| 1. |
- Alehagen, Urban, et al.
(författare)
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Significant Changes in Metabolic Profiles after Intervention with Selenium and Coenzyme Q10 in an Elderly Population
- 2019
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Ingår i: BIOMOLECULES. - : MDPI. - 2218-273X. ; 9:10
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Tidskriftsartikel (refereegranskat)abstract
- Selenium and coenzyme Q10 (SeQ10) are important for normal cellular function. Low selenium intake leads to increased cardiovascular mortality. Intervention with these substances with healthy elderly persons over a period of four years in a double-blind, randomised placebo-controlled prospective study showed reduced cardiovascular mortality, increased cardiac function, and a lower level of NT-proBNP. Therefore, we wanted to evaluate changes in biochemical pathways as a result of the intervention with SeQ10 using metabolic profiling. From a population of 443 healthy elderly individuals that were given 200 µg selenium and 200 mg coenzyme Q10, or placebo daily for four years, we selected nine males on active intervention and nine males on placebo for metabolic profiling in the main study. To confirm the results, two validation studies (study 1 n = 60 males, study 2 n = 37 males) were conducted. Principal component analyses were used on clinical and demographic data to select representative sets of samples for analysis and to divide the samples into batches for analysis. Gas chromatography time-of-flight mass spectrometry-based metabolomics was applied. The metabolite data were evaluated using univariate and multivariate approaches, mainly T-tests and orthogonal projections to latent structures (OPLS) analyses. Out of 95 identified metabolites, 19 were significantly decreased due to the intervention after 18 months of intervention. Significant changes could be seen in the pentose phosphate, the mevalonate, the beta-oxidation and the xanthine oxidase pathways. The intervention also resulted in changes in the urea cycle, and increases in the levels of the precursors to neurotransmitters of the brain. This adds information to previous published results reporting decreased oxidative stress and inflammation. This is the first-time metabolic profiling has been applied to elucidate the mechanisms behind an intervention with SeQ10. The study is small and should be regarded as hypothesis-generating; however, the results are interesting and, therefore, further research in the area is needed.
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| 2. |
- Alinaghi, Masoumeh, et al.
(författare)
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Hierarchical time-series analysis of dynamic bioprocess systems
- 2022
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Ingår i: Biotechnology Journal. - : John Wiley & Sons. - 1860-6768 .- 1860-7314. ; 17:12
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Tidskriftsartikel (refereegranskat)abstract
- Background: Monoclonal antibodies (mAbs) are leading types of ‘blockbuster’ biotherapeutics worldwide; they have been successfully used to treat various cancers and chronic inflammatory and autoimmune diseases. Biotherapeutics process development and manufacturing are complicated due to lack of understanding the factors that impact cell productivity and product quality attributes. Understanding complex interactions between cells, media, and process parameters on the molecular level is essential to bring biomanufacturing to the next level. This can be achieved by analyzing cell culture metabolic levels connected to vital process parameters like viable cell density (VCD). However, VCD and metabolic profiles are dynamic parameters and inherently correlated with time, leading to a significant correlation without actual causality. Many time-series methods deal with such issues. However, with metabolic profiling, the number of measured variables vastly exceeds the number of experiments, making most of existing methods ill-suited and hard to interpret. Methods and MajorResults: Here we propose an alternative workflow using hierarchical dimension reduction to visualize and interpret the relation between evolution of metabolic profiles and dynamic process parameters. The first step of proposed method is focused on finding predictive relation between metabolic profiles and process parameter at all time points using OPLS regression. For each time point, the p(corr) obtained from OPLS model is considered as a differential metabogram and is further assessed using principal components analysis (PCA).Conclusions: Compared to traditional batch modeling, applying proposed methodology on metabolic data from Chinese Hamster Ovary (CHO) antibody production characterized the dynamic relation between metabolic profiles and critical process parameters.
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| 3. |
- Bengtsson, Anders A., et al.
(författare)
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Metabolic Profiling of Systemic Lupus Erythematosus and Comparison with Primary Sjögren’s Syndrome and Systemic Sclerosis
- 2016
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:7
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Tidskriftsartikel (refereegranskat)abstract
- Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease which can affect most organ systems including skin, joints and the kidney. Clinically, SLE is a heterogeneous disease and shares features of several other rheumatic diseases, in particular primary Sjögrens syndrome (pSS) and systemic sclerosis (SSc), why it is difficult to diag- nose The pathogenesis of SLE is not completely understood, partly due to the heterogeneity of the disease. This study demonstrates that metabolomics can be used as a tool for improved diagnosis of SLE compared to other similar autoimmune diseases. We observed differences in metabolic profiles with a classification specificity above 67% in the comparison of SLE with pSS, SSc and a matched group of healthy individuals. Selected metabolites were also significantly different between studied diseases. Biochemical pathway analysis was conducted to gain understanding of underlying pathways involved in the SLE pathogenesis. We found an increased oxidative activity in SLE, supported by increased xanthine oxidase activity and an increased turnover in the urea cycle. The most discriminatory metabolite observed was tryptophan, with decreased levels in SLE patients compared to control groups. Changes of tryptophan levels were related to changes in the activity of the aromatic amino acid decarboxylase (AADC) and/or to activation of the kynurenine pathway.
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| 4. |
- Blaise, Benjamin J., et al.
(författare)
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Statistical analysis in metabolic phenotyping
- 2021
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Ingår i: Nature Protocols. - : Nature Publishing Group. - 1754-2189 .- 1750-2799. ; 16:9, s. 4299-4326
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Forskningsöversikt (refereegranskat)abstract
- Metabolic phenotyping is an important tool in translational biomedical research. The advanced analytical technologies commonly used for phenotyping, including mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy, generate complex data requiring tailored statistical analysis methods. Detailed protocols have been published for data acquisition by liquid NMR, solid-state NMR, ultra-performance liquid chromatography (LC-)MS and gas chromatography (GC-)MS on biofluids or tissues and their preprocessing. Here we propose an efficient protocol (guidelines and software) for statistical analysis of metabolic data generated by these methods. Code for all steps is provided, and no prior coding skill is necessary. We offer efficient solutions for the different steps required within the complete phenotyping data analytics workflow: scaling, normalization, outlier detection, multivariate analysis to explore and model study-related effects, selection of candidate biomarkers, validation, multiple testing correction and performance evaluation of statistical models. We also provide a statistical power calculation algorithm and safeguards to ensure robust and meaningful experimental designs that deliver reliable results. We exemplify the protocol with a two-group classification study and data from an epidemiological cohort; however, the protocol can be easily modified to cover a wider range of experimental designs or incorporate different modeling approaches. This protocol describes a minimal set of analyses needed to rigorously investigate typical datasets encountered in metabolic phenotyping.
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| 5. |
- Bos, Maxime M., et al.
(författare)
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Metabolomics analyses in non-diabetic middle-aged individuals reveal metabolites impacting early glucose disturbances and insulin sensitivity
- 2020
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Ingår i: Metabolomics. - : Springer. - 1573-3882 .- 1573-3890. ; 16:3
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Several plasma metabolites have been associated with insulin resistance and type 2 diabetes mellitus.Objectives: We aimed to identify plasma metabolites associated with different indices of early disturbances in glucose metabolism and insulin sensitivity.Methods: This cross-sectional study was conducted in a subsample of the Leiden Longevity Study comprising individuals without a history of diabetes mellitus (n = 233) with a mean age of 63.3 ± 6.7 years of which 48.1% were men. We tested for associations of fasting glucose, fasting insulin, HOMA-IR, Matsuda Index, Insulinogenic Index and glycated hemoglobin with metabolites (Swedish Metabolomics Platform) using linear regression analysis adjusted for age, sex and BMI. Results were validated internally using an independent metabolomics platform (Biocrates platform) and replicated externally in the independent Netherlands Epidemiology of Obesity (NEO) study (Metabolon platform) (n = 545, mean age of 55.8 ± 6.0 years of which 48.6% were men). Moreover, in the NEO study, we replicated our analyses in individuals with diabetes mellitus (cases: n = 36; controls = 561).Results: Out of the 34 metabolites, a total of 12 plasma metabolites were associated with different indices of disturbances in glucose metabolism and insulin sensitivity in individuals without diabetes mellitus. These findings were validated using a different metabolomics platform as well as in an independent cohort of non-diabetics. Moreover, tyrosine, alanine, valine, tryptophan and alpha-ketoglutaric acid levels were higher in individuals with diabetes mellitus.Conclusion: We found several plasma metabolites that are associated with early disturbances in glucose metabolism and insulin sensitivity of which five were also higher in individuals with diabetes mellitus.
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| 6. |
- Checa, A., et al.
(författare)
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Dysregulations in circulating sphingolipids associate with disease activity indices in female patients with systemic lupus erythematosus : a cross-sectional study
- 2017
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Ingår i: Lupus. - : SAGE PUBLICATIONS LTD. - 0961-2033 .- 1477-0962. ; 26:10, s. 1023-1033
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Tidskriftsartikel (refereegranskat)abstract
- Objective The objective of this study was to investigate the association of clinical and renal disease activity with circulating sphingolipids in patients with systemic lupus erythematosus.Methods We used liquid chromatography tandem mass spectrometry to measure the levels of 27 sphingolipids in plasma from 107 female systemic lupus erythematosus patients and 23 controls selected using a design of experiment approach. We investigated the associations between sphingolipids and two disease activity indices, the Systemic Lupus Activity Measurement and the Systemic Lupus Erythematosus Disease Activity Index. Damage was scored according to the Systemic Lupus International Collaborating Clinics damage index. Renal activity was evaluated with the British Island Lupus Activity Group index. The effects of immunosuppressive treatment on sphingolipid levels were evaluated before and after treatment in 22 female systemic lupus erythematosus patients with active disease.Results Circulating sphingolipids from the ceramide and hexosylceramide families were increased, and sphingoid bases were decreased, in systemic lupus erythematosus patients compared to controls. The ratio of C-16:0-ceramide to sphingosine-1-phosphate was the best discriminator between patients and controls, with an area under the receiver-operating curve of 0.77. The C-16:0-ceramide to sphingosine-1-phosphate ratio was associated with ongoing disease activity according to the Systemic Lupus Activity Measurement and the Systemic Lupus Erythematosus Disease Activity Index, but not with accumulated damage according to the Systemic Lupus International Collaborating Clinics Damage Index. Levels of C-16:0- and C-24:1-hexosylceramides were able to discriminate patients with current versus inactive/no renal involvement. All dysregulated sphingolipids were normalized after immunosuppressive treatment.Conclusion We provide evidence that sphingolipids are dysregulated in systemic lupus erythematosus and associated with disease activity. This study demonstrates the utility of simultaneously targeting multiple components of a pathway to establish disease associations.
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| 7. |
- Karimpour, Masoumeh, et al.
(författare)
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Postprandial metabolomics : A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal
- 2016
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Ingår i: Analytica Chimica Acta. - Elsevier : Elsevier BV. - 0003-2670 .- 1873-4324. ; 908, s. 121-131
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Tidskriftsartikel (refereegranskat)abstract
- The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms – gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) – to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1–86% for GC-MS and 0.9–42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2–97% for the positive and 4–69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a multi-platform metabolomics approach followed by multivariate and univariate data analysis for a broad-scale screen of the individual metabolome, particularly for studies using repeated measures to determine dietary response phenotype.
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| 8. |
- Machleid, Rafael, et al.
(författare)
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Feasibility and performance of cross-clone Raman calibration models in CHO cultivation
- 2024
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Ingår i: Biotechnology Journal. - : John Wiley & Sons. - 1860-6768 .- 1860-7314. ; 19:1
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Tidskriftsartikel (refereegranskat)abstract
- Raman spectroscopy is widely used in monitoring and controlling cell cultivations for biopharmaceutical drug manufacturing. However, its implementation for culture monitoring in the cell line development stage has received little attention. Therefore, the impact of clonal differences, such as productivity and growth, on the prediction accuracy and transferability of Raman calibration models is not yet well described. Raman OPLS models were developed for predicting titer, glucose and lactate using eleven CHO clones from a single cell line. These clones exhibited diverse productivity and growth rates. The calibration models were evaluated for clone-related biases using clone-wise linear regression analysis on cross validated predictions. The results revealed that clonal differences did not affect the prediction of glucose and lactate, but titer models showed a significant clone-related bias, which remained even after applying variable selection methods. The bias was associated with clonal productivity and lead to increased prediction errors when titer models were transferred to cultivations with productivity levels outside the range of their training data. The findings demonstrate the feasibility of Raman-based monitoring of glucose and lactate in cell line development with high accuracy. However, accurate titer prediction requires careful consideration of clonal characteristics during model development.
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| 9. |
- Marcinowska, Renata, et al.
(författare)
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Optimization of a sample preparation method for the metabolomic analysis of clinically relevant bacteria
- 2011
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Ingår i: Journal of Microbiological Methods. - : Elsevier. - 0167-7012 .- 1872-8359. ; 87:1, s. 24-31
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Tidskriftsartikel (refereegranskat)abstract
- Metabolomics, or metabolite profiling, is an approach that is increasingly used to study the metabolism of diverse organisms, elucidate biological processes and/or find characteristic biomarkers of physiological states. Here, we describe the optimization of a method for global metabolomic analysis of bacterial cultures, with the following steps. Cells are grown to log-phase, starting from an overnight culture and bacterial concentrations are monitored by measuring the optical density of the cultures at 600nm. At an appropriate density they are harvested by centrifugation, washed three times with NaCl solution and metabolites are extracted using methanol and a bead-mill. Dried extracts are methoxymated and derivatized with methyltrimethylsilyltrifluoroacetamide (MSTFA) then analyzed using gas chromatography coupled to time-of-flight mass spectrometry (GC-MS/TOF). Finally, patterns in the acquired data are examined by multivariate data modeling. This method enabled us to obtain reproducible metabolite profiles of Yersinia pseudotuberculosis, with about 25% compound identification, based on comparison with entries in available GC-MS libraries. To assess the potential utility of the method for comparative analysis of other bacterial species we analyzed cultures of Pseudomonas aeruginosa, Salmonella typhimurium, Escherichia coli and methicillin-sensitive Staphylococcus aureus (MSSA). Multivariate analysis of the acquired data showed that it was possible to differentiate the species according to their metabolic profiles. Our results show that the presented procedure can be used for metabolomic analysis of a wide range of bacterial species of clinical interest.
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| 10. |
- Orikiiriza, Judy, et al.
(författare)
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Lipid response patterns in acute phase paediatric Plasmodium falciparum malaria
- 2017
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Ingår i: Metabolomics. - : Springer Science and Business Media LLC. - 1573-3882 .- 1573-3890. ; 13:4
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Several studies have observed serum lipid changes during malaria infection in humans. All of them were focused at analysis of lipoproteins, not specific lipid molecules. The aim of our study was to identify novel patterns of lipid species in malaria infected patients using lipidomics profiling, to enhance diagnosis of malaria and to evaluate biochemical pathways activated during parasite infection.Methods: Using a multivariate characterization approach, 60 samples were representatively selected, 20 from each category (mild, severe and controls) of the 690 study participants between age of 0.5–6 years. Lipids from patient’s plasma were extracted with chloroform/methanol mixture and subjected to lipid profiling with application of the LCMS-QTOF method.Results: We observed a structured plasma lipid response among the malaria-infected patients as compared to healthy controls, demonstrated by higher levels of a majority of plasma lipids with the exception of even-chain length lysophosphatidylcholines and triglycerides with lower mass and higher saturation of the fatty acid chains. An inverse lipid profile relationship was observed when plasma lipids were correlated to parasitaemia.Conclusions: This study demonstrates how mapping the full physiological lipid response in plasma from malaria-infected individuals can be used to understand biochemical processes during infection. It also gives insights to how the levels of these molecules relate to acute immune responses.
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| 11. |
- Skotare, Tomas, et al.
(författare)
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Visualization of descriptive multiblock analysis
- 2020
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Ingår i: Journal of Chemometrics. - : John Wiley & Sons. - 0886-9383 .- 1099-128X. ; 34:1
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Tidskriftsartikel (refereegranskat)abstract
- Understanding and making the most of complex data collected from multiple sources is a challenging task. Data integration is the procedure of describing the main features in multiple data blocks, and several methods for multiblock analysis have been previously developed, including OnPLS and JIVE. One of the main challenges is how to visualize and interpret the results of multiblock analyses because of the increased model complexity and sheer size of data. In this paper, we present novel visualization tools that simplify interpretation and overview of multiblock analysis. We introduce a correlation matrix plot that provides an overview of the relationships between blocks found by multiblock models. We also present a multiblock scatter plot, a metadata correlation plot, and a variation distribution plot, that simplify the interpretation of multiblock models. We demonstrate our visualizations on an industrial case study in vibration spectroscopy (NIR, UV, and Raman datasets) as well as a multiomics integration study (transcript, metabolite, and protein datasets). We conclude that our visualizations provide useful tools to harness the complexity of multiblock analysis and enable better understanding of the investigated system.
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| 12. |
- Stenman, Katarina, et al.
(författare)
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Detection of local prostate metabolites by HRMAs NMR spectroscopy : a comparative study of human and rat prostate tissues
- 2010
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Ingår i: Magnetic Resonance Insights. - : Libertas Academica. - 1178-623X. ; 4, s. 27-41
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Tidskriftsartikel (refereegranskat)abstract
- The use of magnetic resonance spectroscopy (MRS) for the detection of in-vivo metabolic perturbations is increasing in popularity in Prostate Cancer (PCa) research on both humans and rodent models. However, there are distinct metabolic differences between species and prostate areas; a fact making general conclusions about PCa difficult. Here, we use High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) spectroscopy to provide tissue specific identification of metabolites and their relative ratios; information useful in providing insight into the biochemical pathways of the prostate. As our NMR-based approach reveals, human and rat prostate tissues have different metabolic signatures as reflected in numerous key metabolites, including citrate and choline compounds, but also aspartate, lysine, taurine, glutamate, glutamine, creatine and inositol. In general, distribution of these metabolites is not only highly dependent on the species (human versus rat), but also on the location (lobe/zone) in the prostate tissue and the sample pathology; an observation making HRMAS NMR of intact tissue samples a promising method for extracting differences and common features in various experimental prostate cancer models.
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| 13. |
- Surowiec, Izabella, et al.
(författare)
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Generalized Subset Designs in Analytical Chemistry
- 2017
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Ingår i: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 89:12, s. 6491-6497
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Tidskriftsartikel (refereegranskat)abstract
- Design of experiments (DOE) is an established methodology in research, development, manufacturing, and production for screening, optimization, and robustness testing. Two-level fractional factorial designs remain the preferred approach due to high information content while keeping the number of experiments low. These types of designs, however, have never been extended to a generalized multilevel reduced design type that would be capable to include both qualitative and quantitative factors. In this Article we describe a novel generalized fractional factorial design. In addition, it also provides complementary and balanced subdesigns analogous to a fold-over in two-level reduced factorial designs. We demonstrate how this design type can be applied with good results in three different applications in analytical chemistry including (a) multivariate calibration using microwave resonance spectroscopy for the determination of water in tablets, (b) stability study in drug product development, and (c) representative sample selection in clinical studies. This demonstrates the potential of generalized fractional factorial designs to be applied in many other areas of analytical chemistry where representative, balanced, and complementary subsets are required, especially when a combination of quantitative and qualitative factors at multiple levels exists.
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| 14. |
- Surowiec, Izabella, et al.
(författare)
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Joint and unique multiblock analysis of biological data : multiomics malaria study
- 2019
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Ingår i: Faraday discussions. - Cambridge : Royal Society of Chemistry. - 1359-6640 .- 1364-5498. ; 218, s. 268-283
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Tidskriftsartikel (refereegranskat)abstract
- Modern profiling technologies enable obtaining large amounts of data which can be later used for comprehensive understanding of the studied system. Proper evaluation of such data is challenging, and cannot be faced by bare analysis of separate datasets. Integrated approaches are necessary, because only data integration allows finding correlation trends common for all studied data sets and revealing hidden structures not known a priori. This improves understanding and interpretation of the complex systems. Joint and Unique MultiBlock Analysis (JUMBA) is an analysis method based on the OnPLS-algorithm that decomposes a set of matrices into joint parts containing variation shared with other connected matrices and variation that is unique for each single matrix. Mapping unique variation is important from a data integration perspective, since it certainly cannot be expected that all variation co-varies. In this work we used JUMBA for integrated analysis of lipidomic, metabolomic and oxylipin datasets obtained from profiling of plasma samples from children infected with P. falciparum malaria. P. falciparum is one of the primary contributors to childhood mortality and obstetric complications in the developing world, what makes development of the new diagnostic and prognostic tools, as well as better understanding of the disease, of utmost importance. In presented work JUMBA made it possible to detect already known trends related to disease progression, but also to discover new structures in the data connected to food intake and personal differences in metabolism. By separating the variation in each data set into joint and unique, JUMBA reduced complexity of the analysis, facilitated detection of samples and variables corresponding to specific structures across multiple datasets and by doing this enabled fast interpretation of the studied system. All this makes JUMBA a perfect choice for multiblock analysis of systems biology data.
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| 15. |
- Surowiec, Izabella, et al.
(författare)
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LC-MS/MS profiling for detection of endogenous steroids and prostaglandins in tissue samples
- 2011
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Ingår i: Journal of Separation Science. - : Wiley. - 1615-9306 .- 1615-9314. ; 34:19, s. 2650-2658
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Tidskriftsartikel (refereegranskat)abstract
- Roles of steroid hormones, and compounds that can influence their levels in cells, are of increasing interest in e.g. cancer research, partly because resistance to hormone therapies often complicates treatment. To elucidate the processes involved, the hormones and related compounds need to be accurately measured. Reversed-phase liquid chromatography with dynamic multiple reaction monitoring mass spectrometric detection in electrospray mode is capable of providing such measurements. Therefore, LC-MS/MS was developed for sensitive, selective analysis of 11 steroid hormones, cholesterol and two prostaglandins. The effects of the tissue matrix, and solid-phase extraction (SPE) sample clean-up, on the LC-MS/MS signals of the hormones were also investigated. The results show that the developed LC-MS/MS method, following SPE clean-up to reduce matrix interference, can detect selected steroids in extracts of mouse tissues. The method provides linear measurements of the steroids at concentrations up to few ng/μL, and limits of detection in the range 0.03–0.2 pg/μL (for some compounds lower than those of previously reported methods).
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| 16. |
- Surowiec, Izabella, et al.
(författare)
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Mass spectrometric identification of new minor indigoids in shellfish purple dye from Hexaplex trunculus
- 2012
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Ingår i: Dyes and pigments. - : Elsevier BV. - 0143-7208 .- 1873-3743. ; 94:2, s. 363-369
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Tidskriftsartikel (refereegranskat)abstract
- Analysis of natural dyes in historical objects is important for both conservation purposes and to determine the origin and culture that produced it. Identification of a particular dye is usually made based on the presence of its main components, while consideration of minor components is important for differentiating between dyes originating from closely related species. Tyrian purple is one of the oldest dyes known to man and derives from different species of marine molluscs. In all of these species, indigotin, indirubin and their brominated analogues are the main colouring compounds. Here, we describe the identification of minor indigoids found in extracts of the pigment obtained from one of the Tyrian purple species, Hexaplex trunculus. Identification of these compounds was made based on isotopic patterns and accurate mass measurements of protonated molecular ions and their high collision energy fragments obtained in LC-MS/MS experiments. The unknown compounds appeared to be analogues of indirubin and its mono- and dibrominated derivatives with one CO group in the indirubin backbone substituted by a CNH group. Identification of these compounds facilitates the detection of dyestuffs from H. trunculus in historical objects and increases our knowledge about the dye biosynthesis and technology of Tyrian purple production. (C) 2012 Elsevier Ltd. All rights reserved.
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| 17. |
- Surowiec, Izabella, et al.
(författare)
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Metabolic signature profiling as a diagnostic and prognostic tool in paediatric Plasmodium falciparum malaria
- 2015
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Ingår i: Open Forum Infectious Diseases. - : Oxford University Press. - 2328-8957. ; 2:2
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Tidskriftsartikel (refereegranskat)abstract
- Background: Accuracy in malaria diagnosis and staging is vital in order to reduce mortality and post infectious sequelae. Herein we present a metabolomics approach to diagnostic staging of malaria infection, specifically Plasmodium falciparum infection in children. Methods: A group of 421 patients between six months and six years of age with mild and severe states of malaria with age-matched controls were included in the study, 107, 192 and 122 individuals respectively. A multivariate design was used as basis for representative selection of twenty patients in each category. Patient plasma was subjected to Gas Chromatography-Mass Spectrometry analysis and a full metabolite profile was produced from each patient. In addition, a proof-of-concept model was tested in a Plasmodium berghei in-vivo model where metabolic profiles were discernible over time of infection. Results: A two-component principal component analysis (PCA) revealed that the patients could be separated into disease categories according to metabolite profiles, independently of any clinical information. Furthermore, two sub-groups could be identified in the mild malaria cohort who we believe represent patients with divergent prognoses. Conclusion: Metabolite signature profiling could be used both for decision support in disease staging and prognostication.
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| 18. |
- Surowiec, Izabella, et al.
(författare)
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Metabolite and Lipid Profiling of Biobank Plasma Samples Collected Prior to Onset of Rheumatoid Arthritis
- 2016
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 11:10
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The early diagnosis of rheumatoid arthritis (RA) is desirable to install treatment to prevent disease progression and joint destruction. Autoantibodies and immunological markers pre-date the onset of symptoms by years albeit not all patients will present these factors, even at disease onset. Additional biomarkers would be of high value to improve early diagnosis and understanding of the process, leading to disease development. Methods: Plasma samples donated before the onset of RA were identified in the Biobank of Northern Sweden, a collection within national health survey programs. Thirty samples from pre-symptomatic individuals and nineteen from controls were subjected to liquid chromatography-mass spectrometry (LCMS) metabolite and lipid profiling. Lipid and metabolite profiles discriminating samples from pre-symptomatic individuals from controls were identified after univariate and multivariate OPLS-DA based analyses. Results: The OPLS-DA models including pre-symptomatic individuals and controls identified profiles differentiating between the groups that was characterized by lower levels of acyl-carnitines and fatty acids, with higher levels of lysophospatidylcholines (LPCs) and metabolites from tryptophan metabolism in pre-symptomatic individuals compared with controls. Lipid profiling showed that the majority of phospholipids and sphingomyelins were at higher levels in pre-symptomatic individuals in comparison with controls. Conclusions: Our LCMS based approach demonstrated that there are changes in small molecule and lipid profiles detectable in plasma samples collected from the pre-symptomatic individuals who subsequently developed RA, which point to an up-regulation of levels of lysophospatidylcholines, and of tryptophan metabolism, perturbation of fatty acid beta-oxidation and increased oxidative stress in pre-symptomatic individuals' years before onset of symptoms.
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| 19. |
- Surowiec, Izabella, et al.
(författare)
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Metabolomics study of fatigue in patients with rheumatoid arthritis na < ve to biological treatment
- 2016
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Ingår i: Rheumatology International. - : Springer Science and Business Media LLC. - 0172-8172 .- 1437-160X. ; 36:5, s. 703-711
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Tidskriftsartikel (refereegranskat)abstract
- Fatigue occurs in all chronic inflammatory diseases, in cancer, and in some neurological conditions. Patients often regard fatigue as one of their most debilitating problems, but currently there is no established treatment and the mechanisms that lead to and regulate fatigue are incompletely understood. Our objective was to more completely understand the physiology of this phenomenon. Twenty-four patients with rheumatoid arthritis (RA) na < ve to treatment with biological drugs were enrolled for the study. Fatigue was measured with a fatigue visual analogue scale (fVAS). Ethylenediaminetetraacetic acid (EDTA) plasma samples were subjected to gas chromatography-time-of-flight mass spectrometry (GC/MS-TOF)-based metabolite profiling. Obtained metabolite data were evaluated by multivariate data analysis with orthogonal projections to latent structures (OPLS) method to pinpoint metabolic changes related to fatigue severity. A significant multivariate OPLS model was obtained between the fVAS scores and the measured metabolic levels. Increasing fatigue scores were associated with a metabolic pattern characterized by down-regulation of metabolites from the urea cycle, fatty acids, tocopherols, aromatic amino acids, and hypoxanthine. Uric acid levels were increased. Apart from fatigue, we found no other disease-related variables that might be responsible for these changes. Our MS-based metabolomic approach demonstrated strong associations between fatigue and several biochemical patterns related to oxidative stress.
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| 20. |
- Surowiec, Izabella, et al.
(författare)
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Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study
- 2016
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Ingår i: Analytical and Bioanalytical Chemistry. - : Springer Science and Business Media LLC. - 1618-2642 .- 1618-2650. ; 408:17, s. 4751-4764
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Tidskriftsartikel (refereegranskat)abstract
- Metabolomics protocols are used to comprehensively characterize the metabolite content of biological samples by exploiting cutting-edge analytical platforms, such as gas chromatography (GC) or liquid chromatography (LC) coupled to mass spectrometry (MS) assays, as well as nuclear magnetic resonance (NMR) assays. We have developed novel sample preparation procedures combined with GC-MS, LC-MS, and NMR metabolomics profiling for analyzing bronchial wash (BW) and bronchoalveolar lavage (BAL) fluid from 15 healthy volunteers following exposure to biodiesel exhaust and filtered air. Our aim was to investigate the responsiveness of metabolite profiles in the human lung to air pollution exposure derived from combustion of biofuels, such as rapeseed methyl ester biodiesel, which are increasingly being promoted as alternatives to conventional fossil fuels. Our multi-platform approach enabled us to detect the greatest number of unique metabolites yet reported in BW and BAL fluid (82 in total). All of the metabolomics assays indicated that the metabolite profiles of the BW and BAL fluids differed appreciably, with 46 metabolites showing significantly different levels in the corresponding lung compartments. Furthermore, the GC-MS assay revealed an effect of biodiesel exhaust exposure on the levels of 1-monostearylglycerol, sucrose, inosine, nonanoic acid, and ethanolamine (in BAL) and pentadecanoic acid (in BW), whereas the LC-MS assay indicated a shift in the levels of niacinamide (in BAL). The NMR assay only identified lactic acid (in BW) as being responsive to biodiesel exhaust exposure. Our findings demonstrate that the proposed multi-platform approach is useful for wide metabolomics screening of BW and BAL fluids and can facilitate elucidation of metabolites responsive to biodiesel exhaust exposure.
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| 21. |
- Surowiec, Izabella, et al.
(författare)
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Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics
- 2017
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Ingår i: Metabolomics. - : SPRINGER. - 1573-3882 .- 1573-3890. ; 13:10
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Availability of large cohorts of samples with related metadata provides scientists with extensive material for studies. At the same time, recent development of modern high-throughput 'omics' technologies, including metabolomics, has resulted in the potential for analysis of large sample sizes. Representative subset selection becomes critical for selection of samples from bigger cohorts and their division into analytical batches. This especially holds true when relative quantification of compound levels is used.Objectives We present a multivariate strategy for representative sample selection and integration of results from multi-batch experiments in metabolomics.Methods Multivariate characterization was applied for design of experiment based sample selection and subsequent subdivision into four analytical batches which were analyzed on different days by metabolomics profiling using gas-chromatography time-of-flight mass spectrometry (GC-TOFMS). For each batch OPLS-DA (R) was used and its p(corr) vectors were averaged to obtain combined metabolic profile. Jackknifed standard errors were used to calculate confidence intervals for each metabolite in the average p(corr) profile.Results A combined, representative metabolic profile describing differences between systemic lupus erythematosus (SLE) patients and controls was obtained and used for elucidation of metabolic pathways that could be disturbed in SLE.Conclusion Design of experiment based representative sample selection ensured diversity and minimized bias that could be introduced at this step. Combined metabolic profile enabled unified analysis and interpretation.
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| 22. |
- Surowiec, Izabella, et al.
(författare)
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Quantification of run order effect on chromatography : mass spectrometry profiling data
- 2018
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Ingår i: Journal of Chromatography A. - : Elsevier BV. - 0021-9673 .- 1873-3778. ; 1568, s. 229-234
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Tidskriftsartikel (refereegranskat)abstract
- Chromatographic systems coupled with mass spectrometry detection are widely used in biological studies investigating how levels of biomolecules respond to different internal and external stimuli. Such changes are normally expected to be of low magnitude and therefore all experimental factors that can influence the analysis need to be understood and minimized. Run order effect is commonly observed and constitutes a major challenge in chromatography-mass spectrometry based profiling studies that needs to be addressed before the biological evaluation of measured data is made. So far there is no established consensus, metric or method that quickly estimates the size of this effect. In this paper we demonstrate how orthogonal projections to latent structures (OPLS®) can be used for objective quantification of the run order effect in profiling studies. The quantification metric is expressed as the amount of variation in the experimental data that is correlated to the run order. One of the primary advantages with this approach is that it provides a fast way of quantifying run-order effect for all detected features, not only internal standards. Results obtained from quantification of run order effect as provided by the OPLS can be used in the evaluation of data normalization, support the optimization of analytical protocols and identification of compounds highly influenced by instrumental drift. The application of OPLS for quantification of run order is demonstrated on experimental data from plasma profiling performed on three analytical platforms: GCMS metabolomics, LCMS metabolomics and LCMS lipidomics.
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| 23. |
- Surowiec, Izabella, et al.
(författare)
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The oxylipin and endocannabidome responses in acute phase Plasmodium falciparum malaria in children
- 2017
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Ingår i: Malaria Journal. - : BIOMED CENTRAL LTD. - 1475-2875. ; 16
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Tidskriftsartikel (refereegranskat)abstract
- Background: Oxylipins and endocannabinoids are low molecular weight bioactive lipids that are crucial for initiation and resolution of inflammation during microbial infections. Metabolic complications in malaria are recognized contributors to severe and fatal malaria, but the impact of malaria infection on the production of small lipid derived signalling molecules is unknown. Knowledge of immunoregulatory patterns of these molecules in malaria is of great value for better understanding of the disease and improvement of treatment regimes, since the action of these classes of molecules is directly connected to the inflammatory response of the organism.Methods: Detection of oxylipins and endocannabinoids from plasma samples from forty children with uncomplicated and severe malaria as well as twenty controls was done after solid phase extraction followed by chromatography mass spectrometry analysis. The stable isotope dilution method was used for compound quantification. Data analysis was done with multivariate (principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA (R)) and univariate approaches (receiver operating characteristic (ROC) curves, t tests, correlation analysis).Results: Forty different oxylipin and thirteen endocannabinoid metabolites were detected in the studied samples, with one oxylipin (thromboxane B2, TXB2) in significantly lower levels and four endocannabinoids (OEA, PEA, DEA and EPEA) at significantly higher levels in infected individuals as compared to controls according to t test analysis with Bonferroni correction. Three oxylipins (13-HODE, 9-HODE and 13-oxo-ODE) were higher in severe compared to uncomplicated malaria cases according to the results from multivariate analysis. Observed changes in oxylipin levels can be connected to activation of cytochrome P450 (CYP) and 5-lipoxygenase (5-LOX) metabolic pathways in malaria infected individuals compared to controls, and related to increased levels of all linoleic acid oxylipins in severe patients compared to uncomplicated ones. The endocannabinoids were extremely responsive to malaria infection with majority of this class of molecules found at higher levels in infected individuals compared to controls.Conclusions: It was possible to detect oxylipin and endocannabinoid molecules that can be potential biomarkers for differentiation between malaria infected individuals and controls and between different classes of malaria. Metabolic pathways that could be targeted towards an adjunctive therapy in the treatment of malaria were also pinpointed.
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| 24. |
- Thysell, Elin, et al.
(författare)
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Metabolomic characterization of human prostate cancer bone metastases reveals increased levels of cholesterol
- 2010
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Ingår i: PLoS One. - : Public Library of Science. - 1932-6203. ; 5:12
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Tidskriftsartikel (refereegranskat)abstract
- Background: Metastasis to the bone is one clinically important features of prostate cancer (PCa). Current diagnostic methods cannot predict metastatic PCa at a curable stage of the disease. Identification of metabolic pathways involved in the growth of bone metastases therefore has the potential to improve PCa prognostication as well as therapy.Methodology/Principal Findings: Metabolomics was applied for the study of PCa bone metastases (n = 20) in comparison with corresponding normal bone (n = 14), and furthermore of malignant (n = 13) and benign (n = 17) prostate tissue and corresponding plasma samples obtained from patients with (n = 15) and without (n = 13) diagnosed metastases and from men with benign prostate disease (n = 30). This was done using gas chromatography-mass spectrometry for sample characterization, and chemometric bioinformatics for data analysis. Results were verified in a separate test set including metastatic and normal bone tissue from patients with other cancers (n = 7). Significant differences were found between PCa bone metastases, bone metastases of other cancers, and normal bone. Furthermore, we identified metabolites in primary tumor tissue and in plasma which were significantly associated with metastatic disease. Among the metabolites in PCa bone metastases especially cholesterol was noted. In a test set the mean cholesterol level in PCa bone metastases was 127.30 mg/g as compared to 81.06 and 35.85 mg/g in bone metastases of different origin and normal bone, respectively (P = 0.0002 and 0.001). Immunohistochemical staining of PCa bone metastases showed intense staining of the low density lipoprotein receptor and variable levels of the scavenger receptor class B type 1 and 3-hydroxy-3-methylglutaryl-coenzyme reductase in tumor epithelial cells, indicating possibilities for influx and de novo synthesis of cholesterol.Conclusions/Significance: We have identified metabolites associated with PCa metastasis and specifically identified high levels of cholesterol in PCa bone metastases. Based on our findings and the previous literature, this makes cholesterol a possible therapeutic target for advanced PCa.
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| 25. |
- Wibom, Carl, 1977-, et al.
(författare)
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Metabolomic patterns in glioblastoma and changes during radiotherapy : a clinical microdialysis study
- 2010
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 9:6, s. 2909-2919
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Tidskriftsartikel (refereegranskat)abstract
- We employed stereotactic microdialysis to sample extracellular fluid intracranially from glioblastoma patients, before and during the first five days of conventional radiotherapy treatment. Microdialysis catheters were implanted in the contrast enhancing tumor as well as in the brain adjacent to tumor (BAT). Reference samples were collected subcutaneously from the patients' abdomen. The samples were analyzed by gas chromatography-time-of-flight mass spectrometry (GC-TOF MS), and the acquired data was processed by hierarchical multivariate curve resolution (H-MCR) and analyzed with orthogonal partial least-squares (OPLS). To enable detection of treatment-induced alterations, the data was processed by individual treatment over time (ITOT) normalization. One-hundred fifty-one metabolites were reliably detected, of which 67 were identified. We found distinct metabolic differences between the intracranially collected samples from tumor and the BAT region. There was also a marked difference between the intracranially and the subcutaneously collected samples. Furthermore, we observed systematic metabolic changes induced by radiotherapy treatment among both tumor and BAT samples. The metabolite patterns affected by treatment were different between tumor and BAT, both containing highly discriminating information, ROC values of 0.896 and 0.821, respectively. Our findings contribute to increased molecular knowledge of basic glioblastoma pathophysiology and point to the possibility of detecting metabolic marker patterns associated to early treatment response.
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