RNA-sequencing improves diagnosis for neurodevelopmental disorders by identifying pathogenic non-coding variants and reinterpretation of coding variants

Abstract

BackgroundFor neurodevelopmental disorders (NDD), a molecular diagnosis is key for predicting outcome, treatment and genetic counseling. Currently, in about half of NDD cases, routine DNA-based testing fails to establish a genetic diagnosis. Transcriptome analysis (RNA-seq) improves the diagnostic yield for some groups of diseases, but has not been applied to NDD in a routine diagnostic setting.MethodsHere, we explored the diagnostic potential of RNA-seq in a cohort of 96 individuals including 67 undiagnosed NDD subjects. We created a user-friendly web-application to analyze RNA-seq data from single individuals’ cultured skin fibroblasts for genic, exonic and intronic expression outliers, based on modified OUTRIDER Z-scores. Candidate pathogenic events were complemented/matched with genomic data and, if required, confirmed with additional functional assays.ResultsWe identified pathogenic small genomic deletions, mono-allelic expression, aberrant splicing events, deep intronic variants resulting in pseudo-exon insertion, but also synonymous and nonsynonymous variants with deleterious effects on transcription. This approach increased the diagnostic yield for NDD by 12%. Diagnostic pitfalls during transcriptome analysis include detection of splice abnormalities in putative disease genes caused by benign polymorphisms and/or absence of expression of the responsible gene in the tissue of choice. This was misleading in one case and could have led to the wrong diagnosis in the absence of appropriate phenotyping.ConclusionsNonetheless, our results demonstrate the utility of RNA-seq in molecular diagnostics and stress the importance of multidisciplinary team consultation. In particular, the approach is useful for the identification and interpretation of unexpected pathogenic changes in mRNA processing and expression in NDD.

Functional Assays Combined with Pre-mRNA-Splicing Analysis Improve Variant Classification and Diagnostics for Individuals with Neurofibromatosis Type 1 and Legius Syndrome

“…: not significant. 10 Human Mutation discrepancies between the exon trap and RT-PCR results that would have led to a different classification for any of the variants tested, consistent with other work from our laboratory [24,40]. Furthermore, the exon trap analysis meant that the observed in vitro effects of a potentially pathogenic variant could be communicated prior to taking a tissue sample for confirmation.…”

High‐yield identification of pathogenic NF1 variants by skin fibroblast transcriptome screening after apparently normal diagnostic DNA testing

“…For cases from our clinic where other approaches fail to identify a pathogenic DNA variant, we apply RNA‐seq for transcriptome‐wide detection of abnormal transcripts (Cummings et al, 2017 ; Dekker et al, 2022 ; Kremer et al, 2017 ). We chose to analyze cultured skin fibroblast RNA as the expression of NF1 and many other genes is high compared to expression in lymphocytes (data not shown) and because our laboratory routinely uses cultured fibroblasts for the diagnosis of metabolic disorders, enzyme deficiencies, ciliopathies and neurodevelopmental disorders (van den Bosch et al, 2011 ; Dekker et al, 2022 ; Kheradmand Kia et al, 2012 ; Sofou et al, 2021 ). Furthermore, fibroblasts yield large amounts of high‐quality RNA and can easily be stored for reculture, validation, and further research.…”

“…In this respect, other NGS‐based approaches, including targeted RNA‐seq analysis after enrichment for NF1 transcripts, yielding a high gene‐specific coverage, or analysis of CAL or neurofibroma tissue directly increase the capacity to detect pathogenic variants (Koster et al, 2021 ; Maertens et al, 2007 ). Nonetheless, an advantage of our approach is that it is not limited to NF1, and the same laboratory flow can be applied to most genes that are expressed at moderate to high levels in cultured fibroblasts (Dekker et al, 2022 ).…”

“…Transcriptome analysis of RNA from skin fibroblasts by high throughput sequencing of cDNA libraries—RNAseq—, has been shown to be effective for the detection of pathogenic splice variants missed by routine DNA sequencing in a range of disorders (Cummings et al, 2017 ; Dekker et al, 2022 ; Kremer et al, 2017 ) and we reasoned that RNAseq of skin fibroblast RNA might improve molecular diagnostics for NF1 in our laboratory. Here we present our initial findings in a cohort of 15 NF1 NMI individuals.…”