Stepwise use of genomics and transcriptomics technologies increases diagnostic yield in Mendelian disorders

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Colin, Estelle | Duffourd, Yannis | Chevarin, Martin | Tisserant, Emilie | Verdez, Simon | Paccaud, Julien | Bruel, Ange-Line | Tran Mau-Them, Frédéric | Denommé-Pichon, Anne-Sophie | Thevenon, Julien | Safraou, Hana | Besnard, Thomas | Goldenberg, Alice | Cogné, Benjamin | Isidor, Bertrand | Delanne, Julian | Sorlin, Arthur | Moutton, Sébastien | Fradin, Mélanie | Dubourg, Christèle | Gorce, Magali | Bonneau, Dominique | El Chehadeh, Salima | Debray, François-Guillaume | Doco-Fenzy, Martine | Uguen, Kevin | Chatron, Nicolas | Aral, Bernard | Marle, Nathalie | Kuentz, Paul | Boland, Anne | Olaso, Robert | Deleuze, Jean-François | Sanlaville, Damien | Callier, Patrick | Philippe, Christophe | Thauvin-Robinet, Christel | Faivre, Laurence | Vitobello, Antonio

Edité par CCSD ; Frontiers media -

International audience. 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.

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