The Erythrocyte Sedimentation Rate and Its Relation to Cell Shape and Rigidity of Red Blood Cells from Chorea-Acanthocytosis Patients in an Off-Label Treatment with Dasatinib

Abstract

Background: Chorea-acanthocytosis (ChAc) is a rare hereditary neurodegenerative disease with deformed red blood cells (RBCs), so-called acanthocytes, as a typical marker of the disease. Erythrocyte sedimentation rate (ESR) was recently proposed as a diagnostic biomarker. To date, there is no treatment option for affected patients, but promising therapy candidates, such as dasatinib, a Lyn-kinase inhibitor, have been identified.

Methods: RBCs of two ChAc patients during and after dasatinib treatment were characterized by the ESR, clinical hematology parameters and the 3D shape classification in stasis based on an artificial neural network. Furthermore, mathematical modeling was performed to understand the contribution of cell morphology and cell rigidity to the ESR. Microfluidic measurements were used to compare the RBC rigidity between ChAc patients and healthy controls.

Results: The mechano-morphological characterization of RBCs from two ChAc patients in an off-label treatment with dasatinib revealed differences in the ESR and the acanthocyte count during and after the treatment period, which could not directly be related to each other. Clinical hematology parameters were in the normal range. Mathematical modeling indicated that RBC rigidity is more important for delayed ESR than cell shape. Microfluidic experiments confirmed a higher rigidity in the normocytes of ChAc patients compared to healthy controls.

Conclusions: The results increase our understanding of the role of acanthocytes and their associated properties in the ESR, but the data are too sparse to answer the question of whether the ESR is a suitable biomarker for treatment success, whereas a correlation between hematological and neuronal phenotype is still subject to verification.

Keywords: 3D shapes; acanthocytes; cell rigidity; dasatinib; erythrocyte sedimentation rate; mesoscopic modeling; microfluidics; phase diagram.

Figure 1

The course of the off-label treatment of two ChAc patients with dasatinib. The diagram depicts the temporal information of the treatment with the sampling time points of the measurements performed within this study. The insert shows the structural formula of the Lyn-kinase inhibitor dasatinib.

Figure 2

Measurements of the ESR with the standard Westergren method using EDTA blood. (A) Plots of the color-coded sedimentation curves retrieved from optical images taken every minute, i.e., the density of the data points corresponds approximately to the printed resolution. (B) Comparison of the sedimentation height after 2 h, which was proposed to be a diagnostic biomarker [10]. Please note that panels (A,B) are logarithmic plots. (C) Representative micrographs of sedimented RBCs forming aggregates on a coverslip. RBC are diluted in plasma, forming a hematocrit of approximately 45% in the 2D layer on the coverslip. The cyan-framed area is an example to indicate a ‘hole’.

Figure 3

Classification of RBC morphology by an artificial neural network (ANN). (A) Panel A shows 3D-rendered RBCs based on confocal stack recordings. We present the comparison of acanthocytes on the left and echinocytes on the right, as classified by the ANN. (B) Panel B depicts the quantification of the morphological classification for a representative healthy control, a pooled control of 10 donors and the two ChAc patients for the three sampling time points. (C) In panel C, the acanthocyte number is plotted against the ESR for the two ChAc patients. There is no correlation between the parameters (slope of the linear regression is not significantly different from zero (p = 0.8)).

Figure 4

2D modeling of RBC aggregation to better understand the dependence of characteristic hole size on the aggregation strength and fraction of acanthocytes. The larger the hole size, the faster the ESR. (A) Panel A shows hole sizes when only the interaction energy varies. An increase in the interaction energy mimics an increase in the plasma protein concentration, mainly the fibrinogen. (B) Panel B represents the situation of a variable number of acanthocytes, whereas acanthocytes have a different shape and are completely rigid. (C) Panel C depicts the situation when the interaction energy is constant, and all cells have the same discocyte shape, but the number of rigidified cells increases. ** refers to a significance level of p < 0.01, *** to p < 0.001 and **** to p < 0.0001. The abbreviation ns stands for not significant. (D,E) are example images for 20% acanthocytes and 20% rigidified cells respectively, as presented in panels (B,C). For a better visualization, the holes are marked in a variety of false colors. The scale bar refers to 100 µm.

Figure 5

Investigation of RBC shapes in microfluidic flow. (A) Panel A shows the flow shapes of healthy RBCs (normocytes) on the left and a variety of acanthocytes on the right. (B) Panel B compares representative phase diagrams of a healthy control donor on the left and an (untreated) ChAc patient on the right, with the fitted exponential changes in the cell numbers. The transition point, where the number of croissants and slippers is identical, is marked with brown circles. (C) Panel C compares the transition points of a cohort of healthy controls and untreated ChAc pa-tients, indicating a higher rigidity of the normocytes in ChAc patients. * refers to a significance level of p < 0.05. (D) Panel D depicts the variance of the deformation parameter, d, of the acan-thocytes of different donors in flow.