FADS Polymorphisms Affect the Clinical and Biochemical Phenotypes of Metabolic Syndrome
Rattachement africain : cz. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Long-chain polyunsaturated fatty acids (LC-PUFAs) play important roles in human health, from controlling inflammation to lipid and glucose homeostasis. In our previous study, which employed a cluster analysis of a plasma fatty acid (FA) pattern, we identified two clusters of metabolic syndrome (MetS) independent of clinical and biochemical parameters within the whole study group (controls together with metabolic syndrome (MetS) patients). FA desaturase (FADS) genes are the key regulators of LC-PUFA metabolism. The aim of this study was to analyze associations between FADS polymorphisms and clusters of MetS. The study group consisted of 188 controls and 166 patients with MetS. The first cluster contained 71 controls (CON1) and 109 MetS patients (MetS1). The second cluster consisted of 117 controls (CON2) and 57 MetS patients (MetS2). In comparison with MetS2, cluster MetS1 displayed a more adverse risk profile. Cluster CON1 had, in comparison with CON2, higher body weight and increased triacylglycerol levels (p < 0.05). We found that the FADS rs174537 (p < 0.001), rs174570 (p < 0.01), and rs174602 (p < 0.05) polymorphisms along with two inferred haplotypes had statistically significant genotype associations with the splitting of MetS into MetS1 and MetS2. Conversely, we observed no significant differences in the distribution of FADS polymorphisms between MetS and CON subjects, or between CON1 and CON2. These associations between FADS polymorphisms and two clusters of MetS (differing in waist circumference, HOMA-IR, lipolysis, and oxidative stress) implicate the important influence of genetic factors on the phenotypic manifestation of MetS.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- FADS Polymorphisms Affect the Clinical and Biochemical Phenotypes of Metabolic Syndrome
- Date Crossref
- 20/06/2022
- Éditeur
- MDPI AG
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Charles University Institute of Clinical Chemistry and Laboratory Diagnostics pays non établi dans la noticeUniversité ou école supérieure
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General University Hospital in Prague pays non établi dans la noticeOrganisme public
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University of Ostrava Institute for Research and Applications of Fuzzy Modeling pays non établi dans la noticeUniversité ou école supérieure
Institute of Clinical Chemistry and Laboratory Diagnostics — Charles University, General University Hospital in Prague et Institute for Research and Applications of Fuzzy Modeling — University of Ostrava.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.