Studying blood is a critical component of health research. It is the key to understanding disease and plays an important role in developing new treatments and cures. However, effective blood research and treatments like blood product transfusion rely on a deep understanding of all components of the transfusion chain—from donors to processing and storage to recipients. How can we ensure we are addressing key blood-related research questions quickly and sharing those outcomes widely to improve health outcomes for all?
One of the major goals of organizations like the National Heart, Lung, and Blood Institute (NHLBI) through the Recipient Epidemiology Donor Evaluation Study (REDS) is to improve the safety and availability of the nation’s blood supply and the effectiveness of blood transfusion therapies. Decades of research have examined how blood is stored and how red blood cells (RBCs) can age and break down during storage, perhaps limiting their effectiveness for research and treatments. Being able to identify and predict what causes these changes in RBCs over time can help reduce threats to our blood supply and improve health outcomes from transfusions.
Accelerating Advancements in Blood and Transfusion Research through Open Access Publications and Data Sharing
Integrating a multi-omics approach to blood research has transformed research outcomes, giving insight into genetic markers, proteins, and metabolites that can vastly improve disease diagnosis, treatment, donor-recipient matching, and blood storage practices. Understanding gene and cell-based therapies has evolved the path to precision medicine to improve patient outcomes and better manage conditions for blood disorders like sickle cell disease.
My experience applying genome-wide association (GWA) analyses and whole-genome sequencing (WGS) studies has shown that being able to analyze vast amounts of gene variations alone and in combination with other high dimensional omic data—such as transcriptomics, microbiome, metabolomics and methylation—allows us to better understand critical omic genetic indicators and other characteristics. These insights can better shape blood research, expand precision transfusion medicine, increase fundamental understanding of RBCs, and improve treatment practices.
My REDS-associated work is highly collaborative with other RTI investigators who bring their own expertise. Greg Keele, PhD, works with proteomic data and brings extensive experience with murine models of blood disorders (references 1,2,4,10, and 12). Amy Moore, PhD, is an expert bioinformatician with great understanding of the genetic regulation of quantitative traits (references 3,5,6,10). Fang Fang, PhD, brings deep expertise in genomic methylation and the effect of sex and hormones (references 7, 8) upon blood and blood disorders.
As important research discoveries are made in the field, scientific reports detailing the analysis and impact of study outcomes must be made available to help further advance blood research rapidly and efficiently through open access publication and data sharing. Existing research networks, such as REDS, and researchers at various stages in their careers can contribute their findings as one of many resources to ensure patient safety and improve outcomes.
Over the past eight years, my REDS colleagues and I have authored a number of publications that have supported significant scientific advancements related to blood research, particularly through a genomics lens. A sample of some of those publications is featured below, with topics ranging from genetic indicators of RBC aging, predicting RBC breakdown rates, and ways to improve transfusion. These twelve papers have been cited over 331 times at the time of this blog’s publication, signaling the importance of making research findings widely available to continue to build upon the impact of this work. In addition, the work on REDS has led to insights for other hematological disorders such as sickle cell disease (13, 14), pica (15,16), and restless legs syndrome (17,18) and the impact of sex (19), hormones (20) and obesity (21) on blood and transfusion.
1. Understanding why stored RBCs in storage break down at different rates
In this study (1), we investigated why RBCs break down at different rates both after transfusion and while being stored. We found that when a gene called STEAP3 does not function properly, RBCs are likely to undergo ferroptosis (programmed cell death), break down more easily, carry more oxidative stress markers, and can result in smaller increases of hemoglobin levels after a transfusion. One of the main goals of transfusion is to increase the level of hemoglobin in recipients to enable them to better fight disease, transport oxygen and other metabolites, and maintain homeostasis. By increasing the efficacy of a transfusion unit, precision transfusion medicine will be able to make better use of the limited resource of a blood unit and increase the efficacy of a unit of blood on a recipient.
Read the full paper: Ferroptosis regulates hemolysis in stored murine and human red blood cells.
2. Identifying biomarkers of human aging in RBCs
In this study (2) we used a multi-omics approach to examine age-associated changes in RBCs. We expanded upon previous studies of RBCs and aging, looking at over 15,700 specimens from 13,757 human study participants (which included both healthy donors and sickle cell disease patients) and found arginine metabolism to be a key biomarker of aging.
Read the full paper: Arginine metabolism is a biomarker of red blood cell and human aging.
3. Understanding how genes related to glycolysis impact blood storage and transfusion outcomes
In this paper (3) we demonstrated how genetic differences in genes related to glycolysis—such as ATP and hypoxanthine—explain why RBCs break down at different rates during storage. As a result, identification of these gene signatures can help improve blood storage practices and even serve as predictors of how well stored blood will perform in transfusions.
Read the full paper: Biological and genetic determinants of glycolysis: Phosphofructokinase isoforms boost energy status of stored red blood cells and transfusion outcomes.
4. Identifying genetic factors that can influence carnitine levels in blood
This study (4) analyzed levels of carnitine in blood donations and determined that lower levels caused more RBC breakdown and damage. We identified genetic variations that were linked to lower levels of carnitine and determined that since RBCs also naturally lose carnitine as they age over time, supplementing RBCs with carnitine during storage could help improve quality of stored blood and potentially positively impact transfusion outcomes.
Read the full paper: Genetic regulation of carnitine metabolism controls lipid damage repair and aging RBC hemolysis in vivo and in vitro.
5. Using kynurenine to predict how easily RBCs can break down under stress to improve transfusions
Through this work (5), we identified kynurenine as a predictor of how easily RBCs break down under osmotic stress. Since kynurenine levels are influenced by a donor’s age and Body Mass Index (BMI), we investigated genetic variations that could also impact kynurenine levels to help improve transfusion outcomes by customizing blood management for patients based on genetic factors.
Read the full paper: Regulation of kynurenine metabolism by blood donor genetics and biology impacts red cell hemolysis in vitro and in vivo.
6. Determining how genetic markers influence metabolic characteristics of RBCs
As part of this study (6), our research team uncovered insights into RBC function by identifying genetic markers that influence RBC metabolism to give a more complete picture. Our study greatly expanded our understanding of the active RBCs play in glycolysis and transport of numerous metabolites around the body.
Read the full paper: Genome-wide metabolite quantitative trait loci analysis (mQTL) in red blood cells from volunteer blood donors.
7. Assessing genetic and nongenetic factors that impact the effectiveness of blood transfusions
In this study (7) we report how transfusion effectiveness—defined as decreased hemoglobin or increased bilirubin increments—can be impacted by both nongenetic factors, such as RBC storage duration, and donor genetic factors. Addressing these critical factors can help improve patient outcomes, especially for chronically transfused RBC recipients, by providing a precision medicine approach for more effective transfusion product storage and use.
Read the full paper: Donor genetic and nongenetic factors affecting red blood cell transfusion effectiveness.
8. Identifying genetic locations that are associated with hemolysis during storage
In an additional study (8), we used a GWA approach with over 12,300 blood donors to see how RBCs responded to various stressful conditions to identify which genetic variations influenced their durability. We found 27 significant genetic loci that were associated with RBC function, which can be used to help improve transfusion practices by better matching blood with recipients based on genetic factors and improve treatments for hemolytic diseases like sickle cell disease and malaria.
Read the full paper: Multiple-ancestry genome-wide association study identifies 27 loci associated with measures of hemolysis following blood storage.
9. Building a comprehensive data set of blood donors and tracking the outcomes of patients who received transfusions of donated RBCs
Through this work (9) we detailed how an RBC-omics study built a large data set containing behavioral, genetic, and biochemical characteristics of blood donors. The study also linked donors to the outcomes of the patients who received transfusion with their donated RBCs to better understand how donor characteristics impact the effectiveness of transfusion therapies.
Read the full paper: Blood, sweat, and tears: Red Blood Cell-Omics study objectives, design, and recruitment activities.
10. Understanding the impact of external exposures such as caffeine on blood storage and transfusion response
In this work (10) we found that caffeine, the most widely used psycho active substance, strongly impacts metabolism in RBCs by reducing glycosis and increased markers of hemolysis. Clinically we found that caffeine consumption by RBC donors lead to increased hemolysis and poorer transfusion recipient response. This study identified caffeine consumption as a modifiable factor in blood transfusion practice, having rapid translational potential for improving transfusion outcomes.
Read the full paper: Caffeine Impairs Red Blood Cell Storage Quality by Dual Inhibition of ADORA2b Signaling and G6PD Activity.
11. Insights from understanding RBC biology are highly transferable into other research questions
In our study (11) of type 1 diabetes and maple syrup urine disease we were able to identify common mechanisms of the disease through our insights into RBCs and identify a potential novel therapeutic target for both diseases.
Read the full paper: Altered branched chain ketoacids underlie shared metabolic phenotypes in type 1 diabetes and maple syrup urine disease.
12. Insights into RBC oxidation and glutathione through murine omic studies
To better understand genetic regulation of RBC oxidation, we used proteomics, metabolomics, lipidomics and genetics in our study (12) of a large population of genetically diverse mice. Novelly, we identified genetic regulators of post-translational modifiers of proteins. We also found that the loss of reactive C93 in humanized mice disrupted redox balance, affect glutathione pools, protein glutathionylation, and redox PTMs. These findings highlight genetic regulation of RBC oxidation, with implications for transfusion biology and oxidative stress-dependent hemolytic disorders.
Read the full paper: Genetic architecture of the red blood cell proteome in genetically diverse mice reveals central role of hemoglobin beta cysteine redox status in maintaining circulating glutathione pools.
Multi-omic Advances Pave the Way for Precision Medicine
These multi-omic breakthroughs in blood research are helping to build the foundation upon which we can improve overall health outcomes and to better position us to rapidly respond to emerging research and clinical practice needs. Learn more about the importance of RTI omics research and how precision medicine can shape the future of blood-related prevention, diagnosis, and treatment.
(1) Ferroptosis regulates hemolysis in stored murine and human red blood cells.
D'Alessandro A, Keele GR, Hay A, Nemkov T, Earley EJ, Stephenson D, Vincent M, Deng X, Stone M, Dzieciatkowska M, Hansen KC, Kleinman S, Spitalnik SL, Roubinian N, Norris PJ, Busch MP, Page GP, Stockwell BR, Churchill GA, Zimring JC.Blood. 2025 Feb 13;145(7):765-783. doi: 10.1182/blood.2024026109.PMID: 39541586
(2) Arginine metabolism is a biomarker of red blood cell and human aging.
Reisz JA, Earley EJ, Nemkov T, Key A, Stephenson D, Keele GR, Dzieciatkowska M, Spitalnik SL, Hod EA, Kleinman S, Roubinian NH, Gladwin MT, Hansen KC, Norris PJ, Busch MP, Zimring JC, Churchill GA, Page GP, D'Alessandro A.Aging Cell. 2025 Feb;24(2):e14388. doi: 10.1111/acel.14388. Epub 2024 Oct 30.PMID: 39478346
Nemkov T, Stephenson D, Earley EJ, Keele GR, Hay A, Key A, Haiman ZB, Erickson C, Dzieciatkowska M, Reisz JA, Moore A, Stone M, Deng X, Kleinman S, Spitalnik SL, Hod EA, Hudson KE, Hansen KC, Palsson BO, Churchill GA, Roubinian N, Norris PJ, Busch MP, Zimring JC, Page GP, D'Alessandro A.Cell Metab. 2024 Sep 3;36(9):1979-1997.e13. doi: 10.1016/j.cmet.2024.06.007. Epub 2024 Jul 3. PMID: 38964323
Nemkov T, Key A, Stephenson D, Earley EJ, Keele GR, Hay A, Amireault P, Casimir M, Dussiot M, Dzieciatkowska M, Reisz JA, Deng X, Stone M, Kleinman S, Spitalnik SL, Hansen KC, Norris PJ, Churchill GA, Busch MP, Roubinian N, Page GP, Zimring JC, Arduini A, D'Alessandro A.Blood. 2024 Jun 13;143(24):2517-2533. doi: 10.1182/blood.2024023983. PMID: 38513237
Nemkov T, Stephenson D, Erickson C, Dzieciatkowska M, Key A, Moore A, Earley EJ, Page GP, Lacroix IS, Stone M, Deng X, Raife T, Kleinman S, Zimring JC, Roubinian N, Hansen KC, Busch MP, Norris PJ, D'Alessandro A.Blood. 2024 Feb 1;143(5):456-472. doi: 10.1182/blood.2023022052. PMID: 37976448
Moore A, Busch MP, Dziewulska K, Francis RO, Hod EA, Zimring JC, D'Alessandro A, Page GP, J Biol Chem. 2022 Dec;298(12):102706. doi: 10.1016/j.jbc.2022.102706. Epub 2022 Nov 15.PMID: 36395887
(7) Donor genetic and nongenetic factors affecting red blood cell transfusion effectiveness.
Roubinian NH, Reese SE, Qiao H, Plimier C, Fang F, Page GP, Cable RG, Custer B, Gladwin MT, Goel R, Harris B, Hendrickson JE, Kanias T, Kleinman S, Mast AE, Sloan SR, Spencer BR, Spitalnik SL, Busch MP, Hod EA; National Heart Lung and Blood Institute (NHLBI) Recipient Epidemiology and Donor Evaluation Study IV Pediatrics (REDS-IV-P).JCI Insight. 2022 Jan 11;7(1):e152598. doi: 10.1172/jci.insight.152598.PMID: 34793330
Page GP, Kanias T, Guo YJ, Lanteri MC, Zhang X, Mast AE, Cable RG, Spencer BR, Kiss JE, Fang F, Endres-Dighe SM, Brambilla D, Nouraie M, Gordeuk VR, Kleinman S, Busch MP, Gladwin MT; National Heart, Lung, and Blood Institute (NHLBI) Recipient Epidemiology Donor Evaluation Study–III (REDS-III) program.J Clin Invest. 2021 Jul 1;131(13):e146077. doi: 10.1172/JCI146077.PMID: 34014839
(9) Blood, sweat, and tears: Red Blood Cell-Omics study objectives, design, and recruitment activities.
Endres-Dighe SM, Guo Y, Kanias T, Lanteri M, Stone M, Spencer B, Cable RG, Kiss JE, Kleinman S, Gladwin MT, Brambilla DJ, D'Andrea P, Triulzi DJ, Mast AE, Page GP, Busch MP; NHLBI Recipient Epidemiology Donor Evaluation Study (REDS)-III Program.Transfusion. 2019 Jan;59(1):46-56. doi: 10.1111/trf.14971. Epub 2018 Sep 28.PMID: 30267427
Dzieciatkowska M, Hay A, Issaian A, Keele GR, Bevers S, Nemkov T, Reisz JA, Maslanka M, Stephenson D, Moore AL, Deng X, Stone M, Hansen KC, Kleinman S, Norris PJ, Busch MP, Page GP, Roubinian N, Xia Y, Zimring JC, D'Alessandro A.bioRxiv [Preprint]. 2025 May 30:2025.05.27.656446. doi: 10.1101/2025.05.27.656446.PMID: 40502093
Roberti D, Grier AL, Reisz JA, Vallefuoco F, Key A, Bevers S, Dzieciatkowska M, Nemkov T, Contieri M, Zanfardino A, Norris PJ, Busch MP, Kauffman V, Morton HD, Earley EJ, Page GP, Marzuillo P, D'Alessandro A.Commun Med (Lond). 2025 Jul 26;5(1):311. doi: 10.1038/s43856-025-01028-w. PMID: 40715470
Keele GR, Dzieciatkowska M, Hay AM, Vincent M, O'Connor C, Stephenson D, Reisz JA, Nemkov T, Hansen KC, Page GP, Zimring JC, Churchill GA, D'Alessandro A.bioRxiv [Preprint]. 2025 Mar 4:2025.02.27.640676. doi: 10.1101/2025.02.27.640676.PMID: 40093052
Earley EJ, Kelly S, Fang F, Alencar CS, Rodrigues DOW, Soares Cruz DT, Flanagan JM, Ware RE, Zhang X, Gordeuk V, Gladwin M, Zhang Y, Nouraie M, Nekhai S, Sabino E, Custer B, Dinardo C, Page GP; International Component of the NHLBI Recipient Epidemiology and Donor Evaluation Study (REDS-III) and the NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium.Br J Haematol. 2023 Apr;201(2):343-352. doi: 10.1111/bjh.18637. Epub 2023 Jan 5.PMID: 36602125
Cintho Ozahata M, Guo Y, Gomes I, Malta B, Belisário A, Amorim L, Teles D, Park M, Kelly S, Sabino EC, Page GP, Custer B, Dinardo CL; International Component of the NHLBI Recipient Epidemiology and Donor Evaluation Study (REDS‐III) and for the TOPMed (NHLBI TransOmics for Precision Medicine) SCD working. Br J Haematol. 2024 Nov;205(5):1974-1984. doi: 10.1111/bjh.19758. Epub 2024 Sep 15.PMID: 39279196
(15) Demographic, clinical, and biochemical predictors of pica in high-intensity blood donors.
Liu H, Burns RT, Spencer BR, Page GP, Mast AE; NHLBI Recipient Epidemiology Donor Evaluation Study (REDS)-III. Transfus Med. 2022 Aug;32(4):288-292. doi: 10.1111/tme.12890. Epub 2022 Jun 24.PMID: 35750589
(16) Demographic, clinical, and biochemical predictors of pica in a large cohort of blood donors.
Liu H, Burns RT, Spencer BR, Page GP, Mast AE; NHLBI Recipient Epidemiology Donor Evaluation Study (REDS)-III. Transfusion. 2021 Jul;61(7):2090-2098. doi: 10.1111/trf.16409. Epub 2021 Apr 29.PMID: 33913181
Earley EJ, Didriksen M, Spencer BR, Kiss JE, Erikstrup C, Pedersen OB, Sørensen E, Burgdorf KS, Kleinman SH, Mast AE, Busch MP, Ullum H, Page GP. Sleep. 2021 Apr 9;44(4):zsaa220. doi: 10.1093/sleep/zsaa220.PMID: 33119070
(18) Large genome-wide association study identifies three novel risk variants for restless legs syndrome.
Didriksen M, Nawaz MS, Dowsett J, Bell S, Erikstrup C, Pedersen OB, Sørensen E, Jennum PJ, Burgdorf KS, Burchell B, Butterworth AS, Soranzo N, Rye DB, Trotti LM, Saini P, Stefansdottir L, Magnusson SH, Thorleifsson G, Sigmundsson T, Sigurdsson AP, Van Den Hurk K, Quee F, Tanck MWT, Ouwehand WH, Roberts DJ, Earley EJ, Busch MP, Mast AE, Page GP, Danesh J, Di Angelantonio E, Stefansson H, Ullum H, Stefansson K. Commun Biol. 2020 Nov 25;3(1):703. doi: 10.1038/s42003-020-01430-1.PMID: 33239738
Fang F, Hazegh K, Mast AE, Triulzi DJ, Spencer BR, Gladwin MT, Busch MP, Kanias T, Page GP.BMC Genomics. 2022 Mar 23;23(1):227. doi: 10.1186/s12864-022-08461-4.PMID: 35321643
Alexander K, Hazegh K, Fang F, Sinchar D, Kiss JE, Page GP, DʼAlessandro A, Kanias T. Transfusion. 2021 Jan;61(1):108-123. doi: 10.1111/trf.16141. Epub 2020 Oct 18.PMID: 33073382
Hazegh K, Fang F, Bravo MD, Tran JQ, Muench MO, Jackman RP, Roubinian N, Bertolone L, DʼAlessandro A, Dumont L, Page GP, Kanias T. Transfusion. 2021 Feb;61(2):435-448. doi: 10.1111/trf.16168. Epub 2020 Nov 4.PMID: 33146433