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Citation: Jason, L.A.; Katz, B.Z.
Predisposing and Precipitating
Factors in Epstein–Barr Virus-Caused
Myalgic Encephalomyelitis/Chronic
Fatigue Syndrome. Microorganisms
2025,13, 702. https://doi.org/
10.3390/microorganisms13040702
Copyright: © 2025 by the authors.
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Review
Predisposing and Precipitating Factors in Epstein–Barr
Virus-Caused Myalgic Encephalomyelitis/Chronic
Fatigue Syndrome
Leonard A. Jason 1, * and Ben Z. Katz 2
1Center for Community Research, DePaul University, Chicago, IL 60614, USA
2Feinberg School of Medicine, Ann and Robert H. Lurie Children’s Hospital of Chicago, Northwestern
University, Chicago, IL 60208, USA; bkatz@luriechildrens.org
*Correspondence: ljason@depaul.edu
Abstract: Long COVID following SARS-CoV-2 and Myalgic Encephalomyelitis/Chronic
Fatigue Syndrome (ME/CFS) following infectious mononucleosis (IM) are two examples
of post-viral syndromes. The identification of risk factors predisposing patients to de-
veloping and maintaining post-infectious syndromes may help uncover their underlying
mechanisms. The majority of patients with ME/CFS report infectious illnesses before the
onset of ME/CFS, with 30% of cases of ME/CFS due to IM caused by the Epstein–Barr
virus. After developing IM, one study found 11% of adults had ME/CFS at 6 months
and 9% had ME/CFS at 1 year. Another study of adolescents found 13% and 7% with
ME/CFS at 6 and 12 months following IM, respectively. However, it is unclear which
variables are potential risk factors contributing to the development and maintenance of
ME/CFS following IM, because few prospective studies have collected baseline data before
the onset of the triggering illness. The current article provides an overview of a study
that included pre-illness predictors of ME/CFS development following IM in a diverse
group of college students who were enrolled before the onset of IM. Our data set included
an ethnically and sociodemographically diverse group of young adult students, and we
were able to longitudinally follow these youths over time to better understand the risk
factors associated with the pathophysiology of ME/CFS. General screens of health and
psychological well-being, as well as blood samples, were obtained at three stages of the
study (Stage 1—Baseline—when the students were well, at least 6 weeks before the student
developed IM; Stage 2—within 6 weeks following the diagnosis of IM, and Stage 3—six
months after IM, when they had either developed ME/CFS or recovered). We focused on
the risk factors for new cases of ME/CFS following IM and found factors both at baseline
(Stage 1) and at the time of IM (Stage 2) that predicted nonrecovery. We are now collecting
seven-year follow-up data on this sample, as well as including cases of long COVID. The
lessons learned in this prospective study are reviewed.
Keywords: prospective; ME/CFS; risk factors; cytokines
1. Predisposing and Precipitating Factors in Epstein–Barr Virus-Caused
ME/CFS
Epstein–Barr virus (EBV) causes almost all cases of heterophile antibody positive
Infectious Mononucleosis (IM), and the heterophile antibody test is positive in about 90%
of young adults who develop IM (as reviewed in [
1
]). Several studies have attempted
to better define the relationship between EBV and Myalgic Encephalomyelitis/Chronic
Microorganisms 2025,13, 702 https://doi.org/10.3390/microorganisms13040702
Microorganisms 2025,13, 702 2 of 11
Fatigue Syndrome (ME/CFS). For example, White et al. [
2
] assessed patients with IM
or an upper respiratory tract infection for the development of fatigue and/or ME/CFS.
Nine percent of subjects with IM, due to EBV, were fatigued and complained of excessive
sleeping at 6 months, compared with none who had a previous upper respiratory tract
infection. Hickie et al. [
3
] showed an 11% rate of ME/CFS 6 months following IM as well
as following 2 other similar systemic infections. In another study, following a diagnosis of
IM among youths, the incidence of ME/CFS at 6, 12, and 24 months was 13%, 7%, and 4%,
respectively [4].
Most patients with IM improve over time, whereas those individuals who develop
ME/CFS remain impaired [
5
]. There are likely a host of predisposing, precipitating, and
perpetuating factors for the development of ME/CFS, which might be similar or different to
risk factors identified for developing long COVID (e.g., SARS-CoV-2 viremia, Epstein–Barr
viremia, specific autoantibodies, type II diabetes, obesity, elevated blood pressure, chronic
lung disease, and depression [6]).
There is evidence of inflammation among those with ME/CFS. Increases in IL-8 in
the cerebrospinal fluid of some patients with ME/CFS have been reported, supporting
the hypothesis that symptoms may be related to immune dysfunction within the central
nervous system [
7
]. Broderick et al. [
8
] applied network analysis to cytokines in patients
with ME/CFS and healthy controls; outcomes were consistent with attenuated T-cell helper
[Th]1 and Th17 immune responses in the presence of a Th2 inflammatory milieu. Thus
ME/CFS following IM might be an extension of the known autoimmune phenomena that
can accompany primary EBV infection [9].
Multiple studies in recent years have reported detectable changes in metabolic path-
ways related to energy production, amino acids, nucleotides, nitrogen, lipids, and neuro-
transmitters in patients with ME/CFS [
10
–
13
]. Other studies have indicated an increased
risk of ME/CFS among close relatives of index patients, suggesting a heritable compo-
nent [
14
]. People with ME/CFS with positive ME/CFS family histories are more likely
to have gastrointestinal symptoms than those with ME/CFS without those family histo-
ries [
15
]. Guo et al. [
16
] and Xiong et al. [
17
] have found disruptions in the gastrointestinal
microbiome among patients with ME/CFS, and we have found that GI symptoms predis-
pose to the development of severe ME/CFS following IM [
18
]. Furthermore, the disruptions
in the gastrointestinal microbiome described in patients with ME/CFS are associated with
an increase in pro-inflammatory and a reduction in anti-inflammatory species [19].
There are a range of other areas of impaired biological functioning among those
with ME/CFS and long COVID, including deficits in cerebral blood flow [
20
]. Thapaliya
et al. [
21
] found significantly larger volumes of the pons, the superior cerebellar peduncle,
and the brainstem in both patients with long COVID and ME/CFS, and inflammation
could be causing varied deficits in brain function in these patients (e.g., brain fog). “Diffuse
white-matter disease” might also contribute to the cognitive difficulties seen in patients
with ME/CFS and long COVID [
22
]. Inflammatory immune system response to the virus,
injury to blood vessels, and/or lack of oxygen to the brain may account for these changes.
Finally, microglia in the white matter of the brain, which are responsible for pruning the
connections between neurons to improve neural circuits, could be damaged by cytokines
(e.g., CCL11) and consequently reduce the generation of new nerve cells, affect memory
formation [
23
], and lead the neurological symptoms of long COVID and/or ME/CFS. Zinn
and Jason [
24
] explored the role of the cortical autonomic network involved in higher-order
control of autonomic nervous system functioning in patients with ME/CFS and healthy
controls under resting-state quantitative electroencephalographic (qEEG) scalp recordings
and found evidence for reduced higher-order homeostatic regulation and adaptability
in ME/CFS.
Microorganisms 2025,13, 702 3 of 11
Almost all studies reviewed above examined patients after becoming ill, with some
patients being infected with EBV or SARS-CoV-2. A key question is why some people
remain ill after a viral infection, while others recover. Prospective studies of individuals
before infection may yield critical insights about conditions that predispose to long-term
illness. For the past decade, the authors have been working to identify biological pro-
files and behavioral domains that predispose and precipitate ME/CFS, and our work is
described below.
2. Prospective Study
From 2014 through 2018, data were collected from 4501 demographically diverse col-
lege students at least 6 weeks before the development of IM (baseline, Stage 1). They were
then followed for the development of IM (Stage 2—diagnosed via a positive monospot or
specific Epstein–Barr virus serologies [a positive viral capsid antigen {VCA} immunoglobu-
lin {Ig} M or a positive VCA IgG with a negative Epstein–Barr nuclear antigen antibody]).
Six months later (Stage 3), they were assessed for the development of ME/CFS or recovery;
for further details see Jason et al. [
25
]. Individuals were examined by a physician in Stage 3
and this information as well as self-report questionnaires was used to designate whether the
person had ME/CFS. We stored biological samples from each stage of the study, including
pre-illness serum and plasma, as well as viable white blood cells from Stages 2 and 3.
Figure 1shows that 238 of the 4501 students (5.3%) developed IM. Six months later,
55 of the 238 met the criteria for ME/CFS, and 157 were asymptomatic [
25
]. In all, 67 of
the 157 asymptomatic students served as recovered controls. Students with “severe”
ME/CFS (those who met > 1 set of criteria for ME/CFS) were compared to students who
met a single set of criteria (“moderate” ME/CFS) and to those who recovered 6 months
following IM (See Figure 1). We did not find any significant differences between those
who developed ME/CFS versus those who recovered, on pre-illness baseline differences in
stress, coping, anxiety, or depression. We did find baseline pre-illness complaints of fatigue
and deficiencies in IL-5 and IL-13 in the group that went on to develop severe ME/CFS
versus those who recovered. Deficiencies in IL-5 and IL-13 before contracting IM may
influence the immune response once the virus is contracted. For example, there is evidence
in human and mouse models that IL-5 and IL-13 contribute to the pathology associated
with ulcerative colitis.
Microorganisms 2025, 13, x FOR PEER REVIEW 4 of 12
Figure 1. Recruitment of participants for prospective study at Waves 1, 2, and 3.
3. Baseline Network Analysis
In a network analysis study, we next examined groups of cytokines within each con-
dition before developing IM. Figures 2 and 3 show intercommunication in the pre-illness
immune systems of the severe ME/CFS group and the recovered controls. It is evident that
when compared to the groupings of cytokines in the recovered controls, the cytokines of
those who went on to develop severe ME/CFS are highly clustered [26]. This network
analysis suggests that the baseline deficiencies of IL5 and IL13 in the severe ME/CFS group
may have led to the clustering of cytokines seen at baseline in the participants who devel-
oped severe ME/CFS following IM compared to those who recovered. More differentiated
cytokine networks were seen for the recovered controls at baseline. In general, as with
findings from Sorenson et al. [27], we found a different paern of cytokine activation in
control subjects versus subjects with post-viral fatigue, both before developing IM and
after [26]. In the ME/CFS sample, the in silico-modeled cytokine-association paerns were
also more interwoven, with less grouping into functional categorizations than in the
healthy controls. The implication is that pathway activation is less discrete and more re-
flective of an ill-orchestrated immunologic response in those who developed ME/CFS. The
differences in the paern associations between these two samples were statistically signif-
icant, providing support for an immunologic pathogenic process.
Figure 1. Recruitment of participants for prospective study at Waves 1, 2, and 3.
Microorganisms 2025,13, 702 4 of 11
3. Baseline Network Analysis
In a network analysis study, we next examined groups of cytokines within each
condition before developing IM. Figures 2and 3show intercommunication in the pre-illness
immune systems of the severe ME/CFS group and the recovered controls. It is evident
that when compared to the groupings of cytokines in the recovered controls, the cytokines
of those who went on to develop severe ME/CFS are highly clustered [
26
]. This network
analysis suggests that the baseline deficiencies of IL5 and IL13 in the severe ME/CFS
group may have led to the clustering of cytokines seen at baseline in the participants
who developed severe ME/CFS following IM compared to those who recovered. More
differentiated cytokine networks were seen for the recovered controls at baseline. In general,
as with findings from Sorenson et al. [
27
], we found a different pattern of cytokine activation
in control subjects versus subjects with post-viral fatigue, both before developing IM and
after [
26
]. In the ME/CFS sample, the in silico-modeled cytokine-association patterns were
also more interwoven, with less grouping into functional categorizations than in the healthy
controls. The implication is that pathway activation is less discrete and more reflective of an
ill-orchestrated immunologic response in those who developed ME/CFS. The differences in
the pattern associations between these two samples were statistically significant, providing
support for an immunologic pathogenic process.
Microorganisms 2025, 13, x FOR PEER REVIEW 5 of 12
Figure 2. Cytokine data at baseline for participants who eventually had severe ME/CFS. Cytokines
colored red are pro-inflammatory, those colored blue are anti-inflammatory. Cytokines not colored
have multi-purpose functions.
Figure 3. Cytokine data at baseline for Controls. Cytokines colored red are pro-inflammatory, those
colored blue are anti-inflammatory. Cytokines not colored have multi-purpose functions.
4. Predicting ME/CFS
We next examined other predictors (i.e., other pre-illness variables as well as varia-
bles present at the onset of IM) of those who developed moderate and severe ME/CFS
following IM. Multiple data points included seven self-report questionnaires, physical ex-
amination findings, the severity of the mononucleosis scale [28], and cytokine analyses.
Two random forest classification analyses were conducted to predict the development of
ME/CFS [18]. Patients with stomach pain, bloating, and symptoms of an irritable bowel at
pre-illness baseline, low levels of IL-13 and/or IL-5 at pre-illness baseline (previously dis-
cussed), and severe gastrointestinal symptoms at the time they contracted mononucleosis
had a nearly 80% chance of developing severe ME/CFS six months following IM.
5. Baseline Metabolic Pathways
Metabolomics has allowed investigators to beer understand which metabolic path-
ways are dysregulated in several different diseases. In our next study, Jason et al. [29]
examined baseline metabolomics levels among those with severe ME/CFS versus controls.
A series of binary logistic regressions were conducted to classify the severe ME/CFS and
recovered groups. Significant differences were observed for the following metabolites: S-
adenosyl-L-methionine (part of one-carbon metabolism and is a methyl donor for epige-
netic regulation), glutathione (part of glutathione metabolism), cysteine (an amino acid
that participates in a variety of pathways, including glutathione metabolism), thiamine
(modified and used as a cofactor in several TCA cycle enzymes), and N-acetyl-alanine
Figure 2. Cytokine data at baseline for participants who eventually had severe ME/CFS. Cytokines
colored red are pro-inflammatory, those colored blue are anti-inflammatory. Cytokines not colored
have multi-purpose functions.
Microorganisms 2025, 13, x FOR PEER REVIEW 5 of 12
Figure 2. Cytokine data at baseline for participants who eventually had severe ME/CFS. Cytokines
colored red are pro-inflammatory, those colored blue are anti-inflammatory. Cytokines not colored
have multi-purpose functions.
Figure 3. Cytokine data at baseline for Controls. Cytokines colored red are pro-inflammatory, those
colored blue are anti-inflammatory. Cytokines not colored have multi-purpose functions.
4. Predicting ME/CFS
We next examined other predictors (i.e., other pre-illness variables as well as varia-
bles present at the onset of IM) of those who developed moderate and severe ME/CFS
following IM. Multiple data points included seven self-report questionnaires, physical ex-
amination findings, the severity of the mononucleosis scale [28], and cytokine analyses.
Two random forest classification analyses were conducted to predict the development of
ME/CFS [18]. Patients with stomach pain, bloating, and symptoms of an irritable bowel at
pre-illness baseline, low levels of IL-13 and/or IL-5 at pre-illness baseline (previously dis-
cussed), and severe gastrointestinal symptoms at the time they contracted mononucleosis
had a nearly 80% chance of developing severe ME/CFS six months following IM.
5. Baseline Metabolic Pathways
Metabolomics has allowed investigators to beer understand which metabolic path-
ways are dysregulated in several different diseases. In our next study, Jason et al. [29]
examined baseline metabolomics levels among those with severe ME/CFS versus controls.
A series of binary logistic regressions were conducted to classify the severe ME/CFS and
recovered groups. Significant differences were observed for the following metabolites: S-
adenosyl-L-methionine (part of one-carbon metabolism and is a methyl donor for epige-
netic regulation), glutathione (part of glutathione metabolism), cysteine (an amino acid
that participates in a variety of pathways, including glutathione metabolism), thiamine
(modified and used as a cofactor in several TCA cycle enzymes), and N-acetyl-alanine
Figure 3. Cytokine data at baseline for Controls. Cytokines colored red are pro-inflammatory, those
colored blue are anti-inflammatory. Cytokines not colored have multi-purpose functions.
4. Predicting ME/CFS
We next examined other predictors (i.e., other pre-illness variables as well as variables
present at the onset of IM) of those who developed moderate and severe ME/CFS following
Microorganisms 2025,13, 702 5 of 11
IM. Multiple data points included seven self-report questionnaires, physical examination
findings, the severity of the mononucleosis scale [
28
], and cytokine analyses. Two random
forest classification analyses were conducted to predict the development of ME/CFS [
18
].
Patients with stomach pain, bloating, and symptoms of an irritable bowel at pre-illness
baseline, low levels of IL-13 and/or IL-5 at pre-illness baseline (previously discussed), and
severe gastrointestinal symptoms at the time they contracted mononucleosis had a nearly
80% chance of developing severe ME/CFS six months following IM.
5. Baseline Metabolic Pathways
Metabolomics has allowed investigators to better understand which metabolic path-
ways are dysregulated in several different diseases. In our next study, Jason et al. [
29
]
examined baseline metabolomics levels among those with severe ME/CFS versus controls.
A series of binary logistic regressions were conducted to classify the severe ME/CFS and
recovered groups. Significant differences were observed for the following metabolites:
S-adenosyl-L-methionine (part of one-carbon metabolism and is a methyl donor for epi-
genetic regulation), glutathione (part of glutathione metabolism), cysteine (an amino acid
that participates in a variety of pathways, including glutathione metabolism), thiamine
(modified and used as a cofactor in several TCA cycle enzymes), and N-acetyl-alanine
(may have a role in protein signaling and post-translational modifications). The models
produced correctly classified those with severe ME/CFS from recovered controls with an
accuracy of 97%, sensitivity of 94%, and specificity of 100%. We thus identified potentially
dysregulated pre-illness pathways that are essential for proliferating cells, particularly dur-
ing a pro-inflammatory immune response, and are thus consistent with the irregularities in
cytokines seen in our prior studies (see Table 1).
Table 1. Significant metabolomic results at baseline (prior to IM) in controls who recovered from IM
vs participants who went on to develop severe ME/CFS 6 months following IM.
S-CFS Controls
KEEG Metabolite M(SD) M(SD) U p
aC00750 spermine 18.79 (0.13) 19.54 (0.16) 0
0.0000000002
cC00354. . .C00665 F-1,6/2,6-DP 14.94 (0.43) 13.90 (0.24) 321
0.0000000015
aC00315 spermidine 19.18 (0.66) 17.84 (0.33) 311
0.0000000822
cC00002. . .C00286 ATP/dGTP 14.57 (1.02) 13.16 (0.54) 301
0.0000012586
bC00169 carbamoyl phosphate 15.67 (0.45) 16.65 (0.12) 23
0.0000012586
aC00127 glutathione disulfide 13.63 (1.00) 11.64 (1.11) 300
0.0000015973
cC00158. . .C00311 citrate/citrate(iso) 22.90 (0.28) 22.40 (0.30) 290
0.0000135233
aC00112 CDP 10.84 (1.29) 8.88 (0.85) 297
0.0000169794
Note:
a
= identity confirmed,
b
= identity not confirmed,
c
= cannot separate. Note: Bonferroni correction
(p< 0.000038).
6. Long COVID
Our studies of ME/CFS following IM began before the onset of the COVID-19 pan-
demic. We are now collecting 7-year follow-up data from our original sample and are also
gathering information regarding whether the students had been infected with SARS-CoV-2
in the interim and whether or not they recovered. We are also studying a new group of
college students who did and did not recover from SARS-CoV-2 and will compare and
contrast the mechanisms of nonrecovery from IM and COVID-19. These participants with
SARS-CoV-2 infection were recruited in 2023–2024 by social media sources and from posters
and recruitment efforts at local universities. Participants recruited were provided a medical
evaluation, and that along with the self-report questionnaires helped determine whether
a person had recovered or not from SARS-CoV-2. Those classified as long COVID had
Microorganisms 2025,13, 702 6 of 11
continuous, relapsing, or remitting symptoms affecting one or more organ symptoms for at
least three months following acute SARS-CoV-2 infection [
30
]. Matching occurred on sex,
race, ethnicity, and age for those with ME/CFS following IM and those with long COVID,
and the controls who recovered from mono and those who recovered from SARS-CoV-2.
7. Discussion
Insights from our prospective study and others can help improve efforts to understand
ME/CFS pathophysiology, early diagnosis, and prognosis. We found that at Stage 1, those
fated to develop ME/CFS 6 months following IM had low levels of IL-5 and IL-13 [
25
].
IL-5 enhances the production of B1 cells which are anti-inflammatory (impaired B1 cells
have been found in multiple sclerosis, systemic lupus erythematosus, and rheumatoid
arthritis), and IL-13 has anti-inflammatory properties. Jason et al. [
26
] also found that
students who failed to recover from IM had more restricted, inflexible cytokine networks
whereas those who recovered had more flexible, less interconnected networks. Network
analysis suggests that IL-5 and IL-13 influence other cytokines at baseline in the participants
who are fated to develop ME/CFS following IM compared to those who recover. Both IL-5
and IL-13 are critical signaling proteins for eosinophil recruitment and production [
31
];
deficiencies in these cytokines before contracting IM may cause the immune system to
lack the breadth or suppleness needed to cope successfully with primary EBV infection.
Thus, the wider range of resources available to those with looser and broader immune
networks may have helped them recover. In addition, the ME/CFS group displayed a
“lack of involvement” in networks that are effective in fighting off EBV, as found by Loebel
et al. [
32
]. To summarize, those who go on to develop post-viral fatigue after IM had the
densest networks of cytokines pre-illness, and it is cytokine networks that are thought to
drive disease processes such as inflammatory bowel disease [33].
A consistent theme in our work has been differentiating patients who have what
we have termed severe ME/CFS from those with moderate ME/CFS. Those with severe
ME/CFS meet more than just the Fukuda criteria, which are less specific than other crite-
ria for diagnosing ME/CFS. Those in the severe group in contrast to controls had saliva
biomarkers of fatigue [
34
], more dense pre-illness interconnected cytokine networks [
26
],
and more gastrointestinal distress and autonomic symptoms within 2 months of their de-
veloping IM, along with several immune [
18
], and metabolomic pre-illness biomarkers [
29
].
We have found many benefits of using multiple methods in assessing our participants.
We provided our participants with comprehensive physician exams to assess for multiple
orthostatic indicators (pulse, blood pressure, syncope); testing of plasma cytokines, lym-
phocyte counts, natural killer cell counts and activity, and T-cell subsets; autoantibodies;
metabolomic analysis; and saliva. We also developed the severity of the Mononucleosis
Scale to assess the severity of IM. In addition, we collected family history of ME/CFS and
other diseases and validated self-report ratings to measure fatigue, symptoms, limitations,
and psychological variables. We benefited from working with a multidisciplinary team
of investigators, including those from infectious disease medicine, clinical psychology,
computer science, immunology, metabolomics, and neurology. We also employed multiple
types of statistics including network analysis, data mining, machine learning, logistic
regression, and receiver operating characteristic curves.
In working with ME/CFS, we also documented the presence of ME/CFS by using
validated questionnaires such as the DePaul Symptom Questionnaire (DSQ), conducted
medical and psychological examinations, and excluded other diagnoses such as anemia,
hypothyroidism, and depression. We have learned it is important to use methods that can
rely on more than just asking patients whether or not they have ME/CFS or long COVID.
In adult and pediatric community-based studies, 90 to 95% of participants are not even
Microorganisms 2025,13, 702 7 of 11
aware they have ME/CFS [
35
,
36
]. In a study with a sample of 465 individuals with long
COVID, of respondents who reported that they had ME/CFS, 29% did not meet the criteria
for ME/CFS [
37
]. Relying purely on self-reporting of ME/CFS and long COVID status can
result in over-diagnosis and under-diagnosis.
Because fatigue affects about 25% of the population, we have found it is inadequate to
merely assess whether a patient has experienced the occurrence (yes versus no) of fatigue or
other common somatic symptoms. These types of measures will not differentiate ME/CFS
from psychiatric conditions such as Major Depressive Disorder [
38
]. Thus, we also measure
the frequency and severity of each symptom, using the DePaul Symptom Questionnaire, to
better differentiate cases of ME/CFS from controls [39].
There is a clear need to better understand similarities and differences between varieties
of post-viral illnesses, such as long COVID and ME/CFS following IM. For example, in
one study using the DePaul Symptom Questionnaire, those with long COVID had similar
symptom scores to patients with ME/CFS [
40
]. A year later, five symptoms improved
significantly for those patients with long COVID including fatigue, post-exertional malaise,
brain fog, irritable bowel symptoms, and feeling unsteady. In contrast, there were no
significant symptom improvements for the patients with ME/CFS a year later. Using
another data set with the DePaul Symptom Questionnaire, McGarrigle et al. [
41
] examined
differences between those with ME/CFS and long COVID and found that “Cold limbs” and
“Flu-like symptoms” were significantly more likely to occur in the ME/CFS group. Finally,
in another study using the DePaul Symptom Questionnaire, Hua et al. [
42
] built predictive
models based on a random forest algorithm analysis using the participants’ symptoms
from the initial weeks of COVID-19 infection to predict if the participants would go on to
later meet the criteria for ME/CFS. Early symptoms, particularly those of post-exertional
malaise, predicted the development of ME/CFS with an accuracy of 95%.
There are probably similarities in pathophysiology between ME/CFS due to IM
and long COVID. After EVB infection, Müller-Durovic et al. [
43
] found the viral protein,
EBV-encoded transactivator EBNA2, in cooperation with the host B cell transcription
factor EBFI, drove induction of indoleamine 2,3-dioxygenase 1 (IDO1), the first and rate-
limiting enzyme of the kynurenine pathway. This same pathway may be involved in the
development of long COVID as well [
44
]. Following acute COVID-19 infection, some
patients experience a strong inflammatory response, with increased levels of interferon-y
(IFN-y), interferon-p (IFN-P), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-a).
These cytokines activate the enzyme IDO1, causing the first step of tryptophan breakdown
through the kynurenine pathway, leading to the production of several neurotoxic and
immunosuppressive metabolites, which might be responsible for some of the symptoms of
post-viral illnesses such as brain fog. Ruffieux et al. [
45
] studied individuals infected with
SARS-CoV-2 a year after disease onset. They found that patients had a metabolic signature
characterized by increased expression of intermediates from the kynurenine pathway and
depletion of the upstream amino acid tryptophan. The authors suggest that abnormal levels
of kynurenine-pathway intermediates, coupled with the significant reduction in serotonin,
contribute to fatigue, weakness, and chronic pain of long COVID.
Since the start of the SARS-CoV-2 pandemic, most research funding has been directed
at long COVID rather than ME/CFS. This might be due to scientists and government
funders perceiving long COVID to have a clear, specific trigger whereas ME/CFS does
not. However, SARS-CoV-2 has continually evolved, resulting in the emergence of several
lineages and variants of concern. Long COVID samples often include different variants
(e.g., Alpha, Beta, Gamma, Delta, Omicron) that have different transmission, severity,
and immune-evasion properties. The majority of patients with ME/CFS report infectious
illnesses before the onset of ME/CFS, with 30% of cases of ME/CFS due to preceding
Microorganisms 2025,13, 702 8 of 11
infectious mononucleosis caused by the Epstein–Barr virus (EBV) [
46
]. Therefore, it is
possible to study ME/CFS caused by a single virus, EBV.
A better understanding of the etiology and biomarkers for ME/CFS might lead to
treatments. Regrettably, there are no FDA-approved ME/CFS treatments. Consequently,
healthcare professionals have prioritized the management of ME/CFS symptoms such as
fatigue through energy conservation activities [
47
], the control of postural tachycardia syn-
drome [
48
–
50
], and the management of pain [
51
], sleep disorders [
52
], and gastrointestinal
dysbiosis [
53
]. Inflammation, immune dysfunction, neuroinflammation, and mitochon-
drial dysfunction may play a role in the etiology of post-viral fatigue (e.g., ME/CFS and
long COVID) [
54
], with subsequent developments of therapeutics. Since the majority of
these studies have not been replicated and the majority of the tested drugs have not been
subjected to large, well-designed, randomized, placebo-controlled trials, it is currently
not possible to evaluate the evidence of efficacy. Regrettably, most patients with ME/CFS
report they benefited relatively little from most interventions offered to them, and many
report that the interventions negatively affected their health [
55
], and as a consequence,
patients report low satisfaction with the medical care they received [56]).
The current study only reports on a few of the current investigations that will occur
with this prospective study. Certainly, there are multiple other areas that can be further
investigated with this data set involving cognitive, genetic, and sex-related factors. For
example, Pipper et al. [
57
] recently found that females with ME/CFS had higher levels
of 11-deoxycortisol, 17
α
-hydroxyprogesterone, and progesterone levels versus controls,
whereas males with ME/CFS had lower circulating levels of cortisol and corticosterone,
and higher progesterone levels, than controls. These types of analyses could be investigated
with the current data set.
A limitation of the findings in this article is that there are several case definitions of
ME/CFS as well as long COVID, and this will make it more difficult to study comparable
samples across different laboratories. While follow-up data is being collected on patients
with ME/CFS, there is also a need to investigate the longer-term consequences of infection
with SARS-CoV-2. In addition, our review focused on a prospective study of IM, but there
are many other viral infections such as Dengue, West Nile, Chikungunya, etc. The research
community would benefit from research on these typeillnesses.
Case definitions are crucial for science, and even more critical for diseases like ME/CFS
and long COVID that lack a consistent biomarker. There is a clear benefit for a more
uniform case definition because, currently, physicians often make a diagnosis on a case-
by-case basis with a mix of definitions and their judgment. However, there are potential
negative consequences of overly broad criteria. For example, the National Academies of
Sciences, Engineering, and Medicine have recently proposed a new case definition for
long COVID [
30
]. The criteria specify that the condition “is present for at least 3 months
as a continuous, relapsing and remitting, or progressive disease state” and the condition
can be defined by “single or multiple symptoms” that “can range from mild to severe.”
However, a person can meet these proposed long COVID criteria by merely having one
symptom that is not a burden to the person or does not have any negative impact on
the person’s functioning. If a person has trivial pain in the toe for 3 months following
COVID-19 infection, with no negative consequences to the person’s functioning or quality
of life, that person would still be eligible for a long COVID diagnosis. The failure to list any
thresholds of frequency or severity of symptoms, so that the symptoms are not trivial, has
major consequences for an infection that is as widespread as COVID.
The behavioral and pathophysiological underpinnings of both ME/CFS following
IM and long COVID are still poorly understood [
58
]. Prospective longitudinal studies
can help in the understanding of post-infection illness following the onset of EBV and
Microorganisms 2025,13, 702 9 of 11
SARS-CoV-2. Our ongoing prospective longitudinal study of ME/CFS following IM will
hopefully continue to uncover immunologic or metabolomic commonalities and differences
between ME/CFS and long COVID.
Funding: Funding was provided by the National Institute of Allergy and Infectious Diseases (grant
number AI105781) and the National Institute of Neurological Disorders and Stroke (grant number
R01NS111105).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Informed consent was obtained from all participants.
Data Availability Statement: No new data were created or analyzed in this study. Data sharing is
not applicable to this article.
Conflicts of Interest: The authors declare no conflict of interest.
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