Abstract- http://jcp.bmj.com/cgi/content/short/jcp.2009.072561v1?rss=3D1
Full text- http://jcp.bmj.com/cgi/rapidpdf/jcp.2009.072561v1
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'Microbial infections in eight genomic subtypes of Chronic Fatigue
Syndrome/Myalgic Encephalomyelitis (CFS/ME)'
Lihan Zhang,1 John Gough,1 David Christmas,2 Derek L Mattey,3 Selwyn
CM Richards,4 Janice Main, 5 Derek Enlander,6 David Honeybourne,7 Jon
G Ayres,8 David J Nutt,2 Jonathan R Kerr.1
1Department of Cellular & Molecular Medicine, St George=E2=80=99s Universit=
y
of London, London, UK;
2Psychopharmacology Unit, Dept of Community Based Medicine, University
of Bristol, Bristol, UK;
3Staffordshire Rheumatology Centre, Stoke on Trent, UK;
4Dorset CFS Service, Poole Hospital, Dorset, UK;
5Dept of Infectious Diseases and General Medicine, Imperial College
London, St Mary=E2=80=99s Hospital, London, UK;
6New York ME / CFS Service, 860 Fifth Avenue, New York, USA;
7Dept of Respiratory Medicine, Birmingham Heartlands Hospital, UK;
8Dept of Environmental and Occupational Medicine, University of Birmingham,=
UK.
Reprints or correspondence: Dr Jonathan R Kerr, Room 2.267, Jenner
Wing, St George=E2=80=99s University of London, Cranmer Terrace, London SW1=
7
0RE, UK. Email: jkerr@sgul.ac.uk.
JCP Online First, published on December 2, 2009 as 10.1136/jcp.2009.072561
Abstract
We have previously reported genomic subtypes of CFS/ME based on
expression of 88 human genes. In this study we attempted to reproduce
these findings, determine specificity of this signature to CFS/ME, and
test for associations between CFS/ME subtype and infection.
We determined expression levels of 88 human genes in blood of 61 new
patients with idiopathic CFS/ME (according to Fukuda criteria), 6
patients with Q-fever associated CFS/ME form the Birmingham Q-fever
outbreak (according to Fukuda criteria), 14 patients with endogenous
depression (according to DSM-IV criteria) and 18 normal blood donors.
In patients with CFS/ME differential expression was confirmed for all
88 genes. Q-CFS/ME patients had similar patterns of gene expression to
idiopathic CFS/ME. Gene expression in endogenous depression patients
was similar to that in the normal controls, except for upregulation of
five genes (APP, CREBBP, GNAS, PDCD2, PDCD6).
Clustering of combined gene data in CFS/ME patients for this and our
previous study (n=3D117 CFS/ME patients) revealed genomic subtypes with
distinct differences in SF-36 scores, clinical phenotypes, severity
and geographical distribution. Antibody testing for Epstein-Barr virus
(EBV), enterovirus, Coxiella burnetii and parvovirus B19 revealed
evidence of subtype-specific relationships for EBV and enterovirus,
the two most common infectious triggers of CFS/ME.
Keywords: Chronic fatigue syndrome, myalgic encephalomyelitis,
subtypes, gene expression, endogenous depression, Epstein-Barr virus,
parvovirus B19, Coxiella burnetii, enterovirus
Introduction
Chronic Fatigue Syndrome / Myalgic Encephalomyelitis (CFS/ME) is a
disease characterised by severe and debilitating fatigue, sleep
abnormalities, impaired memory and concentration, and musculoskeletal
pain [1]. In the Western world, the
population prevalence is estimated to be of the order of 0.5% [2,3].
Research studies have identified various features relevant to the
pathogenesis of CFS/ME such as viral infection, immune abnormalities
and immune activation, exposure to toxins,
chemicals and pesticides, stress, hypotension, lymphocyte
abnormalities and neuroendocrine dysfunction. However, the precise
underlying disease mechanisms and means by which these abnormalities
inter-relate in CFS/ME patients, remain to
be clarified [4,5].
Various groups have analysed the gene expression in peripheral blood
of patients with CFS/ME and in all of these studies, genes of immunity
and defense are prominent. Following a pilot microarray study which
identified 16 abnormally expressed genes in CFS/ME [6], we have
reported on a comprehensive microarray study which reveals abnormal
expression of 88 human genes in patients with CFS/ME [7]. Clustering
of these data revealed 7 genomic subtypes of CFS/ME with distinct
differences in SF-36 scores, clinical phenotypes, severity and
geographical distribution [7,8]. However, remaining questions relate
to reproducibility and the specificity of these gene abnormalities to
CFS/ME and possible associations with infectious agents.
In this study, we set out to determine whether these findings were
reproducible in fresh subjects, whether the previously reported
dysregulation of these genes also occurred in drug-free patients with
endogenous depression, and whether there was
any relationship between particular microbial infections and CFS/ME
genomic subtype. Results show that these findings are reproducible,
and that gene expression in endogenous depression patients was
markedly different to that in CFS/ME patients, and was similar to that
in the normal controls, in terms of these 88 human genes. Also,
clustering of gene data revealed 8 genomic subtypes with distinct
clinical differences, and several of these had interesting
associations with particular microbial infections.
Methods
Subject enrolment, clinical characterisation and blood sampling CFS/ME
patients (n=3D62), who lived in Birmingham (n=3D6), Bristol (n=3D3), London
(n=3D9) and New York (n=3D44) were diagnosed according to Fukuda
diagnostic criteria for CFS/ME [1] and enrolled into the study. All
these suffered from idiopathic CFS/ME except the 6 Birmingham
patients, who suffered from CFS/ME which had been triggered by
laboratory documented Q fever. Patients with psychiatric disease were
excluded using the Minnesota International Neuropsychiatric Interview
(MINI), thus ensuring that none of our CFS/ME patients was suffering
from major psychiatric disease or abuse of alcohol or other drugs.
Clinical and Q-PCR data for these new patients were combined with 55
CFS/ME patients from a previous study [7,8], giving a total of 116
CFS/ME patients, who lived in Birmingham (n=3D6), Bristol (n=3D14),
Leicester (n=3D1), London (n=3D12), New York (n=3D55) and Dorset (n=3D28).
Patients suffering from endogenous depression (n=3D14) were enrolled
from Bristol, UK, and surrounding area. These patients fulfilled
DSM-IV criteria, had not smoked within the previous year, and had not
taken antidepressants in the previous year.
Healthy normal blood donors enrolled from the Dorset National Blood
Service (NBS) (n=3D29) were used as a comparison group. Restrictions
imposed by the NBS on those allowed to donate blood are outlined
elsewhere [6].
For all patient groups, individuals who smoked in the previous year,
who abused alcohol or other drugs, were currently taking (or were
within 3 months of taking) antibiotics, steroids, cytotoxic drugs or
antidepressants were excluded from the study.
For all enrolled subjects (patients and controls), according to the
recommendations of the International CFS Study Group [9], severity of
physical and mental fatigue was assessed using the Chalder Fatigue
Scale [10]; level of disability was assessed using the Medical
Outcomes Survey Short Form-36 (SF-36); accompanying symptoms were
characterised using the Somatic and Psychological Health Report
(SPHERE); sleep abnormalities were assessed using the Pittsburgh Sleep
Questionnaire; and assessment of type and severity of pain was
performed using the McGill Pain Questionnaire.
Patients and controls gave informed written consent according to
guidance of the Wandsworth Research Ethics Committee (approval number
05/Q0803/137). For the New York patients, approval of the local
Institutional Review Board was obtained.
The human experimentation guidelines of the US Department of Health
and Human Services were followed in this study.
2.5ml blood was taken from both CFS/ME patients and normal blood
donors (as part of routine blood donation) into PAXgene tubes
(PreAnalytix) and total RNA extracted using the PAXgene blood RNA kit
(PreAnalytix), according to the instructions of the manufacturer. RNA
quality and amount were confirmed by micro-spectrophotometry
(Nanodrop, Rockland, DE, USA). Total RNA samples used in this study
had an absorbance ratio (A260/280) of 1.9-2.0.
QPCR
QPCR (Applied Biosystems, Foster City, CA, USA) was used to quantitate
the amount of mRNA for 88 CFS/ME-associated human genes by the
comparative method, using custom 384-well low-density arrays (LDA) and
the ABI PRISM 7900HT instrument (Applied Biosystems) with
glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as the endogenous
control gene. Experiments were performed in triplicate using the
protocol described previously [6,7]. Data was displayed using SDS 2.2
software (ABI), discordant data between replicates omitted, and
results for each LDA calculated, and loaded into ABI SDS v2.2
Enterprise Edition software.
The threshold cycle (Ct) for each test gene in each sample was
compared to that for GAPDH to calculate a =CE=94Ct value. =CE=94Ct values f=
or
were then normalised to the calibrator sample to give the =CE=94=CE=94Ct va=
lues.
Relative quantities (RQ) (2-=CE=94=CE=94Ct) of each
mRNA of interest were then calculated. Samples showing a difference
between minimum and maximum RQ values of =E2=89=A5100 (indicating poor
replicate concordance) were excluded. The t-test was used to compare
mean RQ values between groups. A
p value of =E2=89=A40.05 was taken to be significant.
Clustering of QPCR-generated gene values of CFS/ME patients
Ct values for all 88 CFS/ME-associated genes in 117 CFS/ME patients
were then normalised and clustered using Genesis software [11]. For
each of the eight CFS/ME subtypes identified using this approach, mean
RQ values were calculated for each
gene, and used to generate fold-difference (CFS/ME / Normal) values
for each gene in each CFS/ME subtype. Mean fold-difference values for
each gene in each CFS/ME subtype were then clustered with and without
normalisation / median centering using Cluster version 2.11 software
and visualised using Treeview version 1.60 software [12]. The
clustering algorithm in both of these software programs has been
described previously [12].
Detection of anti-microbial antibodies
IgM and IgG antibodies specific to 4 microbes which are well
recognised to trigger CFS/ME were detected by ELISA, according to the
manufacturer=E2=80=99s instructions; Epstein-Barr virus (viral capsid antig=
en
(VCA) IgM and IgG, early antigen (EA) IgG,
and Epstein-Barr nuclear antigen (EBNA) IgG) (Meridien Bioscience Inc,
Cincinnati, OH, USA), enterovirus (all serotypes) (Virion Serion,
Wurzberg, Germany), parvovirus B19 (viral protein 2 (VP2) IgM and IgG)
(Biotrin, Dublin, Ireland) and Coxiella burnetii (phase I and II IgG)
(Virion Serion, Wurzberg, Germany).
Statistical testing
Testing of the significance of associations of gene expression levels
with different patient groups was performed using a 2-tailed t-test.
Testing of the significance of association between clinical parameters
and CFS/ME genomic subtype was performed using =CF=872, ANOVA and the
Mann-Whitney U tests. Testing of the significance of association
between microbial markers in CFS/ME and CFS/ME subtypes was performed
using =CF=872 analyses, and ANOVA.
Results
Subjects and clinical characterisation
A total of 117 CFS/ME patients fulfilling CDC diagnostic criteria were
used in this study. For 55 CFS/ME patients, previously published data
was used, while the remaining 62 CFS/ME patients had not previously
been tested; for 6 of these, CFS/ME disease had been triggered by
laboratory documented C. burnetii infection. In addition, 14 patients
with endogenous depression and 18 normal blood donors were also
studied.
A summary of the clinical details of these subjects is shown in Table
1. In general, all CFS/ME groups had similar profiles of symptoms and
mean clinical scores, and QCFS/ME was phenotypically similar to the
other CFS/ME patients for whom the
triggering factors were unknown. Endogenous depression patients had a
markedly low prevalence of numbness / tingling and tender
lymphadenopathy, and lower bodily pain as indicated by the McGill pain
questionnaire mean score, as compared with
CFS/ME. Normal blood donors had very low prevalence of all symptoms,
little fatigue (Chalder), pain (McGill), associated symptoms (SPHERE),
normal sleep (PSQI) and high SF36 total scores (Table 1), as would be
expected.
QPCR
Quantitative PCR was carried out using TaqMan primers/probes specific
for 88 human genes which were previously found to be differentially
expressed in CFS/ME patients [7]. This analysis confirmed that most of
these genes differed significantly between CFS/ME and Normal groups.
Of the 88 genes, 84 were found to be upregulated and 4 were
downregulated (HIF1A, IL7R, PAPOLA, SHPRH), which is similar to what
we reported previously [7]. Gene expression in patients with QCFS/ME
was also found to be markedly different to the normal group, and very
similar to that found in patients with CFS/ME. Gene expression in
patients with endogenous depression did not differ markedly from that
in the normal group, except in the case of five genes (APP, CREBBP,
GNAS, PDCD2, PDCD6), where significant upregulation (fold-difference
=E2=89=A51.5) was found (Table 2).
Genomic CFS/ME subtypes
Clustering of =CE=94Ct values for the 88 CFS/ME-associated genes in the 117
CFS/ME patients identified 8 subtypes (designated A =E2=80=93 H); consistin=
g
of 27, 6, 19, 5, 21, 13, 19 and 4 CFS/ME patients, respectively. There
were 3 patients whose gene profile
did not fit into any of these 8 subtype groupings. Mean fold
difference values for each CFS/ME subtype are shown in Table 3 and
Figure 1. Most genes in each subtype were shown to be upregulated
(Table 3 & Figure 1).
The relationship between the subtypes of the present study and those
of the previous study which examined only 55 CFS/ME patients [7,8]
maybe difficult to determine. As these subtypes are derived using
clustering, which finds similar groups on the basis of gene expression
values, there is no means to predict the outcome of the clustering. As
there was only moderate preservation of the previous CFS/ME patient
groupings in the present study, we have designated the subtypes, A =E2=80=
=93
H, to distinguish them from those of the previous study, which were
designated 1 =E2=80=93 7 [7].
Analysis of sex ratios for each subtype reveals that subtype D is made
up of females only, subtype H is made up of equal number of males and
females, and the remaining subtypes are made up predominantly of
females.
It is particularly interesting that 5 of 6 CFS/ME patients with
Q-CFS/ME clustered in the same subtype (subtype A).
The clinical phenotype was distinct between subtypes; subtype D was
the most severe, having the lowest scores for SF36 modules RP, VIT,
GH, BP and Total score, and the highest frequency of occurrence of
muscle pain and sleep problems. Subtype B was the least severe, having
the highest scores for SF36 modules RP, GH, MH and total score.
Subtype B had a higher median score for the SF36-RP (physical role)
than all the others combined (87.5 v 0), p=3D0.04; Mann-Whitney test).
However, subtype B had the highest frequency of cognitive dysfunction,
muscle weakness and post-exertional malaise. Subtype B showed a higher
frequency of cognitive dysfunction than all non-subtype B patients
combined (p=3D0.03) and showed
an increased severity and duration of headache compared with all
non-subtype B patients combined (p=3D0.02). Subtype B also had a higher
median score for mental fatigue (Chalder scale) than all non-subtype B
patients combined although this did not reach significance (9.5 v 7.0;
p=3D0.06). Subtypes B and C had the best mental health scores, and
subtypes A and F had the worst (Figure 2, panels A & B).
Subtype E had a higher median score for SF36-VIT (vitality) than all
the others combined (35.0 v 15.0; p=3D0.05; Mann-Whitney test). Subtype
E had the highest frequency of GI problems. Patients of subtype F
showed a higher frequency of increased severity of numbness / tingling
compared with all non-subtype F patients combined (p=3D0.03). Patients
of subtype H showed an increased frequency of severity of sore throat
compared with all non-subtype H patients combined (p=3D0.01) (Figure 2,
panels A & B).
As regards possible association of subtype with geographical location,
there was evidence to support this, as we found previously [7].
Predominant subtypes in each geographical location were as follows;
Birmingham (subtype A), Bristol (subtype C), Leicester (subtype C),
London (subtype C, then subtype G), New York (subtype E, then subtypes
G, A, C and F), Dorset (subtypes A, F, B). Subtype A was prominent in
New York, Birmingham and Dorset; subtype B was prominent in Dorset;
subtype C was prominent in Bristol, London and New York; subtype D was
prominent in Bristol and London; subtype E was prominent in New York;
subtype F was prominent in Dorset and New York; subtype G was
prominent in New York; subtype H was prominent in Dorset (Figure 2,
panel C).
Microbial infections
The presence and titre of specific antibodies (IgM and IgG) to four
treatable microbial infections which are well recognised as triggers
of CFS/ME were also determined in serum samples; these were
Epstein-Barr virus, enterovirus, parvovirus B19 and
Coxiella burnetii. The seroprevalence (proportion of subjects who were
positive for specific IgG) of each of these infections was typical of
the general population; EBV (based on VCA IgG) (88%), enterovirus
(49%), parvovirus B19 (based on VP2 IgG)
(74%), C. burnetii (based on phase I or II IgG) (10%). Of those 11
patients who had C. burnetii IgG, 5 were patients whose CFS/ME disease
had been triggered by laboratory documented Q fever.
CFS/ME patients with acute infection with one or more of these agents
(IgM or acute phase IgG) were also detected; EBV (based on VCA IgM)
(n=3D3), enterovirus (n=3D6), parvovirus B19 (n=3D1), C. burnetii (based on
phase II IgG) (n=3D12). Of those 12
patients who were positive for C. burnetii phase II IgG, 5 were
patients with QCFS/ME. There were no acute infections detected in the
normal group.
Regarding EBV serology, there were also associations between CFS/ME
subtype and both EBV VCA IgM titre (p=3D0.0038) and EBV EBNA IgG titre
(p=3D0.0011) (Figure 2, panel D). Using the EBV markers VCA IgM, VCA
IgG, EA IgG and EBNA IgG, we
determined the EBV serostatus of infection for each subject (ie.
seronegative, primary infection / reactivation, late phase of
infection). Among the CFS/ME patients, there were 11 seronegative, 61
primary / reactivation, and 39 late phase of infection,
as compared the Normal group, in which there was 1 seronegative, 8
primary / reactivation, and 19 late phase of infection (=CF=872 =3D 9.91,
degrees of freedom =3D 2, p =3D 0.007) (Figure 2, panel E).
The distribution of CFS/ME patients with EBV serostatus categories,
seronegative, primary / reactivation and late phase of infection,
across the 8 CFS/ME genomic subtypes is shown in Figure 2, panel E. In
the normal persons, the predominant
category of EBV serostatus was late phase of infection, while in the
CFS/ME subtypes, the predominant category of EBV serostatus was
primary / reactivation, which was seen in subtypes A, B, C, D, F and
H. Subtype G had equal numbers of
primary / reactivation and late phase, while subtype E had a
predominance of late phase subjects, but also had 5 seronegative
subjects. This distribution was found to be almost statistically
significant (=CF=872 =3D 25.9, degrees of freedom =3D 16, p =3D 0.055).
EBV-associated genes in each CFS/ME subtype
Within the CFS/ME-associated gene signature of 88 human genes, there
were 12 which have recognised associations with EBV infection; these
associations have been summarised previously [7]. The fold-difference
values, for each of these 12 genes in each CFS/ME subtype / normal,
were analysed using ANOVA, for significant associations. With all 12
genes, there was a trend which did not reach significance (df =3D
89,p=3D0.119). However, when GABPA and EGR1 were removed from the
analysis, the remaining 10 genes showed a striking association with
subtype (ANOVA, df=3D73, p=3D0.0001) (Figure 2, panel F).
Discussion
We have previously reported the differential expression of 88 human
genes in CFS/ME and evidence of clinically relevant subtypes [7,8]. In
the present study, we have confirmed this differential expression in
62 additional and previously untested
CFS/ME patients. Combining the previous cohort and the new cohort, we
have found evidence of 8 genomic CFS/ME subtypes with marked
differences in global functioning, clinical symptoms, levels of
severity and geographical distribution. The function of these genes
and their networks has been published previously [7].
We have addressed the question of the specificity of these 88 genes to
CFS/ME, by testing drug-free patients with endogenous depression. The
fact that only 5 of these genes were abnormally expressed in
endogenous depression patients as compared with normals, supports the
view that CFS/ME and endogenous depression are biologically distinct,
and that the psychological features of CFS/ME are in fact secondary to
the pathogenesis.
It is particularly interesting that 5 of 6 CFS/ME patients with
Q-CFS/ME clustered in the same subtype (subtype A). As these patients
had suffered from CFS/ME for several years, this finding suggests that
they have a common underlying theme, which maybe stable for a long
time after the onset of disease. In view of this, and as various genes
within this human gene signature are closely linked with EBV infection
(NFKB1, EGR1, ETS1, GABPA, CREBBP, CXCR4, EBI2, HIF1A, JAK1, IL6R,
IL7R,
PIK3R1), and enterovirus infection (EIF4G1), we tested the serum
samples for markers for four treatable microbial infections which are
well recognised to trigger CFS/ME; EBV, enterovirus, parvovirus B19
and C. burnetii (the agent of Q fever), with the hypothesis that these
genomic CFS/ME subtypes may represent host responses to particular
infectious agents.
One patient with subtype E was suffering from acute parvovirus B19 at
the time of sampling. This patient=E2=80=99s symptoms were typical of CFS/M=
E,
but this is not unexpected as B19 is a recognized trigger for CFS/ME
[13]. The importance of testing for these infections is illustrated
here as we have shown previously that B19-CFS/ME is highly responsive
to treatment with intravenous immunoglobulin (IVIG) [14].
Six patients were suffering from acute enterovirus infections (of
undetermined serotype) at the time of sampling, but there was no
subtype relationship as 2 patients occurred in each of subtypes A, E
and G, respectively. Enteroviruses have long been
recognized to trigger CFS/ME [15], and they have been detected in the
stool [16] and stomach epithelium [17] in CFS/ME patients. Detection
in the stomach has been shown to be associated with gastrointestinal
symptoms in CFS/ME patients [17].
However, in the present study, subtypes A, E and G did not exhibit GI
symptoms more prominently than the other subtypes.
Twelve CFS/ME patients and 1 Normal subject exhibited IgG to Coxiella
burnetii phase II antigen, suggesting possible acute infection. Five
of these CFS/ME patients were those with Q-CFS/ME. The patients in
whom these antibodies were detected
were of subtypes A, B, D, E, and G. Therefore, apart from the patients
with QCFS/ME (whose CFS/ME disease onset was associated with
laboratory documented acute Q fever), there were no subtype specific
relationships with C. burnetii antibodies.
The subtype associations with EBV and EBV-linked genes are
interesting, suggesting differences in the role of EBV and consequent
host responses in the different subtypes. The finding of a noticeably
large proportion of CFS/ME patients who were EBV seronegative (10%),
compared to 4% in the normal group was quite surprising, given the
strong link between EBV and CFS/ME. The fact that 5 of these 11
seronegative cases occurred in subtype E is interesting, but remains
unexplained at present.
It has been recognized for some time that subtypes of CFS/ME exist,
and it has been thought that these subtypes may, at least in part,
reflect particular aetiological factors [18]. A symptom-based approach
has had some success in identifying
musculoskeletal, inflammatory and neurological subtypes [19], however,
these groups had only minor differences in overall functional severity
in contrast to those of the present study.
It is intriguing that it is possible to identify CFS/ME subtypes on
the basis of expression values for these 88 genes, and even more so
that these subtypes have distinct clinical phenotypes, with marked
differences in the occurrence of particular symptoms and their
severity. However, what precise sequence of events are involved in the
genesis of the gene signatures in each subtype remains to be
elucidated. Further work is urgently required to validate and develop
these findings.
Acknowledgements
This work was supported by grants from the Chronic Fatigue Syndrome
Research Foundation (CFSRF), UK (salaries of JG and DC), Sir Joseph
Hotung (salaries of JRK and BB), and a Wellcome Trust Vacation
Scholarship (awarded to LZ). We thank Dr Frank Boulton, Ms Julie
Williams, Mr Peter Rogers, Ms Diana Carr and the NBS teams of East
Dorset for their help in enrolment and sampling of normal blood
donors; Beverley Burke, Deepika Devanur, Joanne Hunt and Robert Petty
for help with sample processing and omission of non-concordant Q-PCR
data, and all the patients with CFS/ME and blood donors for their
participation.
This work was presented at the International Association for Chronic
Fatigue Syndrome / Myalgic Encephalomyelitis (IACFSME), Reno, Nevada,
USA, March 2009.
Competing interests =E2=80=93 none to declare
Take Home Messages
Expression of 88 human genes was confirmed as being significantly
different between CFS/ME patients and normal controls.
Gene expression in endogenous depression patients was similar to that
in the normal controls.
CFS/ME patients can be grouped into Genomic subtypes which have
different clinical phenotypes.
There was evidence of subtype-specific relationships for Epstein-Barr
virus (EBV) and enterovirus, the two most common triggers for CFS/ME.
The Corresponding Author has the right to grant on behalf of all
authors and does grant on behalf of all authors, an exclusive licence
(or non-exclusive for government employees) on a worldwide basis to
the BMJ Publishing Group Ltd and its Licensees
to permit this article to be published in Journal of Clinical
Pathology editions and any other BMJPGL products to exploit all
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http://jcp.bmjjournals.com/ifora/licence.pdf
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FIGURE LEGENDS
Figure 1.
Absolute fold-difference values (mean RQ in CFS/ME patients / mean RQ
in normal controls) for each of 88 CFS/ME associated genes in 8 CFS/ME
subtypes (A =E2=80=93 H).
Figure 2, panel A.
SF36 domain and total scores for each CFS/ME subtype, all CFS/ME
subjects and Normals; physical function, physical role (RP), bodily
pain (BP), general health (GH), vitality (VIT), social functioning
(SF), emotional role (RE), mental health (MH) and
total score (Total).
Figure 2, panel B.
Scores indicating occurrence and severity of 11 clinical symptoms and
results of neurocognitive testing for each CFS/ME subtype, all CFS/ME
subjects and Normals; headache (HA), sore throat (ST), swollen glands
(GLA), cognitive defect (COG),
muscle pain (MP), joint pain (JP), muscle weakness (MW),
postexertional malaise (PEM), sleep problems (SLE), fainting /
dizziness (F/D), gastrointestinal complaints (GI), numbness / tingling
(N/T); Spatial span (SSP), Verbal recognition memory (VRM).
Figure 2, panel C.
Histogram showing the numbers of CFS/ME patients of each subtype
occurring in each of the 6 geographical locations.
Figure 2, panel D.
Epstein Barr virus (EBV) antibody titres (VCA IgM, VCA IgG, EA IgG,
EBNA IgG) in each CFS/ME subtype and the normal comparison group.
Figure 2, panel E. Distribution of categories of EBV serostatus
(seronegative, primary / reactivation, late phase of infection) in the
CFS/ME subtypes, A to H, in CFS/ME (all subtypes combined) and in
Normal controls.
Figure 2, panel F. Log (base 2) of fold-difference values of 10 human
genes known to be important in EBV infection, in 8 CFS subtypes (A =E2=80=
=93
H).
(rest is tables and charts)
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