Identifying phenotypic expansions for congenital diaphragmatic hernia plus (CDH+) using DECIPHER data.
Amy HardcastleAliska M BerryIan M CampbellXiaonan ZhaoPengfei LiuAmanda E GerardJill A RosenfeldSaumya D SisoudiyaAndres Hernandez-GarciaSara LoddoSilvia Di TommasoAntonio NovelliMaria Lisa DenticiRossella CapolinoMaria C DigilioLudovico GrazianiCecilie F RustadKatherine NeasGiovanni B FerreroAlfredo BruscoEleonora Di GregorioDiana WellesleyClaire BeneteauMadeleine JoubertKris Van Den BogaertAnneleen BoogaertsDominic J McMullanJohn DeanMaria G GiuffridaLaura BernardiniVinod VargheseNora L ShannonRachel E HarrisonWayne W K LamShane McKeePeter D TurnpennyTrevor ColeJenny MortonJacqueline EasonMarilyn C JonesRebecca HallMichael WrightKaren HorridgeChad A ShawWendy K ChungDaryl A ScottPublished in: American journal of medical genetics. Part A (2022)
Congenital diaphragmatic hernia (CDH) can occur in isolation or in conjunction with other birth defects (CDH+). A molecular etiology can only be identified in a subset of CDH cases. This is due, in part, to an incomplete understanding of the genes that contribute to diaphragm development. Here, we used clinical and molecular data from 36 individuals with CDH+ who are cataloged in the DECIPHER database to identify genes that may play a role in diaphragm development and to discover new phenotypic expansions. Among this group, we identified individuals who carried putatively deleterious sequence or copy number variants affecting CREBBP, SMARCA4, UBA2, and USP9X. The role of these genes in diaphragm development was supported by their expression in the developing mouse diaphragm, their similarity to known CDH genes using data from a previously published and validated machine learning algorithm, and/or the presence of CDH in other individuals with their associated genetic disorders. Our results demonstrate how data from DECIPHER, and other public databases, can be used to identify new phenotypic expansions and suggest that CREBBP, SMARCA4, UBA2, and USP9X play a role in diaphragm development.
Keyphrases
- copy number
- genome wide
- machine learning
- big data
- mechanical ventilation
- electronic health record
- mitochondrial dna
- dna methylation
- healthcare
- bioinformatics analysis
- poor prognosis
- gene expression
- acute respiratory distress syndrome
- artificial intelligence
- mental health
- data analysis
- adverse drug
- deep learning
- genome wide analysis
- amino acid
- gestational age