Optimized selection process to identify a metabolic syndrome metabolomic/lipidomic signature in older adults of the NuAge cohort

Poster presentations / European Geriatric Medicine 8S1 (2017) S40–S247National audienceIntroduction: Metabolic syndrome (MetS) is characterized by a cluster of risk factors including obesity, metabolic dysregulations such as insulin resistance, hypertension, and dyslipidemia, raising the risk for type 2 diabetes development and its complications. It involves multifaceted processes at multiple levels that are still far from being understood. New tools are therefore necessary to bring new knowledge about MetS, better stratify populations and customise strategies for its prevention and/or reversal. Methods: The Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge) regroups 853 men and 940 women, aged 68–82 at recruitment in 2003–2005 (T1) and followed up annually for three years (T2-T4). In the present study, a nested case-control study on MetS was designed to identify a metabolomic/lipidomic signature of MetS in older men, reflecting its phenotypic spectrum. An optimized participant selection strategy was developed based on presence and number of MetS criteria, including medication, their stability over 3 years, as well as the identification of outliers. Results: The final selection included 123 men, 61 cases and 62 controls, with similar age and partial overlap of values defining MetS. This design is necessary to precisely detect and estimate the amplitude of metabolic deviations among the massive data sets, at an individual metabolite level as well as for a multivariate description. Conclusion: This selection process, optimized to limit cofounding effects, will allow identifying specific metabolomic/lipidomic signatures along with significant features for sample classification. Thus, one complex molecular phenotyping will provide a new approach/tool for a better MetS stratification in elderl