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

Abstract

Metabolomics studies in sickle cell disease (SCD) have been so far limited to tens of samples, owing to technical and experimental limitations. To overcome these limitations, we performed plasma metabolomics analyses on 596 samples from patients with sickle cell sickle cell disease (SCD) enrolled in the WALK-PHaSST study. Clinical covariates informed the biological interpretation of metabolomics data, including genotypes (hemoglobin SS, hemoglobin SC), history of recent transfusion (HbA%), response to hydroxyurea treatment (HbF%). We investigated metabolic correlates to the degree of intravascular hemolysis, cardiorenal function, as determined by tricuspid regurgitation velocity (TRV), estimated glomerular filtration rate (eGFR), and overall hazard ratio (unadjusted or adjusted by age). Recent transfusion events or hydroxyurea treatment were associated with elevation in plasma free fatty acids and decreases in acyl-carnitines, urate, kynurenine, indoles, carboxylic acids, and glycine- or taurine-conjugated bile acids. High levels of these metabolites, along with low levels of plasma S1P and L-arginine were identified as top markers of hemolysis, cardiorenal function (TRV, eGFR), and overall hazard ratio. We thus uploaded all omics and clinical data on a novel online portal that we used to identify a potential mechanism of dysregulated red cell S1P synthesis and export as a contributor to the more severe clinical manifestations in patients with the SS genotype compared to SC. In conclusion, plasma metabolic signatures – including low S1P, arginine and elevated kynurenine, acyl-carnitines and bile acids - are associated with clinical manifestation and therapeutic efficacy in SCD patients, suggesting new avenues for metabolic interventions in this patient population.

Metabolic blood profile and response to treatment with the pyruvate kinase activator mitapivat in patients with sickle cell disease

“…While mitapivat was initially designed to treat hemolytic anemia in patients with PK deficiency, we showed that patients with SCD also have reduced PK enzyme activity and stability, which is consistent with the literature 5 . Previous metabolomics studies describe slightly increased levels of glycolytic intermediates upstream of PK in RBCs from patients with SCD 4,25,26 . Taken together, these findings provide a rationale for the treatment of SCD with mitapivat.…”

“… 5 Previous metabolomics studies describe slightly increased levels of glycolytic intermediates upstream of PK in RBCs from patients with SCD. 4 , 25 , 26 Taken together, these findings provide a rationale for the treatment of SCD with mitapivat. We did not observe significant differences between patients and HCs in glycolytic and PPP intermediates, except for glyceraldehyde‐3‐phosphate, 6‐phosphate gluconolactone, and pentose phosphate (and/or metabolites with the same respective mass to charge ratio, legend Figure 4 ).…”

“…Nevertheless, many observed differences between HCs and SCD patients at baseline have been previously reported in RBC content and plasma, indicating that the effects of some of these confounders can be considered minimal. 4 , 25 , 26 , 38 …”

Cardiovascular Consequences of Uremic Metabolites: an Overview of the Involved Signaling Pathways

“…267 The mechanisms involved in the sodium-glucose cotransporter-2 inhibitor-triggered delay in the progression of chronic heart failure seem to be mediated by a reduction in oxidative and ER stress, restoration of mitochondrial function, and a decrease in proinflammatory and profibrotic pathways. 267 Therefore, new mechanisms using the multiomics approach, such as genomics, metabolomics, and transcriptomics, 268–270 should be involved in mapping the pathogenesis of cardiorenal crosstalk to advance new therapeutic strategies in this field. Moreover, to maximize the potential key crosstalks within the renocardial axis, which could lead to a single-target treatment of multiple pathologies, revolutionary tools such as the computational ecosystems for multiorgan diseases 271 might be integrated.…”

Modeling Red Blood Cell Metabolism in the Omics Era

“…It has been proposed that S1P can cooperatively bind to deoxyhemoglobin upon its complexing with DPG, further stabilizing the tense deoxygenated state. While beneficial for acclimatization to hypoxia, this mechanism is actually deleterious in the context of sickle cell disease [52], as it promotes sickle hemoglobin crystallization, driving cardiorenal dysfunction [53,54]. Among other lipid classes, phosphatidylserines participate in RBC removal from the bloodstream upon loss of phospholipid asymmetry, a process that is maintained by ATP-dependent flippases like ATP11C (EC 7.6.2.1) [55,56].…”