Stepwise use of genomics and transcriptomics technologies increases diagnostic yield in Mendelian disorders
Estelle Colin, Yannis Duffourd, Martin Chevarin, Émilie Tisserant, Simon Verdez, Julien Paccaud, Ange‐Line Bruel, Frédéric Tran Mau‐Them, Anne‐Sophie Denommé‐Pichon, Julien Thévenon, 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, Kévin 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
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.