2023 ACMG Annual Clinical Genetics Meeting Digital Edition: Poster Gallery-Early Results from a Multiomics Cohort: Unique RIPK1 Fusions Identified in Two Individuals with Irritable Bowel Disease

Early Results from a Multiomics Cohort: Unique RIPK1 Fusions Identified in Two Individuals with Irritable Bowel Disease
Back to course

Pdf Summary
In this document, researchers at Mayo Clinic describe their multiomics approach to identify potential disease-causing genetic variations in patients who had previously undergone exome sequencing (ES) but did not receive a diagnosis. They collected exome sequencing and RNA-seq data from blood samples of 405 individuals referred to their diagnostic program. Using the Combined Annotation Dependent Depletion (CADD) algorithm, they identified the highest scoring rare variant per gene from the ES data. They also extracted outlier gene expression, splicing alterations, allele-specific expression, and fusion transcripts from the RNA-seq data. These different types of data were combined to create a multiomics p-value per gene, allowing for the ranking of genes across multiple data types. The researchers used the Phenotype Consensus Analysis (PCAN) tool to score the correlation between phenotype and genotype based on human phenotype ontology terms. Genes with multiple hits from different data types that ranked in the top 15 for at least one data type were selected. Genes that were hits in more than 10 of the 405 individuals and genes without a PCAN rank were excluded. From these filtering parameters, they found promising results for 15 individuals (3.7% of the cohort). Two of these hits were unique fusions in the RIPK1 gene, which had phenotypic overlap with reported disorders associated with variants in this gene. However, further work is needed to confirm the pathogenicity of these fusions and single nucleotide variants. The researchers noted that both loss-of-function and functional variants in the RIPK1 gene have been implicated in irritable bowel disease. The fusion in patient one preserved most of the kinase domain and may result in gain-of-function. The zygosity of these fusion events is currently unknown, and it is uncertain what the disease mechanism may be for these patients. In conclusion, the multiomics approach used in this study showed promise in identifying potential disease-causing genetic variations in patients who had previously undergone ES without a diagnosis. This method has the potential to broaden the understanding of disease causality beyond the primary DNA sequence. The researchers plan to improve their multiomics platform by incorporating genome sequencing methylation and structural variant data.

Asset Subtitle

Presenting Author - Joseph Farris, PhD; Co-Author - Gavin Oliver, MS; Co-Author - Garrett Jenkinson, PhD; Co-Author - Andrew Osbourne, MS; Co-Author - Sarah Kroc, MS, CGC; Co-Author - Teresa Kruisselbrink, MS; Co-Author - Ralitza Gavrilova, MD; Co-Author - Michael Stephens, MD; Co-Author - Eric Klee;

Meta Tag

Bioinformatics

Exome sequencing

Gastrointestinal System

Phenotype

Co-Author Gavin Oliver, MS

Co-Author Garrett Jenkinson, PhD

Co-Author Andrew Osbourne, MS

Co-Author Sarah Kroc, MS, CGC

Co-Author Teresa Kruisselbrink, MS

Co-Author Ralitza Gavrilova, MD

Co-Author Michael Stephens, MD

Co-Author Eric Klee

Presenting Author Joseph Farris, PhD

Keywords

Mayo Clinic

multiomics approach

disease-causing genetic variations

exome sequencing

CADD algorithm

RNA-seq data

gene expression

fusion transcripts

RIPK1 gene

irritable bowel disease