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Original article doi:10.1093/rheumatology/kev376
In juvenile dermatomyositis, heart rate variability
is reduced, and associated with both cardiac
dysfunction and markers of inflammation: a
cross-sectional study median 13.5 years after
symptom onset
Zoltan Barth
1,2,3
, Birgit Nomeland Witczak
1
, Thomas Schwartz
1,4,5
,
Knut Gjesdal
4,6
, Berit Flatø
4,5
, Akos Koller
2
, Helga Sanner
5
and Ivar Sjaastad
1,6
Abstract
Objectives. Low heart rate variability (HRV) is a well-established predictor of cardiac death. The aim of
this study was to investigate arrhythmias and HRV in patients with JDM, and associations between HRV
and inflammatory markers, echocardiographic measurements and disease parameters.
Methods. Fifty-five patients with JDM were examined 234 years (median 13.5 years) after disease onset,
and compared with 55 age and sex matched controls. Holter ECG monitoring and echocardiography were
analysed blinded to patient information. Arrhythmia and HRV (six parameters) were analysed by standard
software, finally adjudicated by an experienced cardiologist. Markers of inflammation (ESR, high sensitivity
(hs)CRP and cytokines) were analysed. Disease activity and organ damage were assessed by clinical
examination at follow-up and retrospectively by chart review.
Results. In two out of six HRV parameters, JDM patients had lower values than controls. No difference in
arrhythmias was found between the groups. In patients, but not in controls, there were significant negative
correlations between five out of six HRV parameters, and ESR and hsCRP (Spearman correlation coef-
ficient, 0.306 to 0.470; P, 0.023 to <0.001). Also, in patients, negative correlations were found between
three out of six HRV parameters and systolic and diastolic function. Active disease and low HRV were
associated. Patients with hsCRP in the highest quartile (Q4) had lower HRV in all parameters compared
with those in pooled Q13(P<0.001).
Conclusion. JDM patients had reduced HRV, which was associated with elevated inflammatory markers,
active disease and reduced myocardial function. This suggests reduced vagal control of the heart; further
studies are needed to determine whether this is also associated with cardiac morbidity or mortality.
Key words: paediatric rheumatology, juvenile dermatomyositis, heart rate variability, arrhythmia, echocardiog-
raphy, autonomic impairment, cardiac dysfunction.
Rheumatology key messages
.Heart rate variability is decreased in patients with JDM compared with controls.
.Lower heart rate variability in JDM is associated with systolic and diastolic cardiac dysfunction.
.Heart rate variability in JDM patients is associated with high-sensitivity CRP and active disease.
1
Institute for Experimental Medical Research, Oslo University
Hospital-Ulleva
˚l and University of Oslo, Oslo, Norway,
2
Department
of Pathophysiology and Gerontology, Medical School, University
of Pe
´cs, Pe
´cs, Hungary,
3
Department of Health sciences,
Bjørknes College, Oslo, Norway,
4
Institute for Clinical Medicine,
Medical Faculty, University of Oslo, Oslo, Norway,
5
Section of
Rheumatology, Oslo University Hospital-Rikshospitalet, Oslo,
Norway and
6
Department of Cardiology, Oslo University Hospital-
Ulleva
˚l, Oslo, Norway
*Correspondence to: Ivar Sjaastad, Institute for Experimental Medical
Research, Oslo University Hospital, Ulleva
˚l 0027 Oslo, Norway.
E-mail: ivar.sjaastad@medisin.uio.no
Submitted 23 March 2015; revised version accepted
16 September 2015
!The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com 1
RHEUMATOLOGY 284
CLINICAL
SCIENCE
Rheumatology Advance Access published October 24, 2015
at University of Oslo Library on October 24, 2015http://rheumatology.oxfordjournals.org/Downloaded from
Introduction
JDM is a systemic autoimmune disease of unknown aeti-
ology, characterized primarily by weakness in proximal
muscles and pathognomonic skin rashes. Other organ
systems may also be affected, such as the respiratory
and cardiovascular systems [1]. In our established
Norwegian JDM cohort, systolic and diastolic dysfunction
have previously been demonstrated by echocardiography
[2, 3].
Long-term ECG (Holter ECG) documents arrhythmias
and heart rate variability (HRV), the latter reflecting the
autonomic nervous control of the heart rhythm. The inter-
vals between successive heart beats in the long-term
ECG can be analysed by conventional statistics (time
domain) or by fast-Fourier transformation (frequency
domain) analyses. Both provide information on the sym-
pathetic and parasympathetic influence. In general, high
vagal modulation of the heart rate (HR) is associated with
higher survival [4]. Low HRV is an independent predictor
of adverse outcomes including cardiovascular death both
in apparently healthy individuals and among those with
established cardiovascular disease [5].
HRV is scarcely investigated in patients with childhood
rheumatic diseases. However, low HRV is associated with
preclinical cardiac involvement in SSc [6]. Furthermore,
increased risk for sudden cardiac death in RA and SLE
is most probably related to fatal arrhythmias due to severe
autonomic dysfunction, as may be indicated by low HRV
[7].
A high degree of inflammation is associated with low
HRV in several cardiovascular [8] and some rheumatic
disorders (RA [9,10], SLE [11, 12] and PsA [13]), and
even in healthy individuals [14, 15]. There are no studies
available on HRV in patients with adult or juvenile der-
mato- and polymyositis. Thus, the primary aim of the pre-
sent study was to assess HRV in JDM patients and sex-
and age-matched controls, and furthermore, to investi-
gate the possible associations between HRV and disease
parameters, including inflammatory markers and meas-
ures of cardiac dysfunction.
Methods
Patients and controls
Inclusion criteria were a probable or definitive diagnosis of
DM [16], disease onset before the age of 18 years, 524
months from symptom onset to follow-up and age at
follow-up 56 years. An initial cohort of 66 JDM patients
diagnosed between January 1970 and June 2006 in
Norway was identified from hospital records [17, 18].
Four patients were deceased, another three did not
want to participate, and in four of the patientcontrol
pairs, Holter data were not available in the relevant
period. The remaining 55 patients represent our study
population. One sex- and age-matched control per patient
was randomly drawn from the National Population
Register. Controls with clinical lung or heart diseases
were excluded; in total only one control was excluded (a
subject with atrial fibrillation). Informed consent was ob-
tained from all participants (and their parents, if age <16
years), according to the Declaration of Helsinki. The study
was approved by the Regional Ethics Committee, Helse
Sør-Øst.
Data collection and clinical measurements
One clinical examination of all patients (at follow-up) and
matched controls was performed by one physician (HS) at
Oslo University Hospital, Rikshospitalet (OUS) between
September 2005 and May 2009. Clinically inactive disease
was defined by the proposed PRINTO criteria [19] as pre-
viously described [20], and patients were classified as
JDM-inactive or JDM-active. Disease activity was also
measured by DAS for JDM (range 020, 0 defines no ac-
tivity) [21] and cumulative organ damage by myositis
damage index (MDI, range 035/40) [22] Data on disease
onset, course, comorbidity and use of medication includ-
ing cumulative prednisolone dose were obtained retro-
spectively from the medical records at OUS or, when
necessary, from other hospitals.
Disease onset was defined as the time of the first
muscle or skin symptom, and follow-up time as the time
from disease onset to the follow-up examination. The
blood samples were collected from non-fasting patients
and controls. Some of the data have previously been pub-
lished, but are included due to a different number of
patientcontrol pairs, or for the sake of clarity and
completeness.
Holter ECG recording
All patients underwent two-channel, 24 h ambulatory
Holter monitoring, using Vista Axess Holter digital re-
corders and analysed with Holtersoft Ultima version
2.4.4 (Novacor, Rueil-Malmaison, France). In order to
avoid the disturbing effect of variable daily activity, the
period between 11 p.m. and 7 a.m. was analysed both
in patients and controls, blinded to subjects’ identity.
This period was available in 55 patientcontrol pairs.
Heart rate variability and arrhythmia analysis
The recordings were edited to exclude artefacts and to
validate the automated annotations. Only periods without
noisy signals were used for HRV analysis. Intervals be-
tween ectopic beats, between ectopic and normal
beats, and artefacts were rejected by a template recogni-
tion algorithm. The calculation of internationally accepted
time- and frequency-domain parameters [4] was per-
formed by the software package.
The time-domain parameters used are as follows:
standard deviation of all normal-to-normal QRS (NN) inter-
vals (SDNN; ms); SDNN corrected for HR (cSDNN; ms;
cSDNN = SDNN/e(HR/58.8); standard deviation of the
averages of NN intervals in all 5 min segments of the
entire recording (SDANN; ms); the root mean square of
the successive differences between adjacent NN intervals
(RMSSD; ms); NN50 count (pNN50; %; number of pairs of
adjacent NN intervals differing by >50 ms in the entire
recording divided by the total number of all NN intervals).
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The frequency-domain parameters are as follows: low fre-
quency (LF) power (ms
2
; power in the 0.040.15 Hz range);
high frequency (HF) power (ms
2
; power in the 0.150.4 Hz
range).
SDNN and SDANN are the most frequently used and
simplest time-domain parameters, reflecting the overall
variability of sinus cycle length [23]. A recent article has
shown that HRV is inextricably linked to HR in an expo-
nential manner [24], where the lower the HR, the greater
the HRV. In our article, we use the SDNN values corrected
by the HR (cSDNN) [24] in order to examine the HRV in-
dependently from HR. RMSSD and pNN50 reflect vagal
activity and are measures of parasympathetic tone. LF
reflects both sympathetic and vagal tone and correlates
with baroreflex sensitivity. HF is mainly supported by
vagal activity.
Arrhythmic beats were detected by the computer,
verified visually and classified as either supraventricular
(SVES) or ventricular (VES) beats. A pause was con-
sidered significant if longer than 3 s.
Echocardiography
Two-dimensional, M-mode and Doppler echocardio-
graphy were performed at time of follow-up examination
and analysed blinded to patient/control identity and pa-
tient information, as previously described [25]. A minimum
of three cardiac cycles were recorded, analysed and
averaged.
Early diastolic tissue velocities (e0) in the mitral ring in
two- and four-chamber views were recorded and aver-
aged; a low value suggests diastolic dysfunction [2, 26].
Long axis strain (LAS) is mitral annulus displacement as a
percentage of end-diastolic left ventricular length, and
was measured as previously described [3, 27]. A low
value suggests systolic dysfunction.
Inflammatory markers and cytokines
At follow-up examination, non-fasting, venous blood sam-
ples were collected and stored at 80C. ESR was mea-
sured, and serum concentration of CRP analysed by a
high-sensitivity method (high sensitivity (hs)CRP). Based
on previously published results from the same participants
[28, 29], IL-6, monocyte chemotactic protein-1 (MCP-1;
CCL2) and eotaxin (CCL11) were selected for association
analysis with HRV. TNFawas included as well, since it
differed between patients and controls in the current
data set. The Luminex based analysis of cytokine levels
was performed as previously described [28, 29].
Statistical analysis
Differences between patients and matched controls were
tested by paired sample t-test. Differences between
patients with active and inactive disease, furthermore,
between high and low hsCRP groups, were tested by in-
dependent sample t-test (normally and continuously dis-
tributed variables). It is not reasonable to believe that
patients would have better values than their controls,
and thus one-tailed tests were used to compare HRV
parameters, cytokines, hsCRP and ESR values in patients
and controls. Two-tailed tests were used for all other cal-
culations, and P <0.05 was considered significant.
Correlations were determined by the Spearman correl-
ation coefficient (r
sp
). Due to the hypothesis generating
nature of the study, and the limited number of patients
available in Norway, we were unable to do statistical cor-
rections for multiple comparisons. IBM SPSS Statistics v.
22.0 (IBM, Armonk, NY, USA).
Results
Clinical characteristics in JDM patients and controls
Table 1 shows general clinical characteristics in patients
with JDM and sex- and age-matched controls. The follow-
up time in patients was median 13.5 (range 234) years,
mean 16.0 (SD 10.2) years. No significant difference in
BMI or in the prevalence of smoking was found between
the groups.
Holter parameters in JDM patients and controls at
follow-up
Average HR was comparable between patients and
controls (Table 2). The HRV analysis revealed that the
time-domain parameter cSDNN was 17% decreased in
patients compared with controls (P <0.032). Among
frequency-domain parameters, we found 22% lower LF
in patients compared with controls (P <0.031) (Table 2).
There were no significant differences in the number of
premature SVES or VES between patients and controls
(Table 2). No patients or controls had significant pauses
or sustained tachycardia.
Other cardiac parameters
At follow-up, and as previously shown (albeit in a some-
what different JDM population) [2, 3], left ventricular LAS
and e0were lower in patients than controls (Table 2),
suggesting both systolic and diastolic left ventricular dys-
function. Also, systolic blood pressure values were higher
in patients than controls. Six patients, but no controls, had
hypertension.
Inflammatory markers and cytokines in patients and
controls
ESR was higher in patients than controls (P <0.035), but
hsCRP was not significantly different (Table 2). The levels
of TNFa, IL-6, MCP-1 and eotaxin were 40%, 71%, 29%
and 31% higher in patients than controls, respectively (all
P<0.05).
Correlations between HR variability and
echocardiographic, laboratory and clinical parameters
We analysed the correlation between HRV time- and
frequency-domain parameters and the following para-
meters: e0and LAS, inflammatory markers, cytokines,
DAS total and MDI. The HRV variables showing significant
associations with disease variables in patients are shown
in Table 3. Significant correlations were found between
the HRV parameters reflecting predominantly vagal activ-
ity (RMSSD, pNN50, HF) and LAS as well as e0. Weak to
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moderate negative correlations were found between five
out of six HRV parameters and ESR and hsCRP. Higher
MCP-1 and eotaxin levels correlated with two and three
HRV parameters, respectively.
MDI and DAS at follow-up did not correlate with any
HRV parameters (data not shown). In SF 36, the physical
component score correlated negatively only with HR
(r
sp
=0.393, P <0.008).
TABLE 1Characteristics of JDM patients and their matched controls at follow-up
Characteristics JDM patients Controls
Sex, M/F, n 21/34 21/34
Duration from disease onset, years 13.5 (2.034.3) NA
Age, years 19.8 (6.748.9) 20.1 (6.248.9)
BMI, kg/m
2
22.2 (4.9) 22.5 (4.6)
Daily smokers
a
, n (%) 13 (23) 11 (20)
Calcinosis during disease course, n (%) 26 (47.3) NA
Cumulative prednisolone dose, g 7.8 (0.027.3) NA
Active disease, n (%) 28 (51) NA
MDI total 4.1 (2.9) NA
DAS total 4.8 (3.0) NA
DAS skin 3.22 (2.2) NA
DAS muscle 1.55 (1.8) NA
Values are mean (SD) or median (range) unless otherwise indicated. n: number; n = 55 for patients and controls, unless
otherwise stated;
a
n = 47 for patients and controls aged >14 years. NA: not applicable.
TABLE 2Cardiovascular and inflammatory parameters and cytokines in patients and controls
Cardiac parameters JDM patients Controls P value
Holter parameters
Average heart rate 67.9 (10.0) 66.9 (15.3) 0.318
cSDNN, ms 40.1 (16.7) 46.8 (24) 0.032
SDANN, ms 82 (32.4) 91.7 (41) 0.063
RMSSD, ms 62.7 (36.1) 68.5 (34.2) 0.166
pNN50, % 24.8 (18.5) 30.1 (19) 0.051
LF, ms
2
1581 (1114) 2034 (1495) 0.031
HF, ms
2
1292 (1621) 1310 (1052) 0.471
Total SVES 12 (01013) 17 (0430) 0.141
Total VES 0 (03624) 0 (01794) 0.321
Echocardiographic parameters
LAS, % 16.6 (2.5) 17.7 (2.1) 0.001
e0, cm/s
a
11.5 (2.6) 12.6 (2) 0.004
BP systolic, mmHg
b
117 (22) 110 (12) 0.019
BP diastolic, mmHg
b
69 (13) 67 (9) 0.138
Hypertension, n (%) 6 (11) 0 (0) 0.007
Inflammatory parameters
ESR
c
, mm/h 7.7 (6.3) 5.8 (4.9) 0.035
hsCRP, mg/l 2.2 (3.3) 1.6 (3.3) 0.168
Cytokines
TNFa
d
, pg/ml 23 (22.9) 16.5 (7.3) 0.032
IL-6
d
, pg/ml 6.9 (11) 4 (2) 0.035
MCP-1
d
, pg/ml 32.8 (20.1) 25.4 (11.6) 0.01
Eotaxin
d
, pg/ml 139 (107) 107 (65) 0.028
Values are mean (SD) or median (range) unless otherwise indicated. n: number; n = 55 for patients and controls respectively,
unless otherwise stated;
a
n = 52;
b
n = 54;
c
n = 51;
d
n = 50. cSDNN: standard deviation of all normal-to-normal intervals
corrected for the heart rate; SDANN: standard deviation of the averages of normal-to-normal intervals in all 5 min segments of
the entire recording; RMSSD: root mean square of the successive differences between adjacent normal-to-normal intervals;
pNN50: number of pairs of adjacent NN intervals differing by more than 50 ms in the entire recording divided by the total
number of all NN intervals; LF: low frequency; HF: high frequency; SVES, supraventricular extrasystole; VES, ventricular
extrasystole; LAS: long axis strain; e0: early diastolic tissue velocity; BP: blood pressure; hsCRP: high-sensitivity CRP;
MCP-1: monocyte chemotactic protein-1.
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In controls, no significant correlation was found be-
tween HRV and the above-described echocardiographic
measurements, inflammatory markers or cytokines (data
not shown), except a correlation between HF and e0(r
sp
=
0.312, P = 0.023).
Cardiac and laboratory parameters in JDM-active and
JDM-inactive patients
When comparing JDM-active with JDM-inactive patients,
follow-up time was similar (mean 16.1 vs 15.8 years, P =
0.9). The JDM-active patients had higher HR (70.7 vs 65.0,
P = 0.033), and decreased cSDNN (34.7 vs 45.7, P =
0.013) and SDANN (73.5 vs 90.7, P = 0.047). JDM-active
patients also had higher ESR levels (9.5 and 6.1, P =
0.036). hsCRP levels were not significantly different be-
tween the two groups (2.5 and 1.9, P = 0.815). None of
the analysed echocardiographic parameters or cytokines
were significantly different between the groups.
Association between HRV parameters and high vs
low hsCRP level in patients and controls
We divided both the patient and the control group into
subgroups, based on their hsCRP values, comparing the
highest quartile (Q4) with the pooled remaining three
lowest quartiles (Q13). In patients, all HRV parameters
were lower (Fig. 1) in the high hsCRP subgroup (Q4)
than in the subgroup of subjects with lower hsCRP
levels (Q13); however, no such associations were found
in the controls (Table 4).
Discussion
The present study is the first to demonstrate dysregulation
of the autonomic nervous system in JDM. Increased HR
and decreased HRV were found in patients with JDM
compared with sex- and age-matched controls. Among
patients, reduced HRV correlated both with cardiac dys-
function and with increased levels of inflammatory mar-
kers. Furthermore, patients with hsCRP in the upper
normal range had lower HRV than those with lower
hsCRP, and patients with active disease had lower HRV
than patients with inactive disease.
Our patient cohort contains the majority of patients
diagnosed with JDM between 1970 and 2006 in Norway,
and has previously been described [17]. Female predomi-
nance, age at diagnosis and symptom duration from di-
sease onset to the diagnosis correspond with other JDM
studies [3032]. We believe that the randomly selected
age- and sex-matched controls provide a potential to
detect subtle, organ-specific changes in JDM, in particu-
lar since subjects are relatively young without manifest
clinical heart disease.
The primary aim of the study was to assess HRV in
patients with JDM vs controls. In our patients, two out
of six HRV parameters were found to be decreased des-
pite their young age. This suggests that JDM patients had
impaired vagal and/or sympathetic HR control at the
follow-up. To our knowledge, there is no data published
on HRV in adult or juvenile dermatomyositis; furthermore,
studies on HRV has been scarcely published in any juve-
nile onset rheumatic disease. However, impaired auto-
nomic control with decreased HRV has been described
in a number of adult rheumatic diseases, such as SLE
[11,12], RA [9,10], SSc [3335] and PsA [13]. The under-
lying pathophysiological mechanisms are not convincingly
understood, but may be caused by autoimmune inflam-
mation or specific autoantibodies, as will be discussed
later.
Reduced HRV is associated with increased tendency
of arrhythmias and related sudden death [36]. However,
we did not detect any arrhythmias in our JDM patients,
which might again be due to the relatively young age
of the study participants. However, to our knowledge,
there are no studies investigating whether impaired
autonomic control of the heart (decreased HRV)
predicts later cardiovascular disease also in young
individuals.
TABLE 3Correlations between HRV and echocardiographic parameters, inflammatory markers and cytokines in JDM
patients at follow-up
cSDNN RMSSD pNN50 LF HF
r
sp
Pr
sp
Pr
sp
Pr
sp
Pr
sp
P
LAS 0.053 0.702 0.314 0.019 0.363 0.006 0.119 0.386 0.300 0.026
e00.106 0.446 0.360 0.007 0.415 0.002 0.213 0.121 0.394 0.003
ESR 0.345 0.010 0.349 0.009 0.322 0.017 0.371 0.005 0.309 0.022
hsCRP 0.316 0.019 0.462 0.000 0.468 0.000 0.368 0.006 0.470 0.000
MCP-1 0.214 0.136 0.242 0.090 0.292 0.040 0.130 0.366 0.326 0.021
Eotaxin 0.011 0.941 0.312 0.027 0.346 0.014 0.129 0.374 0.352 0.012
HRV: Heart rate variability. Values are Spearman’s correlation coefficient (rsp) or P value. n = 55 patient-control pairs, except
for MCP-1 and eotaxin where n = 50, and e0where n = 54. cSDNN: standard deviation of all normal-to-normal intervals
corrected for the heart rate; RMSSD: root mean square of the successive differences between adjacent normal-to-normal
intervals; pNN50: number of pairs of adjacent NN intervals differing by >50 ms in the entire recording divided by the total
number of all NN intervals; LF: low frequency; HF: high frequency; LAS: long axis strain; e0: early diastolic tissue velocity;
hsCRP: high-sensitivity CRP; MCP-1: monocyte chemotactic protein.
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TABLE 4Comparison of HRV parameters between high and low hsCRP subgroups in patients at follow-up and controls
Patients Controls
Parameter Low hsCRP High hsCRP Low hsCRP High hsCRP
hsCRP 0.76 (0.69) 6.44 (4.27) 0.47 (0.33) 4.91 (5.36)
cSDNN 45.2 (15.3) 25.1 (11.0)** 47.8 (24.2) 43.8 (24)
SDANN 90.2 (32.1) 57.9 (19.0)** 93.2 (41.7) 87.1 (39.9)
RMSSD 71.5 (35) 36.7 (26.0)** 68.4 (33.2) 68.6 (38.5)
pNN50 29.7 (16.8) 10.7 (16.3)** 30.5 (18.5) 28.8 (20.9)
LF 1829 (1135) 853 (647)** 1992 (1492) 2156 (1555)
HF 1588 (1761) 422 (532)** 1333 (1073) 1243 (1023)
HRV: heart rate variability; hsCRP: high-sensitivity CRP. Values are mean (SD). **P <0.001. Quartiles based on levels of
hsCRP. Low hsCRP subgroup; quartile 13; n = 41. High hsCRP subgroup: quartile 4; n = 14. cSDNN: standard deviation
of all normal-to-normal intervals corrected for the heart rate; SDANN: standard deviation of the averages of normal-to-normal
intervals in all 5 min segments of the entire recording; RMSSD: root mean square of the successive differences between
adjacent normal-to-normal intervals; pNN50: number of pairs of adjacent NN intervals differing by >50 ms in the entire
recording divided by the total number of all NN intervals; LF: low frequency; HF: high frequency.
FIG.1Comparison of HRV parameters between low and high hsCRP subgroups of patients
HRV: heart rate variability; hsCRP: high-sensitivity CRP. Data are presented as median, 25th-75th percentile, and error
bars by the Tukey method. Low hsCRP subgroup: pooled 1-3 quartiles based on the patients’ hsCRP levels; n = 41. High
hsCRP subgroup: fourth quartile based on the patients’ hsCRP levels; n = 14. cSDNN: standard deviation of all normal-
to-normal intervals corrected for the heart rate; HF: high frequency; LF: low frequency; pNN50: number of pairs of
adjacent NN intervals differing by >50 ms in the entire recording divided by the total number of all NN intervals; RMSSD:
root mean square of the successive differences between adjacent normal-to-normal intervals; SDANN: standard
deviation of the averages of normal-to-normal intervals in all 5 min segments of the entire recording.
6www.rheumatology.oxfordjournals.org
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We have previously shown subclinical systolic and
diastolic dysfunction in our JDM cohort [2, 3]; in the cur-
rent study, cardiac function correlated with the HRV
parameters that reflect vagal activity. The finding is in
line with a study performed on SSc patients, demonstrat-
ing that decreased HRV was associated with early cardiac
affection [6].
High ESR and hsCRP levels were associated with
impaired values of five of six HRV parameters in patients
with JDM, and patients with high hsCRP levels showed
decreased HRV values compared with the rest of the pa-
tients. An association between systemic inflammation and
HRV is well documented in patients with cardiovascular
diseases [8] and in some rheumatic diseases [913], and
moreover, in the general population [14,15]. Interestingly,
we did not find such an association between low HRV and
inflammation in our controls, probably because of the low
number of subjects. Nevertheless, the association
between inflammation and decreased HRV seems to be
universal, even though knowledge on the exact linkage is
lacking. Generally, HRV is decreased when inflammation
is present, suggesting that attenuation of HRV could be
the effect of inflammation. Conversely, chronic vagal
stimulation reduced plasma CRP levels in a canine high-
rate pacing model, indicating that vagal stimulation can
decrease the level of inflammatory markers [37].
A correlation, although weak, was found between
eotaxin and MCP-1, and the HRV parameters that are
most characteristic for increased vagal tone. These cyto-
kines are chemoattractant proteins that mainly affect eosi-
nophiles and monocytes. This could also suggest that
inflammation interferes with autonomic regulation of the
heart in JDM.
No association was found between HRV and organ
damage or DAS. However, patients with active disease
by the PRINTO criteria had decreased HRV in two import-
ant time-domain parameters, cSDNN and SDANN. No re-
lationship was found between HRV and physical function
assessed by CHAQ/HAQ.
During the last decades, a considerable number of
studies have shown the unfavourable prognostic value
of low HRV, especially the time-domain parameter
SDNN, for the prediction of mortality in cardiac patients
[36]. In the present cohort, the patients present impaired
autonomic control, especially parasympathetic impair-
ment, despite their young age. The mechanism for this
is unclear. A prospective study in type 1 diabetic patients
revealed strong association between autoantibodies
against the autonomic nervous system and autonomic
dysfunction 7 years after blood sampling, but not before
it [38]. These findings propose specific autoimmunity,
acting via autoantibodies against sympathetic ganglia,
adrenal medulla or vagus nerve. These relationships may
serve as an interesting topic for further research, investi-
gating the role of autoimmunity in dysautonomia.
The mean HRV values in the present study are generally
higher than previously reported normal values in healthy
adults [39]. However, our data are in accordance with
recently published results from Oflaz et al. on children
with primary Raynaud’s phenomenon [40]. The study is
underpowered to allow sub-group analysis on the effect
of medication in patients with inactive and active disease;
thus we were unable to explore the possible confounding
effects of medication.
In JDM there was reduced HRV, which was associated
with elevated levels of inflammatory markers, active
disease and reduced myocardial function. This suggests
reduced vagal control over the heart. Whether this is
associated with increased risk of sudden cardiac death
in JDM needs to be addressed in further studies.
Acknowledgements
All authors were involved in revising the article critically for
important intellectual content, and all authors approved
the final version to be published. Z.B. had full access to
all of the data in the study and takes responsibility for the
integrity of the data and the accuracy of the data analysis.
Study conception and design: Z.B., H.S., B.F., K.G. and
I.S. Acquisition of data: H.S., T.S. and I.S. Analysis and
interpretation of data: Z.B., H.S., K.G. and I.S.
Funding: The project has received funding from the K. G.
Jebsen Cardiac Research Center, Center for Heart Failure
Research, University of Oslo, Oslo, Norway, and the
Anders Jahres Fund for the Promotion of Science, The
Hungarian National Science Research Fund (OTKA, K
108444), and the Campus Hungary Program (TA
´MOP-
4.2.4B/2-11/1-2012-0001).
Disclosure statement: The authors have declared no
conflicts of interest.
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