Author, as appears in the article.: Hernandez-Alonso, Pablo; Garcia-Gavilan, Jesus; Camacho-Barcia, Lucia; Sjodin, Anders; Hansen, Thea T; Harrold, Jo; Salas-Salvado, Jordi; Halford, Jason C G; Canudas, Silvia; Bullo, Monica
Department: Bioquímica i Biotecnologia
URV's Author/s: Bulló Bonet, Mònica / García Gavilán, Jesús Francisco / Salas Salvadó, Jorge
Keywords: Young adult Vitamin-e Sensitivity Roc curve Risk Plasma Overweight Obese Middle aged Metabolomics Male Linoleic-acid Insulin resistance Humans Homeostasis Glucose Female Cross-sectional studies Branched-chain Body mass index Area under curve Aged Adult
Abstract: Different plasma metabolites have been related to insulin resistance (IR). However, there is a lack of metabolite models predicting IR with external validation. The aim of this study is to identify a multi-metabolite model associated to the homeostatic model assessment (HOMA)-IR values. We performed a cross-sectional metabolomics analysis of samples collected from overweight and obese subjects from two independent studies. The training step was performed in 236 subjects from the SATIN study and validated in 102 subjects from the GLYNDIET study. Plasma metabolomics profile was analyzed using three different approaches: GC/quadrupole-TOF, LC/quadrupole-TOF, and nuclear magnetic resonance (NMR). Associations between metabolites and HOMA-IR were assessed using elastic net regression analysis with a leave-one-out cross validation (CV) and 100 CV runs. HOMA-IR was analyzed both as linear and categorical (median or lower versus higher than the median). Receiver operating characteristic curves were constructed based on metabolites' weighted models. A set of 30 metabolites discriminating extremes of HOMA-IR were consistently selected. These metabolites comprised some amino acids, lipid species and different organic acids. The area under the curve (AUC) for the discrimination between HOMA-IR extreme categories was 0.82 (95% CI: 0.74-0.90), based on the multi-metabolite model weighted with the regression coefficients of metabolites in the validation dataset. We identified a set of metabolites discriminating between extremes of HOMA-IR and able to predict HOMA-IR with high accuracy.
Thematic Areas: Zootecnia / recursos pesqueiros Saúde coletiva Química Psicología Odontología Nutrição Multidisciplinary sciences Multidisciplinary Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Letras / linguística Interdisciplinar Geografía Geociências Farmacia Engenharias iv Engenharias iii Engenharias ii Enfermagem Educação física Educação Economia Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Ciência da computação Biotecnología Biodiversidade Astronomia / física
licence for use: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 20452322
Author's mail: jesusfrancisco.garcia@urv.cat jesusfrancisco.garcia@urv.cat monica.bullo@urv.cat jordi.salas@urv.cat
Author identifier: 0000-0002-0218-7046 0000-0003-2700-7459
Record's date: 2024-10-12
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.nature.com/articles/s41598-019-50260-7
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Scientific Reports. 9 (1): 13895-13895
APA: Hernandez-Alonso, Pablo; Garcia-Gavilan, Jesus; Camacho-Barcia, Lucia; Sjodin, Anders; Hansen, Thea T; Harrold, Jo; Salas-Salvado, Jordi; Halford, Jas (2019). Plasma metabolites associated with homeostatic model assessment of insulin resistance: metabolite-model design and external validation. Scientific Reports, 9(1), 13895-13895. DOI: 10.1038/s41598-019-50260-7
Article's DOI: 10.1038/s41598-019-50260-7
Entity: Universitat Rovira i Virgili
Journal publication year: 2019
Publication Type: Journal Publications
Repositori URV