Pathogenic Mechanisms in Neurodevelopmental Disorders: Advances in Cellular Models and Multi-omics Approaches

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Cover image for research topic "Pathogenic Mechanisms in Neurodevelopmental Disorders: Advances in Cellular Models and Multi-omics Approaches"
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Original Research
28 February 2023
Stepwise use of genomics and transcriptomics technologies increases diagnostic yield in Mendelian disorders
Estelle Colin
37 more and 
Antonio Vitobello

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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