Literature DB >> 27554084

Biomarkers defining the metabolic age of red blood cells during cold storage.

Giuseppe Paglia1, Angelo D'Alessandro2, Óttar Rolfsson3, Ólafur E Sigurjónsson4, Aarash Bordbar5, Sirus Palsson6, Travis Nemkov2, Kirk C Hansen2, Sveinn Gudmundsson7, Bernhard O Palsson3.   

Abstract

Metabolomic investigations of packed red blood cells (RBCs) stored under refrigerated conditions in saline adenine glucose mannitol (SAGM) additives have revealed the presence of 3 distinct metabolic phases, occurring on days 0-10, 10-18, and after day 18 of storage. Here we used receiving operating characteristics curve analysis to identify biomarkers that can differentiate between the 3 metabolic states. We first recruited 24 donors and analyzed 308 samples coming from RBC concentrates stored in SAGM and additive solution 3. We found that 8 extracellular compounds (lactic acid, nicotinamide, 5-oxoproline, xanthine, hypoxanthine, glucose, malic acid, and adenine) form the basis for an accurate classification/regression model and are able to differentiate among the metabolic phases. This model was then validated by analyzing an additional 49 samples obtained by preparing 7 new RBC concentrates in SAGM. Despite the technical variability associated with RBC processing strategies, verification of these markers was independently confirmed in 2 separate laboratories with different analytical setups and different sample sets. The 8 compounds proposed here highly correlate with the metabolic age of packed RBCs, and can be prospectively validated as biomarkers of the RBC metabolic lesion.
© 2016 by The American Society of Hematology.

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Year:  2016        PMID: 27554084     DOI: 10.1182/blood-2016-06-721688

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


  51 in total

1.  A three-minute method for high-throughput quantitative metabolomics and quantitative tracing experiments of central carbon and nitrogen pathways.

Authors:  Travis Nemkov; Kirk C Hansen; Angelo D'Alessandro
Journal:  Rapid Commun Mass Spectrom       Date:  2017-04-30       Impact factor: 2.419

2.  Metabolic effect of alkaline additives and guanosine/gluconate in storage solutions for red blood cells.

Authors:  Angelo D'Alessandro; Julie A Reisz; Rachel Culp-Hill; Herbert Korsten; Robin van Bruggen; Dirk de Korte
Journal:  Transfusion       Date:  2018-04-06       Impact factor: 3.157

3.  The 3-phase evolution of stored red blood cells and the clinical trials: an obvious relationship.

Authors:  Michel Prudent; Jean-Daniel Tissot; Niels Lion
Journal:  Blood Transfus       Date:  2017-03       Impact factor: 3.443

Review 4.  Omics markers of the red cell storage lesion and metabolic linkage.

Authors:  Angelo D'alessandro; Travis Nemkov; Julie Reisz; Monika Dzieciatkowska; Matthew J Wither; Kirk C Hansen
Journal:  Blood Transfus       Date:  2017-03       Impact factor: 3.443

Review 5.  Duration of red blood cell storage and inflammatory marker generation.

Authors:  Caroline Sut; Sofiane Tariket; Ming Li Chou; Olivier Garraud; Sandrine Laradi; Hind Hamzeh-Cognasse; Jerard Seghatchian; Thierry Burnouf; Fabrice Cognasse
Journal:  Blood Transfus       Date:  2017-03       Impact factor: 3.443

6.  Red blood cell storage and clinical outcomes: new insights.

Authors:  Angelo D'alessandro; Giancarlo M Liumbruno
Journal:  Blood Transfus       Date:  2017-03       Impact factor: 3.443

Review 7.  Unraveling the Gordian knot: red blood cell storage lesion and transfusion outcomes.

Authors:  Vassilis L Tzounakas; Anastasios G Kriebardis; Jerard Seghatchian; Issidora S Papassideri; Marianna H Antonelou
Journal:  Blood Transfus       Date:  2017-03       Impact factor: 3.443

8.  Interpreting the deluge of omics data: new approaches offer new possibilities.

Authors:  Aarash Bordbar
Journal:  Blood Transfus       Date:  2017-03       Impact factor: 3.443

Review 9.  Red blood cell storage time and transfusion: current practice, concerns and future perspectives.

Authors:  María García-Roa; María Del Carmen Vicente-Ayuso; Alejandro M Bobes; Alexandra C Pedraza; Ataúlfo González-Fernández; María Paz Martín; Isabel Sáez; Jerard Seghatchian; Laura Gutiérrez
Journal:  Blood Transfus       Date:  2017-05       Impact factor: 3.443

10.  Heterogeneity of blood processing and storage additives in different centers impacts stored red blood cell metabolism as much as storage time: lessons from REDS-III-Omics.

Authors:  Angelo D'Alessandro; Rachel Culp-Hill; Julie A Reisz; Mikayla Anderson; Xiaoyun Fu; Travis Nemkov; Sarah Gehrke; Connie Zheng; Tamir Kanias; Yuelong Guo; Grier Page; Mark T Gladwin; Steve Kleinman; Marion Lanteri; Mars Stone; Michael Busch; James C Zimring
Journal:  Transfusion       Date:  2018-10-24       Impact factor: 3.157

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