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Serum lactate as a novel potential biomarker in multiple sclerosis
Angela M. Amorini
a
, Viviana Nociti
b,c
,AxelPetzold
d
, Claudio Gasperini
e
, Esmeralda Quartuccio
e
,
Giacomo Lazzarino
a
, Valentina Di Pietro
f
, Antonio Belli
f,g
, Stefano Signoretti
e
,RobertoVagnozzi
h
,
Giuseppe Lazzarino
i,
⁎, Barbara Tavazzi
a
a
Institute ofBiochemistry and Clinical Biochemistry Largo F. Vito 1, 00168 Rome, Italy
b
Institute of Neurology, Catholic University of Rome, Largo F. Vito 1, 00168 Rome, Italy
c
Fondazione Don C. Gnocchi, Onlus, Piazzale Morandi 6, 20121 Milano, Italy
d
Department of Neurology, VU Medical Centre, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
e
Department of Neurosciences, S Camillo Forlanini Hospital, Circonvallazione Gianicolense 87 00152 Rome, Italy
f
Neurotrauma and Neurodegeneretion Section, School of Clinical and Experimental Medicine, College of Medical and Dental Sciences, University of Birmingham, Edgbaston B15 2TT,
Birmingham, UK
g
National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre, Queen Elizabeth Hospital, Edgbaston B15 2TH, Birmingham, UK
h
Department of Biomedicine and Prevention, Section of Neurosurgery, University of Rome “Tor Vergata”, Via Montpellier 1, 00133 Rome, Italy
i
Department of Biology, Geology and Environmental Sciences, Division of Biochemistry and Molecular Biology, University of Catania, Viale A. Doria 6, 95125 Catania, Italy
abstractarticle info
Article history:
Received 21 November 2013
Received in revised form 13 March 2014
Accepted 4 April 2014
Available online 13 April 2014
Keywords:
Clinical disability
Energy penalty
Mitochondrial dysfunction
Multiple sclerosis
Serum lactate
Multiple sclerosis (MS) is a primary inflammatory demyelinating disease associated with a probably secondary
progressive neurodegenerative component. Impaired mitochondrial functioning has been hypothesized to
drive neurodegeneration and to cause increased anaerobic metabolism in MS. The aim of our multicentre
study was to determine whether MS patients had values of circulating lactatedifferent from those ofcontrols. Pa-
tients (n = 613) were recruited, assessed for disability and clinically classified (relapsing–remitting, secondary
progressive, primary progressive) at the Catholic University of Rome, Italy (n = 281), at the MS Centre
Amsterdam, The Netherlands (n = 158) and at the S. Camillo Forlanini Hospital, Rome, Italy (n = 174). Serum
lactate levels were quantified spectrophotometrically with the analyst being blinded to all clinical information.
In patients with MS serum lactate was three times higher (3.04 ± 1.26 mmol/l) than that of healthy controls
(1.09 ± 0.25 mmol/l, p b0.0001) and increased across clinical groups, with higherlevels in cases with a progres-
sive than with a relapsing–remitting disease course. In addition, there was a linear correlation between serum
lactate levels and the expanded disability scale (EDSS) (R
2
=0.419;pb0.001). These data support the hypoth-
esis that mitochondrial dysfunction is an important feature in MS and of particular relevance to the neurodegen-
erative phase of the disease. Measurement of serum lactate in MS might be a relative inexpensive test for
longitudinal monitoring of “virtual hypoxia”in MS and also a secondary outcome for treatment trials aimed to
improve mitochondrial function in patients with MS.
© 2014 Elsevier B.V. All rights reserved.
1. Introduction
Multiple sclerosis (MS) is a primary inflammatory demyelinating
disease of the central nervous system, associated with a probably sec-
ondary progressive neurodegenerative component, causing accumula-
tion of disability to the patients. MS is believed to be of autoimmune
pathology [1] although the reasons for the autoimmune attack towards
myelin are not yet totally clear [2]. As it occurs in other chronic neuro-
degenerative disorders (Alzheimer's disease, Parkinson's disease), MS
is characterized by various molecular alterations, including change in
ionic homeostasis [3,4] and overproduction of reactive oxygen (ROS)
and nitrogen species (RNS), with consequent oxidative/nitrosative
stress and induction of apoptosis [5–7]. All these events seriously com-
promise several fundamental neuronal functions and certainly play a
role in the disease progression and clinical deterioration of the patients.
Biochimica et Biophysica Acta 1842 (2014) 1137–1143
Abbreviations: CPK-BB, creatinphosphokinase brain specific isoform; CrP, creatine
phosphate; EDSS, expanded disability status scale; ETC, electron transport chain;
1
HMRS,
proton-magnetic resonancespectroscopy; MS, multiple sclerosis; PP, primary progressive;
RNS, reactive nitrogen species; ROS, reactive oxygen species; RR, relapsing remitting; SP,
secondary progressive
⁎Corresponding author. Tel.: +39 0957384095; fax: +39 095337036.
E-mail addresses: angela.amorini@rm.unicatt.it (A.M. Amorini), viv.nociti@libero.it,
viviana.nociti@tiscali.it (V. Nociti), a.petzold@ion.ucl.ac.uk,a.petzold@vumc.nl
(A. Petzold), c.gasperini@libero.it (C. Gasperini), e.quartuccio@libero.it (E. Quartuccio),
g.lazzarino@libero.it (G. Lazzarino), v.dipietro@bham.ac.uk (V. Di Pietro),
a.belli@bham.ac.uk (A. Belli), stefano.signoretti@tiscali.it (S. Signoretti),
vagnozzi@uniroma2.it (R. Vagnozzi), lazzarig@unict.it (G. Lazzarino),
btavazzi@rm.unicatt.it (B. Tavazzi).
http://dx.doi.org/10.1016/j.bbadis.2014.04.005
0925-4439/© 2014 Elsevier B.V. All rights reserved.
Contents lists available at ScienceDirect
Biochimica et Biophysica Acta
journal homepage: www.elsevier.com/locate/bbadis
Author's personal copy
In addition, these molecular changes seem to have, as a common
feature, the malfunctioning of mitochondria which has led to the “mito-
chondrial hypothesis”of axonal degeneration in MS [8–10],aswellas
the concept of “virtual hypoxia”in which chronically demyelinated
axons of MS patients are forced to operate [11].
This hypothesis is supportedby many experimental and clinical data
showing that MS is characterized by a remarkable energy penalty due to
the imbalance between energy production and consumption [10–12].
This is determined by a decreased mitochondrial ability to supply ade-
quate ATP concentrations for the various energy-dependent functions
crucial for neuronal survival.
In particular, imbalance in creatine phosphate (CrP) homeostasis
[13] and decreased activity of the brain specific isoform of the enzyme
creatinphosphokinase (CPK-BB) detected in MS [14] should be respon-
sible for the reduced export of the mitochondrially generated ATP to the
cytoplasm, with consequent decreased availability of cytoplasmic ATP.
Contribution to a net decrease in ATP cellular content is also due to an
impairment in the activity of the mitochondrial electron transport
chain (ETC). In fact, it has been demonstrated that MS patients have de-
creased expression of several subunitsof complexes I, III, IV and V of the
ETC in different brain regions [15],withconsequentdiminutioninthe
electron flow through the chain and inevitable decrease in ATP forma-
tion by the electron-dependent oxidative phosphorylation. The
overall decline in cytoplasmic ATP negatively influences all the ATP-
dependent reactions, including the activity of ATP-ases involved in
ionic homeostasis [16], causing imbalance in intracellular calcium and
membrane depolarization [16,17].
In line with the hypothesis of mitochondrial malfunctioning, we
have previously demonstrated that MS patients have increased levels
of compounds deriving from ATP catabolism (hypoxanthine, xanthine,
uric acid, uridine, creatinine) in their cerebrospinal fluid (CSF) and
blood [18–20]. These data strongly supported the concept that MS pa-
tients have impaired energy metabolism, with significant alterations
in the production and consumption of ATP [13,14] ultimately causing
an overproduction of its catabolites in the cerebral tissue [21]. Thanks
to their ability to freely cross the neuronal membrane, these low molec-
ular weight compounds are initially released into the CSF of MS patients,
subsequently reaching the blood stream, and finally leading to a signif-
icant rise in their concentrations in the biological fluids with respect to
the values found in healthy controls [18–20]. With this current knowl-
edge of an energy penalty in MS, it is reasonable to hypothesize that,
in order to counteract the diminished ATP supply caused by altered mi-
tochondrial functions, the cerebral tissue would tend to increase the
glycolytic pathway to rates exceeding the already compromised capac-
ity of mitochondria to metabolize pyruvate. As a consequence of an in-
creased glycolytic rate and pyruvate accumulation, an increase in
lactate production would be expected. Recently, by using proton-
magnetic resonance spectroscopy (
1
HMRS),ithasbeenshownthat
MS patients had increased lactate in their CSF, suggesting increased
extra-mitochondrial glucose metabolism due to mitochondrial dysfunc-
tion [22]. A correlation between lactate concentration in the CSF and the
number of inflammatory plaques reinforced the indication of increased
glycolysis in MS due to mitochondrial malfunctioning [23,24].Notwith-
standing, data reporting decrease in CSF lactate in the early stages of MS
have also been published [25], casting doubts over the role of this com-
pound and, therefore, over the importance of its measurements. Fur-
thermore, to compound this uncertainty, further
1
H MRS studies
indicated either elevated [26] or no change [27] of brain lactate in MS
patients. To date, no data are available concerning the concentration
of circulating lactate in MS patients. Interestingly, a retrospective evalu-
ation of the chromatographic runs of serum samples of MS patients en-
rolled in our previous studies [18,20] showed an impure peak having
the retention time of true lactate which, in the majority of samples,
was much higher than that found in controls (data not shown).
In this study, we measured the concentration of serum lactate in a
large cross-sectional cohort of MS patients recruited in three different
centers, comparing these values with those recorded in a control
group of healthy subjects matched for age and sex. We reasoned that,
firstly, an energy deficit in MS would lead to higher serum lactate levels
than controls and that, secondly, any rise of serum lactate in MS would
be clinically relevant and related to clinical disability and disease course.
2. Materials and methods
2.1. Selection and clinical evaluation of the MS patients
Patients (n = 613) fulfilling the 2 005 revision of the diagnostic panel
criteria for MS [28] were recruited at the Institute of Neurology of
the “Policlinico Gemelli”of the Catholic University of Rome (center 1;
n = 281), at the Department of Neurosciences, S. Camillo Forlanini
Hospital, Rome, Italy (center 2; n = 174) and at the Department of
Neurology, VU Medical Centre, Amsterdam, The Netherlands (center
3; n = 158). They were clinically assessed using the Extended Disability
Status Scale score (EDSS) [29]. At the same time of the clinical assess-
ment, patients were asked to undergo to a venipuncture for the blood
samples to be used for this research study. Only patients that were clin-
ically stable at the time of the blood sampling were included in the
study. A clinical relapse within one month before withdrawal was
used as an exclusion criterion.
Patients were classified into relapsing remitting (RR), secondary
progressive (SP) or primary progressive (PP), according to Lublin and
Reingold [30]. The control group consisted of 625 healthy subjects,
matched for age and gender, and recruited among the students of the
Catholic University of Rome and the University of Catania, as well as
among the personnel of these two Universities who underwent their
annual health check-up. Subjects suffering from any acute or chronic
systemic disease, which might have influenced the serum lactate levels,
were not included in the control group. The study was approved by the
local Ethic Committees and written informed consent was obtained
from all patients according to the Declaration of Helsinki.
2.2. Preparation of samples
In both controls and MS patients, peripheral venous blood samples
were collected after at least 15 min of complete rest, using the standard
tourniquet procedure, from the antecubital vein into a single
VACUETTE® polypropylene tube containing serum separator and clot
activator (Greiner-Bio One GmbH, Kremsmunster, Austria). After
30 min at room temperature, blood withdrawals were centrifuged at
1890 ×gfor 10 min and the resulting serum samples were saved at
−80 °C until the analysis. To measure lactate concentration, an aliquot
of all serumsamples was used with no further processing.This protocol
for blood withdrawal and serum preparation was strictly observed in
the three centers involved and was equally used in both controls and
MS patients.
2.3. Spectrophotometric assay of serum lactate
The spectrophotometric determination of lactate was carried out
using an Agilent 89090A spectrophotometer (Agilent Technologies,
Santa Clara Ca, USA) and following the method described by Artiss
et al. [31].Briefly, the reaction mixture contained 100 mM Tris–HCl,
1.5 mM N-ethyl-N-2-hydroxy-3-sulfopropyl-3-methylalanine, 1.7 mM
4-aminoantipyrine, and 5 IU horseradish peroxidase. Fifty microliters
of serum were added to the mixture, let to stand for 5 min and read at
545 nm wavelength. The reaction was started with the addition of
5 IU of lactate oxidase to the cuvette (finale volume = 1 ml) and it
was considered ended when no change in absorbance was recorded
for at least 3 min. To calculate lactate in serum samples, the difference
in absorbance at 545 nm wavelength (Δ
abs
) of each sample wasinterpo-
lated with a calibration curve obtained by plotting Δ
abs
measured in
standard solutions of lactate with increasing known concentrations.
1138 A.M. Amorini et al. / Biochimica et Biophysica Acta 1842 (2014) 1137–1143
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To compare analytical results of serum lactate obtained with the
aforementioned method, 150 samples from the control group and 150
samples from the groups of MS patients were randomly selected and
assayed applying the same lactate oxidase-based method and using
conventional apparatus routinely used in the clinical biochemistry set-
ting (Cobas c 702, Roche Diagnostics).
The analysis of lactate in the1238 samples collected in the threecen-
ters, as well as the comparison between the two analytical methods,
was performed at the Institute of Biochemistry and Clinical Biochemis-
try of the Catholic University of Rome, Italy. When assaying samples of
MS patients, the analyst was blinded to all clinical information.
2.4. Statistical analysis
Normal data distribution was tested using the Kolmogorov–Smirnov
test. For normally distributed data, group differences were assessed by
the Student's t-test for unpaired observations. Due to the unbalanced
study design the Kruskal–Wallis one-way ANOVA by ranks followed
by the Friedman test was used for comparison of MS subgroups
(RR, SP, PP) and controls. Correlation and regression analyses of serum
lactate levels with the EDSS were followed by ANOVA of the regression
coefficients. Only two-tailed p-values of less than 0.05 were considered
as statistically significant.
3. Results
The demographic and clinical data of the group of control healthy
subjects and of MS patients enrolled in this study are summarized in
Table 1. When subgrouped on the basis of the EDSS scores, 64 patients
were EDSS 0, 72 EDSS 1, 26 EDSS 1.5, 76 EDSS 2, 25 EDSS 2.5, 75 EDSS
3, 37 EDSS 3.5, 58 EDSS 4, 16 EDSS 4.5, 26 EDSS 5, 10 EDSS 5.5, 72
EDSS 6, 20 EDSS 6.5, 24 EDSS 7, 6 EDSS 7.5 and 6 EDSS 8. The majority
of patients with MS had a RR disease course (n = 430; 70.1%), with
smaller numbers of them being affected by the SP (n = 153; 25.0%)
and the PP (n = 30; 4.9%) forms. The group of RR-MS patients had sig-
nificantly lower mean values of EDSS and disease duration compared to
the corresponding values recorded in the groups of both SP-MS and PP-
MS patients (p b0.01).
3.1. Serum lactate in controls and MS patients
Data referring to the concentration of circulating lactate detected in
the serum of controls and MS patients are illustrated in Fig. 1. In our
group of 625 resting healthy controls we found a mean lactate value
of 1.09 ± 0.25 mmol/l serum (Panel A), with 615 of them having lactate
ranging between 0.5 and 1.5 mmol/l serum and 10 outliers (1.6%) with
a lactate range of 1.76–2 mmol/l serum. Irrespective of the clinical sub-
type and the EDSS score (Panel A), we detected a mean lactate value of
3.04 ± 1.26 mmol/l serum in resting MS patients, i.e. about 2.8 times
higher than that of controls (p b0.0001).
As shown in the scatterplot of Panel B, 101 (16.5%) of the 613 MS pa-
tients had serum lactate falling within the range of values determined in
controls (0.5–2 mmol/l serum). The remaining 502 (84.5%) MS patients
had values higher than the maximal concentration of circulating lactate
(2.0 mmol/l) recorded in one control healthy subject only. In MS pa-
tients, serum lactate ranged from 0.60 mmol/l to 7.56 mmol/l. Analysis
of the clinical and biochemical results considering MS patients as three
separate cohorts (one for each recruiting center) is reported in Table 2.
We found that the patients recruited at center 2 had significantly lower
EDSS scores compared to both centers 1 and 3 (p b0.05), with center 3
having the highest mean EDSS score. Additionally, center 3 recruitedthe
highest % number of PP patients with respect to both centers 1 and 2.
The very relevant finding is that MS patients of the three centers had
lactate values of 3.38 ± 1.83 mmol/l serum (center 1), 2.74 ±
1.39 mmol/l serum(center 2) and 2.94 ± 1.26 mmol/l serum (center 3),
i.e. each of the three subsets of MS patients had significantly higher lac-
tate values than those found in healthy controls (1.09 ± 0.25 mmol/l
serum; p b0.0001). Because of the differences in the EDSS score, lactate
Table 1
Clinical neurological data of MS patients and controls.
CTRL (n = 625) MS (all) (n = 613) RR (n = 430) SP (n = 153) PP (n = 30)
Age (years) 44.8 ± 11.7;46.0 (15–73) 45.4 ± 12.8; 46.5 (15–80) 43.1 ± 12.5; 42.0 (15–70) 49.7 ± 11.7; 50.2 (28–72) 51.3 ± 13.4; 53.0 (26–80)
Gender F 420: M 205 F 411: M 202 F 276: M 154 F 110: M 43 F 21: M 9
Disease duration (years) N/A 12.9 ± 9.5; 12.0 (0–44) 10.8 ± 9.7; 9.0 (0–38) 18.8 ± 10.0; 18.2 (1–44) 14.8 ± 9.8; 15.1 (0.6–35)
EDSS N/A 3.3 ± 2.1; 3.0 (0–8) 2.1 ± 1.6; 2.0 (0–8) 5.8 ± 1.5; 6.0 (0–8) 5.2 ± 1.5; 6.0 (3.0–8)
Values are expressed as mean ± S.D. and median (range). CTRL = controls; MS (all) = total number of multiple sclerosis patients; PP = primary progres sive; SP = secondary
progressive; RR = relapsing remitting; N/A = not available; EDSS = Extended Disability Status Scale score.
Fig. 1. Concentration of serum lactate determined in peripheral venous blood samples of
625 control healthy subjects and 613 MS patients. In Panel A, mean values with standard
deviations represented by vertical bars are reported. In Panel B, the individual values of
each subject of both groups, with medians represented by horizontal marks (1.10 and
2.87 in controls and MS patients, respectively), are reported. Dashed lines represent the
range of the serum lactate values of controls. *Significantly different from the group of
sex and age matched healthy controls, p b0.0001.
1139A.M. Amorini et al. / Biochimica et Biophysica Acta 1842 (2014) 1137–1143
Author's personal copy
values recorded in patients recruited at center 2 were significantly
lower than those measured in patients recruited in center 1, thus rein-
forcing the notion of a correlation between serum lactate and clinical
status in MS.
To confirm these analytical results and to corroborate their
relevancefor the clinical biochemical monitoring of MS patients, we re-
ported in Table 3 values of serum lactate determined in 150, randomly
selected, samples of controls and 150, randomly selected, samples of
MS patients, in which lactate was assayed both with the method de-
scribed above and with the conventional method routinely applied in
the clinical biochemistry setting. Data indicate that no significant differ-
ences exist in the lactate values obtained with these two methods,
thereby demonstrating the analytical validity of the present results.
To asses whether circulating lactate was correlated to clinical
subtypes, MS patients were divided into RR, SP and PP and values
of serum lactate in these groups were then calculated. As shown in
Fig. 2, all three subgroups of MS patients had higher values of lactate
(2.72 ± 1.12, 3.86 ± 1.29 and 3.32 ± 1.16 mmol/l serum, respec-
tively; p b0.0001) than those detected in controls (Panel A). Signif-
icant differences were recorded in the comparisons between RR and
SP (p b0.0001), RR versus PP (p b0.01), and SP versus PP (p b0.05).
Significantly, the subgroup analysis with all progressive patients
pooled together (SP and PP) demonstrated higher serum lactate
levels (3.77 ± 1.28) compared to either RR-MS patients or control
subjects (p b0.0001 for both comparisons), thus suggesting a corre-
lation between MS subtype and serum values of this glycolytic end
product (Fig. 2,PanelB).
In order to investigate the correlation with the disease progression,
values of serum lactate were plotted as a function of the EDSS scores
(Fig. 3). Since the number of subjects in the different EDSS subgroups
did not exceed the 76 units, in order to avoid an excess weight of the
control group in the calculation of the regression coefficients, we re-
duced the number of controls accordingly, for the further statistical
comparisons (analysis of regression and analysis of variance on the re-
gression coefficients). Therefore, we randomly selected 76 values from
the 625 lactate values of controls. This reduced in size control group
(mean = 0.95 ± 0.26, median = 0.88) had the same distribution (cal-
culated using the Kolmogorov–Smirnov test) of the original larger con-
trol group and was used in the linear regression analysis. Lactate values
in the control group were tabulated as the 0 values (no disease), while
those in the MS patients were tabulated as the original EDSS score
+1.InFig. 3, the equation describing the best fitting regression line
(y = 0.3657 x + 1.4289; R = 0.6473; R
2
= 0.419; p b0.0001) indi-
cates a strong positive correlation linking serum lactate with disease
progression (increase in EDSS scores), thus suggesting that the worsen-
ing of the clinical conditions of MS patients is associated with evident
deterioration in their cell energy metabolism.
It is however worth underlining that 16.5% of MS patients had values
of circulating lactate falling within the range of variability of control
Table 2
Clinical status and serum lactate in MS patients recruited per center.
MS (all) RR SP PP EDSS Serum lactate
Center 1 n = 281 202 (71.9%) 72 (25.6%) 7 (2.5%) 3.82 ± 2.23 3.31 ± 1.83
Center 2 n = 174 132 (75.9%) 37 (21.2%) 5 (2.9%)
a
2.18 ± 1.97
b
2.81 ± 1.39
Center 3 n = 158 96 (60.8%) 44 (27.8%) 18 (11.4%) 4.21 ± 1.79 2.94 ± 1.26
MS (all) = number of all multiplesclerosis patients in each center;PP = number of primary progressive patients(% in each center),SP = number of secondaryprogressivepatients (% in
each center);RR = number of relapsing remitting patients (% in each center); EDSS = Extended Disability Status Scale score. In the EDSS and serum lactate columns, values represent
mean ± S.D. and lactate is expressed in mmol/l serum.
a
Significantly different from centers 1 and 3 (p b0.05).
b
Significantly different from center 1 (p b0.05).
Table 3
Comparison of the analytical results obtained with a standard laboratory
spectrophotometer and an apparatus in use in the clinical biochemistry setting and
referring to serum lactate recorded in 150 randomly selected samples of controls and
MS patients.
Controls (n = 150) MS patients (n = 150)
Serum lactate (mmol/l)
laboratory spectrophotometer
1.06 ± 0.22
a
3.29 ± 1.18
a,b
Serum lactate (mmol/l)
clinical biochemistry apparatus
1.11 ± 0.25 3.38 ± 1.26
b
Values are expressed as mean ± S.D.
a
Not different from the values of the same group assayed by the clinical biochemistry
apparatus (longitudinal identity).
b
Significantly different from controls (p b0.0001) (latitudinal difference).
Fig. 2. Concentration of serum lactate in controls and MS patients divided according to
their different clinical subtype. In Panel A, patients were divided into three groups
(RR = relapsing remitting; SP = secondary progressive; PP primary progressive) of
very different sizes (RR = 430; SP = 153; PP = 30). In Panel B, progressive patients
were grouped (SP + PP = 189) to allow a better statistical comparison. Values are re-
ported as means, with standard deviations represented by vertical bars. *Significantly
different from the group of sex and age matched healthy controls, p b0.001. **Signif-
icantly different from the group of RR patients, p b0.0001.
1140 A.M. Amorini et al. / Biochimica et Biophysica Acta 1842 (2014) 1137–1143
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healthy subjects (Fig. 1). These 101 “low lactate”MS patients were not
found in MS patients scoring 3.5, 5.5, 6.5 and 7.5 on EDSS. Where
present, they represented the 54.7% (EDSS 0), 29.1% (EDSS 1), 15.4%
(EDSS 1.5), 21.0% (EDSS 2), 20.0 (EDSS 2.5), 16.1% (EDSS 3), 17.2%
(EDSS 4), 10.0% (EDSS 4.5), 6.0% (EDSS 5), 11.1% (EDSS 6), 9.7% (EDSS
7) and 16.7% (EDSS 8) of the respective EDSS class, with an evident clus-
tering in theEDSS 0, characterized by the less severe clinical symptoms.
It is important to note that if the 10 outliers of the control group (having
lactate ranging between 1.76 and 2 mmol/l serum and representing the
1.6% of the 625 control values) are excluded, the number of MS patients
falling within the range of controls drops from 101 to 70 (11.5%),
The box plot in Fig. 4 shows the best fitting linear regression calculat-
ed on the medians of the different EDSS scores. According to the equa-
tion y = 0.3935 x + 0.83 (R = 0.9859; R
2
= 0.972; p b0.0001) it is
possible to appreciate how medians of serumlactate in MS patients lin-
early increased as a function of the increase in EDSS score. It should be
observed that, since in a box plot the abscissa is equally divided on the
basis of the number of x values, patients with the intermediate EDSS
scores (1.5, 2.5, 3.5, 4.5, 5.5, 6.5 and 7.5) were grouped with those of
the upper EDSS class (1.5–2, 2.5–3, 3.5–4, 4.5–5, 5.5–6, 6.5–7 and 7.5–
8), in order to have equally spaced x values. In addition, even in this
case, the control group used in Fig. 3 (n = 76) was considered as the
0 group (no disease) and the EDSS scores + 1 were tabulated to perform
the regression analysis.
4. Discussion
Data reported in the present study show, for the first time to the best
of our knowledge, that MS patients have remarkably elevated concen-
tration of serum lactate respect to control healthy subjects. Further-
more, we also found that increased levels of circulating lactate in MS
patients are tightly correlated with the EDSS scores and with the clinical
Fig. 3. Dispersion graphics inwhich 76 values of serum lactate of controls (randomly selected in the lactate values of the 625 healthysubjects) and eachof the 613 patients were plotted as
a functionof the EDSS scores. To thegroup of the 76 controls, the real 0 on the y axiswas assigned. Thevalue of the correlation coefficient (R
2
=0.419;pb0.0001) indicated that the two
parameters were linearly correlated.
Fig. 4. Box plotshowing the linearcorrelation between the mediansof the values of serumlactate recordedin controls and thosedetermined inMS patients dividedon EDSS scores. Values
in controlsrefer to 76 serum lactate randomly selected in the values of the 625 healthysubjects. To plot this graph, patientswith non-integerEDSS scores were grouped with those of the
nearest upper class, as indicated in the figure. The value of the correlation coefficient (R
2
=0.972;pb0.0001) indicated a statistically significant linear correlation.
1141A.M. Amorini et al. / Biochimica et Biophysica Acta 1842 (2014) 1137–1143
Author's personal copy
MS subtype (RR, SP, PP), thereby opening new perspectives for an easy,
low cost, low invasive monitoring of disease progression.
In the last decades, also thanks to the development of new imaging
techniques such as
1
Hand
31
P MRS, several studies have clearly demon-
strated significant metabolic changes in MS lesions and in normal
appearing white matter suggesting that changes in important metabolic
functions may be implicated in the disease progression. In particular,
decreasein NAA [32–34], decrease in the total
31
P peak integrals and d e-
crease in phosphodiesters/total
31
P[35], increase in total creatine [33,
36], and change in the activity of CPK-BB [13,14,34] are all suggestive
of altered mitochondrial functions and neuronal energy state. In accor-
dance to these findings, we found that MS patients showed significant
alterations of parameters indicative of impaired energy metabolism,
such as uric acid, hypoxanthine, xanthine, and creatinine, not only in
the CSF but also in serum/plasma [18–20].
According to this strong indication that MS is characterized by met-
abolic imbalance due to compromised mitochondrial functions, it is
conceivable to expect that MS may cause an increase in neuronal lactate
production through compensatory mechanisms. Data referring to possi-
ble changes in lactate in MS patients are controversial, since either in-
crease [22–24] or decrease [25] in CSF lactate has been reported. To
compound the uncertainty about changes of lactate in relation to MS,
it should be remembered that both elevated [26] and no change [27]
of brain lactate have been reported. In addition, data available in litera-
ture have mainly been obtained in relatively restricted cohorts of MS pa-
tients [22–25]. However, when lactate was found elevated in the CSF of
MS patients [22–24] no correlation with the disease progression on
EDSS or with the clinical subtype (RR, SP, PP) has been demonstrated,
thus raising questions as to the usefulness of monitoring this molecule
in MS. Moreover, no systematic studies aimed at measuring lactate in
serum/plasma of MS patients have been performed. Recently, it has
been reported that levels of circulating lactate of patients with RR-MS
were not different from those found in controls, even though the results
of this studywere obtained in a very small number of subjects (n= 16,
for both controls and patients) characterized by a low value of EDSS
[37].
The results reported in the present study, demonstrating nearly 3-
times higher values of circulating lactate in MS patients than in control
healthy subjects, allow hypothesizing that either hyperglycolysis of
sclerotic plaques or metabolism of activated inflammatory cells might
give raise to overproduction of lactate, which only transiently remains
in the CSF and rapidly diffuses into the blood stream. This sequence of
events might explain not only the conflicting data of literature
[22–27], but also why the increase in CSF lactate was not found to be
correlated with EDSS or MS clinical subtype [22–27].Itiscertainlypos-
sible that lactate in MS is not constantly overproduced but that it is sub-
jected to fluctuations; this would render detecting significant
differences difficult with respect to controls when assaying lactate in
the nervous tissue or in the CSF. To clarify this issue, it should be impor-
tant to perform longitudinal studies. It is conceivable that most of the
exceeding lactate, intermittently or constantly, flows from the CSF to
the blood, thus explaining the significant differences recorded in the
concentration of serum lactate, even when MS patients were divided
into the RR, SP and PP clinical subtypes (Fig. 2). In fact, we found that
the SP and PP subgroups, characterized by higher mean EDSS scores
(Table 1) dueto higher neurodegenerative component leading to exten-
sive neuroaxonal damage [38], had higher circulating lactate than the
RR-MS subgroup (Fig. 2).
In our cohort of 613 MS patients, when plotting the concentrations
of circulating lactate asa function of the EDSS scores, a linear correlation
has been obtained (Figs. 3 and 4), notwithstanding the presence of
some outliers particularly evident in the EDSS 2.5, 6 and 8. Medians of
0.88 mmol/l serum for the control group and of 1.90 (EDSS 0), 2.12
(EDSS 1), 2.58 (EDSS 1.5–2), 2.78 (EDSS 2.5–3), 3.04 (EDSS 3.5–4),
3.60 (EDSS 4.5–5), 3.75 (EDSS 5.5–6), 4.61 (EDSS 6.5–7) and 4.71
(EDSS 7.5–8) for the MS patients divided on EDSS scores (Fig. 4)
strongly support the hypothesis of a metabolic impairment associated
with the progression of the disease. However, it can be postulated that
neither inflammation nor hyperglycolysis at the sclerotic plaques is suf-
ficient to cause such a remarkable increase (up to 5 times the median
value of controls) in the concentrations of circulating lactate. According
to previous data, MS patients showed an abnormal intramuscular com-
ponent of fatigue [39] and, those with mild disability, evidenced an in-
creased cost of walking [40,41]. Both findings suggest the potential
muscular involvement in MS, possibly caused by a metabolic imbalance
of myocytes, and let to assume that part of the elevated circulating lac-
tate detected in our cohort of MS patients is of muscular origin. It is cer-
tainly important to observe that not all MS patients had serum lactate
higher than that found in controls. A consistent 16.5% of them had
values of circulating lactate falling within the range of variability of con-
trol healthy subjects (Fig. 1).
It is reasonable to suppose that the increase of lactate may trigger (or
may be the result of) a vicious circle in which thecompensatory product
of mitochondrial malfunctioning (lactate) may contribute to worsen
mitochondrial activityitself. In fact, the intracellular acidification caused
by increased lactate production may cause dramatic adverse effects on
various cell functions, including mitochondrial functions [42].
One important additional observation that can be drawn from the
results reported in this study is certainly related to the potential use of
serum lactate determination to follow the disease progression in MS pa-
tients, as well as to monitor the eventual benefits of a pharmacological
treatment. In spite of the very many efforts devoted to find new reliable
biomarkers correlated with MS progression [43–47], to date clinicians
are still waiting to know what should be assayed in order to have objec-
tive parameters, easily measurable, with which predicting the evolution
of the disease or following the efficacy of drug administration. It may
also be affirmed that clinicians are also waiting to know where this po-
tential biomarker should be assayed: (post mortem) brain tissue, CSF,
blood, and extracellular fluid. At present, most of the proposed bio-
markers are expensive in terms of cost of analysis (MRS, MRI, immuno-
genic profile, CD lymphocyte profile, antibodies detection, etc.), of
invasiveness (lumbar puncture), and of still uncertain reliability.
Detection of serum lactate is characterized by a very low cost, limit-
ed invasiveness, high automation, high reproducibility: the present re-
sults, indicating high correlation with the MS progression and MS
clinical subtypes, suggest that lactate has all the characteristics of one
of the best candidate to become one of the biomarkers of choice to fol-
low MS progression and drug efficacy. It may be easily hypothesized
that a frequent serum lactate determination would be of great help for
physicians in knowing how an MS patient responds to a given therapy
and how the disease is progressing. Also, improvement in the quality
of results obtainable by the use of the so called “lactometer”for the
self-made lactate measurement might allow an even more frequent
measurement of this new potential biomarker.
5. Acknowledgements
This work is dedicated to the memory of Professor Anna Paola
Batocchi who had recently passed away. She dedicated her life to
study multiple sclerosis and autoimmune diseases of the central ner-
vous system. Without her initial input and idea, this study would have
never been carried out.
This work has been funded in part by research funds of the Catholic
University of Rome and the University of Catania.
References
[1] E. Miller, Multiple sclerosis, Adv. Exp. Med. Biol. (724) (2012) 222–238.
[2] D. Brassat, When does multiple sclerosis start? Three case reports and a review of
the literature, Rev. Neurol. (Paris) 168 (2012) 846–851.
[3] P. Ehling, S. Bittner, T. Budde, H. Wiendl, S.G. Meuth, Ion channels in autoimmune
neurodegeneration, FEBS Lett. 585 (2011) 3836–3842.
1142 A.M. Amorini et al. / Biochimica et Biophysica Acta 1842 (2014) 1137–1143
Author's personal copy
[4] C. Stadelmann, Multiple sclerosis as a neurodegenerative disease: pathology, mech-
anisms and therapeutic implications, Curr. Opin. Neurol. 24 (2011) 224–229.
[5] A. Seven, M. Aslan, S. Incir, A. Altıntaş, Evaluation of oxidative and nitrosative stress
in relapsing remitting multiple sclerosis: effect of corticosteroi d therapy, Folia
Neuropathol. 51 (2013) 58–64.
[6] A. Fiorini, T. Koudriavtseva, E. Bucaj, R. Coccia, C. Foppoli, A. Giorgi, M.E. Schininà, F.
Di Domenico,F. De Marco, M. Perluigi, Involvement of oxidative stress in occurrence
of relapses in multiple sclerosis: the spectrum of oxidatively modified serum pro-
teins detected by proteomics and redox proteomics analysis, PLoS One 8 (2013)
e65184.
[7] L. Haider, M.T. Fischer, J.M. Frischer, J. Bauer, R. Höftberger, G. Botond, H. Esterbauer,
C.J. Binder, J.L. Witztudim, H. Lassmann, Oxidative damage in multiple sclerosis le-
sions, Brain 134 (2011) 1914–1924.
[8] K.G. Su, G. Banker, D. Bourdette, M. Forte, Axonal degeneration in multiple sclerosis:
the mitochondrial hypothesis, Curr. Neurol. Neurosci. Rep. 9 (2009) 411–417.
[9] K. Su, D. Bourdette, M. Forte, Mitochondrial dysfunction and neurodegeneration in
multiple sclerosis, Front. Physiol. 4 (169) (2013) 1–10.
[10] M. Cambron, M. D'Haeseleer, G. Laureys, R. Clinckers, J. Debruyne, J. De Keyse r,
White-matter astrocytes, axonal energy metabolism, and axonal degeneration in
multiple sclerosis, J. Cereb. Blood Flow Metab. 32 (2012) 413–424.
[11] B.D. Trapp, P.K. Stys, Virtual hypoxia and chronic necrosis of demyelinated axons in
multiple sclerosis, Lancet Neurol. 8 (2009) 280–291.
[12] E. Hattingen, J. Magerkurth, U. Pilatus, A. Hübers, M. Wahl, U. Ziemann, Combined
1
Hand
31
P spectroscopy p rovides new insi ghts into the pathobiochemistry of
brain damage in multiple sclerosis, NMR Biomed. 24 (2011) 536–546.
[13] C. Tur, C.A. Wheeler-Kingshott, D.R. Altmann, D.H. Miller, A.J. Thompson, O.
Ciccarelli, Spatial variability and changes of metabolite concentrations in the
cortico-spinal tract in multiple sclerosis using coronal CSI, Hum. Brain Mapp.
(2012), http://dx.doi.org/10.1002/hbm.22229: 1-12.
[14] C. Steen,N. Wilczak, J.M. Hoogduin, M. Koch, J. De Keyser, Reduced creatine kinase B
activity in multiple sclerosis normal appearing white matter, PLoS One 5 (2010)
e10811.
[15] A. Pandit, J. Vadnal, S. Houston, E. Freeman, J. McDonough, Impaired regulation of
electron transport chain subunit genes by nuclear respiratory factor 2 in multiple
sclerosis, J. Neurol. Sci. 279 (2009) 14–20.
[16] R. Dutta,J. McDonough, X. Yin, J. Peterson, A.Chang, T. Torres, T. Gudz, W.B. Macklin,
D.A. Lewis, R.J. Fox, R. Rudick, K. Mirnics, B.D. Trapp, Mitochondrial dysfunction as a
cause of axonal degeneration in multiple sclerosis patients, Ann. Neurol. 59 (2006)
478–489.
[17] H.E. Andrews, P.P. Nichols, D. Bates, D.M. Turnbull, Mitochondrial dysfunction plays
a key role in progressive axonal loss in multiple sclerosis, Med. Hypotheses 64
(2005) 669–677.
[18] A.M. Amorini, A. Petzold, B. Tavazzi, J. Eikelenboom, G. Keir, A. Belli, G. Giovannoni,
V. Di Pietro, C.Polman, S. D'Urso, R. Vagnozzi, B. Utidehaag, G. Lazzarino,Increase of
uric acid and purine compounds in biological fluids of multiple sclerosis patients,
Clin. Biochem. 42 (2009) 1001–1006.
[19] G. Lazzarino, A.M. Amorini, M.J. Eikelenboom, J. Killestein, A. Belli, V. Di Pietro, B.
Tavazzi, F. Barkhof, C.H. Polman, B.M. Uitdehaag, A. Petzold, Cerebrospinal fluid
ATP metabolites in multiple sclerosis, Mult. Scler. 16 (2010) 549–554.
[20] B. Tavazzi, A.P. Batocchi, A.M. Amorini, V. Nociti, S. D'Urso, S. Longo, S. Gullotta, M.
Picardi, G. Lazzarino, Serum metabolic profile in multiple sclerosis patients, Mult.
Scler. Int. 2011 (167156) (2011) 1–8.
[21] H. Langemann, A. Kabiersch, J. Newcombe, Measurement of low-molecular-weight
antioxidants, uric acid, tyrosine and tryptophan in plaques and white matter from
patients with multiple sclerosis, Eur. Neurol. 32 (1992) 248–252.
[22] W.T. Regenold, P. Phatak, M.J. Makley, R.D. Stone, M.A. Kling, Cerebrospinal fluid ev-
idence of increased extra-mitochondrial glucose metabolism implicates mitochon-
drial dysfuncti on in multiple sclerosis disease progression, J. Neurol. Sci. 275
(2008) 106–112.
[23] I.L. Simone, F. Federico, M. Trojano, C.Tortorella, M. Liguori, P. Giannini, E. Picciola,G.
Natile, P. Livrea, High resolution proton MR spectroscopy of cerebrospinal fluid in
MS patients. Comparison with biochemical changes in dem yelinating plaques, J.
Neurol. Sci. 144 (1996) 182–190.
[24] N.W. Lutz, A. Viola, I. Malikova, S. Confort-Gouny, B. Audoin, J.P. Ranjeva, J. Pelletier,
P.J. Cozzone, Inflammatory multiple-sclerosis plaques generate characteristic meta-
bolic profiles in cerebrospinal fluid, PLoS One 2 (2007) e595.
[25] M.A. Fonalledas Perelló, J.V. Politi, M.A. Dallo Lizarraga, R.S. Cardona, The cerebrospi-
nal fluid lactate is decreasedin early stages of multiple sclerosis,P. R. Health Sci. J. 27
(2008) 171–174.
[26] W.Zaaraoui,A.Rico,B.Audoin,F.Reuter,I.Malikova,E.Soulier,P.Viout,Y. Le
Fur, S. Confort-Gouny, P.J. Cozzone, J. Pellettier, J.P. Ranjeva, Unfolding the
long-term pathophysiological processes following an acute inflammatory de-
myelinating lesion of multiple sclerosis, Magn. Reson. Imaging 28 (2010)
477–486.
[27] M.F.Schocke, T. Berger, S.R.Felber, C. Wolf, F. Deisenhammer, C. Kremser, K. Seppi, F.
T. Aichner,Serial contrast-enhanced magnetic resonance imaging and spectroscopic
imaging of acute multiple sclerosis lesions under high-dose methylprednisolone
therapy, Neuroimage 20 (2003) 1253–1263.
[28] C.H. Polman, S.C. Reingold, G. Edan, M. Filippi, H.P. Hartung, L. Kappos, F.D.
Lublin, L.M. Metz, H.F. McFarland, P.W. O'Connor, M. Sandberg-Wollheim, A.J.
Thompson, B.G. Weinshenker, J.S. Wolinskj, Diagnostic criteria for multiple
sclerosis: 2005 revisions to the “McDonald Criteria”,Ann.Neurol.58(2005)
840–846.
[29] J.F. Kurtzke, Rating neurologic impairment in multiple sclerosis: an expanded dis-
ability status scale (EDSS), Neurology 33 (1983) 1444–1452.
[30] F.D. Lublin, S.C. Reingold, Defining the clinical course of multiple sclerosis: results of
an international survey National MultipleSclerosis Society (USA) Advisory Commit-
tee on clinical tr ials of new agents in multiple sclerosis, Neurology 46 (1996)
907–911.
[31] J.D. Artiss, R.E. Karcher, K.T. Cavanagh, S.L. Collins, V.J. Peterson, S. Varma, B. Zak, A
liquid-stable reagent for lacti c acid levels. Application to the Hi tachi 911 and
Beckman CX7, Am. J. Clin. Pathol. 114 (2000) 139–143.
[32] M.L. Stromillo, A. Giorgio, F. Rossi, M. Battaglini, B. Hakiki, G. Malentacchi, M.
Santangelo, C. Gasperini, M.L. Bartolozzi, E. Portaccio, M.P. Amato, N. De Stefano,
Brain metabolic changes suggestive of axonal damage in radiologically isolatedsyn-
drome, Neurology 80 (2013) 2090–2094.
[33] I.I. Kirov, A. Tal, J.S. Babb, J. Herbert, O. Gonen, Serial proton MR spectroscopy of gray
and white matter in relapsing–remitting MS, Neurology 80 (2013) 39–46.
[34] C. Steen, M. D'haeseleer, J.M. Hoogduin, Y. Fierens, M. Cambron, J.P. Mostert, D.J.
Heersema, M.W. Koch, J. De Keyser, Cerebral white matter blood flow and energy
metabolism in multiple sclerosis, Mult. Scler. 19 (2013) 1282–1289.
[35] C.A. Husted, D.S. Goodin, J.W. Hugg, A.A. Maudsley, J.S. Tsuruda, S.H. de Bie, G. Fein,
G.B. Matson, M.W. Weiner, Biochemical alterations in multiple sclerosis lesions and
normal-appearing white matter detected by in vivo
31
Pand
1
H spectroscopic imag-
ing, Ann. Neurol. 36 (1994) 157–165.
[36] M. Bagory, F. Durand-Dubief, D. Ibarrola, J.C. Comte, F. Cotton, C. Confavreux, D.
Sappey-Marinier, Implementation of an absolute brain 1H-MRS quantification
method to assess different tissue alterations in multiple sclerosis, IEEE Trans.
Biomed. Eng. 59 (2012) 2687–2694.
[37] A.Mähler,J.Steiniger,M.Bock,A.U.Brandt,V.Haas,M.Boschmann,F.Paul,Is
metabolic flexibility altered in multiple sclerosis patients? PLoS One 7 (2012)
e43675.
[38] W. Brück, C. Stadelmann, Inflammation and degeneration in mu ltiple sclerosis,
Neurol. Sci. 24 (Suppl. 5) (2003) S265–S267.
[39] K.R. Sharma, J. Kent-Braun, M.A. Mynhier, M.W. Weiner, R.G. Miller, Evidence of an
abnormal intramuscular component of fatigue in multiple sclerosis, Muscle Nerve
18 (1995) 1403-1111.
[40] N.F. Taylor, K.J. Dodd, D. Prasad, S. Denisenko, Progressive resistance exercise for
people with multiple sclerosis, Disabil. Rehabil. 28 (2006) 1119–1126.
[41] M. Franceschini, A. Rampello, F. Bovole nta, M. Aiello, P. Tzani, A. Chetta, Cost of
walking, exertional dyspnoea and fatigue in individuals with multiple sclerosi s
not requiring assistive devices, J. Rehabil. Med. 42 (2010) 719–723.
[42] R.A. Robergs, F. Ghiasvand, D. Parker, Biochemistry of exercise-induced
metabolic acidosis, Am. J. Physiol. Regul. Integr. Comp. Physiol. 287 (2004)
R502–R516.
[43] I. Dujmovic, Cerebrospinal fluid and blood biomarkers of neuroaxonal damage in
multiple sclerosis, Mult Scler Int (2011), http://dx.doi.org/10.1155/2011/767083.
[44] U. Ziemann, M. Wahl, E. Hattingen, H. Tumani, Development of biomarkers for
multiple sclerosis as a neurodegenerative disorder, Prog. Neurobiol. 95 (2011)
670–685.
[45] V. Pravica, D. Popadic, E. Savic, M. Markovic, J. Drulovic, M. Mostarica-Stojkovic, Sin-
gle nucleotide polymorphisms in multiple sclerosis: disease susceptibility and treat-
ment response biomarkers, Immunol. Res. 52 (2012) 42–52.
[46] V. Singh, R.Q. Hintzen, T.M. Luider, M.P. Stoop, Proteomics technologies for
biomarker discovery in multiple sclerosis, J. Neuroimmunol. 248 (2012)
40–47.
[47] T. Tourdias, V. Dousset, Neuroi nflammatory imaging biomarkers: relevance to mul-
tiple sclerosis and its therapy, Neurotherapeutics 10 (2013) 111–123
1143A.M. Amorini et al. / Biochimica et Biophysica Acta 1842 (2014) 1137–1143