AG Genetik 2

Understanding the causes of common diseases and their risk factors is a focus of health research, which can help us to prevent diseases or to apply a better treatment.

In my working group, we use complex multi-omics datasets to better understand the genetic and epigenetic relationships between diseases or their risk factors. For this purpose, information about genetic variation, gene expression and DNA methylation patterns primarily assessed via array technologies are analyzed. The comprehensively phenotyped data sets of the Greifswald SHIP, SHIP-Trend und GANI_MED studies, as well as data in cooperation within national and international consortia serve as the basis for our scientific projects. Another research focus is the analysis of causal relationships between diseases and their risk factors using genetic information (Mendelian randomization). The focus of our work is on the analysis of the hypothalamus-pituitary axis and the systemic effects of the thyroid, e.g. on kidney function.

The results of our work improve the understanding of the causes of diseases, and provide candidate genes for drug development.

• Conducting and leading of research projects for genome-wide, transcriptome-wide und epigenome-wide association studies focusing on thyroid, kidney function, and subcortical brain structures
• Quality control of array-based SNP, mRNA and DNA-methylation data
• Analyses of causal relationships using Mendelian randomization
• Education for (genetic) epidemiology at the University Medicine Greifswald and the Medical University of Bialystok
• Supervision of master and PhD students
• A list of funded research projects is available in the University’s research information system

• Ghasemi, S., Becker, T., Grabe, H. J. & Teumer, A. Discovery of novel eGFR-associated multiple independent signals using a quasi-adaptive method. Front. Genet. 13, 997302 (2022).
• Schlosser P, Tin A, Matias-Garcia PR, Thio CHL, Joehanes R, Liu H, ..., Köttgen A, Teumer A. Meta-analyses identify DNA methylation associated with kidney function and damage. Nat Commun. (2021);12: 7174.
• Ghasemi, S., Teumer, A., Wuttke, M. & Becker, T. Assessment of significance of conditionally independent GWAS signals. Bioinformatics 37, 3521–3529 (2021).
• Teumer A, Li Y, Ghasemi S, Prins BP, Wuttke M, Hermle T, et al. Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria. Nat Commun. (2019);10: 4130.
• Teumer A, Chaker L, Groeneweg S, Li Y, Di Munno C, Barbieri C, et al. Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation. Nat Commun. (2018);9: 4455.
• Teumer A, Schurmann C, Schillert A, Schramm K, Ziegler A, Prokisch H. Analyzing Illumina Gene Expression Microarray Data Obtained From Human Whole Blood Cell and Blood Monocyte Samples. Methods Mol Biol. (2016);1368: 85–97.
• Köttgen A, Albrecht E, Teumer A, Vitart V, Krumsiek J, Hundertmark C, et al. Genome-wide association analyses identify 18 new loci associated with serum urate concentrations. Nat Genet. (2013);45: 145–154.

All publications listed in PubMed