Download Phosphorus and proton magnetic resonance

doi:10.1093/brain/awp293
Brain 2009: 132; 3285–3297
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BRAIN
A JOURNAL OF NEUROLOGY
Phosphorus and proton magnetic resonance
spectroscopy demonstrates mitochondrial
dysfunction in early and advanced Parkinson’s
disease
Elke Hattingen,1 Jörg Magerkurth,1 Ulrich Pilatus,1 Anne Mozer,2 Carola Seifried,2
Helmuth Steinmetz,2 Friedhelm Zanella1 and Rüdiger Hilker2
1 Institute of Neuroradiology, J.W. Goethe University, Frankfurt/Main, Germany
2 Department of Neurology, J.W. Goethe University, Frankfurt/Main, Germany
Correspondence to: Elke Hattingen, MD,
Institute of Neuroradiology,
J.W. Goethe University Schleusenweg 2 – 16,
60528 Frankfurt/Main,
Germany
E-mail: [email protected]
Mitochondrial dysfunction hypothetically contributes to neuronal degeneration in patients with Parkinson’s disease. While
several in vitro data exist, the measurement of cerebral mitochondrial dysfunction in living patients with Parkinson’s disease
is challenging. Anatomical magnetic resonance imaging combined with phosphorus and proton magnetic resonance spectroscopic imaging provides information about the functional integrity of mitochondria in specific brain areas. We measured partial
volume corrected concentrations of low-energy metabolites and high-energy phosphates with sufficient resolution to focus on
pathology related target areas in Parkinson’s disease. Combined phosphorus and proton magnetic resonance spectroscopic
imaging in the mesostriatal region was performed in 16 early and 13 advanced patients with Parkinson’s disease and compared
to 19 age-matched controls at 3 Tesla. In the putamen and midbrain of both Parkinson’s disease groups, we found a bilateral
reduction of high-energy phosphates such as adenosine triphophosphate and phosphocreatine as final acceptors of energy from
mitochondrial oxidative phosphorylation. In contrast, low-energy metabolites such as adenosine diphophosphate and inorganic
phosphate were within normal ranges. These results provide strong in vivo evidence that mitochondrial dysfunction of mesostriatal neurons is a central and persistent phenomenon in the pathogenesis cascade of Parkinson’s disease which occurs early in
the course of the disease.
Keywords: Parkinson’s disease; MR spectroscopy; 31P MRS; energy metabolism; mitochondrial dysfunction
Abbreviations: ADP = adenosine diphosphate; ATP = adenosine triphosphate; MRSI = magnetic resonance spectroscopic imaging;
PCr = phosphocreatine; Pi = inorganic phosphate
Received July 29, 2009. Revised September 23, 2009. Accepted September 24, 2009
ß The Author (2009). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved.
For Permissions, please email: [email protected]
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Introduction
Parkinson’s disease is the most common neurodegenerative movement disorder with a very high socioeconomic impact. The clinical
symptoms of early stage Parkinson’s disease mainly result from
progressive degeneration of dopaminergic neurons in the substantia nigra and other monoaminergic cell groups in the brainstem
(Braak et al., 2003) accompanied by increased microglial activation
and intraneural accumulation of proteins called Lewy bodies
(Forno, 1996).
Though Parkinson’s disease is a sporadic condition of uncertain
aetiology, there is some evidence that mitochondrial dysfunction
considerably contributes to the pathogenesis of the disorder
(Schapira, 2008). Since the brain is the organ system which
is most reliant on mitochondrial energy supply, it is particularly
susceptible to mitochondrial dysfunction (Wallace, 2005). Postmortem studies of brain tissue reported diminished cortical and
nigral complex I activity in the mitochondrial electron transport
system in Parkinson’s disease (Schapira, 1994; Keeney et al.,
2006). Further studies observed mitochondrial complex I deficiency in blood cells and muscle tissue of patients with
Parkinson’s disease (Parker et al., 1989; Shoffner et al., 1991;
Yoshino et al., 1992; Schapira et al., 1999). Recently, familial
monogenetic parkinsonism has been shown to result from autosomal mutations in gene loci encoding for proteins which are
involved in mitochondrial functioning (Polymeropoulos et al.,
1997; Hyun et al., 2002; Palacino et al., 2004; Valente et al.,
2004). Therefore, the question arises whether disturbances of
energy metabolism can also be detected in living Parkinsonian
humans. This is of special interest in the early stage of
Parkinson’s disease when possible disease modifying therapeutic
interventions targeted at mitochondrial functioning are most
promising. To provide answers to this question, phosphorus (31P)
magnetic resonance spectroscopic imaging (MRSI) is a suitable
tool since this technique allows direct monitoring of the energy
metabolism of the brain (Ross and Bluml, 2001). Consequently,
cerebral oxidative energy metabolism has been studied with
31
P MRSI in mitochondrial cythopathies (Eleff et al., 1990;
Montagna et al., 1992; Barbiroli et al., 1993), but also in
Parkinson’s disease (Montagna et al., 1993; Barbiroli et al.,
1999; Hu et al., 2000; Rango et al., 2006). Most of these studies
evaluated adenosine diphosphate (ADP) concentration as a widely
accepted major regulator in mitochondrial activity (Chance et al.,
1955, 1986) from the phosphocreatine/adenosine triphosphate
(PCr/ATP) ratio, assuming constant values for ATP (3 mmol/l)
(Eleff et al., 1990; Barbiroli et al., 1993, 1999; Montagna et al.,
1992, 1993). In mitochondrial cythopathies, decreased PCr as well
as increased inorganic phosphate (Pi) and ADP was reported,
whereas in patients with advanced Parkinson’s disease only
increased inorganic phosphate/ATP ratios but no change in PCr/
ATP ratio were found (Montagna et al., 1993; Barbiroli et al.,
1999). Thus an altered phosphate metabolism rather than mitochondrial malfunction was suggested (Barbiroli et al., 1999).
Two previous studies investigated ATP in Parkinson’s disease
rather than the PCr/ATP ratio (Hu et al., 2000; Rango et al.,
2006; for review see Henchcliffe et al., 2008). Rango and colleagues observed a decrease of occipital high-energy phosphates
E. Hattingen et al.
including ATP during the recovery period after visual stimulation
in patients with Parkinson’s disease but not in controls (Rango
et al., 2006); while Hu et al., (2000) found decreased b-ATP
ratios in a large midline voxel including the meso-diencephalon
in rest condition.
In this study we obtained a more comprehensive picture of
energy metabolism with a combined 31P and 1H MRSI study,
which provides absolute ADP, ATP and PCr concentrations in
two well-defined cohorts of patients with early and advanced
Parkinson’s disease. We used spectroscopic imaging at a 3 Tesla
scanner with a double tuned 1H/31P-volume coil which allowed us
to focus on the substantia nigra and on the putamen since these
are anatomical key areas in the neurodegenerative process of the
dopaminergic system in Parkinson’s disease.
Materials and methods
Study subjects
The study was approved by the local ethics committee and informed
consent was obtained from each participant prior to inclusion. We
investigated 29 patients with Parkinson’s disease and 19 age-matched
healthy controls without neurological, psychiatric or systemic diseases.
Exclusion criteria were alcohol and substance abuse, dementia, history
of epilepsy or stroke, structural brain disease, brain surgery and severe
arterial hypertension or diabetes mellitus. The diagnosis of Parkinson’s
disease was established according to the UK Brain Bank criteria
(Hughes et al., 1992). Patients with Parkinson’s disease were stratified
according to the Hoehn and Yahr scale into early (Hoehn and Yahr I
and II, n = 16) and advanced disease (Hoehn and Yahr III and IV,
n = 13). Gender was almost matched for early disease and healthy
controls while patients with advanced disease were mainly male.
Demographic and clinical data of the Parkinson’s disease cohorts are
given in Table 1.
Magnetic resonance spectroscopy
imaging
MRSI of the brain was performed on a 3 T whole body system
(Magnetom Trio, Siemens Medical AG, Erlangen, Germany) with a
double tuned 1H/31P volume head coil (Rapid Biomedical, Würzburg,
Germany). Antiparkinsonian medication was stopped 12 h prior to
MRSI. Two MRSI slices were recorded with 1H MRSI: an axial slice
including the putamen and a coronal slice aligned on the dorsal line of
the pontine and midbrain tegmentum. A weighted circular phase
encoding scheme was used with repetition time 1500 ms, echo time
30 ms and 2 acquisitions. The volume of interest was selected by a
combination of point resolved selective spectroscopy and outer volume
suppression. For the coronal orientation a 28 28 matrix with
240 240 mm2 field of view and 10 mm slice thickness was acquired.
The axial slice was recorded with a 16 16 matrix, field of view of
240 240 mm2 and 12 mm slice thickness. Before Fourier transformation, the matrix was extrapolated to 48 48 (coronal) or 32 32
(axial) resulting in a 5 5 mm2 or 7.5 7.5 mm2 in plane grid size.
For 31P spectroscopy, a 3D MRSI sequence with wideband alternating
phase low power technique for zero residual splitting proton decoupling was used with flip angle 60 , repetition time 2000 ms, echo time
2.3 ms and 10 acquisitions. An axial slab of 100 mm aligned to the
axial 1H MRSI slice was recorded employing circular phase encoding
MRSI in Parkinson’s disease for mitochondrial function
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Table 1 Demographic and clinical data of patients with Parkinson’s disease and controls
Stage of disease
Age (years)
Sex
Duration of disease (years)
Age at onset of Parkinson’s disease (years)
Type of parkinsonism
Side of Parkinson’s disease onset
Levodopa equivalence dosea
Agonist monotherapy
Without therapy
Unified Parkinson disease rating scale III off stateb
n
Mean and SD
Median and range
n
Mean and SD
Median and range
Mean and SD
Akinetic (a)
Equivalence (e)
Tremor (t)
n
mg
n
n
Controls
Hoehn and Yahr I–II
Hoehn and Yahr III–IV
19
62.9 7.9
66 (50–78)
9 males/10 females
–
–
–
16
62.4 9.2
60 (45–77)
11 males/5 females
6.4 4.3
5.5 (2–17)
56 9
8 a/5 e/3 t
13
66.7 7.6
68 (48–76)
12 males/1 female
10.5 4.6
10 (7–20)
57 6
6 a/6 e/1 t
–
–
–
–
–
7 right/9 left
347 244
5
2
17 6
7 right/6 left
680 371
2
0
30 7
a One milligram of pergolide, 1 mg of lisuride, 1 mg of pramipexole, 2 mg of carbergoline, 5 mg of ropinirole, 10 mg of bromocriptine, 10 mg of apomorphine, 20 mg of
dihydroergocriptine = 100 mg levodopa.
b Obtained at least 12 h after cessation of antiparkinsonian medication (practically defined off).
with a weighted acquisition scheme on a 10 10 8 matrix,
field of view of 300 300 200 mm3, nominal voxel size of
30 30 25 mm3. The matrix size was extrapolated to a
20 20 16 matrix resulting in a series of axial slices with 12.5 mm
thickness and 15 15 mm2 in plane grid size. For taking into account
partial volume effects originating from the cerebrospinal fluid, the fraction of grey and white matter contributing signal to each voxel was
calculated as described in literature (Hetherington et al., 1996). In
brief, segmented T1-weighted 3D images of the total brain were
aligned to the MRSI slab followed by digital filtering to mimic the
effect of the poor point spread function and resolution caused by
the limited number of phase encoding steps (Gasparovic et al.,
2006). The resulting parameter maps provided a value for the partial
volume of grey and white matter for each MRSI voxel. The basic data
for tissue segmentation were obtained from a sagittal oriented magnetization prepared rapid gradient echo sequence performed with
1.3 mm isotropic resolution in 4 min and 8 s scan time. In order to
match these datasets with the MRSI scans, a short magnetization
prepared rapid gradient echo was measured aligned to the MRSI
slab. The shorter acquisition time of 1 min and 39 s was achieved by
reduced resolution (2 mm isotropic). Oversampling of 38% in the
head-to-foot direction was applied to avoid aliasing. The whole magnetic resonance examination took 45 min.
Data processing
Data were processed offline on a Linux workstation. Spatially transformed MRSI from the scanner console were resampled to the
required grid resolution by Fourier transformation and zero-filling,
and inverse Fourier transformation using MATLAB (The Mathworks,
Inc., Natick, MA, USA). Segmentation of anatomical data was performed with the vbm5 extension (http://dbm.neuro.uni-jena.de/
vbm/vbm5-for-spm5/) in Statistical Parametric Mapping-5 (http://
www.fil.ion.ucl.ac.uk/spm/). The MRSI-aligned low quality 3D
images were registered to the high quality anatomy by rotational
and translational transformations (6 degrees of freedom) with
Functional Magnetic Resonance Imaging of the Brain’s (FMRIB)
Linear Image Registration Tool, which performs linear interand intra-modal registration within the FMRIB Software Library
(http://www.fmrib.ox.ac.uk/fsl/). The inverse registration matrix was
then used to transform the segmented data onto the MRSI coordinate
system in order to obtain the anatomical information for each MRSI
voxel.
Down-sampling and filtering of anatomical information to MRSI
resolution was performed with MATLAB according to the procedure
previously described by Gasparovic et al. (2006). In addition to filtering, the dataset was multiplied before spatial Fourier transformation
with a linear increasing phase in up to three directions causing a ‘grid
shift’ which corrects for different offsets of the 31P slab and the 1H
slice. The 31P spectra were analysed in the time domain with the
jMRUI software tool (Version 3.0, available at http://www.mrui
.uab.es) employing a non-linear least square fitting algorithm
(AMARES) (Vanhamme et al., 1997). The time domain model function
was composed of 14 exponentially decaying sinusoids in the frequency
domain. Six of those, which had identical damping, were corresponding to peaks assigned PCr, phosphocholine, glycero-phosphocholine,
phosphoethanolamine, glycero-phosphoethanolamine and Pi. PCr was
adjusted to 0 ppm and constraints for the chemical shifts of the other
signals except for Pi were applied as a fixed difference with regard to
the position of PCr. ATP was represented by seven exponentially
damped sinusoids, defining each multiplet by the respective number
of peaks with identical damping and adequate amplitude ratios. The
coupling constant was fixed at 18 Hz. One signal with a fixed chemical
shift of 2.24 ppm and maximum line width of 50 Hz was used to
account for potential macromolecule signals in the phosphodiester
region.
The 1H MRSI spectra were fitted in the frequency domain by
a linear combination of a set of model spectra including the main
metabolites total choline (tCho), total creatine and total
N-acetylaspartate using the commercially available software tool
LCModel (Provencher, downloadable test version at http://
s-provencher.com) (Provencher, 1993). Baseline correction was performed including macromolecules. Absolute concentrations were
calculated by referring to an independent measurement with a spherical phantom of 15 cm diameter containing a solution of 20 mmol/l
creatine and 20 mmol/l phosphate. For 1H MRSI, the in vivo sequence
was used but repetition time was increased to 10 s. For 31P MRSI, 2D
MRSI was performed instead of a 3D approach to avoid errors due to
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the poor point spread function. A full 16 16 matrix (field of view
240 240 mm2) was acquired with 90 flip angle and a repetition time
of 40 s. The coil loading, which was obtained from the radiofrequency
power required to achieve a 90 pulse for 1H was adjusted with
sodium chloride to match the mean coil loading of the in vivo studies.
For 1H MRSI, correction terms for longitudinal (T1) and transversal
relaxations were applied as described by our group recently
(Hattingen et al., 2008). The 31P data were corrected for the reduced
flip angle (60 ) and partial saturation using T1s of 2.4 s for PCr, 1.1 s
for Pi, and 1.0 s for ATP resulting in intensity correction terms of 1.6,
1.27 and 1.24, respectively. The relaxation times were within the error
range of published data measured at 1.5 (Buchli et al., 1994) and 4 T
(Hetherington et al., 2001). The calibration of signal intensity was
done with the phantom replacement method (Michaelis et al.,
1993). Coil loading was taken into account as a covariate in the statistical analysis.
Anatomical parameters for the two target regions are summarized in
Figs 1 and 2. Figure 1a shows the axial MRSI slice for 1H MRSI and
E. Hattingen et al.
31
P MRSI in a sagittal image. The respective grid resolution is shown
for 1H in Fig. 1c and for 31P in Fig. 1d. The orange framed voxels from
the putamen of each hemisphere were studied. Representative spectra are shown in Fig. 1b. The selection of corresponding 1H and 31P
data for the midbrain are depicted in Fig. 2. The sagittal image
(Fig. 2a) depicts the orientation of the coronal 1H and the axial
31
P slices.
All spectra from the selected voxels were inspected visually. Bad
data were discarded according to the following criteria: (i) remaining
signals in 31P residual data; (ii) either huge baseline modulation or
extensive line broadening that obscures the discrimination between
total choline and total creatine in 1H data and (iii) the Cramer-Rao
lower bounds (%SD) of the non-linear fit exceeded 20% for both total
creatine and total choline, in 1H data. The remaining data were used
for further analysis.
In healthy control brains, lactate is not detectable by 1H MRSI with
the data acquisition scheme described (Isobe et al., 2007). However,
anaerobic glycolysis (i.e. an excess of glycolysis over oxidative
Figure 1 Anatomical details and MRSI slice orientation for putamen. (a) Sagittal image showing the orientation and feet-head
extension of the axial 2D 1H MRSI (red borders). The respective slice of the 3D 31P MRSI data (green bar) was adjusted by grid shift to
match position of the 1H MRSI slice (see Material and methods section). (b) Representative 31P spectra (upper row) and 1H spectra
from the target areas. The red line marks the result of the fitting procedure. (c) Axial slice with grid representing the resolution of 31P
MRSI data. An in-plane grid shift was applied to obtain anatomically matched midlines of the 31P MRSI slice and the 1H MRSI slice
(b) The dorsal part of the putamen from each hemisphere was selected as target region (orange squared voxel). (d) Axial slice with grid
representing the resolution of 1H MRSI data. The orange marked area matches the respective region in (c).
MRSI in Parkinson’s disease for mitochondrial function
Brain 2009: 132; 3285–3297
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Figure 2 Anatomical details and MRSI slice orientation for midbrain. (a) Sagittal image showing the orientation and extensions of the
2D 1H MRSI (red bar) slice and an appropriate slice of the 3D 31P MRSI data (green bar). The 31P MRSI slice was adjusted to the
midbrain by grid shift. (b) Representative 31P spectra (upper row) and 1H spectra from the target areas. The red line shows the result of
the fitting procedure. (c) Axial slice with grid representing anatomy and resolution of 31P MRSI data. An in-plane grid shift was applied
to position the centre in the cerebral peduncle as indicated by the broken white lines. The red line marks the intersection with the
centre of the 1H MRSI slice. The orange squared voxels represent the target region. (d) Coronal 1H MRSI slice with the target voxels.
Six voxels matching the target volume in (c) are framed in orange. The green line marks the centre of the intersection with the
31
P slice (c).
phosphorylation) can lead to elevated and therefore detectable lactate
levels (Prichard et al., 1991). The LCModel software provides a value
for the lactate concentration and an estimation of its accuracy is given
(%SD). Each complete MRSI data set was screened for lactate SD
values 520%. The presence of a clear positive doublet signal at
1.3 ppm in the spectra was then verified. Voxels fulfilling these criteria
were considered to have elevated lactate levels.
Calculated parameters
The pH was determined from the signal position of inorganic phosphate (Pi) and the concentration of magnesium (Mg)2+. The latter was
estimated from the chemical shift difference between the b-ATP and
the phosphocreatine signal (b) according to the formula given by Iotti
et al. (1996, 2000) using the tool provided by the authors (http://
www.cermiv.unibo.it/):
(i) pMg = 4.24
log10 [(18.58 + b)0.42/( 15.74
b)0.84]
(ii) pH = 6.706
0.0307 [Mg] + log10 [(Pi
3.245)/(5.778
Pi)]
The following parameters were calculated from measured values
(Petroff et al., 1985; Pietz et al., 2003; Iotti et al., 2005):
(i) ADP concentrations were calculated based on the equilibrium constant of the creatine kinase reaction KCK (Iotti et al.,
2005):
[ADP] = ([total creatine] [PCr]) [b-ATP]/([PCr] [H] KCK)
KCK = 4.0 108 M 1 and [H] = 10 pH M
The value of KCK was estimated according to the calculation
presented in the paper of Iotti et al. (2005).
(ii) Unphosphorylated choline concentration [Cho] was calculated as difference
[Cho] = [total choline] [phosphocholine]
[glycero-phosphocholine];
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NA = not applicable. Values indicate amount of metabolite (given in mmol) divided by the volume of the region of interest (given in l). The resulting concentrations (in mmol/l) still require correction for partial volume effects to depict tissue
concentrations. The partial volume was determined from registered anatomical images (see Materials and methods section). Coil loading might also affect the MRSI detected concentrations. Means (in arbitrary units) were 168.8 (12.8), 168.0
(14.3) and 178.6 (10.2) for control, mild and severe group, respectively. High energy metabolites (HEP) were determined as sum of ATP and PCr concentrations. ADP and low energy metabolites (LEM) were calculated by combining 31P and
1
H data (see Materials and methods section). pH was determined from the chemical shift difference of inorganic phosphate and phosphocreatine, as described in Materials and methods section. Energy metabolism related metabolites with
significant differences are printed in bold. Significance was determined using post hoc Scheffé Test (see Materials and methods section).
11
9
0.74 (0.108)
0.89 (0.058)
2.44 (0.40)
0.69 (0.26)
0.026 (0.018)
0.92 (0.20)
6.949 (0.030)
3.14 (0.46)
3.40 (0.90)
15
15
0.76 (0.079)
0.91 (0.039)
2.67 (0.37)
0.66 (0.26)
0.022 (0.009)
0.86 (0.24)
6.935 (0.036)
3.33 (0.58)
3.79 (1.33)
11
10
0.74 (0.106)
0.87 (0.063)
2.48 (0.44)
0.61 (0.23)
0.025 (0.027)
0.92 (0.20)
6.952 (0.027)
3.10 (0.49)
3.45 (1.56)
15
14
0.75 (0.079)
0.90 (0.046)
2.66 (0.36)
0.65 (0.23)
0.024 (0.009)
0.87 (0.14)
6.939 (0.015)
3.32 (0.54)
3.97 (0.98)
19
17
0.80 (0.087)
0.92 (0.032)
2.79 (0.39)
0.88 (0.27)
0.027 (0.013)
0.97 (0.21)
6.938 (0.013)
3.67 (0.55)
3.86 (0.89)
9
8
0.92 (0.091)
1.02 (0.052)
2.62 (0.35)
1.44 (0.33)
0.087 (0.016)
1.04 (0.21)
6.932 (0.014)
4.06 (0.54)
6.43 (1.38)
15
15
0.96 (0.096)
0.99 (0.062)
2.84 (0.41)
1.49 (0.31)
0.088 (0.024)
1.12 (0.33)
6.934 (0.017)
4.33 (0.64)
6.51 (1.16)
9
8
0.092 (0.079)
1.00 (0.077)
2.61 (0.37)
1.35 (0.28)
0.090 (0.027)
1.02 (0.29)
6.934 (0.016)
3.96 (0.48)
6.55 (0.85)
15
15
0.94 (0.086)
0.98 (0.079)
2.72 (0.40)
1.48 (0.23)
0.087 (0.020)
1.02 (0.22)
6.921 (0.011)
4.20 (0.54)
6.14 (0.95)
III–IV
I–II
I–II
III–IV
NA
I–II
III–IV
Ipsilateral
Contralateral
III–IV
I–II
NA
n for P data
19
n for 1H and combined data 19
Tissue fraction for 31P
0.99 (0.095)
Tissue fraction for 1H
0.98 (0.057)
Phosphocreatine
3.31 (0.44)
ATP
1.86 (0.22)
ADP
0.102 (0.021)
Inorganic phosphate
1.16 (0.22)
pH
6.924 (0.009)
HEP
5.17 (0.60)
LEM
6.92 (0.96)
31
Hoehn and Yahr
The amounts of metabolites divided by the volume of the region
of interest are listed in Tables 2 and 3. The resulting concentrations (in mmol/l) still require correction for partial volume effects
to depict tissue concentrations. The partial volume was determined
from registered anatomical images (see Material and methods section) and is listed as tissue fractions for 31P and 1H voxels in separate rows in Table 2. As expected, there is a considerable amount
of cerebrospinal fluid (25%) in the 31P target area of the midbrain.
Due to the high resolution and careful visual alignment to the
anatomy, partial volume effects for 1H MRSI are in the order of
10%. No significant difference was detected between control and
the two stages of the disease. Significance was calculated taking
into account partial volume effects and coil loading using the general linear model. Significant changes against the control group are
Midbrain
Results
Control
Statistical analysis was performed with STATISTICA (version 7.1,
StatSoft, Tulsa, OK, USA). Mean values for each metabolite were
calculated for every volume of interest separately, for both cerebral
hemispheres. The latter were assigned ipsi- and contralateral to the
clinically most affected side of the body in patients with Parkinson’s
disease. For healthy subjects, the data of both hemispheres were
averaged.
In addition, a mean value for the tissue fraction of the respective
area was calculated as the sum of grey- and white-matter fractions
The statistical analysis was based on the General Linear Model using
multivariate analysis of variance (ANOVA) with coil loading and tissue
contents for both modalities as covariates. According to the a priori
hypothesis of the study, the concentrations of metabolites related to
cerebral energy metabolism (ATP, PCr, Pi, ADP) were analysed for
significant difference with ANOVA with post hoc correction for multiple comparisons (Scheffé test) using target region and control/early
(Hoehn and Yahr I/II) and advanced Parkinson’s disease (Hoehn and
Yahr III/IV) as categorical variables. Changes in pH were analysed with
ANOVA without covariates, since these parameters depend on signal
position only. Significant changes (P50.05) for each variable and
localization were reported. For all other metabolites not directly related
to energy metabolism significance levels were estimated by contrast
analysis with univariate ANOVA. Side related concentration differences
were analysed by multivariate ANOVA with repeated measurements.
Metabolite differences were tested for significance using a post hoc
Scheffé test.
Ipsilateral
Statistical methods
Contralateral
Metabolite concentration differences were calculated for each volume
of interest in individual datasets. Since tissue concentrations were
calculated, a correction for different partial volume effects in both
MRSI modalities was performed. This was achieved by transforming
the volume concentrations of the 1H detectable metabolites to values
which are related to the respective tissue fraction of the 31P MRSI data
using the ratio of 31P tissue fraction to 1H tissue fraction as a correction factor. Metabolite intensities were also corrected for the dependence on coil loading with linear regression.
Control
[PCr]) + [Pi].
Putamen
(iii) [High-energy phosphates] = [ATP] + [PCr];
(iv) [Low-energy metabolites] =
[ADP] + ([total creatine]
E. Hattingen et al.
Table 2 Concentrations of energy metabolites in different brain areas ipsilateral and contralateral to the clinically most affected body side at different stages of
disease compared to healthy controls
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NA = not applicable. Values indicate amount of metabolite (given in mmol) divided by the volume of the region of interest (given in l). The resulting concentrations (in mmol/l) still require correction for partial volume effects
listed in Table 2 to depict tissue concentrations. Coil loading might also affect the 1H MRSI detected concentrations. Means (in arbitrary units) were 168.8 (12.8), 168.0 (14.3) and 178.6 (10.2) for control, mild and severe
group, respectively. Metabolite differences were tested for significance by contrast analysis according to the General Linear Model (see Materials and methods section) Values with P50.05 are printed in bold. Choline was
calculated by combining 31P and 1H data (see Materials and methods section).
(0.07)
(0.21)
(0.48)
(0.15)
(0.28)
(0.44)
(1.13)
(2.31)
(0.07) 0.17
(0.24) 1.19
(0.40) 0.64
(0.19) 0.74
(0.25) 1.22
(0.54) 2.36
(1.54) 5.68
(2.37) 11.06
(0.07) 0.17
(0.22) 1.20
(0.75) 0.76
(0.14) 0.86
(0.35) 1.19
(0.52) 2.57
(1.45) 6.75
(1.75) 12.91
(0.07) 0.19
(0.22) 1.21
(0.55) 0.75
(0.17) 0.74
(0.20) 1.28
(0.60) 2.58
(1.05) 5.71
(2.15) 11.52
(0.07) 0.17
(0.20) 1.18
(0.44) 1.07
(0.17) 0.87
(0.25) 1.18
(0.43) 2.85
(0.91) 6.91
(1.45) 13.16
(0.085) 0.16
(0.22)
1.21
(0.45)
0.89
(0.14)
0.92
(0.13)
1.20
(0.47)
2.63
(1.69)
6.48
(1.61) 12.69
(0.12) 0.16
(0.28) 1.44
(0.44) 0.92
(0.20) 0.44
(0.25) 1.28
(0.50) 2.78
(1.48) 8.41
(1.94) 12.38
(0.060) 0.19
(0.33)
1.48
(0.40)
1.02
(0.17)
0.88
(0.27)
1.27
(0.24)
2.78
(0.74)
8.51
(0.89) 13.92
(0.064) 0.16
(0.19)
1.55
(0.46)
0.84
(0.20)
0.82
(0.27)
1.43
(0.49)
2.75
(1.26)
8.39
(1.70) 12.37
(0.053) 0.12
(0.22)
1.43
(0.050) 1.07
(0.15)
0.83
(0.25)
1.16
(0.43)
2.74
(0.98)
8.19
(1.50) 13.00
Phosphocholine
0.18
Glycero-phosphocholine
1.64
Choline
1.11
Phosphoethanolamine
1.04
Glycero-phosphoethanolamine 1.45
Total choline
2.89
Total creatine
8.98
Total N-Acetyl-Aspartate
13.44
III–IV
I–II
I–II
I–II
NA
Hoehn and Yahr
Contralateral
III–IV
Ipsilateral
III–IV
NA
I–II
III–IV
Ipsilateral
Contralateral
Control
Control
This is the first quantitative 31P MRSI and 1H MRSI study which
investigates brain energy metabolism measuring the concentration
of total creatine, PCr, Pi, ATP and ADP in the midbrain and putamen of early and advanced patients with Parkinson’s disease. The
data demonstrate defects of mitochondrial oxidative phosphorylation with depletion of high-energy phosphates in the mesostriatal
region occurring early in the course of the disorder. They are in
line with the previous 31P study which investigated a large midline
voxel including the basal ganglia and brainstem (Hu et al., 2000).
This study measured the metabolite values either in terms of ratios
to ATP or to the integrated signal intensity of the entire 31P spectrum. Since ATP contributes significantly to the total amount of
phosphate, the decrease in ATP might simulate the increase of
other metabolites. Hu et al. (2000) reported a significant decrease
of ATP in the central voxel as well as a temporo-parietal rise of Pi,
both measured as ratio to total 31P. The authors suggested a shift
to anaerobic metabolism. In a more recent study, Rango et al.
(2006) measured the concentration of high-energy phosphates
in the visual cortex before, during and following visual stimulation.
The data were referenced to a standard solution which was recorded together with the in vivo data to avoid the use of ATP as
internal standard. They observed a decrease compared to controls,
but only in the recovery period. At rest the ATP decrease may be
Midbrain
Discussion
Putamen
printed in bold (multivariate post hoc Scheffé test). The other
metabolites are shown in Table 3. The terms ipsilateral and contralateral define the hemisphere in reference to the clinically most
affected body side. Significant changes (univariate ANOVA) are
printed in bold. Adjusted means calculated by the General Linear
Model approach are shown in Figs 3–5 for energy metabolites.
ATP was decreased versus controls in the putamen and in the
midbrain of patients with early and advanced stage of Parkinson’s
disease. All mean differences in ATP reached statistical significance
(P50.05) with the exception of the ipsilateral midbrain in
advanced Parkinson’s disease. PCr was significantly reduced in
the putamen of both hemispheres in the early and advanced
patient cohorts (P50.05) and showed a consistent similar trend
in the ipsi- and contralateral midbrain. High-energy phosphates
were significantly decreased in all contralateral areas for the
early and advanced stage. For ipsilateral hemisphere, the decrease
was only significant in the putamen. In contrast, ADP, Pi and lowenergy metabolites concentration did not show a consistent trend
in the two target regions with a slight decrease for ADP in the
putamen and rather an increase in the midbrain but the differences were small and did not reach statistical significance. The pH
was significantly increased in the contralateral putamen for the
advanced stage of Parkinson’s disease. Lactate was detected in
two patients and one healthy subject, all other subjects did not
show any sign of elevated lactate.
For other metabolites (Fig. 6) decreased concentrations of
the membrane lipid precursors (phosphoethanolamine, PCho)
and degradation products (glycero-phosphocholine, glycerophosphoethanolamine) were found in early Parkinson’s disease,
but not in the advanced stage of the disease.
Brain 2009: 132; 3285–3297
Table 3 Concentrations of metabolites not involved in energy metabolism in different brain areas ipsilateral and contralateral to the clinically most affected body
side at different stages of disease compared to healthy controls
MRSI in Parkinson’s disease for mitochondrial function
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| Brain 2009: 132; 3285–3297
E. Hattingen et al.
Figure 3 Concentration of energy metabolism related metabolites and pH in the putamen. Left column shows data from contralateral,
right column shows data from the ipsilateral hemisphere. Adjusted means, corrected for partial volume and coil loading (see Materials
and methods section) are given in mmol/l. The bar represents 95% confidence interval according to univariate ANOVA. Asterisk
marks significant difference compared to controls (na) (P50.05).
compensated and latent in this area which is not a primary target
region of pathology in Parkinson’s disease.
The most important function of the mitochondria is to assure
sufficient energy supply of the neuron, particularly by the regeneration of high energy phosphates via oxidative phosphorylation
(Erecinka and Silver, 1989). Therefore, the significant depletion of
high energy metabolites in the putamen (ATP and PCr) and in
the midbrain (ATP) indicates mitochondrial dysfunction in the
mesostriatal dopaminergic neurons in early and advanced
Parkinson’s disease. In the putamen and midbrain, we observed
a characteristic pattern of MRSI changes with decreased high- but
unchanged low-energy metabolites. The significant reduction of
high-energy phosphates argues for an insufficient ATP production
due to impaired oxidative phosphorylation in Parkinson’s disease.
The metabolism of ATP and PCr is tightly coupled via the enzyme
creatine phosphokinase that generates ATP by the transfer of a
phosphate group from PCr to ADP under conditions of increased
energy demand or decreased ATP production through oxidative
phosphorylation. PCr is a high-energy source for rapid retrieval
of ATP and, therefore, a sensitive marker for mitochondrial functioning. The reduced putaminal PCr concentration in patients with
Parkinson’s disease might represent an insufficient compensatory
mechanism to maintain adequate ATP levels and indicate a
restricted capacity of the neuron to cope with further energy
demands.
In contrast to ATP, the low-energy metabolites unphosphorylated creatine, ADP and Pi were unchanged in patients with
Parkinson’s disease compared to controls. This is consistent
with previous findings in patients with Parkinson’s disease and
with progressive supranuclear palsy (Montagna et al., 1993;
Stamelou et al., 2009). However, in some encephalomyopathies
and in chronic hypoperfusion elevated ADP concentrations were
MRSI in Parkinson’s disease for mitochondrial function
Brain 2009: 132; 3285–3297
| 3293
Figure 4 Concentration of energy metabolism related metabolites and pH in the midbrain. Left column shows data from
contralateral, right column shows data from the ipsilateral hemisphere. Adjusted means, corrected for partial volume and coil
loading (see Materials and methods section) are given in mmol/l. The bar represents 95% confidence interval according to
univariate ANOVA. Asterisk marks significant difference compared to controls (na) (P50.05).
found (Eleff et al., 1990; Montagna et al., 1992; Barbiroli et al.,
1993; Lodi et al., 1994; Hattingen et al., 2009). ADP might be a
regulator for temporary oxidative stress situations as it
might appear under chronic hypoperfusion (Petroff et al., 1985)
or relapsing phases of mitochondriopathies rather than for chronic
dysfunction of oxidative phosphorylation. Also, there is some
evidence that the most important factor in determining ATP synthesis is not the level of ADP but the oxygen concentration and
the state of the membrane (Reynafarje and Ferreira, 2008). We
also did not find increased lactate levels or alterations of intracellular pH in most of our patients suggesting a slowly progressive
disease process which is not accompanied by ineffective anaerobic
energy production in the long-term.
Beyond the characterization of a Parkinson’s disease-related pattern of disturbed neuronal energy metabolism, our study design
permitted access to the evolution of mitochondrial dysfunction
during the course of Parkinson’s disease. All significant reductions
were present in both hemispheres, with the exception of highenergy phosphates in the midbrain and did not show differences
between patients with early and advanced Parkinson’s disease.
These findings indicate that even patients with early Parkinson’s
disease (Hoehn and Yahr stage I/II), with clearly lateralized motor
symptoms, exhibit a significant reduction of putamen high-energy
phosphates in the less affected hemisphere with a less pronounced
dopaminergic cell loss. Therefore, we conclude that mitochondrial
dysfunction is a rather early occurring and subsequently persistent
event in the pathophysiology of dopaminergic degeneration in
Parkinson’s disease. However, it has to be emphasized that the
midbrain results have to be interpreted with caution in view of the
limited spatial resolution of 31P MRSI and a considerable amount
of signal spreading between the two sides. These potential partial
volume effects might have obscured the rather mild PCr decrease
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| Brain 2009: 132; 3285–3297
E. Hattingen et al.
Figure 5 Concentration of high-energy phosphates ([ATP]+[PCr]) in the putamen. Left column shows data from contralateral, right
column shows data from the ipsilateral hemisphere. Adjusted means, corrected for partial volume and coil loading (see Materials
and methods section) are given in mmol/l. The bar represents 95% confidence interval according to univariate ANOVA. Asterisk marks
significant difference compared to controls (na) (P50.05).
in the midbrain in contrast to the more prominent and robust ATP
decrease in this region. A PCr decrease may also result in an
decrease of the total creatine, which is in turn measurable with
1
H MRSI. O’Neill et al. (2002) reported a decrease in total creatine
concentration in the midbrain of patients with Parkinson’s disease.
We could only find a significant decrease of total creatine in the
putamen, contralateral to the most affected side, and a trend of
total creatine decrease in the midbrain of patients in the advanced
stage of Parkinson’s disease. Unfortunately, many publications
dealing with 1H MRSI in Parkinson’s disease discussed metabolite
concentration changes as intensity ratios to total creatine (Davie
et al., 1995; Cruz et al., 1997; Federico et al., 1997; Tedeschi
et al., 1997; Choe et al., 1998; Simoes-Ribeiro et al., 1998;
Firbank et al., 2002).
It is worthwhile to note that we also found changes in membrane related metabolites obtained from 31P MRSI, namely a
decreased concentration of membrane lipid precursors (phosphoethanolamine, PCho) and degradation products (glycerophosphocholine, glycero-phosphoethanolamine) in the putamen
of patients with early Parkinson’s disease. This might indicate
reduced membrane turnover rates due to the impaired energy
metabolism.
Our MRSI in vivo findings corroborate the pathogenetic relevance of mitochondrial dysfunction in Parkinson’s disease which
was first supposed by Schapira et al. (1989), who discovered a
mitochondrial complex I deficiency of the respiratory chain in the
substantia nigra post-mortem (Schapira et al., 1989). Complex I
deficiency as a systemic defect due to genetic or environmental
causes is present in nearly 25% of patients with Parkinson’s
disease (Schapira, 2008). This deficiency has been shown to
render neurons more vulnerable to apoptosis and excitotoxicity
contributing to cellular dysfunction and neuronal death in
Parkinson’s disease (Beal, 1998; Green and Kroemer, 2004).
Oxidative damage has been shown to impair proteasomal ubiquitination and degradation of proteins, leading to alpha-synuclein
aggregation in Parkinson’s disease in the form of characteristic
Lewy bodies (Jenner, 2003). The ubiquitin proteosomal system
degrades intracellular proteins by several ATP-dependent enzymes.
Thus, decreased ATP production due to impaired oxidative phosphorylation causes a decreased catalytic function of the ubiquitin
proteosomal system and subsequent accumulation of damaged
proteins (Hoglinger et al., 2003). In turn, alpha-synuclein overexpression is associated with a mitochondrial load of this protein,
lower cytosolic ATP levels and an increased susceptibility to cell
death (Shavali et al., 2008). Mutations in the PARK6 gene locus,
which are associated with familial autosomal recessive parkinsonism in humans, are associated with mitochondrial dysfunction,
dopaminergic cell loss and reduced ATP levels in Drosophila melanogaster (Clark et al., 2006). Taken together, mitochondrial dysfunction seems to be a converging pathway of multifactorial
mechanisms in the neurodegenerative cascade which is linked
with oxidative stress, diminished proteosomal activity, neuroinflammation and excitotoxicity as major determinants of pathogenesis in Parkinson’s disease.
The MRSI data underline the possible usefulness of mitochondria targeted therapies in Parkinson’s disease. Similar to our findings, a recent study revealed decreased high-energy phosphates
and unchanged low-energy metabolites in the basal ganglia of
progressive supranuclear palsy patients, which was less severe
after the oral administration of the antioxidant coenzyme Q10
acting as a cofactor of complex I of the mitochondrial respiratory
chain (Stamelou et al., 2008). Despite controversial debate, treatment with coenzyme Q10 has been shown to slow functional
decline in a previous pilot study on 80 Parkinson’s disease patients
MRSI in Parkinson’s disease for mitochondrial function
Brain 2009: 132; 3285–3297
| 3295
Figure 6 Concentration of membrane metabolism related metabolites in the putamen. Left column shows data from contralateral,
right column shows data from the ipsilateral hemisphere. Adjusted means, corrected for partial volume and coil loading (see Materials
and methods section) are given in millmoles per litre. The bar represents 95% confidence interval according to univariate ANOVA.
na = controls; Cho = choline; PCho = phosphocholine; GPC = glycero-phosphocholine.
(Shults et al., 2002) but did not display a symptomatic effect given
as an adjunct in midstage patients (Storch et al., 2007). Moreover,
it did not meet the pre-specified criteria for futility in another trial
(Investigators, 2007). The combined administration of coenzyme
Q10 and creatine showed additive neuroprotective effects against
dopamine depletion in the striatum and loss of tyrosine hydroxylase neurons in the substantia nigra pars compacta following
chronic subcutaneous administration of 1-methyl-4-phenyl1,2,3,6-tetrahydropyridine in a mouse model of Parkinson’s disease (Yang et al., 2009). Therefore, a large clinical trial on the
potential of coenzyme Q10 as a disease modifying agent in
patients with Parkinson’s disease is currently planned.
In conclusion, combined 1H/31P MR spectroscopy revealed a
significant decrease of high energy phosphates in the mesostriatal
region of patients with Parkinson’s disease in vivo, which was
similarly present in early and advanced stages of the disease.
The data strongly support the hypothesis that mitochondrial dysfunction is involved early in the pathogenesis of Parkinson’s disease and a major constituent of the pathogenetic cascade.
Funding
Bundesministerium für Bildung und Forschung (Brain Imaging
Center Frankfurt); contract number: DLR 01GO0203 and
Deutsche Forschungsgemeinschaft; contract number: ZA 233/1-1.
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