| 1. |
- Brunius, Carl, 1974, et al.
(författare)
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Prediction and modeling of pre-analytical sampling errors as a strategy to improve plasma NMR metabolomics data
- 2017
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1460-2059 .- 1367-4811. ; 33:22, s. 3567-3574
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Tidskriftsartikel (refereegranskat)abstract
- Biobanks are important infrastructures for life science research. Optimal sample handling regarding e.g. collection and processing of biological samples is highly complex, with many variables that could alter sample integrity and even more complex when considering multiple study centers or using legacy samples with limited documentation on sample management. Novel means to understand and take into account such variability would enable high-quality research on archived samples. This study investigated whether pre-analytical sample variability could be predicted and reduced by modeling alterations in the plasma metabolome, measured by NMR, as a function of pre-centrifugation conditions (1-36 h pre-centrifugation delay time at 4 A degrees C and 22 A degrees C) in 16 individuals. Pre-centrifugation temperature and delay times were predicted using random forest modeling and performance was validated on independent samples. Alterations in the metabolome were modeled at each temperature using a cluster-based approach, revealing reproducible effects of delay time on energy metabolism intermediates at both temperatures, but more pronounced at 22 A degrees C. Moreover, pre-centrifugation delay at 4 A degrees C resulted in large, specific variability at 3 h, predominantly of lipids. Pre-analytical sample handling error correction resulted in significant improvement of data quality, particularly at 22 A degrees C. This approach offers the possibility to predict pre-centrifugation delay temperature and time in biobanked samples before use in costly downstream applications. Moreover, the results suggest potential to decrease the impact of undesired, delay-induced variability. However, these findings need to be validated in multiple, large sample sets and with analytical techniques covering a wider range of the metabolome, such as LC-MS.
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| 2. |
- Rådjursöga, Millie, 1977, et al.
(författare)
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The H-1 NMR serum metabolomics response to a two meal challenge: a cross-over dietary intervention study in healthy human volunteers
- 2019
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Ingår i: Nutrition Journal. - : Springer Science and Business Media LLC. - 1475-2891. ; 18:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Metabolomics represents a powerful tool for exploring modulation of the human metabolome in response to food intake. However, the choice of multivariate statistical approach is not always evident, especially for complex experimental designs with repeated measurements per individual. Here we have investigated the serum metabolic responses to two breakfast meals: an egg and ham based breakfast and a cereal based breakfast using three different multivariate approaches based on the Projections to Latent Structures framework. Methods: In a cross over design, 24 healthy volunteers ate the egg and ham breakfast and cereal breakfast on four occasions each. Postprandial serum samples were subjected to metabolite profiling using H-1 nuclear magnetic resonance spectroscopy and metabolites were identified using 2D nuclear magnetic resonance spectroscopy. Metabolic profiles were analyzed using Orthogonal Projections to Latent Structures with Discriminant Analysis and Effect Projections and ANOVA-decomposed Projections to Latent Structures. Results: The Orthogonal Projections to Latent Structures with Discriminant Analysis model correctly classified 92 and 90% of the samples from the cereal breakfast and egg and ham breakfast, respectively, but confounded dietary effects with inter-personal variability. Orthogonal Projections to Latent Structures with Effect Projections removed inter-personal variability and performed perfect classification between breakfasts, however at the expense of comparing means of respective breakfasts instead of all samples. ANOVA-decomposed Projections to Latent Structures managed to remove inter-personal variability and predicted 99% of all individual samples correctly. Proline, tyrosine, and N-acetylated amino acids were found in higher concentration after consumption of the cereal breakfast while creatine, methanol, and isoleucine were found in higher concentration after the egg and ham breakfast. Conclusions: Our results demonstrate that the choice of statistical method will influence the results and adequate methods need to be employed to manage sample dependency and repeated measurements in cross-over studies. In addition, H-1 nuclear magnetic resonance serum metabolomics could reproducibly characterize postprandial metabolic profiles and identify discriminatory metabolites largely reflecting dietary composition.
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| 3. |
- Hall, Ulrika Andersson, et al.
(författare)
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Higher Concentrations of BCAAs and 3-HIB Are Associated with Insulin Resistance in the Transition from Gestational Diabetes to Type 2 Diabetes
- 2018
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Ingår i: Journal of Diabetes Research. - : Hindawi Limited. - 2314-6745 .- 2314-6753.
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Tidskriftsartikel (refereegranskat)abstract
- Aim. Determine the metabolic profile and identify risk factors of women transitioning from gestational diabetes mellitus (GDM) to type 2 diabetes mellitus (T2DM). Methods. 237 women diagnosed with GDM underwent an oral glucose tolerance test (OGTT), anthropometrics assessment, and completed lifestyle questionnaires six years after pregnancy. Blood was analysed for clinical variables (e.g., insulin, glucose, HbA1c, adiponectin, leptin, and lipid levels) and NMR metabolomics. Based on the OGTT, women were divided into three groups: normal glucose tolerance (NGT), impaired glucose tolerance (IGT), and T2DM. Results. Six years after GDM, 19% of subjects had T2DM and 19% IGT. After BMI adjustment, the IGT group had lower HDL, higher leptin, and higher free fatty acid (FFA) levels, and the T2DM group higher triglyceride, FFA, and C-reactive protein levels than the NGT group. IGT and T2DM groups reported lower physical activity. NMR measurements revealed that levels of branched-chain amino acids (BCAAs) and the valine metabolite 3-hydroxyisobyturate were higher in T2DM and IGT groups and correlated with measures of insulin resistance and lipid metabolism. Conclusion. In addition to well-known clinical risk factors, BCAAs and 3-hydroxyisobyturate are potential markers to be evaluated as predictors of metabolic risk after pregnancy complicated by GDM.
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| 4. |
- Hall, Ulrika Andersson, et al.
(författare)
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Metabolism and Whole-Body Fat Oxidation Following Post-Exercise Carbohydrate or Protein Intake.
- 2018
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Ingår i: International journal of sport nutrition and exercise metabolism. - : Human Kinetics. - 1543-2742 .- 1526-484X. ; 28:1, s. 37-45
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Tidskriftsartikel (refereegranskat)abstract
- This study investigated how post-exercise intake of placebo (PLA), protein (PRO) or carbohydrate (CHO) affected fat oxidation (FO) and metabolic parameters during recovery and subsequent exercise.In a cross-over design, 12 moderately trained women (VO2max 45 ± 6 ml·min(-1)·kg(-1)) performed three days of testing. A 23 min control (CON) incremental FO bike test (30-80% VO2max) was followed by 60 min exercise at 75% VO2max. Immediately post-exercise, subjects ingested PLA, 20 g PRO or 40 g CHO followed by a second FO bike test 2h later.Maximal fat oxidation (MFO) and the intensity at which MFO occurs (Fatmax) increased at the second FO test compared to the first following all three post-exercise drinks (MFO for CON=0.28±0.08, PLA=0.57±0.13, PRO=0.52±0.08, CHO=0.44±0.12 g fat·min(-1); Fatmax for CON=41±7, PLA=54±4, PRO=55±6, CHO=50±8 %VO2max, P<0.01 for all values compared to CON). Resting FO, MFO and Fatmax were not significantly different between PLA and PRO, but lower for CHO. PRO and CHO increased insulin levels at 1h post-exercise, though both glucose and insulin were equal with PLA at 2h. Increased post-exercise ketone levels only occurred with PLA.Protein supplementation immediately post-exercise did not affect the doubling in whole body fat oxidation seen during a subsequent exercise trial 2 hours later. Neither did it affect resting fat oxidation during the post-exercise period despite increased insulin levels and attenuated ketosis. Carbohydrate intake dampened the increase in fat oxidation during the second test, though a significant increase was still observed compared to the first test.
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| 5. |
- Lindqvist, Helen, 1977, et al.
(författare)
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Serum metabolite profiles of habitual diet: evaluation by 1H-nuclear magnetic resonance analysis
- 2019
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Ingår i: American Journal of Clinical Nutrition. - : Elsevier BV. - 0002-9165. ; 110:1, s. 53-62
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Tidskriftsartikel (refereegranskat)abstract
- Background: Objective and reliable methods to measure dietary exposure and prove associations and causation between diet and health are desirable. Objective: The aim of this study was to investigate if 1H-nuclear magnetic resonance (1H NMR) analysis of serum samples may be used as an objective method to discriminate vegan, vegetarian, and omnivore diets. Specifically, the aim was to identify a metabolite pattern that separated meat-eaters from non-meat-eaters and vegans from nonvegans. Methods: Healthy volunteers (45 men and 75 women) complying with habitual vegan (n = 43), vegetarian (n = 24 + vegetarians adding fish n = 13), or omnivore (n = 40) diets were enrolled in the study. Data were collected on clinical phenotype, body composition, lifestyle including a food-frequency questionnaire (FFQ), and a 4-d weighed food diary. Serum samples were analyzed by routine clinical test and for metabolites by 1H NMR spectroscopy. NMR data were nonnormalized, UV-scaled, and analyzed with multivariate data analysis [principal component analysis, orthogonal projections to latent structures (OPLS) and OPLS with discriminant analysis]. In the multivariate analysis volunteers were assigned as meat-eaters (omnivores), non-meat-eaters (vegans and vegetarians), vegans, or nonvegans (lacto-ovo-vegetarians, vegetarians adding fish, and omnivores). Metabolites were identified by line-fitting of 1D 1H NMR spectra and the use of statistical total correlation spectroscopy. Results: Although many metabolites differ in concentration between men and women as well as by age, body mass index, and body composition, it was possible to correctly classify 97.5% of the meat-eaters compared with non-meat-eaters and 92.5% of the vegans compared with nonvegans. The branched-chain amino acids, creatine, lysine, 2-aminobutyrate, glutamine, glycine, trimethylamine, and 1 unidentified metabolite were among the most important metabolites in the discriminating patterns in relation to intake of both meat and other animal products. Conclusions: 1H NMR serum metabolomics appears to be a possible objective tool to identify and predict habitual intake of meat and other animal products in healthy subjects. These results should be confirmed in larger cohort studies or intervention trials. This trial was registered at clinicaltrials.gov as NCT02039609.
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| 6. |
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| 7. |
- Malmodin, Daniel, 1974, et al.
(författare)
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High-throughput analysis of protein NMR spectra
- 2005
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Ingår i: Progress in Nuclear Magnetic Resonance Spectroscopy. - : Elsevier BV. - 0079-6565. ; 46:2-3, s. 109-129
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Tidskriftsartikel (refereegranskat)
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| 8. |
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| 9. |
- Malmodin, Daniel, 1974, et al.
(författare)
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NMR Spectroscopic Analysis to Evaluate the Quality of Insulin: Concentration, Variability, and Excipient Content.
- 2020
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Ingår i: Journal of diabetes science and technology. - : SAGE Publications. - 1932-2968. ; 14:1, s. 180-184
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Tidskriftsartikel (refereegranskat)abstract
- Known and consistent bioactivity between samples of insulin is essential to correctly estimate the dose. Insulin concentration is not the same thing as bioactivity, however, and methods to correctly determine both are required. Here we show that one dimensional nuclear magnetic resonance (1D NMR), in contrast to, for example, reverse phase high pressure liquid chromatography, can be used to determine both insulin concentration as well as confirm the structural integrity required for activity. In response to the report by Carter and Heinemann, we decided to investigate insulin intended for public use. Insulin from several manufacturers was investigated. Correct insulin concentrations were found in all tested samples although the general sample variability, which possibly could influence the bioactivity, varied depending on insulin type and manufacturer.
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| 10. |
- Malmodin, Daniel, 1974, et al.
(författare)
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Robust and versatile interpretation of spectra with coupled evolution periods using multi-way decomposition.
- 2006
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Ingår i: Magnetic resonance in chemistry : MRC. - : Wiley. - 0749-1581 .- 1097-458X. ; 44 Spec No
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Tidskriftsartikel (refereegranskat)abstract
- Coupling of evolution periods in NMR experiments is a very promising approach that has recently attracted much attention for its substantial savings in measurement time. Another novel concept, which has already proved useful in many types of NMR applications is multi-way decomposition. The PRODECOMP tool described here addresses the combination of these two modern tools in protein NMR. The following properties of this approach are described and illustrated. Highly similar information to what would be found in a corresponding full-dimensional spectrum is extracted from a set of projected spectra. All experimental spectra are used simultaneously, avoiding sensitivity loss associated with individual examination of the spectra. Aliasing caused by the linear combinations of individual shifts in the projected spectra is automatically resolved, allowing for better resolution due to smaller spectral widths. Reconstructions of various high-dimensional spectra, including the corresponding full-dimensional spectrum become straightforward. Spectral overlap is efficiently resolved. The capabilities of PRODECOMP are illustrated for a 14 kD protein, for which 12 projections of a 5-dimensional spectrum with the nuclei N, HN, CO, Calpha and Halpha are analysed.
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