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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 an inherited bone marrow failure syndrome (IBMFS) characterized by hypoplastic anemia, congenital malformations and an increased risk to develop malignancies.Until now, treatment of DBA consists of red blood cell (RBC) transfusions, glucocorticoids (GC) and allogeneic hematopoietic stem cell transplantation in a selection of patients. Whereas RBC transfusions are the main cause of IO, elevated iron parameters have also been reported in non-transfusion-dependent DBA patients. Here we investigated the incidence and severity of IO in a well-described cohort of transfusion-dependent and non-transfusion-dependent DBA patients in order to gain more insight in the regulation of iron metabolism in DBA, and to provide clinical guiding to improve the diagnosis and management of IO in DBA. Methods: In this retrospective, observational study we have included twenty-nine pediatric and adult DBA patients for whom at least one serum ferritin level and/or MRI result was available. Ten patients (34%) were classified as transfusion-dependent (TD) (ten or more transfusions during the twelve months prior to evaluation). Non-transfusion-dependent (NTD) patients (66%) were treated with either GC, incidental transfusions or received no treatment. Transfusion burden (transfusion history) was assessed via medical records. Serum ferritin levels ≥250 ng/mL in males and ≥150 ng/mL in females were considered to be elevated. Results of MRI were expressed as liver iron content (LIC) and as cardiac T2* in milliseconds (ms). LIC ≥3 mg/g indicates significant hepatic IO, and LIC ≥7 mg/g is associated with clinical morbidity. Cardiac T2* ≤20 ms indicates significant cardiac IO. Results: In 15/29 (52%) MRI analysis of IO was performed. Hepatic IO (LIC >3 mg/g) was present in 9/29 (31%) of DBA patients, of which 8/9 (89%) had moderate to severe IO (LIC>7mg/g), despite the fact that all but one were treated with chelation therapy. Overall serum ferritin levels and LIC correlated significantly (r=0.7907, p1000 ng/mL (Figure 1A). Interestingly, in the NTD group, hepatic IO was present in 2/7 patients (29%), who both only had mildly elevated serum ferritin levels (263 ng/mL and 277 ng/mL) and were not treated with iron chelation therapy. Based on total transfusion burden since birth, patients were classified in distinct groups: nine patients who received ³10 transfusions during life (9/10) were diagnosed with hepatic IO, whilst none of the patients who received Discussion: We demonstrate that IO is common in DBA yet can be easily overlooked in NTD patients that were treated with transfusions in the past. While serum ferritin levels significantly correlated with LIC values, this parameter cannot be used exclusively to screen for IO or titrate iron chelation therapy. We conclude that in clinical practice, biochemical parameters in combination with transfusion history justify a low-threshold to perform an MRI-based evaluation of IO, and to start adequate chelation therapy. Figure 1 Figure 1. Disclosures Van Beers: Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Novartis: Research Funding; RR Mechatronics: Research Funding. Wijk: Global Blood Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Axcella health: Research Funding; Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding.

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.

Background: Diamond-Blackfan anemia (DBA) is a rare inherited bone marrow failure syndrome (IBMFS) marked by erythroid hypoplasia, reticulocytopenia and macrocytosis, and associated with congenital malformations and an increased risk of developing malignancies. From a clinical and molecular perspective this disease is highly heterogeneous, and no clear genotype-phenotype correlations can be found. Since the majority of molecular defects have been found in ribosomal protein (RP) genes, DBA is regarded a "ribosomopathy". While the molecular basis has been studied intensively, the pathophysiology of DBA is still not fully understood. One of the major unresolved issues is how RP gene mutations result in the specific erythroid defect seen in DBA, with macrocytic erythrocytes and increased adenosine deaminase activity. In addition, the highly heterogeneous and variable clinical presentation and disease course, even in patients with similar molecular defects, remains enigmatic. Hence, in order to investigate the cellular defect, and increase our understanding of disease pathophysiology and clinical heterogeneity, novel tools are needed. In this study, we explore the potential of untargeted metabolomics on dried blood spots and report for the first time a metabolic fingerprint for DBA. Aims: Defining a metabolic signature for DBA in order to: 1. Increase our understanding of cellular determinants of impaired ribosome biogenesis, and 2. Extend the toolbox for diagnostic evaluation. Methods: Untargeted metabolic profiling was performed on DBS samples obtained from 18 DBA patients and 45 healthy controls using direct infusion high resolution mass spectrometry following a previously established approach1. Statistical analysis was performed in MetaboAnalyst and predictive modeling was executed within R-software. Results: In total, 1917 unique metabolite features were identified in DBS samples from patients and controls. Multivariate analysis yielded distinct metabolic profiles, reflected by natural separation detected by principal component analysis (Figure 1A), and emphasized by clear distinction with partial least square discriminant analysis (Figure 1B). This 'metabolic fingerprint' was incorporated into a machine learning algorithm, and subsequently a binary classification (or prediction) model was constructed by randomly dividing patient and controls into 'training' (32 HC, 13 DBA) or 'test' set (13 HC, 5 DBA). Accurate class assignment was achieved for all patients and controls in the training set (Figure 1C). Prominent metabolites in the fingerprint and classification algorithm were a.o. menadione (a vitamin K precursor), 4-hydroxyproline (collagen component) and methylmalonylcarnitine (an acylcarnitine). In addition a large number of interesting metabolites were identified that could provide novel starting points for studying/understanding downstream effects of RP defects in DBA and therapeutic mechanisms (Figure 1D). Conclusion: In this study we performed untargeted metabolomics on dried blood spots from a substantial cohort of DBA patients and report for the first time a metabolic fingerprint of this disease. By incorporating this fingerprint in a machine learning algorithm we underlined the diagnostic potential of this approach. Moreover, the metabolites identified in this fingerprint, provide promising starting points for further studies to increase our insights in disease pathophysiology, including the mechanism involved in elevated eADA activity, as well as the development of new therapeutic strategies. References: 1. de Sain-van der Velden MGM, van der Ham M, Gerrits J, et al. Quantification of metabolites in dried blood spots by direct infusion high resolution mass spectrometry. Anal Chim Acta. 2017;979:45-50. Disclosures Wijk: Agios Pharmaceuticals Inc.: Research Funding; RR mechatronics: Research Funding.

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.

Background: The group of rare hereditary anemias includes a large variety of intrinsic defects of the red blood cell, as well as erythropoiesis. They include hemolytic anemias (e.g. enzyme deficiencies), hemoglobinopathies, hypoplastic anemias (e.g. Diamond-Blackfan Anemia, DBA), and dyserythropoietic anemias. As a result of the rapid developments in genetic testing and the subsequent increased knowledge of molecular defects underlying hereditary anemias, our understanding of the pathophysiology of rare anemias has increased during the last decade. However, in a substantial number of patients, the clinical phenotype does not fit classical criteria of a disease, response to therapy is less than expected, or a molecular defect cannot be found. In addition, in patients with well-described molecular defects, there is often no clear genotype-phenotype correlation. In order to better understand the underlying pathophysiological mechanisms driving ineffective erythropoiesis in patients and to improve their classification and clinical evaluation, novel functional tests are needed. Metabolomics is the large-scale, unbiased study of metabolites and their interactions within a biological system, directly reflecting the underlying biochemical activity and state of cells. Metabolomics can be used to identify novel disease biomarkers, study deregulated cellular pathways, and to determine the cellular responses to therapeutic interventions. In this study we demonstrate that dried blood spots (DBS) can be used as a minimal invasive and validated technical approach to perform large scale metabolomics in a variety of rare hereditary anemias. Methods: DBS samples from >100 patients suffering from a variety of rare anemiaswere collected during regular hospital visits. Quantification of metabolites was performed by direct infusion high resolution mass spectrometry (DI-HRMS) followed by an untargetedmetabolomics pipeline. For annotation, the Human Metabolome Database (HMDB) was used. Results were compared with DBS samples of 70 healthy adult controls and 35 pediatric patients negatively screened for metabolic diseases Results: For each patient sample, Z-scores were calculated for all mass peaks annotated with metabolites (HMDB, 3930). Mass peak, intensity and corresponding Z-scores were compared with two distinct groups of controls (∆Z-scores): pediatric patients who were screened for metabolic diseases but were found negative, and healthy adult controls. For data interpretation, two strategies were used. First, by untargeted statistical analysis in Metabo-analyst, we identified metabolites (and/or isomers) that showed either increased or decreased intensity. For the second strategy we specifically focused on red blood cell metabolic pathways, including glycolysis, the pentose phosphate pathway, ascorbate and glutathione metabolism, arginine and polyamine metabolism, and erythrocyte membrane turnover and transport. We corrected for a potential hematocrit effect and performed subgroup analyses correcting for reticulocyte counts. Our preliminary data indicate potential biomarkers for distinct disease entities, including altered polyamine metabolism (DBA, SCD), glycolysis (DBA, HS), and aberrant arginine metabolism (SCD) (Figure 1). Further in-depth pathway analyses, and targeted validation of biomarker profiles are currently being performed. Conclusion: Untargeted metabolomics using dried blood spots provides a novel functional tool to identify disease biomarkers and common and distinct deregulated cellular pathways. This will improve diagnostic evaluation and clinical management of patients with rare hereditary anemias, contribute to a better understanding of disease pathophysiology, and aid in the development of therapeutic strategies. Disclosures van Beers: Agios Pharmaceuticals, Inc.: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Research Funding; Pfizer: Research Funding; RR Mechatronics: Research Funding. van Wijk:RR Mechatronics: Research Funding; Agios Pharmaceuticals: Consultancy, Research Funding.