Due to long-running global demographic changes, age, aging-associated diseases and obesity-related co-morbidities develop into a significant challenge in all areas of society. Therefore, a better understanding, measurement and intervention of age-related changes in human physiology is of critical importance. The University of Cologne with it’s Excellence Cluster for Aging (CECAD), as well as the neighboring Max Planck Institutes, form a center of aging research in Germany and beyond.
Research Objectives
Create better metrics for measurement of age-related changes and decline
Validate findings on molecular changes in aging and dysregulated metabolism from model organisms, cell line experiments and smaller studies in a large human cohort
Elucidate the role of increasing stochasticity and its effects in human aging across levels of information
Research Questions
How well, and how far in the future, can human (multi-)morbidity be predicted from biological data?
What factors in biological measurements drive those predictions, and could they be manipulated for improving human health with age?
How are genetic variants in genes involved in metabolism associated with obesity- and age-related co-morbidities?
Scientific Rationale
Numerous publications have shown that human age can be predicted from biological data, most prominently with the discovery of methylation aging clocks in 2013 (Horvath, Hannum). In 2024, a competition to benchmark the best aging clocks was started (“Biomarkers of Aging Challenge”). Proteomics will likely play an important role in the upcoming comparison of multi-morbidity predictions. The UK Biobank contains one of the largest omics datasets matched with health data, and thus is indispensable for building a competitive measurement algorithm. To elucidate the mechanisms driving these predictive models, we aim to investigate specific aspects like molecular changes in the cardio-metabolic syndrome and its interplay with genetic variation.