Tag: biomarker

Measuring Biomarkers of Oxidative Stress in ME/CFS Patients

Abstract:

Patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) have a deficiency in energy production as a result of dysfunctions in their mitochondrial metabolism, defects in the complexes of the electron transport chain, and in the regulation of reactive oxygen species (ROS). This can lead to an imbalance and excess of these species with subsequent modifications of proteins, lipids, and DNA.

Oxidative stress is defined as an accumulation of ROS due to a loss of regulation and the subsequent inability to detoxify them. The modifications to the cellular macromolecules by ROS can be used as biomarkers of oxidative stress and so have the potential to monitor the disease course of a condition like ME/CFS.

Proteins are especially vulnerable to oxidative stress as amino acid residues are naturally modified as part of cell signaling so, in an imbalance between ROS and antioxidants, proteins become modified at multiple sites potentially altering structure and function. Protein carbonyl modifications are stable and can be measured using 2,4-dinitrophenylhydrazine using a commercial ELISA assay. This has been applied here to immune cell proteins and plasma from ME/CFS patients who had moderate functional activity before and during an exercise protocol, and was shown to have potential as a marker of oxidative stress in these patients. The methods used to measure the DNA modification, 8-hydroxy-2′-deoxyguanosine (8-OHdG) are known to give varied results depending on the technology used.

Here, a commercial ELISA assay did not have the sensitivity to detect the modifications in the DNA before and during the exercise protocol of these ME/CFS patients.

Source: Walker M. Measuring Biomarkers of Oxidative Stress in ME/CFS Patients. Methods Mol Biol. 2025;2920:225-244. doi: 10.1007/978-1-0716-4498-0_13. PMID: 40372686. https://link.springer.com/protocol/10.1007/978-1-0716-4498-0_13

HERV activation segregates ME/CFS from fibromyalgia while defining a novel nosologic entity

Abstract:

Research of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and fibromyalgia (FM), two acquired chronic illnesses affecting mainly females, has failed to ascertain their frequent co-appearance and etiology. Despite prior detection of human endogenous retrovirus (HERV) activation in these diseases, the potential biomarker value of HERV expression profiles for their diagnosis, and the relationship of HERV expression profiles with patient immune systems and symptoms had remained unexplored.

By using HERV-V3 high-density microarrays (including over 350k HERV elements and more than 1500 immune-related genes) to interrogate the transcriptomes of peripheral blood mononuclear cells from female patients diagnosed with ME/CFS, FM, or both, and matched healthy controls (n = 43), this study fills this gap of knowledge. Hierarchical clustering of HERV expression profiles strikingly allowed perfect participant assignment into four distinct groups: ME/CFS, FM, co-diagnosed, or healthy, pointing at a potent biomarker value of HERV expression profiles to differentiate between these hard-to-diagnose chronic syndromes.

Differentially expressed HERV-immune-gene modules revealed unique profiles for each of the four study groups and highlighting decreased γδ T cells, and increased plasma and resting CD4 memory T cells, correlating with patient symptom severity in ME/CFS. Moreover, activation of HERV sequences coincided with enrichment of binding sequences targeted by transcription factors which recruit SETDB1 and TRIM28, two known epigenetic silencers of HERV, in ME/CFS, offering a mechanistic explanation for the findings.

Unexpectedly, HERV expression profiles appeared minimally affected in co-diagnosed patients denoting a new nosological entity with low epigenetic impact, a seemingly relevant aspect for the diagnosis and treatment of this prevalent group of patients.

Source: Giménez-Orenga K, Martín-Martínez E, Nathanson L, Oltra E. HERV activation segregates ME/CFS from fibromyalgia while defining a novel nosologic entity. Elife. 2025 May 8;14:RP104441. doi: 10.7554/eLife.104441. PMID: 40338225. https://elifesciences.org/articles/104441 (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)

Machine learning and multi-omics in precision medicine for ME/CFS

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex and multifaceted disorder that defies simplistic characterisation. Traditional approaches to diagnosing and treating ME/CFS have often fallen short due to the condition’s heterogeneity and the lack of validated biomarkers. The growing field of precision medicine offers a promising approach which focuses on the genetic and molecular underpinnings of individual patients.

In this review, we explore how machine learning and multi-omics (genomics, transcriptomics, proteomics, and metabolomics) can transform precision medicine in ME/CFS research and healthcare. We provide an overview on machine learning concepts for analysing large-scale biological data, highlight key advancements in multi-omics biomarker discovery, data quality and integration strategies, while reflecting on ME/CFS case study examples. We also highlight several priorities, including the critical need for applying robust computational tools and collaborative data-sharing initiatives in the endeavour to unravel the biological intricacies of ME/CFS.

Source: Huang K, Lidbury BA, Thomas N, Gooley PR, Armstrong CW. Machine learning and multi-omics in precision medicine for ME/CFS. J Transl Med. 2025 Jan 14;23(1):68. doi: 10.1186/s12967-024-05915-z. PMID: 39810236. Huang K, Lidbury BA, Thomas N, Gooley PR, Armstrong CW. Machine learning and multi-omics in precision medicine for ME/CFS. J Transl Med. 2025 Jan 14;23(1):68. doi: 10.1186/s12967-024-05915-z. PMID: 39810236. https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-024-05915-z (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)

Hypocapnic cerebral hypoperfusion: A biomarker of orthostatic intolerance

Abstract:

The objective of the study was to identify markers of hypocapnic cerebral hypoperfusion (HYCH) in patients with orthostatic intolerance (OI) without tachycardia and without orthostatic hypotension. This single center, retrospective study included OI patients referred for autonomic evaluation with the 10 min tilt test. Heart rate, end-tidal CO2 (ET-CO2), blood pressure, and cerebral blood flow velocity (CBFv) from middle cerebral artery were monitored. HYCH was defined by: (1) Symptoms of OI; (2) Orthostatic hypocapnia (low ET-CO2); (3) Abnormal decline in orthostatic CBFv due to hypocapnia; 4) Absence of tachycardia, orthostatic hypotension, or other causes of low CBFv or hypocapnia.

Sixteen subjects met HYCH criteria (15/1 women/men, age 38.5±8.0 years) and were matched by age and gender to postural tachycardia patients (POTS, n = 16) and healthy controls (n = 16). During the tilt, CBFv decreased more in HYCH (-22.4±7.7%, p<0.0001) and POTS (-19.0±10.3%, p<0.0001) compared to controls (-3.0±5.0%). Orthostatic ET-CO2 was lower in HYCH (26.4±4.2 (mmHg), p<0.0001) and POTS (28.6±4.3, p<0.0001) compared to controls (36.9 ± 2.1 mmHg). Orthostatic heart rate was normal in HYCH (89.0±10.9 (BPM), p<0.08) and controls (80.8 ±11.2), but was higher in POTS (123.7±11.2, p<0.0001). Blood pressure was normal and similar in all groups.

It is concluded that both HYCH and POTS patients have comparable decrease in CBFv which is due to vasoconstrictive effect of hypocapnia. Blood flow velocity monitoring can provide an objective biomarker for HYCH in OI patients without tachycardia.

Source: Novak P. Hypocapnic cerebral hypoperfusion: A biomarker of orthostatic intolerance. PLoS One. 2018 Sep 26;13(9):e0204419. doi: 10.1371/journal.pone.0204419. PMID: 30256820; PMCID: PMC6157889. https://pmc.ncbi.nlm.nih.gov/articles/PMC6157889/ (Full text)

Immunometabolic changes and potential biomarkers in CFS peripheral immune cells revealed by single-cell RNA sequencing

Abstract:

The pathogenesis of Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) remains unclear, though increasing evidence suggests inflammatory processes play key roles. In this study, single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) was used to decipher the immunometabolic profile in 4 ME/CFS patients and 4 heathy controls.

We analyzed changes in the composition of major PBMC subpopulations and observed an increased frequency of total T cells and a significant reduction in NKs, monocytes, cDCs and pDCs. Further investigation revealed even more complex changes in the proportions of cell subpopulations within each subpopulation. Gene expression patterns revealed upregulated transcription factors related to immune regulation, as well as genes associated with viral infections and neurodegenerative diseases.

CD4+ and CD8+ T cells in ME/CFS patients show different differentiation states and altered trajectories, indicating a possible suppression of differentiation. Memory B cells in ME/CFS patients are found early in the pseudotime, indicating a unique subtype specific to ME/CFS, with increased differentiation to plasma cells suggesting B cell overactivity. NK cells in ME/CFS patients exhibit reduced cytotoxicity and impaired responses, with reduced expression of perforin and CD107a upon stimulation. Pseudotime analysis showed abnormal development of adaptive immune cells and an enhanced cell-cell communication network converging on monocytes in particular.

Our analysis also identified the estrogen-related receptor alpha (ESRRA)-APP-CD74 signaling pathway as a potential biomarker for ME/CFS in peripheral blood. In addition, data from the GSE214284 database confirmed higher ESRRA expression in the monocyte cell types of male ME/CFS patients. These results suggest a link between immune and neurological symptoms.

The results support a disease model of immune dysfunction ranging from autoimmunity to immunodeficiency and point to amyloidotic neurodegenerative signaling pathways in the pathogenesis of ME/CFS. While the study provides important insights, limitations include the modest sample size and the evaluation of peripheral blood only.

These findings highlight potential targets for diagnostic biomarkers and therapeutic interventions. Further research is needed to validate these biomarkers and explore their clinical applications in managing ME/CFS.

Source: Sun Y, Zhang Z, Qiao Q, Zou Y, Wang L, Wang T, Lou B, Li G, Xu M, Wang Y, Zhang Z, Hou X, Chen L, Zhao R. Immunometabolic changes and potential biomarkers in CFS peripheral immune cells revealed by single-cell RNA sequencing. J Transl Med. 2024 Oct 11;22(1):925. doi: 10.1186/s12967-024-05710-w. PMID: 39394558. https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-024-05710-w (Full text)

Identifying microRNAs Possibly Implicated in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Fibromyalgia: A Review

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and fibromyalgia (FM) are chronic syndromes of unknown etiology, accompanied by numerous symptoms affecting neurological and physical conditions. Despite frequent revisions of the diagnostic criteria, clinical practice guidelines are often outdated, leading to underdiagnosis and ineffective treatment. Our aim was to identify microRNA (miRNA) biomarkers implicated in pathological mechanisms underlying these diseases.
A comprehensive literature review using publicly accessible databases was conducted. Interesting miRNAs were extracted from relevant publications on ME/CFS and/or FM, and were then linked to pathophysiological processes possibly manifesting these chronic diseases. Dysregulated miRNAs in ME/CFS and FM may serve as promising biomarkers for these diseases.
Key identified miRNAs, such as miR-29c, miR-99b, miR-128, miR-374b, and miR-766, were frequently mentioned for their roles in immune response, mitochondrial dysfunction, oxidative stress, and central sensitization, while miR-23a, miR-103, miR-152, and miR-320 were implicated in multiple crucial pathological processes for FM and/or ME/CFS.
In summary, both ME/CFS and FM seem to share many dysregulated biological or molecular processes, which may contribute to their commonly shared symptoms. This miRNA-based approach offers new angles for discovering molecular markers urgently needed for early diagnosis or therapeutics to tackle the pathology of these medically unexplained chronic diseases.
Source: Tsamou M, Kremers FAC, Samaritakis KA, Roggen EL. Identifying microRNAs Possibly Implicated in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Fibromyalgia: A Review. International Journal of Molecular Sciences. 2024; 25(17):9551. https://doi.org/10.3390/ijms25179551 https://www.mdpi.com/1422-0067/25/17/9551 (Full text)

Replicated blood-based biomarkers for Myalgic Encephalomyelitis not explicable by inactivity

Abstract:

Myalgic Encephalomyelitis (ME; sometimes referred to as chronic fatigue syndrome) is a relatively common and female-biased disease of unknown pathogenesis that profoundly decreases patients’ health-related quality-of-life. ME diagnosis is hindered by the absence of robustly-defined and specific biomarkers that are easily measured from available sources such as blood, and unaffected by ME patients’ low level of physical activity.

Previous studies of blood biomarkers have not yielded replicated results, perhaps due to low study sample sizes (n<100). Here, we use UK Biobank (UKB) data for up to 1,455 ME cases and 131,303 population controls to discover hundreds of molecular and cellular blood traits that differ significantly between cases and controls. Importantly, 116 of these traits are replicated, as they are significant for both female and male cohorts.

Our analysis used semi-parametric efficient estimators, an initial Super Learner fit followed by a one-step correction, three types of mediators, and natural direct and indirect estimands, to decompose the average effect of ME status on molecular and cellular traits. Strikingly, these trait differences cannot be explained by ME cases’ restricted activity.

Of 3,237 traits considered, ME status had a significant effect on only one, via the “Duration of walk” (UKB field 874) mediator. By contrast, ME status had a significant direct effect on 290 traits (9%). As expected, these effects became more significant with increased stringency of case and control definition.

Significant female and male traits were indicative of chronic inflammation, insulin resistance and liver disease. Individually, significant effects on blood traits, however, were not sufficient to cleanly distinguish cases from controls. Nevertheless, their large number, lack of sex-bias, and strong significance, despite the ‘healthy volunteer’ selection bias of UKB participants, keep alive the future ambition of a blood-based biomarker panel for accurate ME diagnosis.

Source: Sjoerd V Beentjes, Julia Kaczmarczyk, Amanda Cassar, Gemma Louise Samms, Nima S Hejazi, Ava Khamseh, Chris P Ponting. Replicated blood-based biomarkers for Myalgic Encephalomyelitis not explicable by inactivity. medRxiv 2024.08.26.24312606; doi: https://doi.org/10.1101/2024.08.26.24312606 https://www.medrxiv.org/content/10.1101/2024.08.26.24312606v1 (Full text available as PDF file)

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)