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

Trends in Molecular Medicine, Journal Year: 2024, Volume and Issue: 30(5), P. 443 - 458

Published: March 4, 2024

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 to disease remains unknown, but interest in this phenomenon has escalated since the COVID-19 pandemic and post-COVID-19 illness, termed 'long COVID' (LC). Both ME/CFS LC share many clinical similarities. Here, we present recent findings research focussing on proposed pathologies shared with LC. Understanding these how they influence each other key developing effective therapeutics diagnostic tests. Given that typically longer duration compared LC, symptoms evolving over time, may provide insights into future progression of

Language: Английский

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

Journal of Translational Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: Feb. 4, 2025

Language: Английский

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Raman micro-spectroscopy as a tool to study immunometabolism

Biochemical Society Transactions, Journal Year: 2024, Volume and Issue: 52(2), P. 733 - 745

Published: March 13, 2024

In the past two decades, immunometabolism has emerged as a crucial field, unraveling intricate molecular connections between cellular metabolism and immune function across various cell types, tissues, diseases. This review explores insights gained from studies using emerging technology, Raman micro-spectroscopy, to investigate immunometabolism. micro-spectroscopy provides an exciting opportunity directly study at single level where it can be combined with other Raman-based technologies platforms such RNA sequencing. The showcases applications of system including identification, activation, autoimmune disease diagnosis, offering rapid, label-free, minimally invasive analytical approach. spotlights three promising technologies, Raman-activated sorting, stable isotope probing, imaging. synergy machine learning is poised enhance understanding complex phenotypes, enabling biomarker discovery comprehensive investigations in encourages further exploration these evolving rapidly advancing field

Language: Английский

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

Advanced Science, Journal Year: 2023, Volume and Issue: 10(30)

Published: Aug. 31, 2023

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

Language: Английский

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

Journal of Translational Medicine, Journal Year: 2025, Volume and Issue: 23(1)

Published: Jan. 14, 2025

Abstract Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex and multifaceted disorder that defies simplistic characterisation. Traditional approaches to diagnosing treating ME/CFS have often fallen short due the condition’s heterogeneity lack of validated biomarkers. The growing field precision medicine offers promising approach which focuses on genetic molecular underpinnings individual patients. In this review, we explore how machine learning multi-omics (genomics, transcriptomics, proteomics, metabolomics) can transform in research healthcare. We provide an overview concepts for analysing large-scale biological data, highlight key advancements biomarker discovery, data quality integration strategies, while reflecting case study examples. also several priorities, including critical need applying robust computational tools collaborative data-sharing initiatives endeavour unravel intricacies ME/CFS.

Language: Английский

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Dysregulation of lipid metabolism, energy production, and oxidative stress in myalgic encephalomyelitis/chronic fatigue syndrome, Gulf War Syndrome and fibromyalgia

Frontiers in Neuroscience, Journal Year: 2025, Volume and Issue: 19

Published: March 10, 2025

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), Gulf War Syndrome (GWS), and Fibromyalgia (FM) are complex, chronic illnesses with overlapping clinical features. Symptoms that reported across these conditions include post-exertional malaise (PEM), fatigue, pain, yet the etiology of remains largely unknown. Diagnosis is challenging in patients as definitive biomarkers lacking; required to meet criteria often undergo lengthy testing exclude other conditions, a process prolonged, costly, burdensome for patients. The identification reliable validated could facilitate earlier more accurate diagnosis drive development targeted pharmacological therapies might address underlying pathophysiology diseases. Major driving forces biomarker advancing fields metabolomics proteomics allow comprehensive characterization metabolites proteins biological specimens. Recent technological developments areas enable high-throughput analysis thousands from variety samples model systems, provides powerful approach unraveling metabolic phenotypes associated complex Emerging evidence suggests ME/CFS, GWS, FM all characterized by disturbances pathways, particularly those related energy production, lipid metabolism, oxidative stress. Altered levels key pathways have been studies highlighting potential common biochemical abnormalities. precise mechanisms altered remain be elucidated; however, elevated stress observed may contribute symptoms offer target therapeutic intervention. Investigating mechanisms, their role disease process, provide insights into pathogenesis reveal novel treatment targets. As such, metabolomic proteomic analyses crucial understanding in-order identify both common, unique, alterations serve diagnostic markers or

Language: Английский

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Long COVID and post‐acute sequelae of SARS‐CoV‐2 pathogenesis and treatment: A Keystone Symposia report

Annals of the New York Academy of Sciences, Journal Year: 2024, Volume and Issue: 1535(1), P. 31 - 41

Published: April 9, 2024

In 2023, the Keystone Symposia held first international scientific conference convening research leaders investigating pathology of post-acute sequelae COVID-19 (PASC) or Long COVID, a growing and urgent public health priority. this report, we present insights from talks workshops presented during meeting highlight key themes regarding what researchers have discovered underlying biology PASC directions toward future treatment. Several emerged in biology, with inflammation other immune alterations being most common focus, potentially related to viral persistence, latent virus reactivation, and/or tissue damage dysfunction, especially endothelium, nervous system, mitochondria. order develop safe effective treatments for people PASC, critical next steps should focus on replication major findings potential mechanisms, disentangling pathogenic mechanisms downstream effects, development cellular animal models, mechanism-focused randomized, placebo-controlled trials, closer collaboration between lived experience, scientists, stakeholders. Ultimately, by learning post-infectious syndromes, knowledge gained may help not only those PASC/Long but also syndromes.

Language: Английский

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Real-time monitoring of single dendritic cell maturation using deep learning-assisted surface-enhanced Raman spectroscopy

Theranostics, Journal Year: 2024, Volume and Issue: 14(17), P. 6818 - 6830

Published: Jan. 1, 2024

Dynamic real-time detection of dendritic cell (DC) maturation is pivotal for accurately predicting immune system activation, assessing vaccine efficacy, and determining the effectiveness immunotherapy. The heterogeneity cells underscores significance status each individual cell, while achieving monitoring DC at single-cell level poses significant challenges. Surface-enhanced Raman spectroscopy (SERS) holds great potential providing specific fingerprinting information DCs to detect biochemical alterations evaluate their status.

Language: Английский

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

Communications Medicine, Journal Year: 2024, Volume and Issue: 4(1)

Published: Nov. 26, 2024

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 condition's symptomatology severity, better reflect real-life patient experiences. We performed association studies machine learning on 1194 individuals blood plasma nuclear magnetic resonance (NMR) metabolomics profiles, seven exclusive cohorts: hypertension (n = 13,559), depression 2522), asthma 6406), irritable bowel syndrome 859), hay fever 3025), hypothyroidism 1226), migraine 1551) non-diseased control group 53,009). lipoprotein perspective pathophysiology, highlighting gender-specific differences identifying overlapping associations conditions, specifically surface lipids, ketone bodies from 168 significant individual biomarker associations. Additionally, we searched for, trained, optimised algorithm, resulting in predictive model using 19 baseline characteristics nine NMR biomarkers which could identify an AUC 0.83 recall 0.70. A multi-variable score was subsequently derived same 28 features, exhibited ~2.5 times greater than top biomarker. This study provides end-to-end analytical workflow that explores potential clinical utility scores may have for other difficult diagnose illness severe fatigue without known cause. Further symptoms overlap medical problems making diagnosis difficult. wanted find way easily people this condition, so used data UK Biobank compare who had problems. developed mathematical calculation, basic factors markers, classify non-ME/CFS correctly 83% time, recognise condition 70% time. lead serve as example diseases lacking definite laboratory testing. Huang et al. train optimize predict cases Biobank. works heterogenous condition.

Language: Английский

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

ACS Chemical Neuroscience, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 20, 2024

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic, complex illness characterized by severe and often disabling physical mental fatigue. So far, scientists have not been able to fully pinpoint the biological cause of yet it affects millions people worldwide. To gain better understanding ME/CFS, we compared metabolic networks in plasma 38 ME/CFS patients those 24 healthy control participants. This involved an untargeted metabolomics approach addition measurement targeted substances including tryptophan its metabolites, as well tyrosine, phenylalanine, B vitamins, hypoxanthine using liquid chromatography coupled mass spectrometry. We observed significant alterations several pathways, vitamin B3, arginine-proline, aspartate-asparagine analysis. The analysis revealed changes levels 3-hydroxyanthranilic acid, 3-hydroxykynurenine, hypoxanthine, phenylalanine group. These findings suggest potential immune system response oxidative stress patients.

Language: Английский

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