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

TitleIdentification of rare-disease genes using blood transcriptome sequencing and large control cohorts.
Publication TypeJournal Article
Year of Publication2019
AuthorsFrésard, L, Smail, C, Ferraro, NM, Teran, NA, Li, X, Smith, KS, Bonner, D, Kernohan, KD, Marwaha, S, Zappala, Z, Balliu, B, Davis, JR, Liu, B, Prybol, CJ, Kohler, JN, Zastrow, DB, Reuter, CM, Fisk, DG, Grove, ME, Davidson, JM, Hartley, T, Joshi, R, Strober, BJ, Utiramerur, S, Lind, L, Ingelsson, E, Battle, A, Bejerano, G, Bernstein, JA, Ashley, EA, Boycott, KM, Merker, JD, Wheeler, MT, Montgomery, SB
Corporate AuthorsUndiagnosed Diseases Network, Care4Rare Canada Consortium
JournalNat Med
Date Published2019 06
KeywordsAcid Ceramidase, Case-Control Studies, Child, Child, Preschool, Cohort Studies, Female, Genetic Variation, Humans, Male, Models, Genetic, Mutation, Oxidoreductases Acting on CH-CH Group Donors, Potassium Channels, Rare Diseases, RNA, RNA Splicing, Sequence Analysis, RNA, Whole Exome Sequencing

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. 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.

Alternate JournalNat. Med.
PubMed ID31160820
PubMed Central IDPMC6634302
Grant ListR01 HG008150 / HG / NHGRI NIH HHS / United States
U01 HG007708 / HG / NHGRI NIH HHS / United States
U01 HG010218 / HG / NHGRI NIH HHS / United States
U01 HG009080 / HG / NHGRI NIH HHS / United States
T32 HG000044 / HG / NHGRI NIH HHS / United States
T32 LM012409 / LM / NLM NIH HHS / United States