Blood donor exposome and impact of common drugs on red blood cell metabolism
Travis Nemkov, Davide Stefanoni, Aarash Bordbar, Aaron Issaian, Bernhard O. Palsson, Larry J. Dumont, Ariel Hay, Anren Song, Yang Xia, Jasmina S. Redzic, Elan Z. Eisenmesser, James C. Zimring, Steve Kleinman, Kirk C. Hansen, Michael P. Busch, Angelo D’Alessandro, the Recipient Epidemiology and Donor Evaluation Study III Red Blood Cell–Omics (REDS-III RBC-Omics) Study
Travis Nemkov, Davide Stefanoni, Aarash Bordbar, Aaron Issaian, Bernhard O. Palsson, Larry J. Dumont, Ariel Hay, Anren Song, Yang Xia, Jasmina S. Redzic, Elan Z. Eisenmesser, James C. Zimring, Steve Kleinman, Kirk C. Hansen, Michael P. Busch, Angelo D’Alessandro, the Recipient Epidemiology and Donor Evaluation Study III Red Blood Cell–Omics (REDS-III RBC-Omics) Study
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Research Article Hematology Metabolism

Blood donor exposome and impact of common drugs on red blood cell metabolism

Abstract

Computational models based on recent maps of the RBC proteome suggest that mature erythrocytes may harbor targets for common drugs. This prediction is relevant to RBC storage in the blood bank, in which the impact of small molecule drugs or other xenometabolites deriving from dietary, iatrogenic, or environmental exposures (“exposome”) may alter erythrocyte energy and redox metabolism and, in so doing, affect red cell storage quality and posttransfusion efficacy. To test this prediction, here we provide a comprehensive characterization of the blood donor exposome, including the detection of common prescription and over-the-counter drugs in blood units donated by 250 healthy volunteers in the Recipient Epidemiology and Donor Evaluation Study III Red Blood Cell–Omics (REDS-III RBC-Omics) Study. Based on high-throughput drug screenings of 1366 FDA-approved drugs, we report that approximately 65% of the tested drugs had an impact on erythrocyte metabolism. Machine learning models built using metabolites as predictors were able to accurately predict drugs for several drug classes/targets (bisphosphonates, anticholinergics, calcium channel blockers, adrenergics, proton pump inhibitors, antimetabolites, selective serotonin reuptake inhibitors, and mTOR), suggesting that these drugs have a direct, conserved, and substantial impact on erythrocyte metabolism. As a proof of principle, here we show that the antacid ranitidine — though rarely detected in the blood donor population — has a strong effect on RBC markers of storage quality in vitro. We thus show that supplementation of blood units stored in bags with ranitidine could — through mechanisms involving sphingosine 1–phosphate–dependent modulation of erythrocyte glycolysis and/or direct binding to hemoglobin — improve erythrocyte metabolism and storage quality.

Authors

Travis Nemkov, Davide Stefanoni, Aarash Bordbar, Aaron Issaian, Bernhard O. Palsson, Larry J. Dumont, Ariel Hay, Anren Song, Yang Xia, Jasmina S. Redzic, Elan Z. Eisenmesser, James C. Zimring, Steve Kleinman, Kirk C. Hansen, Michael P. Busch, Angelo D’Alessandro, the Recipient Epidemiology and Donor Evaluation Study III Red Blood Cell–Omics (REDS-III RBC-Omics) Study

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Figure 7

Ranitidine boosts glycolysis in a dose-response fashion in human RBCs.

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Ranitidine boosts glycolysis in a dose-response fashion in human RBCs. (...
(A) Human RBCs (n = 3) were incubated with increasing doses of ranitidine in the presence of 1,2,3-13C3-glucose for up to 60 minutes. At increasing doses of ranitidine (B) corresponded increasing levels of 13C3-labeled 1,6-fructose diphosphate (rate-limiting step of glycolysis, plateauing at 100 μM ranitidine; C) and 13C3-lactate (D) — suggestive of increased fluxes through glycolysis but not the Rapoport-Luebering shunt. (E) RBCs were also obtained from 3 WT and 3 Sphk1-KO mice, prior to incubation with 100 μM ranitidine for 60 minutes. (F) After confirming significant decreases in S1P levels in the Sphk1-KO mouse RBCs, we observed that ex vivo incubation with ranitidine promoted increases in the levels of several glycolytic intermediates, including G6P, G3P, 2,3-DPG, phosphoglycerate, and pyruvate. However, increases in the total levels of lactate were observed in WT but not in Sphk1-KO mice following incubation with ranitidine. On the other hand, Sphk1-KO mice showed increased steady-state levels of ribose phosphate, suggestive of increased fluxes through the pentose phosphate pathway and increased NADPH-dependent recycling of glutathione. This observation is consistent with the observed increases in levels of reduced glutathione in Sphk1-KO mice after incubation with ranitidine. These mice were characterized by lower levels of another antioxidant, methionine. (F) Finally, the total adenylate pool (high-energy phosphate compounds including adenosine tri-, di-, and monophosphate [ATP + ADP + AMP]) increased in WT cells following incubation with ranitidine, but decreased in Sphk1-KO mouse RBCs. Color key in E applies to E and F. (G) Storage of RBCs from mice with poor storage quality (FVB, n = 3) in the presence of ranitidine (0, 50, 100, or 200 μM) resulted in significant improvements in RBC storage quality at 100 μM. Colors representing ranitidine doses correspond to the values detailed in B. In A–F, y axes indicate integrated peak areas in AU.