Imaging flow cytometry for automated detection of hypoxia-induced erythrocyte shape change in sickle cell disease

Eduard J. Van Beers, Leigh Samsel, Laurel Mendelsohn, Rehan Saiyed, Kleber Y. Fertrin, Christine A. Brantner, Mathew P. Daniels, James Nichols, J. Philip McCoy, Gregory J. Kato

Research output: Contribution to journalArticle

Abstract

In preclinical and early phase pharmacologic trials in sickle cell disease, the percentage of sickled erythrocytes after deoxygenation, an ex vivo functional sickling assay, has been used as a measure of a patient's disease outcome. We developed a new sickle imaging flow cytometry assay (SIFCA) and investigated its application. To perform the SIFCA, peripheral blood was diluted, deoxygenated (2% oxygen) for 2 hr, fixed, and analyzed using imaging flow cytometry. We developed a software algorithm that correctly classified investigator tagged "sickled" and "normal" erythrocyte morphology with a sensitivity of 100% and a specificity of 99.1%. The percentage of sickled cells as measured by SIFCA correlated strongly with the percentage of sickle cell anemia blood in experimentally admixed samples (R=0.98, P≤0.001), negatively with fetal hemoglobin (HbF) levels (R=-0.558, P=0.027), negatively with pH (R=-0.688, P=0.026), negatively with pretreatment with the antisickling agent, Aes-103 (5-hydroxymethyl-2-furfural) (R=-0.766, P=0.002), and positively with the presence of long intracellular fibers as visualized by transmission electron microscopy (R=0.799, P=0.002). This study shows proof of principle that the automated, operator-independent SIFCA is associated with predictable physiologic and clinical parameters and is altered by the putative antisickling agent, Aes-103. SIFCA is a new method that may be useful in sickle cell drug development.

Original languageEnglish (US)
Pages (from-to)598-603
Number of pages6
JournalAmerican journal of hematology
Volume89
Issue number6
DOIs
StatePublished - May 2014

ASJC Scopus subject areas

  • Hematology

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    Van Beers, E. J., Samsel, L., Mendelsohn, L., Saiyed, R., Fertrin, K. Y., Brantner, C. A., Daniels, M. P., Nichols, J., McCoy, J. P., & Kato, G. J. (2014). Imaging flow cytometry for automated detection of hypoxia-induced erythrocyte shape change in sickle cell disease. American journal of hematology, 89(6), 598-603. https://doi.org/10.1002/ajh.23699