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Accurate diagnosis of rare inherited anaemias is challenging, requiring a series of complex and expensive laboratory tests. Targeted next-generation-sequencing (NGS) has been used to investigate these disorders, but the selection of genes on individual panels has been narrow and the validation strategies used have fallen short of the standards required for clinical use. Clinical-grade validation of negative results requires the test to distinguish between lack of adequate sequencing reads at the locations of known mutations and a real absence of mutations. To achieve a clinically-reliable diagnostic test and minimize false-negative results we developed an open-source tool (CoverMi) to accurately determine base-coverage and the 'discoverability' of known mutations for every sample. We validated our 33-gene panel using Sanger sequencing and microarray. Our panel demonstrated 100% specificity and 99·7% sensitivity. We then analysed 57 clinical samples: molecular diagnoses were made in 22/57 (38·6%), corresponding to 32 mutations of which 16 were new. In all cases, accurate molecular diagnosis had a positive impact on clinical management. Using a validated NGS-based platform for routine molecular diagnosis of previously undiagnosed congenital anaemias is feasible in a clinical diagnostic setting, improves precise diagnosis and enhances management and counselling of the patient and their family.

Original publication

DOI

10.1111/bjh.14221

Type

Journal article

Journal

Br J Haematol

Publication Date

10/2016

Volume

175

Pages

318 - 330

Keywords

congenital dyserythropoietic anaemia, inherited anaemia, molecular genetics, next-generation sequencing, pyruvate kinase deficiency, Anemia, Computational Biology, Disease Management, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Testing, High-Throughput Nucleotide Sequencing, Humans, Infant, Male, Mutation, Polymorphism, Single Nucleotide, Rare Diseases, Reproducibility of Results, Workflow