Blood Rheological Characterization of β-Thalassemia Trait and Iron Deficiency Anemia Using Front Microrheometry

fphys-12-761411 October 18, 2021 Time: 15:8 # 1 ORIGINAL RESEARCH published: 21 October 2021 doi: 10.3389/fphys.2021.761411 Edited by: Paola Bianchi, IRCCS Ca’ Granda Foundation Maggiore Policlinico Hospital, Italy Reviewed by: Pedro Moura, Karolinska Institutet (KI), Sweden Giovanna Tomaiuolo, University of Naples Federico II, Italy *Correspondence: Lourdes Méndez-Mora [email protected] Specialty section: This article was submitted to Red Blood Cell Physiology, a section of the journal Frontiers in Physiology Received: 19 August 2021 Accepted: 30 September 2021 Published: 21 October 2021 Citation: Méndez-Mora L, Cabello-Fusarés M, Ferré-Torres J, Riera-Llobet C, Krishnevskaya E, Trejo-Soto C, Payán-Pernía S, Hernández-Rodríguez I, Morales-Indiano C, Alarcón T, Vives-Corrons J-L and Hernandez-Machado A (2021) Blood Rheological Characterization of β-Thalassemia Trait and Iron Deficiency Anemia Using Front Microrheometry. Front. Physiol. 12:761411. doi: 10.3389/fphys.2021.761411 Blood Rheological Characterization of β-Thalassemia Trait and Iron Deficiency Anemia Using Front Microrheometry Lourdes Méndez-Mora1*, Maria Cabello-Fusarés2, Josep Ferré-Torres1, Carla Riera-Llobet1, Elena Krishnevskaya3, Claudia Trejo-Soto4, Salvador Payán-Pernía5, Inés Hernández-Rodríguez6, Cristian Morales-Indiano7, Tomas Alarcón2,8,9, Joan-Lluis Vives-Corrons3and Aurora Hernandez-Machado1,2,10 1Department of Condensed Matter Physics, University of Barcelona, Barcelona, Spain, 2Centre de Recerca Matemàtica, Barcelona, Spain, 3Red Cell Pathology and Hematopoietic Disorders (Rare Anemias) Unit, Josep Carreras Leukaemia Research Institute, Badalona, Spain, 4Instituto de Física, Pontificia Universidad Católica de Valparaiso, Valparaiso, Chile, 5Red Blood Cell Disorders Unit, Hematology Department, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS/CSIC), Seville, Spain, 6Hematology Service, Institut Català d’Oncologia, Germans Trias i Pujol University Hospital, Badalona, Spain, 7Laboratory Medicine Department, Laboratori Clínic Metropolitana Nord, Hospital Universitari Germans Trias i Pujol, Badalona, Spain, 8Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain, 9Departament de Matemàtiques, Universitat Autónoma de Barcelona, Bellaterra, Spain, 10 Institute of Nanoscience and Nanotechnology, University of Barcelona, Barcelona, Spain The purpose of this work is to develop a hematocrit-independent method for the detection of beta-thalassemia trait (β-TT) and iron deficiency anemia (IDA), through the rheological characterization of whole blood samples from different donors. The results obtained herein are the basis for the development of a front microrheometry point-of-care device for the diagnosis and clinical follow-up of β-TT patients suffering hematological diseases and alterations in the morphology of the red blood cell (RBC). The viscosity is calculated as a function of the mean front velocity by detecting the sample fluid-air interface advancing through a microfluidic channel. Different viscosity curves are obtained for healthy donors, β-TT and IDA samples. A mathematical model is introduced to compare samples of distinct hematocrit, classifying the viscosity curve patterns with respect to the health condition of blood. The viscosity of the fluid at certain shear rate values varies depending on several RBC factors such as shape and size, hemoglobin (Hb) content, membrane rigidity and hematocrit concentration. Blood and plasma from healthy donors are used as reference. To validate their potential clinical value as a diagnostic tool, the viscosity results are compared to those obtained by the gold-standard method for RBC deformability evaluation, the Laser-Optical Rotational Red Cell Analyzer (LoRRCA). Keywords: beta-thalassemia trait, iron deficiency (anemia), anemia, hemorheology, rheology, microfluidics, blood rheology, microrheometer Frontiers in Physiology | www.frontiersin.org 1October 2021 | Volume 12 | Article 761411 fphys-12-761411 October 18, 2021 Time: 15:8 # 2 Méndez-Mora et al. Rheological Characterization of β-TT and IDA INTRODUCTION Blood is a biological fluid composed of red blood cells (RBCs), white blood cells (WBC), and platelets suspended in plasma, a Newtonian fluid containing organic molecules, proteins and salts (Baskurt and Meiselman, 2003). The viscosity of plasma is constant; it does not depend on the pressure that is applied onto it (Késmárky et al., 2008). Whole blood is a non-Newtonian shearthinning fluid, and its viscosity decreases when an increasing pressure is applied. WBCs and platelets can affect blood rheology but, under normal conditions, RBCs represent most of the cellular components and make the biggest contribution to viscosity (Pop et al., 2002). As a result, the viscosity of blood depends mostly on the ability of RBCs to deform under circulation flow (Baskurt and Meiselman, 2003;Cokelet and Meiselman, 2007;Mehri et al., 2018). Red blood cells have a characteristic discoid shape with a biconcave profile, under normal physiological conditions; the well-known discocyte shape (Diez-Silva et al., 2010). This shape combines a large area to volume ratio, which is an important factor to maximize oxygen diffusion. The erythrocytes have a unique ability to deform and pass through small capillaries before rapidly recovering their initial shape. The deformation capacity of RBCs is mainly due to three factors; their large area to volume ratio; the viscosity of the intracellular fluid that is dominated by the presence of hemoglobin and the viscoelastic properties of the cell membrane (Lázaro et al., 2013;Tomaiuolo, 2014). However, the deformability of RBCs is impaired in some pathological conditions as a result of defects in cell membrane skeletal architecture (Faustino et al., 2019;Hymel et al., 2020), erythrocyte aging (Diez-Silva et al., 2010;Simmonds et al., 2013), and mechanical damage (Rico et al., 2018). β-thalassemia syndromes are a heterogeneous group of genetic conditions characterized by reduced or abolished synthesis of the hemoglobin subunit beta (hemoglobin beta chain). The β-thalassemia carrier state is also referred as heterozygous β-thalassemia or β-thalassemia trait (β-TT) (Galanello and Origa, 2010). When β-TT is present, RBCs show rheological abnormalities (Berga et al., 1989). The RBC membrane can be affected due to a selective interaction between the α-chain excess and the erythrocyte membrane cytoskeleton (Rachmilewitz and Kahane, 1980), while other alterations are caused by hemoglobin denaturalization (Fiorelli et al., 1996). In addition, microcytosis, or decreased mean corpuscular volume (MCV) of RBCs, is present in β-TT carriers. Previous works suggest that the decreased RBC deformability is probably due to microcytosis (Rasia et al., 1986;Iborra et al., 2003). More recently, by comparing two non-healthy sets of samples, of iron deficiency anemia (IDA) (DeLoughery, 2017) and β-thalassemia trait, a study based on ektacytometry showed two distinct deformation patterns, indicating that the observed decrease in the deformability is not only due to microcytosis (Payán-Pernía et al., 2021). Osmotic gradient ektacytometry measures RBC deformability under defined shear stress as a function of suspending medium osmolarity (Llaudet-Planas et al., 2018). IDA and β-TT are two very common causes of microcytic hypochromic anemia in the Mediterranean region (Galanello and Origa, 2010). Alterations in the deformation capacity of RBCs can produce changes in the non-linear rheological behavior of the whole blood; these alterations are potentially detectable via a rheometry study. Rheological measurements are usually performed with rotational rheometers, a type of shear rheometer (Macosko, 1994). However, this type of equipment is expensive, requires a considerable laboratory space and must be operated by trained personnel. Moreover, the measurements take several minutes and need a large sample amount. For these reasons, there is a demand for Point-of-care (PoC) devices for analyzing the rheological properties of whole blood. To be efficient and cost-effective, many portable PoC devices employ microfluidic devices that generally consist of low-cost microfluidic chips, that are easy to fabricate and are made of glass, polydimethylsiloxane (PDMS) and other polymeric materials that are biocompatible and widely available. The microfluidic approach permits to obtain a high precision measurement of blood conditions in motion with only one drop of blood, in a time and cost-effective way in comparison to rotational rheometers (Davies and Stokes, 2008;Pipe and McKinley, 2009;Choi and Park, 2010;Galindo-Rosales et al., 2012). Many applications that aim at analyzing the properties of the blood through its rheological characterization, employ microfluidic devices that measure the behavior of blood as a function of the shear rate (Srivastava and Burns, 2006;Fedosov et al., 2011;Tomaiuolo, 2014;Rico et al., 2018;RodriguezVillarreal et al., 2020). In addition, some microfluidic applications permit the observation of the flow of blood under high confinement conditions (Davies and Stokes, 2008;Bartolo and Aarts, 2012;Lázaro et al., 2014). PoC diagnostics, including microfluidic tools, are very promising for early detection of different diseases, and for the monitoring of health conditions. In this work, a PoC front-microrheometer with electronic detection is used to characterize blood samples from different donors. The viscosity value as a function of the shear rate of the blood front is measured, details on the mathematical model developed can be found in previous works (Trejo-Soto et al., 2017,Trejo-Soto et al., 2018;Méndez-Mora et al., 2021). Three types of samples are analyzed: control samples from healthy donors, and blood samples from IDA and β-TT patients. Due to the morphological and membrane differences of the RBCs in the three groups, it is expected to obtain a distinctive viscosity pattern for each group. As it is expected that RBCs volume has an impact on blood viscosity, and the microcytosis is present in IDA and β-TT blood donors, the samples are classified in terms of the MVC of their RBCs, ensuring that microcytosis does not mask other rheological effects. The main purpose of this study is to demonstrate that the micro-rheometer developed can differentiate distinct hematological pathologies, regardless their hematocrit percentage. This is done by the differentiation, through whole-blood viscosity, between two very common conditions that affect RBCs, IDA, and β-TT, beyond the effect of the low MCV that characterizes both of them, and after hematocrit normalization. The research represents and advancement in the development of PoC devices for the diagnosis of anemia-related Frontiers in Physiology | www.frontiersin.org 2October 2021 | Volume 12 | Article 761411 fphys-12-761411 October 18, 2021 Time: 15:8 # 3 Méndez-Mora et al. Rheological Characterization of β-TT and IDA diseases. This is of global concern, since information about the precise world distribution and frequency of the inherited and acquired hemoglobin disorders is still limited (Williams and Weatherall, 2012). It is also an issue of particular interest in the developing countries, where anemia is more prevalent (Kassebaum et al., 2016). MATERIALS AND METHODS Mathematical Model The method used here to analyze the fluid flow consists of the study of the fluid-air interface advancement. Inside a microfluidic channel, the front velocity ˙ h, is the change in position of the fluid, h(t)through time along the microfluidic channel. The term h(t)is the average position of the front h(t)=1 NPN j=1hj(t), where hj(t)is the fluid front position. Shear rate, ˙ γis the normalization of mean front velocity (˙ h)according to the depth of the microchannel, b: ˙ γ= ˙ h b(1) According to the Ostwald-De Waele Power-Law model for fluids, the viscosity can be expressed as a function of shear rate: η(γ)=m˙ γn−1(2) where mis a prefactor obtained experimentally, n is a constant that depends on the studied fluid and defines the nature of its viscosity, being n =1 for Newtonian fluids. To remove the effects on viscosity caused by distinct hematocrit levels in different samples, the first step is to calculate the effective viscosity, (ηeff). This is the viscosity of blood relative to the viscosity of plasma. It consists of establishing a relation between the pressure versus shear rate fit for plasma and the sample that needs to be normalized (Trejo-Soto and Hernández-Machado, 2021). This is expressed as follows: ηeff =˙ γPlasma1PSample ˙ γSample1PPlasma (3) where 1PSample and 1PPlasma are the pressure inside the microfluidic system for the blood sample and its plasma, respectively. Analogously, ˙ γSample and ˙ γPlasma are the shear rates of the blood and plasma samples, respectively. Finally, (ηeff)is normalized with respect to the maximum hematocrit level of the studied samples. The hematocrit normalized viscosity ηhct, is calculated using the following equation: ηhct =1+ηeff −1φmax φsample (4) where φmax is the maximum hematocrit with respect to which the different samples need to be normalized. φsample is the hematocrit of the sample being normalized. Experimental Method The experimental setup used consists of a microfluidic channel with 24 gold electrodes, a pumping source, and a computer terminal (Méndez-Mora et al., 2021). A series of shear rates is obtained by applying a set of pressures on the sample fluid. The fluid front advancement is detected in a fast and accurate manner by the gold electrodes printed beneath the microfluidic channel. The microfluidic chips made of polydimethylsiloxane (PDMS) attached to glass substrates by oxygen plasma bonding. The microfluidic channel and the electrodes have been fabricated FIGURE 1 | Schematics of the microfluidic setup. A micropump is used as a pressure source. The pump is connected to the reservoir with the fluid sample using a tube. The fluid is flowing through the microchannel. The microfluidic consumable is made of PDMS sealed on a glass substrate with electrodes. Frontiers in Physiology | www.frontiersin.org 3October 2021 | Volume 12 | Article 761411 fphys-12-761411 October 18, 2021 Time: 15:8 # 4 Méndez-Mora et al. Rheological Characterization of β-TT and IDA using lithography techniques (Qin et al., 2010). The distance between electrodes is 350 µm. There are four groups of electrodes, and each has six pairs of electrodes. The distance between each group of electrodes is 8.5 mm. The channel width is ω=1000 µm height b =300 µm and the length from inlet to outlet is lc=4 cm. PDMS, glass, and Tygon tubes are biocompatible. Using a tube of an internal diameter of 254 µm and length 20 cm the pump is connected to a closed reservoir holding the fluid, and this communicates the reservoir with the microchannel. The pump is easy to control through the computer, using a simple graphic interface. Different pressures for the Fluika Pump are set to run the experiment, from 1,000 to 5,000 Pa The electrodes in the microfluidic channel are connected to a data acquisition system by a set of contact pins. As soon as the pressure starts being applied, the electronic reading is activated thanks to the controller of a myRIO National Instruments card. This tool communicates the fluidic pump and the electronic reading pins, through the computer. The sample fluid comes out of the reservoir at the set pressure and advances through the channel. As the fluid enters the microchannel and contacts the electrodes, it acts as a switch and sets the time required for the fluid front to reach each electrode pair. Using the time data and the distance between electrodes, it is possible to calculate the fluid front velocity. All these tests are performed at room temperature (∼24◦C). The way these microfluidic elements are connected is displayed in Figure 1. The experimental setup is comprised of a pumping source that connects to a fluid reservoir. The sample stored in the reservoir is pushed out through a connecting tube of radius r, and length lt. The tube transporting is connected into the microfluidic channel of rectangular cross-section, of width ωand height b. The pressures acting on the system depicted in Figure 1, relate to each other as: 1P=Pp+PH−1Pt−Pcap (5) Here 1P, the pressure drop inside the microchannel, is the summation of all the pressures involved in the experiment. The set pressure Pp, is the pressure coming from the pumping source. The hydrostatic pressure PHis the product of the density ρ, gravity g, and height of the fluid with respect to the channel height H; expressed as PH=ρgH. The pressure drop represented by the tube connection is 1Pt. The capillary pressure, Pcapis defined as the resistance that the hydrophobic channel walls oppose to the fluid advancement. Pcap is dependent on the contact angle and the surface tension of the fluid, τ. Thanks to the mass conservation principle, the flow inside the system is Q =Qt→ωb˙ h=πr2vt, where Qtand vt, are the flow and velocity inside the tube, respectively, and Q is the flow inside the channel (Méndez-Mora et al., 2021). The relation vt= ˙ hωb πr2is valid for the coupled system and 1Ptcan be written as: 1Pt=m2ltωb πr2n1 r1+n1 n+3n ˙ hn(6) Now, the effective pressure inside the system can be calculated as: Peff =m2ltωb πr2n1 r1+n1 n+3n ˙ hn =m2lt ωb2 πr2!n1 r1+n1 n+3n ˙ γn(7) The mean front velocity ˙ h, at each set pressure is experimentally obtained. By calculating velocity values and the channel dimensions, shear rate values are obtained. By fitting a curve for the relation between Peff and ˙ γ, the next relation is obtained: Peff =K(m,n)˙ γn−1(8) All the independent variables are grouped in K, which depends on the fluid properties (mand n) and the geometrical parameters of the system (ω,b,lt,r), K(m,n)=m2lt ωb2 πr2!n1 r1+n1 n+3n (9) Patients and Sample Preparation A total of five patients with IDA, 15 patients with β-TT, and 10 normal controls (healthy individuals) were included in the study. The ages range for patients was from 18 to 95 years old. None of the patients had been transfused in the previous months. IDA was considered present when serum ferritin (SF) was <15 µg/L, or when SF was <30 µg/L, and transferrin saturation index (TSI) was <20%. IDA is present when (Hb <12.0 g/dL in non-pregnant adult women and Hb <13.0 g/dL in adult men). β-TT was diagnosed if mild microcytic anemia was present in absence of iron deficiency and the Hb analysis showed an increase in HbA2 (>3.5%) with or without an increase in Hb F (if present, <5%). All subjects in the control group had normal Hb levels, RBC indices, and iron parameters. Samples were collected in ethylenediaminetetraacetic acid (EDTA) anticoagulant tubes during the course of routine analysis, shipped and stored at a temperature of 4◦C, and processed within 24 h after the extraction. Complete blood count (CBC) parameters were assessed on a Sysmex XN-10 (Sysmex Corporation) analyzer. Total iron-binding capacity (TIBC), and serum ferritin (SF) were measured on Architect ci16000 System (Abbott Laboratories). Serum iron (SI), and (TIBC) by enzymatic methods, and SF by a two-step chemiluminescent micro-particle immunoassay (CMIA). The (TSI) was calculated as the ratio of iron to TIBC. Hb analysis was performed using highperformance liquid chromatography (HPLC) on a D-10 Dual A2/F/A1c (Bio-Rad Laboratories) or capillary electrophoresis on a Capillaris-2 Flex Piercing (Sebia). The use of the samples was authorized by the Bioethics Committee of the University of Barcelona (IRB 00003099) and the Ethics Committee of IJC [Comité Ético de Investigación Clínica (CEIC)]. Samples with different hematocrit concentrations were manually prepared by properly mixing plasma and RBC in the desired ratio. To obtain plasma, whole blood samples were centrifuged at 2,500 rpm for 5 min. The plasma that rests at the top is collected with a pipette. The different hematocrit Frontiers in Physiology | www.frontiersin.org 4October 2021 | Volume 12 | Article 761411 fphys-12-761411 October 18, 2021 Time: 15:8 # 5 Méndez-Mora et al. Rheological Characterization of β-TT and IDA 0 1000 2000 3000 4000 5000 6000 7000 0 5 10 15 20 25 Effecve Pressure, Peff (Pa) Shear rate, (s⁻¹) CN at 35%hct CN at 30%hct CN at 25%hct Plasma FIGURE 2 | Effective pressure vs. shear rate for blood from a healthy donor at different hematocrit levels. concentrations hct (%) are prepared by taking plasma previously separated from whole blood and then adding to it the desired volume of RBCs corresponding to each hematocrit percentage. The sample volume prepared for each individual experiment is 500 µL. RESULTS AND DISCUSSION Blood Viscosity Normalization by Hematocrit The hematocrit value in blood samples has a high impact on blood viscosity differences between different patients with the same blood conditions (Baskurt and Meiselman, 2003). Heterogeneity across patients regarding blood viscosity is expected to be present, mostly due to variations in hematocrit, hct (%). To observe differences in viscosity caused by blood abnormalities and be able to compare the blood viscosity curve of different patients, blood viscosity needs to be normalized to account for variations in hematocrit. To validate the normalization procedure, we first take a control sample (CN) from a healthy donor and prepare three different hct (%): 35%, 30%, and 25%. Viscosity is calculated for each hematocrit using Eq. 2. By using Eqs. 3, 4, the effects of hematocrit are removed. The effective pressure, Peff as a function of the shear rate, ˙ γfor each prepared hematocrit and plasma are presented in Figure 2. As seen in Figure 2, the shear rate, which is the normalization of the front velocity respect to the channel height, increases as the hct (%) value decreases under constant pressure conditions. Plasma has the highest front velocity when the same pressure is applied. Once the mean front velocity associated with each set pressure has been measured, it is possible to calculate the effective viscosity for the different hematocrit samples according to their plasma. The effective viscosity, ηeff is calculated using Eq. 3. The effective viscosity ηeff depends on plasma viscosity. The result is shown in Figure 3. The normalization of viscosity according to hematocrit can be done by applying Eq. 4, which takes the highest hematocrit from the sample measured and compares it to the reduced hematocrit samples. Since the samples come from the same donor, if the equations were properly deduced, all curves must collapse onto a single viscosity curve for all the hematocrit levels, meaning that the differences observed before are only due to hematocrit FIGURE 3 | Effective viscosity vs. shear rate for different hematocrit of healthy blood from a single healthy donor (CN). Frontiers in Physiology | www.frontiersin.org 5October 2021 | Volume 12 | Article 761411 fphys-12-761411 October 18, 2021 Time: 15:8 # 6 Méndez-Mora et al. Rheological Characterization of β-TT and IDA 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 0 5 10 15 20 25 Hematocrit normalized viscosity, ηhct (mPa·s) Shear rate, (s⁻¹) CN at 35%hct CN at 30%hct CN at 25%hct FIGURE 4 | Hematocrit normalized viscosity vs. shear rate for different hematocrit percentages from a single healthy donor (CN). variations. The hematocrit normalized viscosity, ηhct is presented in Figure 4. The results presented in Figure 4, indicate that the method employed is useful to remove effects caused by hematocrit differences. Furthermore, it will be helpful to contrast with samples that show differences related to RBCs count and abnormalities affecting the cells in suspension. The shear rate response for each sample will depend, mostly, on the percentage of RBCs present in suspension. This response can also be affected by the presence of abnormalities developed by the blood cells, such as in β-TT. To validate the normalization of viscosity for non-healthy donors, the same experiment is conducted with β-TT samples. For validation, three hematocrit percentages (25%,30%,and 35% hct)from a single β-TT patient are prepared. Note that β-TT samples are tested at lower ˙ γto avoid hemolysis. The effective viscosity, ηeff is calculated for each hematocrit using Eq. 3. The resulting curves are presented in Figure 5. After calculating ηeff, hematocrit normalized viscosity, ηhct is calculated using Eq. 4. By taking φmax =35% hct, a normalized curve for β-TT is obtained, it is presented in Figure 6. The results obtained in Figures 4,6demonstrate that the method presented makes it possible to normalize different samples by hematocrit, regardless of their health condition. Using this normalization, curves for diverse pathologies could be compared without the effects of different hematocrit levels. For comparison purposes, we contrast both curves (healthy donors and β-TT donors) in Figure 7, where the measurements obtained for each patient collapse into well differentiated curves. Moreover, the method used to measure viscosity allows us to obtain points at low shear rates, giving us the advantage to observe the shear-thinning behavior of blood. This also makes it possible to observe that viscosity values are larger at low ˙ γ for β-TT than for healthy samples. The hematocrit normalized viscosity curves obtained in Figure 6 for β-TT show higher viscosity than the control samples in Figure 4. Study of Beta-Thalassemia Trait Samples When beta-thalassemia is present, RBC indices show microcytic anemia. Thalassemia major is characterized by reduced Hb level (<7 g/dl), mean corpuscular volume (MCV) >50 <70 fL and mean corpuscular hemoglobin (MCH) >12 <20 pg. Thalassemia intermedia is characterized by Hb levels between 7 and 10 g/dl, MCV between 50 and 80 fL, and MCH between 16 and 24 pg. Thalassemia minor (BT Trait) is characterized by reduced MCV and MCH, with increased Hb A2 level (Galanello 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 0246810 Effecve viscosity, ηeff (mPa·s) Shear rate, (s⁻¹) β-TT at 35%hct β-TT at 30%hct β-TT at 25%hct FIGURE 5 | Effective viscosity vs. shear rate from a patient with β-TT at three different RBCs concentrations. Frontiers in Physiology | www.frontiersin.org 6October 2021 | Volume 12 | Article 761411 fphys-12-761411 October 18, 2021 Time: 15:8 # 7 Méndez-Mora et al. Rheological Characterization of β-TT and IDA 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 0246810 Hematocrit normalized viscosity, ηhct (mPa·s) Shear rate, (s⁻) β-TT at 35%hct β-TT at 30%hct β-TT at 25%hct FIGURE 6 | Hematocrit normalized viscosity vs. shear rate for different hematocrit percentages from a single β-TT donor. et al., 1989;Galanello and Origa, 2010). To carry out this study, whole blood samples from healthy donors and patients diagnosed with β-TT are used. To avoid effects caused by the variation of microcytosis, the samples were classified into three groups, according to their MCV, as presented in Table 1. For each MCV group, five samples from different patients were tested. The effective viscosity was calculated with Eq. 3. The ηhct, obtained by using Eq. 4, for all the measured samples are TABLE 1 | Classification of β-TT and CN samples according to their MCV. Group Type MCV (fL) Lowest Beta-thalassemia 58–65 Very low Beta-thalassemia 66–70 Low Beta-thalassemia 71–75 Normal volume Healthy blood 90–92 presented in Figure 8. A tendency line indicating the average value obtained for each kind of sample is included. As seen in Figure 8,β-TT samples with the smallest MCV (58–65 fL) have a higher viscosity than β-TT samples with higher MCV (66–70 fL and 71–75 fL). This indicates that the size of the erythrocyte may be affecting the viscosity measurement results. When two or more samples have equivalent hct (%) and different MCV, it implies that the number of RBCs is greater as lower is the MCV, which generates a greater number of cell rows in the flow when circulating through the microchannel. This effect, studied in detail for healthy red blood cells in a previous work (Lázaro et al., 2019) implies a stronger RBC interaction which leads to an increase in the magnitude of the viscosity, similar to the effect on viscosity observed in Figure 8. The parameters m and ndescribing the viscosity curves, calculated using Eq. 2, for each sample included in Figure 8, are presented in Table 2. The β-TT samples with the smallest MCV values have the highest average mvalue, which equals the value of viscosity at ˙ γ=1. β-TT samples with MCV between 66 and 75 fL have very similar rheological parameters. The curves in Figure 8 differ 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 5 0 5 10 15 20 25 Hematocrit normalized viscosity, ηhct (mPa·s) Shear rate, (s⁻¹) β-TT at 35%hct β-TT at 30%hct β-TT at 25%hct CN at 35%hct CN at 30%hct CN at 25%hct FIGURE 7 | Hematocrit normalized viscosity vs. shear rate for β-TT samples and healthy blood samples. Frontiers in Physiology | www.frontiersin.org 7October 2021 | Volume 12 | Article 761411 fphys-12-761411 October 18, 2021 Time: 15:8 # 8 Méndez-Mora et al. Rheological Characterization of β-TT and IDA 0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 9,0 10,0 0,0 2,0 4,0 6,0 8,0 10,0 Hematocrit Normalised Viscosity, ηht (mPa·s) Shear rate , (s⁻¹) β-TT MCV 58-65(fL) β-TT MCV 66-70(fL) β-TT MCV 71-75(fL) CN MCV 90-92(fL) FIGURE 8 | Hematocrit normalized viscosity for β-TT and healthy control blood (CN) classified by MCV in Table 1. Whole blood is used in all cases. TABLE 2 | Average values of mand nfor healthy blood and β-TT samples according to MCV in fL. Type Group m n MCV (fL) β-TT Lowest 7.4295 0.872 58–65 β-TT Very low 5.7582 0.953 66–70 β-TT Low 5.6265 0.955 71–75 CN Normal volume 2.8272 0.880 90–92 Viscosity is normalized by hematocrit. from those of healthy blood for two reasons, because the MCV is different, and because the mechanical properties of healthy and pathological red blood cells are different. We want to verify that alterations such as the changes in cell morphology and rigidity caused by the presence of β-TT, have a direct effect on the viscosity. The normal reference range for MCV is typically 80–100 fL, but this value is altered in some conditions. Comparison of Blood Samples With Microcytic Red Blood Cells: Iron Deficiency Anemia and Beta-Thalassemia Trait Anemia is a condition in which the number of red blood cells, and consequently their oxygen-carrying capacity, is insufficient to meet the physiologic needs of the body, and it is diagnosed as a decrease in the blood hemoglobin concentration (Hb) (Vitamin and Mineral Nutrition Information System (VMNIS), 2011). Iron deficiency limits the synthesis of heme, which in turn limits the synthesis of hemoglobin (Nagababu et al., 2008;DeLoughery, 2017), as it happens in β-TT as a result of a mutation. It is also characterized by decreased ferritin, and MCV, while total ironbinding capacity and red blood cell distribution are increased. Hypochromic red blood cells can be also be observed by visual inspection on a blood smear (Wagley, 1953;DeLoughery, 2017). To confirm that the alterations seen in the viscosity of β-TT samples are not only attributed to microcytosis, we compared results obtained from samples with MCV of 66–75 fL to results of samples of IDA patients, with similar values of MCV. Using the same method as in Figure 8, we tested ten β-TT samples with MCV between 66 and 75 fL, five IDA samples with MCV between 66 and 79 fL and five samples from healthy donors with MCV between 90 and 92 fL. The results are shown in Figure 9. Figure 9 shows that despite having similar MCV, β-TT and IDA samples have different viscosity patterns. The mand n parameters describing the viscosity curve for each group are presented in Table 3. Iron deficiency anemia and β-TT curves have a different viscosity pattern even though they have similar MCV, indicating that pathological RBC conditions are reflected in viscosity, and they can be differentiated with the micro-rheometer. The IDA viscosity results show a much less Newtonian behavior; the n value differs more from 1 than that obtained with the β-TT samples. Since both diseases present Hb deficiency and RBCs with similar MCV, we conclude that the difference observed in viscosity between the β-TT and IDA cannot be considered a consequence of differences in RBC size. The higher viscosity obtained for the β-TT samples might be attributed to a greater rigidity in the RBC membrane. This can be caused by the excess of αchains that bind to the RBC membrane (DeLoughery, 2017; Payán-Pernía et al., 2021). Frontiers in Physiology | www.frontiersin.org 8October 2021 | Volume 12 | Article 761411 fphys-12-761411 October 18, 2021 Time: 15:8 # 9 Méndez-Mora et al. Rheological Characterization of β-TT and IDA 0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0 0,0 2,0 4,0 6,0 8,0 10,0 Hematocrit Normalized Viscosity, ηhct (mPa·s) Shear rate (s¯¹) β-TT MCV 66-75(fL) IDA MCV 66-79(fL) CN WB MCV 90-92(fL) FIGURE 9 | Hematocrit normalized viscosity for ten samples of β-TT, five samples of IDA and five samples from healthy donors (CN). Whole blood in all cases. TABLE 3 | Average values of mand nfor IDA and samples according to MCV after normalizing by hematocrit. Sample Type m n MCV fL β-TT Beta-thalassemia trait 5.6923 0.954 66–75 IDA Iron deficiency anemia 4.3391 0.782 66–79 Control Healthy blood 2.8272 0.880 90–92 Deformability Changes in Beta-Thalassemia Trait and Iron Deficiency Anemia To verify that the differences in viscosity found between β-TT, IDA, and healthy donors are caused by changes in the properties of RBCs, we compare the results obtained with the LoRRCA ektacytometer between the samples. By measuring the elongation index, the LoRRCA can detect elasticity changes in single cells. The measurements performed determine elongation of a huge number of RBCs utilizing laser detection, at different osmolarity values, as illustrated in Figure 10. The elongation index (EI) depicted in Figure 10 is determined by the expression: EI = A−B A+B(10) where A and B are the major and minor dimensions of the RBC, respectively. With this test, it is possible to obtain a characteristic profile of each sample, according to the deformability of the RBCs as a function of osmolarity. These results do not depend on the hematocrit value of the samples. Figure 11 shows the Osmoscan curve for the healthy subjects, IDA samples and β-TT samples. These results were previously described and differences between the three groups were statistically significant, reflecting deformability differences between these three states (Payán-Pernía et al., 2021). When β-TT is present, the ektacytometry curve is displaced to the left with respect to healthy RBC, revealing a decrease in the RBC deformability capacity. The osmotic gradient ektacytometry analysis shown in Figure 11 was performed using the Osmoscan module of the LoRRca MaxSis (RR Mechatronics). By measuring elongation index, LoRRCA can detect individual erythrocyte deformability in a mixture of RBCs. When β-TT is present, the ektacytometry curve is displaced to the left with respect to healthy RBC. IDA samples, however, show a shift that put them in between β-TT and the control samples. By observing Figures 9,11, it is possible to establish that alterations in RBC wall rigidity can be translated into viscosity changes. After normalizing the hct (%), the viscosity of samples for IDA falls below the viscosity of β-TT and over the viscosity of control samples. As seen in Figure 10,β-TT samples have a higher viscosity than control samples. This is consistent with samples that appear to have a left shift in their ektacytometry measurements. Observing the two results together lets us have a bigger picture of the effects of single cell rheology. LoRRCA is very powerful at finding individual differences within cells. The results obtained in this study, demonstrate that our method can detect the presence of these alterations through the study of the fluid front rheology of the whole blood. Therefore, the method proposed can distinguish differences between healthy blood and blood affected by pathologies that modify the red blood cell rheology. Changes in viscosity seem to have a direct relation to individual cells’ changes in β-TT. Frontiers in Physiology | www.frontiersin.org 9October 2021 | Volume 12 | Article 761411