Defining therapeutic chimerism thresholds for comprehensive sickle cell disease correction in the townes mouse model Free

Sickle cell disease (SCD) is caused by a point mutation in the beta-globin gene, resulting in the production of an abnormal hemoglobin variant known as sickle hemoglobin (HbS). This variant profoundly alters red blood cell (RBC) characteristics and function, leading to severe anemia, painful vaso-occlusive crises, progressive organ damage, poor quality of life and a significantly reduced life expectancy. Recent advances in gene therapy aim to restore healthy RBC function by genetically editing blood-producing hematopoietic stem cells (HSCs) to either correct the disease-causing mutation or reactivate fetal hemoglobin as a substitute for the defective sickle hemoglobin. However, with current approaches, only a fraction of the HSC compartment is edited, leading to a mixture of corrected and sickle RBCs in the peripheral blood. Some mathematical models and human case studies^1-4 suggest that a chimerism of as little as 20% corrected HSCs may be sufficient to eliminate sickle RBCs and HbS from the blood. Yet, the minimum proportion of corrected HSCs needed to effectively alleviate most other clinical complications of SCD remains unclear.

In this study, we utilized the Townes SCD mouse model to generate mixed hematopoietic chimeras by transplanting mixtures of SCD:wild-type donor HSCs at varying ratios. Once stable chimerism was achieved in the recipient mice (16 weeks post-transplantation), we investigated the relationship between healthy donor chimerism, HbS levels, the proportion of sickle RBCs in peripheral blood, and a range of SCD pathological manifestations. We assessed 66 Townes HbSS mice, which exhibited mixed hematopoietic chimerism ranging from 0% to 98% wild-type donor cells in the bone marrow HSC compartment. This chimerism was also mirrored in peripheral blood myeloid cells, which, due to their rapid turnover, serve as a direct measure of ongoing HSC activity and are easily monitored through minimally invasive sampling—a key advantage for clinical settings.

Our findings revealed that as little as 2–3% wild-type HSC chimerism was sufficient to reduce sickle RBC proportions and HbS levels in the blood by 50%. Near-complete elimination of sickle RBCs and HbS in the blood was observed at wild-type HSC chimerism levels of 10–30%, accompanied by significant improvement in most other pathological phenotypes. Specifically, hemolysis, extramedullary hematopoiesis in the spleen, and liver pathology markers showed near-complete resolution above 30% HSC chimerism. Other pathological manifestations, such as anemia, also improved significantly with increasing chimerism but required a higher proportion of wild-type HSCs to fully normalize. Notably, a minimum of 40% HSC chimerism was needed to raise blood hemoglobin levels by 1 g/dL relative to pre-transplantation values.

Our study, which mimics clinical bone marrow transplantation, provides valuable insights into how HSC chimerism impacts SCD pathology. While affirming that 20-30% wild-type HSCs can abolish sickling red blood cells in peripheral blood, our comprehensive analysis also offers unprecedented insights into the correction of a broader spectrum of SCD complications, directly informing the refinement of therapeutic targets for successful gene therapies.

• Fitzhugh, C. D. et al. At least 20% donor myeloid chimerism is necessary to reverse the sickle phenotype after allogeneic HSCT. Blood 130, 1946–1948 (2017).

• Wu, C. J. et al. Mixed haematopoietic chimerism for sickle cell disease prevents intravascular haemolysis: Correspondence. British Journal of Haematology 139, 504–507 (2007).

• Abraham, A. et al. Relationship between Mixed Donor–Recipient Chimerism and Disease Recurrence after Hematopoietic Cell Transplantation for Sickle Cell Disease. Biology of Blood and Marrow Transplantation 23, 2178–2183 (2017).

• Altrock, P. M. et al. Mathematical modeling of erythrocyte chimerism informs genetic intervention strategies for sickle cell disease: Mathematical modeling predicts gene therapy outcomes of blood disorders. Am. J. Hematol. 91, 931–937 (2016).