A map of metabolic phenotypes in patients with myalgic encephalomyelitis/chronic fatigue syndrome

Dysregulation of the Kynurenine Pathway, Cytokine Expression Pattern, and Proteomics Profile Link to Symptomology in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Dysregulation of the kynurenine pathway (KP) is believed to play a significant role in neurodegenerative and cognitive disorders. While some evidence links the KP to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), further studies are needed to clarify the overall picture of how inflammation-driven KP disturbances may contribute to symptomology in ME/CFS. Here, we report that plasma levels of most bioactive KP metabolites differed significantly between ME/CFS patients and healthy controls in a manner consistent with their known contribution to symptomology in other neurological disorders. Importantly, we found that enhanced production of the first KP metabolite, kynurenine (KYN), correlated with symptom severity, highlighting the relationship between inflammation, KP dysregulation, and ME/CFS symptomology. Other significant changes in the KP included lower levels of the downstream KP metabolites 3-HK, 3-HAA, QUIN, and PIC that could negatively impact cellular energetics. We also rationalized KP dysregulation to changes in the expression of inflammatory cytokines and, for the first time, assessed levels of the iron (Fe)-regulating hormone hepcidin that is also inflammation-responsive. Levels of hepcidin in ME/CFS decreased nearly by half, which might reflect systemic low Fe levels or possibly ongoing hypoxia. We next performed a proteomics screen to survey for other significant differences in protein expression in ME/CFS. Interestingly, out of the seven most significantly modulated proteins in ME/CFS patient plasma, 5 proteins have roles in maintaining gut health, which considering the new appreciation of how gut microbiome and health modulates systemic KP could highlight a new explanation of symptomology in ME/CFS patients and potential new prognostic biomarker/s and/or treatment avenues.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: the biology of a neglected disease

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic, debilitating disease characterised by a wide range of symptoms that severely impact all aspects of life. Despite its significant prevalence, ME/CFS remains one of the most understudied and misunderstood conditions in modern medicine. ME/CFS lacks standardised diagnostic criteria owing to variations in both inclusion and exclusion criteria across different diagnostic guidelines, and furthermore, there are currently no effective treatments available. Moving beyond the traditional fragmented perspectives that have limited our understanding and management of the disease, our analysis of current information on ME/CFS represents a significant paradigm shift by synthesising the disease's multifactorial origins into a cohesive model. We discuss how ME/CFS emerges from an intricate web of genetic vulnerabilities and environmental triggers, notably viral infections, leading to a complex series of pathological responses including immune dysregulation, chronic inflammation, gut dysbiosis, and metabolic disturbances. This comprehensive model not only advances our understanding of ME/CFS's pathophysiology but also opens new avenues for research and potential therapeutic strategies. By integrating these disparate elements, our work emphasises the necessity of a holistic approach to diagnosing, researching, and treating ME/CFS, urging the scientific community to reconsider the disease's complexity and the multifaceted approach required for its study and management.

Chronic Overlapping Pain Conditions and Nociplastic Pain

Chronic Overlapping Pain Conditions (COPCs) are a subset of chronic pain conditions commonly comorbid with one another and more prevalent in women and assigned female at birth (AFAB) individuals. Pain experience in these conditions may better fit with a new mechanistic pain descriptor, nociplastic pain, and nociplastic type pain may represent a shared underlying factor among COPCs. We applied GenomicSEM common-factor genome wide association study (GWAS) and multivariate transcriptome-wide association (TWAS) analyses to existing GWAS output for six COPCs in order to find genetic variation associated with nociplastic type pain, followed by genetic correlation (linkage-disequilibrium score regression), gene-set and tissue enrichment analyses. We found 24 independent single nucleotide polymorphisms (SNPs), and 127 unique genes significantly associated with nociplastic type pain, and showed nociplastic type pain to be a polygenic trait with significant SNP-heritability. We found significant genetic overlap between multisite chronic pain and nociplastic type pain, and to a smaller extent with rheumatoid arthritis and a neuropathic pain phenotype. Tissue enrichment analyses highlighted cardiac and thyroid tissue, and gene set enrichment analyses emphasized potential shared mechanisms in cognitive, personality, and metabolic traits and nociplastic type pain along with distinct pathology in migraine and headache. We use a well-powered network approach to investigate nociplastic type pain using existing COPC GWAS output, and show nociplastic type pain to be a complex, heritable trait, in addition to contributing to understanding of potential mechanisms in development of nociplastic pain.

Unravelling shared mechanisms: insights from recent ME/CFS research to illuminate long COVID pathologies

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic illness often triggered by an initiating acute event, mainly viral infections. The transition from acute to chronic disease remains unknown, but interest in this phenomenon has escalated since the COVID-19 pandemic and the post-COVID-19 illness, termed 'long COVID' (LC). Both ME/CFS and LC share many clinical similarities. Here, we present recent findings in ME/CFS research focussing on proposed disease pathologies shared with LC. Understanding these disease pathologies and how they influence each other is key to developing effective therapeutics and diagnostic tests. Given that ME/CFS typically has a longer disease duration compared with LC, with symptoms and pathologies evolving over time, ME/CFS may provide insights into the future progression of LC.

Myalgic encephalomyelitis/chronic fatigue syndrome from current evidence to new diagnostic perspectives through skeletal muscle and metabolic disturbances

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a demanding medical condition for patients and society. It has raised much more public awareness after the COVID-19 pandemic since ME/CFS and long-COVID patients share many clinical symptoms such as debilitating chronic fatigue. However, unlike long COVID, the etiopathology of ME/CFS remains a mystery despite several decades' research. This review moves from pathophysiology of ME/CFS through the compelling evidence and most interesting hypotheses. It focuses on the pathophysiology of skeletal muscle by proposing the hypothesis that skeletal muscle tissue offers novel opportunities for diagnosis and treatment of this syndrome and that new evidence can help resolve the long-standing debate on terminology.

Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe condition with an uncertain origin and a dismal prognosis. There is presently no precise diagnostic test for ME/CFS, and the diagnosis is determined primarily by the presence of certain symptoms. The current study presents an explainable artificial intelligence (XAI) integrated machine learning (ML) framework that identifies and classifies potential metabolic biomarkers of ME/CFS. Metabolomic data from blood samples from 19 controls and 32 ME/CFS patients, all female, who were between age and body mass index (BMI) frequency-matched groups, were used to develop the XAI-based model. The dataset contained 832 metabolites, and after feature selection, the model was developed using only 50 metabolites, meaning less medical knowledge is required, thus reducing diagnostic costs and improving prognostic time. The computational method was developed using six different ML algorithms before and after feature selection. The final classification model was explained using the XAI approach, SHAP. The best-performing classification model (XGBoost) achieved an area under the receiver operating characteristic curve (AUCROC) value of 98.85%. SHAP results showed that decreased levels of alpha-CEHC sulfate, hypoxanthine, and phenylacetylglutamine, as well as increased levels of N-delta-acetylornithine and oleoyl-linoloyl-glycerol (18:1/18:2)[2], increased the risk of ME/CFS. Besides the robustness of the methodology used, the results showed that the combination of ML and XAI could explain the biomarker prediction of ME/CFS and provided a first step toward establishing prognostic models for ME/CFS.

Why the Psychosomatic View on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Inconsistent with Current Evidence and Harmful to Patients

Since 1969, Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) has been classified as a neurological disease in the International Classification of Diseases by the World Health Organization. Although numerous studies over time have uncovered organic abnormalities in patients with ME/CFS, and the majority of researchers to date classify the disease as organic, many physicians still believe that ME/CFS is a psychosomatic illness. In this article, we show how detrimental this belief is to the care and well-being of affected patients and, as a consequence, how important the education of physicians and the public is to stop misdiagnosis, mistreatment, and stigmatization on the grounds of incorrect psychosomatic attributions about the etiology and clinical course of ME/CFS.

Corticosteroid-Binding Globulin (SERPINA6) Consolidates Sexual Dimorphism of Adult Rat Liver

Produced by the liver, corticosteroid-binding globulin (CBG) regulates the plasma distribution and actions of glucocorticoids. A sex difference in pituitary growth hormone secretion patterns established during puberty in rats results in increased hepatic CBG production and 2-fold higher plasma corticosterone levels in females. Glucocorticoids control hepatic development and metabolic activities, and we have therefore examined how disrupting the SerpinA6 gene encoding CBG influences plasma corticosterone dynamics, as well as liver gene expression in male and female rats before and after puberty. Comparisons of corticosterone plasma clearance and hepatic uptake in adult rats, with or without CBG, indicated that CBG limits corticosterone clearance by reducing its hepatic uptake. Hepatic transcriptomic profiling revealed minor sex differences (207 differentially expressed genes) and minimal effect of CBG deficiency in 30-day-old rats before puberty. While liver transcriptomes in 60-day-old males lacking CBG remained essentially unchanged, 2710 genes were differentially expressed in wild-type female vs male livers at this age. Importantly, ∼10% of these genes lost their sexually dimorphic expression in adult females lacking CBG, including those related to cholesterol biosynthesis, inflammation, and lipid and amino acid catabolism. Another 203 genes were altered by the loss of CBG specifically in adult females, including those related to xenobiotic metabolism, circadian rhythm, and gluconeogenesis. Our findings reveal that CBG consolidates the sexual dimorphism of the rat liver initiated by sex differences in growth hormone secretion patterns and provide insight into how CBG deficiencies are linked to glucocorticoid-dependent diseases.

Developing a Blood Cell-Based Diagnostic Test for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Peripheral Blood Mononuclear Cells

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is characterized by debilitating fatigue that profoundly impacts patients' lives. Diagnosis of ME/CFS remains challenging, with most patients relying on self-report, questionnaires, and subjective measures to receive a diagnosis, and many never receiving a clear diagnosis at all. In this study, a single-cell Raman platform and artificial intelligence are utilized to analyze blood cells from 98 human subjects, including 61 ME/CFS patients of varying disease severity and 37 healthy and disease controls. These results demonstrate that Raman profiles of blood cells can distinguish between healthy individuals, disease controls, and ME/CFS patients with high accuracy (91%), and can further differentiate between mild, moderate, and severe ME/CFS patients (84%). Additionally, specific Raman peaks that correlate with ME/CFS phenotypes and have the potential to provide insights into biological changes and support the development of new therapeutics are identified. This study presents a promising approach for aiding in the diagnosis and management of ME/CFS and can be extended to other unexplained chronic diseases such as long COVID and post-treatment Lyme disease syndrome, which share many of the same symptoms as ME/CFS.

Bayesian Statistics Improves Biological Interpretability of Metabolomics Data from Human Cohorts

Univariate analyses of metabolomics data currently follow a frequentist approach, using p-values to reject a null hypothesis. We here propose the use of Bayesian statistics to quantify evidence supporting different hypotheses and discriminate between the null hypothesis versus the lack of statistical power. We used metabolomics data from three independent human cohorts that studied the plasma signatures of subjects with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). The data are publicly available, covering 84-197 subjects in each study with 562-888 identified metabolites of which 777 were common between the two studies and 93 were compounds reported in all three studies. We show how Bayesian statistics incorporates results from one study as "prior information" into the next study, thereby improving the overall assessment of the likelihood of finding specific differences between plasma metabolite levels. Using classic statistics and Benjamini-Hochberg FDR-corrections, Study 1 detected 18 metabolic differences and Study 2 detected no differences. Using Bayesian statistics on the same data, we found a high likelihood that 97 compounds were altered in concentration in Study 2, after using the results of Study 1 as the prior distributions. These findings included lower levels of peroxisome-produced ether-lipids, higher levels of long-chain unsaturated triacylglycerides, and the presence of exposome compounds that are explained by the difference in diet and medication between healthy subjects and ME/CFS patients. Although Study 3 reported only 92 compounds in common with the other two studies, these major differences were confirmed. We also found that prostaglandin F2alpha, a lipid mediator of physiological relevance, was reduced in ME/CFS patients across all three studies. The use of Bayesian statistics led to biological conclusions from metabolomic data that were not found through frequentist approaches. We propose that Bayesian statistics is highly useful for studies with similar research designs if similar metabolomic assays are used.

ME/CFS and Long COVID share similar symptoms and biological abnormalities: road map to the literature

Some patients remain unwell for months after "recovering" from acute COVID-19. They develop persistent fatigue, cognitive problems, headaches, disrupted sleep, myalgias and arthralgias, post-exertional malaise, orthostatic intolerance and other symptoms that greatly interfere with their ability to function and that can leave some people housebound and disabled. The illness (Long COVID) is similar to myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) as well as to persisting illnesses that can follow a wide variety of other infectious agents and following major traumatic injury. Together, these illnesses are projected to cost the U.S. trillions of dollars. In this review, we first compare the symptoms of ME/CFS and Long COVID, noting the considerable similarities and the few differences. We then compare in extensive detail the underlying pathophysiology of these two conditions, focusing on abnormalities of the central and autonomic nervous system, lungs, heart, vasculature, immune system, gut microbiome, energy metabolism and redox balance. This comparison highlights how strong the evidence is for each abnormality, in each illness, and helps to set priorities for future investigation. The review provides a current road map to the extensive literature on the underlying biology of both illnesses.

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

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.

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

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.

Pre-illness data reveals differences in multiple metabolites and metabolic pathways in those who do and do not recover from infectious mononucleosis

Metabolic pathways related to energy production, amino acids, nucleotides, nitrogen, lipids, and neurotransmitters in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) may contribute to the pathophysiology of ME/CFS. 4501 Northwestern University college students were enrolled in a prospective, longitudinal study. We collected data before illness, during infectious mononucleosis (IM), and at a 6 month follow-up for those who recovered (N = 18) versus those who went on to develop ME/CFS 6 months later (N = 18). Examining pre-illness blood samples, we found significant detectable metabolite differences between participants fated to develop severe ME/CFS following IM versus recovered controls. We identified glutathione metabolism, nucleotide metabolism, and the TCA cycle (among others) as potentially dysregulated pathways. The pathways that differed between cases and controls are essential for proliferating cells, particularly during a pro-inflammatory immune response. Performing a series of binary logistic regressions using a leave-one-out cross-validation (LOOCV), our models correctly classified the severe ME/CFS group and recovered controls with an accuracy of 97.2%, sensitivity of 94.4%, and specificity of 100.0%. These changes are consistent with the elevations in pro-inflammatory cytokines that we have reported for patients fated to develop severe ME/CFS 6 months after IM.

Metabolomic Evidence for Peroxisomal Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating disease characterized by unexplained physical fatigue, cognitive and sensory dysfunction, sleeping disturbances, orthostatic intolerance, and gastrointestinal problems. People with ME/CFS often report a prodrome consistent with infections. Using regression, Bayesian and enrichment analyses, we conducted targeted and untargeted metabolomic analysis of plasma from 106 ME/CFS cases and 91 frequency-matched healthy controls. Subjects in the ME/CFS group had significantly decreased levels of plasmalogens and phospholipid ethers (p < 0.001), phosphatidylcholines (p < 0.001) and sphingomyelins (p < 0.001), and elevated levels of dicarboxylic acids (p = 0.013). Using machine learning algorithms, we were able to differentiate ME/CFS or subgroups of ME/CFS from controls with area under the receiver operating characteristic curve (AUC) values up to 0.873. Our findings provide the first metabolomic evidence of peroxisomal dysfunction, and are consistent with dysregulation of lipid remodeling and the tricarboxylic acid cycle. These findings, if validated in other cohorts, could provide new insights into the pathogenesis of ME/CFS and highlight the potential use of the plasma metabolome as a source of biomarkers for the disease.

Plasma metabolomics reveals disrupted response and recovery following maximal exercise in myalgic encephalomyelitis/chronic fatigue syndrome

Post-exertional malaise (PEM) is a hallmark symptom of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). We monitored the evolution of 1157 plasma metabolites in 60 ME/CFS (45 female, 15 male) and 45 matched healthy control participants (30 female, 15 male) before and after 2 maximal cardiopulmonary exercise test (CPET) challenges separated by 24 hours, with the intent of provoking PEM in patients. Four time points allowed exploration of the metabolic response to maximal energy-producing capacity and the recovery pattern of participants with ME/CFS compared with the healthy control group. Baseline comparison identified several significantly different metabolites, along with an enriched percentage of yet-to-be identified compounds. Additionally, temporal measures demonstrated an increased metabolic disparity between cohorts, including unknown metabolites. The effects of exertion in the ME/CFS cohort predominantly highlighted lipid-related as well as energy-related pathways and chemical structure clusters, which were disparately affected by the first and second exercise sessions. The 24-hour recovery period was distinct in the ME/CFS cohort, with over a quarter of the identified pathways statistically different from the controls. The pathways that are uniquely different 24 hours after an exercise challenge provide clues to metabolic disruptions that lead to PEM. Numerous altered pathways were observed to depend on glutamate metabolism, a crucial component of the homeostasis of many organs in the body, including the brain.

Decreased NO production in endothelial cells exposed to plasma from ME/CFS patients

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease characterized by severe and persistent fatigue. Along with clinical studies showing endothelial dysfunction (ED) in a subset of ME/CFS patients, we have recently reported altered ED-related microRNAs in plasma from affected individuals. Inadequate nitric oxide (NO), mainly produced by the endothelial isoform of nitric oxide synthase (eNOS) in endothelial cells (ECs), is a major cause of ED. In this study, we hypothesized that plasma from that cohort of ME/CFS patients induces eNOS-related ED in vitro. To test this, we cultured human umbilical vein endothelial cells (HUVECs) in the presence of plasma from either ME/CFS patients (ME/CFS-plasma, n = 11) or healthy controls (HC-plasma, n = 12). Then, we measured the NO production in the absence and presence of tyrosine kinase and G protein-coupled receptors agonists (TKRs and GPCRs, respectively), well-known to activate eNOS in ECs. Our data showed that HUVECs incubated with ME/CFS-plasma produced less NO either in the absence or presence of eNOS activators compared to ones in presence of HC-plasma. Also, the NO production elicited by bradykinin, histamine, and acetylcholine (GPCRs agonists) was more affected than the one triggered by insulin (TKR agonist). Finally, inhibitory eNOS phosphorylation at Thr495 was higher in HUVECs treated with ME/CFS-plasma compared to the same treatment with HC-plasma. In conclusion, this study in vitro shows a decreased NO production in HUVECs exposed to plasma from ME/CFS patients, suggesting an unreported role of eNOS in the pathophysiology of this disease.

Evidence for Peroxisomal Dysfunction and Dysregulation of the CDP-Choline Pathway in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Background

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating disease that is characterized by unexplained physical fatigue unrelieved by rest. Symptoms also include cognitive and sensory dysfunction, sleeping disturbances, orthostatic intolerance, and gastrointestinal problems. A syndrome clinically similar to ME/CFS has been reported following well-documented infections with the coronaviruses SARS-CoV and MERS-CoV. At least 10% of COVID-19 survivors develop post acute sequelae of SARS-CoV-2 infection (PASC). Although many individuals with PASC have evidence of structural organ damage, a subset have symptoms consistent with ME/CFS including fatigue, post exertional malaise, cognitive dysfunction, gastrointestinal disturbances, and postural orthostatic intolerance. These common features in ME/CFS and PASC suggest that insights into the pathogenesis of either may enrich our understanding of both syndromes, and could expedite the development of strategies for identifying those at risk and interventions that prevent or mitigate disease.

Methods

Using regression, Bayesian and enrichment analyses, we conducted targeted and untargeted metabolomic analysis of 888 metabolic analytes in plasma samples of 106 ME/CFS cases and 91 frequency-matched healthy controls.

Results

In ME/CFS cases, regression, Bayesian and enrichment analyses revealed evidence of peroxisomal dysfunction with decreased levels of plasmalogens. Other findings included decreased levels of several membrane lipids, including phosphatidylcholines and sphingomyelins, that may indicate dysregulation of the cytidine-5’-diphosphocholine pathway. Enrichment analyses revealed decreased levels of choline, ceramides and carnitines, and increased levels of long chain triglycerides (TG) and hydroxy-eicosapentaenoic acid. Elevated levels of dicarboxylic acids were consistent with abnormalities in the tricarboxylic acid cycle. Using machine learning algorithms with selected metabolites as predictors, we were able to differentiate female ME/CFS cases from female controls (highest AUC=0.794) and ME/CFS cases without self-reported irritable bowel syndrome (sr-IBS) from controls without sr-IBS (highest AUC=0.873).

Conclusion

Our findings are consistent with earlier ME/CFS work indicating compromised energy metabolism and redox imbalance, and highlight new abnormalities that may provide insights into the pathogenesis of ME/CFS.

Plasma levels of plasmalogens are decreased in patients with myalgic encephalomyelitis/chronic fatigue syndrome suggesting peroxisome dysfunction.

Tryptophan Metabolites, Cytokines, and Fatty Acid Binding Protein 2 in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) differ for triggers, mode of start, associated symptoms, evolution, and biochemical traits. Therefore, serious attempts are underway to partition them into subgroups useful for a personalized medicine approach to the disease. Here, we investigated clinical and biochemical traits in 40 ME/CFS patients and 40 sex- and age-matched healthy controls. Particularly, we analyzed serum levels of some cytokines, Fatty Acid Binding Protein 2 (FAPB-2), tryptophan, and some of its metabolites via serotonin and kynurenine. ME/CFS patients were heterogeneous for genetic background, trigger, start mode, symptoms, and evolution. ME/CFS patients had higher levels of IL-17A (p = 0.018), FABP-2 (p = 0.002), and 3-hydroxykynurenine (p = 0.037) and lower levels of kynurenine (p = 0.012) and serotonin (p = 0.045) than controls. Changes in kynurenine and 3-hydroxykynurenine were associated with increased kynurenic acid/kynurenine and 3-hydroxykynurenine/kynurenine ratios, indirect measures of kynurenine aminotransferases and kynurenine 3-monooxygenase enzymatic activities, respectively. No correlation was found among cytokines, FABP-2, and tryptophan metabolites, suggesting that inflammation, anomalies of the intestinal barrier, and changes of tryptophan metabolism may be independently associated with the pathogenesis of the disease. Interestingly, patients with the start of the disease after infection showed lower levels of kynurenine (p = 0.034) than those not starting after an infection. Changes in tryptophan metabolites and increased IL-17A levels in ME/CFS could both be compatible with anomalies in the sphere of energy metabolism. Overall, clinical traits together with serum biomarkers related to inflammation, intestine function, and tryptophan metabolism deserve to be further considered for the development of personalized medicine strategies for ME/CFS.

Turning a Corner in ME/CFS Research

This collection of research papers addresses fundamental questions concerning the nature of myalgic encephalomyelitis/ chronic fatigue syndrome (ME/CFS), the problem of disbelief and lack of knowledge and understanding of the condition among many doctors and the origins of this problem, and its impact on patients and their families. We report briefly the growing knowledge of the underlying pathological processes in ME/CFS, and the development of new organizations, including Doctors with ME, the US ME/CFS Clinical Coalition and EUROMENE, to address aspects of the challenges posed by the illness. We discuss the implications of COVID-19, which has much in common with ME/CFS, with much overlap of symptoms, and propose a new taxonomic category, which we are terming post-active phase of infection syndromes (PAPIS) to include both. This collection of papers includes a number of papers reporting similar serious impacts on the quality of life of patients and their families in various European countries. The advice of EUROMENE experts on diagnosis and management is included in the collection. We report this in light of guidance from other parts of the world, including the USA and Australia, and in the context of current difficulties in the UK over the promulgation of a revised guideline from the National Institute for Health and Care Excellence (NICE). We also consider evidence on the cost-effectiveness of interventions for ME/CFS, and on the difficulties of determining the costs of care when a high proportion of people with ME/CFS are never diagnosed as such. The Special Issue includes a paper which is a reminder of the importance of a person-centred approach to care by reviewing mind-body interventions. Finally, another paper reviews the scope for prevention in minimizing the population burden of ME/CFS, and concludes that secondary prevention, through early detection and diagnosis, could be of value.