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Drakulic et al., J Mult Scler (Foster City) 2018, 5:2
DOI: 10.4172/2376-0389.1000220
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Journal of Multiple Sclerosis
ISSN: 2376-0389
Research Article
Open Access
Event Related Brain Potentials (ERP) Could Not Assess the Risk of
Cognitive Impairment in Relapse-Remitting Multiple Sclerosis (RRMS)
Svetlana Miletic Drakulic1, Ana Vujic2, Ana Azanjac Arsic1, Snezana Lazarevic1, Jasna Jevdjic3, Dejan Z. Aleksic1*
1
Department of neurology, Faculty of Medical Sciences, University of Kragujevac, Serbia
Department of Pediatrics, Faculty of Medical Sciences, University of Kragujevac, Serbia
3
Department of Surgery, Faculty of Medical Sciences, University of Kragujevac, Serbia
2
Abstract
Objectives: The first objective of our study was to determine differences between groups of patients receiving
disease modifying therapy (DMTs) (INFβ-1a and INFβ-1b), patients without DMTs and a control group, in terms of
neuropsychological tests and event-related brain potentials (ERP). The second objective was to determine factors that
may serve to assess the risk of cognitive impairment in patients with relapsing remitting multiple sclerosis (RRMS).
Methods: A total of 81 RRMS patients (mean age 41.09 ± 8.71 years old, 51 women, mean disease duration
133.05 ± 76.56 months) and 32 healthy controls participated in the study. Cognitive functions were evaluated using a
standard PASAT-3, the symbol digit modality test (SDMT) and ERP.
Results: There were statistically significant differences between the mean values for parietal (Pz) (p ≤ 0.05) and
central (Cz) latency (p<0.05) between the four groups of study participants. RRMS increased the risk of cognitive
impairment approximately 3.5 fold. Each year of age raised the risk of cognitive impairment by 6.0%. Each unit increase
in level of education reduced the risk of cognitive impairment approximately 2.5 fold. Increase in reaction time (RT) Cz
by 1 ms elevated the risk of cognitive impairment by 0.5%.
Conclusions: There were statistically significant differences between the mean values of Pz and Cz latency
between the four groups of study participants. Factors that may be used to assess the risk of developing cognitive
impairment in patients with RRMS include age, education level, and RT Cz. However, ERP (latency and amplitude) did
not independently assess the risk of cognitive impairment in RRMS patients.
Keywords: Event related brain potentials; Cognitive impairment;
Multiple sclerosis; PASAT; SDMT; INFβ
Introduction
Cognitive problems in patients with multiple sclerosis (MS) occur
widely in up to 62% of cases, especially concerning executive functions,
processing speed, attention, short-term memory and verbal fluency [1].
The use of disease modifying therapies (DMTs), such as interferon
beta-1a (INFβ-1a) and interferon beta-1b (INFβ-1b) is considered
to affect the cognitive performance of patients with relapsingremitting multiple sclerosis (RRMS) [2-4], although there are opposite
opinions [5].
Cognitive assessment is performed using a battery of
neuropsychological tests, such as the Paced Auditory Serial Addition
Test 3 (PASAT-3) [6], and Symbol Digit Modalities Test (SDMT) [7-11].
In some studies with a small number of patients, p300 event-related
brain potentials (ERP) are considered to be an indicator of objective
neuropsychological cognitive functioning for measuring cognitive
function in patients with MS [12].
The first objective of our study was to determine whether there
are differences between groups of patients receiving therapy, patients
without therapy and a control group, in terms of neuropsychological
test results and ERP. The second objective was to determine factors that
may serve to assess the risk of cognitive impairment in patients with
RRMS.
Materials and Methods
Participants
In the period from 01.05.2016 to 01.07.2016 in the Department of
Neurology of the Clinical Center Kragujevac and the Faculty of medical
Sciences, University of Kragujevac, Kragujevac, Serbia, we examined a
J Mult Scler (Foster City), an open access journal
ISSN: 2376-0389
total of 81 patients with RRMS (71.7%) and 32 healthy controls (28.3%).
We tested all patients from our center with RRMS who were on DMTs.
The aims of our study were explained to them and informed consent
was signed by all participants and approved by the Ethics Committee of
the Clinical Center, Kragujevac.
Diagnosis of definitive RRMS was made using the 2010 revisions to
the McDonald criteria [13]. All patients fulfilled the inclusion criteria,
i.e. they had RRMS without disability in a functional system that would
prevent testing. The exclusion criteria for the group of patients were
presence of other neurological diseases and psychiatric disorders, use
of neuroleptics, anticholinergics, antidepressants and antiepileptic
drugs, relapse and use of corticosteroid therapy in the last month before
the tests. The inclusion criteria for the control group were absence
of: neurological disease, psychiatric diagnoses, use of any drugs. The
RRMS group and the control group were matched by age, gender and
education.
Patients were divided into three subgroups: those who were not
receiving DMTs, patients on INF β-1a and patients on INFβ-1b. Some
patients were not receiving DMTs for economic (financial) reasons in
Serbia. They had not been given other types of DMTs earlier.
*Corresponding author: Aleksic DZ, Department of neurology, Faculty of
Medical Sciences, University of Kragujevac, Serbia, Tel: 381642287184; E-mail:
drdeal1987@gmail.com
Received May 13, 2018; Accepted June 12, 2018; Published June 19, 2018
Citation: Drakulic SM, Vujic A, Arsic AA, Lazarevic S, Jevdjic J, et al. (2018) Event
Related Brain Potentials (ERP) Could Not Assess the Risk of Cognitive Impairment
in Relapse-Remitting Multiple Sclerosis (RRMS). J Mult Scler (Foster City) 5: 220.
doi: 10.4172/2376-0389.1000220
Copyright: © 2018 Drakulic SM, et al. This is an open-access article distributed
under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the
original author and source are credited
Volume 5 • Issue 2 • 1000220
Citation: Drakulic SM, Vujic A, Arsic AA, Lazarevic S, Jevdjic J, et al. (2018) Event Related Brain Potentials (ERP) Could Not Assess the Risk of
Cognitive Impairment in Relapse-Remitting Multiple Sclerosis (RRMS). J Mult Scler (Foster City) 5: 220. doi: 10.4172/2376-0389.1000220
Page 2 of 5
Clinical and neuropsychological evaluation
Neurological disability was evaluated according to the Expanded
Disability Status Scale (EDSS), by the same experienced EDSS certified
neurologists [14].
Cognitive functions were evaluated using a standard PASAT 3 (form
A and B) and SDMT. Means with standard deviation were calculated for
SDMT and standard deviations ≤ 1.5 below the mean value of correct
responses for the SDMT by the control group was used as the threshold
value separating cognitively preserved (CP) and cognitively impaired
(CI) MS patients [10].
Objective cognitive testing
ERP were determined for all patients and control subjects. ERP
were registered from the scalp during the morning in the same soundproofed room. Participants listened to auditory stimuli through a
headset and responded by pressing a button with their dominant
hand. Bioelectrical activity of the brain was registered by monopolar
electrodes placed on the center line of the frontal region (Fz), central
region (Cz) and parietal region (Pz) using “Keypoint® Software ver. 3.00
with three dual-channels (Ag¬AgCl). Inactive electrodes were placed
on the mastoid process, and the ground electrode was on the forearm of
the subjects. Impedance was kept below 5 Ω after detailed preparation
of the place where they were put. The resulting signals were amplified,
filtered and sampled in the time frame of 1000 ms. We used the
“oddball” paradigm with two tones: a “standard” tone of 90 dB and 1000
Hz and an “expecting“ tone of 90 dB and 2000 Hz. These were presented
binaurally at irregular intervals and in incorrect order through a special
headset. Participants were ordered to ignore low “standard” tones, and
to react as quickly as possible by pressing the key with the dominant
hand, every time they heard the “expecting” high tone. About 260
attempts were registered with the ratio “standard” 80%-“expecting”
20%. Processing ERP included individual identification of the highest
positive wave in the window of 220 to 450 ms for each electrode and
determination of the amplitude and latency of the p300 wave. Reaction
time (RT) was also registered (time elapsed from the occurrence of the
stimulus to the response of the patient by pressing the button).
Statistical analysis
Descriptive data are presented as medians with percentages.
Kolmogorov-Smirnov and Shapiro-Wilk tests were used to test
for normality of distribution of numerical data. For differences in
parametric variables Student’s t-test and for nonparametric variables
the Mann-Whitney U test was employed. Categorical variables were
compared using the Chi-square test. Spearman’s test was used to
Measures
determine correlations between variables for data that did not follow
a normal distribution. ANOVA was employed to examine differences
in latency and amplitude and RT of ERP between the groups of
participants in the study. Univariate and multivariate logistic regression
was performed to examine which factors influence the occurrence of
cognitive impairment in patients with RRMS. Multivariate binary
logistic regression allows creation of a model for assessing the risk
of cognitive impairment. A model showing the influence of factors
affecting the occurrence of cognitive impairment was made based
on the significant factors obtained in the univariate and multivariate
logistic regression analysis. Probability (P) values<0.05 were considered
statistically significant. All statistical analyses were processed in the
SPSS v.20 program.
Result
Demographic, clinical and neuropsychological characteristics for
RRMS patients compared to the control group are presented in Table
1. There were negative correlations between EDSS and the results of
PASAT A (r=-0.289, p=0.010) and PASAT B (r=-0.319, p<0.001). The
results of the SDMT were influenced by gender (women performed
better p<0.05), age (p<0.05, r=-0.217), duration of education (p<0.01,
r=0.460), educational level (people with a university degree performed
better than those with secondary (p<0.05) and primary school
education only (p<0.01). There was a significant negative correlation
between SDMT and EDSS (r=-0.387, p=0.001). When patients were
divided into groups of CP and CI participants, in the RRMS group the
relative number with cognitive impairment was 53.2%. The difference
between the mean values of EDSS between these groups was statistically
significant (CP=2.2 ± 1.5, CI=2.6 ± 1.4, p<0.05). The differences in
mean values for PASAT A (CP=45.8 ± 11.1, CI=37.4 ± 10.8, p<0.05)
and PASAT B (CP=49.5 ± 9.5, CI=40.4 ± 11.5, p<0.01) between these
two groups were statistically significant. CP was related to the level of
education (p<0.05).
Our study showed that therapy did not affect performance in PASAT
A and PASAT B (PASAT A: INFβ-1b vs. without DMTs p=0.739; INFβ1a vs. without DMTs p=0.776; PASAT B: INFβ-1b vs. without DMTs
p=0.243, INFβ-1a vs. without DMTs p=0.844). Moreover, no differences
between the groups on DMTs and patients without DMTs (INFβ-1b vs.
no DMTs p=1.000; INFβ-1a vs. no DMTs p=0.676) or between the two
groups receiving DMTs (INFβ-1b vs. INFβ-1a p=1.000) were found.
There was also no significant difference in relation to DMTs between
the CP and CI groups (χ2=6.876, p=0.076).
Comparison of ERP latency (ANOVA) between four groups of
participants is presented in Figure 1. There were significant differences
Patients with RRMS
INFb1b
INFB1a
Control group
p value
Without DMTs
4/9
43391
43417
16/16
(p=0.420)
40.3 ± 8.4
38.9 ± 9.1
44.5 ± 8.0
38.8 ± 9.3
(p=0.076)
Duration of education (mean ± SD) (years)
13 ± 2.7
13.4 ± 2.9
12.3 ± 3.4
14.4 ± 4.4
(p=0.157)
Education level (number) Primary/Secondary/Higher/ University
1/20/2/6
1/19/2/6
4/13/5/2
2/18/5/7
(p=0.377)
Male/female (number)
Age (mean ± SD) (years)
143.6 ± 87.9
132 ± 64.3
121 ± 76.4
-
(p=0.575)
EDSS (mediana, IQR)
2 (1.5-3.0)
1.5 (1.125-2.375)
3 (1.5-5.5)
-
p<0.05
PASAT A-3 (mean ± SD)
42.0 ± 11.1
42.0 ± 11.8
37.2 ± 11.6
48.6 ± 10.0
p<0.05
PASAT B-3 (mean ± SD)
46.7 ± 9.9
44.2 ± 11.9
40.5 ± 11.9
51.8 ± 8.7
p<0.05
SDMT (mean ± SD)
37.8 ± 10.9
38.8 ± 13.0
32.8 ± 16.7
50.3 ± 12.5
p<0.01
Duration of illness (mean ± SD) (months)
RRMS: Relapsing-Remitting Multiple Sclerosis; SD: Standard Deviation; EDSS: Expanded Disability Status Scale; IQR: Interquartile Rang; PASAT: Paced Auditory
Serial Addition Test; SDMT: Symbol Digit Modalities Test
Table 1: Demographic, clinical and neuropsychological characteristics for RRMS patients compared to control group.
J Mult Scler (Foster City), an open access journal
ISSN: 2376-0389
Volume 5 • Issue 2 • 1000220
Citation: Drakulic SM, Vujic A, Arsic AA, Lazarevic S, Jevdjic J, et al. (2018) Event Related Brain Potentials (ERP) Could Not Assess the Risk of
Cognitive Impairment in Relapse-Remitting Multiple Sclerosis (RRMS). J Mult Scler (Foster City) 5: 220. doi: 10.4172/2376-0389.1000220
Page 3 of 5
between the mean values of Pz (p<0.05) and Cz latency (p<0.05)
between the four groups of study participants. Thus, Cz latency for the
control group diverged from that for patients without DMTs (p<0.05),
while Pz latency for the control group diverged from that for patients
on INFβ-1b (p<0.01) (Figure 1).
Correlations of ERP with demographic characteristics,
neuropsychological tests and EDSS in the RRMS group are shown in
Table 2.
Univariate binary logistic regression and multivariate binary logistic
regression indicated factors that have an impact on the occurrence of
cognitive impairment (Table 3).
RRMS increased the risk of cognitive impairment by approximately 3.5
times. Each year of age raised the risk of cognitive impairment by 6.0%.
Unit increase in level of education reduced the risk of cognitive impairment
approximately 2.5 fold. Increase in the variable RT Cz by 1 ms elevated
the risk of cognitive impairment by 0.5%. Multivariate binary logistic
regression allowed creation of a model for assessing the risk of cognitive
impairment. The model is a new variable calculated as follows:
Model =esum/(1 + esum)·100
sum=1.278*MS+0.058*age-0.913*level of education+0.005*RT Cz3.291.
Figure 1: The comparison of event related potentials latency, in milliseconds,
between 4 groups of participants, from Fz, Cz and Pz electrode.
Figure 2: ROC curve.
Measures
Age
Duration of education
EDSS
PASAT A-3
PASAT B-3
SDMT
Fz latency (ms)
r=0.249*
p=0.355
p=0.126
p=0.315
p=0.402
p=0.440
Fz amplitude (μV)
p=0.132
p=0.520
p=0.561
p=0.578
p=0.547
p=0.543
RT Fz (ms)
p=0.511
p=0.400
p=0.283
p=0.700
r=-0.267*
p=0.257
Cz latency (ms)
p=0.623
p=0.859
r=0.363**
p=0.892
p=0.666
p=0.260
Cz amplitude (μV)
p=0.277
p=0.481
p=0.088
p=0.724
p=0.460
p=0.649
RT Cz (ms)
p=0.934
p=0.286
p=0.207
p=0.892
p=0.235
p=0.110
Pz latency (ms)
p=0.674
p=0.599
r=0.284*
p=0.337
p=0.510
p=0.663
Pz amplitude (μV)
r=-0.313*
r=0.273*
r=-0.296**
p=0.469
p=0.244
p=0.171
RT Pz (ms)
p=0.703
p=0.233
p=0.164
p=0.785
p=224
p=0.116
RRMS: Relapsing-Remitting Multiple Sclerosis; EDSS: Expanded Disability Status Scale; PASAT: Paced Auditory Serial Addition Test; SDMT: Symbol Digit Modalities Test;
Fz: Frontal; ms: Milisecond; *p<0.05; μV–microvolt; **p<0.01; RT: Reaction Time; Cz: Central; Pz: Parietal
Table 2: Correlation of P300 event-related potentials with demographic characteristics, neuropsychological tests and EDSS in the group of patients with RRMS.
Univariate binary regression
Multivariate binary regression
Measures
OR with 95% CI
p value
OR with 95% CI
p value
RRMS
3.905 (1.505-10.1332)
p<0.01
3.589 (1.152–11.175)
p<0.05
Age
1.052 (1.006-1.101)
p<0.05
1.060 (1.006-1.117)
p<0.05
Education level
0.377 (0.212-0.673)
p<0.01
0.401 (0.219-0.735)
p<0.01
Duration of education
0.751 (0.630-0.894)
p<0.01
Fz latency
1.012 (1.000-1.024)
p<0.05
RT Fz
1.006 (1.002-1.010)
p<0.01
RT Cz
1.006 (1.002-1.010)
p<0.01
1.005 (1.000-1.009)
p<0.05
RT Pz
1.005 (1.001-1.009)
p<0.05
OR: Odds Ratio; CI: Confidence Interval; RRMS: Relapsing-Remitting Multiple Sclerosis; RT: Reaction Time; Fz: Frontal; Cz: Central; Pz: Parietal
Table 3: Univariate and Multivariate binary regression showed which factors influence the occurrence of cognitive impairment and the values of OR with 95% CI.
J Mult Scler (Foster City), an open access journal
ISSN: 2376-0389
Volume 5 • Issue 2 • 1000220
Citation: Drakulic SM, Vujic A, Arsic AA, Lazarevic S, Jevdjic J, et al. (2018) Event Related Brain Potentials (ERP) Could Not Assess the Risk of
Cognitive Impairment in Relapse-Remitting Multiple Sclerosis (RRMS). J Mult Scler (Foster City) 5: 220. doi: 10.4172/2376-0389.1000220
Page 4 of 5
The ROC curve showed that this model may be a good marker to
separate participants into those with cognitive impairment and those
without cognitive impairment (AUROC=0.803, p<0.01) (Figure 2).
Discussion
Cognitive impairment has been registered over a wide range of
proportions of RRMS patients, i.e. from 9% to 62% [5,15-23]. In our
sample of RRMS patients the percentage of CI (defined as ≤ 1.5 standard
deviations below the mean value of correct responses for the SDMT by
the control group) was 53.2%.
In our cross-sectional study therapy did not affect performance
in PASAT A and PASAT B, while some longitudinal studies have
shown that performance in PASAT improves slightly after one year of
application of INFβ-1b, but not statistically significantly, while use of
INFβ-1a led to a statistically significant improvement [3].
There were also marked improvements in the SDMT one year after
the application of INFβ-1b and INFβ-1a [3], which was not confirmed
in our cross-sectional study. Thus, no differences between the groups on
DMTs and patients without DMTs or between the two groups receiving
DMTs or in relation to DMTs in those with CP and with CI.
A small number of studies have aimed to investigate the effect of
DMTs on latency, amplitude and RT of ERP in patients with RRMS.
Thus, INFβ-1b was shown to reduce amplitude and latency [1]. In
our cross-sectional study, there were no differences in amplitude and
latency and RT between patients without DMTs and patients on INFβ1a and INFβ-1b (Figure 1).
Others have recorded significantly higher EDSS in CI patients
[20,24], which was also the case in our group of participants. Cognitive
assessment using PASAT-3 indicated better performance by our control
group than the RRMS group (Table 1), in accordance with earlier
findings [25,26].
Parmenter and Borghi showed high sensitivity and specificity of
the SDMT demonstrating its efficiency as a screening test for cognitive
impairment in patients with MS [15,27]. Thus our control group also
achieved better results on SDMT than our patients, confirming the
findings of others [25]. In our group of participants, women achieved
better scores in the SDMT. According to our knowledge, no other study
has demonstrated a difference in SDMT between the genders.
SDMT negatively correlated with EDSS during the entire follow-up
of patients in Brochet’s study [7,25], similarly to our group of patients
(p<0.01, rho=-0.363).
We have found that performance of neuropsychological tests is
significantly affected by education level, in accordance with Luerding’s
conclusion that cognitive reserve is the greatest among the highly
educated. He found an especially strong relation of educational
background to memory and executive functions [28].
The two main neuropsychological markers of cognitive functioning
are ERP latency and ERP amplitude. Prolonged latency indicates a
long information processing time [29]. Some research has confirmed
a connection between ERP and cognitive impairment, defined
by neuropsychological tests in MS patients [12,30-32] but this
correlation is stronger in patients with Alzheimer’s disease where
the cortical dementia concept is dominant [33-35]. The correlation
between multifocal white-matter and gray-matter lesions in cognitive
dysfunction pathology has laid the foundations of the theory of multiple
disconnection. Disconnection occurs between cortical and subcortical
regions. MS patients with CI manifested more cortical lesions than
J Mult Scler (Foster City), an open access journal
ISSN: 2376-0389
patients who were CP. The multiple disconnection syndrome means
that more than one cognitive domain can be interrupted, producing a
variety of neuropsychological deficits [36]. As far as we know there is
no study connecting ERP and multiple disconnection syndrome.
Duration of education in our RRMS patients significantly correlated
with Pz amplitude. Sundgren stated that half of the variance of cognitive
functioning in patients with RRMS is explained by variations in ERP
amplitude and RT, together with EDSS, but there are different opinions
[30,31]. Positive correlations of EDSS with Cz and Pz latency, and a
negative one with Pz amplitude, were also observed in our patients with
RRMS. Others have shown that changes in ERP correlate significantly
with changes in PASAT during a one year follow-up [37]. While
Sundgren found that success in neuropsychological tests correlates
with ERP from the parietal region, and not from the frontal region in
patients with RRMS [31] we only obtained correlation of PASAT B and
RT Fz (Table 2).
The risk of cognitive impairment was calculated in percentages,
with a formula that includes factors of importance for the assessment
of cognitive risk: the diagnosis of RRMS, age, education level and RT
Cz. For example, participant number 38 without a diagnosis of RRMS,
was 32 years old, has finished university, and his RT Cz was 414 ms.
Our model calculated that the relative risk of cognitive impairment for
this participant was 10.87%. This subject had no cognitive impairment.
Participant number 41 had an RRMS diagnosis, was 43 years old,
finished secondary school and his RT Cz was 674 ms. The risk of
cognitive impairment for this individual was high, 88.34% and he did
manifest cognitive impairment. In the model the significant factors for
assessing cognitive impairment in RRMS patients did not include either
latency or amplitude from ERP, so we conclude that ERP is not a reliable
indicator of cognitive impairment in these patients.
The advantages of our research are the size of the sample of
patients with RRMS, who were receiving DMTs, and who were tested
for ERP. We are the first to form a model that calculates an adequate
assessment of the risk of cognitive impairment for each RRMS patient.
A limitation of this study is that some patients were not receiving DMTs
for economic reasons in Serbia.
Conclusion
There were a significant differences between the mean values for
Pz (p<0.05) and Cz latency (p<0.05) between four groups of study
participants. Thus, Cz latency for the control group differed from that
for patients without DMTs (p<0.05), while Pz latency for the control
group differed from that for patients on INFβ-1b (p<0.01). Factors
that can be used to assess the risk of developing cognitive impairment
in patients with RRMS are age, education level, RT Cz. However,
ERP (latency and amplitude) did not independently assess the risk of
cognitive impairment in RRMS patients.
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Volume 5 • Issue 2 • 1000220
Citation: Drakulic SM, Vujic A, Arsic AA, Lazarevic S, Jevdjic J, et al. (2018) Event Related Brain Potentials (ERP) Could Not Assess the Risk of
Cognitive Impairment in Relapse-Remitting Multiple Sclerosis (RRMS). J Mult Scler (Foster City) 5: 220. doi: 10.4172/2376-0389.1000220
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