Elucidation of the genetic causes of bicuspid aortic valve disease.

AIMS The present study aims to characterize the genetic risk architecture of bicuspid aortic valve (BAV) disease, the most common congenital heart defect. METHODS AND RESULTS We carried out a genome-wide association study (GWAS) including 2236 BAV patients and 11 604 controls. This led to the identification of a new risk locus for BAV on chromosome 3q29. The single nucleotide polymorphism rs2550262 was genome-wide significant BAV associated (P = 3.49 × 10-08) and was replicated in an independent case-control sample. The risk locus encodes a deleterious missense variant in MUC4 (p.Ala4821Ser), a gene that is involved in epithelial-to-mesenchymal transformation. Mechanistical studies in zebrafish revealed that loss of Muc4 led to a delay in cardiac valvular development suggesting that loss of MUC4 may also play a role in aortic valve malformation. The GWAS also confirmed previously reported BAV risk loci at PALMD (P = 3.97 × 10-16), GATA4 (P = 1.61 × 10-09), and TEX41 (P = 7.68 × 10-04). In addition, the genetic BAV architecture was examined beyond the single-marker level revealing that a substantial fraction of BAV heritability is polygenic and ∼20% of the observed heritability can be explained by our GWAS data. Furthermore, we used the largest human single-cell atlas for foetal gene expression and show that the transcriptome profile in endothelial cells is a major source contributing to BAV pathology. CONCLUSION Our study provides a deeper understanding of the genetic risk architecture of BAV formation on the single marker and polygenic level

A genome-wide association study with tissue transcriptomics identifies genetic drivers for classic bladder exstrophy

Classic bladder exstrophy represents the most severe end of all human congenital anomalies of the kidney and urinary tract and is associated with bladder cancer susceptibility. Previous genetic studies identified one locus to be involved in classic bladder exstrophy, but were limited to a restrict number of cohort. Here we show the largest classic bladder exstrophy genome-wide association analysis to date where we identify eight genome-wide significant loci, seven of which are novel. In these regions reside ten coding and four non-coding genes. Among the coding genes is EFNA1, strongly expressed in mouse embryonic genital tubercle, urethra, and primitive bladder. Re-sequence of EFNA1 in the investigated classic bladder exstrophy cohort of our study displays an enrichment of rare protein altering variants. We show that all coding genes are expressed and/or significantly regulated in both mouse and human embryonic developmental bladder stages. Furthermore, nine of the coding genes residing in the regions of genome-wide significance are differentially expressed in bladder cancers. Our data suggest genetic drivers for classic bladder exstrophy, as well as a possible role for these drivers to relevant bladder cancer susceptibility. A genome-wide association study on classic bladder exstrophy reveals eight genome-wide significant loci, most of which contained genes expressed in embryonic developmental bladder stages

Elucidation of the genetic causes of bicuspid aortic valve disease

Aims The present study aims to characterize the genetic risk architecture of bicuspid aortic valve (BAV) disease, the most common congenital heart defect. Methods and results We carried out a genome-wide association study (GWAS) including 2236 BAV patients and 11 604 controls. This led to the identification of a new risk locus for BAV on chromosome 3q29. The single nucleotide polymorphism rs2550262 was genome-wide significant BAV associated (P = 3.49 x 10(-08)) and was replicated in an independent case-control sample. The risk locus encodes a deleterious missense variant in MUC4 (p.Ala4821Ser), a gene that is involved in epithelial-to-mesenchymal transformation. Mechanistical studies in zebrafish revealed that loss of Muc4 led to a delay in cardiac valvular development suggesting that loss of MUC4 may also play a role in aortic valve malformation. The GWAS also confirmed previously reported BAV risk loci at PALMD (P = 3.97 x 10(-16)), GATA4 (P = 1.61 x 10(-09)), and TEX41 (P = 7.68 x 10(-04)). In addition, the genetic BAV architecture was examined beyond the single-marker level revealing that a substantial fraction of BAV heritability is polygenic and similar to 20% of the observed heritability can be explained by our GWAS data. Furthermore, we used the largest human single-cell atlas for foetal gene expression and show that the transcriptome profile in endothelial cells is a major source contributing to BAV pathology. Conclusion Our study provides a deeper understanding of the genetic risk architecture of BAV formation on the single marker and polygenic level

First genome-wide association study of esophageal atresia identifies three genetic risk loci at CTNNA3, FOXF1/FOXC2/FOXL1, and HNF1B

Esophageal atresia with or without tracheoesophageal fistula (EA/TEF) is the most common congenital malformation of the upper digestive tract. This study represents the first genome-wide association study (GWAS) to identify risk loci for EA/TEF. We used a European case-control sample comprising 764 EA/TEF patients and 5,778 controls and observed genome-wide significant associations at three loci. On chromosome 10q21 within the gene CTNNA3 (p = 2.11 x 10(-8); odds ratio [OR] = 3.94; 95% confidence interval [CI], 3.10-5.00), on chromosome 16q24 next to the FOX gene cluster (p = 2.25 x 10(-10); OR = 1.47; 95% CI, 1.38-1.55) and on chromosome 17q12 next to the gene HNF1B (p = 3.35 x 10(-16); OR = 1.75; 95% CI, 1.64-1.87). We next carried out an esophageal/tracheal transcriptome profiling in rat embryos at four selected embryonic time points. Based on these data and on already published data, the implicated genes at all three GWAS loci are promising candidates for EA/TEF development. We also analyzed the genetic EA/TEF architecture beyond the single marker level, which revealed an estimated single-nucleotide polymorphism (SNP)-based heritability of around 37% +/- 14% standard deviation. In addition, we examined the polygenicity of EA/TEF and found that EA/TEF is less polygenic than other complex genetic diseases. In conclusion, the results of our study contribute to a better understanding on the underlying genetic architecture of ET/TEF with the identification of three risk loci and candidate genes