While parts of the global population still suffer from mal- and under-nutrition, other parts of the population face – at least caloric – overfeeding. In obesity, too many calories are often accompanied by too few micronutrients (malnutrition). The combined public health care problems of diabetes and obesity (‘diabesity’) and metabolic syndrome cannot be sustainably addressed by pharmaceutical treatment alone. Systems health strategies complementing reductionist approaches are required to better understand and characterise the continuum of diabesity phenotypes1. Nutritional prevention is the key to the solution.
We have developed mass spectrometric technologies2 and workflows3 to analyse >1’000 human plasma samples each in two independent clinical obesity cohorts across a low-caloric weight reduction and a subsequent weight maintenance phase4,5. This integrated clinical proteomics platform has delivered protein signatures explanatory for the obesity condition, useful for cohort stratification, and – most importantly – predictive of dietary response4,5.
Audience take away:
- Multi-omics-based molecular phenotyping beyond genetics in humans is key to derive diagnostic fingerprints that can predict response to (nutritional) intervention and indicate/explain predisposition towards metabolic health conditions.
- Mass spectrometry-based proteomics has matured into a biomarker discovery platform that can deliver candidate diagnostic signatures to be validated and applied in assays compatible with clinics, medical cabinets, and – eventually – households. Robustness and throughput are key for a proteomics platform to be clinically applicable at large scale.
- In (clinical) nutrition biomarker research, minimally invasive sampling is typically required and, therefore, human blood plasma proteomics is often the tissue of choice. Yet, it is the most challenging human body fluid in terms of both composition and dynamic range.
- Replication of proteomic signatures in independent clinical cohorts has to date been rare, yet it is necessary.
- Proteomic signatures predictive of dietary response can help tailor nutritional interventions to specific obese sub-populations and thereby enable personalized nutrition for maintenance or restoration of metabolic health.