Amino acid-level signal-to-noise analysis of incidentally identified variants in genes associated with long QT syndrome during pediatric whole exome sequencing reflects background genetic noise.

Published

Journal Article

BACKGROUND: Due to rapid expansion of clinical genetic testing, an increasing number of genetic variants of undetermined significance and unclear diagnostic value are being identified in children. Variants found in genes associated with heritable channelopathies, such as long QT syndrome (LQTS), are particularly difficult to interpret given the risk of sudden cardiac death associated with pathologic mutations. OBJECTIVE: The purpose of this study was to determine whether variants in LQTS-associated genes from whole exome sequencing (WES) represent disease-associated biomarkers or background genetic "noise." METHODS: WES variants from Baylor Genetics Laboratories were obtained for 17 LQTS-associated genes. Rare variants from healthy controls were obtained from the GnomAD database. LQTS case variants were extracted from the literature. Amino acid-level mapping and signal-to-noise calculations were conducted. Clinical history and diagnostic studies were analyzed for WES subjects evaluated at our institution. RESULTS: Variants in LQTS case-associated genes were present in 38.3% of 7244 WES probands. There was a similar frequency of variants in the WES and healthy cohorts for LQTS1-3 (11.2% and 12.9%, respectively) and LQTS4-17 (27.1% and 38.4%, respectively). WES variants preferentially localized to amino acids altered in control individuals compared to cases. Based on amino acid-level analysis, WES-identified variants are indistinguishable from healthy background variation, whereas LQTS1 and 2 case-identified variants localized to clear pathologic "hotspots." No individuals who underwent clinical evaluation had clinical suspicion for LQTS. CONCLUSION: The prevalence of incidentally identified LQTS-associated variants is ∼38% among WES tests. These variants most likely represent benign healthy background genetic variation rather than disease-associated mutations.

Full Text

Duke Authors

Cited Authors

  • Landstrom, AP; Fernandez, E; Rosenfeld, JA; Yang, Y; Dailey-Schwartz, AL; Miyake, CY; Allen, HD; Penny, DJ; Kim, JJ

Published Date

  • July 2018

Published In

Volume / Issue

  • 15 / 7

Start / End Page

  • 1042 - 1050

PubMed ID

  • 29501670

Pubmed Central ID

  • 29501670

Electronic International Standard Serial Number (EISSN)

  • 1556-3871

Digital Object Identifier (DOI)

  • 10.1016/j.hrthm.2018.02.031

Language

  • eng

Conference Location

  • United States