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Ferrata Storti Foundation
Haematologica 2021 Volume 106(10):2720-2725
Untargeted metabolic profiling in dried blood spots identifies disease fingerprint for pyruvate kinase deficiency
Birgit van Dooijeweert,1,2* Melissa H. Broeks,3* Nanda M. Verhoeven-Duif,3 Eduard J. van Beers,4 Edward E.S. Nieuwenhuis,2 Wouter W. van Solinge,1 Marije Bartels,2,4 Judith J.M. Jans3# and Richard van Wijk1#
1Central Diagnostic Laboratory-Research, University Medical Center Utrecht; 2Department of Pediatric Hematology, University Medical Center Utrecht; 3Section Metabolic Diagnostics, Department of Genetics, University Medical Center Utrecht and 4Van Creveldkliniek, University Medical Center Utrecht, Utrecht, the Netherlands
*BvD and MHB contributed equally as co-first authors. #JJMJ and RvW contributed equally as co-senior authors.
ABSTRACT
The diagnostic evaluation and clinical characterization of rare hereditary anemia (RHA) is to date still challenging. In particular, there is little knowledge of the broad metabolic impact of many of the molecular defects underlying RHA. In this study we explored the potential of untargeted metabolomics to diagnose a relatively common type of RHA: pyruvate kinase deficiency (PKD). In total, 1,903 unique metabolite features were identified in dried blood spot samples from 16 PKD patients and 32 healthy controls. A metabolic fingerprint was iden- tified using a machine learning algorithm, and subsequently a binary classification model was designed. The model showed high perform- ance characteristics (AUC 0.990, 95% CI: 0.981-0.999) and an accurate class assignment was achieved for all newly added control (n=13) and patient samples, (n=6) with the exception of one patient (accuracy 94%). Important metabolites in the metabolic fingerprint included gly- colytic intermediates, polyamines and several acyl carnitines. In general, the application of untargeted metabolomics in dried blood spots is a novel functional tool that holds promise for the diagnostic stratification and studies on the disease pathophysiology in RHA.
Introduction
The group of rare hereditary anemias (RHA) includes a large variety of intrinsic defects of red blood cells and erythropoiesis. Our knowledge of the pathophysi- ology of RHA has recently vastly improved, powered by genetic testing and sub- sequent increased knowledge of underlying molecular defects.1-4 However, in a substantial number of patients, the clinical phenotype does not fit classical disease criteria, the response to therapy is unexpectedly poor, or a molecular defect can- not be identified.5-7 In addition, in patients with well-described genetic defects, there is often no clear genotype-phenotype correlation.7-9
Pyruvate kinase deficiency (PKD; OMIM 266 200), the most common red cell glycolytic enzyme defect, is no exception in this respect. The clinical phenotype of PKD varies widely, from well-compensated hemolytic anemia to severe hemol- ysis and neonatal mortality. Currently the diagnosis of PKD relies on the meas- urement of PK activity and/or the identification of homozygous or compound heterozygous mutations in the PKLR gene.10,11
However, in a significant number of patients only one mutation is identified. In addition, the exact mechanisms leading to reduced lifespan of PK-deficient ery- throcytes are still largely unknown. Thus, in order to improve the diagnostic eval- uation as well as our understanding of PKD pathophysiology and the genotype- to-phenotype correlation, novel functional tests are needed.
Red Cell Biology & its Disorders
In this study we demonstrate the potential of untargeted metabolomics in dried
Correspondence:
BIRGIT VAN DOOIJEWEERT
b.vandooijeweert-3@umcutrecht.nl
Received: July 16, 2020.
Accepted: August 28, 2020. Pre-published: September 10, 2020.
https://doi.org/10.3324/haematol.2020.266957 ©2021 Ferrata Storti Foundation
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