From Molecular Profiling to Precision Medicine in Metabolic Syndrome - Université Clermont Auvergne Accéder directement au contenu
Poster De Conférence Année : 2019

From Molecular Profiling to Precision Medicine in Metabolic Syndrome

Blandine Comte
Cécile Canlet
Benoit Colsch
Charlotte Joly
Natacha Lenuzza
  • Fonction : Auteur
Bernard Lyan
Carole Migné
José A. Morais
  • Fonction : Auteur
Mélanie Pétéra
Etienne Thévenot
  • Fonction : Auteur
Christophe Junot
  • Fonction : Auteur

Résumé

Metabolic syndrome (MetS), defined as a cluster of cardio-metabolic factors including obesity, hypertension, dysglycemia, and dyslipidemia, and mostly affecting older adults, is now a public health challenge because of its growing prevalence. In the context of personalized medicine/nutrition, new tools are necessary to bring additional knowledge about MetS etiology, better stratify populations and customise strategies for prevention. The objective of this study was to investigate the integration of data from complementary untargeted metabolomics platforms (HRMS, RMN) and technologies to characterize the MetS phenotypic spectrum. A case-control study was designed within the Quebec NuAge cohort1. Six complementary untargeted metabolomic/lipidomic approaches, available within the MetaboHUB infrastructure2, were performed on serum samples collected at recruitment and 3 years later. Standard operating procedures were designed to guaranty the inter-laboratory standardisationfrom sample preparation to data processing. Data analyses were performed using reproducible online Galaxy workflows3. A full feature selection strategy was developed to build a comprehensive molecular MetS signature, stable over time. Consistent cross-sectional and longitudinal data were observed with a wide range of metabolites (lipids, carbohydrates, amino-acids, peptides…) reflecting subject stability regarding MetS, and providingnew insights about underlying mechanisms. Correlation network analysis contributed to explore the links between the molecular signature and clinical parameters. Additionally, an optimized reduced signature was proposed, allowing good prediction performances (12% misclassification, AUC=0.96, CI:[0.94-0.98]), for future clinical application. These results demonstrated the interest of a multidimensional molecular phenotyping aspart of the next generation of medicine tools in the frame of non-communicable diseases.
Fichier principal
Vignette du fichier
2019-Metabolomics_La Hague_1.pdf (13.65 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-02293580 , version 1 (02-06-2020)

Licence

Paternité

Identifiants

  • HAL Id : hal-02293580 , version 1
  • PRODINRA : 483947

Citer

Blandine Comte, Stéphanie Monnerie, Marion Brandolini-Bunlon, Cécile Canlet, Florence Castelli, et al.. From Molecular Profiling to Precision Medicine in Metabolic Syndrome. 15th Annual Conference of the Metabolomics Society (Metabolomics 2019), Jun 2019, La Haye, Netherlands. 300 p., 2019. ⟨hal-02293580⟩
311 Consultations
251 Téléchargements

Partager

Gmail Facebook X LinkedIn More