A Genocentric Approach to Discovery of Mendelian Disorders.

TitleA Genocentric Approach to Discovery of Mendelian Disorders.
Publication TypeJournal Article
Year of Publication2019
AuthorsHansen, AW, Murugan, M, Li, H, Khayat, MM, Wang, L, Rosenfeld, J, B Andrews, K, Jhangiani, SN, Akdemir, ZHCoban, Sedlazeck, FJ, Ashley-Koch, AE, Liu, P, Muzny, DM, Davis, EE, Katsanis, N, Sabo, A, Posey, JE, Yang, Y, Wangler, MF, Eng, CM, V Sutton, R, Lupski, JR, Boerwinkle, E, Gibbs, RA
Corporate AuthorsTask Force for Neonatal Genomics
JournalAm J Hum Genet
Volume105
Issue5
Pagination974-986
Date Published2019 11 07
ISSN1537-6605
KeywordsDatabases, Genetic, Exome, Genetic Diseases, Inborn, Genetic Predisposition to Disease, Genetic Variation, Genomics, Humans, Pedigree, Phenotype, Whole Exome Sequencing
Abstract

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.

DOI10.1016/j.ajhg.2019.09.027
Alternate JournalAm. J. Hum. Genet.
PubMed ID31668702
PubMed Central IDPMC6849092
Grant ListP50 MH094268 / MH / NIMH NIH HHS / United States
UM1 HG006542 / HG / NHGRI NIH HHS / United States
K08 HG008986 / HG / NHGRI NIH HHS / United States
UM1 HG008898 / HG / NHGRI NIH HHS / United States
R35 NS105078 / NS / NINDS NIH HHS / United States
P50 DK096415 / DK / NIDDK NIH HHS / United States
R01 NS058529 / NS / NINDS NIH HHS / United States
T32 GM008307 / GM / NIGMS NIH HHS / United States