P855 - LIPIDOMIC PROFILE ANALYSIS REVEALS NEW LINKS TO SARCOPENIC OBESITY CRITERIA IN THE OBESAR COHORT

P855

LIPIDOMIC PROFILE ANALYSIS REVEALS NEW LINKS TO SARCOPENIC OBESITY CRITERIA IN THE OBESAR COHORT

F. Capel^1,*, A. Pinel¹, M. Pouget², A. Mulliez³, M. Ponnaiah⁴, M. Lhomme⁴, M. Miolanne², N. Farigon², O. Le Bacquer¹, C. Guillet¹, Y. Boirie^1,2

¹Human Nutrition Unit, Clermont Auvergne University, INRAE, ²Clinical Nutrition Department, ³Biostatistics Unit, CHU Clermont-Ferrand, Clermont-Ferrand, ⁴ICAN OMICS and ICAN I/O, IHU ICAN , Foundation For Innovation in Cardiometabolism and Nutrition, Paris, France

Rationale: Sarcopenic obesity (SO) is recognized as a clinical entity defined by a low muscle mass and function, together with a high body fatness. This study aimed to investigate how the circulating lipidome could enhance our understanding of the early mechanisms underlying SO and the diagnosis of sarcopenia in patients with obesity.

Methods: A circulating lipidomic profile was obtained by LC-MS/MS from patients in the OBESAR cohort (age 54.8±6.3 years; BMI 44±6kg/m²; weight 114.7±17kg). An ANOVA compared lipid profiles across 3 groups stratified by the severity of SO (Low, medium, high) using the SO phenotype index (SOPi). SOPi was calculated using a formula that incorporates handgrip strength, appendicular lean mass and body fat. A t-test compared low versus high SOPi and a binary logistic regression model was applied to classify patients into the 2 groups. Finally, the correlation between lipid levels and SOPi was assessed using Pearson correlation test. Subsequently, a multivariate linear regression model was calculated for lipids exhibiting significant correlation.

Results: In a group of 130 female patients, 53 lipid species were significantly altered across the 3 SOPi groups (P<0.05). The binary logistic model demonstrated a sensitivity of 82% in classifying low and high SOPi patients using 6 variables. Among all lipids tested for linear correlation with the SOPi, 3 species containing polyunsaturated fatty acids (PUFA) were used to construct a linear regression model which was found to be significantly inversely related to SOPi.

Conclusion: These results demonstrate alterations in plasma lipidomic profile in a population of patients with severe obesity. A subset of lipid species containing PUFA are correlated with criteria of SO. These lipid metabolites could be useful to identify patients at high risk of SO or to better target nutritional or pharmacological interventions in these patients.

Disclosure of Interest: None declared