Tag: extracellular vesicles

Proteomics and cytokine analyses distinguish myalgic encephalomyelitis/chronic fatigue syndrome cases from controls

Abstract:

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, heterogenous disease characterized by unexplained persistent fatigue and other features including cognitive impairment, myalgias, post-exertional malaise, and immune system dysfunction. Cytokines are present in plasma and encapsulated in extracellular vesicles (EVs), but there have been only a few reports of EV characteristics and cargo in ME/CFS. Several small studies have previously described plasma proteins or protein pathways that are associated with ME/CFS.

Methods: We prepared extracellular vesicles (EVs) from frozen plasma samples from a cohort of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) cases and controls with prior published plasma cytokine and plasma proteomics data. The cytokine content of the plasma-derived extracellular vesicles was determined by a multiplex assay and differences between patients and controls were assessed. We then performed multi-omic statistical analyses that considered not only this new data, but extensive clinical data describing the health of the subjects.

Results: ME/CFS cases exhibited greater size and concentration of EVs in plasma. Assays of cytokine content in EVs revealed IL2 was significantly higher in cases. We observed numerous correlations among EV cytokines, among plasma cytokines, and among plasma proteins from mass spectrometry proteomics. Significant correlations between clinical data and protein levels suggest roles of particular proteins and pathways in the disease. For example, higher levels of the pro-inflammatory cytokines Granulocyte-Monocyte Colony-Stimulating Factor (CSF2) and Tumor Necrosis Factor (TNFα) were correlated with greater physical and fatigue symptoms in ME/CFS cases. Higher serine protease SERPINA5, which is involved in hemostasis, was correlated with higher SF-36 general health scores in ME/CFS. Machine learning classifiers were able to identify a list of 20 proteins that could discriminate between cases and controls, with XGBoost providing the best classification with 86.1% accuracy and a cross-validated AUROC value of 0.947. Random Forest distinguished cases from controls with 79.1% accuracy and an AUROC value of 0.891 using only 7 proteins.

Conclusions: These findings add to the substantial number of objective differences in biomolecules that have been identified in individuals with ME/CFS. The observed correlations of proteins important in immune responses and hemostasis with clinical data further implicates a disturbance of these functions in ME/CFS.

Source: Giloteaux L, Li J, Hornig M, Lipkin WI, Ruppert D, Hanson MR. Proteomics and cytokine analyses distinguish myalgic encephalomyelitis/chronic fatigue syndrome cases from controls. J Transl Med. 2023 May 13;21(1):322. doi: 10.1186/s12967-023-04179-3. PMID: 37179299. https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-023-04179-3 (Full text)

Diagnosis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome with partial least squares discriminant analysis: Relevance of blood extracellular vesicles

Abstract:

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), a chronic disease characterized by long-lasting persistent debilitating widespread fatigue and post-exertional malaise, remains diagnosed by clinical criteria. Our group and others have identified differentially expressed miRNA profiles in the blood of patients. However, their diagnostic power individually or in combinations seems limited. A Partial Least Squares-Discriminant Analysis (PLS-DA) model initially based on 817 variables: two demographic, 34 blood analytic, 136 PBMC miRNAs, 639 Extracellular Vesicle (EV) miRNAs, and six EV features, selected an optimal number of five components, and a subset of 32 regressors showing statistically significant discriminant power. The presence of four EV-features (size and z-values of EVs prepared with or without proteinase K treatment) among the 32 regressors, suggested that blood vesicles carry relevant disease information. To further explore the features of ME/CFS EVs, we subjected them to Raman micro-spectroscopic analysis, identifying carotenoid peaks as ME/CFS fingerprints, possibly due to erythrocyte deficiencies. Although PLS-DA analysis showed limited capacity of Raman fingerprints for diagnosis (AUC = 0.7067), Raman data served to refine the number of PBMC miRNAs from our previous model still ensuring a perfect classification of subjects (AUC=1). Further investigations to evaluate model performance in extended cohorts of patients, to identify the precise ME/CFS EV components detected by Raman and to reveal their functional significance in the disease are warranted.

Source: González-Cebrián Alba, Almenar-Pérez Eloy, Xu Jiabao, Yu Tong, Huang Wei E., Giménez-Orenga Karen, Hutchinson Sarah, Lodge Tiffany, Nathanson Lubov, Morten Karl J., Ferrer Alberto, Oltra Elisa. Diagnosis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome With Partial Least Squares Discriminant Analysis: Relevance of Blood Extracellular Vesicles. Frontiers in Medicine, 9, 2022 , DOI: 10.3389/fmed.2022.842991 https://www.frontiersin.org/article/10.3389/fmed.2022.842991 (Full study)

Cytokine profiling of extracellular vesicles isolated from plasma in myalgic encephalomyelitis/chronic fatigue syndrome: a pilot study

Abstract:

Background: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating disease of unknown etiology lasting for a minimum of 6 months but usually for many years, with features including fatigue, cognitive impairment, myalgias, post-exertional malaise, and immune system dysfunction. Dysregulation of cytokine signaling could give rise to many of these symptoms. Cytokines are present in both plasma and extracellular vesicles, but little investigation of EVs in ME/CFS has been reported. Therefore, we aimed to characterize the content of extracellular vesicles (EVs) isolated from plasma (including circulating cytokine/chemokine profiling) from individuals with ME/CFS and healthy controls.

Methods: We included 35 ME/CFS patients and 35 controls matched for age, sex and BMI. EVs were enriched from plasma by using a polymer-based precipitation method and characterized by Nanoparticle Tracking Analysis (NTA), Transmission Electron Microscopy (TEM) and immunoblotting. A 45-plex immunoassay was used to determine cytokine levels in both plasma and isolated EVs from a subset of 19 patients and controls. Linear regression, principal component analysis and inter-cytokine correlations were analyzed.

Results: ME/CFS individuals had significantly higher levels of EVs that ranged from 30 to 130 nm in size as compared to controls, but the mean size for total extracellular vesicles did not differ between groups. The enrichment of typical EV markers CD63, CD81, TSG101 and HSP70 was confirmed by Western blot analysis and the morphology assessed by TEM showed a homogeneous population of vesicles in both groups. Comparison of cytokine concentrations in plasma and isolated EVs of cases and controls yielded no significant differences. Cytokine-cytokine correlations in plasma revealed a significant higher number of interactions in ME/CFS cases along with 13 inverse correlations that were mainly driven by the Interferon gamma-induced protein 10 (IP-10), whereas in the plasma of controls, no inverse relationships were found across any of the cytokines. Network analysis in EVs from controls showed 2.5 times more significant inter-cytokine interactions than in the ME/CFS group, and both groups presented a unique negative association.

Conclusions: Elevated levels of 30-130 nm EVs were found in plasma from ME/CFS patients and inter-cytokine correlations revealed unusual regulatory relationships among cytokines in the ME/CFS group that were different from the control group in both plasma and EVs. These disturbances in cytokine networks are further evidence of immune dysregulation in ME/CFS.

Source: Giloteaux L, O’Neal A, Castro-Marrero J, Levine SM, Hanson MR. Cytokine profiling of extracellular vesicles isolated from plasma in myalgic encephalomyelitis/chronic fatigue syndrome: a pilot study. J Transl Med. 2020 Oct 12;18(1):387. doi: 10.1186/s12967-020-02560-0. PMID: 33046133. https://pubmed.ncbi.nlm.nih.gov/33046133/

Circulating extracellular vesicles as potential biomarkers in chronic fatigue syndrome/myalgic encephalomyelitis: an exploratory pilot study

Abstract:

Chronic Fatigue Syndrome (CFS), also known as Myalgic Encephalomyelitis (ME) is an acquired, complex and multisystem condition of unknown etiology, no established diagnostic lab tests and no universally FDA-approved drugs for treatment. CFS/ME is characterised by unexplicable disabling fatigue and is often also associated with numerous core symptoms. A growing body of evidence suggests that extracellular vesicles (EVs) play a role in cell-to-cell communication, and are involved in both physiological and pathological processes. To date, no data on EV biology in CFS/ME are as yet available.

The aim of this study was to isolate and characterise blood-derived EVs in CFS/ME. Blood samples were collected from 10 Spanish CFS/ME patients and 5 matched healthy controls (HCs), and EVs were isolated from the serum using a polymer-based method. Their protein cargo, size distribution and concentration were measured by Western blot and nanoparticle tracking analysis. Furthermore, EVs were detected using a lateral flow immunoassay based on biomarkers CD9 and CD63.

We found that the amount of EV-enriched fraction was significantly higher in CFS/ME subjects than in HCs (p = 0.007) and that EVs were significantly smaller in CFS/ME patients (p = 0.014). Circulating EVs could be an emerging tool for biomedical research in CFS/ME. These findings provide preliminary evidence that blood-derived EVs may distinguish CFS/ME patients from HCs. This will allow offer new opportunities and also may open a new door to identifying novel potential biomarkers and therapeutic approaches for the condition.

Source: Castro-Marrero J, Serrano-Pertierra E, Oliveira-Rodríguez M, Zaragozá MC, Martínez-Martínez A, Blanco-López MDC, Alegre J. Circulating extracellular vesicles as potential biomarkers in chronic fatigue syndrome/myalgic encephalomyelitis: an exploratory pilot study. J Extracell Vesicles. 2018 Mar 22;7(1):1453730. doi: 10.1080/20013078.2018.1453730. eCollection 2018. https://www.ncbi.nlm.nih.gov/pubmed/29696075