Assessing the kinetics of oxygen-unloading from red cells using FlowScore, a flow-cytometric proxy of the functional quality of blood

Julija Rabcuka; Peter A Smethurst; Katharina Dammert; Jarob Saker; Gemma Aran; Geraldine M Walsh; Joanne C G Tan; Margarita Codinach; Ken McTaggart; Denese C Marks; Stephan J L Bakker; Amy McMahon; Emanuele Di Angelantonio; David J Roberts; Slawomir Blonski; Piotr M Korczyk; Atsushi Shirakami; Rebecca Cardigan; Pawel Swietach

doi:10.1016/j.ebiom.2024.105498

Assessing the kinetics of oxygen-unloading from red cells using FlowScore, a flow-cytometric proxy of the functional quality of blood

EBioMedicine. 2024 Dec 13:111:105498. doi: 10.1016/j.ebiom.2024.105498. Online ahead of print.

Authors

Julija Rabcuka¹, Peter A Smethurst², Katharina Dammert³, Jarob Saker³, Gemma Aran⁴, Geraldine M Walsh⁵, Joanne C G Tan⁶, Margarita Codinach⁷, Ken McTaggart⁸, Denese C Marks⁶, Stephan J L Bakker⁹, Amy McMahon¹⁰, Emanuele Di Angelantonio¹¹, David J Roberts¹², Slawomir Blonski¹³, Piotr M Korczyk¹³, Atsushi Shirakami¹⁴, Rebecca Cardigan¹⁵, Pawel Swietach¹⁶

Affiliations

¹ Department of Physiology, Anatomy & Genetics, University of Oxford, Oxford, UK.
² Component Development Laboratory, NHS Blood and Transplant, Cambridge, UK.
³ Sysmex Europe SE, Bornbarch 1, Norderstedt, 22848, Germany.
⁴ Cell Laboratory, Banc de Sang i Teixits, Barcelona, Spain.
⁵ Product and Process Development, Canadian Blood Services, Vancouver, Canada.
⁶ Research and Development, Australian Red Cross Lifeblood, Sydney, Australia; Sydney Medical School, University of Sydney, Camperdown, Australia.
⁷ Cell Laboratory, Banc de Sang i Teixits, Barcelona, Spain; Transfusional Medicine Group, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain.
⁸ Product and Process Development, Canadian Blood Services, Ottawa, Canada.
⁹ Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
¹⁰ British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health & Primary Care, University of Cambridge, UK; Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK; National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK.
¹¹ British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health & Primary Care, University of Cambridge, UK; Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK; National Institute for Health and Care Research Blood and Transplant Research Unit in Donor Health and Behaviour, University of Cambridge, Cambridge, UK; British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK; Health Data Science Research Centre, Human Technopole, Milan, Italy.
¹² NHS Blood and Transplant, John Radcliffe Hospital, Oxford, UK; Radcliffe Department of Medicine, University of Oxford, Oxford, UK.
¹³ Institute of Fundamental Technological Research Polish Academy of Sciences, Warsaw, Poland.
¹⁴ Medical and Scientific Affairs, Sysmex Corporation, Kobe, Japan.
¹⁵ Component Development Laboratory, NHS Blood and Transplant, Cambridge, UK; Department of Haematology, University of Cambridge, UK.
¹⁶ Department of Physiology, Anatomy & Genetics, University of Oxford, Oxford, UK. Electronic address: [email protected].

PMID: 39674089
DOI: 10.1016/j.ebiom.2024.105498

Abstract

Background: Metrics evaluating the functional quality of red blood cells (RBCs) must consider their role in oxygen delivery. Whereas oxygen-carrying capacity is routinely reported using haemoglobin assays, the rate of oxygen exchange is not measured, yet also important for tissue oxygenation. Since oxygen-unloading depends on the diffusion pathlength inside RBCs, cell geometry offers a plausible surrogate.

Methods: We related the time-constant of oxygen-unloading (τ), measured using single-cell oxygen saturation imaging, with flow-cytometric variables recorded on a haematology analyser. Experiments compared freshly-drawn RBCs with stored RBCs, wherein metabolic run-down and spherical remodelling hinder oxygen unloading.

Findings: Multivariable regression related τ to a ratio of side- and forward-scatter, referred to herein as FlowScore. FlowScore was able to distinguish, with sensitivity and specificity >80%, freshly drawn blood from blood that underwent storage-related kinetic attrition in O₂-handling. Moreover, FlowScore predicted τ restoration upon biochemical rejuvenation of stored blood. Since RBC geometry and metabolic state are related, variants of FlowScore estimated [ATP] and [2,3-diphosphoglycerate]. The veracity of FlowScore was confirmed by four blood-banking systems (Australia, Canada, England, Spain). Applying FlowScore to data from the COMPARE study revealed a positive association with the time-delay from sample collection to measurement, which was verified experimentally. The LifeLines dataset revealed age, sex, and smoking among factors affecting FlowScore.

Interpretation: We establish FlowScore as a widely-accessible and cost-effective surrogate of RBC oxygen-unloading kinetics. As a metric of a cellular process that is sensitive to storage and disease, we propose FlowScore as an RBC quality marker for blood-banking and haematology.

Funding: See Acknowledgements.

Keywords: Assay; Erythrocytes; Haematology; Oxygen transport; Storage lesion; Transfusion.