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Genetic Epidemiology

Our bioinformatics laboratory investigates the genetic architecture of complex multifactorial traits and diseases using advanced statistical and computational approaches. We conduct genome-wide association studies (GWAS) to map common variants and apply rare-variant burden tests to detect low-frequency alleles contributing to phenotypic variation. For genetic risk stratification, we integrate  monogenic  findings  with  genome-wide  polygenic  scores,  yielding  individualized estimates that combine single-variant effects with overall polygenic burden.  

Our research spans targeted in-house projects, national and international cohort collaborations, and analyses of large population biobanks. To elucidate how non-coding variants influence complex traits, we analyze quantitative trait loci across multi-omics datasets—such as expression (eQTL) and protein (pQTL) data—at single-variant resolution. We further model genetically driven regulation through transcriptome- and proteome-wide association studies (TWAS and PWAS) in both bulk and single-cell contexts, revealing tissue- and cell-specific regulatory effects and prioritizing GWAS signals for downstream functional characterization.  

Based at the Center for Human Genetics, Philipps-Universität Marburg and Universitätsklinikum Marburg, our interdisciplinary team combines expertise in bioinformatics and statistical genetics to elucidate disease mechanisms and advance precision medicine applications.