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GUARD – Genes Underlying Aortic valve Disease

Aortic valve stenosis (AS) is characterized by thickened and calcified valvular cusps, causing an obstruction of the left ventricular outflow. Severe AS represents a significant cause of morbidity and mortality and affects around 5% of individuals over 70 years of age [1]. The pathophysiology of AS remains poorly understood, although it has several clinical and pathological findings in common with atherosclerotic diseases [2]. In addition, early developmental pathways play an important role in variation of the anatomical structure of aortic valves and thereby influence the risk for developing AS. Bicuspid aortic valve (BAV), the most common congenital heart disease, accelerates the development of AS by decades. While the prevalence of BAV is 0.5-2% in the general population, it is found in up to half of patients with severe AS [3].

In the vast majority of cases AS, has a multifactorial etiology, i.e. it involves a combination of the cumulative effect of genetic risk variants and environmental factors. In recent years, it has become possible to identify the genetic risk variants underlying multifactorial diseases through the development of genome-wide association studies (GWAS). This method has already been successfully applied to AS and led to the identification of genetic risk variants near the genes PALMD, TEX41, LPA, and MYH6 [4]. Most of these associations showed pleiotropic effects with other cardiovascular traits, for example, aortic valve calcification, coronary artery disease, serum Lp(a) levels, and congenital heart diseases. Although this GWAS has substantially contributed to a better understanding about the genetics of AS and has suggested the first relevant biological mechanisms, most of the genetic factors that contribute to AS have not yet been identified. In order to further elucidate the complex genetic architecture that contributes to AS, we have founded the scientific network GUARD (Genes Underlying Aortic valve Disease, GUARD is already well established with regard to the recruitment of a large number of phenotypically characterized aortic valve disease patients, with both bicuspid and tricuspid backgrounds, for large-scale molecular genetic studies. At present, 700 patients with BAV and 600 patients with tricuspid AS have already been recruited through GUARD, and the enrolment of further patients is ongoing in the participating centers Bonn, Cologne, and Düsseldorf for tricuspid AS and nation-wide for BAV.

We hypothesize that the development of bicuspid and tricuspid AS is profoundly influenced by genetic risk variants.

Thus, the aim of the project is to further elucidate the complex genetic mechanisms that contribute to AS development. In Aim 1, we will perform a GWAS using our already recruited BAV sample (N = 700 patients), together with an already genome-wide genotyped BAV sample (N = 410) from the Institute for Cardiogenetics at the University of Lübeck. All identified risk variants from our final GWAS sample of >1,100 BAV cases will be followed up by in silico functional studies, in order to determine their cellular function and to identify disease-relevant biological pathways. Aim 2 will focus on tricuspid AS. We will perform a GWAS using 2,000 patients with severe and 1,000 with moderate AS, recruited through GUARD, and will combine the data with already existing GWAS data on tricuspid AS. Patients with moderate AS are included to better understand the genetic determinants of slow versus fast progression of the disease in a five-year longitudinal study with yearly follow-ups. Like for BAV, identified risk variants will be followed up by in silico functional studies in order to elucidate the molecular pathophysiology. In Aim 3, we will compare our GWAS data (from Aims 1 and 2) with GWAS data from other cardiovascular diseases (e.g. atrial septal defect, ventricular septal defect, CAD) on the polygenic level. We also will perform enrichment analyses of concordant effects between risk variants of etiologically shared diseases on the single-marker level and will use shared risk variants for pathway analyses. Aim 4 plans to use the findings from other TR259 projects (disease-relevant genes and pathways) in order to systematically test them for association enrichment in our GWAS data. In addition, we will estimate polygenic risk scores using our GWAS data for different human cell lines that are investigated by other TR259 projects. This will enable the other groups to perform stratified analyses of cell lines with high/low polygenic risk load. In Aim 5, we will recruit 1,000 independent BAV and 1,000 independent tricuspid AS patients for future stage-2 GWAS, which will further elucidate the genetic background of aortic valve disease. In addition, we will use our entire GWAS samples in the future for detailed genotype-phenotype (GxP) studies, using our phenotypically well-characterized patients.

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