Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield
of patients with rare diseases. However, the cost and efforts required for reanalysis
prevent its routine implementation in research and clinical environments. The Solve-RD
project aims to reveal the molecular causes underlying undiagnosed rare diseases.
One of the goals is to implement innovative approaches to reanalyse the exomes and
genomes from thousands of well-studied undiagnosed cases. The raw genomic data is
submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP)
together with standardised phenotypic and pedigree data. We have developed a programmatic
workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application
Programming Interface (API) and relies on the big-data technologies upon which the
system is built. We have applied the workflow to prioritise rare known pathogenic
variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants
per case, which first were evaluated in bulk by a panel of disease experts and afterwards
specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised
cases, 2.7% of all exome/genome-negative samples) have already been solved, with others
being under investigation. The implementation of solutions as the one described here
provide the technical framework to enable periodic case-level data re-evaluation in
clinical settings, as recommended by the American College of Medical Genetics.
