Abstract

Background: Sickle cell disease (SCD) is a chronic life threatening autosomal recessive disorder, caused by the presence of structurally abnormal adult hemoglobin S (HbS). Under low oxygen saturation, HbS forms hemoglobin polymers that deform the red blood cell structure, referred to as ‘sickling’. Sickled erythrocytes result in hemolytic anemia and recurrent vaso-occlusive crisis, which lead to long-term morbidity and ultimate early death. The patient specific pO2 at which sickling starts (PoS) along with RBC deformability at normoxia (EImax) and upon deoxygenation (EImin) can be measured by oxygen gradient ektacytometry (Laser Optical Rotational Red Cell Analyzer (LoRRca)). In the GenoMed4ALL project, oxygen gradient ektacytometry data will be integrated with genomics, metabolomics and clinical data of 1000 SCD patients. This will allow better characterization of SCD and development of Artificial Intelligence (AI) algorithms for personalized medicine. Aims: To analyze the correlation of Lorrca parameters (PoS, EImax and EImin) with SCD genotypes (SS, Sβo, SC and Sβ+), hydroxyurea treatment (HU-, HU+) and HbF. Methods: SCD patients with SS, Sβo, SC and Sβ+ genotypes, older than 1yo at steady state with no transfusion in the last 3 months were analyzed by oxygen gradient ektacytometry. All samples were processed in duplicates. Derived parameters were correlated with genotypes, and for severe SCD (SS, Sβo) with hydroxyurea options (HU-, HU+) and HbF. An Anova analysis has been carried out to test the relation of the parameters among groups. The post-hoc test Scheffe has been used to test which groups are different two by two. Results:: 49 samples were analyzed: 32 SS, 2 Sβo, 12 SC and 3 Sβ+. Mean and standard deviation values for PoS, EImax and EImin are shown in Table 1. PoS and EImin allowed patients’ clustering in 2 groups according to genotype: SS PoS: 34.34±5.0 Elmin: 0.23±0.1 vs Sβo, SC and Sβ+ SS PoS: 24.62±3.7 and Elmin: 0.34±0.1. EImin showed statistically significant Scheffe test value in discriminating SS vs Sßo and SS vs SC, while PoS was statistically significant only in discriminating SS vs SC. 31 samples from severe SCD patients (SS, Sβo) were further analyzed for correlation with HU (7 HU-, 24 HU+) and HbF. Mean and SD values are shown in Table 1. The differences in mean values for PoS, EImax and EImin between HU- and HU+ were of -27%, 54% and 135% respectively. The best correlation between Lorrca parameters and HbF was found in group of patients without treatment (HU-). EImin showed the highest correlation being 93% in HU- and 81% in HU+ group. Image:Summary/Conclusion: Our results demonstrate the value of oxygen gradient ektacytometry to the characterization of SCD patients. PoS and Elmin were able to distinguish between SS and other genotypes, regardless of HU treatment. In addition, PoS, EImax and EImin all showed differences between HU+ and HU- groups, being Elmin the most valuable one. Elmin also showed the highest correlation with HbF. It is highly likely that PoS could be impacted by other variables: 2,3 DPG, pH, RBC hydration, genetic variants or metabolomics. Pooling data of 1000 SCD patients from at least 9 EU centers in the GenoMed4LL project is needed to improve results robustness. Standardization of Oxygenscan data generation should be ensured for data comparison and development AI algorithms for personalized medicine.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call