Category: Biomarker

Proteomics and cytokine analyses distinguish myalgic encephalomyelitis/chronic fatigue syndrome cases from controls

Abstract:

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, heterogenous disease characterized by unexplained persistent fatigue and other features including cognitive impairment, myalgias, post-exertional malaise, and immune system dysfunction. Cytokines are present in plasma and encapsulated in extracellular vesicles (EVs), but there have been only a few reports of EV characteristics and cargo in ME/CFS. Several small studies have previously described plasma proteins or protein pathways that are associated with ME/CFS.

Methods: We prepared extracellular vesicles (EVs) from frozen plasma samples from a cohort of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) cases and controls with prior published plasma cytokine and plasma proteomics data. The cytokine content of the plasma-derived extracellular vesicles was determined by a multiplex assay and differences between patients and controls were assessed. We then performed multi-omic statistical analyses that considered not only this new data, but extensive clinical data describing the health of the subjects.

Results: ME/CFS cases exhibited greater size and concentration of EVs in plasma. Assays of cytokine content in EVs revealed IL2 was significantly higher in cases. We observed numerous correlations among EV cytokines, among plasma cytokines, and among plasma proteins from mass spectrometry proteomics. Significant correlations between clinical data and protein levels suggest roles of particular proteins and pathways in the disease. For example, higher levels of the pro-inflammatory cytokines Granulocyte-Monocyte Colony-Stimulating Factor (CSF2) and Tumor Necrosis Factor (TNFα) were correlated with greater physical and fatigue symptoms in ME/CFS cases. Higher serine protease SERPINA5, which is involved in hemostasis, was correlated with higher SF-36 general health scores in ME/CFS. Machine learning classifiers were able to identify a list of 20 proteins that could discriminate between cases and controls, with XGBoost providing the best classification with 86.1% accuracy and a cross-validated AUROC value of 0.947. Random Forest distinguished cases from controls with 79.1% accuracy and an AUROC value of 0.891 using only 7 proteins.

Conclusions: These findings add to the substantial number of objective differences in biomolecules that have been identified in individuals with ME/CFS. The observed correlations of proteins important in immune responses and hemostasis with clinical data further implicates a disturbance of these functions in ME/CFS.

Source: Giloteaux L, Li J, Hornig M, Lipkin WI, Ruppert D, Hanson MR. Proteomics and cytokine analyses distinguish myalgic encephalomyelitis/chronic fatigue syndrome cases from controls. J Transl Med. 2023 May 13;21(1):322. doi: 10.1186/s12967-023-04179-3. PMID: 37179299. https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-023-04179-3 (Full text)

Serum GDF-15 Levels Accurately Differentiate Patients with Primary Mitochondrial Myopathy, Manifesting with Exercise Intolerance and Fatigue, from Patients with Chronic Fatigue Syndrome

Abstract:

Primary mitochondrial myopathies (PMM) are a clinically and genetically highly heterogeneous group that, in some cases, may manifest exclusively as fatigue and exercise intolerance, with minimal or no signs on examination. On these occasions, the symptoms can be confused with the much more common chronic fatigue syndrome (CFS).
Nonetheless, other possibilities must be excluded for the final diagnosis of CFS, with PMM being one of the primary differential diagnoses. For this reason, many patients with CFS undergo extensive studies, including extensive genetic testing and muscle biopsies, to rule out this possibility.
This study evaluated the diagnostic performance of growth differentiation factor-15 (GDF-15) as a potential biomarker to distinguish which patient with chronic fatigue has a mitochondrial disorder. We studied 34 adult patients with symptoms of fatigue and exercise intolerance with a definitive diagnosis of PMM (7), CFS (22), or other non-mitochondrial disorders (5).
The results indicate that GDF-15 can accurately discriminate between patients with PMM and CFS (AUC = 0.95) and between PMM and patients with fatigue due to other non-mitochondrial disorders (AUC = 0.94). Therefore, GDF-15 emerges as a promising biomarker to select which patients with fatigue should undergo further studies to exclude mitochondrial disease.
Source: Bermejo-Guerrero L, de Fuenmayor-Fernández de la Hoz CP, Guerrero-Molina MP, Martín-Jiménez P, Blázquez A, Serrano-Lorenzo P, Lora D, Morales-Conejo M, González-Martínez I, López-Jiménez EA, Martín MA, Domínguez-González C. Serum GDF-15 Levels Accurately Differentiate Patients with Primary Mitochondrial Myopathy, Manifesting with Exercise Intolerance and Fatigue, from Patients with Chronic Fatigue Syndrome. Journal of Clinical Medicine. 2023; 12(6):2435. https://doi.org/10.3390/jcm12062435 (Full text)

Heart Rate Variability and Salivary Biomarkers Differences between Fibromyalgia and Healthy Participants after an Exercise Fatigue Protocol: An Experimental Study

Abstract:

Previous studies showed that people with Fibromyalgia (FM) suffer from dysautonomia. Dysautonomia consists of persistent autonomic nervous system hyperactivity at rest and hyporeactivity during stressful situations. There is evidence that parameters reflecting the complex interplay between the autonomic nervous system and the cardiovascular system during exercise can provide significant prognostic information. Therefore, this study aimed to investigate the differences between people with FM and healthy controls on heart rate variability (HRV) and salivary parameters (such as flow, protein concentration, enzymatic activities of amylase, catalase and glutathione peroxidase) in two moments: (1) at baseline, and (2) after an exercise fatigue protocol.

A total of 37 participants, twenty-one were people with fibromyalgia and sixteen were healthy controls, participated in this cross-sectional study. HRV and salivary samples were collected before and after an exercise fatigue protocol. The fatigue protocol consisted of 20 repetitions of knee extensions and flexions of the dominant leg at 180 °·s-1 (degrees per second).

Significant differences were found in the HRV (stress index, LF and HF variables) and salivary biomarkers (with a higher concentration of salivary amylase in people with FM compared to healthy controls). Exercise acute effects on HRV showed that people with FM did not significantly react to exercise. However, significant differences between baseline and post-exercise on HRV significantly induce alteration on the HRV of healthy controls. Catalase significantly increased after exercise in healthy controls whereas salivary flow significantly increased in women with FM after an exercise fatigue protocol.

Our study suggests that a higher α-amylase activity and an impaired HRV can be used as possible biomarkers of fibromyalgia, associated with a reduction in salivary flow without changes in HRV and catalase activity after a fatigue exercise protocol. More studies should be carried out in the future to evaluate this hypothesis, in order to find diagnostic biomarkers in fibromyalgia.

Source: Costa AR, Freire A, Parraca JA, Silva V, Tomas-Carus P, Villafaina S. Heart Rate Variability and Salivary Biomarkers Differences between Fibromyalgia and Healthy Participants after an Exercise Fatigue Protocol: An Experimental Study. Diagnostics (Basel). 2022 Sep 14;12(9):2220. doi: 10.3390/diagnostics12092220. PMID: 36140620; PMCID: PMC9497903. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497903/ (Full text)

Urine Metabolomics Exposes Anomalous Recovery after Maximal Exertion in Female ME/CFS Patients

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease with unknown etiology or effective treatments. Post-exertional malaise (PEM) is a key symptom that distinguishes ME/CFS patients. Investigating changes in the urine metabolome between ME/CFS patients and healthy subjects following exertion may help us understand PEM.
The aim of this pilot study was to comprehensively characterize the urine metabolomes of eight female healthy sedentary control subjects and ten female ME/CFS patients in response to a maximal cardiopulmonary exercise test (CPET). Each subject provided urine samples at baseline and 24 h post-exercise. A total of 1403 metabolites were detected via LC-MS/MS by Metabolon® including amino acids, carbohydrates, lipids, nucleotides, cofactors and vitamins, xenobiotics, and unknown compounds.
Using a linear mixed effects model, pathway enrichment analysis, topology analysis, and correlations between urine and plasma metabolite levels, significant differences were discovered between controls and ME/CFS patients in many lipid (steroids, acyl carnitines and acyl glycines) and amino acid subpathways (cysteine, methionine, SAM, and taurine; leucine, isoleucine, and valine; polyamine; tryptophan; and urea cycle, arginine and proline).
Our most unanticipated discovery is the lack of changes in the urine metabolome of ME/CFS patients during recovery while significant changes are induced in controls after CPET, potentially demonstrating the lack of adaptation to a severe stress in ME/CFS patients.
Source: Glass KA, Germain A, Huang YV, Hanson MR. Urine Metabolomics Exposes Anomalous Recovery after Maximal Exertion in Female ME/CFS Patients. International Journal of Molecular Sciences. 2023; 24(4):3685. https://doi.org/10.3390/ijms24043685 https://www.mdpi.com/1422-0067/24/4/3685 (Full text available as PDF file)

Multi-‘omics of gut microbiome-host interactions in short- and long-term myalgic encephalomyelitis/chronic fatigue syndrome patients

Highlights

  • Multi-‘omics identified phenotypic, gut microbial, and metabolic biomarkers for ME/CFS.
  • Reduced gut microbial diversity and increased plasma sphingomyelins in ME/CFS.
  • Short-term patients had more severe gut microbial dysbiosis with decreased butyrate.
  • Long-term patients had more significant metabolic and clinical aberrations

Summary

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, debilitating disorder manifesting as severe fatigue and post-exertional malaise. The etiology of ME/CFS remains elusive.

Here, we present a deep metagenomic analysis of stool combined with plasma metabolomics and clinical phenotyping of two ME/CFS cohorts with short-term (<4 years, n = 75) or long-term disease (>10 years, n = 79) compared with healthy controls (n = 79).

First, we describe microbial and metabolomic dysbiosis in ME/CFS patients. Short-term patients showed significant microbial dysbiosis, while long-term patients had largely resolved microbial dysbiosis but had metabolic and clinical aberrations.

Second, we identified phenotypic, microbial, and metabolic biomarkers specific to patient cohorts. These revealed potential functional mechanisms underlying disease onset and duration, including reduced microbial butyrate biosynthesis and a reduction in plasma butyrate, bile acids, and benzoate.

In addition to the insights derived, our data represent an important resource to facilitate mechanistic hypotheses of host-microbiome interactions in ME/CFS.

Source: Ruoyun Xiong, Courtney Gunter, Elizabeth Fleming, Suzanne D. Vernon, Lucinda Bateman, Derya Unutmaz, Julia Oh. Multi-‘omics of gut microbiome-host interactions in short- and long-term myalgic encephalomyelitis/chronic fatigue syndrome patients. Cell Host & Microbe 31, 273–287. https://www.cell.com/cell-host-microbe/fulltext/S1931-3128(23)00021-5 (Full text)

Studies find that microbiome changes may be a signature for ME/CFS

Researchers have found differences in the gut microbiomes of people with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) compared to healthy controls. Findings from two studies, published in Cell Host & Microbe and funded by the National Institutes of Health add to growing evidence that connects disruptions in the gut microbiome, the complete collection of bacteria, viruses, and fungi that live in our gastrointestinal system, to ME/CFS.

“The microbiome has emerged as a potential contributor to ME/CFS. These findings provide unique insights into the role the microbiome plays in the disease and suggest that certain differences in gut microbes could serve as biomarkers for ME/CFS,” said Vicky Whittemore, Ph.D., program director at NIH’s National Institute of Neurological Disorders and Stroke (NINDS).

ME/CFS is a serious, chronic, and debilitating disease characterized by a range of symptoms, including fatigue, post-exertional malaise, sleep disturbance, cognitive difficulties, pain, and gastrointestinal issues. The causes of the disease are unknown and there are no treatments.

In one study, senior author Brent L. Williams, Ph.D., assistant professor, W. Ian Lipkin, M.D., John Snow Professor of Epidemiology and director of the Center for Infection and Immunity at the Columbia University Mailman School of Public Health, in New York City, and their collaborators analyzed the genetic makeup of gut bacteria in fecal samples collected from a geographically diverse cohort of 106 people with ME/CFS and 91 healthy controls. The results revealed key differences in microbiome diversity, quantity, metabolic pathways, and interactions between species of gut bacteria.

Dr. Williams and his colleagues found that people with ME/CFS had abnormally low levels of several bacterial species compared to healthy controls, including Faecalibacterium prausnitzii (F. prausnitzii) and Eubacterium rectale. These health-promoting bacteria produce a short chain fatty acid called butyrate, a bacterial metabolite, or by-product, that plays an important role in maintaining gut health. An acetate-producing bacterium was also reduced in samples obtained from people with ME/CFS.

More detailed metabolomic analyses confirmed that a reduction in these bacteria was associated with reduced butyrate production in ME/CFS. Butyrate is the primary energy source for cells that line the gut, providing up to 70% of their energy requirements, support for the gut immune system, and protection against diseases of the digestive tract. Butyrate, tryptophan, and other metabolites detected in the blood are important for regulating immune, metabolic, and endocrine functions.

While species of butyrate-producing bacteria decreased, there were increased levels of nine other species in ME/CFS, including Enterocloster bolteae and Ruminococcus gnavus, which are associated with autoimmune diseases and inflammatory bowel disease, respectively.

Dr. Williams’ group also reported that an abundance of F. prausnitzii was inversely associated with fatigue severity in ME/CFS, suggesting a possible link between gut bacteria and disease symptoms. More research is needed to determine if differences in the gut microbiome are a consequence or cause of symptoms.

The findings indicate that imbalances in these 12 species of bacteria could be used as biomarkers for ME/CFS classification, potentially providing consistent, measurable targets to improve diagnosis.

The gut microbiome is an ecosystem with complex interactions between bacteria, where microbes can exchange or compete for nutrients, metabolites, or other molecular signals. Researchers found notable differences in the network of species interactions in people with ME/CFS—including unique interactions between F. prausnitzii and other species. This indicates that there is an extensive rewiring of bacterial networks in ME/CFS.

“In addition to differences in individual species in ME/CFS, focusing a lens on community interaction dynamics may add greater specificity to the broad definition of dysbiosis, distinguishing between other diseases in which the gut microbiome becomes imbalanced,” said Dr. Williams. “This is also important for generating new testable hypotheses about the underlying mechanisms and mediators of dysbiosis in ME/CFS and may eventually inform strategies to correct these imbalances.”

A balanced microbiome is also essential for a variety of neural systems, especially immune regulation and coupling between energy metabolism and blood supply in the brain, as well as the function of the nerves that supply the gut.

In another study at the Jackson Laboratory in Farmington, Connecticut, Julia Oh, Ph.D.(link is external), associate professor, and Derya Unutmaz, M.D., professor, teamed up with other ME/CFS experts to study microbiome abnormalities in different phases of ME/CFS. Dr. Oh’s team collected and analyzed clinical data, fecal samples, and blood samples from 149 people with ME/CFS who had been diagnosed within the previous four years (74 short-term) or who had been diagnosed more than 10 years ago (75 long-term) and 79 healthy controls.

The results showed that the short-term group had less microbial diversity, while the long-term group established a stable, but individualized gut microbiome similar to healthy controls. Dr. Oh and her colleagues found lower levels of several butyrate-producing species, including F. prausnitzii, especially in the short-term participants. There was also a reduction in species associated with tryptophan metabolism in all ME/CFS participants compared to controls.

Dr. Oh’s group also collected detailed clinical and lifestyle data from participants. By combining these data with genetic and metabolome data, the team developed a way to accurately classify and differentiate ME/CFS from healthy controls. Using this approach, they found that individuals with long-term ME/CFS had a more balanced microbiome but showed more severe clinical symptoms and progressive metabolic irregularities compared to the other groups.

Both studies identify potential biomarkers for ME/CFS, which may inform diagnostic tests and disease classification. Understanding the connection between disturbances in the gut microbiome and ME/CFS may also guide the development of new therapeutics.

Additional research is required to learn more about the pathophysiological implications of butyrate and other metabolite deficiencies in ME/CFS. Future studies will determine how gut microbe disturbances contribute to symptoms, including changes during disease progression.

The studies were funded in part by the NIH’s ME/CFS Collaborative Research Network(link is external), a consortium supported by multiple institutes and centers at NIH, consisting of three collaborative research centers and a data management coordinating center. The research network was established in 2017 to help advance research on ME/CFS. The research was supported by NINDS grant U54NS105539, National Institute of Allergy and Infectious Diseases grants U54AI138370 and R56AI120724, and anonymous donors through the Crowdfunding Microbe Discovery Project.

Circulating microRNA expression signatures accurately discriminate myalgic encephalomyelitis from fibromyalgia and comorbid conditions

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), and fibromyalgia (FM) are two chronic complex diseases with overlapping symptoms affecting multiple systems and organs over time. Due to the absence of validated biomarkers and similarity in symptoms, both disorders are misdiagnosed, and the comorbidity of the two is often unrecognized.

Our study aimed to investigate the expression profiles of 11 circulating miRNAs previously associated with ME/CFS pathogenesis in FM patients and individuals with a comorbid diagnosis of FM associated with ME/CFS (ME/CFS + FM), and matched sedentary healthy controls. Whether these 11 circulating miRNAs expression can differentiate between the two disorders was also examined.

Our results highlight differential circulating miRNAs expression signatures between ME/CFS, FM and ME/CFS + FM, which also correlate to symptom severity between ME/CFS and ME/CFS + FM groups. We provided a prediction model, by using a machine-learning approach based on 11 circulating miRNAs levels, which can be used to discriminate between patients suffering from ME/CFS, FM and ME/CFS + FM. These 11 miRNAs are proposed as potential biomarkers for discriminating ME/CFS from FM.

The results of this study demonstrate that ME/CFS and FM are two distinct illnesses, and we highlight the comorbidity between the two conditions. Proper diagnosis of patients suffering from ME/CFS, FM or ME/CFS + FM is crucial to elucidate the pathophysiology of both diseases, determine preventive measures, and establish more effective treatments.

Source: Nepotchatykh E, Caraus I, Elremaly W, Leveau C, Elbakry M, Godbout C, Rostami-Afshari B, Petre D, Khatami N, Franco A, Moreau A. Circulating microRNA expression signatures accurately discriminate myalgic encephalomyelitis from fibromyalgia and comorbid conditions. Sci Rep. 2023 Feb 2;13(1):1896. doi: 10.1038/s41598-023-28955-9. PMID: 36732593. https://www.nature.com/articles/s41598-023-28955-9 (Full text)

The Role of Leptin and Inflammatory Related Biomarkers in Individuals with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Purpose: Leptin is a member of the cytokine family; its receptor (LEPR-b) is the longest form receptor expressed in cells of the immune system; wherein LEPR-b deficiency causes a decrease in CD4+ cells. LEPR-b is located in hypothalamic and brain stem nuclei, and it primarily regulates energy status. As well, leptin indirectly regulates widespread pain and exercise tolerance by decreasing circulating cortisol.

Hyperinsulinemia increases leptin production in adipocytes on a diurnal rhythm; however, the precise relationship between insulin, leptin and pro-inflammatory markers remains uncertain. In clinical settings, high-sensitivity C-reactive protein (hsCRP) has been widely used, as an inflammatory predictor for leptin-related cardiometabolic outcomes and chronic inflammatory symptoms.

Leptin-related metabolic and inflammation dysregulations have been clinically reported in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), but not fully elucidated. We examined the association of plasma insulin, leptin, and hsCRP levels with ME/CFS self-reported symptom severity.

Methods: Prospective analyses were conducted on ME/CFS patients who met Fukuda/CDC criteria at Birmingham hospital, Alabama, U.S.A. The independent variables were hyperinsulinemia (>174 μIU/mL), hyperleptinemia/hypoleptinemia (>18.3/<3.3 ng/mL), residual inflammation risk (hsCRP ≥2 and ≠26.2 mg/L) and within-individual-variability (WIV) for each biomarker.

WIV was defined for each individual as standard deviation/sample residuals adjusting for time and calculated from once-daily random plasma samples over 10–12 weeks.

The primary outcomes were:

(1) ME/CFS symptom score trends [generalized pain, persistent fatigue, sleep disturbance, impairment of concentration and memory (brain fog), and post-exertional malaise (PEM)] calculated from the MFI-20 questionnaire with anchors from 0 to 100 and recorded once daily over a matching 12–14 weeks, and

(2) dichotomized symptom severity, with severe symptoms defined as scores > 60/100. After adjusting for age and time, we reported: (1) standard errors (SEM) and p-values for symptom trends using multivariable mixed-effect linear regression models, and (2) odds ratios for severe symptoms using multivariable alternating logistic regression models.

Results: We included 29 ME/CFS patients. All were females and >18 years old. Hyperinsulinemia, hyperleptinemia/hypoleptinemia, and residual inflammation risk were 7%, 80%/7%, and 74%, respectively.

The medians of insulin-WIV, leptin-WIV and hsCRP-WIV were [(0.24; IQR 0.15–0.38), (0.25; IQR 0.15–0.40), (0.33; IQR 0.18–0.51)] respectively. On average, hyperleptinemic patients had the highest leptin-WIV and 50% of them had residual inflammation risk.

Severe (fatigue, pain, brain fog, sleep disturbance, and PEM) were reported in 50%, 29%, 41%, 30%, and 57% of patients, respectively. In the adjusted analysis, worse fatigue scores (7.49; SEM, 2.23; p = 0.002) were associated with higher insulin-WIV.

Hyperleptinemia (OR 1.54; 95% CI 1.13–2.09) compared to hypoleptinemia, and residual inflammation risk (OR 1.65; 95% CI 1.21–2.25) were associated with higher odds of severe fatigue. Worse pain scores (7.17; SEM, 2.30; p = 0.005) were associated with higher leptin-WIV, and (8.45; SEM, 2.25; p = 0.0009) higher hsCRP-WIV, and residual inflammation risk (OR 1.75; 95% CI 1.34–2.29) was associated with higher odds of severe pain.

Severe brain fog scores (9.20; SEM, 2.44; p = 0.0008) were associated with higher insulin-WIV, higher leptin-WIV (4.73; SEM, 2.12; p = 0.03). Residual inflammation risk (OR 1.40; 95% CI 1.16–1.77) was associated with higher odds of severe brain fog.

Hyperleptinemia (OR 0.60; 95% CI 0.43–1.19) was associated with lower odds of severe PEM compared to hypoleptinemia, and better sleep quality was associated (6.07; SEM, 1.70; p = 0.001) with higher insulin-WIV, and (3.37; SEM, 1.47; p = 0.03) higher leptin-WIV.

Conclusions: In patients with ME/CFS, symptoms severity was associated with hyperleptinemia, inflammation and within-individual-variability of these biomarkers. Leptin and hsCRP may be clinically useful in predicting symptom severity.

Larger clinical trials are needed to further examine the prediction and causality of these biomarkers in the development of ME/CFS diagnosis. The efficacy and safety of anti-inflammatory therapies may be evaluated in sub-clusters of ME/CFS with metabolic responses and inflammation dysregulations to improve patient-reported symptoms.

Source: Rahaf Al Assil and Jarred W Younger. “The Role of Leptin and Inflammatory Related Biomarkers in Individuals with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome” in Karandrea S, Agarwal N, Organizing Committee of Cardiometabolic Health Congress. Report from the Scientific Poster Session at the 16th Annual Cardiometabolic Health Congress in National Harbor, USA, 14–17 October 2021. Proceedings. 2022; 80(1):6. https://doi.org/10.3390/proceedings2022080006 (Full text)

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: The Human Herpesviruses Are Back!

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) or Systemic Exertion Intolerance Disease (SEID) is a chronic multisystem illness of unconfirmed etiology. There are currently no biomarkers and/or signatures available to assist in the diagnosis of the syndrome and while numerous mechanisms have been hypothesized to explain the pathology of ME/CFS, the triggers and/or drivers remain unknown.

Initial studies suggested a potential role of the human herpesviruses especially Epstein-Barr virus (EBV) in the disease process but inconsistent and conflicting data led to the erroneous suggestion that these viruses had no role in the syndrome. New studies using more advanced approaches have now demonstrated that specific proteins encoded by EBV could contribute to the immune and neurological abnormalities exhibited by a subgroup of patients with ME/CFS. Elucidating the role of these herpesvirus proteins in ME/CFS may lead to the identification of specific biomarkers and the development of novel therapeutics.

Source: Ariza ME. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: The Human Herpesviruses Are Back! Biomolecules. 2021 Jan 29;11(2):185. doi: 10.3390/biom11020185. PMID: 33572802; PMCID: PMC7912523. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7912523/ (Full text)

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and fibromyalgia are indistinguishable by their cerebrospinal fluid proteomes

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and fibromyalgia have overlapping neurologic symptoms particularly disabling fatigue. This has given rise to the question whether they are distinct central nervous system (CNS) entities or is one an extension of the other. To investigate this, we used unbiased quantitative mass spectrometry-based proteomics to examine the most proximal fluid to the brain, cerebrospinal fluid (CSF). This was to ascertain if the proteome profile of one was the same or different from the other.

We examined two separate groups of ME/CFS, one with (n=15) and one without (n=15) fibromyalgia. We quantified a total of 2,083 proteins using immunoaffinity depletion, tandem mass tag isobaric labeling and offline two-dimensional liquid chromatography coupled to tandem mass spectrometry, including 1,789 that were quantified in all the CSF samples. ANOVA analysis did not yield any proteins with an adjusted p-value < 0.05. This supports the notion that ME/CFS and fibromyalgia as currently defined are not distinct entities.

Source: Steven E. Schutzer, Tao Liu, Chia-Feng Tsai, Vladislav A. Petyuk, Athena A. Schepmoes, Yi-Ting Wang, Karl K. Weitz, Jonas Bergquist, Richard D. Smith, Benjamin H Natelson. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and fibromyalgia are indistinguishable by their cerebrospinal fluid proteomes. bioRxiv 2022.09.14.506792; doi: https://doi.org/10.1101/2022.09.14.506792 https://www.biorxiv.org/content/10.1101/2022.09.14.506792v2.full (Full text)