Browsing by Subject "Whole Exome Sequencing"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    A Genocentric Approach to Discovery of Mendelian Disorders.
    (American journal of human genetics, 2019-11) Hansen, Adam W; Murugan, Mullai; Li, He; Khayat, Michael M; Wang, Liwen; Rosenfeld, Jill; Andrews, B Kim; Jhangiani, Shalini N; Coban Akdemir, Zeynep H; Sedlazeck, Fritz J; Ashley-Koch, Allison E; Liu, Pengfei; Muzny, Donna M; Task Force for Neonatal Genomics; Davis, Erica E; Katsanis, Nicholas; Sabo, Aniko; Posey, Jennifer E; Yang, Yaping; Wangler, Michael F; Eng, Christine M; Sutton, V Reid; Lupski, James R; Boerwinkle, Eric; Gibbs, Richard A
    The advent of inexpensive, clinical exome sequencing (ES) has led to the accumulation of genetic data from thousands of samples from individuals affected with a wide range of diseases, but for whom the underlying genetic and molecular etiology of their clinical phenotype remains unknown. In many cases, detailed phenotypes are unavailable or poorly recorded and there is little family history to guide study. To accelerate discovery, we integrated ES data from 18,696 individuals referred for suspected Mendelian disease, together with relatives, in an Apache Hadoop data lake (Hadoop Architecture Lake of Exomes [HARLEE]) and implemented a genocentric analysis that rapidly identified 154 genes harboring variants suspected to cause Mendelian disorders. The approach did not rely on case-specific phenotypic classifications but was driven by optimization of gene- and variant-level filter parameters utilizing historical Mendelian disease-gene association discovery data. Variants in 19 of the 154 candidate genes were subsequently reported as causative of a Mendelian trait and additional data support the association of all other candidate genes with disease endpoints.
  • Thumbnail Image
    ItemOpen Access
    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.
    (Heart rhythm, 2018-07) Landstrom, Andrew P; Fernandez, Ernesto; Rosenfeld, Jill A; Yang, Yaping; Dailey-Schwartz, Andrew L; Miyake, Christina Y; Allen, Hugh D; Penny, Daniel J; Kim, Jeffrey J
    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.