Tag: metabolomics

Advocating the role of trained immunity in the pathogenesis of ME/CFS: a mini review

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex chronic disease of which the underlying (molecular) mechanisms are mostly unknown. An estimated 0.89% of the global population is affected by ME/CFS. Most patients experience a multitude of symptoms that severely affect their lives. These symptoms include post-exertional malaise, chronic fatigue, sleep disorder, impaired cognitive functions, flu-like symptoms, and chronic immune activation. Therapy focusses on symptom management, as there are no drugs available. Approximately 60% of patients develop ME/CFS following an acute infection.

Such a preceding infection may induce a state of trained immunity; defined as acquired, nonspecific, immunological memory of innate immune cells. Trained immune cells undergo long term epigenetic reprogramming, which leads to changes in chromatin accessibility, metabolism, and results in a hyperresponsive phenotype. Initially, trained immunity has only been demonstrated in peripheral blood monocytes and macrophages. However, more recent findings indicate that hematopoietic stem cells in the bone marrow are required for long-term persistence of trained immunity. While trained immunity is beneficial to combat infections, a disproportionate response may cause disease.

We hypothesize that pronounced hyperresponsiveness of innate immune cells to stimuli could account for the aberrant activation of various immune pathways, thereby contributing to the pathophysiology of ME/CFS. In this mini review, we elaborate on the concept of trained immunity as a factor involved in the pathogenesis of ME/CFS by presenting evidence from other post-infectious diseases with symptoms that closely resemble those of ME/CFS.

Source: Humer B, Dik WA, Versnel MA. Advocating the role of trained immunity in the pathogenesis of ME/CFS: a mini review. Front Immunol. 2025 Mar 25;16:1483764. doi: 10.3389/fimmu.2025.1483764. PMID: 40201181; PMCID: PMC11975576. https://pmc.ncbi.nlm.nih.gov/articles/PMC11975576/ (Full text)

The metabolic and physiologic impairments underlying long COVID associated exercise intolerance

Abstract:

Data from invasive CPET (iCPET) revealed long COVID patients have impaired systemic oxygen extraction (EO2), suggesting impaired mitochondrial ATP production. However, it remains uncertain whether the initial severity of SARS-CoV-2 infection has implications on EO2 and exercise capacity (VO2) nor has there been assessment of anerobic ATP generation in long COVID patients. iCPET was performed on 47 long COVID patients (i.e., full cohort; n = 8 with severe SARS-CoV-2 infection). ‘

In a subset of patients (i.e., metabolomic cohort; n = 26) metabolomics on venous and arterial blood samples during iCPET was performed. In the full cohort, long COVID patients exhibited reduced peak EO2 with reduced peak VO2 (90 ± 17% predicted) relative to cardiac output (118 ± 23% predicted). Peak VO2 [88% predicted (IQR 81% – 108%) vs. 70% predicted (IQR 64% – 89%); p = 0.02] and EO2 [0.59(IQR 0.53-0.62) vs. 0.53(IQR 0.50-0.48); p = 0.01) were lower in severe versus mild infection.

In the metabolomic cohort, 12 metabolites were significantly consumed, and 41 metabolites were significantly released (p-values < 0.05). Quantitative metabolomics demonstrated significant increases in inosine and succinate arteriovenous gradients during exercise. Peak VO2 was significantly correlated with peak venous succinate (r = 0.68; p = 0.0008) and peak venous lactate (r = 0.49; p = 0.0004). Peak EO2 and consequently peak VO2 impact long COVID patients in a severity dependent manner.

Exercise intolerance associated with long COVID is defined by impaired aerobic and anaerobic energy production. Peak venous succinate may serve as a potential biomarker in long COVID.

Source: Leitner BP, Joseph P, Quast AF, Ramirez MA, Heerdt PM, Villalobos JG, Singh I. The metabolic and physiologic impairments underlying long COVID associated exercise intolerance. Pulm Circ. 2024 Nov 13;14(4):e70009. doi: 10.1002/pul2.70009. PMID: 39544193; PMCID: PMC11560803. https://pmc.ncbi.nlm.nih.gov/articles/PMC11560803/ (Full text)

Cerebrospinal fluid metabolomics, lipidomics and serine pathway dysfunction in myalgic encephalomyelitis/chronic fatigue syndroome (ME/CFS)

Abstract:

We proposed that cerebrospinal fluid would provide objective evidence for disrupted brain metabolism in myalgic encephalomyelitis/chronic fatigue syndroome (ME/CFS). The concept of postexertional malaise (PEM) with disabling symptom exacerbation after limited exertion that does not respond to rest is a diagnostic criterion for ME/CFS. We proposed that submaximal exercise provocation would cause additional metabolic perturbations.

The metabolomic and lipidomic constituents of cerebrospinal fluid from separate nonexercise and postexercise cohorts of ME/CFS and sedentary control subjects were contrasted using targeted mass spectrometry (Biocrates) and frequentist multivariate general linear regression analysis with diagnosis, exercise, gender, age and body mass index as independent variables. ME/CFS diagnosis was associated with elevated serine but reduced 5-methyltetrahydrofolate (5MTHF).

One carbon pathways were disrupted. Methylation of glycine led to elevated sarcosine but further methylation to dimethylglycine and choline was decreased. Creatine and purine intermediates were elevated. Transaconitate from the tricarboxylic acid cycle was elevated in ME/CFS along with essential aromatic amino acids, lysine, purine, pyrimidine and microbiome metabolites. Serine is a precursor of phospholipids and sphingomyelins that were also elevated in ME/CFS. Exercise led to consumption of lipids in ME/CFS and controls while metabolites were consumed in ME/CFS but generated in controls.

The findings differ from prior hypometabolic findings in ME/CFS plasma. The novel findings generate new hypotheses regarding serine-folate-glycine one carbon and serine-phospholipid metabolism, elevation of end products of catabolic pathways, shifts in folate, thiamine and other vitamins with exercise, and changes in sphingomyelins that may indicate myelin and white matter dysfunction in ME/CFS.

Source: Baraniuk JN. Cerebrospinal fluid metabolomics, lipidomics and serine pathway dysfunction in myalgic encephalomyelitis/chronic fatigue syndroome (ME/CFS). Sci Rep. 2025 Mar 3;15(1):7381. doi: 10.1038/s41598-025-91324-1. PMID: 40025157. https://www.nature.com/articles/s41598-025-91324-1 (Full text)

The search for a blood-based biomarker for Myalgic Encephalomyelitis/ Chronic Fatigue Syndrome (ME/CFS): from biochemistry to electrophysiology

Abstract:

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disease of unknown aetiology characterised by symptoms of post-exertional malaise (PEM) and fatigue leading to substantial impairment in functioning. Other key symptoms include cognitive impairment and unrefreshing sleep, with many experiencing pain. To date there is no complete understanding of the triggering pathomechanisms of disease, and no quantitative biomarker available with sufficient sensitivity, specificity, and adoptability to provide conclusive diagnosis. Clinicians thus eliminate differential diagnoses, and rely on subjective, unspecific, and disputed clinical diagnostic criteria-a process that often takes years with patients being misdiagnosed and receiving inappropriate and sometimes detrimental care. Without a quantitative biomarker, trivialisation, scepticism, marginalisation, and misunderstanding of ME/CFS continues despite the significant disability for many. One in four individuals are bed-bound for long periods of time, others have difficulties maintaining a job/attending school, incurring individual income losses of thousands, while few participate in social activities.

Main body: Recent studies have reported promising quantifiable differences in the biochemical and electrophysiological properties of blood cells, which separate ME/CFS and non-ME/CFS participants with high sensitivities and specificities-demonstrating potential development of an accessible and relatively non-invasive diagnostic biomarker. This includes profiling immune cells using Raman spectroscopy, measuring the electrical impedance of blood samples during hyperosmotic challenge using a nano-electronic assay, use of metabolomic assays, and certain techniques which assess mitochondrial dysfunction. However, for clinical application, the specificity of these biomarkers to ME/CFS needs to be explored in more disease controls, and their practicality/logistics considered. Differences in cytokine profiles in ME/CFS are also well documented, but finding a consistent, stable, and replicable cytokine profile may not be possible. Increasing evidence demonstrates acetylcholine receptor and transient receptor potential ion channel dysfunction in ME/CFS, though how these findings could translate to a diagnostic biomarker are yet to be explored.

Conclusion: Different biochemical and electrophysiological properties which differentiate ME/CFS have been identified across studies, holding promise as potential blood-based quantitative diagnostic biomarkers for ME/CFS. However, further research is required to determine their specificity to ME/CFS and adoptability for clinical use.

Source: Clarke KSP, Kingdon CC, Hughes MP, Lacerda EM, Lewis R, Kruchek EJ, Dorey RA, Labeed FH. The search for a blood-based biomarker for Myalgic Encephalomyelitis/ Chronic Fatigue Syndrome (ME/CFS): from biochemistry to electrophysiology. J Transl Med. 2025 Feb 4;23(1):149. doi: 10.1186/s12967-025-06146-6. PMID: 39905423.  https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-025-06146-6 (Full text)

Exertional Exhaustion (Post-Exertional Malaise, PEM) Evaluated by the Effects of Exercise on Cerebrospinal Fluid Metabolomics–Lipidomics and Serine Pathway in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract

Post-exertional malaise (PEM) is a defining condition of myalgic encephalomyelitis (ME/CFS). The concept requires that a provocation causes disabling limitation of cognitive and functional effort (“fatigue”) that does not respond to rest. Cerebrospinal fluid was examined as a proxy for brain metabolite and lipid flux and to provide objective evidence of pathophysiological dysfunction. Two cohorts of ME/CFS and sedentary control subjects had lumbar punctures at baseline (non-exercise) or after submaximal exercise (post-exercise). Cerebrospinal fluid metabolites and lipids were quantified by targeted Biocrates mass spectrometry methods.
Significant differences between ME/CFS and control, non-exercise vs. post-exercise, and by gender were examined by multivariate general linear regression and Bayesian regression methods. Differences were found at baseline between ME/CFS and control groups indicating disease-related pathologies, and between non-exercise and post-exercise groups implicating PEM-related pathologies.
A new, novel finding was elevated serine and its derivatives sarcosine and phospholipids with a decrease in 5-methyltetrahydrofolate (5MTHF), which suggests general dysfunction of folate and one-carbon metabolism in ME/CFS. Exercise led to consumption of lipids in ME/CFS and controls while metabolites were consumed in ME/CFS but generated in controls. In general, the frequentist and Bayesian analyses generated complementary but not identical sets of analytes that matched the metabolic modules and pathway analysis. Cerebrospinal fluid is unique because it samples the choroid plexus, brain interstitial fluid, and cells of the brain parenchyma.
The quantitative outcomes were placed into the context of the cell danger response hypothesis to explain shifts in serine and phospholipid synthesis; folate and one-carbon metabolism that affect sarcosine, creatine, purines, and thymidylate; aromatic and anaplerotic amino acids; glucose, TCA cycle, trans-aconitate, and coenzyme A in energy metabolism; and vitamin activities that may be altered by exertion. The metabolic and phospholipid profiles suggest the additional hypothesis that white matter dysfunction may contribute to the cognitive dysfunction in ME/CFS.
Source: Baraniuk JN. Exertional Exhaustion (Post-Exertional Malaise, PEM) Evaluated by the Effects of Exercise on Cerebrospinal Fluid Metabolomics–Lipidomics and Serine Pathway in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. International Journal of Molecular Sciences. 2025; 26(3):1282. https://doi.org/10.3390/ijms26031282 https://www.mdpi.com/1422-0067/26/3/1282 (Full text)

Discriminating Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and comorbid conditions using metabolomics in UK Biobank

Abstract:

Background: Diagnosing complex illnesses like Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is complicated due to the diverse symptomology and presence of comorbid conditions. ME/CFS patients often present with multiple health issues, therefore, incorporating comorbidities into research can provide a more accurate understanding of the condition’s symptomatology and severity, to better reflect real-life patient experiences.

Methods: We performed association studies and machine learning on 1194 ME/CFS individuals with blood plasma nuclear magnetic resonance (NMR) metabolomics profiles, and seven exclusive comorbid cohorts: hypertension (n = 13,559), depression (n = 2522), asthma (n = 6406), irritable bowel syndrome (n = 859), hay fever (n = 3025), hypothyroidism (n = 1226), migraine (n = 1551) and a non-diseased control group (n = 53,009).

Results: We present a lipoprotein perspective on ME/CFS pathophysiology, highlighting gender-specific differences and identifying overlapping associations with comorbid conditions, specifically surface lipids, and ketone bodies from 168 significant individual biomarker associations. Additionally, we searched for, trained, and optimised a machine learning algorithm, resulting in a predictive model using 19 baseline characteristics and nine NMR biomarkers which could identify ME/CFS with an AUC of 0.83 and recall of 0.70. A multi-variable score was subsequently derived from the same 28 features, which exhibited ~2.5 times greater association than the top individual biomarker.

Conclusions: This study provides an end-to-end analytical workflow that explores the potential clinical utility that association scores may have for ME/CFS and other difficult to diagnose conditions.

Source: Huang K, G C de Sá A, Thomas N, Phair RD, Gooley PR, Ascher DB, Armstrong CW. Discriminating Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and comorbid conditions using metabolomics in UK Biobank. Commun Med (Lond). 2024 Nov 26;4(1):248. doi: 10.1038/s43856-024-00669-7. PMID: 39592839; PMCID: PMC11599898.  https://pmc.ncbi.nlm.nih.gov/articles/PMC11599898/ (Full text)

Untargeted Metabolomics and Quantitative Analysis of Tryptophan Metabolites in Myalgic Encephalomyelitis Patients and Healthy Volunteers: A Comparative Study Using High-Resolution Mass Spectrometry

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic, complex illness characterized by severe and often disabling physical and mental fatigue. So far, scientists have not been able to fully pinpoint the biological cause of the illness and yet it affects millions of people worldwide.

To gain a better understanding of ME/CFS, we compared the metabolic networks in the plasma of 38 ME/CFS patients to those of 24 healthy control participants. This involved an untargeted metabolomics approach in addition to the measurement of targeted substances including tryptophan and its metabolites, as well as tyrosine, phenylalanine, B vitamins, and hypoxanthine using liquid chromatography coupled to mass spectrometry.

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Source: Abujrais S, Vallianatou T, Bergquist J. Untargeted Metabolomics and Quantitative Analysis of Tryptophan Metabolites in Myalgic Encephalomyelitis Patients and Healthy Volunteers: A Comparative Study Using High-Resolution Mass Spectrometry. ACS Chem Neurosci. 2024 Sep 20. doi: 10.1021/acschemneuro.4c00444. Epub ahead of print. PMID: 39302151. https://pubs.acs.org/doi/10.1021/acschemneuro.4c00444 (Full text)

Fast Targeted Metabolomics for Analyzing Metabolic Diversity of Bacterial Indole Derivatives in ME/CFS Gut Microbiome

Abstract:

Disruptions in microbial metabolite interactions due to gut microbiome dysbiosis and metabolomic shifts may contribute to Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and other immune-related conditions. The aryl hydrocarbon receptor (AhR), activated upon binding various tryptophan metabolites, modulates host immune responses. This study investigates whether the metabolic diversity-the concentration distribution-of bacterial indole pathway metabolites can differentiate bacterial strains and classify ME/CFS samples.

A fast targeted liquid chromatography-parallel reaction monitoring method at a rate of 4 minutes per sample was developed for large-scale analysis. This method revealed significant metabolic differences in indole derivatives among B. uniformis strains cultured from human isolates. Principal component analysis identified two major components (PC1, 68.9%; PC2, 18.7%), accounting for 87.6% of the variance and distinguishing two distinct B. uniformis clusters. The metabolic difference between clusters was particularly evident in the relative contributions of indole-3-acrylate and indole-3-aldehyde.

We further measured concentration distributions of indole derivatives in ME/CFS by analyzing fecal samples from 10 patients and 10 healthy controls using the fast targeted metabolomics method. An AdaBoost-LOOCV model achieved moderate classification success with a mean LOOCV accuracy of 0.65 (Control: precision of 0.67, recall of 0.60, F1-score of 0.63; ME/CFS: precision of 0.64, recall of 0.7000, F1-score of 0.67).

These results suggest that the metabolic diversity of indole derivatives from tryptophan degradation, facilitated by the fast targeted metabolomics and machine learning, is a potential biomarker for differentiating bacterial strains and classifying ME/CFS samples.

Mass spectrometry datasets are accessible at the National Metabolomics Data Repository (ST002308, DOI: 10.21228/M8G13Q; ST003344, DOI: 10.21228/M8RJ9N; ST003346, DOI: 10.21228/M8RJ9N).

Source: Tian H, Wang L, Aiken E, Ortega RJV, Hardy R, Placek L, Kozhaya L, Unutmaz D, Oh J, Yao X. Fast Targeted Metabolomics for Analyzing Metabolic Diversity of Bacterial Indole Derivatives in ME/CFS Gut Microbiome. bioRxiv [Preprint]. 2024 Jul 29:2024.07.29.605643. doi: 10.1101/2024.07.29.605643. PMID: 39131327; PMCID: PMC11312560. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11312560/ (Full text)

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

Abstract:

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.

Source: Yagin FH, Shateri A, Nasiri H, Yagin B, Colak C, Alghannam AF. Development of an expert system for the classification of myalgic encephalomyelitis/chronic fatigue syndrome. PeerJ Comput Sci. 2024 Mar 20;10:e1857. doi: 10.7717/peerj-cs.1857. PMID: 38660205; PMCID: PMC11041999. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11041999/ (Full text)

Reinforcing the Evidence of Mitochondrial Dysfunction in Long COVID Patients Using a Multiplatform Mass Spectrometry-Based Metabolomics Approach

Abstract:

Despite the recent and increasing knowledge surrounding COVID-19 infection, the underlying mechanisms of the persistence of symptoms for a long time after the acute infection are still not completely understood. Here, a multiplatform mass spectrometry-based approach was used for metabolomic and lipidomic profiling of human plasma samples from Long COVID patients (n = 40) to reveal mitochondrial dysfunction when compared with individuals fully recovered from acute mild COVID-19 (n = 40).

Untargeted metabolomic analysis using CE-ESI(+/-)-TOF-MS and GC-Q-MS was performed. Additionally, a lipidomic analysis using LC-ESI(+/-)-QTOF-MS based on an in-house library revealed 447 lipid species identified with a high confidence annotation level. The integration of complementary analytical platforms has allowed a comprehensive metabolic and lipidomic characterization of plasma alterations in Long COVID disease that found 46 relevant metabolites which allowed to discriminate between Long COVID and fully recovered patients.

We report specific metabolites altered in Long COVID, mainly related to a decrease in the amino acid metabolism and ceramide plasma levels and an increase in the tricarboxylic acid (TCA) cycle, reinforcing the evidence of an impaired mitochondrial function. The most relevant alterations shown in this study will help to better understand the insights of Long COVID syndrome by providing a deeper knowledge of the metabolomic basis of the pathology.

Source: Martínez S, Albóniga OE, López-Huertas MR, Gradillas A, Barbas C. Reinforcing the Evidence of Mitochondrial Dysfunction in Long COVID Patients Using a Multiplatform Mass Spectrometry-Based Metabolomics Approach. J Proteome Res. 2024 Apr 2. doi: 10.1021/acs.jproteome.3c00706. Epub ahead of print. PMID: 38566450. https://pubmed.ncbi.nlm.nih.gov/38566450/