Prioritization of Candidate Genes for Congenital Diaphragmatic Hernia in a Critical Region on Chromosome 4p16 using a Machine-Learning Algorithm - Callaway, Danielle A.; Campbell, Ian M.; Stover, Samantha R.; Hernandez-Garcia, Andres; Jhangiani, Shalini N.; Punetha, Jaya; Paine, Ingrid S.; Posey, Jennifer E.; Muzny, Donna; Lally, Kevin P.; Lupski, James R.; Shaw, Chad A.; Fernandes, Caraciolo J.; Scott, Daryl A. (Journal of Pediatric Genetics, 2018)
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.
Keywords: Wolf–Hirschhorn syndrome; congenital diaphragmatic hernia; machine-learning algorithm