Human Genetics and Genomics AdvancesGenetic & Genomic MedicinePeer-reviewed journal article
Identification and validation of novel candidate risk genes in endocytic vesicular trafficking associated with esophageal atresia and tracheoesophageal fistulas
Guojie ZhongiD, Priyanka R. AhimaziD, Nicole A. EdwardsiD, Jacob Hagen, Christophe C. FaureiD, Lu QiaoiD, Paul S. KingmaiD, William MiddlesworthiD, Julie KhlevneriD, Mahmoud M. A. ElfikyiD, David T. Schindel, Elizabeth FialkowskiiD, Adhish Kashyap, Sophia Forlenza, Alan P. KennyiD, Aaron M. ZorniD, Yufeng SheniD, Wendy K. ChungiD
Abstract
Esophageal atresias/tracheoesophageal fistulas (EA/TEF) are rare congenital anomalies caused by aberrant development of the foregut. Previous studies indicate that rare or de novo genetic variants significantly contribute to EA/TEF risk, and most individuals with EA/TEF do not have pathogenic genetic variants in established risk genes. To identify novel genetic contributions to EA/TEF, we performed whole genome sequencing of 185 trios (probands and parents) with EA/TEF, including 59 isolated and 126 complex cases with additional congenital anomalies and/or neurodevelopmental disorders. There was a significant burden of protein altering de novo coding variants in complex cases (p=3.3e-4), especially in genes that are intolerant of loss of function variants in the population. We performed simulation analysis of pathway enrichment based on background mutation rate and identified a number of pathways related to endocytosis and intracellular trafficking that as a group have a significant burden of protein altering de novo variants. We assessed 18 variants for disease causality using CRISPR-Cas9 mutagenesis in Xenopus and confirmed 13 with tracheoesophageal phenotypes. Our results implicate disruption of endosome-mediated epithelial remodeling as a potential mechanism of foregut developmental defects. This research may have implications for the mechanisms of other rare congenital anomalies.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 14
- FWCI
- 2.63
- Field percentile
- top 10%
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