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Updated: Aug 10, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Evaluating High-Confidence Genes in Conotruncal Cardiac Defects by Gene Burden Analyses
Martin M C Chui1, Christopher C Y Mak1, Mullin H C Yu1
1Department of Paediatrics and Adolescent Medicine, School of Clinical Medicine, LKS Faculty of Medicine The University of Hong Kong Hong Kong SAR China.
Abstract:
Background In nonsyndromic conotruncal cardiac defects, the use of next-generation sequencing for clinical diagnosis is increasingly adopted, but gene-disease associations in research are only partially translated to diagnostic panels, suggesting a need for evidence-based consensus. Methods and Results In an exome data set of 245 patients with conotruncal cardiac defects, we performed burden analysis on a high-confidence congenital heart disease gene list (n=132) with rare (<0.01%) and ultrarare (absent in the Genome Aggregation Database) protein-altering variants. Overall, we confirmed an excess of rare variants compared with ethnicity-matched controls and identified 2 known genes (GATA6, NOTCH1) and 4 candidate genes supported by the literature (ANKRD11, DOCK6, NPHP4, and STRA6). Ultrarare variant analysis was performed in combination with 3 other published studies (n=1451) and identified 3 genes (FLT4, NOTCH1, TBX1) to be significant, whereas a subgroup analysis involving 391 Chinese subjects identified only GATA6 as significant. Conclusions We suggest that these significant genes in our rare and ultrarare burden analyses warrant prioritization for clinical testing implied for rare inherited and de novo variants. Additionally, associations on ClinVar for these genes were predominantly variants of uncertain significance. Therefore, a more stringent assessment of gene-disease associations in a larger and ethnically diverse cohort is required to be prudent for future curation of conotruncal cardiac defect genes.
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