Tag: Raman spectroscopy

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)

Using Single-Cell Raman Microspectroscopy to Profile Human Peripheral Blood Mononuclear Cells

Abstract:

A reliable, validated test would enhance our ability to treat and research chronic conditions. Early and accurate diagnosis would provide an entry point into clinical care, give access to benefits, remove the stigma associated with these conditions, and importantly, provide researchers with a fundamental tool they require to study these heterogeneous disorders.

In this chapter, we describe how Raman microspectroscopy can be utilised to study the biology of peripheral blood mononuclear cells (PBMCs) isolated from human blood samples. Using machine learning approaches, the data generated can be used to attempt to separate different patient and control groups, subgroups within a patient cohort, and identify differences in intracellular metabolites which may provide clues about disease mechanisms.

Source: Gan E, Stoker M, Guo E, Morten KJ, Xu J. Using Single-Cell Raman Microspectroscopy to Profile Human Peripheral Blood Mononuclear Cells. Methods Mol Biol. 2025;2920:29-37. doi: 10.1007/978-1-0716-4498-0_3. PMID: 40372676. https://link.springer.com/protocol/10.1007/978-1-0716-4498-0_3

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)