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Metabolomics analysis of type 2 diabetes remission identifies 12 metabolites with predictive capacity: a CORDIOPREV clinical trial study.

dc.contributor.authorMora-Ortiz, Marina
dc.contributor.authorAlcala-Diaz, Juan F
dc.contributor.authorRangel-Zuñiga, Oriol Alberto
dc.contributor.authorArenas-de Larriva, Antonio Pablo
dc.contributor.authorAbollo-Jimenez, Fernando
dc.contributor.authorLuque-Cordoba, Diego
dc.contributor.authorPriego-Capote, Feliciano
dc.contributor.authorMalagon, Maria M
dc.contributor.authorDelgado-Lista, Javier
dc.contributor.authorOrdovas, Jose M
dc.contributor.authorPerez-Martinez, Pablo
dc.contributor.authorCamargo, Antonio
dc.contributor.authorLopez-Miranda, Jose
dc.contributor.funderMinisterio de Economia y Competitividad, Spain
dc.contributor.funderISCIII research contract, Programa Miguel-Servet
dc.contributor.funderEuropean Union’s Horizon 2020 research and innovation programme
dc.contributor.funderFundacion Patrimonio Comunal Olivarero J
dc.contributor.funderConsejería de Salud, Consejeria de Agricultura y Pesca
dc.contributor.funderConsejería de Innovacion, Ciencia y Empresa
dc.contributor.funderMinisterio de Medio Ambiente, Medio Rural y Marino
dc.contributor.funderConsejeria de Innovación, Ciencia y Empresa
dc.date.accessioned2023-05-03T13:34:03Z
dc.date.available2023-05-03T13:34:03Z
dc.date.issued2022-09-12
dc.description.abstractType 2 diabetes mellitus (T2DM) is one of the most widely spread diseases, affecting around 90% of the patients with diabetes. Metabolomics has proven useful in diabetes research discovering new biomarkers to assist in therapeutical studies and elucidating pathways of interest. However, this technique has not yet been applied to a cohort of patients that have remitted from T2DM. All patients with a newly diagnosed T2DM at baseline (n = 190) were included. An untargeted metabolomics approach was employed to identify metabolic differences between individuals who remitted (RE), and those who did not (non-RE) from T2DM, during a 5-year study of dietary intervention. The biostatistical pipeline consisted of an orthogonal projection on the latent structure discriminant analysis (O-PLS DA), a generalized linear model (GLM), a receiver operating characteristic (ROC), a DeLong test, a Cox regression, and pathway analyses. The model identified a significant increase in 12 metabolites in the non-RE group compared to the RE group. Cox proportional hazard models, calculated using these 12 metabolites, showed that patients in the high-score tercile had significantly (p-value  Our study identified 12 endogenous metabolites with the potential to predict T2DM remission following a dietary intervention. These metabolites, combined with clinical variables, can be used to provide, in clinical practice, a more precise therapy.
dc.description.versionSi
dc.identifier.citationMora-Ortiz M, Alcala-Diaz JF, Rangel-Zuñiga OA, Arenas-de Larriva AP, Abollo-Jimenez F, Luque-Cordoba D, et al. Metabolomics analysis of type 2 diabetes remission identifies 12 metabolites with predictive capacity: a CORDIOPREV clinical trial study. BMC Med. 2022 Oct 27;20(1):373
dc.identifier.doi10.1186/s12916-022-02566-z
dc.identifier.essn1741-7015
dc.identifier.pmcPMC9609192
dc.identifier.pmid36289459
dc.identifier.pubmedURLhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9609192/pdf
dc.identifier.unpaywallURLhttps://bmcmedicine.biomedcentral.com/counter/pdf/10.1186/s12916-022-02566-z
dc.identifier.urihttp://hdl.handle.net/10668/20310
dc.issue.number1
dc.journal.titleBMC medicine
dc.journal.titleabbreviationBMC Med
dc.language.isoen
dc.organizationHospital Universitario Reina Sofía
dc.organizationInstituto Maimónides de Investigación Biomédica de Córdoba-IMIBIC
dc.page.number373
dc.publisherBioMed Central
dc.pubmedtypeClinical Trial
dc.pubmedtypeJournal Article
dc.pubmedtypeResearch Support, Non-U.S. Gov't
dc.relation.projectIDAGL2012/39615
dc.relation.projectIDPIE14/00005
dc.relation.projectIDPIE14/00031
dc.relation.projectIDAGL2015-67896-P
dc.relation.projectIDCP14/00114
dc.relation.projectIDPI19/00299
dc.relation.projectIDDTS19/00007
dc.relation.projectIDFIS PI13/00023
dc.relation.projectIDPI16/01777
dc.relation.publisherversionhttps://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-022-02566-z
dc.rightsAttribution 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectDiabetes
dc.subjectInsulin resistance
dc.subjectMetabolomics
dc.subjectProspective human study
dc.subject.decsAnálisis discriminante
dc.subject.decsBiomarcadores
dc.subject.decsCurva ROC
dc.subject.decsDiabetes mellitus tipo 2
dc.subject.decsMetabolómica
dc.subject.meshHumans
dc.subject.meshBiomarkers
dc.subject.meshDiabetes mellitus, type 2
dc.subject.meshDiscriminant analysis
dc.subject.meshMetabolomics
dc.subject.meshROC Curve
dc.titleMetabolomics analysis of type 2 diabetes remission identifies 12 metabolites with predictive capacity: a CORDIOPREV clinical trial study.
dc.typeResearch article
dc.type.hasVersionVoR
dc.volume.number20
dspace.entity.typePublication

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