Introduction: Sickle cell disease (SCD) is a genetic disorder caused by a single mutation in the beta-globin gene, resulting in abnormal sickle hemoglobin (HbS). Under low oxygen tension, HbS polymerizes within red blood cells (RBCs), causing them to sickle, the primary pathological event in SCD. Repeated sickling and unsickling of RBCs yields dehydrated RBCs known as irreversibly sickled cells (ISCs) [1]. The shortened lifespan of sickle RBCs triggers an increase in the production of reticulocytes to sustain stress erythropoiesis. These ISCs, reticulocytes, and other forms of RBCs constitute the subpopulations of sickle RBCs that are key to understanding the disease variability. We previously reported hypercoagulability of SCD blood and reduced clot strength. However, the impact of the different subpopulations of sickle RBCs on the hypercoagulability and dynamic compactness of blood clots has not been examined. Herein, we use a microfluidic dielectric sensor, termed ClotChip®, to investigate the impact of the sickle RBCs subpopulations characterized by enrichment in either reticulocytes, fetal hemoglobin (HbF), or ISC on the clotting kinetics and characteristics.

Methods: Venous blood samples from subjects with homozygous HbSS and healthy HbAA were collected in sodium citrate tubes under an IRB-approved protocol. RBCs were isolated from plasma and washed 3× in PBS. Using Percoll-renografin (76%) density gradient fractionation, we isolated three different subpopulations of RBCs in HbAA and HbSS samples that were characterized by enrichment in either reticulocyte (Top layer), HbF (Middle layer), or ISC (Bottom layer) [2]. 1mL of washed RBCs were carefully layered onto 20mL of the gradient mix and ultracentrifuged for 20 min at 35,000g and 5 °C. The subpopulations from each sample were harvested and washed 3× in PBS before reconstituting them back in their plasma at 20% Hematocrit. Samples were mixed with CaCl2 to start coagulation and immediately injected into the ClotChip®. The ClotChip® readout curve, which is defined as the temporal variation of the normalized real part of blood dielectric permittivity at 1 MHz, was obtained using a miniaturized impedance analyzer (MIA) system. Two parameters were extracted from the ClotChip® readout curve, i.e., Tpeak [3], Δεr,max [4]. Data was reported as mean ± standard deviation

Results: ClotChip® Tpeak (as a surrogate for clotting time) and Δεr,max (as a surrogate for clot strength) readout parameters for three RBCs subpopulations from HbSS (n=10) and HbAA (n=8) were analyzed. The clotting time of HbSS samples were reduced by ~40% compared to HbAA. No significant difference was observed in the clotting time across all subpopulations for HbAA; (bottom vs. middle layer vs. top layer; p=0.594, p =0.357, p=0.103 respectively). No significant difference was observed in the clotting time across all subpopulations for HbSS (bottom vs. middle layer vs. top layer; p=0.940, p=0.678, p=0.659 respectively). The clot strength of HbSS samples were reduced by ~10% across all subpopulations. There were statistical differences in HbAA (middle vs top layer; p=0.019) subpopulations; however, no differences were observed for all other subpopulations (bottom vs. middle layer; p=0.839 and bottom vs. top layer; p = 0.061). For HbSS, significant differences were observed for clot strength across all subpopulations (bottom vs. middle layer vs. top layer; p=0.024, p=0.001, p=0.000 respectively). p-values were determined using a paired t-test).

Conclusion: Our results suggest that RBC heterogeneity impacts clot strength significantly but not clotting time. In SCD, the clot strength is affected by all subpopulations of RBCs; however, reticulocyte-enriched subpopulations improved the clot strength more compared to enriched HbF and ISCs. Our findings also suggest that patient-to-patient variability in the clotting dynamics and characteristics might be due to the heterogeneous distribution of RBCs in SCD. Further investigation is needed to understand the contribution of each subpopulation of RBCs to the clinical outcomes in SCD clotting characteristics.

References:

1. Kato, G.J., et al., Nat Rev Dis Primers, 2018. 4: p. 18010.

2. Vettore, L., M.C. De Matteis, and P. Zampini,. Am J Hematol, 1980. 8(3): p. 291-7.

3. Maji, D., et al., J Thromb Haemost, 2018. 16(10): p. 2050-2056.

4. Maji, D., et al., IEEE Trans Biomed Circuits Syst, 2017. 11(6): p. 1459-1469.

Disclosures

Suster:XaTek Inc: Current equity holder in private company, Current holder of stock options in a privately-held company, Patents & Royalties, Research Funding. Gurkan:Hemex Health Inc: Consultancy, Current Employment, Current equity holder in private company, Current holder of stock options in a privately-held company, Patents & Royalties, Research Funding; DxNow Inc: Patents & Royalties; XaTek Inc: Patents & Royalties; BioChip Labs Inc: Consultancy, Current Employment, Current equity holder in private company, Current holder of stock options in a privately-held company, Patents & Royalties, Research Funding. Mohseni:XaTek Inc: Current equity holder in private company, Current holder of stock options in a privately-held company, Patents & Royalties, Research Funding.

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