Genetic Epidemiology of Heart Failure

Coordinator:    Prof. Dr. Monika Stoll
Institution: Leibniz-Institut für Arterioskleroseforschung an der Universität Münster
The subproject „Genetic Epidemiology of Heart Failure“ supports the IG on the dissection of the genetic basis of cardiovascular diseases by usage of established statistical and bioinformatics tools as well as by development of novel algorithms.

Within the framework of the GWAS consortium statistical analyses are performed for the genome-wide association studies (GWAS) regarding the phenotypes dilated cardiomyopathy (DCM) and left ventricular hypertrophy (LVH). By this hypothesis-free approach, hundreds of thousands different genetic markers (single nucleotide polymorphism, SNP) are compared between numerous affected and unaffected probands. The statistical association of these markers sheds light on genes, which may contribute to the disease in interaction with other genes and factors.

A locus on chromosome 6p21 has been identified for DCM (fig. 1), which indicates the influence of inflammatory processes in development of DCM. The strongest associated SNP has been replicated successfully in a replication cohort from Germany and Italy as well as in a French cohort. Recently, the results of this study have been accepted for publication by the European Heart Journal.

For downstream analysis of GWAS results a new R programme package “postgwas” has been developed and is publicly available for the research community at the CRAN webpage ( Besides generation of annotated Manhattan and regional plots, it enables the visualization of gene networks, which are connected with associated SNPs from a GWA study. Several public or custom data sources can be used as basis for network topology such as protein-protein-interactions or gene ontology annotations. Subsequently, the network is divided into functional sub-networks by applying a graph partitioning algorithm. A further R package “boostSeq” is developed for selection of a set of most informative probands for next generation sequencing of selected target regions discovered by a GWA study.

Furthermore, GWAS results from the four subphenotypes DCM, LVH, atrial fibrillation and diastolic dysfunction are combined within a meta analysis to identify further susceptibility loci for heart failure.

Fig. 1: Manhattan plot of the genome-wide association-study for DCM. Each dot represents a genetic marker (SNP) at its genomic position (x-axis). Minus Log10 p-values (y-axis) indicate the strength of the association. A locus on chromosome 6 shows particularly strong association with DCM.
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