Prioritization of Candidate Genes for Congenital Diaphragmatic Hernia in a Critical Region on Chromosome 4p16 using a Machine-Learning Algorithm

J Pediatr Genet. 2018 Dec;7(4):164-173. doi: 10.1055/s-0038-1655755. Epub 2018 May 30.


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.

Publication types

  • Case Reports