Platelet aggregates detected using quantitative phase imaging associate with COVID-19 severity

Author:

Klenk ChristianORCID,Erber Johanna,Fresacher DavidORCID,Röhrl StefanORCID,Lengl Manuel,Heim DominikORCID,Irl HedwigORCID,Schlegel MartinORCID,Haller BernhardORCID,Lahmer Tobias,Diepold Klaus,Rasch SebastianORCID,Hayden OliverORCID

Abstract

Abstract Background The clinical spectrum of acute SARS-CoV-2 infection ranges from an asymptomatic to life-threatening disease. Considering the broad spectrum of severity, reliable biomarkers are required for early risk stratification and prediction of clinical outcomes. Despite numerous efforts, no COVID-19-specific biomarker has been established to guide further diagnostic or even therapeutic approaches, most likely due to insufficient validation, methodical complexity, or economic factors. COVID-19-associated coagulopathy is a hallmark of the disease and is mainly attributed to dysregulated immunothrombosis. This process describes an intricate interplay of platelets, innate immune cells, the coagulation cascade, and the vascular endothelium leading to both micro- and macrothrombotic complications. In this context, increased levels of immunothrombotic components, including platelet and platelet-leukocyte aggregates, have been described and linked to COVID-19 severity. Methods Here, we describe a label-free quantitative phase imaging approach, allowing the identification of cell-aggregates and their components at single-cell resolution within 30 min, which prospectively qualifies the method as point-of-care (POC) testing. Results We find a significant association between the severity of COVID-19 and the amount of platelet and platelet-leukocyte aggregates. Additionally, we observe a linkage between severity, aggregate composition, and size distribution of platelets in aggregates. Conclusions This study presents a POC-compatible method for rapid quantitative analysis of blood cell aggregates in patients with COVID-19.

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

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