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

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. PMID: 31160820 Funding information This work was supported by: NLM NIH HHS, United States Grant ID: T32 LM012409 NIH HHS, United States Grant ID: S10 OD023452 NHGRI NIH HHS, United States Grant ID: T32 HG000044 NHGRI NIH HHS, United States Grant ID: U01 HG009080 NLM NIH HHS, United States Grant ID: T15 LM007033 NHGRI NIH HHS, United States Grant ID: U01 HG010218 NHGRI NIH HHS, United States Grant ID: U01 HG007708 NHGRI NIH HHS, United States Grant ID: R01 HG008150 More Less keyboard_arrow_down