AG Genetic Epidemiology

Understanding the causes of common diseases and their risk factors is a focus of health research, which helps us identifying the effective treatment at the right time depending on the individual characteristics of each patient.

In my workgroup, 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 using complex statistical models and machine learning approaches. 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 like the ThyroidOmics Consortium, the CKDGen Consortium or ENIGMA serve as the basis for our scientific projects.

Further research topics include the analysis of causal relationships between diseases and their risk factors using genetic information as instruments (Mendelian randomization), and automatic segmentation of MRI images of hypothalamus-pituitary-thyroid (HPT) axis related organs. The segmentation of the brain structures is done in close collaboration with the imaging unit (AG Bildgebung) at the department.

The general focus of our work lies on the HPT axis and the systemic effects of the thyroid hormones, e.g. on kidney disease and brain aging, and in translating our findings into clinical routine aiming to help in disease treatment and prevention.

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

• 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

• Bujnis MN, Sterenborg RBTM, Li Y, Åsvold BO, Brčić L, Boraska Perica V, …, Medici M, Teumer A. Multi-ancestry genome-wide association analyses provide insights into the genetic basis of Hashimoto’s thyroiditis. Nat Genet. (2026) 58, 1855–1865.
• Weihs AL, Wittfeld K, Bülow R, Wielpütz MO, Nauck M, Völzke H, Grabe H, Teumer A. Thyroid hormones are associated with pituitary and thyroid volume in a population-based study. J Endocr Soc. (2026);10: bvag060.
• Nasr MK, König E, Fuchsberger C, Ghasemi S, Völker U, Völzke H, Grabe H, Teumer A. Removing array-specific batch effects in GWAS mega-analyses by applying a two-step imputation workflow. Bioinforma Adv. (2026);6: vbaf317.
• Sterenborg RBTM, Steinbrenner I, Li Y, Bujnis MN, Naito T, Marouli E, …, Teumer A, Medici M. Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications. Nat Commun. (2024); 15: 888.
• Nasr MK, Schurmann C, Böttinger EP, Teumer A. Mendelian randomization indicates causal effects of estradiol levels on kidney function in males. Front Endocrinol (Lausanne). (2023);14:1232266.
• Weihs A, Chaker L, Martin TC, Braun KVE, Campbell PJ, …, Teumer A. Epigenome-Wide Association Study Reveals CpG Sites Associated with Thyroid Function and Regulatory Effects on KLF9. Thyroid. (2023). 301-311.
• 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).
• Grasby KL, Jahanshad N, Painter JN, Janowitz D, ..., Teumer A, ..., Wittfeld K, ..., Grabe HJ, ..., Medland SE. The genetic architecture of the human cerebral cortex. Science. (2020);367(6484):eaay6690
• 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