Document Type

Article

Publication Date

9-1-2021

Publication Title

European journal of human genetics : EJHG

Keywords

JGM

JAX Source

Eur J Hum Genet 2021; 29:1337-1347

Volume

29

Issue

9

First Page

1337

Last Page

1347

ISSN

1476-5438

PMID

34075210

DOI

https://doi.org/10.1038/s41431-021-00852-7

Abstract

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.

Comments

Dr. Peter Robinson is a member of the Solve-RD Consortia.

This article is licensed under a Creative Commons Attribution 4.0 International License.

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