Metabolomics

Disease and Lifestyle Biomarkers

We are searching for chemical substances that are characteristic for chronic diseases (e.g. diabetes, cardio-vascular diseases) and a certain lifestyle. Also, we are investigating in host-pathogen interactions. So far, we could identify biomarkers for lifestyle factors such as coffee consumption, smoking or nutrition habits. Furthermore, we could identify diabetes specific metabolic pathways.

Research highlights:

Questionnaire-based self-reported nutrition habits associate with serum metabolism as revealed by quantitative targeted metabolomics
It is unclear in how far self-reported nutrition intake reflects de facto differences in body metabolite composition. To investigate this question on an epidemiological scale we conducted a metabolomics study analyzing the association of self-reported nutrition habits with 363 metabolites quantified in blood serum of 284 male participants of the KORA population study. Published in Eur J Epidemiol, 2010. Article

Drug Metabolism

We are investigating the molecular mechanisms of drugs using data from human cohort studies and animal models.

Research highlights:

Effects of antihypertensives and lipid-lowering drugs on the human metabolism
We report a metabolome-wide association study with 295 metabolites in human serum from 1,762 participants of the KORA F4 study population. Our intent was to find variations of metabolite concentrations related to the intake of various drug classes and — based on the associations found — to generate new hypotheses about on-target as well as off-target effects of these drugs. In total, we found 41 significant associations for the drug classes investigated. Published in Genetic Epidemiology, 2014. Article

Uncovering old and new tales of diabetic mice under medication
We performed a systematic analysis of a targeted quantitative characterization of more than 800 metabolites in blood plasma samples from healthy and diabetic mice under rosiglitazone treatment. We show that known and new metabolic phenotypes of diabetes and medication can be recovered in a statistically objective manner. Published in Endocrinology, 2008. Article