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dc.contributor.authorGalvez Fernandez, Marta
dc.contributor.authorSanchez-Saez, Francisco
dc.contributor.authorDomingo Relloso, Arce
dc.contributor.authorRodriguez-Hernandez, Zulema
dc.contributor.authorTarazona, Sonia
dc.contributor.authorGonzalez-Marrachelli, Vannina
dc.contributor.authorGrau-Perez, Maria
dc.contributor.authorMorales-Tatay, Jose M.
dc.contributor.authorAmigo, Nuria
dc.contributor.authorGarcia-Barrera, Tamara
dc.contributor.authorGomez-Ariza, Jose L.
dc.contributor.authorChaves, F. Javier
dc.contributor.authorGarcia-Garcia, Ana Barbara
dc.contributor.authorMelero, Rebeca
dc.contributor.authorTellez Plaza, Maria
dc.contributor.authorRedon, Josep
dc.contributor.authorMonleon Salvado, Daniel
dc.contributor.authorMartín Escudero, Juan Carlos 
dc.date.accessioned2024-01-24T13:01:14Z
dc.date.available2024-01-24T13:01:14Z
dc.date.issued2022
dc.identifier.citationRedox Biology, junio 2022, vol. 52, 102314 p.1-12es
dc.identifier.issn2213-2317es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/64968
dc.descriptionProducción Científicaes
dc.description.abstractBackground: Limited studies have evaluated the joint influence of redox-related metals and genetic variation on metabolic pathways. We analyzed the association of 11 metals with metabolic patterns, and the interacting role of candidate genetic variants, in 1145 participants from the Hortega Study, a population-based sample from Spain. Methods: Urine antimony (Sb), arsenic, barium (Ba), cadmium (Cd), chromium (Cr), cobalt (Co), molybdenum (Mo) and vanadium (V), and plasma copper (Cu), selenium (Se) and zinc (Zn) were measured by ICP-MS and AAS, respectively. We summarized 54 plasma metabolites, measured with targeted NMR, by estimating metabolic principal components (mPC). Redox-related SNPs (N = 291) were measured by oligo-ligation assay. Results: In our study, the association with metabolic principal component (mPC) 1 (reflecting non-essential and essential amino acids, including branched chain, and bacterial co-metabolism versus fatty acids and VLDL subclasses) was positive for Se and Zn, but inverse for Cu, arsenobetaine-corrected arsenic (As) and Sb. The association with mPC2 (reflecting essential amino acids, including aromatic, and bacterial co-metabolism) was inverse for Se, Zn and Cd. The association with mPC3 (reflecting LDL subclasses) was positive for Cu, Se and Zn, but inverse for Co. The association for mPC4 (reflecting HDL subclasses) was positive for Sb, but inverse for plasma Zn. These associations were mainly driven by Cu and Sb for mPC1; Se, Zn and Cd for mPC2; Co, Se and Zn for mPC3; and Zn for mPC4. The most SNP-metal interacting genes were NOX1, GSR, GCLC, AGT and REN. Co and Zn showed the highest number of interactions with genetic variants associated to enriched endocrine, cardiovascular and neurological pathways. Conclusions: Exposures to Co, Cu, Se, Zn, As, Cd and Sb were associated with several metabolic patterns involved in chronic disease. Carriers of redox-related variants may have differential susceptibility to metabolic alterations associated to excessive exposure to metals.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevier Science BVes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.subject.classificationMetals, Metabolomics, Oxidative stress, Candidate genes, Gene-environment interaction,es
dc.titleGene-environment interaction analysis of redox-related metals and genetic variants with plasma metabolic patterns in a general population from Spain: The Hortega Studyes
dc.typeinfo:eu-repo/semantics/articlees
dc.identifier.doi10.1016/j.redox.2022.102314es
dc.identifier.publicationfirstpage102314es
dc.identifier.publicationlastpage12es
dc.identifier.publicationtitleRedox Biologyes
dc.identifier.publicationvolume52es
dc.peerreviewedSIes
dc.description.projectThis work was supported by the Strategic Action for Research in Health sciences [CP12/03080, PI15/00071, PI10/0082, PI13/01848, PI14/00874, PI16/01402, PI21/00506 and PI11/00726], CIBER Fisiopatología Obesidad y Nutrición (CIBEROBN) (CIBER-02-08-2009, CB06/03 and CB12/03/30,016), the State Agency for Research (PID2019-108973RB- C21 and C22), the Valencia Government (GRUPOS 03/101; PROM- ETEO/2009/029 and ACOMP/2013/039, IDIFEDER/ 2021/072 and GRISOLIAP/2021/119), the Castilla-Leon Government (GRS/279/A/08) and European Network of Excellence Ingenious Hypercare (EPSS- 037093) from the European Commission. The Strategic Action for Research in Health sciences, CIBERDEM and CIBEROBN are initiatives from Carlos III Health Institute Madrid and cofunded with European Funds for Regional Development (FEDER). The State Agency for Research and Carlos III Health Institute belong to the Spanish Ministry of Science and Innovation. ADR received the support of a fellowship from “la Caixa” Foundation (ID 100010434) (fellowship code “LCF/BQ/DR19/11740016”). MGP received the support of a fellowship from “la Caixa” Foundation (ID 100010434, fellowship code LCFLCF/BQ/DI18/11660001).es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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