The power of next-generation-sequencing: A game-changer with limitations

Abstract

The article by Baardman et al.¹ tackles the power of next-generation sequencing (NGS) in the context of the evolution of genome diagnostics in epidermolysis bullosa (EB), a prototypic group of rare disorders with skin fragility characterized by blistering after minimal trauma with disruption at the dermo-epidermal junction. The authors investigated the utility of NGS in EB diagnostics by systematically evaluating the performance of different types of genome diagnostics based on data from the Dutch EB Registry.

A basic prerequisite for early prognostication of the disease course, genetic counselling and future gene therapeutic approaches is the exact detection of the disease-causing gene variants in EB and other genodermatoses which is carried out using various methods of genome diagnostics that are currently considered as gold standard. However, skin biopsy and subsequent immunofluorescence mapping may still be valuable. Particularly severe phenotypes of EB often require rapid initial diagnosis and parents might not want to wait for the result of a lengthy NGS procedure. Furthermore, the absence of laminin-332 and collagen VII protein expression at the BMZ can be a more sensitive marker than the type of mutation in laminin-332 genes and in COL7A1, respectively. For example, splice site mutations have unpredictable effects on the open reading frame of mature transcripts and can result in either premature protein truncation (severe) or a partially functional protein (non-severe). Finally, the level of the residual protein expression and the type of gene mutation can have a major impact on patient enrolment in clinical trials for EB molecular therapies.²

NGS refers to a high-throughput nucleotide sequencing method that allows the sequencing of multiple genes in parallel. It has significantly increased the speed of DNA sequencing in genetic diagnostics, making it more accessible for research institutions and clinics. However, despite these advancements, NGS is not without challenges.

To improve current EB diagnostics and identify all causative variants in EB patients, the development and implementation of additional powerful techniques (e.g. whole-genome-, long-read- and RNA sequencing) and the improvement of bioinformatic data analysis algorithms are necessary.

Supported by DEBRA Austria.

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