Evaluating High-Confidence Genes in Conotruncal Cardiac Defects by Gene Burden Analyses.

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.

Diagnostic potential of the amniotic fluid cells transcriptome in deciphering mendelian disease: a proof-of-concept.

RNA sequencing (RNA-seq) is emerging in genetic diagnoses as it provides functional support for the interpretation of variants of uncertain significance. However, the use of amniotic fluid (AF) cells for RNA-seq has not yet been explored. Here, we examined the expression of clinically relevant genes in AF cells (n = 48) compared with whole blood and fibroblasts. The number of well-expressed genes in AF cells was comparable to that in fibroblasts and much higher than that in blood across different disease categories. We found AF cells RNA-seq feasible and beneficial in prenatal diagnosis (n = 4) as transcriptomic data elucidated the molecular consequence leading to the pathogenicity upgrade of variants in CHD7 and COL1A2 and revising the in silico prediction of a variant in MYRF. AF cells RNA-seq could become a reasonable choice for postnatal patients with advantages over fibroblasts and blood as it prevents invasive procedures.