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 1

RBC exposome in the REDS-III RBC-Omics Study.

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RBC exposome in the REDS-III RBC-Omics Study. (A) Within the framework o...
(A) Within the framework of the REDS-III RBC-Omics Study, 13,800 healthy donor volunteers were enrolled to donate a unit of whole blood that was processed into leukoreduced erythrocyte concentrates. Units were stored until the end of their shelf life (42 days), when they were tested for the propensity of RBCs to hemolyze, spontaneously or following osmotic and oxidative stress. Donors in the 5th and 95th percentiles for hemolysis measurements were asked to donate a second unit of blood, which was sampled on storage days 10, 23, and 42 for metabolomics analyses of the RBC exposome, i.e., the compendium of small molecule metabolites derived from diet, the microbiome, or other xenometabolites, such as pollutants or drugs. (B) Unsupervised PCA of the exposome data clustered the subjects (dots) on the basis of storage duration (red, green, and blue for days 10, 23 and 42, respectively). (C) Hierarchical clustering analysis of blood donors (n = 250) on storage day 10 on the basis of exposome measurements (black to white: absent to high-abundance). (D–H) The exposome informs on donor metabolic status and various habits, as highlighted in a few cases from the hierarchical clustering analysis. PPI, proton pump inhibitor; def., deficiency.