Acanthocyte Sedimentation Rate as a Diagnostic Biomarker for Neuroacanthocytosis Syndromes: Experimental Evidence and Physical Justification

Abstract

(1) Background: Chorea-acanthocytosis and McLeod syndrome are the core diseases among the group of rare neurodegenerative disorders called neuroacanthocytosis syndromes (NASs). NAS patients have a variable number of irregularly spiky erythrocytes, so-called acanthocytes. Their detection is a crucial but error-prone parameter in the diagnosis of NASs, often leading to misdiagnoses. (2) Methods: We measured the standard Westergren erythrocyte sedimentation rate (ESR) of various blood samples from NAS patients and healthy controls. Furthermore, we manipulated the ESR by swapping the erythrocytes and plasma of different individuals, as well as replacing plasma with dextran. These measurements were complemented by clinical laboratory data and single-cell adhesion force measurements. Additionally, we followed theoretical modeling approaches. (3) Results: We show that the acanthocyte sedimentation rate (ASR) with a two-hour read-out is significantly prolonged in chorea-acanthocytosis and McLeod syndrome without overlap compared to the ESR of the controls. Mechanistically, through modern colloidal physics, we show that acanthocyte aggregation and plasma fibrinogen levels slow down the sedimentation. Moreover, the inverse of ASR correlates with the number of acanthocytes (R2=0.61, p=0.004). (4) Conclusions: The ASR/ESR is a clear, robust and easily obtainable diagnostic marker. Independently of NASs, we also regard this study as a hallmark of the physical view of erythrocyte sedimentation by describing anticoagulated blood in stasis as a percolating gel, allowing the application of colloidal physics theory.

Keywords: diagnosis; erythrocyte sedimentation rate (ESR); neuroacanthocytosis.

Figure 1

Comparison of the erythrocyte sedimentation rate (ESR) between neuroacanthocytosis patients and healthy controls. (A): ESR measurement setup: Standard Westergren tubes were filled with full blood and left to rest. The sedimentation height was measured over time. The picture was taken after 2 h. The first two tubes contain blood from an MLS patient, and the last two tubes contain blood from a healthy control donor. (B): Representative time traces of the sedimentation height for the different conditions. (C): Statistics on sedimentation height after typical times for healthy controls, chorea-acanthocytosis (ChAc) patients, and McLeod syndrome (MLS) patients. The bar height represents the average value, and the error bar depicts the range of individual values. Stars indicate the significance levels (Brown–Forsythe and Welch analysis of variance (ANOVA) test): n.s., not significant (p-value > 0.05); * p < 0.05; and ** p < 0.01. N refers to the number of patients. (D): Span of all individual sedimentation height measurements (each blood sample was measured at least in duplicate, and the blood of some patients was measured at different time points). After 2 h, a $\Delta h$ of 10 mm could be regarded as a threshold to differentiate the ChAc and MLS conditions. The number n refers to the number of individual measurements out of the same number N of patients.

Figure 2

Relation of acanthocyte counts to ESR. (A): A representative stained blood smear of a ChAc patient. (B): Representative 3D-rendered acanthocytes from the freshly fixed blood of a ChAc patient. (C): Plot of the number of acanthocytes vs. the inverse of the ESR at 2 h and the corresponding correlation analysis. (D): Plot of the number of all deformed erythrocytes (echinocytes, acanthocytes, and other unspecified cell shapes) vs. the inverse of the ESR at 2 h and the corresponding correlation analysis. Panels C and D contain measurements from nine patients (cp. Table 1), where one patient was measured twice (independent blood sampling on different days). Since none of the controls presented with acanthocytes, they are summarized in one data point with their average ESR. The plotted line represents the linear regression. The analysis reveals a significant correlation for both parameters (panels C and D, $R^2$ coefficients of 0.61 and 0.59, respectively).

Figure 3

Characteristics of sedimenting erythrocyte aggregates in autologous plasma. (A,B): Sedimented layer of erythrocytes in plasma for a control subject and a patient on the bottom of a microscopy chamber after 2 h. Pictures were taken from the bottom of the well. (A): Healthy control donor and (B): patient (MLS-3). The volume fraction (hematocrit) in the microscope slide well (inner diameter 5 mm, height 1.5 mm) was initially 0.33% to reach a volume fraction close to 45% at the bottom of the well after sedimentation. (C,D): The same pictures as the previous, but with the holes detected in the percolating network of erythrocytes highlighted with random colors. The 50 $\mathsf{\mu }$m scale is valid for panels (A) to (D). (E): Example of distributions of the square root of the hole areas, or hole diameter, shown as complementary cumulative density functions. The linear curve reflects an exponential distribution with the mean hole diameter as a single scale parameter. This scale parameter was estimated by the maximum likelihood method. (F): Statistical comparison of the scale parameters for control and neuroanthocytosis syndrome (NAS) erythrocytes in autologous plasma. The scale parameters are normally distributed among each population, and a t-test between the two populations indicates a significant difference ($p=0.005$, implying a significance level **, i.e. p < 0.01). (G): Simulation snapshot of healthy conditions with 100% discoid erythrocytes shown in black color, similarly to experimental images. (H): Simulated aggregate of a mixture of 80% normal erythrocytes (black area) and 20% acanthocytes (gray color) by area fraction. The scale bar is valid for panels (G,H). (I): Complementary cumulative density function of the square root of the hole areas from the simulations of healthy erythrocytes and the erythrocyte–acanthocyte mixture exemplified in (G,H).

Figure 3

Characteristics of sedimenting erythrocyte aggregates in autologous plasma. (A,B): Sedimented layer of erythrocytes in plasma for a control subject and a patient on the bottom of a microscopy chamber after 2 h. Pictures were taken from the bottom of the well. (A): Healthy control donor and (B): patient (MLS-3). The volume fraction (hematocrit) in the microscope slide well (inner diameter 5 mm, height 1.5 mm) was initially 0.33% to reach a volume fraction close to 45% at the bottom of the well after sedimentation. (C,D): The same pictures as the previous, but with the holes detected in the percolating network of erythrocytes highlighted with random colors. The 50 $\mathsf{\mu }$m scale is valid for panels (A) to (D). (E): Example of distributions of the square root of the hole areas, or hole diameter, shown as complementary cumulative density functions. The linear curve reflects an exponential distribution with the mean hole diameter as a single scale parameter. This scale parameter was estimated by the maximum likelihood method. (F): Statistical comparison of the scale parameters for control and neuroanthocytosis syndrome (NAS) erythrocytes in autologous plasma. The scale parameters are normally distributed among each population, and a t-test between the two populations indicates a significant difference ($p=0.005$, implying a significance level **, i.e. p < 0.01). (G): Simulation snapshot of healthy conditions with 100% discoid erythrocytes shown in black color, similarly to experimental images. (H): Simulated aggregate of a mixture of 80% normal erythrocytes (black area) and 20% acanthocytes (gray color) by area fraction. The scale bar is valid for panels (G,H). (I): Complementary cumulative density function of the square root of the hole areas from the simulations of healthy erythrocytes and the erythrocyte–acanthocyte mixture exemplified in (G,H).

Figure 4

Characteristics of sedimenting erythrocyte aggregates in various suspension media. (A,B): Sedimented layer of erythrocytes in 55 mg/mL dextran from (A): a healthy control donor and (B): a NAS patient (MLS-3). The characteristic area of the holes in the network is visibly smaller in the network of the NAS patient’s erythrocytes. As a replacement medium, we used 70 kDa dextran diluted in PBS to a final mass concentration of 55 mg/mL. (C): The measured ratio of mean hole size for the suspension media (autologous plasma and dextran diluted in PBS with a mass concentration of 55 mg/mL). The dextran concentration was empirically chosen in order to achieve a sedimentation speed as close as possible to the rate obtained in the plasma of the healthy samples. (D): Characteristic (maximal) erythrocyte sedimentation velocities, with scaling based on aggregate geometries. The bars indicate the values of the characteristic erythrocyte sedimentation velocities. For each suspension medium, the patient scaling was obtained by multiplying the characteristic speed of each patient’s erythrocytes by the ratio of the characteristic hole areas, as justified by Equation (3). While the scaled velocity in autologous plasma is significantly smaller than the characteristic speed of the control erythrocytes, the scaling lies within the same range when the autologous plasma is replaced by a dextran-based medium. n.s., not significant (p > 0.05); * p < 0.05.

Figure 5

Measurements related to the role of plasma in sedimentation. (A): Comparison of fibrinogen concentrations. A significant difference consistent with the aggregation force difference was observed. (B): Comparison of sedimentation velocities of control samples, NAS patient samples, and samples with erythrocytes and plasma exchanged. (C) 1: Schematic of the forces acting on the erythrocytes trapped in optical tweezers. (C) 2: Microphotographs of the protocol for the measurement of the aggregating force. The purple circles show the locations of external optical traps. From left to right: After being selected, erythorcytes were lifted 15 $\mathsf{\mu }$m from the microscope slide by four optical traps, one for each erythrocyte extremity. The optical traps had known trapping forces. The erythrocytes were then brought into contact. At equilibrium, the two inner traps were removed. The optical force holding the cells was decreased stepwise, and the overlap distance tended to increase in the same manner. Finally, spontaneous aggregation overcame the optical forces, and the erythrocytes escaped the trap. The trapping force at which the cells aggregated was considered to be the aggregation force. (D): Comparison of aggregation forces. A significant difference between patients and controls was observed. n.s., not significant (p > 0.05); ** p < 0.01; *** p < 0.001; and **** p < 0.0001.