Using blood RNA-seq to study rare-disease genes

It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene. The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases. This includes muscle biopsies from patients with undiagnosed rare muscle disorders, and cultured fibroblasts from patients with mitochondrial disorders. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access.

Stanford University researchers sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. They generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. They developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across their cohort, the researchers observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.

ran-seq

a, Disease categories of sequenced affected patients. The majority of individuals have diseases in the neurology (n = 40), musculoskeletal and orthopedics (n = 8), hematology (n = 8) and ophthalmology (n = 8) categories. b, Percentages of disease genes (from curated lists) expressed in blood. We used the median TPM across 909 DGN samples, 65 PIVUS samples and our 143 samples.

Availability – The pipeline to highlight candidate variants is available at https://github.com/lfresard/blood_rnaseq_rare_disease_paper/blob/master/pipeline.md

Q&A with senior author Stephen Montgomery

Frésard L et al. (2019) Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. Nat Med 25(6):911-919. [abstract]

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