Stepwise use of genomics and transcriptomics technologies increases diagnostic yield in Mendelian disorders - 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; et al. (Frontiers in Cell and Developmental Biology, 2023)
Purpose: Multi-omics approaches represent attractive tools becoming more accessible to diagnostic laboratories, striving for potential second-tier strategies to solve unsolved rare disease patients, and in particular, individuals with a clinical diagnosis of a rare OMIM disease. However, there is no consensus regarding the best diagnostic care pathway to undertake after negative reference approaches. Methods: In 15 unsolved individuals with a clinical diagnosis of recognizable OMIM diseases but with negative or inconclusive first-line genetic results, we explored the utility of a multi-step approach deploying several novel omics technologies to establish a molecular diagnosis. The inclusion criteria included the clinical diagnosis of an autosomal recessive disease and a 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 solve 87% of individuals thanks to the identification of single nucleotide variants/indels missed by first-line targeted tests, the identification of variants affecting transcription, or structural variant sometimes requiring lrGS or oGM to be resolved. Conclusion: Hypothesis-driven implementation of combined omics technologies is particularly effective in identifying molecular etiologies. In this study, we return our experience on the implementation of genomics and transcriptomics technologies in a pilot cohort of already explored patients with a typical clinical diagnosis without a molecular etiology.