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Träfflista för sökning "WFRF:(Gürdeniz Gözde) srt2:(2021)"

Sökning: WFRF:(Gürdeniz Gözde) > (2021)

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1.
  • Gürdeniz, Gözde, et al. (författare)
  • Analysis of the SYSDIET Healthy Nordic Diet randomized trial based on metabolic profiling reveal beneficial effects on glucose metabolism and blood lipids
  • 2021
  • Ingår i: Clinical Nutrition. - : Elsevier. - 0261-5614 .- 1532-1983. ; 41:2, s. 441-451
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND & AIMS: Intake assessment in multicenter trials is challenging, yet important for accurate outcome evaluation. The present study aimed to characterize a multicenter randomized controlled trial with a healthy Nordic diet (HND) compared to a Control diet (CD) by plasma and urine metabolic profiles and to associate them with cardiometabolic markers.METHODS: During 18-24 weeks of intervention, 200 participants with metabolic syndrome were advised at six centres to eat either HND (e.g. whole-grain products, berries, rapeseed oil, fish and low-fat dairy) or CD while being weight stable. Of these 166/159 completers delivered blood/urine samples. Metabolic profiles of fasting plasma and 24 h pooled urine were analysed to identify characteristic diet-related patterns. Principal components analysis (PCA) scores (i.e. PC1 and PC2 scores) were used to test their combined effect on blood glucose response (primary endpoint), serum lipoproteins, triglycerides, and inflammatory markers.RESULTS: The profiles distinguished HND and CD with AUC of 0.96 ± 0.03 and 0.93 ± 0.02 for plasma and urine, respectively, with limited heterogeneity between centers, reflecting markers of key foods. Markers of fish, whole grain and polyunsaturated lipids characterized HND, while CD was reflected by lipids containing palmitoleic acid. The PC1 scores of plasma metabolites characterizing the intervention is associated with HDL (β = 0.05; 95% CI: 0.02, 0.08; P = 0.001) and triglycerides (β = -0.06; 95% CI: -0.09, -0.03; P < 0.001). PC2 scores were related with glucose metabolism (2 h Glucose, β = 0.1; 95% CI: 0.05, 0.15; P < 0.001), LDL (β = 0.06; 95% CI: 0.01, 0.1; P = 0.02) and triglycerides (β = 0.11; 95% CI: 0.06, 0.15; P < 0.001). For urine, the scores were related with LDL cholesterol.CONCLUSIONS: Plasma and urine metabolite profiles from SYSDIET reflected good compliance with dietary recommendations across the region. The scores of metabolites characterizing the diets associated with outcomes related with cardio-metabolic risk. Our analysis therefore offers a novel way to approach a per protocol analysis with a balanced compliance assessment in larger multicentre dietary trials. The study was registered at clinicaltrials.gov with NCT00992641.
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2.
  • Low, Dorrain Yanwen, et al. (författare)
  • Data sharing in PredRet for accurate prediction of retention time: Application to plant food bioactive compounds
  • 2021
  • Ingår i: Food Chemistry. - : Elsevier BV. - 0308-8146 .- 1873-7072. ; 357
  • Tidskriftsartikel (refereegranskat)abstract
    • Prediction of retention times (RTs) is increasingly considered in untargeted metabolomics to complement MS/MS matching for annotation of unidentified peaks. We tested the performance of PredRet (http://predret.org/) to predict RTs for plant food bioactive metabolites in a data sharing initiative containing entry sets of 29–103 compounds (totalling 467 compounds, >30 families) across 24 chromatographic systems (CSs). Between 27 and 667 predictions were obtained with a median prediction error of 0.03–0.76 min and interval width of 0.33–8.78 min. An external validation test of eight CSs showed high prediction accuracy. RT prediction was dependent on shape and type of LC gradient, and number of commonly measured compounds. Our study highlights PredRet's accuracy and ability to transpose RT data acquired from one CS to another CS. We recommend extensive RT data sharing in PredRet by the community interested in plant food bioactive metabolites to achieve a powerful community-driven open-access tool for metabolomics annotation.
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2021 (2)Ta bort avgränsningen

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