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In the Institute of Genetic Epidemiology at the Medical Center – University of Freiburg, we are interested in risk factors for and consequences of complex diseases. Complex diseases are thought to arise from a combination of environmental exposures and genetic susceptibility variants. We are working in four areas to gain insights into the physiology of complex traits and the pathophysiology of complex diseases:

  1. The design and conduct of epidemiological studies to study causes and progression of complex diseases
  2. The identification and characterization of (epi-)genetic risk variants 
  3. The influence of endo- and exogenous environmental and metabolic risk factors on disease risk
  4. The development of methods in molecular epidemiology

Our goal is to better understand how genetic variants interact with the environment to shape complex traits and diseases. We attempt to initiate experimental follow-up projects to understand the functions of disease risk genes and how genetic variation leads to impaired function. 

A special focus of our work is the investigation of the genetic underpinnings of kidney function in health and disease. Chronic kidney disease (CKD) is the most common form of kidney disease with a prevalence of 5-10% among adults. It is defined by a decreased ability of the kidneys to clear the blood, or by kidney damage. Not only can CKD progress to kidney failure, but it also increases risk for cardiovascular morbidity and mortality. Other complex traits of special interest are hyperuricemia and gout, thyroid function and disease, and disorders of electrolyte and metabolite handling.

1. The design and conduct of epidemiological studies to study causes and progression of complex diseases

To gain a better understanding of causes and consequences of CKD, we are participating in the conduct and analysis of epidemiological and clinical studies. We are directing one of nine study centers of the German Chronic Kidney Disease (GCKD) Study (http://www.gckd.de). This observational prospective study enrolled 5,217 participants sinc 2010 with CKD and follows them for renal and cardiovascular events for up to ten years. We are collecting detailed information about disease etiology and progression from each participant. In addition, we are working on data from 15,792 participants of the large ongoing observational Atherosclerosis Risk in Communities (ARIC) Study in the United States (https://www2.cscc.unc.edu/aric/) as well as on several other cohort studies including the newly established German National Cohort Health Study (http://www.nako.de).

2. The identification and characterization of (epi-)genetic risk variants

Genetic variation is assessed both through genotyping and sequencing. We are interested in the evaluation of candidate genes as well as in the conduct of genome-wide genetic screens. These screens evaluate millions of genetic variants and have the potential to discover genes not previously known to be associated with complex traits or diseases. 

The genome-wide genetic screens mostly carried out in the setting of large international collaborations such as the CHARGE Consortium or the CKDGen Consortium. Researchers in the CKDGen Consortium, which Dr. Köttgen is co-directing, have combined information from more than 750,000 individuals, resulting in the identification of >250 genomic loci in which variation associates with altered kidney function and CKD risk. Datasets from publications of the CKDGen Consortium can be found here. We are currently further extending these genetic studies in terms of sample size (>1 million participants), number of genetic variants, and the range of studied diseases. In addition, we are establishing international collaborations to search for disease-associated DNA methylation sites through epigenome-wide association studies.

3. The influence of endo- and exogenous environmental and metabolic risk factors on disease risk

Complex diseases result from a combination of genetic susceptibility variants in many genes and their interactions with the environment. We study both the “internal environment” (e.g., through quantification of biomarkers and metabolites such as glucose) as well as the “external environment” (e.g., through quantification of xenobiotics and questionnaires about lifestyle factors, medication intake and diet). We use high-throughput methods such as metabolomics and proteomics that can capture both types of exposures from collected biomaterials in an unbiased and comprehensive manner. By integrating metabolomics and genomics data, we gain novel insights into human physiology and pathophysiology in general and in mechanisms of metabolite detoxification and excretion in particular.

4. The development of methods in molecular epidemiology

Population-based biomedical science, and in particular statistical genomics, has seen a rapid development in recent years with respect to measurement technologies (omics quantification), data availability (mega biobank-scale datasets such as UK Biobank) and the methods available to analyze at this sample size and resolution. At the Institute, we bring together expertise from statistics, bioinformatics, biology and medicine to develop the methods to gain insights into the physiology and pathophysiology of complex traits and diseases, with a particular focus on causal inference, integrative omics, and conducting large-scale meta-analyses of genetic studies.


Our research is supported by several national and international funding agencies (Funded projects). We are part of the Collaborative Research Centers (CRC) 992 (http://www.sfb992.uni-freiburg.de), 1479 (https://www.sfb1479.uni-freiburg.de) and 1597 (https://www.smalldata-initiative.de) of the German Research Foundation at the University of Freiburg, Germany, and lead the CRC 1453 (NephroGenetics, https://www.sfb1453.uni-freiburg.de). These CRCs aim to understand mechanisms underlying complex (epi)genetic diseases thereby generating optimal synergies. Additional funding by the German Research Foundation supports our research into renal metabolite handling and the identification of novel imaging-based biomarkers of kidney function based on whole-body MRIs of 35,000 study participants. We participate in the EU Innovative Training Network “CKDTrainDis”.