| 1. |
- Almanza-Aguilera, Enrique, et al.
(författare)
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Impact in Plasma Metabolome as Effect of Lifestyle Intervention for Weight-Loss Reveals Metabolic Benefits in Metabolically Healthy Obese Women
- 2018
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3907 .- 1535-3893. ; 17:8, s. 2600-2610
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Tidskriftsartikel (refereegranskat)abstract
- Little is known regarding metabolic benefits of weight loss (WL) on the metabolically healthy obese (MHO) patients. We aimed to examine the impact of a lifestyle weight loss (LWL) treatment on the plasma metabolomic profile in MHO individuals. Plasma samples from 57 MHO women allocated to an intensive LWL treatment group (TG, hypocaloric Mediterranean diet and regular physical activity, n = 30) or to a control group (CG, general recommendations of a healthy diet and physical activity, n = 27) were analyzed using an untargeted1H NMR metabolomics approach at baseline, after 3 months (intervention), and 12 months (follow-up). The impact of the LWL intervention on plasma metabolome was statistically significant at 3 months but not at follow-up and included higher levels of formate and phosphocreatine and lower levels of LDL/VLDL (signals) and trimethylamine in the TG. These metabolites were also correlated with WL. Higher myo-inositol, methylguanidine, and 3-hydroxybutyrate, and lower proline, were also found in the TG; higher levels of hippurate and asparagine, and lower levels of 2-hydroxybutyrate and creatine, were associated with WL. The current findings suggest that an intensive LWL treatment, and the consequent WL, leads to an improved plasma metabolic profile in MHO women through its impact on energy, amino acid, lipoprotein, and microbial metabolism.
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| 2. |
- Iversen, Kia Noehr, 1987, et al.
(författare)
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Appetite and Subsequent Food Intake Were Unaffected by the Amount of Sourdough and Rye in Soft Bread-A Randomized Cross-Over Breakfast Study
- 2018
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Ingår i: Nutrients. - : MDPI AG. - 2072-6643 .- 2072-6643. ; 10:11
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Tidskriftsartikel (refereegranskat)abstract
- Sourdough fermented bread has been suggested to have beneficial health effects, in part mediated by increased satiety in the postprandial phase, but only limited research has been conducted to verify this. The current study aimed to investigate the effect of the amounts of sourdough and rye in soft bread on postprandial appetite. On 6 occasions, 23 healthy volunteers consumed 5 different test breads, with varying amount of rye and sourdough, and a yeast-fermented refined wheat control bread as part of a breakfast meal. The sourdough ranged between 9⁻51% of dough weight and rye content between 35⁻48% of flour weight. Appetite was recorded using visual analogue scales from immediately before breakfast and every 30 min the following 4 h. An ad libitum lunch was served 4 h after the breakfast meal, from which voluntary energy intake was measured. While some of the test breads resulted in lower hunger ratings and increased sense of fullness compared to the refined wheat bread, there were no differences between the test breads. The content of rye in the test breads differed within a narrow range, which might explain the lack of a consistent effect of rye on appetite. Microstructural examination of the test breads showed an increased aggregation of proteins in the breads with high content of sourdough, indicating additional changes to the breads, beyond change in pH, which may counteract the potential effect of decreased pH in the bread on appetite. In conclusion, our study does not support an effect of sourdough on appetite and ad libitum food intake.
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| 3. |
- Madawala, Samanthi R.P., et al.
(författare)
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Impact of location on composition of selected phytochemicals in wild sea buckthorn (Hippophae rhamnoides)
- 2018
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Ingår i: Journal of Food Composition and Analysis. - : Elsevier BV. - 0889-1575 .- 1096-0481. ; 72, s. 115-121
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Tidskriftsartikel (refereegranskat)abstract
- Sea buckthorn (Hippophae rhamnoides; SB) is rich in many essential nutrients and an ideal crop for the sub-Himalayan region in India, as well as other marginal lands with extreme weather conditions. Naturally growing SB from selected geographical locations in India and Sweden were evaluated for total lipid content, fatty acid composition, carotenoids, tocopherols, sterols and phenolic compounds, as well as for untargeted metabolite profiles. Principal component and partial least squares analyses of targeted data showed similar distinctions between Swedish and Indian locations in the first component, attributed to differences in total lipids, individual fatty acids and phenols. The second component distinguished between Indian locations, predominantly due to differences in fatty acids, sitostanol, lutein and caffeic acid. Untargeted analysis by LC–MS metabolomics analysis confirmed that variability from targeted analysis was representative of overall variability. All analyses of targeted and untargeted data indicated a large systematic variability in phytochemicals in relation to sampling location. The results have implications for optimisation of agronomical factors for differential use of SB as a source for food and nutraceuticals and further downstream for increased profitability for the sub-Himalayan and other regions with suitable growing conditions for sea buckthorn. The results also clearly showed that differences between locations were well captured with a few targeted analyses.
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| 4. |
- Madrid-Gambin, Francisco, et al.
(författare)
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Untargeted 1H NMR-Based Metabolomics Analysis of Urine and Serum Profiles after Consumption of Lentils, Chickpeas, and Beans: An Extended Meal Study to Discover Dietary Biomarkers of Pulses
- 2018
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Ingår i: Journal of Agricultural and Food Chemistry. - : American Chemical Society (ACS). - 0021-8561 .- 1520-5118. ; 66:27, s. 6997-7005
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Tidskriftsartikel (refereegranskat)abstract
- High legume intake has been shown to have beneficial effects on the health of humans. The use of nutritional biomarkers, as a complement to self-reported questionnaires, could assist in evaluating dietary intake and downstream effects on human health. The aim of this study was to investigate potential biomarkers of the consumption of pulses (i.e., white beans, chickpeas, and lentils) by using untargeted NMR-based metabolomics. Meals rich in pulses were consumed by a total of 11 participants in a randomized crossover study and multilevel partial least-squares regression was employed for paired comparisons. Metabolomics analysis indicated that trigonelline, 3-methylhistidine, dimethylglycine, trimethylamine, and lysine were potential, though not highly specific, biomarkers of pulse intake. Furthermore, monitoring of these metabolites for a period of 48 h after intake revealed a range of different excretion patterns among pulses. Following the consumption of pulses, a metabolomic profiling revealed that the concentration ratios of trigonelline, choline, lysine, and histidine were similar to those found in urine. In conclusion, this study identified potential urinary biomarkers of exposure to dietary pulses and provided valuable information about the time-response effect of these putative biomarkers.
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| 5. |
- Shi, Lin, 1988, et al.
(författare)
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Plasma metabolites associated with healthy Nordic dietary indexes and risk of type 2 diabetes-a nested case-control study in a Swedish population
- 2018
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Ingår i: American Journal of Clinical Nutrition. - : Elsevier BV. - 0002-9165 .- 1938-3207. ; 108:3, s. 564-575
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Tidskriftsartikel (refereegranskat)abstract
- Background: Epidemiologic evidence on the association of a healthy Nordic diet and future type 2 diabetes (T2D) is limited. Exploring metabolites as biomarkers of healthy Nordic dietary patterns may facilitate investigation of associations between such patterns and T2D. Objectives: We aimed to identify metabolites related to a priori-defined healthy Nordic dietary indexes, the Baltic Sea Diet Score (BSDS) and Healthy Nordic Food Index (HNFI), and evaluate associations with the T2D risk in a case-control study nested in a Swedish population-based prospective cohort. Design: Plasma samples from 421 case-control pairs at baseline and samples from a subset of 151 healthy controls at a 10-y follow-up were analyzed with the use of untargeted liquid chromatography-mass spectrometry metabolomics. Index-related metabolites were identified through the use of random forest modelling followed by partial correlation analysis adjustment for lifestyle confounders. Metabolite patterns were derived via principal component analysis (PCA). ORs of T2D were estimated via conditional logistic regression. Reproducibility of metabolites was assessed by intraclass correlation (ICC) in healthy controls. Associations were also assessed for 10 metabolites previously identified as linking a healthy Nordic diet with T2D. Results: In total, 31 metabolites were associated with BSDS and/or HNFI (-0.19 <= r <= 0.21, 0.10 <= ICC <= 0.59). Two PCs were determined from index-related metabolites: PC1 strongly correlated to the indexes (r = 0.27 for BSDS, r = 0.25 for HNFI, ICC = 0.45) but showed no association with T2D risk. PC2 was weakly associated with the indexes, but more strongly with foods not part of the indexes, e.g., pizza, sausages, and hamburgers. PC2 was also significantly associated with T2D risk. Predefined metabolites were confirmed to be reflective of consumption of whole grains, fish, or vegetables, but not related to T2D risk. Conclusions: Our study did not support an association between healthy Nordic dietary indexes and T2D. However, foods such as hamburger, sausage, and pizza not covered by the indexes appeared to be more important for T2D risk in the current population.
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| 6. |
- Shi, Lin, 1988, et al.
(författare)
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Plasma metabolites associated with type 2 diabetes in a Swedish population: a case-control study nested in a prospective cohort
- 2018
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 61:4, s. 849-861
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis The aims of the present work were to identify plasma metabolites that predict future type 2 diabetes, to investigate the changes in identified metabolites among individuals who later did or did not develop type 2 diabetes over time, and to assess the extent to which inclusion of predictive metabolites could improve risk prediction. Methods We established a nested case-control study within the Swedish prospective population-based Vasterbotten Intervention Programme cohort. Using untargeted liquid chromatography-MS metabolomics, we analysed plasma samples from 503 case-control pairs at baseline (a median time of 7 years prior to diagnosis) and samples from a subset of 187 case-control pairs at 10 years of follow-up. Discriminative metabolites between cases and controls at baseline were optimally selected using a multivariate data analysis pipeline adapted for large-scale metabolomics. Conditional logistic regression was used to assess associations between discriminative metabolites and future type 2 diabetes, adjusting for several known risk factors. Reproducibility of identified metabolites was estimated by intra-class correlation over the 10 year period among the subset of healthy participants; their systematic changes over time in relation to diagnosis among those who developed type 2 diabetes were investigated using mixed models. Risk prediction performance of models made from different predictors was evaluated using area under the receiver operating characteristic curve, discrimination improvement index and net reclassification index. Results We identified 46 predictive plasma metabolites of type 2 diabetes. Among novel findings, phosphatidylcholines (PCs) containing odd-chain fatty acids (C19: 1 and C17:0) and 2-hydroxyethanesulfonate were associated with the likelihood of developing type 2 diabetes; we also confirmed previously identified predictive biomarkers. Identified metabolites strongly correlated with insulin resistance and/or beta cell dysfunction. Of 46 identified metabolites, 26 showed intermediate to high reproducibility among healthy individuals. Moreover, PCs with odd-chain fatty acids, branched-chain amino acids, 3-methyl-2-oxovaleric acid and glutamate changed over time along with disease progression among diabetes cases. Importantly, we found that a combination of five of the most robustly predictive metabolites significantly improved risk prediction if added to models with an a priori defined set of traditional risk factors, but only a marginal improvement was achieved when using models based on optimally selected traditional risk factors. Conclusions/interpretation Predictive metabolites may improve understanding of the pathophysiology of type 2 diabetes and reflect disease progression, but they provide limited incremental value in risk prediction beyond optimal use of traditional risk factors.
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