Preprint Flow Clotometry: Measuring Amyloid Microclots in ME/CFS, Long COVID, and Healthy Samples with Imaging Flow Cytometry, 2024, Pretorius

https://www.researchsquare.com/article/rs-4507472/v1

Article

Flow Clotometry: Measuring Amyloid Microclots in ME/CFS, Long COVID, and Healthy Samples with Imaging Flow Cytometry

Etheresia Pretorius Stellenbosch University Massimo Nunes Stellenbosch University Jan pretorius Douglas Kell University of Liverpool

https://doi.org/10.21203/rs.3.rs-4507472/v1



Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) has received more attention since the characterization of Long COVID (LC), a condition somewhat similar in symptom presentation and, to some extent, pathophysiological mechanisms.

A prominent feature of LC pathology is amyloid, fibrinolysis-resistant fibrin(ogen) fragments, termed microclots.

Despite prior identification of microclots in ME/CFS, quantitative analysis has remained challenging due to the reliance on representative micrographs and software processing for estimations.

Addressing this gap, the present study uses a cell-free imaging flow cytometry approach, optimized for the quantitative analysis of Thioflavin T-stained microclots, to precisely measure microclot concentration and size distribution across ME/CFS, LC, and healthy cohorts.

We refer to our cell-free flow cytometry technique for detecting microclots as 'flow clotometry'.

We demonstrate significant microclot prevalence in ME/CFS and LC, with LC patients exhibiting the highest concentration (18- and 3-fold greater than the healthy and ME/CFS groups, respectively).

This finding underscores a common pathology across both conditions, emphasizing a dysregulated coagulation system.

Moreover, relating to microclot size distribution, the ME/CFS group exhibited a significantly higher prevalence across all area ranges when compared to the controls, but demonstrated a significant difference for only a single area range when compared to the LC group.

This suggests a partially overlapping microclot profile in ME/CFS relative to LC, despite the overall higher concentration in the latter.

The present study paves the way for prospective clinical application that aims to efficiently detect, measure and treat microclots.

Health sciences/Medical research/Biomarkers/Diagnostic markers

Biological sciences/Biological techniques/Imaging/Fluorescence imaging


Expanded Key Points for Review Only

• We have recently developed a method to detect microclots in plasma samples using cell-free flow cytometry analysis, which we have coined 'flow clotometry'.
• Quantitative data presented in this paper corroborate that microclots are present in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) plasma samples at significant levels when compared to ‘healthy’ participants, and that Long COVID patients exhibit the highest concentrations of microclots, with an 18- and 3-fold change in their median compared to the healthy participants and ME/CFS group, respectively.
• The size distribution of microclots in the ME/CFS group is significantly different from that of healthy participants in all area ranges, but were only significantly different in one area range when compared to the LC group. Hence, the size distribution of microclots in ME/CFS samples is broadly comparable to that of LC samples.
• Importantly, microclots are present in an easily accessible and measurable fraction of blood, and hence the implementation of flow cytometry (clotometry) microclot assessment in the clinical setting is warranted. Such methods can provide a high throughput, and deliver quantitative information regarding both burden and size distribution of fibrinaloid microclots.

Main Key Points

• We have developed a method to detect microclots in plasma samples using cell-free flow cytometry analysis, which has been coined 'flow clotometry'.
• Quantitative data corroborate that microclots are present in myalgic encephalomyelitis/chronic fatigue samples at significant levels when compared to healthy participants

 

Does anyone know if this group have used healthy controls in their previous studies?

ETA: I only ask as if they haven't this could be the first evidence that the blood clots seen in the previous studies were not an artefact of the testing process and were genuinely in the patients blood. That is of course if the healthy control samples were collected/stored/processed/tested exactly the same as the patient samples.