Category: Biomarker

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)

Exploring the role of galectin-9 and artemin as biomarkers in long COVID with chronic fatigue syndrome: links to inflammation and cognitive function

Abstract:

This study aimed to assess plasma galectin-9 (Gal-9) and artemin (ARTN) concentrations as potential biomarkers to differentiate individuals with Long COVID (LC) patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) from SARS-CoV-2 recovered (R) and healthy controls (HCs).

Receiver operating characteristic (ROC) curve analysis determined a cut-off value of plasma Gal-9 and ARTN to differentiate LC patients from the R group and HCs in two independent cohorts.

Positive correlations were observed between elevated plasma Gal-9 levels and inflammatory markers (e.g. SAA and IP-10), as well as sCD14 and I-FABP in LC patients. Gal-9 also exhibited a positive correlation with cognitive failure scores, suggesting its potential role in cognitive impairment in LC patients with ME/CFS.

This study highlights plasma Gal-9 and/or ARTN as sensitive screening biomarkers for discriminating LC patients from controls. Notably, the elevation of LPS-binding protein in LC patients, as has been observed in HIV infected individuals, suggests microbial translocation. However, despite elevated Gal-9, we found a significant decline in ARTN levels in the plasma of people living with HIV (PLWH). Our study provides a novel and important role for Gal-9/ARTN in LC pathogenesis.

Source: Elahi Shokrollah , Rezaeifar Maryam , Osman Mohammed , Shahbaz Shima. Exploring the role of galectin-9 and artemin as biomarkers in long COVID with chronic fatigue syndrome: links to inflammation and cognitive function. Frontiers in Immunology, Vol 15, 2024. DOI=10.3389/fimmu.2024.1443363. ISSN=1664-3224. https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1443363 (Full text)

 

Gut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles

Abstract:

Recent advancements in translational gut microbiome research have revealed its crucial role in shaping predictive healthcare applications. Herein, we introduce the Gut Microbiome Wellness Index 2 (GMWI2), an enhanced version of our original GMWI prototype, designed as a standardized disease-agnostic health status indicator based on gut microbiome taxonomic profiles.

Our analysis involves pooling existing 8069 stool shotgun metagenomes from 54 published studies across a global demographic landscape (spanning 26 countries and six continents) to identify gut taxonomic signals linked to disease presence or absence. GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence (i.e., outside the “reject option”).

This performance exceeds that of the original GMWI model and traditional species-level α-diversity indices, indicating a more robust gut microbiome signature for differentiating between healthy and non-healthy phenotypes across multiple diseases. When assessed through inter-study validation and external validation cohorts, GMWI2 maintains an average accuracy of nearly 75%.

Furthermore, by reevaluating previously published datasets, GMWI2 offers new insights into the effects of diet, antibiotic exposure, and fecal microbiota transplantation on gut health. Available as an open-source command-line tool, GMWI2 represents a timely, pivotal resource for evaluating health using an individual’s unique gut microbial composition.

Source: Chang, D., Gupta, V.K., Hur, B. et al. Gut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles. Nat Commun 15, 7447 (2024). https://doi.org/10.1038/s41467-024-51651-9 https://www.nature.com/articles/s41467-024-51651-9 (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)

Plasma Neurofilament Light Chain: A Potential Biomarker for Neurological Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex disorder characterized by heterogeneous symptoms, which lack specific biomarkers for its diagnosis. This study aimed to investigate plasma neurofilament light chain (NfL) levels as a potential biomarker for ME/CFS and explore associations with cognitive, autonomic, and neuropathic symptoms.

Here, 67 ME/CFS patients and 43 healthy controls (HCs) underwent comprehensive assessments, including neuropsychological evaluation, autonomic nervous system (ANS) testing, and plasma NfL level analysis. ME/CFS patients exhibited significantly higher plasma NfL levels compared to HC (F = 4.30, p < 0.05). Correlations were observed between NfL levels and cognitive impairment, particularly in visuospatial perception (r = -0.42; p ≤ 0.001), verbal memory (r = -0.35, p ≤ 0.005), and visual memory (r = -0.26; p < 0.05) in ME/CFS. Additionally, higher NfL levels were associated with worsened autonomic dysfunction in these patients, specifically in parasympathetic function (F = 9.48, p ≤ 0.003).

In ME/CFS patients, NfL levels explained up to 17.2% of the results in cognitive tests. Unlike ME/CFS, in HC, NfL levels did not predict cognitive performance. Elevated plasma NfL levels in ME/CFS patients reflect neuroaxonal damage, contributing to cognitive dysfunction and autonomic impairment.

These findings support the potential role of NfL as a biomarker for neurological dysfunction in ME/CFS. Further research is warranted to elucidate underlying mechanisms and clinical implications.

Source: Azcue N, Tijero-Merino B, Acera M, Pérez-Garay R, Fernández-Valle T, Ayo-Mentxakatorre N, Ruiz-López M, Lafuente JV, Gómez Esteban JC, Del Pino R. Plasma Neurofilament Light Chain: A Potential Biomarker for Neurological Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Biomedicines. 2024 Jul 11;12(7):1539. doi: 10.3390/biomedicines12071539. PMID: 39062112; PMCID: PMC11274366. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11274366/ (Full text)

Data-independent LC-MS/MS analysis of ME/CFS plasma reveals a dysregulated coagulation system, endothelial dysfunction, downregulation of complement machinery

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic condition that is characterized by unresolved fatigue, post-exertion symptom exacerbation (PESE), cognitive dysfunction, orthostatic intolerance, and other symptoms. ME/CFS lacks established clinical biomarkers and requires further elucidation of disease mechanisms.

A growing number of studies demonstrate signs of hematological and cardiovascular pathology in ME/CFS cohorts, including hyperactivated platelets, endothelial dysfunction, vascular dysregulation, and anomalous clotting processes. To build on these findings, and to identify potential biomarkers that can be related to pathophysiology, we measured differences in protein expression in platelet-poor plasma (PPP) samples from 15 ME/CFS study participants and 10 controls not previously infected with SARS-CoV-2, using DIA LC-MS/MS.

We identified 24 proteins that are significantly increased in the ME/CFS group compared to the controls, and 21 proteins that are significantly downregulated. Proteins related to clotting processes – thrombospondin-1 (important in platelet activation), platelet factor 4, and protein S – were differentially expressed in the ME/CFS group, suggestive of a dysregulated coagulation system and abnormal endothelial function. Complement machinery was also significantly downregulated, including C9 which forms part of the membrane attack complex. Additionally, we identified a significant upregulation of lactotransferrin, protein S100-A9, and an immunoglobulin variant.

The findings from this experiment further implicate the coagulation and immune system in ME/CFS, and bring to attention the pathology of or imposed on the endothelium. This study highlights potential systems and proteins that require further research with regards to their contribution to the pathogenesis of ME/CFS, symptom manifestation, and biomarker potential, and also gives insight into the hematological and cardiovascular risk for ME/CFS individuals affected by diabetes mellitus.

Source: Nunes, M., Vlok, M., Proal, A. et al. Data-independent LC-MS/MS analysis of ME/CFS plasma reveals a dysregulated coagulation system, endothelial dysfunction, downregulation of complement machinery. Cardiovasc Diabetol 23, 254 (2024). https://doi.org/10.1186/s12933-024-02315-x https://cardiab.biomedcentral.com/articles/10.1186/s12933-024-02315-x (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)

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

Abstract:

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.

Source: Annesley SJ, Missailidis D, Heng B, Josev EK, Armstrong CW. Unravelling shared mechanisms: insights from recent ME/CFS research to illuminate long COVID pathologies. Trends Mol Med. 2024 Mar 4:S1471-4914(24)00028-5. doi: 10.1016/j.molmed.2024.02.003. Epub ahead of print. PMID: 38443223. https://www.sciencedirect.com/science/article/pii/S1471491424000285 (Full text)