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. 2022 Jul 27;15(8):931.
doi: 10.3390/ph15080931.

The Occurrence of Hyperactivated Platelets and Fibrinaloid Microclots in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Jean M Nunes  1 , Arneaux Kruger  1 , Amy Proal  2 , Douglas B Kell  1   3   4 , Etheresia Pretorius  1   3
Affiliations

The Occurrence of Hyperactivated Platelets and Fibrinaloid Microclots in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

Jean M Nunes et al. Pharmaceuticals (Basel). .

Abstract

We have previously demonstrated that platelet-poor plasma (PPP) obtained from patients with Long COVID/Post-Acute Sequelae of COVID-19 (PASC) is characterized by a hypercoagulable state and contains hyperactivated platelets and considerable numbers of already-formed amyloid fibrin(ogen) or fibrinaloid microclots. Due to the substantial overlap in symptoms and etiology between Long COVID/PASC and ME/CFS, we investigated whether coagulopathies reflected in Long COVID/PASC-hypercoagulability, platelet hyperactivation, and fibrinaloid microclot formation-were present in individuals with ME/CFS and gender- and age-matched healthy controls. ME/CFS samples showed significant hypercoagulability as judged by thromboelastography of both whole blood and platelet-poor plasma. The area of plasma images containing fibrinaloid microclots was commonly more than 10-fold greater in untreated PPP from individuals with ME/CFS than in that of healthy controls. A similar difference was found when the plasma samples were treated with thrombin. Using fluorescently labelled PAC-1, which recognizes glycoprotein IIb/IIIa, and CD62P, which binds P-selectin, we observed hyperactivation of platelets in ME/CFS hematocrit samples. Using a quantitative scoring system, the ME/CFS platelets were found to have a mean spreading score of 2.72 ± 1.24 vs. 1.00 (activation with pseudopodia formation) for healthy controls. We conclude that ME/CFS is accompanied by substantial and measurable changes in coagulability, platelet hyperactivation, and fibrinaloid microclot formation. However, the fibrinaloid microclot load was not as great as was previously noted in Long COVID/PASC. Fibrinaloid microclots, in particular, may contribute to many ME/CFS symptoms, such as fatigue, seen in patients with ME/CFS, via the (temporary) blockage of microcapillaries and hence ischemia. Furthermore, fibrinaloid microclots might damage the endothelium. The discovery of these biomarkers represents an important development in ME/CFS research. It also points to possible uses for treatment strategies using known drugs and/or nutraceuticals that target systemic vascular pathology and endothelial inflammation.

Keywords: fibrinaloid microclots; hypercoagulability; myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS); platelets.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(A) Representative fluorescence micrographs of fibrinaloid microclot presence in PPP from controls and individuals with ME/CFS. Each image represents an individual sample. Images were taken at 63× machine magnification. (B) Fluorescence micrographs showing the fibrinaloid microclot scoring system used to define the load of fibrinaloid microclot severity in platelet-poor plasma (PPP). This scoring system was developed to assign a quantitative score to qualitative data. Stage 1 shows minimal fibrinaloid microclot formation as seen in healthy/control PPP, whereas Stage 4 represents a severe fibrinaloid microclot load. The bottom row represents examples of stage 4 microclots using (micrograph A) bright-field microscopy, (micrograph B) fluorescence microscopy, and (micrograph C) an overlay of fluorescence and bright-field microscopy [45]. All images within a row are a reflection of the same score. (C) Mean % area of amyloid signal between control and ME/CFS groups represented as a strip plot. The COVID vaccination status of individuals is color-coded and vaccinated participants are indicated with a blue block and those not vaccinated with an orange circle. (D) Mean % area amyloid/fibrinaloid signal between control and ME/CFS groups. A Mann–Whitney analysis yielded a significant difference (****) (p < 0.0001), with the ME/CFS group exhibiting a greater mean (1.37) than that of the controls (0.10). Statistical significance was recorded at p < 0.05. (* = p < 0.05; ** = p < 0.01; *** = p < 0.001).
Figure 1
Figure 1
(A) Representative fluorescence micrographs of fibrinaloid microclot presence in PPP from controls and individuals with ME/CFS. Each image represents an individual sample. Images were taken at 63× machine magnification. (B) Fluorescence micrographs showing the fibrinaloid microclot scoring system used to define the load of fibrinaloid microclot severity in platelet-poor plasma (PPP). This scoring system was developed to assign a quantitative score to qualitative data. Stage 1 shows minimal fibrinaloid microclot formation as seen in healthy/control PPP, whereas Stage 4 represents a severe fibrinaloid microclot load. The bottom row represents examples of stage 4 microclots using (micrograph A) bright-field microscopy, (micrograph B) fluorescence microscopy, and (micrograph C) an overlay of fluorescence and bright-field microscopy [45]. All images within a row are a reflection of the same score. (C) Mean % area of amyloid signal between control and ME/CFS groups represented as a strip plot. The COVID vaccination status of individuals is color-coded and vaccinated participants are indicated with a blue block and those not vaccinated with an orange circle. (D) Mean % area amyloid/fibrinaloid signal between control and ME/CFS groups. A Mann–Whitney analysis yielded a significant difference (****) (p < 0.0001), with the ME/CFS group exhibiting a greater mean (1.37) than that of the controls (0.10). Statistical significance was recorded at p < 0.05. (* = p < 0.05; ** = p < 0.01; *** = p < 0.001).
Figure 2
Figure 2
(A) Representative micrographs showing thrombin-induced fibrin networks stained with ThT from healthy participants and participants with ME/CFS. Each micrograph represents an individual sample. Images were taken at 63× machine magnification. (B) Strip plot showing the difference in mean fluorescence signal between control (0.11 ± 0.19) and ME/CFS (1.69 ± 1.69) PPP fibrin amyloid networks induced by exogenous thrombin. Vaccinated participants are indicated with a blue block and those not vaccinated, with an orange circle. (C) Mean fluorescent intensity of ThT signal from thrombin-induced PPP clots. A significant difference (****) between ME/CFS (1.69 ± 1.69) and controls (0.11 ± 0.19) was determined by a Mann–Whitney test. Statistical significance was recorded at p < 0.05.
Figure 3
Figure 3
(A) Representative fluorescent micrographs of hematocrit samples from ME/CFS individuals stained with PAC-1 (green fluorescence) and CD62P-PE (purple fluorescence); white areas represent overlap of the two markers. Images were taken at 63× magnification. (B) Fluorescence micrograph examples depicting the scoring system used to measure platelet activation determined by spreading, that was previously developed to score platelet activation in Long COVID/PASC patients. This scoring system functions to assign a quantitative score to qualitative data. In Stage 1 (activation with pseudopodia), platelets are minimally activated and are seen as small and round with few pseudopodia (representative of healthy/control platelets). Severe platelet activation, characterized by large, egg-shaped morphology and aggregations, is registered as Stage 4 [47] and is indicative of hyperactivated platelets. All images within a row reflect the same score. (C) Fluorescence microscopy examples of the scoring system used to assess platelet clumping. This scoring system was developed to assign a quantitative score to qualitative data. Clumping is absent in Stage 1 (representative of control samples). Conversely, severe platelet clumping is registered as Stage 4 [47]. All images within a row reflect the same score. (D) Mean quantitative scores of platelet spreading and clumping parameters in the ME/CFS group. Platelets were scored according to the scoring system depicted in Figure 3B,C.
Figure 3
Figure 3
(A) Representative fluorescent micrographs of hematocrit samples from ME/CFS individuals stained with PAC-1 (green fluorescence) and CD62P-PE (purple fluorescence); white areas represent overlap of the two markers. Images were taken at 63× magnification. (B) Fluorescence micrograph examples depicting the scoring system used to measure platelet activation determined by spreading, that was previously developed to score platelet activation in Long COVID/PASC patients. This scoring system functions to assign a quantitative score to qualitative data. In Stage 1 (activation with pseudopodia), platelets are minimally activated and are seen as small and round with few pseudopodia (representative of healthy/control platelets). Severe platelet activation, characterized by large, egg-shaped morphology and aggregations, is registered as Stage 4 [47] and is indicative of hyperactivated platelets. All images within a row reflect the same score. (C) Fluorescence microscopy examples of the scoring system used to assess platelet clumping. This scoring system was developed to assign a quantitative score to qualitative data. Clumping is absent in Stage 1 (representative of control samples). Conversely, severe platelet clumping is registered as Stage 4 [47]. All images within a row reflect the same score. (D) Mean quantitative scores of platelet spreading and clumping parameters in the ME/CFS group. Platelets were scored according to the scoring system depicted in Figure 3B,C.
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References

    1. Bested A.C., Marshall L.M. Review of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: An evidence-based approach to diagnosis and management by clinicians. Rev. Environ. Health. 2015;30:223–249. doi: 10.1515/reveh-2015-0026. - DOI - PubMed
    1. Clayton E.W. Beyond myalgic encephalomyelitis/chronic fatigue syndrome: An IOM report on redefining an illness. JAMA. 2015;313:1101–1102. doi: 10.1001/jama.2015.1346. - DOI - PubMed
    1. Johnston S., Brenu E.W., Staines D., Marshall-Gradisnik S. The prevalence of chronic fatigue syndrome/myalgic encephalomyelitis: A meta-analysis. Clin. Epidemiol. 2013;5:105–110. doi: 10.2147/CLEP.S39876. - DOI - PMC - PubMed
    1. Lim E.J., Ahn Y.C., Jang E.S., Lee S.W., Lee S.H., Son C.G. Systematic review and meta-analysis of the prevalence of chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) J. Transl. Med. 2020;18:100. doi: 10.1186/s12967-020-02269-0. - DOI - PMC - PubMed
    1. Jason L.A., Mirin A.A. Updating the National Academy of Medicine ME/CFS prevalence and economic impact figures to account for population growth and inflation. Fatigue Biomed. Health Behav. 2021;9:9–13. doi: 10.1080/21641846.2021.1878716. - DOI

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