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Imbalanced expression for predicted high-impact, autosomal-dominant variants in a cohort of 3,818 healthy samples

Authors
de Klein,Patrick Deelen
Urzua Urzua,Annique Claringbould,Vosa Vosa,Joost Verlouw,Monajemi Monajemi,t Hoen,Sinke Sinke,Swertz Swertz,Franke Franke,Nigel Klein,Freerk Dijk,C. Urzúa-Traslaviña,Urmo Võsa,Ramin Monajemi,Peter Hoen,Richard Sinke,Morris Swertz
+17 authors
,Lude Franke
Published
Sep 20, 2020
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Abstract

Abstract Background One of the growing problems in genome diagnostics is the increasing number of variants that get identified through genetic testing but for which it is unknown what the significance for the disease is (Variants of Unknown Significance - VUS) 1,2 . When these variants are observed in patients, clinicians need to be able to determine their relevance for causing the patient’s disease. Here we investigated whether allele-specific expression (ASE) can be used to prioritize disease-relevant VUS and therefore assist diagnostics. In order to do so, we conducted ASE analysis in RNA-seq data from 3,818 blood samples (part of the the Dutch BIOS biobank consortium), to ascertain how VUS affect gene expression. We compared the effect of VUS variants to variants that are predicted to have a high impact, and variants that are predicted to be pathogenic but are either recessive or autosomal-dominant with low penetrance. Results For immune and haematological disorders, we observed that 24.7% of known pathogenic variants from ClinVar show allelic imbalance in blood, as compared to 6.6% of known benign variants with matching allele frequencies. However, for other types of disorders, ASE information from blood did not distinguish (likely) pathogenic variants from benign variants. Unexpectedly, we identified 5 genes ( ALOX5, COMT, PRPF8, PSTPIP1 and SH3BP2 ) in which seven population-based samples had a predicted high impact, autosomal-dominant variant. For these genes the imbalanced expression of the major allele compensates for the lower expression of the minor allele. Conclusions Our analysis in a large population-based gene expression cohort reveals examples of high impact, autosomal-dominant variants that are compensated for by imbalanced expression. Additionally, we observed that ASE analyses in blood are informative for predicting pathogenic variants that are associated with immune and haematological conditions. We have made all our ASE results, including many ASE calls for rare variants (MAF < 1%), available at https://molgenis15.gcc.rug.nl/ .

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