Tag: biomarker

Exploring differences in protein cargo of extracellular vesicles from ME/CFS patient plasma compared to healthy controls

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating disease characterized by post-exertional malaise, fatigue and pain. Yet, its underlying biological mechanisms remain poorly understood. Extracellular vesicles (EVs) are nanoparticles carrying biological cargo and are involved in cell-cell communication. Plasma EVs reflect several disease states and may serve as minimally invasive biomarkers. In this exploratory study, we characterized the plasma EV profiles of ME/CFS patients (N = 49) and healthy controls (N = 50), by enriching for EVs by size-exclusion chromatography coupled to high-resolution quantitative proteomics.

The ME/CFS patients had significantly higher concentrations of EVs than healthy controls. Among the 424 detected proteins included for analyses, 11 had different levels in EVs from ME/CFS patients. The ME/CFS associated EV proteins appear to mainly originate from erythroid cells, hepatocytes and plasma B cells, based on their tissue expression. Albeit differences in EV protein levels did not withstand correction for multiple testing, our study is the largest to date, thereby encouraging future investigations on the role of EV and its cargo in ME/CFS.

Source: Rydland A, Yran ES, Nyman TA, Strand EB, Trøseid AS, Øvstebø R, Heinicke F, Lie BA, Viken MK. Exploring differences in protein cargo of extracellular vesicles from ME/CFS patient plasma compared to healthy controls. Biochem Biophys Rep. 2026 Jun 20;47:102679. doi: 10.1016/j.bbrep.2026.102679. PMID: 42375682; PMCID: PMC13312568. https://pmc.ncbi.nlm.nih.gov/articles/PMC13312568/ (Full text)

Raman Spectroscopy Combined with Machine Learning Reveals Myalgic Encephalomyelitis–Associated Biomolecular Signatures at Rest and After Standardized Stress

Abstract:

Myalgic encephalomyelitis (ME) is characterized by profound fatigue, post-exertional malaise (PEM), and cognitive dysfunction. Despite its clinical significance, the pathophysiology of PEM and disease heterogeneity remain unclear, and no validated biomarkers are available for rapid diagnosis or monitoring. We aimed to develop a screening approach combining label-free Raman spectroscopy (RS) and machine learning modeling (ML) to detect biomolecular changes in blood plasma and differentiate patients with ME from sedentary healthy controls.
Blood plasma was collected from 115 patients with ME and 45 controls at rest (T0) and 90 min after a standardized, non-invasive stress test designed to induce PEM. Plasma samples were analyzed by RS, and ML models were developed independently at each time point to differentiate patients with ME and controls.
The RS-ML models identified spectral features consistent with contributions from proteins, lipids, and low-molecular-weight metabolites. At T0 and T90, the area under the receiver operating characteristic curve, accuracy, specificity and sensitivity were 0.85 and 0.83, 79% and 84%, 82% and 90%, and 73% and 69%, respectively. RS-ML provides a rapid, low-cost approach to detect ME-associated biomolecular signatures in plasma and capture biochemical alterations associated with standardized stress.
Source: Heidarifard M, Moezzi A, Dallaire F, Ember K, Elremaly W, Caraus I, Franco A, Leblond F, Moreau A, Dehaes M. Raman Spectroscopy Combined with Machine Learning Reveals Myalgic Encephalomyelitis–Associated Biomolecular Signatures at Rest and After Standardized Stress. International Journal of Molecular Sciences. 2026; 27(11):4937. https://doi.org/10.3390/ijms27114937 https://www.mdpi.com/1422-0067/27/11/4937 (Full text)

Human Endogenous Retroviruses in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Emerging Roles in Pathogenesis, Immunity, Biomarkers and Therapeutics

Abstract:

Human endogenous retroviruses (HERVs) are potential driving forces of the pathophysiology of Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), linking post-infectious immune dysfunction to chronic inflammation and immune and neurocognitive dysfunction that are hallmark features of ME/CFS.

Accumulating evidence from related autoimmune diseases and cancers has shown that reactivated HERVs can contribute to disease pathogenesis by amplifying immune activation through viral protein-mediated innate sensing, long terminal repeat (LTR)-driven transcription, and disrupting epigenetic silencing. HERV signatures are therefore promising biomarkers for diagnosis, patient stratification for drug-repurposing trials, and therapy monitoring.

Accumulating evidence suggests a possible correlation between HERV expression and ME/CFS symptom severity, alterations in immune phenotypes, function and inflammatory gene networks. Importantly, locus-specific HERV profiling is a promising approach for distinguishing ME/CFS from overlapping or co-morbid conditions and healthy controls. Furthermore, HERV-targeted antibodies, immune modulators, epigenetic and antiviral interventions offer promise as concomitant therapeutic strategies for ME/CFS.

Additional research incorporating viromics and other-omics validation, functional assays, and HERV-stratified clinical trials is now needed to realise this potential and to transform ME/CFS from a symptom-based syndrome into a mechanism-driven, treatable condition.

Source: Perera KD, Oltra E, Carding SR. Human Endogenous Retroviruses in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Emerging Roles in Pathogenesis, Immunity, Biomarkers and Therapeutics. Int J Mol Sci. 2026 May 12;27(10):4309. doi: 10.3390/ijms27104309. PMID: 42196290; PMCID: PMC13207908. https://pmc.ncbi.nlm.nih.gov/articles/PMC13207908/ (Full text)

Plasma Extracellular Vesicle Surface Marker Profiling Reveals Immune Cell-Associated Mitochondrial Membrane Potential Alterations in Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Background: Long COVID (LC) is characterized by symptoms persisting at least 3 months after SARS-CoV-2 infection and affecting multiple organ systems. Diagnosis relies on subjective criteria without established biomarkers. Immune dysregulation and mitochondrial dysfunction are implicated in LC pathophysiology. Given clinical overlap with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), we investigated whether plasma extracellular vesicles (EVs) capture shared molecular signatures.

Methods: Plasma EVs from 125 individuals across pandemic-era and prepandemic cohorts were analyzed. The pandemic-era cohort included COVID-Recovered, LC with ME/CFS phenotype (LC-ME/CFS), and ME/CFS without infection (pan-ME/CFS). The prepandemic cohort included ME/CFS and matched controls. Extracellular vesicles were isolated using size-exclusion chromatography. Concentration and size were assessed by nanoparticle tracking analysis, and surface markers and mitochondrial membrane potential were evaluated by flow cytometry.

Results: Both pan-ME/CFS and LC-ME/CFS exhibited elevated EV concentrations compared with COVID-recovered controls after false discovery rate (FDR) correction (q = 0.0042 and 0.0024). Leukocyte-, monocyte/macrophage-, and platelet-derived EVs were increased, whereas B cell-derived EVs were reduced in both groups. Compared with controls, pan-ME/CFS demonstrated increased mitochondrial membrane potential in B cell-, monocyte/macrophage-, and NK cell-derived subsets after FDR correction, whereas no significant differences were observed in LC-ME/CFS. Prepandemic ME/CFS showed a nominal increase in leukocyte-derived EVs that did not persist after correction, whereas elevated mitochondrial membrane potential in B cell-derived EV subsets remained significant.

Conclusions: ME/CFS and LC-ME/CFS demonstrate partially overlapping immune cell-associated EV alterations. Mitochondrial membrane potential alterations within selected immune-derived EV subsets, particularly B cell-associated EVs, suggest immune-metabolic involvement. Plasma EV profiling may inform future biomarker development.

Source: Ikeda G, Koike-Ieki M, Inoue H, Dadhania AV, El Kamari V, Jagannathan P, Geng LN, Miglis MG, Shafer RW, Yang PC, Bonilla HF. Plasma Extracellular Vesicle Surface Marker Profiling Reveals Immune Cell-Associated Mitochondrial Membrane Potential Alterations in Long COVID and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Open Forum Infect Dis. 2026 May 12;13(5):ofag209. doi: 10.1093/ofid/ofag209. PMID: 42131622; PMCID: PMC13166156. https://pmc.ncbi.nlm.nih.gov/articles/PMC13166156/ (Full text)

A hypothesis connecting dysgeusia due to defects in ATP-P2X3 signaling and fatigue in myalgic encephalomyelitis/chronic fatigue syndrome: lessons learned from long-COVID

Abstract:

Myalgic encephalomyelitis (ME)/chronic fatigue syndrome (CFS) is a neuroimmune disease characterized by debilitating post-exertional malaise (PEM), brain-fog/cognitive problems, and dysregulation of the autonomic nervous system. Currently, there are no objective biomarkers for ME/CFS despite decades of research.

Here, we compile evidence from literature that supports taste dysfunction, particularly alterations of taste perception mediated by Type II taste receptor cells, may be a critical underrecognized feature of ME/CFS. The impetus is drawn from the emerging evidence of clinicopathological similarities between long-COVID and ME/CFS. We discuss in parallel the mechanisms of cellular metabolism, inflammation, vascular dysfunction, and autonomic dysregulation in ME/CFS and long-COVID pathophysiology.

We postulate that mechanistically, dysregulation of ATP signaling through P2X2/P2X3 purinergic receptors underlies both gustatory impairment and core ME/CFS symptoms. Adopting information from the NIH-RECOVER shared resources, we present evidence that suggests chemosensory dysfunction as a potential indicator of progression/severity of PEM. We discuss standardized taste testing as a non-invasive screening tool complementary to molecular biomarkers for ME/CFS.

Notwithstanding, we acknowledge the limitations, confounding and contributing factors such as medications and deficiencies that may exacerbate or independently cause taste-related symptoms in ME/CFS.

In conclusion, we present a compelling case for the multi-factorial role of taste dysfunction in ME/CFS and suggest specific research priorities for investigating the relationship between chemosensory function and post-viral chronic illness.

Source: Srinivasan M, Joseph PV. A hypothesis connecting dysgeusia due to defects in ATP-P2X3 signaling and fatigue in myalgic encephalomyelitis/chronic fatigue syndrome: lessons learned from long-COVID. Front Med (Lausanne). 2026 Apr 8;13:1808646. doi: 10.3389/fmed.2026.1808646. PMID: 42040552; PMCID: PMC13107777. https://pmc.ncbi.nlm.nih.gov/articles/PMC13107777/ (Full text)

Proteomic signatures in cerebrospinal fluid and their clinical associations in patients with ME/CFS

Abstract:

This study evaluated the cerebrospinal fluid (CSF) proteomes from 31 patients diagnosed with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). We quantified 902 proteins, each expressed in at least eleven samples, and systematically categorized clinical factors relevant to ME/CFS symptoms-including autonomic dysfunction, neuroinflammation and metabolic disturbances.

Differentially expressed protein and pathway analyses evaluated protein features associated with both postural orthostatic tachycardia syndrome (POTS) status and disease severity among the patients, while ratio-based analysis further explored associations with severity ratings.

Data are available via ProteomeXchange with identifier PXD076216. Neutrophil degranulation and platelet activation were enriched in patients with POTS, and several pathways, such as the complement cascade, coagulation-related pathways and IGFBP‑mediated insulin-like growth factor transport, were enriched in severe cases. Ratio-based analysis identified four biologically interpretable severity-associated protein ratios related to cellular stress, extracellular remodelling and immune-neuronal interaction.

Together, these findings provide insight into the biological processes associated with clinical heterogeneity in ME/CFS and generate hypotheses for future validation in larger independent cohorts.

Source: Bragée B, Li P, Meadows D, Widgren A, Sjögren P, Ghatan PH, Bertilson BC, Xiao W, Bergquist J. Proteomic signatures in cerebrospinal fluid and their clinical associations in patients with ME/CFS. Sci Rep. 2026 Apr 3. doi: 10.1038/s41598-026-46965-1. Epub ahead of print. PMID: 41932997.  https://www.nature.com/articles/s41598-026-46965-1 (Full text available as PDF file)

Expert perspectives on Myalgic encephalomyelitis/chronic fatigue syndrome – Insights from the 3rd International Conference of the Charité Fatigue Center

Abstract

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, multisystemic disorder mostly triggered by viral infections, with core symptoms including post-exertional malaise (PEM), fatigue, pain, and cognitive dysfunction. Its prevalence has increased significantly in the context of the coronavirus disease 2019 (COVID-19) pandemic. Despite its severity and impact on patients’ quality of life, ME/CFS remains poorly understood.

On May 12 and 13, 2025, the 3rd International Conference hosted by the Charité Fatigue Center brought together nearly 200 researchers from various disciplines on-site, and around 3,700 participants online to discuss recent advances in ME/CFS research, diagnostics, clinical care, and therapeutic trials. The program featured 33 lectures by international experts on key topics such as post-COVID syndrome (PCS), care structures, and pathophysiological mechanisms including cardiovascular dysregulation, immune dysregulation, autoimmune mechanisms, and metabolic dysfunction.

In addition, results from clinical trials addressing disease mechanisms, including those specifically targeting autoantibodies, were presented. While public awareness and funding opportunities have increased in the wake of the pandemic and the emergence of PCS, ME/CFS remains severely underresearched. Sustained and adequately funded research efforts are urgently required to advance understanding, identify diagnostic markers, and develop targeted therapeutic interventions.

Source: Fehrer A, Windzio L, Schoening S, Steiner S, Aschenbrenner AC, Babel N, Behrends U, Bellmann-Strobl J, Cammà G, Cash A, Doehner W, den Dunnen J, Fluge Ø, Franke C, Hoffmann K, Kedor C, Kim L, Löhden W, Mella O, Mihatsch LL, Peluso MJ, Puta C, Putrino D, Ramoji A, Sato W, Sawitzki B, Schlieper G, Schoenfeld Y, Seifert M, Sigurdsson F, Slaghekke A, Sommerfelt K, Sotzny F, Stein E, Steinacker JM, Stingl M, Systrom DM, Tronstad KJ, Wirth K, Wörmann B, Wüst RCI, Yamamura T, Scheibenbogen C. Expert perspectives on Myalgic encephalomyelitis/chronic fatigue syndrome – Insights from the 3rd International Conference of the Charité Fatigue Center. Autoimmun Rev. 2026 Mar 25:104043. doi: 10.1016/j.autrev.2026.104043. Epub ahead of print. PMID: 41895458. https://www.sciencedirect.com/science/article/pii/S1568997226000571 (Full text)

Evidence of White Matter Neuroinflammation in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Diffusion-Based Neuroinflammation Imaging Study

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disorder with suspected neuroinflammatory pathophysiology. However, previous diffusion tensor imaging (DTI) studies have reported inconsistent white matter abnormalities in ME/CFS, and specific white matter inflammatory changes remain poorly characterised. This study employed an advanced diffusion-based neuroinflammation imaging (NII) model to investigate white matter neuroinflammation in ME/CFS.

Diffusion MRI data from 67 ME/CFS patients (median age, 38; and 54 women) and 67 rigorously matched healthy controls (HCs) (median age 38; and 52 women) were analysed. Seven NII-derived metrics were computed: hindered water ratio (NII-HR), restricted fraction (NII-RF), fibre fraction (NII-FF), axial diffusivity (NII-AD), radial diffusivity (NII-RD), mean diffusivity (NII-MD) and fractional anisotropy (NII-FA). Conventional DTI metrics were also calculated. Tract-based spatial statistics were used to perform voxel-wise group comparisons, and multiple regression analysis was conducted to examine the relationship between NII/DTI metrics and clinical measures of mental health, physical health, sleep quality, disability, disease severity and disease duration.

Compared to HCs, ME/CFS patients exhibited widespread white matter abnormalities, including significantly lower NII-HR and NII-RF, and significantly higher NII-FF, NII-AD, NII-MD and NII-FA across association, commissural and projection fibres. Additionally, some regions showed decreased NII-AD and NII-MD in ME/CFS. Lower NII-RF, NII-AD and NII-MD in ME/CFS were significantly associated with worse mental health, while lower NII-RF was also associated with a higher level of disability. Among ME/CFS patients, higher NII-FF was associated with lower disease severity. Conventional DTI showed minimal group differences and no significant clinical associations.

This study provides in vivo evidence of white matter neuroinflammation in ME/CFS, characterised by cerebral edema (reduced NII-HR), cellular infiltration (reduced NII-RF) and axonal reorganisation (increased NII-FF). This suggests NII-derived indices may serve as sensitive biomarkers for neuroinflammation in ME/CFS.

Source: Yu, Q., K.Kothe, R. A.Kwiatek, et al. 2026. “Evidence of White Matter Neuroinflammation in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Diffusion-Based Neuroinflammation Imaging Study.” Human Brain Mapping47, no. 4: e70505. https://doi.org/10.1002/hbm.70505. https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.70505 (Full text)

Use of artificial intelligence and machine learning for the management of fibromyalgia: a scoping review

Abstract:

Background: Fibromyalgia (FM) is a complex and multifactorial syndrome characterized by widespread pain, fatigue, cognitive impairment, and other systemic symptoms. The absence of specific biomarkers and the heterogeneous clinical presentation pose significant diagnostic challenges.

Objective: This scoping review aims to explore the current applications of artificial intelligence (AI) and machine learning (ML) in the diagnosis and clinical management of FM.

Methods: A systematic search was conducted in PubMed, EMBASE, and the Cochrane Library using defined keywords related to FM and AI/ML. Studies were included if they addressed ML applications in FM patients. Following PRISMA-ScR guidelines, 43 studies published between 2011 and 2024 were included and analyzed for ML techniques used, diagnostic targets, data types, and clinical relevance.

Results: As expected, the majority of studies done so far focused on improving diagnostic accuracy through supervised algorithms such as support vector machines, neural networks, and ensemble models, as well as unsupervised clustering and dimensionality reduction techniques. Notable findings include the identification of neurophysiological signatures via fMRI, gene expression patterns, retinal imaging changes, and metabolomic biomarkers that distinguish FM patients from controls. For instance, one study investigating circulating microRNAs used a Random Forest model to identify 11 microRNAs (e.g. hsa-miR-28-5p, hsa-miR-29a-3p, hsa-miR-150-5p) capable of differentiating patients with FM, ME/CFS, and healthy controls, suggesting their potential as biomarkers for more accurate diagnoses. Reported model accuracies ranged from 82% to 100%, although most studies were pilot-based with small and imbalanced samples, limiting generalizability.

Conclusion: AI and ML offer promising tools to overcome longstanding limitations in FM diagnosis and treatment. While current findings demonstrate significant potential, larger, multicenter studies with rigorous validation protocols are essential to finally establish these approaches as clinically reliable solutions.

Source: Clempi Almeida E Silva AL, Reis VHPF, Lamoglia ASA, Souza Desidério C, Freire Oliveira CJ. Use of artificial intelligence and machine learning for the management of fibromyalgia: a scoping review. J Man Manip Ther. 2026 Feb 17:1-17. doi: 10.1080/10669817.2026.2630999. Epub ahead of print. PMID: 41700030. https://pubmed.ncbi.nlm.nih.gov/41700030/

Authors’ Response to “Comment on ‘SMPDL3B as a novel biomarker and therapeutic target in myalgic encephalomyelitis’”

Letter:

We thank Chen and Yan for their thoughtful and positive comments on our recent publication and for their interest in the translational implications of SMPDL3B biology in myalgic encephalomyelitis (ME) [, ]. Their letter provides a welcome opportunity to clarify methodological points related to biomarker validation, in vitro pharmacological assays, and mechanistic interpretation []. We appreciate this constructive dialogue and address each issue below in a collegial and scientifically grounded manner.

Read the rest of this letter HERE>>

Source: Rostami-Afshari B, Elremaly W, Franco A, Moreau A. Authors’ Response to “Comment on ‘SMPDL3B as a novel biomarker and therapeutic target in myalgic encephalomyelitis'”. J Transl Med. 2026 Jan 16;24(1):75. doi: 10.1186/s12967-025-07583-z. PMID: 41546078; PMCID: PMC12809929. https://pmc.ncbi.nlm.nih.gov/articles/PMC12809929/ (Full text)