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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 identified using a machine learning algorithm, and subsequently a binary classification model was designed. The model showed high performance 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 glycolytic 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.

The diagnostic evaluation of Diamond Blackfan Anaemia (DBA), an inherited bone marrow failure syndrome characterised by erythroid hypoplasia, is challenging because of a broad phenotypic variability and the lack of functional screening tests. In this study, we explored the potential of untargeted metabolomics to diagnose DBA. In dried blood spot samples from 18 DBA patients and 40 healthy controls, a total of 1752 unique metabolite features were identified. This metabolic fingerprint was incorporated into a machine-learning algorithm, and a binary classification model was constructed using a training set. The model showed high performance characteristics (average accuracy 91·9%), and correct prediction of class was observed for all controls (n = 12) and all but one patient (n = 4/5) from the validation or 'test' set (accuracy 94%). Importantly, in patients with congenital dyserythropoietic anaemia (CDA) - an erythroid disorder with overlapping features - we observed a distinct metabolic profile, indicating the disease specificity of the DBA fingerprint and underlining its diagnostic potential. Furthermore, when exploring phenotypic heterogeneity, DBA treatment subgroups yielded discrete differences in metabolic profiles, which could hold future potential in understanding therapy responses. Our data demonstrate that untargeted metabolomics in dried blood spots is a promising new diagnostic tool for DBA.

Diamond-Blackfan anemia (DBA) is a rare congenital erythroblastopenia and inherited bone marrow failure syndrome that affects approximately seven individuals in every million live births. In addition to anemia, about 50% of all DBA patients suffer from various physical malformations of the face, hands, heart, or urogenital region. The disorder is almost exclusively driven by haploinsufficient mutations in one of several ribosomal protein (RP) genes, although for similar to 30% of diagnosed patients no mutation is found in any of the known DBA-linked genes. Because DBA is such a rare disease with a particularly wide range of clinical phenotypes and molecular signatures, the development of collaborative efforts such as the ERARE-funded European DBA consortium (EuroDBA) has become imperative for DBA research. EuroDBA was founded in 2012 and brings together dedicated clinical and biological researchers of DBA from France, Italy, the Netherlands, Germany, Israel, Poland, and Turkey to achieve a number of goals including the consolidation of data in patient registries, establishment of minimal diagnostic criteria, and projects aimed at more fully describing the different mutations linked to DBA. This review will cover the history of the EuroDBA registries, the methods used by EuroDBA in the diagnosis of DBA, and how the consortium has successfully worked together towards the discovery of new DBA-linked genes and the better understanding their pathophysiological effects.

INTRODUCTION: Diamond-Blackfan anemia (DBA) is characterized by hypoplastic anemia, congenital anomalies, and a predisposition for malignancies. Most of our understanding of this disorder stems from molecular studies combined with extensive data input from international patient registries.OBJECTIVES: To create an overview of the pediatric DBA population in the Netherlands.METHODS: Forty-three patients diagnosed with DBA from all Dutch university pediatric hospitals were included in this study and their clinical and genetic characteristics were collected from patient records.RESULTS: Congenital malformations were present in 24/43 patients (55.8%). An underlying genetic defect was identified in 26/43 patients (60.5%), the majority of which were found in the RPS19 gene (12/43, 27.9%) with one patient carrying a mutation in a novel DBA candidate gene, RPL9. In 31/35 (88.6%) patients an initial response to glucocorticoid treatment was observed. Six patients (14.0%) underwent hematopoietic stem cell transplantation, and eleven patients (11/43, 25.6%) became treatment-independent spontaneously.CONCLUSION: In agreement with previous reports, the Dutch pediatric DBA population is both clinically and genetically heterogeneous. National and international registries, together with more extensive genetic testing are crucial in order to increase our understanding of genotype and phenotype correlations of this intriguing disorder. This article is protected by copyright. All rights reserved.

Rare hereditary anemias (RHA) represent a group of disorders characterized by either impaired production of erythrocytes or decreased survival (i.e., hemolysis). In RHA, the regulation of iron metabolism and erythropoiesis is often disturbed, leading to iron overload or worsening of chronic anemia due to unavailability of iron for erythropoiesis. Whereas iron overload generally is a well-recognized complication in patients requiring regular blood transfusions, it is also a significant problem in a large proportion of patients with RHA that are not transfusion dependent. This indicates that RHA share disease-specific defects in erythroid development that are linked to intrinsic defects in iron metabolism. In this review, we discuss the key regulators involved in the interplay between iron and erythropoiesis and their importance in the spectrum of RHA.