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Clinical and Diagnostic Laboratory Immunology, January 1999, p. 6-13, Vol. 6, No. 1
1071-412X/99/$00.00+0
Changes in Immune Parameters Seen in Gulf War
Veterans but Not in Civilians with Chronic Fatigue Syndrome
Quanwu
Zhang,1,2
Xia-Di
Zhou,3
Thomas
Denny,1,4
John E.
Ottenweller,1,2
Gudrun
Lange,1,5
John J.
LaManca,1,2
Marc H.
Lavietes,6
Claudia
Pollet,1,6
William C.
Gause,1,3 and
Benjamin H.
Natelson1,2,*
Center for Environmental Hazards Research,
DVA Medical Center, E. Orange,1 and
Departments of Neurosciences,2
Pediatrics,4
Psychiatry,5 and
Medicine,6 University of Medicine and
Dentistry
New Jersey Medical School, Newark, New Jersey, and
Department of Microbiology, Uniformed Services University of
the Health Sciences, Bethesda, Maryland3
Received 28 May 1998/Returned for modification 14 August
1998/Accepted 2 October 1998
 |
ABSTRACT |
The purpose of this study was to evaluate immune function through
the assessment of lymphocyte subpopulations (total T cells, major
histocompatibility complex [MHC] I- and II-restricted T cells, B
cells, NK cells, MHC II-restricted T-cell-derived naive and memory
cells, and several MHC I-restricted T-cell activation markers) and the
measurement of cytokine gene expression (interleukin 2 [IL-2], IL-4,
IL-6, IL-10, IL-12, gamma interferon [IFN-
], and tumor necrosis
factor alpha [TNF-
]) from peripheral blood lymphocytes. Subjects
included two groups of patients meeting published case definitions for
chronic fatigue syndrome (CFS)
a group of veterans who developed their
illness following their return home from participating in the Gulf War
and a group of nonveterans who developed the illness sporadically. Case
control comparison groups were comprised of healthy Gulf War veterans and nonveterans, respectively. We found no significant difference for
any of the immune variables in the nonveteran population. In contrast,
veterans with CFS had significantly more total T cells and MHC
II+ T cells and a significantly higher percentage of these
lymphocyte subpopulations, as well as a significantly lower percentage
of NK cells, than the respective controls. In addition, veterans with
CFS had significantly higher levels of IL-2, IL-10, IFN-
, and
TNF-
than the controls. These data do not support the hypothesis of
immune dysfunction in the genesis of CFS for sporadic cases of CFS but
do suggest that service in the Persian Gulf is associated with an
altered immune status in veterans who returned with severe fatiguing illness.
 |
INTRODUCTION |
One explanation for the lassitude,
malaise, and flu-like symptoms seen in chronic fatigue syndrome (CFS)
is the existence of immune dysregulation with increased levels of
cytokines. Supporting this hypothesis are a number of reports of
reduced NK cell activity (2, 13), upregulation of immune
activation markers (19, 36), and increases in levels of
cytokines in serum (4, 21, 28). However, these results are
far from uniform. In contrast, some researchers have found no evidence
of immune dysfunction (29), while others have found support
for the immune dysfunction hypothesis only in a subset of CFS patients
(25) or only when functional tests are performed
(40).
We have had the unique opportunity to evaluate further the immune
dysfunction hypothesis in two groups of patients with CFS
a group of
civilians who developed the illness sporadically and a group of
veterans who developed the illness following their service in the Gulf
War. We have assessed three hypotheses in exploring the immunological
data obtained: first, that CFS patients would have evidence of immune
dysregulation compared to controls and that this would be more marked
in the civilians because of the increased frequency of sudden onset in
this group (32); second, that more severely ill patients,
those with a sudden onset of their illness, and/or those free of
concurrent psychiatric illness would exhibit the most marked immune
dysregulation; and third, that CFS patients in general and Gulf War
veterans in particular would show a type 2 cytokine profile according
to the hypothesis of Rook and Zumla (33).
 |
MATERIALS AND METHODS |
Sample and data.
The patients were 43 Gulf War veterans on
the Department of Veterans Affairs' (DVA) Gulf War Registry and 68 nonveterans
all of whom initially completed health questionnaires
indicating the symptom profile of CFS. These patients came to East
Orange or Newark, N.J., respectively, where they provided a 3-h history and received a physical examination, a blood test, and a diagnostic psychiatric interview (24) by medical and psychological
personnel to rule out medical and psychiatric (10) causes of
chronic fatigue. Every CFS patient studied here was found to meet the
1994 case definition (10) of CFS (for details of the intake
protocol, see reference 32). Based on the
self-reported percentage of decrease in activity and the number and
severity of their CFS minor symptoms, they were rated on a six-category
CFS severity scale. The most severely affected patients, those with
severe CFS, met the 1988 case definition (14) with the
following modifications: seven symptoms were required to fulfill
criteria, but symptoms were counted only if their severity was rated as
3 or higher on symptom intensity scales from 0 to 5 in the month prior
to intake. In addition, patients were classified according to mode of
illness onset, with "sudden" being defined as the development of
the illness in 1 to 2 days and "gradual" being defined as a more
delayed onset.
The healthy unmedicated controls were 34 Gulf War veterans on the Gulf
War Registry and 53 civilians. We used a health survey to identify
healthy Gulf War veterans and then recruited them for our studies.
Healthy nonveterans were self-selected based on their response to
newspaper advertisements and flyers placed throughout neighboring
communities. Healthy nonveterans who exercised more than once a week or
who had an Axis I psychiatric disorder were excluded. These criteria
were not applied to healthy Gulf War veterans.
Veteran recruitment was limited to patients in the computer database of
the DVA New Jersey Health Care System and individuals with major
complaints of fatigue who were in the Gulf War Registry and resided in
10 states east of the Mississippi River. Civilian recruitment was of
people residing within a 100-mile radius of our center. Because of
their distance from our center, veterans were admitted to the VA
Medical Center for their studies; nonveterans came to the center for
limited times only.
After written informed consent was obtained, subjects underwent
venipuncture, and blood was collected in EDTA anticoagulated tubes that
were coded to disguise the identity of the subject group. Peripheral
blood lymphocytes (PBLs) were labeled within 6 h of collection
with commercially available combinations of monoclonal antibody to the
following cell surface markers: CD45-CD14, CD3-CD8, CD3-CD4, CD3-CD19,
CD3-CD(16+56) (Simulset Reagents, Becton Dickinson [BDIS], San Jose,
Calif.), CD8-CD38, CD8-HLA-DR, CD8-CD11b, CD8-CD28, CD4-CD45RO, and
CD4-CD45RA (antibodies to CD11b from DAKO, Carpinteria, Calif.; all
other antibodies from BDIS). After the samples had been fixed in 0.5 ml
of 1% formalin (methanol free) and refrigerated overnight, all flow
cytometric analyses were performed in the same laboratory with a
FACscan cytometer (BDIS) equipped with a 15-mW air-cooled 488-nm argon ion laser and with standard techniques (9). Thus, the
following cell populations were quantified for each group of subjects:
total leukocyte (WBC) count; number (and percentage of total WBC) of lymphocytes; number (and percentage of total lymphocyte count) of
CD3+ (total T cells), CD3+ CD4+
(major histocompatibility complex [MHC] II-restricted T cells), CD3+ CD8+ (MHC I-restricted T cells),
CD3
CD19+ (B cells), and CD3
CD(16+56)+ (NK cells); percentage of class II-restricted T
cells that were CD45RO+ and CD45RA+; and
percentage of class I-restricted T cells that were CD28+,
HLA-DR+, CD38+, and CD11b
.
PBLs, harvested from additional aliquots of blood, were homogenized in
RNA-zol (Cine/Biotech, Friendswood, Tex.) at 50 mg per 0.2 ml/106 cells. The quantitative reverse transcriptase PCR
(RT-PCR) cytokine assay was used as previously described (11, 38,
39). RNA samples were reverse transcribed with Superscript RT
(Bethesda Research Labs, Rockville, Md.), and cytokine-specific primers were used to amplify the following cytokines (38): gamma
interferon (IFN-
), tumor necrosis factor alpha (TNF-
),
interleukin 2 (IL-2), IL-4, IL-6, IL-10, and IL-12. Amplified PCR
product was detected by Southern blot analysis (38, 39), and
the resultant signal was quantified as the relative differences between
samples with a PhosphorImager (Molecular Dynamics, Sunnyvale, Calif.)
(38, 39). Subjects had no missing data for any of the cell
surface markers or cytokines in the final analysis.
Analysis.
Our goal was to determine if immune alteration or
dysregulation existed in CFS patients, relative to the healthy controls (comprised of both Gulf War veterans and civilians) and to compare veteran and civilian data when possible. A problem in prior reports of
immunological abnormalities in CFS lies in their use of multiple, separate, univariate inferential tests, even in the cases in which multivariate analysis of variance (MANOVA) techniques are used. An
additional problem lies in the relative inability of classical statistical methods to capture theoretical integrated immunological patterns thought to exist, such as type 1 versus type 2 cytokine profiles. These methods do not allow the simultaneous assessment of
such patterns when one increases and the other decreases at the same
time. Further, MANOVA or multivariate regression guards only against a
type I error of overall group differences for all the immune
indicators. However, no standard statistical method exists in these
classical tests to determine appropriate procedures of protecting
against type 1 errors when multiple contrasts are made (5).
Traditional repeated-measures analysis is not appropriate for
hypothesis testing in this report, because the data showed marked heterogeneity of both variances and covariances (7, 22). To
overcome these problems, we used mixed-effects, repeated-measures models which allowed the simultaneous assessment of group differences in the level of activation and differentiation markers and in the level
of cytokines (6, 18, 42). This approach allowed us not only
to explicitly estimate the extent of heterogeneity of variances and
covariances of the multiple immunological measures in each model but
also to test group differences in the multiple immunological measures
as interaction terms (5, 41). With this format of analysis,
we increased the efficiency and precision of our statistical
comparisons and controlled for the risk of inflating the frequency of
type I errors.
Differences in the percentages and actual numbers of cell surface
markers were tested in CFS patients and the respective controls for
Gulf War veterans and civilians and between these two samples simultaneously. Comparisons based on cytokines were performed only
within the veteran and civilian sample groups because the assays were
run separately for the veterans and civilians. We systematically
controlled for potential confounding by the subject's demographic
characteristics, including age, race, sex, and Axis I diagnostic status
in every model. Subsequently, we also evaluated CFS groups based on
illness severity and mode of illness onset (i.e., sudden versus
gradual); since these analyses were independent of the major
statistical model described above, individual comparisons did not
correct for the possibility of the inflated frequency of type 1 errors.
Several steps were taken to test our hypotheses about group differences
in the immune status indicators. First, a general model was constructed
to test a three-way interaction between CFS status (Yes = 1 and
No = 0), veteran membership (Yes = 1 and No = 0), and
the percentages of cell surface markers, while incorporating the main
effects and interaction effects between those covariates and the
percentages of cell surface markers. Special attention was paid to the
testing of interaction effects because of the possibility that some
immune variables in the patient groups would show increases while
others showed decreases relative to controls or that differences from
controls might occur preponderantly in only one of the CFS groups.
Likewise, the effects of the covariates may have differed for the
various immunological measures. For example, men may have lower levels
than women of one cell surface marker but have higher levels than women
of another. These specific differences must be accounted for in order
to determine if a true difference exists between CFS patients and the
controls. The model testing group differences in the percentages of
cell surface markers was specified as follows:
percentij = b0 + b1(sex)i + b2(race)i + b3(age)i + b4
(Axis I)i + b5
(CFS)i + b6(veteran)i + b7(cell surface marker)ij + b8(CFS × veteran)i + b9(sex × cell surface marker)ij + b10(race × cell surface
marker)ij + b11(age × cell surface marker)ij + b12(CFS × cell surface marker)ij + b13(veteran × cell surface
marker)ij + b14(CFS × veteran × cell surface marker)ij + rij (i = 1,2, ... , n, number of subjects;
j = 1, 2, ... , k, number of cell surface markers)
The same specifications were used for the model testing group
differences in the numbers of cell surface markers, except that the
response function was log transformed. The model testing group differences in cytokine levels was specified as follows:
log(cytokine)ij = b0 + b1(assay)i + b2(sex)i + b3(race)i + b4(age)i + b5(Axis I)i + b6(CFS)i + b7(cytokine)ij + b8(sex × cytokine)ij + b9(race × cytokine)ij + b10(age × cytokine)ij + b11(CFS × cytokine)ij + rij (i = 1,2, ... , n, number of subjects;
j = 1, 2, ... , k, number of cytokines)
This approach differed from a traditional repeated-measures
analysis in that the residual terms rij in the
equations were not assumed to be homogeneous within subject
i. Instead, error variances and covariances among subjects
were fully estimated in every model by using the SAS mixed procedure
(22) with an unconstrained error structure to reflect the
interrelations among cell surface markers and among cytokines.
Next, we did a stepwise elimination of nonsignificant interaction terms
between the covariates and the immune status indicators from the models
specified above. A nonsignificant interaction term indicates that the
group differences of interest were not explained by a given covariate.
Thus, for example, the interaction terms of Axis I versus surface
markers and cytokines did not show statistical significance, and so
they were not included in the specified models to be evaluated.
Finally, we systematically evaluated higher-order interactions testing
group differences of interest. A higher-order interaction was
eliminated from a model if it failed to reach statistical significance
(P < 0.05), and then the model with only lower-order terms was evaluated. The final models retained are reported in the next
section. The numbers of cell surface markers and cytokine measurements
were log transformed before analyses to achieve normality and reduce
undue influences from outlying measurements.
 |
RESULTS |
Table 1 gives descriptive statistics
about the sample. The veteran sample consists of predominantly white
men, below age 50, with a high school or college education, while the
civilian sample is predominantly white women of whom a higher
percentage received postgraduate education than the veterans. For the
healthy veterans, the chance of having an education higher than high
school was three times that for the CFS veterans. The chance of having an Axis I diagnosis among the CFS veterans was over 2.5 times that
among civilian CFS patients (odds ratio = 2.78, P < 0.05) and 12 times that of the healthy veterans (odds ratio = 12, P < 0.05). Sixteen percent of veteran patients
were diagnosed in the most severe CFS category, while 87% of civilian
patients were in that category (odds ratio = 0.11, P < 0.05). Sixteen percent of veteran patients reported a sudden onset
of symptoms in comparison to 63% of civilians with CFS (odds
ratio = 0.03, P < 0.05).
Eleven cell surface markers, the percentage and number of lymphocytes,
WBC counts, and levels of seven cytokines were examined in the present
study. We found no systematic group differences between patient groups
and the respective controls for any of the following markers
phenotypes: CD4+ CD45RO+, CD4+
CD45RA+, CD8+ CD28+,
CD8+ HLA-DR+, CD8+
CD38+, or CD8+ CD11b
. Therefore,
our report focuses on the group differences in the five parent cell
surface markers and the seven cytokines.
Table 2 shows the means and standard
errors of cell surface markers in percentages and numbers and of
cytokine levels for the four comparison groups. No significant
differences were found with mixed-effects models for any of these
variables between the civilian CFS group and the controls. Subsequent
analysis did not reveal an effect based on CFS illness severity, but
differences from controls for several cell markers were seen following
the stratification by mode of illness onset. Patients with a gradual onset (n = 25) showed a decrease in the percent total
lymphocytes (mean = 26.6, standard error [SE] = 1.8, P = 0.022) and an increase in the numbers of total WBC
(mean = 7,200, SE = 472.7, P = 0.026). However, these differences were not mutually independent, in that the
decrease in the percent lymphocytes was a result of an increased number
of WBC. Indeed, we found very similar numbers of lymphocytes in the
gradual-onset group (mean = 1,846) and the control group (mean = 1,874). An increase in the percent activated T suppressor cells (CD8+ CD38+) (mean = 58.9, SE = 2.3, P = 0.023), compared to the control (mean = 51.1 and SE = 1.8 [Table 2]), was also found in the gradual onset group. Patients with a sudden onset of CFS (n = 18) showed a decreased percentage of CD8+
CD11b
cells (P = 0.056). No differences
were found for cytokines after these stratifications. There were not
enough veterans with a sudden onset of CFS (n = 7) to
allow a similar stratified test.
Turning to the Gulf War veterans, we systematically tested the three
hypotheses stated in the introduction by utilizing mixed-effects models. The veterans with CFS were found to have a significantly lower
percentage of NK cells (P = 0.011) and a significantly
higher percentage of CD3+ cells (P = 0.007)
and CD3+ CD4+ cells (P < 0.0003) than the healthy veteran controls (Table
3). These differences were tested
simultaneously and confirmed by a significant three-way interaction
(P = 0.0019) between CFS status, veteran status, and
the five cell surface marker phenotypes (CD3
CD(16+56)+, CD3
CD19+,
CD3+, CD3+ CD4+, and
CD3+ CD8+) while controlling for sex, race,
age, and Axis I diagnosis. When the results were averaged across
veterans and civilians, subjects who were age 40 or older had
significantly more CD3+ CD4+ cells
(P = 0.006) and significantly fewer CD3+
CD8+ cells (P = 0.0006) than younger
subjects. These significant age differences could have confounded our
results had we not controlled for this variable in our analysis.
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TABLE 3.
Linear contrasts of CD cell surface markers between Gulf
War veteran and civilian groups from a mixed-effects model with
three-way interaction between factors of veteran status (yes or
no), CFS status (yes or no), and cell
surface markersa
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Veterans with CFS had significantly more CD3+ cells
(P = 0.021) and CD3+ CD4+ cells
(P = 0.002) than veteran controls, but no significant
difference in the number of NK cells was found between the groups
(Table 4). The veterans with CFS had
significantly more NK cells, total T cells, CD3+
CD4+, and CD3+ CD8+ cells, but not
more B cells, than both civilian groups. This general elevation in the
numbers of cell surface markers in veteran patients was tested again
and confirmed by a significant three-way interaction (P = 0.048) between CFS status, veteran status, and the five cell
surface markers.
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TABLE 4.
Linear contrasts of CD cell surface markers between Gulf
War veteran groups and civilian groups from a mixed-effects model with
three-way interaction between factors of veteran status (yes or no),
CFS status (yes or no), and cell
surfacer markersa
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|
Figures 1 and
2 show the observed and predicted numbers
of cell surface markers, confidence intervals for the predicted cell numbers, and the normative ranges of the five cell surface markers in
the general population for the samples of veterans with CFS and of
healthy civilians. Both the healthy civilian group and the CFS veteran
group had cell number values in the normative range; the confidence
intervals of all four subject groups studied here (only two are
depicted in the figures) were within the boundaries of normative
ranges. However, Fig. 1 and 2 show that the confidence intervals were
broader in the healthy civilian group than those in the CFS veteran
group, suggesting greater heterogeneity in the former. Not depicted are
the broad confidence intervals for CFS civilians and the narrow
confidence intervals for the veteran controls
suggesting that all
civilians are more heterogeneous than Gulf War veterans in this regard.

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FIG. 1.
Estimated and observed mean numbers of five cell surface
markers in Gulf War veterans with CFS. Lines are drawn to connect the
measurement points simply to help the reader see the pattern of the
immunological variables. The predicted mean numbers of cell surface
markers were derived from a three-way interaction model between CFS
status (yes or no), veteran status (yes or no), and cell surface
markers. The model was analyzed by a univariate, mixed-effects
repeated-measures analysis that allowed more efficient, simultaneous,
cross-group comparisons between sick and healthy veterans and sick and
healthy civilians than regular multivariate analysis. All predicted
values fell within the laboratory's normative range. Note that the
95% confidence interval is narrower for all five markers relative to
that of civilian controls.
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|
The levels of seven cytokines were examined in the veteran sample
(Table 5). Consistent with the cell
surface marker data, veterans with CFS showed a general tendency toward
upregulation relative to the controls across all cytokines in this
study, indicated by the nonsignificant two-way interaction between CFS
status and cytokines (P = 0.642) and a highly
significant main effect of CFS (P = 0.006). Linear
contrasts indicated that the group differences were statistically
significant for IL-2 (P = 0.021), IL-10 (P = 0.01), IFN-
(P = 0.014), and TNF-
(P = 0.002). Since the veterans with CFS had uniformly
higher levels of all the cytokines (Table 2) than the controls, the
two-way interaction of CFS status versus cytokines was not expected to
be significant.
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TABLE 5.
Linear contrasts of cytokine levels between Gulf War
veterans with CFS and healthy controls from a mixed-effects model with
interaction terms between group membership and
cytokine measurementsa
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|
We next evaluated the hypothesis of a shift from type I to type II
cytokine responses in the Gulf War veterans, especially in those with
CFS (33). This shift was not observed. Instead, the data
indicated a type I response with significant upregulation in IL-2 and
IFN-
and not IL-4 and IL-6 in CFS veterans. In fact, instead of
finding negative correlations between IFN-
and IL-4 or IL-6, we
found significant positive correlations. Similar positive correlations
were found between IL-2, another type 1 cytokine, and IL-4 and IL-6 in
both the veteran and civilian samples (Table 6). Significant increases in IL-10 were
also detected; IL-10 elevations are characteristic of either a type 1 or type 2 response, at least partly because IL-12 induces IL-10 and
IFN-
production (26, 31).
 |
DISCUSSION |
This paper reports important negative and positive findings. The
important negative finding is that we cannot confirm immune dysregulation in this carefully controlled study of nonveterans who
developed CFS sporadically. When we began collecting these immunological samples, we had several a priori hypotheses. One was that
we would find immune dysregulation in the entire group of CFS patients.
A second related to our finding of decreased cognitive function and
brain magnetic resonance imaging abnormalities in the group of CFS
patients devoid of DSM-III-R psychopathology (8, 20). Those
findings led us to hypothesize that we would find immunological
abnormalities in this subgroup
especially in the most symptomatic of
these patients. Again, those hypotheses were not supported. Even after
stratifying the data for presence or absence of Axis I psychiatric
disorder, there were no significant differences between patients and
controls with regard to any of the immunological variables under study.
Because a Centers for Disease Control and Prevention (CDC) group also
found negative results for their entire CFS patient pool but then did
find some differences following stratification based on illness
severity and mode of illness onset (25), we did a similar
analysis. The CDC group reported differences based on severity, which
we did not confirm. Concerning the differences based on mode of illness
onset, we obtained results different from those of Mawle et al. The one
similarity was the results for the phenotype CD8+
CD11b
. However, we found this cell population to be
altered in the gradual-onset group, while Mawle et al. reported finding
this in the sudden-onset group. These differences across studies show the problems associated with using statistical methods that do not
guard against type 1 errors. In contrast to our use of the mixed-effects model detailed in Materials and Methods, this analysis (both for our data and for the CDC data) did not adjust the
significance level for multiple comparisons. Since our results were not
the same as those noted by the CDC group, our inference is that these results are probably statistical artifacts.
The question arises as to why we were unable to confirm immune
dysregulation in the CFS patients studied. However, the literature makes it clear that inconsistency of results from laboratory to laboratory is the rule rather than the exception. Thus, some but not
all laboratories find decreases in NK cell numbers (13, 29),
T-cell populations (23, 34), and activation markers (19, 29, 40). Concerning cytokines, Strober's 1994 conclusion seems applicable (37): "Studies of circulating
levels of various lymphokines and cytokines in CFS have not yielded
evidence of a clear-cut and reproducible abnormality of
lymphokine/cytokine secretion in CFS."
Cannon et al. have indicated that assay methods and type of tissue are
crucial in evaluating cytokines (3). This is the first study
of cytokine gene expression in CFS. Furthermore, we measured cytokine
RNA from PBLs without in vitro restimulation in order to avoid
artifacts resulting from mitogen activation of lymphocytes. Using
RT-PCR, we are unable to confirm the prior reports of elevated IL-6
levels associated with CFS (1, 12); however, elevated IL-10
levels, seen in our veterans with CFS, has also been reported in a
group of patients with a clinical picture resembling severe, chronic
infectious mononucleosis (16).
Besides the difference in assay methodology, there is another major
difference between our study and those of others. In our work, we
excluded healthy controls who exercised regularly. It is known that
some immune parameters are sensitive to state of fitness. For instance,
NK cell numbers increase with fitness (30). Thus, reductions
in NK cell numbers may reflect the inactivity inherent in CFS rather
than the underlying illness itself. A rather different explanation is
that our group is simply studying the wrong immunological markers.
Consistent with this interpretation are unpublished results of a study
on transforming growth factor B in serum in collaboration with Chun
Chao, in which we found a small but significant increase in 20 subjects
in the nonveteran CFS group compared to 19 of the sedentary controls
(CFS = 187 ± 13 pg/ml; control = 141 ± 11 pg/ml
[P < 0.01]). Thus, it is possible that the
evaluation of other cytokines or the assessment of the function of
stimulated lymphocytes might provide more consistent evidence of immune
dysfunction in CFS patients than tests of lymphocytes in the static condition.
However, the argument that we have been studying the wrong
immunological variables is unlikely given the results of our survey of
immune parameters in Gulf War veterans with CFS. In contrast to the
data for civilians with CFS, Gulf War veterans with CFS show definite
evidence of immune status alteration in both lymphocyte subpopulations
and in their cytokine message. Although we had hypothesized that any
immunological activation found would occur preponderantly in specific
subsets of CFS patients
those without concurrent major
psychopathology
the data did not support this. The immunological
upregulation, reflected by increased numbers of T cells and increases
in PBL cytokine levels, was seen regardless of patient grouping.
A second reason for the study was to test the hypothesis of Rook and
Zumla (33) that CFS patients in general and Gulf War veterans with CFS in particular would show a type 2 pattern of cytokine
activation. Our data did not support that hypothesis for either patient
group. In fact, the pattern of cytokine activation exhibited by the
veterans with CFS was type 1, or inflammatory
with increases in IL-2
and IFN-
possibly related to the concurrent increases in
CD3+ CD4+-T-cell numbers. This type 1 shift
was, if anything, suppressed, as it is known that IL-10, which was also
present at elevated levels in the veterans with CFS, can suppress
IFN-
synthesis (27). Since both these cytokines are
induced by IL-12 (26, 31), IL-10 is commonly associated with
type 1 immune responses.
When we began these studies, we assumed that if we found any evidence
of immune dysfunction in either patient group, it would be in the
civilians. We based that line of thinking on the published data
suggesting that sporadic CFS often involved a postinfectious process
(17), while severe fatigue in Gulf War veterans usually did
not have an infectious or sudden type of onset. In fact, our own data
supported this belief, in that we found that civilians with CFS
reported a significantly higher rate of sudden, rather than gradual,
illness onset than Gulf War veterans (Table 1). However, we found
evidence of altered immune status in Gulf War veterans with CFS and not
in the civilian patients.
How do we interpret this result? There are two quite different answers
to this question. One possibility is that something specific to service
in the Gulf War altered the normal control of the immunological system
in veterans with CFS. We have been careful up to this point not to use
words such as abnormal or dysfunctional in describing these changes,
because the standardized laboratory cell surface marker data for the
veterans were within the normative range. However, the variability of
each measurement for both sick and healthy veterans is substantially
less than that exhibited by nonveterans (Fig. 1 and 2). This suggests
that the veterans are immunologically more homogeneous than the
nonveterans. As Rook and Zumla have hypothesized (33), a
reduction in immunological heterogeneity may result from multiple
vaccinations received by deployed troops (33), an
interpretation supported by a recent study of children vaccinated with
Mycobacterium bovis BCG (35). Finding such a
degree of homogeneity would suggest that it is inappropriate to compare
Gulf War veterans' immunological data with those of a normative
nonveteran group. If this view were taken, it would indicate that Gulf
War veterans with CFS indeed do show evidence of immune dysfunction
relative to the respective Gulf War veteran controls.
An alternative explanation is that the putative immune abnormalities
reflect differences between patients and controls that are independent
of illness. An example would focus again on NK cell numbers. Improved
fitness can increase this lymphocyte population (30), while
partially disturbed sleep can reduce it (15). Decreased
fitness due to inactivity and disturbed sleep is common in CFS.
However, there are some immunological data that contradict this
explanation. Poorly conditioned subjects are reported to have no change
in T-cell numbers (30), and individuals with disturbed sleep
show reduced IL-2 production (15). In contrast, total T-cell
counts and IL-2 levels were higher in Gulf War veterans with CFS than
in Gulf War veteran controls.
We have presented two very different possible explanations for our
finding of differences in immunological profiles between Gulf War
veterans with CFS and healthy Gulf War veterans. Obviously the
determination of which answer is correct will require further research.
However, we believe that the data favor the first possibility
that something about serving in the Gulf War altered the immune status of
that group of veterans who also have CFS. We conclude this because the
veteran immunological data are relatively homogeneous but nonetheless
show a clear difference between sick and healthy subjects and because
veterans with CFS are less severely ill than civilians (32)
and thus should have fewer problems with inactivity and poor sleep than
nonveterans with CFS, whose immunological data are similar to those for
carefully selected controls.
 |
ACKNOWLEDGMENT |
This study was supported by DVA medical research funds and by NIH
Center grant AI-32247.
 |
FOOTNOTES |
*
Corresponding author. Present address: Fatigue Research
Center (127A), VA Medical Center, E. Orange, NJ 07018. Phone: (973) 676-1000. Fax: (973) 676-4661. E-mail:
bhn{at}nbunj.jvnc.net.
 |
REFERENCES |
| 1.
|
Buchwald, D.,
M. H. Wener,
T. Pearlman, and P. Kith.
1997.
Markers of inflammation and immune activation in chronic fatigue and chronic fatigue syndrome.
J. Rheumatol.
24:372-376[Medline].
|
| 2.
|
Caliguri, M.,
C. Murray,
D. Buchwald,
H. Levine,
P. Cheney,
D. Peterson,
A. L. Komaroff, and J. Ritz.
1987.
Phenotypic and functional deficiency of natural killer cells in patients with chronic fatigue syndrome.
J. Immunol.
139:3306-3313[Abstract].
|
| 3.
|
Cannon, J. G.,
J. L. Nerad,
D. D. Poutsiaka, and C. A. Dinarello.
1993.
Measuring circulating cytokines.
J. Appl. Physiol.
75:1897-1902[Abstract/Free Full Text].
|
| 4.
|
Chao, C. C.,
E. N. Janoff,
S. Hu,
K. Thomas,
M. Gallagher,
M. Tsang, and P. K. Peterson.
1991.
Altered cytokine release in peripheral blood monocyte cell cultures from patients with the chronic fatigue syndrome.
Cytokine
3:292-298[Medline].
|
| 5.
|
Cliff, N.
1987.
Analyzing multivariate data.
Harcourt Brace Jovanovich, New York, N.Y.
|
| 6.
|
Cnaan, A.,
N. M. Laird, and P. Slasor.
1997.
Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data.
Stat. Med.
16:2349-2380[Medline].
|
| 7.
|
Crowder, M. J., and D. J. Hand.
1990.
Analysis of repeated measures.
Chapman and Hall, London, England.
|
| 8.
|
DeLuca, J.,
S. K. Johnson,
S. P. Ellis, and B. H. Natelson.
1997.
Cognitive functioning is impaired in chronic fatigue syndrome patients devoid of psychiatric disease.
J. Neurol. Neurosurg. Psychiatry
62:151-155[Abstract].
|
| 9.
|
Denny, T.,
R. Yogev,
R. Gelman,
C. Skuza,
J. Oleske,
E. Chadwick,
S. Cheng, and E. Connor.
1992.
Lymphocyte subsets in healthy children during the first 5 years of life.
JAMA
267:1484-1488[Abstract].
|
| 10.
|
Fukuda, K.,
S. E. Straus,
I. Hickie,
M. C. Sharpe,
A. Komaroff,
A. Schluederberg,
J. F. Jones,
A. R. Lloyd,
S. Wessely,
N. G. Gantz, et al.
1994.
The chronic fatigue syndrome: a comprehensive approach to its definition and study.
Ann. Intern. Med.
121:953-959[Abstract/Free Full Text].
|
| 11.
|
Gause, W. C., and J. Adamovivz.
1994.
The use of the PCR to quantitate gene expression.
PCR Methods Appl.
3:S123-S135[Medline].
|
| 12.
|
Gupta, S.,
S. Aggarwal,
D. See, and A. Starr.
1997.
Cytokine production by adherent and non-adherent mononuclear cells in chronic fatigue syndrome.
J. Psychiatr. Res.
31:149-156[Medline].
|
| 13.
|
Gupta, S., and B. Vayuvegula.
1991.
A comprehensive immunological analysis in chronic fatigue syndrome.
Scand. J. Immunol.
33:319-327[Medline].
|
| 14.
|
Holmes, G. P.,
J. E. Kaplan,
N. M. Gantz,
A. L. Komaroff,
L. B. Schonberger,
S. E. Straus, et al.
1988.
Chronic fatigue syndrome: a working case definition.
Ann. Intern. Med.
108:387-389.
|
| 15.
|
Irwin, M.,
J. McClintick,
C. Costlow,
M. Fortner,
J. White, and J. C. Gillin.
1996.
Partial night sleep deprivation reduces natural killer and cellular immune responses in humans.
FASEB J.
10:643-653[Abstract].
|
| 16.
|
Kanegane, H.,
H. Wakiguchi,
C. Kanegane,
T. Kurashige, and G. Tosato.
1997.
Viral interleukin-10 in chronic active Epstein-Barr virus infection.
J. Infect. Dis.
176:254-257[Medline].
|
| 17.
|
Komaroff, A. L.
1988.
Chronic fatigue syndromes: relationship to chronic viral infections.
J. Virol. Methods
21:3-10[Medline].
|
| 18.
|
Laird, N. M., and J. H. Ware.
1982.
Random effects models for longitudinal data: an overview of recent results.
Biometrics
38:963-974[Medline].
|
| 19.
|
Landay, A. L.,
C. Jessop,
E. T. Lennette, and J. A. Levy.
1991.
Chronic fatigue syndrome: clinical condition associated with immune activation.
Lancet
338:707-712[Medline].
|
| 20.
|
Lange, G.,
J. DeLuca,
H. J. Lee,
J. A. Maldjian, and B. H. Natelson.
1997.
Cerebral abnormalities in chronic fatigue syndrome.
Abst. Soc. Neurosci.
23:561.
|
| 21.
|
Linde, A.,
B. Andersson,
S. B. Svenson,
H. Ahrne,
M. Carlsson,
P. Forsberg,
H. Hugo,
A. Karstorp,
R. Lenkei,
A. Lindwall,
A. Loftenius,
C. Säll, and J. Andersson.
1992.
Serum levels of lymphokines and soluble cellular receptors in primary Epstein-Barr virus infection and in patients with chronic fatigue syndrome.
J. Infect. Dis.
165:994-1000[Medline].
|
| 22.
|
Little, R. C.,
G. A. Milliken,
W. W. Stroup, and R. D. Wolfinger.
1996.
SAS system for mixed models.
SAS Institute Inc., Cary, N.C.
|
| 23.
|
Lloyd, A. R.,
D. Wakefield,
C. R. Boughton, and J. M. Dwyer.
1989.
Immunological abnormalities in the chronic fatigue syndrome.
Med. J. Aust.
151:122-124[Medline].
|
| 24.
|
Marcus, S.,
L. N. Robins, and K. Bucholz.
1990.
Quick diagnostic interview schedule 3R version 1.
Washington University School of Medicine, St. Louis, Mo.
|
| 25.
|
Mawle, A. C.,
R. Nisenbaum,
J. G. Dobbins,
H. E. Gary, Jr.,
J. A. Stewart,
M. Reyes,
L. Steele,
D. S. Schmid, and W. C. Reeves.
1997.
Immune responses associated with chronic fatigue syndrome: a case-control study.
J. Infect. Dis.
175:136-141[Medline].
|
| 26.
|
Morris, S. C.,
K. B. Madden,
J. J. Adamovicz,
W. C. Gause,
B. R. Hubbard,
M. K. Gately, and F. D. Finkelman.
1994.
Effects of IL-12 on in vivo cytokine gene expression and Ig isotype selection.
J. Immunol.
152:1047-1056[Abstract].
|
| 27.
|
O'Garra, A.
1998.
Cytokines induce the development of functionally heterogeneous T helper cell subsets.
Immunity
8:275-283[Medline].
|
| 28.
| Patarca, R., N. G. Klimas, S. Lugtendorf, M. Antoni, and M. A. Fletcher. 1994. Dysregulated expression of
tumor necrosis in chronic fatigue syndrome: interrelations with
cellular sources and patterns of soluble immune mediator expression.
Clin. Infect. Dis. 18(Suppl. 1):S147-S153.
|
| 29.
|
Peakman, M.,
A. Deale,
R. Field,
M. Mahalingam, and S. Wessely.
1997.
Clinical improvement in chronic fatigue syndrome is not associated with lymphocyte subsets of function or activation.
Clin. Immunol. Immunopathol.
82:83-91[Medline].
|
| 30.
|
Pedersen, B. K.
1991.
Influence of physical activity on the cellular immune system: mechanisms of action.
Int. J. Sports Med.
12:S23-S29.
|
| 31.
|
Peng, X.,
A. Kasran, and J. L. Ceuppens.
1997.
Interleukin 12 and B7/CD28 interaction synergistically upregulate interleukin 10 production by human T cells.
Cytokine
9:639-649[Medline].
|
| 32.
| Pollet, C., B. H. Natelson, G. Lange, L. Tiersky,
J. DeLuca, T. Policastro, P. Desai, J. E. Ottenweller, L. Korn, N. Fiedler, and H. Kipen. Medical evaluation of Persian Gulf veterans
with fatigue and/or chemical sensitivity. J. Med., in press.
|
| 33.
|
Rook, G. A. W., and A. Zumla.
1997.
Gulf War syndrome: is it due to a systemic shift in cytokine balance towards a Th2 profile?
Lancet
349:1831-1833[Medline].
|
| 34.
|
Sánchez-Franco, F.,
L. Fernández,
G. Fernández, and L. Cacicedo.
1989.
Thyroid hormone action on ACTH secretion.
Horm. Metab. Res.
21:550-552[Medline].
|
| 35.
|
Shirakawa, T.,
T. Enomoto,
S. Shimazu, and J. M. Hopkin.
1997.
The inverse association between tuberculin responses and atopic disorder.
Science
275:77-79[Abstract/Free Full Text].
|
| 36.
|
Straus, S. E.,
S. Fritz,
J. K. Dale,
B. Gould, and W. Strober.
1993.
Lymphocyte phenotype and function in the chronic fatigue syndrome.
J. Clin. Immunol.
13:30-40[Medline].
|
| 37.
|
Strober, W.
1994.
Immunological function in chronic fatigue syndrome, p. 207-237.
In
S. Straus (ed.), Chronic fatigue syndrome. Marcel Dekker, Inc., New York, N.Y.
|
| 38.
|
Svetic, A.,
F. D. Finkelman,
Y. C. Jian,
C. W. Dieffenbach,
D. E. Scott,
K. F. McCarthy,
A. D. Steinberg, and W. C. Gause.
1991.
Cytokine gene expression after in vivo primary immunization with goat antibody to mouse IgD antibody.
J. Immunol.
147:2391-2397[Abstract].
|
| 39.
|
Svetic, A.,
K. B. Madden,
X. D. Zhou,
P. Lu,
I. M. Katona,
F. D. Finkelman,
J. F. Urban, and W. C. Gause.
1993.
A primary helminthic infection rapidly induces a gut-associated elevation of Th2-associated cytokines and IL-8.
J. Immunol.
150:3434-3441[Abstract].
|
| 40.
|
Swanink, C. M. A.,
J. H. M. M. Vercoulen,
J. M. D. Galama,
M. T. L. Roos,
L. Meyaard,
J. Van der Ven-Jongekrijg,
R. De Nijs,
G. Bleijenberg,
J. F. M. Fennis,
F. Miedema, and J. W. M. Van der Meer.
1996.
Lymphocyte subsets, apoptosis, and cytokines in patients with chronic fatigue syndrome.
J. Infect. Dis.
173:460-463[Medline].
|
| 41.
|
Thomas, D. R.
1993.
Univariate repeated measures techniques applied to multivariate data.
Psychometrika
48:451-464.
|
| 42.
|
Timm, N. H., and T. A. Mieczkowski.
1997.
Univariate and multivariate general linear models: theory and applications using SAS software.
SAS Institute Inc., Cary, N.C.
|
Clinical and Diagnostic Laboratory Immunology, January 1999, p. 6-13, Vol. 6, No. 1
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