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Metabolic profiling in Pyruvate Kinase Deficiency
studies of the PKD pathophysiology.
We here report for the first time a metabolic profile for
PKD obtained from dried whole blood spots. This profile resembles the integrated disease specific metabolome to a greater extent compared to the exclusive investigation of the red blood cell metabolome.20,21
In addition, this analysis requires only 50 mL of whole blood and can be obtained in a minimally invasive man- ner by sampling a single blood drop, making it very attractive for (international) sample exchange. Further advantages of DI-HRMS include relatively uncomplicated sample extraction steps and a short run-time of 3 minutes per sample.
The rise of ‘omic’ approaches in the recent past has pro- vided new opportunities for understanding and classify- ing a wide range of disorders. In contrast to conventional medical biology approaches, which focus on individual genes, proteins or metabolites, modern biology regards diseases as a complex, dynamic and especially integrated network.22 Our study, demonstrates the potential diag- nostic application of untargeted metabolomics for PKD. However, the current model was constructed for the binary classification of healthy controls and PKD patients. Future applications, including more samples from various types of RHA could enable the development of an algo- rithm which is suited for the broader differential diagno- sis of RHA in patients.
In conclusion, we demonstrate by proof of principle for PKD, that untargeted metabolomics in DBS is a novel functional tool to identify disease fingerprints and study the pathophysiology in RHA.
This approach opens up a novel area of diagnosis and research in the field of RBC disorders and has the poten- tial to improve diagnostic evaluation and clinical manage- ment of patients.
Disclosures
EvB receives research funding from Agios Pharmaceuticals, Novartis, Bayer, Pfizer and RR Mechatronics, does consultancy for Agios Pharmaceuticals, Novartis and is on the data safety monitoring board for Imara; RvW receives research funding from RR Mechatronics and Agios Pharmaceuticals. The other authors report no relevant conflicts of interest.
Contributions
BvD and MBr contributed to collection, analysis and interpre- tation of the data, and wrote the first draft of the manuscript; EvB was actively involved in collecting patient samples and carefully revised the manuscript; WvS, EN, and NV were all involved in the study design and carefully revised the manu- script; MBa, JJ and RvW were principal investigators and were involved in all aspects of the study, including design, collection, and interpretation of data, as well as revising and co-writing the manuscript.
Acknowledgments
The authors would like to thank Nienke van Unen for her technical support in Bio-informatics.
Funding
This study was supported in part by research funding from Metakids (Grant No. 2017-075) to JJ.
References
1.Da Costa L, Narla A, Mohandas N. An update on the pathogenesis and diagnosis of Diamond-Blackfan anemia. F1000Res. 2018;7:F1000 Factulty Rev-1350.
2.Grace RF, Zanella A, Neufeld EJ, et al. Erythrocyte pyruvate kinase deficiency: 2015 status report. Am J Hematol. 2015;90(9):825-830.
3.Albuisson J, Murthy SE, Bandell M, et al. Dehydrated hereditary stomatocytosis linked to gain-of-function mutations in mechanically activated PIEZO1 ion chan- nels. Nat Commun. 2013;4:1884.
4. Roy NBA, Babbs C. The pathogenesis, diag- nosis and management of congenital dyserythropoietic anaemia type I. Br J Haematol. 2019;185(3):436-449.
5. Vercellati C, Marcello AP, Fermo E, Barcellini W, Zanella A, Bianchi P. A case of hereditary spherocytosis misdiagnosed as pyruvate kinase deficient hemolytic anemia. Clin Lab. 2013;59(3-4):421-424.
6. Steinberg-Shemer O, Keel S, Dgany O, et al. Diamond Blackfan Anemia: a nonclassical Pptient with diagnosis assisted by genomic analysis. J Pediatr Hematol Oncol. 2016;38(7):e260-262.
7. Russo R, Andolfo I, Manna F, et al. Multi- gene panel testing improves diagnosis and management of patients with hereditary anemias. Am J Hematol. 2018;93(5):672-682.
8. van Dooijeweert B, van Ommen CH, Smiers FJ, et al. Pediatric Diamond-Blackfan anemia
in the Netherlands: an overview of clinical characteristics and underlying molecular defects. Eur J Haematol. 2018;100(2):163-170.
9. Zanella A, Fermo E, Bianchi P, Chiarelli LR, Valentini G. Pyruvate kinase deficiency: the genotype-phenotype association. Blood Rev. 2007;21(4):217-231.
10.Grace RF, Bianchi P, van Beers EJ, et al. Clinical spectrum of pyruvate kinase defi- ciency: data from the Pyruvate Kinase Deficiency Natural History Study. Blood. 2018;131(20):2183-2192.
11.Bianchi P, Fermo E, Glader B, et al. Addressing the diagnostic gaps in pyruvate kinase deficiency: Consensus recommenda- tions on the diagnosis of pyruvate kinase deficiency. Am J Hematol. 2019;94(1):149- 161.
12. Haijes HA, Willemsen M, Van der Ham M, et al. Direct infusion based metabolomics identifies metabolic disease in patients' dried blood spots and plasma. Metabolites. 2019;9(1):12.
13. de Sain-van der Velden MGM, van der Ham M, Gerrits J, et al. Quantification of metabo- lites in dried blood spots by direct infusion high resolution mass spectrometry. Anal Chim Acta. 2017;979:45-50.
14. Wishart DS, Jewison T, Guo AC, Wilson M, Knox C, et al., HMDB 3.0 — The Human Metabolome Database in 2013. Nucleic Acids Res. 2013. Jan 1;41(D1):D801-807.
15. Chong J, Wishart DS, Xia J. Using MetaboAnalyst 4.0 for Comprehensive and integrative metabolomics data analysis. Curr
Protoc Bioinformatics. 2019;68(1):e86.
16. Gromski PS, Muhamadali H, Ellis DI, et al. A tutorial review: metabolomics and partial least squares-discriminant analysis--a mar- riage of convenience or a shotgun wedding.
Anal Chim Acta. 2015;879:10-23.
17. Bianchi P, Fermo E, Lezon-Geyda K, et al. Genotype-phenotype correlation and molecular heterogeneity in pyruvate kinase deficiency. Am J Hematol. 2020;95(5):472-
482.
18. Ballas SK, Mohandas N, Marton LJ, Shohet
SB. Stabilization of erythrocyte membranes by polyamines. Proc Natl Acad Sci U S A. 1983;80(7):1942-1946.
19. Arduini A, Mancinelli G, Radatti GL, Dottori S, Molajoni F, Ramsay RR. Role of carnitine and carnitine palmitoyltransferase as inte- gral components of the pathway for mem- brane phospholipid fatty acid turnover in intact human erythrocytes. J Biol Chem. 1992;267(18):12673-12681.
20. Darghouth D, Koehl B, Madalinski G, et al. Pathophysiology of sickle cell disease is mir- rored by the red blood cell metabolome. Blood. 2011;117(6):e57-66.
21. Darghouth D, Koehl B, Heilier JF, et al. Alterations of red blood cell metabolome in overhydrated hereditary stomatocytosis. Haematologica. 2011;96(12):1861-1865.
22.Tebani A, Afonso C, Marret S, Bekri S. Omics-based strategies in precision medi- cine: toward a paradigm shift in inborn errors of metabolism investigations. Int J Mol Sci. 2016;17(9):1555.
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