Automated reanalysis application to assist in detecting novel gene-disease associations after genome sequencing

Abstract

Purpose: This study aimed to investigate whether a bioinformatics application can streamline genome reanalysis and yield new diagnoses for patients with rare diseases.

Methods: We developed TierUp to identify variants in new disease genes for unresolved rare disease cases recruited to the 100,000 Genomes Project, all of whom underwent genome sequencing. TierUp uses the NHS Genomic Medicine Service bioinformatics infrastructure by securely accessing case details from the Clinical Interpretation Portal application programming interface and by querying the curated PanelApp database for novel gene-disease associations. We applied TierUp to 948 cases, and a subset of variants were reclassified according to the American College of Medical Genetics and Genomics/Association of Molecular Pathology guidelines.

Results: A rare form of spondylometaphyseal dysplasia was diagnosed through TierUp reanalysis, and an additional 4 variants have been reported to date. From a total of 564,441 variants across patients, TierUp highlighted 410 variants present in novel disease genes in under 77 minutes, successfully expediting an important reanalysis strategy.

Conclusion: TierUp supports claims that automation can reduce the time taken to reanalyze variants and increase the diagnostic yield from molecular testing. Clinical services should leverage bioinformatics expertise to develop tools that enable routine reanalysis. In addition, services must also explore the ethical, legal, and health economic considerations raised by automation.

Keywords: Automated variant reanalysis; Automated variant reclassification; Variant reanalysis; Variant reassessment; Variant reclassification.