FAME aimed to a) identify novel lipidomics biomarkers as biomarkers of fatty acid status and of future cardiometabolic clinical events, b) establish relationships between diet and tissue status of fatty acids as explanatory factors for diet relationships with cardiometabolic health, and c) to investigate genetic determinants of fatty acid status and metabolism which modify the effects of dietary intake. FAME identified and validated novel lipid biomarkers with the strong potential to define targeted dietary intervention for prevention. FAME has made use of several existing RCTs (PREDIMED, CORDIOPREV, DIVAS, RESET, SATgene, FLAVURS, CIRCLES) and the large prospective cohort study EPIC-Potsdam on diet and chronic disease and their biobanks which provided the unique opportunity to evaluate lipid biomarkers as a reflection of dietary intake and as risk factors and mediators for cardiometabolic health in different methodological settings. In WP1, new lipidomics profiles have been generated in the EPIC-Potsdam and CORDIOPREV. Analyses across different studies revealed several novel lipid markers related to cardiometabolic disease. E.g. significant association between a score composed of a combination of lipids and heart failure risk was found in the PREDIMED and replicated in EPIC-Potsdam. Also, lipids were identified to be associated with type 2 diabetes or CVD and were furthermore demonstrated to be partially influenced by modifying the fat composition of the diet in a randomized intervention study (DIVAS). In WP2, health benefits and potential novel biomarkers of dairy consumption have been investigated. In the French prospective cohort NutriNet-Santé, consumption of fermented dairy was associated with a lower risk of cerebrovascular disease. A specific method allowing optimal separation of dairy specific fatty acids have been developed and used for profiling in different RCTs. Furthermore, odd-chain saturated fatty acids have been linked to cardiometabolic risk in different studies, e.g. PREDIMED, CORRIOPREV and EPIC-Potsdam, also by use of deep lipidomics characterization of lipids containing such fatty acids. In WP3, genetic and dietary modulators of response to dietary FA intake were evaluated in terms of their effect on FA composition and cardiometabolic risk. Fatty acid profiles were generated in about 5000 samples from participants of different RCTs. Genetic variants involved in PUFA metabolism were shown to affect PUFA tissue response to a supplementation with nuts in PREDIMED and further analyses on interactions between genetic variants in PUFA metabolism genes and intake or status of n-6 and (long-chain) n-3 PUFA have been investigated in RCTs and cohorts.