Lookup NU author(s): Dr Peter Carey
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
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 997% sensitivity. We then analysed 57 clinical samples: molecular diagnoses were made in 22/57 (386%), 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.
Author(s): Roy NBA, Wilson EA, Henderson S, Wray K, Babbs C, Okoli S, Atoyebi W, Mixon A, Cahill MR, Carey P, Cullis J, Curtin J, Dreau H, Ferguson DJP, Gibson B, Hall G, Mason J, Morgan M, Proven M, Qureshi A, Garcia JS, Sirachainan N, Teo J, Tedgard U, Higgs D, Roberts D, Roberts I, Schuh A
Publication type: Article
Publication status: Published
Journal: British Journal of Haematology
Print publication date: 01/10/2016
Online publication date: 19/07/2016
Acceptance date: 08/05/2016
Date deposited: 16/01/2017
ISSN (print): 0007-1048
ISSN (electronic): 1365-2141
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