Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts

Undiagnosed Diseases Network, Care4Rare Canada Consortium

Research output: Contribution to journalLetter

7 Citations (Scopus)

Abstract

It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene1. The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches2–5. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases6–8. This includes muscle biopsies from patients with undiagnosed rare muscle disorders6,9, and cultured fibroblasts from patients with mitochondrial disorders7. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We 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 our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.

Original languageEnglish (US)
Pages (from-to)911-919
Number of pages9
JournalNature medicine
Volume25
Issue number6
DOIs
StatePublished - Jun 1 2019
Externally publishedYes

Fingerprint

RNA Sequence Analysis
Rare Diseases
Transcriptome
Blood
Genes
RNA
Exome
Biopsy
Muscle
Tissue
Muscles
Molecular Pathology
Fibroblasts
Gene Expression
Mutation

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. / Undiagnosed Diseases Network; Care4Rare Canada Consortium.

In: Nature medicine, Vol. 25, No. 6, 01.06.2019, p. 911-919.

Research output: Contribution to journalLetter

Undiagnosed Diseases Network ; Care4Rare Canada Consortium. / Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. In: Nature medicine. 2019 ; Vol. 25, No. 6. pp. 911-919.
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abstract = "It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene1. The current molecular diagnostic rate is estimated at 50{\%}, with whole-exome sequencing (WES) among the most successful approaches2–5. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases6–8. This includes muscle biopsies from patients with undiagnosed rare muscle disorders6,9, and cultured fibroblasts from patients with mitochondrial disorders7. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We 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 our cohort, we observed that RNA-seq yields a 7.5{\%} diagnostic rate, and an additional 16.7{\%} with improved candidate gene resolution.",
author = "{Undiagnosed Diseases Network} and {Care4Rare Canada Consortium} and Laure Fr{\'e}sard and Craig Smail and Ferraro, {Nicole M.} and Teran, {Nicole A.} and Xin Li and Smith, {Kevin S.} and Devon Bonner and Kernohan, {Kristin D.} and Shruti Marwaha and Zachary Zappala and Brunilda Balliu and Davis, {Joe R.} and Boxiang Liu and Prybol, {Cameron J.} and Kohler, {Jennefer N.} and Zastrow, {Diane B.} and Reuter, {Chloe M.} and Fisk, {Dianna G.} and Grove, {Megan E.} and Davidson, {Jean M.} and Taila Hartley and Ruchi Joshi and Strober, {Benjamin J.} and Sowmithri Utiramerur and Adams, {David R.} and Aaron Aday and Alejandro, {Mercedes E.} and Patrick Allard and Ashley, {Euan A.} and Azamian, {Mahshid S.} and Bacino, {Carlos A.} and Eva Baker and Ashok Balasubramanyam and Hayk Barseghyan and Batzli, {Gabriel F.} and Beggs, {Alan H.} and Babak Behnam and Bellen, {Hugo J.} and Bernstein, {Jonathan A.} and Berry, {Gerard T.} and Anna Bican and Bick, {David P.} and Birch, {Camille L.} and Devon Bonner and Boone, {Braden E.} and Bostwick, {Bret L.} and Briere, {Lauren C.} and Elly Brokamp and Melissa Haendel and David Koeller",
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AU - Li, Xin

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AU - Bonner, Devon

AU - Kernohan, Kristin D.

AU - Marwaha, Shruti

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AU - Adams, David R.

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AU - Allard, Patrick

AU - Ashley, Euan A.

AU - Azamian, Mahshid S.

AU - Bacino, Carlos A.

AU - Baker, Eva

AU - Balasubramanyam, Ashok

AU - Barseghyan, Hayk

AU - Batzli, Gabriel F.

AU - Beggs, Alan H.

AU - Behnam, Babak

AU - Bellen, Hugo J.

AU - Bernstein, Jonathan A.

AU - Berry, Gerard T.

AU - Bican, Anna

AU - Bick, David P.

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AU - Bonner, Devon

AU - Boone, Braden E.

AU - Bostwick, Bret L.

AU - Briere, Lauren C.

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N2 - It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene1. The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches2–5. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases6–8. This includes muscle biopsies from patients with undiagnosed rare muscle disorders6,9, and cultured fibroblasts from patients with mitochondrial disorders7. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We 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 our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.

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