Gray matter volume reduction in the chronic fatigue syndrome
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Bron:  NeuroImage
       Vol. 26, #3, pp. 777-781
Datum: Juli 2005
URL:   http://www.sciencedirect.com/science/journal/10538119
       http://www.elsevier.com/locate/ynimg
      

Floris P. de Lange(a,*, Joke S. Kalkman(b), Gijs Bleijenberg(b), Peter
Hagoort(a), Jos W.M. van der Meer(c) and Ivan Toni(a)
a F.C. Donders Centre for Cognitive Neuroimaging, Radboud University
  Nijmegen, NL-6500 HB Nijmegen, The Netherlands
b Expert Center Chronic Fatigue, University Medical Center, Nijmegen,
The
  Netherlands
c Department of Internal Medicine, University Medical Center, Nijmegen,
  The Netherlands
* Corresponding author. Fax: +31 24 36 10652.
  E-mail address: [log in to unmask] (F.P. de Lange).

Received 28 September 2004; revised 11 January 2005; accepted 18
February 2005 - Available online 7 April 2005

The chronic fatigue syndrome (CFS) is a disabling disorder of unknown
etiology. The symptomatology of CFS (central fatigue, impaired
concentration, attention and memory) suggests that this disorder could be
related to alterations at the level of the central nervous system. In this
study, we have used an automated and unbiased morphometric technique to
test whether CFS patients display structural cerebral abnormalities.

We mapped structural cerebral morphology and volume in two cohorts of
CFS patients (in total 28 patients) and healthy controls (in total 28
controls) from high-resolution structural magnetic resonance images,
using voxel-based morphometry. Additionally, we recorded physical activity
levels to explore the relation between severity of CFS symptoms and
cerebral abnormalities.

We observed significant reductions in global gray matter volume in both
cohorts of CFS patients, as compared to matched control participants.
Moreover, the decline in gray matter volume was linked to the reduction in
physical activity, a core aspect of CFS. These findings suggest that the
central nervous system plays a key role in the pathophysiology of CFS and
point to a new objective and quantitative tool for clinical diagnosis of
this disabling disorder.

Keywords: Chronic fatigue syndrome; Voxel-based morphometry; Magnetic
resonance imaging; Volumetric MRI

Introduction

The chronic fatigue syndrome (CFS) is characterized by a persistent or
relapsing unexplained fatigue, of new or definite onset and lasting for at
least 6 months (Fukuda et al., 1994). CFS is believed to affect roughly
half a million people in the United States, and results in significant
personal and economic morbidity. The etiology of CFS is still largely
unknown, although infectious, immunological, neuroendocrine, sleep, and
psychological mechanisms have been proposed to play a role (Afari and
Buchwald, 2003). Several symptoms associated with CFS suggest a role for
the central nervous system, notably the central fatigue, impairments in
concentration, attention and memory, headache, and unrefreshing sleep.
Accordingly, structural (Buchwald et al., 1992; Cope and David, 1996;
Lange et al., 1999; Natelson et al., 1993; Schwartz et al., 1994a,b) and
functional (de Lange et al., 2004; MacHale et al., 2000; Schmaling et
al., 2003) neuroimaging studies have investigated possible cerebral
correlates of CFS.

Studies of brain morphology in CFS have focused on (subcortical) white
matter abnormalities, which manifest themselves as foci of bright
intensity on T2-weighted MR scans. These studies provide conflicting
evidence for cerebral abnormalities. Whereas some studies reported an
increased number of subcortical white matter abnormalities associated with
CFS (Buchwald et al., 1992; Lange et al., 1999; Natelson et al., 1993;
Schwartz et al., 1994a), other studies observed equal numbers of white
matter abnormalities in healthy volunteers and CFS patients (Cope et al.,
1995; Cope and David, 1996). An important limitation of these
morphological studies lies in the absence of an automated procedure.
Assessment of cerebral atrophy using human observers and rating scales has
a poor reproducibility among raters and low inter-rater reliability [on
average 50%] (Scheltens et al., 1997). Secondly, studies that observed
MRI abnormalities could not link the abnormalities to physical CFS markers
(Cope et al., 1995) which makes the functional significance and clinical
utility of these findings uncertain.

In this study, we aimed to investigate brain morphology in CFS patients by
relying on a fully automated observer-independent procedure, voxel-based
morphometry (VBM) (Ashburner and Friston, 2000). VBM provides an unbiased
and validated (Watkins et al., 2002) technique for measuring cerebral
volume and tissue concentration from high-resolution structural magnetic
resonance images, and it has been used to assess subtle morphological
brain differences in different pathologies (Draganski et al., 2002; May et
al., 1999; Yamasue et al., 2003). Furthermore, we collected data
pertaining to the physical activity level in the CFS patients and a
subgroup of controls using actigraphic assessment. Patients with CFS are
markedly sedentary (van der Werf et al., 2000). Activity levels provide a
quantitative measure of the severity of this aspect of CFS, so by
acquiring information about the physical activity level, we could assess
the relationship between severity of MRI abnormalities and physical
inactivity within the CFS population. Having observed significant
structural abnormalities in a first cohort of CFS patients, we tested the
reliability of the observation by replicating the experiment in a second
independent cohort of equal size.

Methods

Participants

We studied the experimental effect in two separate cohorts of patients and
matched controls. Since CFS predominantly affects women (Afari and
Buchwald, 2003), and given the differences in brain morphology and size
between men and women (Gur et al., 1991), we restricted this study to
female participants. The first cohort consisted of 13 female CFS patients
(CFS: mean age 28.9 years, SD 6.1, range 19-37) and 15 age-, sex-, and
education-matched healthy controls (HC: mean age 25.7 years, SD 6.5, range
19-42). The second cohort consisted of 15 older female CFS patients
(mean age 43.9 years, SD 14.4, range 24-63) and 13 age-, sex-, and
educationmatched healthy controls (mean age 43.4 years, SD 14.1, range
22-68). All participants took part in the study after giving written
informed consent according to institutional guidelines of the local ethics
committee (CMO region Arnhem-Nijmegen, Netherlands) and in accordance
with the Helsinki Declaration of 1975, as revised in 1983. Patients and
controls were assessed by means of detailed history and investigation, and
computer assessment of questionnaires. The physical activity level of 26
of the CFS patients and 14 of the HC was assessed by actometer
measurements during 2 weeks preceding scanning. All patients conformed to
the US Centers for Disease Control and Prevention (CDC) criteria for CFS
(Fukuda et al., 1994). Participants who manifested psychiatric comorbodity
(e.g., depression) were excluded from the study. None of the participants
took any drugs that acted on the central nervous system. We collected
information regarding self-reported disease severity and disease duration
in all patients. Self-reported disease severity was assessed by the
Checklist Individual Strength (CIS). The Checklist Individual Strength
(CIS) is a 20-item questionnaire that measures several aspects of fatigue
(Dittner et al., 2004; Vercoulen et al., 1994). Self-reported disease
duration reflects the number of years the CFS patient felt she had been
affected by complaints of fatigue.

Actigraphic measurements

The actometer (Actilog V3.0) used is a motion-sensing device that can
register and quantify human physical activity (Vercoulen et al., 1997).
The actometer is small and light and has to be worn at the ankle. The
small size makes it suitable for long-term continuous registrations. The
actometer has a piezoelectric sensor that is sensitive in three
directions. Accelerations of the sensor larger than a predefined threshold
are considered as activity and are stored in an internal memory. Each
second, the counter of the actometer is read and reset by the
microcontroller. The integration counter is set at 5 min providing every 5
min an activity score that is stored in the internal memory of the
actometer. At the end of the registration period, data are fed into an
external computer. Participants wore the actometer day and night during
at least a 14-day period. In order to retain 12 complete registration
days, the first and last registration days were omitted for the analyses.
A general physical activity score reflected the average physical activity
level over the total 12-day time period and was expressed in the average
number of accelerations per 5-min period.

Imaging protocol

High-resolution anatomical images (voxel size=1 mm3) of the whole brain
were acquired on a 1.5-T Siemens Sonata whole-body scanner (Erlangen,
Germany) using a magnetization prepared rapid acquisition gradient echo
sequence. Images were analyzed using VBM (Ashburner and Friston, 2000), a
fully automated technique for computational analysis of differences in
global and local gray and/or white matter volume. This method involved the
following steps: (1) spatial normalization of all images to a standardized
anatomical space by removing differences in overall size, position, and
global shape; (2) extraction of gray and white matter from the normalized
images; (3) correction for volume changes induced by normalization; and
(4) analysis of differences in global and local gray and white matter
volume across the whole brain. We applied an optimized method of VBM
(Ashburner and Friston, 2000; Good et al., 2001) using the SPM2 package
(http://www.fil.ion.ucl.ac.uk/spm) and special-purpose scripting tools
(http://dbm.neuro.uni-jena.de/vbm.html). The spatial normalization to the
standard anatomical space was performed in a two-stage process. In the
first step, we registered each image to the International Consortium for
Brain Mapping template (Montreal Neurological Institute, Montreal,
Canada), which approximates Talairach and Tournoux space (Talairach and
Tournoux, 1988). We applied a 12-parameter affine transformation to
correct for image size and position. Regional volumes were preserved while
corrections for global differences in whole brain volume were made. The
normalized images of all participants were averaged and smoothed with a
Gaussian kernel of 8 mm full-width at half-maximum (FWHM) and then used as
a new template with reduced scanner- and population-specific biases. In
the second normalization step, we locally deformed each image of the whole
group to the new template using a nonlinear spatial transformation. This
accounts for the remaining shape differences between the images and the
template and improves the overlap of corresponding anatomical structures.
Finally, using a modified mixture model cluster analysis, normalized
images were corrected for nonuniformities in signal intensity and
partitioned into gray and white matter, cerebrospinal fluid, and
background. To remove unconnected non-brain voxels (e.g., rims between
brain surface and meninges), we applied a series of morphologicalerosions
and dilations to the segmented images (Good et al., 2001). To correct for
possible volume changes as a result of the nonlinear spatial
normalization, all images were modulated by multiplying voxel values in
the segmented images by the Jacobian determinants derived from the spatial
normalization step (Good et al., 2001). The resulting modulated images
were smoothed with a Gaussian kernel of 12 mm FWHM. Global volume was
calculated from these modulated images. Head size was estimated by means
of a semiautomated procedure. First, the original MR scans of each
participant were aligned to a common stereotactic space defined by the
plane passing through the anterior and posterior commissures (Talairach
and Tournoux, 1988). Second, we manually defined the transverse and
sagittal diameters of the skull along this plane. Head size was calculated
as the product of these two diameters. Self-reported disease severity was
taken from the US Centers for Disease Control and Prevention questionnaire.

Statistical analysis

Global differences in gray and white matter between groups were assessed
with an analysis of covariance (ANCOVA) that considered age as a
confounding covariate. Regional (i.e., voxelby- voxel) differences in gray
matter between groups were assessed with t tests using the general linear
model, considering age and total gray matter volume as confounding
covariates, and correcting the results for search volume by using
family-wise error correction. Head size differences were assessed with an
analysis of variance (ANOVA). The correlation between daily physical
activity and gray matter volume was assessed by means of Pearson's
correlation-coefficients.

Results

Fig. 1 shows two examples of high-resolution anatomical images, and the
resulting gray matter (GM) and white matter (WM) maps derived from the
automated segmentation procedure as described in the Methods section.

Both cohorts of CFS patients showed significant reductions in gray matter
volume (GM) compared to HC [cohort I: F(1,25)=6.2; P=0.019; cohort
II: F(1,25)=8.0; P=0.009]. When the two cohorts are put together, the
GM reduction remains highly significant [F(1,53)=14.5; P<0.001] and
amounts to a reduction in GM of approximately 8% [95% Confidence
Interval: 5-11%] (Fig. 2A). In terms of age-related changes in GM, both CFS
patients and HC show a similar decline in GM as a function of age [
F(1,53)=19.5; P<0.001] (Fig. 2B). This decline amounts to a reduction
of approximately 2.2 ml/year, a decline that is in line with previous
reports on age-related GM loss (Good et al., 2001). Across the wide age
range of our sample (19-66 years), there was age interactions [F(1,52)=
1.01; P=0.32], i.e., the GM reduction observed in the CFS groups was
not due to a faster age-related decline.

We did not detect regionally specific difference in GM (over and above
global GM differences, with a threshold of P<0.05 corrected for search
volume). A further exploratory analysis of statistical trends (P<0.2
corrected for search volume) failed to reveal local foci of reduced GM.
Taken together, these findings suggest that the observed GM reduction in
the CFS patient groups is a global rather than a local phenomenon,
although further studies with larger statistical power might be required
to detect subtle focal structural alterations. White matter volume was not
significantly different between groups [F(1,53)=2.58; P=0.114], even
when taking both cohorts together, indicating that the difference between
groups is specific to GM. Overall head size was not significantly
different between HC and CFS patients [F(1,53)=2.57; P=0.115],
indicating that the differences between groups measured are not a
by-product of differences in head size.

Within the CFS population, there was a positive correlation between daily
physical activity level and GM (Fig. 3; r=0.39, P=0.026 one-tailed).
Conversely, there was no significant correlation between physical activity
level and GM in the control group (Fig. 3; r=0.10, P=0.37 one-tailed).
There was no significant correlation between age and physical activity in
the CFS group (r=0.11, P=0.30 one-tailed), which excludes that the
positive correlation between GM and physical activity in CFS patients is a
by-product of age-related effects. There were no significant correlations
between GM and self-reported CFS duration (r=0.02, P=0.46 one-tailed)
or CFS severity as measured by the Checklist Individual Strength
(r=0.20, P=0.16 one-tailed).

Discussion

By using an automated morphometric technique, we were able to assess
group-related differences across the whole brain in an observer-independent
manner. Two independent cohorts of CFS patients showed a marked decline
in gray matter volume (GM), compared to matched healthy controls. Moreover,
although GM was not related to self-reported disease duration or severity,
there was a relation between the (objectively measured) level of
physical activity and the GM reduction.

The results obtained with this approach corroborate and complement
previous studies that observed cerebral abnormalities associated with CFS
(Buchwald et al., 1992; Lange et al., 1999; Natelson et al., 1993;
Schwartz et al., 1994a). Our findings appear to provide a reliable somatic
marker of CFS, and suggest that the key to this disease might lay in the
central nervous system. However, given the multidimensional nature of CFS
(Afari and Buchwald, 2003), the relationship between the structural brain
abnormalities in CFS and the etiology of this disorder may not be
straightforward. It is conceivable that the reduced gray matter volume is
a cause of chronic fatigue and the ensuing physical inactivity.
Alternatively, it is also possible that the gray matter reduction is a
consequence of the reduced physical activity inherent in CFS. In this
perspective, recent reports have suggested direct links between physical
exercise and neurogenesis (Pham et al., 2003; van Praag et al., 1999).
However, the latter scenario is not immediately compatible with the fact
that the GM decrease is not correlated with CFS duration. Future research
is clearly warranted to assess whether the present results can be
validated in bigger CFS populations and whether the changes we observe
can be influenced by therapeutic intervention.

In conclusion, we found substantial and consistent reductions in
GM volume in two independent cohorts of CFS patients. This GM
reduction was associated to the decline in physical activity in the
CFS patients. These findings suggest that the central nervous
system plays a crucial role in the etiology of CFS. Furthermore,
they provide a new objective and quantitative diagnostic marker of
this disabling disorder.

Acknowledgments

This study was supported by the Netherlands ME foundation (ME Fonds, grant
number W1101/16E) and by NWO (VIDI grant no. 452-03-339). The authors
thank J. Ashburner for his support with methodological issues, R.C.G.
Helmich, Karl Magnus Petersson, and S. van der Werf for helpful
comments.

Figure Captions

Fig. 1. Voxel-based morphometric analysis. Data are shown for one
participant of the healthy control group (HC, upper row) and the patient
group (CFS, lower row). We segmented high-resolution anatomical images
(left column) into gray matter (GM, middle column), white matter (WM,
right column), cerebrospinal fluid, and non-brain tissue (not shown).

Fig. 2. Gray matter volume. (A) Gray matter volume (in liters; mean F
SE) of two cohorts of patients suffering from the chronic fatigue syndrome
(CFS, in red) and healthy control participants (HC, in green). In both
cohorts, CFS patients have markedly reduced gray matter volumes (GM)
than their healthy counterparts. The second cohort of CFS and HC
participants is older than the first, giving rise to overall lower GM.
(B) Scatterplot of gray matter volume as a function of age in the two CFS
and HC cohorts. Both CFS patients and HC show a similar decline in GM as a
function of age.

Fig. 3. Relation between physical activity and gray matter volume. There
is a positive relationship between the amount of general physical
activity and the gray matter volume within the CFS population (in red), but not
in the healthy control group (in green). (*) General physical activity
measured over a 2-week period with a movement-sensing device, expressed
in number of accelerations per 5-min period.

References

Afari, N., Buchwald, D., 2003. Chronic fatigue syndrome: a review. Am.
J.
  Psychiatry 160, 221-236.
Ashburner, J., Friston, K.J., 2000. Voxel-based morphometry—the
methods.
  NeuroImage 11, 805-821.
Buchwald, D., Cheney, P.R., Peterson, D.L., Henry, B., Wormsley, S.B.,
  Geiger, A., Ablashi, D.V., Salahuddin, S.Z., Saxinger, C., Biddle, R.,
  1992. A chronic illness characterized by fatigue, neurologic and
  immunologic disorders, and active human herpesvirus type 6 infection.
  Ann. Intern. Med. 116, 103-113.
Cope, H., David, A.S., 1996. Neuroimaging in chronic fatigue syndrome.
  J. Neurol., Neurosurg. Psychiatry 60, 471-473.
Cope, H., Pernet, A., Kendall, B., David, A., 1995. Cognitive
functioning
  and magnetic resonance imaging in chronic fatigue. Br. J. Psychiatry
  167, 86-94.
De Lange, F.P., Kalkman, J.S., Bleijenberg, G., Hagoort, P., van der
Werf,
  S.P., van der Meer, J.W., Toni, I., 2004. Neural correlates of the
chronic
  fatigue syndrome - an fMRI study. Brain 127, 1948-1957.
Dittner, A.J., Wessely, S.C., Brown, R.G., 2004. The assessment of
fatigue:
  a practical guide for clinicians and researchers. J. Psychosom. Res.
56,
  157-170.
Draganski, B., Geisler, P., Hajak, G., Schuierer, G., Bogdahn, U.,
Winkler,
  J., May, A., 2002. Hypothalamic gray matter changes in narcoleptic
  patients. Nat. Med. 8, 1186-1188.
Fukuda, K., Straus, S.E., Hickie, I., Sharpe, M.C., Dobbins, J.G.,
Komaroff,
  A., 1994. The chronic fatigue syndrome: a comprehensive approach to
  its definition and study. International Chronic Fatigue Syndrome Study
  Group. Ann. Intern. Med. 121, 953-959.
Good, C.D., Johnsrude, I.S., Ashburner, J., Henson, R.N.A., Friston,
K.J.,
  Frackowiak, R.S.J., 2001. A voxel-based morphometric study of ageing
  in 465 normal adult human brains. NeuroImage 14, 21-36.
Gur, R.C., Mozley, P.D., Resnick, S.M., Gottlieb, G.L., Kohn, M.,
Zimmerman,
  R., Herman, G., Atlas, S., Grossman, R., Berretta, D., 1991. Gender
  differences in age effect on brain atrophy measured by magnetic
  resonance imaging. Proc. Natl. Acad. Sci. U. S. A. 88, 2845-2849.
Lange, G., DeLuca, J., Maldjian, J.A., Lee, H., Tiersky, L.A., Natelson,
  B.H., 1999. Brain MRI abnormalities exist in a subset of patients with
  chronic fatigue syndrome. J. Neurol. Sci. 171, 3-7.
MacHale, S.M., Lawrie, S.M., Cavanagh, J.T., Glabus, M.F., Murray, C.L.,
  Goodwin, G.M., Ebmeier, K.P., 2000. Cerebral perfusion in chronic
  fatigue syndrome and depression. Br. J. Psychiatry 176, 550-556.
May, A., Ashburner, J., Buchel, C., McGonigle, D.J., Friston, K.J.,
  Frackowiak, R.S., Goadsby, P.J., 1999. Correlation between structural
  and functional changes in brain in an idiopathic headache syndrome.
  Nat. Med. 5, 836-838.
Natelson, B.H., Cohen, J.M., Brassloff, I., Lee, H.J., 1993. A
controlled
  study of brain magnetic resonance imaging in patients with the chronic
  fatigue syndrome. J. Neurol. Sci. 120, 213-217.
Pham, K., Nacher, J., Hof, P.R., McEwen, B.S., 2003. Repeated restraint
  stress suppresses neurogenesis and induces biphasic PSA-NCAM
  expression in the adult rat dentate gyrus. Eur. J. Neurosci. 17,
879-886.
Scheltens, P., Pasquier, F., Weerts, J.G., Barkhof, F., Leys, D., 1997.
  Qualitative assessment of cerebral atrophy on MRI: inter- and
intraobserver
  reproducibility in dementia and normal aging. Eur. Neurol. 37, 95-99.
Schmaling, K.B., Lewis, D.H., Fiedelak, J.I., Mahurin, R., Buchwald,
D.S.,
  2003. Single-photon emission computerized tomography and
neurocognitive
  function in patients with chronic fatigue syndrome. Psychosom. Med.
65,
  129-136.
Schwartz, R.B., Garada, B.M., Komaroff, A.L., Tice, H.M., Gleit, M.,
  Jolesz, F.A., Holman, B.L., 1994a. Detection of intracranial
abnormalities
  in patients with chronic fatigue syndrome: comparison of MR imaging
and
  SPECT. AJR Am. J. Roentgenol. 162, 935-941.
Schwartz, R.B., Komaroff, A.L., Garada, B.M., Gleit, M., Doolittle,
T.H.,
  Bates, D.W., Vasile, R.G., Holman, B.L., 1994b. SPECT imaging of the
  brain: comparison of findings in patients with chronic fatigue
syndrome,
  AIDS dementia complex, and major unipolar depression. AJR Am. J.
  Roentgenol. 162, 943-951.
Talairach, J., Tournoux, P., 1988. Co-Planar Stereotaxic Atlas of the
Human
  Brain: 3-Dimensional Proportional System: An Approach to Medical
Cerebral
  Imaging. Thieme, Stuttgart.
Van der Werf, S.P., Prins, J.B., Vercoulen, J.H., van der Meer, J.W.,
  Bleijenberg, G., 2000. Identifying physical activity patterns in
chronic
  fatigue syndrome using actigraphic assessment. J. Psychosom. Res. 49,
  373-379.
Van Praag, H., Kempermann, G., Gage, F.H., 1999. Running increases cell
  proliferation and neurogenesis in the adult mouse dentate gyrus. Nat.
  Neurosci. 2, 266-270.
Vercoulen, J.H., Swanink, C.M., Fennis, J.F., Galama, J.M., van der
Meer,
  J.W., Bleijenberg, G., 1994. Dimensional assessment of chronic fatigue
  syndrome. J. Psychosom. Res. 38, 383-392.
Vercoulen, J.H., Bazelmans, E., Swanink, C.M., Fennis, J.F., Galama,
J.M.,
  Jongen, P.J., Hommes, O., van der Meer, J.W., Bleijenberg, G., 1997.
  Physical activity in chronic fatigue syndrome: assessment and its role
in
  fatigue. J. Psychiatr. Res. 31, 661-673.
Watkins, K.E., Vargha-Khadem, F., Ashburner, J., Passingham, R.E.,
  Connelly, A., Friston, K.J., Frackowiak, R.S., Mishkin, M., Gadian,
  D.G., 2002. MRI analysis of an inherited speech and language disorder:
  structural brain abnormalities. Brain 125, 465-478.
Yamasue, H., Kasai, K., Iwanami, A., Ohtani, T., Yamada, H., Abe, O.,
  Kuroki, N., Fukuda, R., Tochigi, M., Furukawa, S., Sadamatsu, M.,
  Sasaki, T., Aoki, S., Ohtomo, K., Asukai, N., Kato, N., 2003.
Voxelbased
  analysis of MRI reveals anterior cingulate gray-matter volume
  reduction in posttraumatic stress disorder due to terrorism. Proc.
Natl.
  Acad. Sci. U. S. A. 100, 9039-904

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