variability in Chagas’
patients. J Auton Nerv Syst 1990; 30(Supp l):S79–S81.
22. Lavadens R, Palmero E. Bradycardia-tachycardia syndrome in
chronic Chagas’ cardiopathy. Arq Bras Cardiol 1984; 42:345–350.
PACE, Vol. 34 June 2011 733
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icense
LLAGUNO, ET AL.
23. Correia D, Junqueira LF, Jr, Molina RJ, Prata A. Cardiac autonomic
modulation evaluated by heart interval variability is unaltered but
subtly widespread in the indeterminate Chagas’ disease. Pacing Clin
Electrophysiol 2007; 30:772–780.
24. Correia D, Miziara Ade N, Molina RJ, Ferreira BD, Barbosa CJ, da
Silva VJ, Prata A. Heart rate variability in Chagas’ patients with
and without hypertension. Rev Soc Bras Med Trop 2003; 36(Suppl
2):5–10.
25. Molina RB, Matsubara BB, Hueb JC, Zanati SG, Meira DA, Cassolato
JL, Paiva SA, et al. Dysautonomia and ventricular dysfunction in the
indeterminate form of Chagas disease. Int J Cardiol 2006; 113:188–
193.
26. Oliveira E, Ribeiro AL, Assis Silva F, Torres RM, Rocha MO. The
Valsalva maneuver in Chagas disease patients without cardiopathy.
Int J Cardiol 2002; 82:49–54.
27. Oliveira L, Correia D, Miziara A, Resende LA. Heart rate variability
in chronic Chagas patients before and after treatment with
benzidazole. Auton Neursci 2010; 158:118–122.
28. Resende LA, Carneiro AC, Ferreira BD, da Silva RA, da Silva
VJ, Prata A, Correia D. Temporal analysis of cardiac frequency
variability in basal condition in elderly chagasic subjects in
indeterminate form in endemic area. Rev Soc Bras Med Trop 2003;
36:703–706.
29. Resende LA, Molina RJ, Ferreira BD, Carneiro AC, Ferreira LA, da
Silva VJ, Prata A, et al. Cardiac autonomic function in chagasic
elderly patients in an endemic area: A time and frequency domain
analysis approach. Auton Neurosci 2007; 131:94–101.
30. Ribeiro AL, Ferreira LM, Oliveira E, Cruzeiro PC, Torres RM, Rocha
MO. Active orthostatic stress and respiratory sinus arrhythmia in
patients with Chagas’ disease with preserved left ventricular global
systolic function. Arq Bras Cardiol 2004; 83:40–44; 35–49.
31. Ribeiro AL, Gimenez LE, Hernandez CC, de Carvalho AC, Teixeira
MM, Guedes VC, Barros MV, et al. Early occurrence of anti-
muscarinic autoantibodies and abnormal vagal modulation in
Chagas disease. Int J Cardiol 2007; 117:59–63.
32. Ribeiro AL, Lombardi F, Sousa MR, Lins Barros MV, Porta A, Costa
Val Barros V, Gomes ME, et al. Power-law behavior of heart rate
variability in Chagas’ disease. Am J Cardiol 2002; 89:414–418.
33. Ribeiro AL, Moraes RS, Ribeiro JP, Ferlin EL, Torres RM,
Oliveira E, Rocha MO. Parasympathetic dysautonomia precedes left
ventricular systolic dysfunction in Chagas disease. Am Heart J 2001;
141:260–265.
34. Sousa L, da Costa Rocha MO, Britto RR, Lombardi F, Ribeiro AL.
Chagas disease alters the relationship between heart rate variability
and daily physical activity. Int J Cardiol 2009; 135:257–259.
35. Vasconcelos DF, Junqueira LF Jr. Distinctive impaired cardiac
autonomic modulation of heart rate variability in chronic Chagas’
indeterminate and heart diseases. J Electrocardio 2009; 42:281–
289.
36. Villar JC, Leon H, Morillo CA. Cardiovascular autonomic function
testing in asymptomatic T. cruzi carriers: A sensitive method to
identify subclinical Chagas’ disease. Int J Cardiol 2004; 93:189–195.
37. Task-Force. Heart rate variability. Standards of measurement,
physiological interpretation, and clinical use. Task Force of the
European Society of Cardiology and the North American Society of
Pacing and Electrophysiology. Eur Heart J 1996; 17:354–381.
38. Morey SS. ACC/AHA guidelines for ambulatory ECG. American
College of Cardiology/American Heart Association. Am Fam
Physician 2000; 61 884:887–888.
39. Junqueira-Junior LF. Disfunção autonômica cardı́aca. In: Porto
(Porto CC, ed.): Doenças do Coração Prevenção e Tratamento. Rio
de Janeiro, Guanabara-Koogan, 1998; pp. 306–311.
40. Correia D. Avaliação clı́nico-funcional, bioquı́mica e imunológica
do sistema nervoso autônomo em residentes em área endêmica
da doença de Chagas. Faculdade de Medicina. Belo Horizonte,
Universidade Federal de Minas Gerais, 2000; pp. 233.
41. Dekker JM, Schouten EG, Klootwijk P, Pool J, Swenne CA,
Kromhout D. Heart rate variability from short electrocardiographic
recordings predicts mortality from all causes in middle-aged and
elderly men. The Zutphen Study. Am J Epidemiol 1997; 145:899–
908.
42. Tsuji H, Venditti FJ, Jr, Manders ES, Evans JC, Larson MG, Feldman
CL, Levy D. Reduced heart rate variability and mortality risk in
an elderly cohort. The Framingham Heart Study. Circulation 1994;
90:878–883.
43. Wichterle D, Simek J, La Rovere MT, Schwartz PJ, Camm AJ,
Malik M. Prevalent low-frequency oscillation of heart rate: Novel
predictor of mortality after myocardial infarction. Circulation 2004;
110:1183–1190.
44. Tulppo M, Huikuri HV. Origin and significance of heart rate
variability. J Am Coll Cardiol 2004; 43:2278–2280.
45. Ridker PM, Rifai N, Pfeffer M, Sacks F, Lepage S, Braunwald
E. Elevation of tumor necrosis factor-alpha and increased risk of
recurrent coronary events after myocardial infarction.Circulation
2000; 101:2149–2153.
46. Ridker PM, Rifai N, Stampfer MJ, Hennekens CH. Plasma
concentration of interleukin-6 and the risk of future myocardial
infarction among apparently healthy men. Circulation 2000;
101:1767–1772.
47. Janszky I, Ericson M, Lekander M, Blom M, Buhlin K, Georgiades A,
Ahnve S. Inflammatory markers and heart rate variability in women
with coronary heart disease. J Intern Med 2004; 256:421–428.
48. Haensel A, Mills PJ, Nelesen RA, Ziegler MG, Dimsdale JE.
The relationship between heart rate variability and inflammatory
markers in cardiovascular diseases. Psychoneuroendocrinology
2008; 33:1305–1312.
49. Malliani A, Lombardi F, Pagani M. Power spectrum analysis of heart
rate variability: A tool to explore neural regulatory mechanisms. Br
Heart J 1994; 71:1–2.
50. Malik M, Camm AJ, Janse MJ, Julian DG, Frangin GA, Schwartz PJ.
Depressed heart rate variability identifies postinfarction patients
who might benefit from prophylactic treatment with amiodarone: A
substudy of EMIAT (The European Myocardial Infarct Amiodarone
Trial). J Am Coll Cardiol 2000; 35:1263–1275.
51. Chiari E, Dias JC, Lana M, Chiari CA. Hemocultures for the
parasitological diagnosis of human chronic Chagas’ disease. Rev
Soc Bras Med Trop 1989; 22:19–23.
52. Camargo EP. Growth and differentiation in Trypanosoma Cruzi. I.
Origin of metacyclic trypanosomes in liquid media. Rev Inst Med
Trop Sao Paulo 1964; 12:93–100.
53. Gomes ML, Macedo AM, Vago AR, Pena SD, Galvao LM, Chiari E.
Trypanosoma cruzi: Optimization of polymerase chain reaction for
detection in human blood. Exp Parasitol 1998; 88:28–33.
54. Degrave W, Fragoso SP, Britto C, van Heuverswyn H, Kidane GZ,
Cardoso MA, Mueller RU, et al. Peculiar sequence organization
of kinetoplast DNA minicircles from Trypanosoma cruzi. Mol
Biochem Parasitol 1988; 27:63–70.
55. Tundo F, Lombardi F, Rocha MC, Botoni F, Schmidt G, Barros VC,
Muzzi B, et al. Heart rate turbulence and left ventricular ejection
fraction in Chagas disease. Europace 2005; 7:197–203.
56. Ribeiro AL, Schmidt G, Sousa MR, Lombardi F, Gomes ME, Perez
AA, Barros MV, et al. Heart rate turbulence in Chagas disease.
Pacing Clin Electrophysiol 2003; 26:406–410.
57. de Sousa MR, Huikuri HV, Lombardi F, Perez AA, Gomes ME,
Barros MV, Barros VC, et al. Abnormalities in fractal heart rate
dynamics in Chagas disease. Ann Noninvasive Electrocardiol 2006;
11:P145–P153.
58. Goin JC, Borda ES, Auger S, Storino R, Sterin-Borda L. Cardiac
M(2) muscarinic cholinoceptor activation by human chagasic
autoantibodies: Association with bradycardia. Heart (Br Card Soc)
1999; 82:273–278.
59. Pincus SM. Approximate entropy as a measure of system
complexity. Proc Natl Acad Sci USA 1991; 88:2297–2301.
60. La Rovere MT, Schwartz PJ. Counting heart beats: A peephole into
prediction of sudden and nonsudden cardiac death. J Cardiovasc
Electrophysiol 2003; 14:174–175.
61. Maestri R, Pinna GD, Accardo A, Allegrini P, Balocchi R, D’Addio
G, Ferrario M, et al. Nonlinear indices of heart rate variability
in chronic heart failure patients: Redundancy and compara-
tive clinical value. J Cardiovasc Electrophysiol 2007; 18:425–
433.
62. Makikallio TH, Ristimae T, Airaksinen KE, Peng CK, Goldberger
AL, Huikuri HV. Heart rate dynamics in patients with stable angina
pectoris and utility of fractal and complexity measures. Am J Cardiol
1998; 81:27–31.
63. Palmero HA, Caeiro TF, Iosa D. Prevalence of slow heart rates
in chronic Chagas’ disease. Am J Trop Med Hyg 1981; 30:1179–
1182.
64. Diaz JO, Makikallio TH, Huikuri HV, Lopera G, Mitrani RD,
Castellanos A, Myerburg RJ, et al. Heart rate dynamics before the
spontaneous onset of ventricular tachyarrhythmias in Chagas’ heart
disease. Am J Cardiol 2001; 87(A1110):1123–1125.
65. Dutra WO, Rocha MO, Teixeira MM. The clinical immunology of
human Chagas disease. Trends Parasitol 2005; 21:581–587.
66. Lannes-Vieira J. Trypanosoma cruzi-elicited CD8+ T cell-mediated
myocarditis: Chemokine receptors and adhesion molecules as
potential therapeutic targets to control chronic inflammation? Mem
Inst Oswaldo Cruz 2003; 98:299–304.
734 June 2011 PACE, Vol. 34
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icense
AUTONOMICAL AND IMMUNOLOGICAL RELATIONSHIP IN CHAGAS DISEASE
67. Higuchi Mde L. Chronic chagasic cardiopathy: The product of a
turbulent host-parasite relationship. Rev Inst Med Trop Sao Paulo
1997; 39:53–60.
68. Laucella SA, Postan M, Martin D, Hubby Fralish B, Albareda
MC, Alvarez MG, Lococo B, et al. Frequency of interferon-
gamma -producing T cells specific for Trypanosoma cruzi inversely
correlates with disease severity in chronic human Chagas disease. J
Infect Dis 2004; 189:909–918.
69. Albareda MC, Laucella SA, Alvarez MG, Armenti AH, Bertochi G,
Tarleton RL, Postan M. Trypanosoma cruzi modulates the profile
of memory CD8+ T cells in chronic Chagas’ disease patients. Int
Immunol 2006; 18:465–471.
70. D’Avila DA, Guedes PM, Castro AM, Gontijo ED, Chiari E, Galvao
LM. Immunological imbalance between IFN-gamma and IL-10
levels in the sera of patients with the cardiac form of Chagas disease.
Mem Inst Oswaldo Cruz 2009; 104:100–105.
71. Abel LC, Rizzo LV, Ianni B, Albuquerque F, Bacal F, Carrara D,
Bocchi EA, et al. Chronic Chagas’ disease cardiomyopathy patients
display an increased IFN-gamma response to Trypanosoma cruzi
infection. J Autoimmun 2001; 17:99–107.
72. Correa-Oliveira R, Gomes J, Lemos EM, Cardoso GM, Reis DD,
Adad S, Crema E, et al. The role of the immune response on the
development of severe clinical forms of human Chagas disease.
Mem Inst Oswaldo Cruz 1999; 94(Suppl 1):253–255.
73. Ribeirao M, Pereira-Chioccola VL, Renia L, Augusto Fragata Filho
A, Schenkman S, Rodrigues MM. Chagasic patients develop a type
1 immune response to Trypanosoma cruzi trans-sialidase. Parasite
Immunol 2000; 22:49–53.
74. Gomes JA, Bahia-Oliveira LM, Rocha MO, Martins-Filho OA,
Gazzinelli G, Correa-Oliveira R. Evidence that development of
severe cardiomyopathy in human Chagas’ disease is due to a
Th1-specific immune response. Infect Immun 2003; 71:1185–
1193.
75. Perez-Fuentes R, Lopez-Colombo A, Ordonez-Toquero G, Gomez-
Albino I, Ramos J, Torres-Rasgado E, Salgado-Rosas H, et al.
Correlation of the serum concentrations of tumour necrosis
factor and nitric oxide with disease severity in chronic Chagas
disease (American trypanosomiasis). Ann Trop Med Parasitol 2007;
101:123–132.
76. Ward LS, Guariento ME, Fernandes GA, Maciel RM. Serum
cytokines in chronic Chagas’ disease. Rev Soc Bras Med Trop 1999;
32:285–289.
PACE, Vol. 34 June 2011 735
 15408159, 2011, 6, D
ow
nloaded from
 https://onlinelibrary.w
iley.com
/doi/10.1111/j.1540-8159.2010.03025.x by U
FT
M
 - U
niversidade Federal do T
riangulo M
ineiro, W
iley O
nline L
ibrary on [17/01/2024]. See the T
erm
s and C
onditions (https://onlinelibrary.w
iley.com
/term
s-and-conditions) on W
iley O
nline L
ibrary for rules of use; O
A
 articles are governed by the applicable C
reative C
om
m
ons L
icense