Deep lipidomics profiling generates superior surrogate markers for the long-term cardiometabolic health effect of improved dietary fat quality
Dr. Wittenbecher’s research leverages molecular profiling data, especially metabolomics, to elucidate the link between dietary composition and cardiometabolic disease risk. Core methods include data-driven network analyses, risk prediction, machine learning, and causal modeling approaches in prospective cohorts and diet intervention trials. Dr. Wittenbecher’s research aims to strengthen the evidence for the causal role of diet composition in cardiometabolic disease etiology and develop biomarkers for precision nutrition approaches.