Mass spectrometry-based analysis of serum metabolome in malnutrition and sarcopenia: preliminary results from SENIOR study

Malnutrition is one of the most pressing problems globally. In Italy, the most affected are low-income families, people with diseases, and elderly individuals. Additionally, the group of people at risk of malnutrition is growing due to the ageing population and the consequential increase in the burden of diseases and health care costs. Sarcopenia is a progressive and generalized skeletal muscle disorder associated with an increased likelihood of adverse outcomes including falls, fractures, physical disability, and mortality. Sarcopenia is linked to several risk factors, including malnutrition, immobilization, disease, and inflammation [1]. The SENIOR project is a cross-sectional multicentre study aimed to assess the prevalence of malnutrition and sarcopenia and the impact of lifestyle, health status and quality of life on the occurrence of these conditions in patients over 65 years of age. This study aims to identify new circulating biomarkers of sarcopenia and malnutrition, representing new research products based on already collected data. To address this issue a mass spectrometry-based metabolomic approach have been performed to discover novel circulating biomarkers of sarcopenia severity and malnutrition. After solvent extraction, serum metabolites have been separated by liquid chromatography on a UPLC HClass coupled to a Xevo G2-XS qTOF mass spectrometer (Waters Corporation) through an ESI source. Progenesis QI (Waters) and Metaboanalyst software were used for data processing and statistical analysis. Comparing the metabolomic profile of 38 patients with overt and severe sarcopenia and 37 non-sarcopenic subjects, multivariate analysis allowed to identify a total of 39 discriminating features with Qvalue<0.05 and a VIP value>1 in PLS-DA analysis. In conclusion, these preliminary results suggest that metabolomic profile analysis might be regarded as a possible tool to discover predictive biomarkers of sarcopenia progression. Discriminating metabolites resulting from multivariate analysis will be also analysed in correlation with data on lifestyle and inflammatory profile.