학술논문
Stepwise use of genomics and transcriptomics technologies increases diagnostic yield in Mendelian disorders
Document Type
article
Author
Estelle Colin; Yannis Duffourd; Martin Chevarin; Emilie Tisserant; Simon Verdez; Julien Paccaud; Ange-Line Bruel; Frédéric Tran Mau-Them; Anne-Sophie Denommé-Pichon; Julien Thevenon; Hana Safraou; Thomas Besnard; Alice Goldenberg; Benjamin Cogné; Bertrand Isidor; Julian Delanne; Arthur Sorlin; Sébastien Moutton; Mélanie Fradin; Christèle Dubourg; Magali Gorce; Dominique Bonneau; Salima El Chehadeh; François-Guillaume Debray; Martine Doco-Fenzy; Kevin Uguen; Nicolas Chatron; Bernard Aral; Nathalie Marle; Paul Kuentz; Anne Boland; Robert Olaso; Jean-François Deleuze; Damien Sanlaville; Patrick Callier; Christophe Philippe; Christel Thauvin-Robinet; Laurence Faivre; Antonio Vitobello
Source
Frontiers in Cell and Developmental Biology, Vol 11 (2023)
Subject
Language
English
ISSN
2296-634X
Abstract
Purpose: Multi-omics offer worthwhile and increasingly accessible technologies to diagnostic laboratories seeking potential second-tier strategies to help patients with unresolved rare diseases, especially patients clinically diagnosed with a rare OMIM (Online Mendelian Inheritance in Man) disease. However, no consensus exists regarding the optimal diagnostic care pathway to adopt after negative results with standard approaches.Methods: In 15 unsolved individuals clinically diagnosed with recognizable OMIM diseases but with negative or inconclusive first-line genetic results, we explored the utility of a multi-step approach using several novel omics technologies to establish a molecular diagnosis. Inclusion criteria included a clinical autosomal recessive disease diagnosis and single heterozygous pathogenic variant in the gene of interest identified by first-line analysis (60%–9/15) or a clinical diagnosis of an X-linked recessive or autosomal dominant disease with no causative variant identified (40%–6/15). We performed a multi-step analysis involving short-read genome sequencing (srGS) and complementary approaches such as mRNA sequencing (mRNA-seq), long-read genome sequencing (lrG), or optical genome mapping (oGM) selected according to the outcome of the GS analysis.Results: SrGS alone or in combination with additional genomic and/or transcriptomic technologies allowed us to resolve 87% of individuals by identifying single nucleotide variants/indels missed by first-line targeted tests, identifying variants affecting transcription, or structural variants sometimes requiring lrGS or oGM for their characterization.Conclusion: Hypothesis-driven implementation of combined omics technologies is particularly effective in identifying molecular etiologies. In this study, we detail our experience of the implementation of genomics and transcriptomics technologies in a pilot cohort of previously investigated patients with a typical clinical diagnosis without molecular etiology.