We perform quantitative empirical research with the aim of helping the development of prevention strategies for neurodegenerative and other age-related diseases, most notably dementia.
We focus on the identification of causes and causal disease mechanisms that can be targeted to prevent or delay onset of clinical disease (etiologic research). Furthermore, we aim to identify biomarkers and develop methods to assess disease risk (risk prediction and risk stratification).
Most age-related diseases occur as the cumulative resultant of varying combinations of protective, restorative, and detrimental factors. The determinants of resilience thereby remain largely unknown. Alongside studying pathophysiology, we aim to better comprehend normal (brain) physiology and physiologic variation, and how this changes over the life course.
To understand what determines people's health one has to study people. Most of our research is being performed in the context of the Rhineland Study, a prospective cohort study that we designed and initiated to address our key research objectives.
Our epidemiologic approach is highly interdisciplinary, and methodologically and technologically advanced. On the data acquisition side we emphasize deep phenotyping and incorporate novel technologies and insights from basic research early on in our studies. On the data analytical side we collaborate with computational data scientists to develop and use innovative methods on our high-dimensional and multimodal data.
Currently, the following research is ongoing
Etiology of diseases
We investigate the effect of diet and other life style factors on cognition and brain health and the possible underlying mechanisms. This research is closely aligned with our examination of the gut microbiome composition in relation to brain outcomes, and with our investigation into the role of infections, (neuro-)inflammation, and the immune status in aging and disease development. Research in this area is supported by the Competence Cluster “Diet-Body-Brain (DietBB)”, the Helmholtz Initiative on personalized medicine (iMed), and the Excellence Cluster “Immunosensation”.
Biomarker discovery and risk prediction
We use advanced brain imaging to non-invasively gather information about brain structure and function to develop imaging biomarkers. Moreover we use high-dimensional multiomic data to derive (blood-based) biomarkers for risk prediction and risk stratification. In this context we collaborate with several other groups at the DZNE, and within the Excellence Cluster “Computational Science for Complex Systems (CASCADE)”.
Normal physiology and aging
We focus on the role of stress in health and disease; the relation between sensory systems and brain structure and function; biomarkers of aging; and pharmacoepidemiologic and pharmacogenomic research. The research is supported by the European Joint Programming Initiative – a Healthy Diet for a Healthy Life (JPI-HDHL) (HEALTHMARK and AMBROSIAC), and by BfArM.