Rapid and Automated Quantitation of Dense Red Blood Cells: A Robust Biomarker of Therapeutic Response to Early Initiation of Hydroxyurea in Young Children with Sickle Cell Anemia

Introduction: Hydroxyurea has well-described clinical and laboratory benefits in sickle cell anemia (SCA). Traditionally, hemoglobin concentration (Hb) and fetal hemoglobin (HbF) are used to assess treatment response, but these aggregate parameters do not fully capture the range of erythrocyte abnormalities in SCA. Dense red blood cells (DRBCs) are defined as RBCs with density >1.11 g/mL as measured by density-gradient fractionation methods, which are tedious and require technical expertise. This subpopulation of dehydrated RBCs has been associated with increased SCA severity but has not been extensively studied in children. Here we describe the utility of rapid, automated DRBC quantitation and show that the percent of DRBCs (%DRBCs) is a robust biomarker of hydroxyurea response in children with SCA. Methods: The Therapeutic Response Evaluation and Adherence Trial (TREAT, NCT02286154) was a single-center prospective study that demonstrated individualized, pharmacokinetic (PK)-guided hydroxyurea dosing in young patients (mean age 12.1 months at initiation) results in robust and sustained HbF levels >30-40% for most adherent patients. The longitudinal follow-up phase of TREAT aims to comprehensively evaluate hematologic parameters and organ function to demonstrate the long-term benefits of this treatment strategy. During clinic visits (every 3-6 months), TREAT participants had complete blood counts (CBCs) with the ADVIA® 2120i system. This automated analyzer quantifies hyperchromic RBCs within seconds by directly measuring cell hemoglobin concentration, where DRBCs are known to correspond to RBCs with a measured MCHC >41 g/dL. Data were analyzed at baseline and after at least 6 months of hydroxyurea therapy (M≥6). α- and β-globin genotypes were determined for all patients. Results: Thirty-three TREAT participants had ADVIA data available for analysis (Table). All had homozygous SCA except one with sickle-β0-thalasemia; 17 (51.5%) were male. The median age at hydroxyurea initiation was 10.3 months (mean 26.1 months; range 6 months - 17 years). The median duration of hydroxyurea therapy was 27.7 months (mean 31.5). At baseline, median %DRBCs was 2.1%. Baseline %DRBCs were directly correlated with age at initiation of hydroxyurea (p=0.022) and inversely correlated with baseline HbF (p=0.001). After initiation of hydroxyurea (M≥6), there was a 47.6% reduction in %DRBCs (p=0.001). Median %DRBCs at M≥6 was directly correlated with absolute reticulocyte (ARC) (p=0.002), absolute neutrophil (ANC) (p=0.003) and platelet counts (p<0.001) and inversely correlated with Hb (p=0.013) and hematocrit (Hct) (p=0.019), consistent with the laboratory benefits of hydroxyurea. In bivariate analysis, the change in %DRBCs from baseline was directly correlated with baseline %DRBCs (p<0.001) and inversely correlated with baseline HbF (p=0.005). In multivariate analysis, baseline %DRBCs was the only biologic parameter that independently predicted %DRBC change (β=-0.86, p<0.001, model r2=0.91; Figure). Even when baseline %DRBCs were only mildly increased (as low as 1.5%), participants had a marked decline in %DRBC with hydroxyurea. When baseline %DRBCs were very low at baseline (<1.5%), they remained low after treatment. Of note, there was no correlation between %DRBC change and α-thalassemia status. Conclusions: DRBCs can be rapidly quantified without the tedium of classical density-gradient fractionation methods using the automated ADVIA 2120i hematology analyzer, which directly measures hyperchromic RBCs. These data from TREAT demonstrate the feasibility of serial %DRBC measurements in clinical trials and clinical practice. TREAT participants had low baseline DRBCs compared to untreated adult SCA patients (reported mean ≈12%), reflecting the young age of these patients. Nevertheless, there was a significant decline in %DRBCs with treatment that correlated strongly with the known laboratory benefits of hydroxyurea. In conclusion, automated DRBC measurements are a robust biomarker that can be incorporated in a panel of laboratory measurements of response to hydroxyurea (and severity of SCA). A larger, multicenter study of PK-guided hydroxyurea therapy (HOPS, NCT03789591) is currently underway in 11 US sickle cell centers and will provide generalizable data on DRBC responses with optimal hydroxyurea therapy. Disclosures Malik: Aruvant Sciences, Forma Therapeutics, Inc.: Consultancy; Aruvant Sciences, CSL Behring: Patents & Royalties. Kalfa:Agios Pharmaceuticals, Inc: Consultancy, Research Funding; Forma Therapeutics, Inc: Research Funding.

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STUDIES ON THE DESTRUCTION OF RED BLOOD CELLS. XII. FACTORS INFLUENCING THE ROLE OF S HEMOGLOBIN IN THE PATHOLOGIC PHYSIOLOGY OF SICKLE CELL ANEMIA AND RELATED DISORDERS 1

Journal of Clinical Investigation ◽

10.1172/jci103489 ◽

1957 ◽

Vol 36 (6 Pt 1) ◽

pp. 833-843 ◽

Cited By ~ 42

Author(s):

Mortimer S. Greenberg ◽

Edward H. Kass ◽

William B. Castle

Keyword(s):

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Factors Influencing ◽

Pathologic Physiology

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Elastic property of sickle cell anemia and sickle cell trait red blood cells

Journal of Biomedical Optics ◽

10.1117/1.jbo.26.9.096502 ◽

2021 ◽

Vol 26 (09) ◽

Author(s):

Endris Muhammed ◽

James Cooper ◽

Daniel Devito ◽

Robert Mushi ◽

Maria del Pilar Aguinaga ◽

...

Keyword(s):

Elastic Property ◽

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Sickle Cell Trait

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The effect of the antisickling compoundGBT1118 on the permeability of red blood cells from patients with sickle cell anemia

Physiological Reports ◽

10.14814/phy2.14027 ◽

2019 ◽

Vol 7 (6) ◽

pp. e14027 ◽

Cited By ~ 2

Author(s):

Halima Al Balushi ◽

Kobina Dufu ◽

David C. Rees ◽

John N. Brewin ◽

Anke Hannemann ◽

...

Keyword(s):

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells

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Peripheral Red Blood Cell Split Chimerism as a Consequence of Intramedullary Selective Apoptosis of Recipient Red Blood Cells in a Case of Sickle Cell Disease

Mediterranean Journal of Hematology and Infectious Diseases ◽

10.4084/mjhid.2014.066 ◽

2014 ◽

Vol 6 (1) ◽

pp. e2014066 ◽

Cited By ~ 1

Author(s):

Marco Marziali ◽

Antonella Isgrò ◽

Pietro Sodani ◽

Javid Gaziev ◽

Daniela Fraboni ◽

...

Keyword(s):

Bone Marrow ◽

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Marrow Transplant ◽

Mixed Chimerism ◽

Radical Cure ◽

Hematopoietic Stem ◽

Hematopoietic Chimerism

Allogeneic cellular gene therapy through hematopoietic stem cell transplantation is the only radical cure for congenital hemoglobinopathies like thalassemia and sickle cell anemia. Persistent mixed hematopoietic chimerism (PMC) has been described in thalassemia and sickle cell anemia. Here, we describe the clinical course of a 6-year-old girl who had received bone marrow transplant for sickle cell anemia. After the transplant, the patient showed 36% donor hematopoietic stem cells in the bone marrow, whereas in the peripheral blood there was evidence of 80% circulating donor red blood cells (RBC). The analysis of apoptosis at the Bone Marrow level suggests that Fas might contribute to the cell death of host erythroid precursors. The increase in NK cells and the regulatory T cell population observed in this patient suggests that these cells might contribute to the condition of mixed chimerism.

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Deep Learning Models for Classification of Red Blood Cells in Microscopy Images to Aid in Sickle Cell Anemia Diagnosis

Electronics ◽

10.3390/electronics9030427 ◽

2020 ◽

Vol 9 (3) ◽

pp. 427 ◽

Cited By ~ 11

Author(s):

Laith Alzubaidi ◽

Mohammed A. Fadhel ◽

Omran Al-Shamma ◽

Jinglan Zhang ◽

Ye Duan

Keyword(s):

Deep Learning ◽

Red Blood Cells ◽

Transfer Learning ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Learning Models ◽

Sickle Cells ◽

Microscopy Images

Sickle cell anemia, which is also called sickle cell disease (SCD), is a hematological disorder that causes occlusion in blood vessels, leading to hurtful episodes and even death. The key function of red blood cells (erythrocytes) is to supply all the parts of the human body with oxygen. Red blood cells (RBCs) form a crescent or sickle shape when sickle cell anemia affects them. This abnormal shape makes it difficult for sickle cells to move through the bloodstream, hence decreasing the oxygen flow. The precise classification of RBCs is the first step toward accurate diagnosis, which aids in evaluating the danger level of sickle cell anemia. The manual classification methods of erythrocytes require immense time, and it is possible that errors may be made throughout the classification stage. Traditional computer-aided techniques, which have been employed for erythrocyte classification, are based on handcrafted features techniques, and their performance relies on the selected features. They also are very sensitive to different sizes, colors, and complex shapes. However, microscopy images of erythrocytes are very complex in shape with different sizes. To this end, this research proposes lightweight deep learning models that classify the erythrocytes into three classes: circular (normal), elongated (sickle cells), and other blood content. These models are different in the number of layers and learnable filters. The available datasets of red blood cells with sickle cell disease are very small for training deep learning models. Therefore, addressing the lack of training data is the main aim of this paper. To tackle this issue and optimize the performance, the transfer learning technique is utilized. Transfer learning does not significantly affect performance on medical image tasks when the source domain is completely different from the target domain. In some cases, it can degrade the performance. Hence, we have applied the same domain transfer learning, unlike other methods that used the ImageNet dataset for transfer learning. To minimize the overfitting effect, we have utilized several data augmentation techniques. Our model obtained state-of-the-art performance and outperformed the latest methods by achieving an accuracy of 99.54% with our model and 99.98% with our model plus a multiclass SVM classifier on the erythrocytesIDB dataset and 98.87% on the collected dataset.

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Nocturnal enuresis and K+ transport in red blood cells from patients with sickle cell anemia

Haematologica ◽

10.3324/haematol.2016.149500 ◽

2016 ◽

Vol 101 (12) ◽

pp. e469-e472 ◽

Cited By ~ 3

Author(s):

S. Tewari ◽

D. C. Rees ◽

A. Hannemann ◽

O. T. Gbotosho ◽

H. W. M. Al Balushi ◽

...

Keyword(s):

Red Blood Cells ◽

Sickle Cell ◽

Sickle Cell Anemia ◽

Blood Cells ◽

Nocturnal Enuresis ◽

K Transport

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Pharmacokinetics-Based Individualized Dosing Strategy to Predict Maximum Tolerated Dose of Hydroxyurea in Children with Sickle Cell Anemia

Blood ◽

10.1182/blood.v126.23.982.982 ◽

2015 ◽

Vol 126 (23) ◽

pp. 982-982

Author(s):

Patrick T. McGann ◽

Min Dong ◽

Russell E. Ware ◽

Alexander A Vinks

Keyword(s):

Sickle Cell ◽

Sickle Cell Anemia ◽

Research Funding ◽

Maximum Tolerated Dose ◽

Serum Concentrations ◽

Individualized Dosing ◽

Clinical Benefits ◽

Dosing Strategy ◽

Sampling Times ◽

Hydroxyurea Therapy

Abstract Background: Hydroxyurea is the primary disease-modifying therapy for adults and children with sickle cell anemia (SCA). Recent NHLBI guidelines include a recommendation for expanded hydroxyurea use, particularly for young children. The laboratory and clinical benefits of hydroxyurea therapy are optimized when escalated to maximum tolerated dose (MTD), but the process of dose escalation requires expertise and frequent laboratory tests. The time to reach MTD using traditional empirical escalation usually takes >6 months, which can delay the laboratory and clinical benefits. In addition, all children with good adherence at MTD will respond to hydroxyurea, but with substantial interpatient variability in both the MTD itself and the %HbF levels achieved, suggesting important individual differences in pharmacokinetics (PK) that contribute to this phenotypic variability. Objective: The primary objective of this study was to develop an individualized Bayesian adaptive dosing strategy to reduce the time required to reach hydroxyurea MTD for children with SCA. Achieving this objective required the development of a population PK model and identification of the most informative sampling times for Bayesian estimation order to reduce the number of observations required for robust estimation of hydroxyurea PK parameters for individual patients. Methods: PK data at baseline from 96 children with SCA enrolled in the prospective Hydroxyurea Study of Long-term Effects (HUSTLE, NCT00305175) were used to develop a population PK model using nonlinear mixed effects modeling (NONMEM 7.2). Patient demographics and clinical chemistry measurements were included for covariate analyses. The final model was validated by bootstrap analysis and visual predictive check. To identify the optimal sampling times and number of samples required to robustly estimate individual PK parameters and total hydroxyurea exposure (AUC), a D-optimal design analysis was performed using the final PK model with constraints of clinical feasibility. Results: Hydroxyurea PK profiles were best described by a one compartment model with Michaelis Menten elimination and a transit absorption model. Hydroxyurea serum concentrations showed substantial interpatient variability with AUC on Day 1 ranging from 40.0 to 149.2 mg*h/L. The average AUC at MTD (mean ± SD) was 115.7 ± 34.0 mg*h/L, so this value was chosen as the target hydroxyurea AUC for the final PK model-based approach. Of the tested covariates, body weight and cystatin C were identified as significant predictors of hydroxyurea clearance, but neither serum creatinine nor estimated creatinine clearance was identified as predictors of hydroxyurea clearance. D-optimal design indicated that three serum concentrations collected at 15-20 minutes, 50-60 minutes, and 3 hours after oral administration would accurately estimate systemic hydroxyurea exposure. Figure 1 demonstrates an example from a patient, demonstrating the PK profile obtained using the sparse sampling technique (Panel A) and the modeling to predict a dose that would target a AUC of 115 mg*h/L (Panel B). Conclusions: We have established a PK model-based individualized dosing strategy to predict hydroxyurea MTD in children with SCA. Our selective sampling strategy requires only three serum samples to be collected over 3 hours and is therefore more feasible and practical, particularly for very young children, than traditional hydroxyurea PK analysis that requires frequent blood collections over 6-8 hours. This novel Bayesian approach is being prospectively evaluated in the Therapeutic Response Evaluation and Adherence Trial (TREAT, ClinicalTrials.gov NCT02286154). In TREAT, hydroxyurea concentrations are measured using HPLC after a single oral dose of 20 mg/kg, requiring only 3 fingerstick blood samples over 3 hours for accurate assessment of each patient's unique hydroxyurea PK profile. The predicted MTD is then calculated based on the amount of drug required to meet the target AUC. This strategy has the potential to individualize therapy and optimize the dose titration of hydroxyurea therapy for children with SCA, such that the laboratory and clinical benefits at MTD are achieved more quickly. Disclosures Off Label Use: Hydroxyurea is not FDA-approved for children with sickle cell anemia. Ware:Bristol Myers Squibb: Research Funding; Biomedomics: Research Funding; Eli Lilly: Other: DSMB membership; Bayer Pharmaceuticals: Consultancy.

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