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Erythrocytosis is a rare disorder characterized by increased red cell mass and elevated hemoglobin concentration and hematocrit. Several genetic variants have been identified as causes for erythrocytosis in genes belonging to different pathways including oxygen sensing, erythropoiesis and oxygen transport. However, despite clinical investigation and screening for these mutations, the cause of disease cannot be found in a considerable number of patients, who are classified as having idiopathic erythrocytosis. In this study, we developed a targeted next-generation sequencing panel encompassing the exonic regions of 21 genes from relevant pathways (~79 Kb) and sequenced 125 patients with idiopathic erythrocytosis. The panel effectively screened 97% of coding regions of these genes, with an average coverage of 450×. It identified 51 different rare variants, all leading to alterations of protein sequence, with 57 out of 125 cases (45.6%) having at least one of these variants. Ten of these were known erythrocytosis-causing variants, which had been missed following existing diagnostic algorithms. Twenty-two were novel variants in erythrocytosis-associated genes (EGLN1, EPAS1, VHL, BPGM, JAK2, SH2B3) and in novel genes included in the panel (e.g. EPO, EGLN2, HIF3A, OS9), some with a high likelihood of functionality, for which future segregation, functional and replication studies will be useful to provide further evidence for causality. The rest were classified as polymorphisms. Overall, these results demonstrate the benefits of using a gene panel rather than existing methods in which focused genetic screening is performed depending on biochemical measurements: the gene panel improves diagnostic accuracy and provides the opportunity for discovery of novel variants.

Original publication

DOI

10.3324/haematol.2016.144063

Type

Journal article

Journal

Haematologica

Publication Date

11/2016

Volume

101

Pages

1306 - 1318

Keywords

Genetic Variation, Humans, Molecular Diagnostic Techniques, Mutation, Polycythemia, Sequence Analysis, DNA