| Literature DB >> 30430034 |
Danielle A Callaway1, Ian M Campbell2, Samantha R Stover3, Andres Hernandez-Garcia3, Shalini N Jhangiani3,4, Jaya Punetha3, Ingrid S Paine3, Jennifer E Posey3, Donna Muzny3,4, Kevin P Lally5, James R Lupski3,4,6, Chad A Shaw3, Caraciolo J Fernandes6, Daryl A Scott3,7.
Abstract
Wolf-Hirschhorn syndrome (WHS) is caused by partial deletion of the short arm of chromosome 4 and is characterized by dysmorphic facies, congenital heart defects, intellectual/developmental disability, and increased risk for congenital diaphragmatic hernia (CDH). In this report, we describe a stillborn girl with WHS and a large CDH. A literature review revealed 15 cases of WHS with CDH, which overlap a 2.3-Mb CDH critical region. We applied a machine-learning algorithm that integrates large-scale genomic knowledge to genes within the 4p16.3 CDH critical region and identified FGFRL1 , CTBP1 , NSD2 , FGFR3 , CPLX1 , MAEA , CTBP1-AS2 , and ZNF141 as genes whose haploinsufficiency may contribute to the development of CDH.Entities:
Keywords: Wolf–Hirschhorn syndrome; congenital diaphragmatic hernia; machine-learning algorithm
Year: 2018 PMID： 30430034 PMCID： PMC6234038 DOI： 10.1055/s-0038-1655755
Source DB: PubMed Journal: J Pediatr Genet ISSN： 2146-460X