In vivo evaluation of the effect of sickle cell hemoglobin S, C and therapeutic transfusion on erythrocyte metabolism and cardiorenal dysfunction

Abstract

Despite a wealth of exploratory plasma metabolomics studies in sickle cell disease (SCD), no study to date has evaluate a large and well phenotyped cohort to compare the primary erythrocyte metabolome of hemoglobin SS, SC and transfused AA red blood cells (RBCs) in vivo. The current study evaluates the RBC metabolome of 587 subjects with sickle cell sickle cell disease (SCD) from the WALK‐PHaSST clinical cohort. The set includes hemoglobin SS, hemoglobin SC SCD patients, with variable levels of HbA related to RBC transfusion events. Here we explore the modulating effects of genotype, age, sex, severity of hemolysis, and transfusion therapy on sickle RBC metabolism. Results show that RBCs from patients with Hb SS genotypes—compared to AA RBCs from recent transfusion events or SC RBCs—are characterized by significant alterations of RBC acylcarnitines, pyruvate, sphingosine 1‐phosphate, creatinine, kynurenine and urate metabolism. Surprisingly, the RBC metabolism of SC RBCs is dramatically different from SS, with all glycolytic intermediates significantly elevated in SS RBCs, with the exception of pyruvate. This result suggests a metabolic blockade at the ATP‐generating phosphoenolpyruvate to pyruvate step of glycolysis, which is catalyzed by redox‐sensitive pyruvate kinase. Metabolomics, clinical and hematological data were collated in a novel online portal. In conclusion, we identified metabolic signatures of HbS RBCs that correlate with the degree of steady state hemolytic anemia, cardiovascular and renal dysfunction and mortality.

Metabolic signatures of cardiorenal dysfunction in plasma from sickle cell patients, as a function of therapeutic transfusion and hydroxyurea treatment

“…As a result, we identified multiple signatures associated with cardiorenal dysfunction and hazard ratios, including alterations in tryptophan/kynurenine/indole metabolism, bile acid deconjugation, acyl-carnitine and S1P metabolism, glutaminolysis and mitochondrial dysfunction and L-arginine metabolism to citrulline and creatinine (Figure 7). Results are relevant in that they confirm and expand upon previous findings in the literature, linking metabolic differences 23 to clinically relevant outcomes and providing a metabolic window on clinical efficacy of common interventions like transfusion of packed RBCs and treatment with hydroxyurea. 39 For example, previous smaller scale studies had documented a beneficial effect of transfusion events in SCD in the circulating plasma and RBC metabolome, 40 though the scale of these studies was limited to a handful of recipients with no characterization of clinical relevant covariates.…”

“…Principal component analyses (PCA) and hierarchical clustering analyses (HCA) of all the metabolomics data showed a significant separation of plasma samples from individuals with SS genotypes compared to the other groups (Supplementary Figure 1.A-B). As previously noted, 23 despite double randomization of the samples and blinding of the analytical team, plasma creatinine levels measured via mass spectrometry significantly correlated with clinical measurement for this metabolite (Supplementary Figure 1.C).…”

“…An extended version of this section is provided in Supplementary Methods Extended, and our previous metabolomics report on RBC samples from the same cohort. 23 Ethical statement, blood collection, processing and storage A total of 596 SCD patients with available plasma samples were recruited as part of the Walk-PHaSST clinical trial (NCT00492531 at ClinicalTrials.gov and HLB01371616a BioLINCC study) under protocols approved by the University of Pittsburgh 9,24-28 . Clinical covariates were collected prior to plasma metabolomics analysis, including hemolysis, tricuspid regurgitation velocity (TRV), 29 parameters indicative of kidney function such as estimated glomerular filtration rate (eGFR), creatinine.…”

“…Clinical and plasma metabolomics data in this study, and RBC metabolomics data from our previous study 23 were collated into an online portal for real time data processing and figure generation. The portal, open and accessible at https://mirages.shinyapps.io/SCD2023/ serves as a repository for the data generated as part of this study, and as a tool to perform real time analyses and export of results upon correlation analyses between metabolites and clinical covariates, with the opportunity to modify filters (e.g.…”

“…To bridge this gap, here we performed a metabolomics study of plasma from 596 SCD patients, for which extensive information on patients' demographics (sex, age, BMI), genotypes, hematological and clinical characteristics, as well as therapeutic interventions (transfusion events, as inferred from HbA %; hydroxyurea treatment) were available. Results from analyses in plasma were compared against the recently characterized RBC metabolome in this cohort 23 , identifying compartment-specific metabolic signatures associated with potential novel strategies for metabolic interventions in SCD.…”