A comprehensive iterative approach is highly effective in diagnosing individuals who are exome negative.

Published

Journal Article

PURPOSE:Sixty to seventy-five percent of individuals with rare and undiagnosed phenotypes remain undiagnosed after exome sequencing (ES). With standard ES reanalysis resolving 10-15% of the ES negatives, further approaches are necessary to maximize diagnoses in these individuals. METHODS:In 38 ES negative patients an individualized genomic-phenotypic approach was employed utilizing (1) phenotyping; (2) reanalyses of FASTQ files, with innovative bioinformatics; (3) targeted molecular testing; (4) genome sequencing (GS); and (5) conferring of clinical diagnoses when pathognomonic clinical findings occurred. RESULTS:Certain and highly likely diagnoses were made in 18/38 (47%) individuals, including identifying two new developmental disorders. The majority of diagnoses (>70%) were due to our bioinformatics, phenotyping, and targeted testing identifying variants that were undetected or not prioritized on prior ES. GS diagnosed 3/18 individuals with structural variants not amenable to ES. Additionally, tentative diagnoses were made in 3 (8%), and in 5 individuals (13%) candidate genes were identified. Overall, diagnoses/potential leads were identified in 26/38 (68%). CONCLUSIONS:Our comprehensive approach to ES negatives maximizes the ES and clinical data for both diagnoses and candidate gene identification, without GS in the majority. This iterative approach is cost-effective and is pertinent to the current conundrum of ES negatives.

Full Text

Duke Authors

Cited Authors

  • Shashi, V; Schoch, K; Spillmann, R; Cope, H; Tan, QK-G; Walley, N; Pena, L; McConkie-Rosell, A; Jiang, Y-H; Stong, N; Need, AC; Goldstein, DB; Undiagnosed Diseases Network,

Published Date

  • January 2019

Published In

Volume / Issue

  • 21 / 1

Start / End Page

  • 161 - 172

PubMed ID

  • 29907797

Pubmed Central ID

  • 29907797

Electronic International Standard Serial Number (EISSN)

  • 1530-0366

International Standard Serial Number (ISSN)

  • 1098-3600

Digital Object Identifier (DOI)

  • 10.1038/s41436-018-0044-2

Language

  • eng