We perform quantitative empirical research with the aim of understanding what determines people’s health across their life span. Specifically, we focus on the identification of causes and causal disease mechanisms that can be targeted to prevent or delay the onset of clinical disease (etiologic research). We also aim to identify biomarkers and develop methods to assess disease risk. Our goal is to aid the development of prevention strategies for neurodegenerative and other age-related diseases, most notably dementia. 

Most age-related diseases occur as the cumulative resultant of varying combinations of protective, restorative, and detrimental factors. We are interested in the effects of the exposome as well as the (epi)genome on health. To derive imaging as well as blood-based biomarkers of (healthy) aging and to find people at risk, we use advanced brain imaging and leverage high-dimensional multi-omic data. In addition, we are interested in the relation between sensory systems and brain structure and function, and conduct pharmacoepidemiologic and pharmacogenomic research. 

Core data collection includes behavioral assessments, cardiovascular measures, sensory systems assessments, as well as questions on medical history, medication intake, life style, nutrition and mental health. Besides detailed clinical data, we also collect wide-ranging omics data, including (epi-)genomic arrays, RNA-Seq, metabolomics, lipidomics, gut microbiome analyses and immune profiles. In addition, all eligible participants of the Rhineland Study undergo an advanced 1h MRI protocol. To develop and use innovative methods on our high-dimensional and multimodal data, we collaborate with computational data scientists. The cohort currently comprises more than 10,000 participants – but up to 20,000 participants will be studied in total.

Current research projects