Platelet-platelet aggregates at single-event resolution as parameter in health monitoring

TL;DR

A new tool called Plateaggrate analyzes platelet aggregation at the single-event level, revealing age-related changes and validating its use for future disease studies.

Contribution

Introduces Plateaggrate, a neural network for single-event platelet aggregation analysis using imaging flow cytometry.

Findings

Plateaggrate identified a slight but significant negative correlation between platelet singlets and age.

ADP-mediated activation showed robust platelet aggregation independent of age, sex, or aggregate type.

The WPA algorithm is validated for single-event platelet aggregation analysis in future disease studies.

Abstract

Platelet analysis is crucial to assess in hemostasis, health, and disease. Current diagnostics primarily analyze bulk platelets, limiting the assessment of subtle, single-aggregate changes. We utilize Plateaggrate, a novel neuronal network-driven tool, for scoring platelet-platelet aggregation at single-event resolution using imaging flow cytometry (IFC) of labeled whole blood. This study evaluated Plateaggrate in 96 healthy human probands (61 males, 35 females; median age 39) to identify age and sex dependencies in native and ADP-stimulated platelets. Antibody-labeled platelets (CD42b and CD62P) were analyzed using IFC and segmented into singlets, doublets, triplets, and multiplets. While the weighted platelet aggregation score (WPA) showed no sex or age dependencies, Plateaggrate identified a slight but significant negative correlation of platelet singlets and total platelets with age. ADP-mediated activation, however, yielded robust platelet activation and aggregation independent of age, sex, and aggregate nature. In summary, this study validates the suitability of the WPA platelet algorithm for single-event platelet aggregation analysis in future disease patient cohorts.

•Plateaggrate, a neural network designed for analyzing single-cell platelet aggregation using imaging flow cytometry (IFC), was utilized to study platelet behavior•Key findings included a slight, yet significant, negative correlation between platelet singlets/total platelets and age•The weighted platelet aggregation (WPA) algorithm is validated for future use in analyzing single-cell platelet aggregation in disease patient cohorts

Plateaggrate, a neural network designed for analyzing single-cell platelet aggregation using imaging flow cytometry (IFC), was utilized to study platelet behavior

Key findings included a slight, yet significant, negative correlation between platelet singlets/total platelets and age

The weighted platelet aggregation (WPA) algorithm is validated for future use in analyzing single-cell platelet aggregation in disease patient cohorts

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