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Surowiec, Izabella
Publications (10 of 15) Show all publications
Surowiec, I., Johansson, E., Stenlund, H., Rantapää-Dahlqvist, S., Bergström, S., Normark, J. & Trygg, J. (2018). Quantification of run order effect on chromatography: mass spectrometry profiling data. Journal of Chromatography A, 1568, 229-234
Open this publication in new window or tab >>Quantification of run order effect on chromatography: mass spectrometry profiling data
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2018 (English)In: Journal of Chromatography A, ISSN 0021-9673, E-ISSN 1873-3778, Vol. 1568, p. 229-234Article in journal (Refereed) Published
Abstract [en]

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.

Keywords
Run order effect quantification, Mass spectrometry profiling, OPLS, Instrumental drift
National Category
Rheumatology and Autoimmunity
Identifiers
urn:nbn:se:umu:diva-150428 (URN)10.1016/j.chroma.2018.07.019 (DOI)000443669600025 ()2-s2.0-85049727571 (Scopus ID)
Available from: 2018-08-07 Created: 2018-08-07 Last updated: 2018-11-05Bibliographically approved
Skotare, T., Sjögren, R., Surowiec, I., Nilsson, D. & Trygg, J. (2018). Visualization of descriptive multiblock analysis. Paper presented at 2018/10/09. Journal of Chemometrics
Open this publication in new window or tab >>Visualization of descriptive multiblock analysis
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2018 (English)In: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128XArticle in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
John Wiley & Sons, 2018
Keywords
data fusion, descriptive analytics, multiblock analysis, OnPLS, visualization
National Category
Other Chemistry Topics
Identifiers
urn:nbn:se:umu:diva-152512 (URN)10.1002/cem.3071 (DOI)
Conference
2018/10/09
Funder
eSSENCE - An eScience CollaborationSwedish Research Council, 2016‐04376
Available from: 2018-10-09 Created: 2018-10-09 Last updated: 2018-11-09Bibliographically approved
Checa, A., Idborg, H., Zandian, A., Sar, D. G., Surowiec, I., Trygg, J., . . . Wheelock, C. E. (2017). Dysregulations in circulating sphingolipids associate with disease activity indices in female patients with systemic lupus erythematosus: a cross-sectional study. Lupus, 26(10), 1023-1033
Open this publication in new window or tab >>Dysregulations in circulating sphingolipids associate with disease activity indices in female patients with systemic lupus erythematosus: a cross-sectional study
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2017 (English)In: Lupus, ISSN 0961-2033, E-ISSN 1477-0962, Vol. 26, no 10, p. 1023-1033Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
SAGE PUBLICATIONS LTD, 2017
Keywords
Systemic lupus erythematosus, sphingolipids, disease activity
National Category
Rheumatology and Autoimmunity Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:umu:diva-139613 (URN)10.1177/0961203316686707 (DOI)000407822000002 ()28134039 (PubMedID)
Available from: 2017-10-09 Created: 2017-10-09 Last updated: 2018-06-09Bibliographically approved
Surowiec, I., Vikström, L., Hector, G., Johansson, E., Vikström, C. & Trygg, J. (2017). Generalized Subset Designs in Analytical Chemistry. Analytical Chemistry, 89(12), 6491-6497
Open this publication in new window or tab >>Generalized Subset Designs in Analytical Chemistry
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2017 (English)In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 89, no 12, p. 6491-6497Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2017
National Category
Analytical Chemistry
Identifiers
urn:nbn:se:umu:diva-137804 (URN)10.1021/acs.analchem.7b00506 (DOI)000404087600031 ()28497952 (PubMedID)
Available from: 2017-07-27 Created: 2017-07-27 Last updated: 2018-06-09Bibliographically approved
Orikiiriza, J., Surowiec, I., Lindquist, E., Bonde, M., Magambo, J., Muhinda, C., . . . Normark, J. (2017). Lipid response patterns in acute phase paediatric Plasmodium falciparum malaria. Metabolomics, 13(4), Article ID 41.
Open this publication in new window or tab >>Lipid response patterns in acute phase paediatric Plasmodium falciparum malaria
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2017 (English)In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 13, no 4, article id 41Article in journal (Refereed) Published
Abstract [en]

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.

Keywords
Lipidomics profiling, Malaria, Plasmodium falciparum, Triacylglycerides, Lysophosphatidylcholines
National Category
Infectious Medicine
Identifiers
urn:nbn:se:umu:diva-133729 (URN)10.1007/s11306-017-1174-2 (DOI)000394544900010 ()28286460 (PubMedID)
Available from: 2017-05-05 Created: 2017-05-05 Last updated: 2018-06-09Bibliographically approved
Surowiec, I., Johansson, E., Torell, F., Idborg, H., Gunnarsson, I., Svenungsson, E., . . . Trygg, J. (2017). Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics. Metabolomics, 13(10), Article ID 114.
Open this publication in new window or tab >>Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics
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2017 (English)In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 13, no 10, article id 114Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
SPRINGER, 2017
Keywords
OPLS, Metabolomics, Multi-batch analysis, Representative sample selection
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:umu:diva-140022 (URN)10.1007/s11306-017-1248-1 (DOI)000410911200007 ()28890672 (PubMedID)
Note

Open Access, link to the Creative Commons license: https://creativecommons.org/licenses/by/4.0/

Available from: 2017-09-29 Created: 2017-09-29 Last updated: 2018-06-09Bibliographically approved
Surowiec, I., Gouveia-Figueira, S., Orikiiriza, J., Lindquist, E., Bonde, M., Magambo, J., . . . Trygg, J. (2017). The oxylipin and endocannabidome responses in acute phase Plasmodium falciparum malaria in children. Malaria Journal, 16, Article ID 358.
Open this publication in new window or tab >>The oxylipin and endocannabidome responses in acute phase Plasmodium falciparum malaria in children
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2017 (English)In: Malaria Journal, ISSN 1475-2875, E-ISSN 1475-2875, Vol. 16, article id 358Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
BIOMED CENTRAL LTD, 2017
Keywords
Oxylipins, Endocannabinoids, Malaria infection, Plasmodium falciparum
National Category
Infectious Medicine Microbiology in the medical area
Identifiers
urn:nbn:se:umu:diva-140041 (URN)10.1186/s12936-017-2001-y (DOI)000410218400001 ()28886714 (PubMedID)
Funder
Swedish Research CouncilSwedish Society of Medicine
Note

Ytterligare finansiär: Jeansson Foundation

Available from: 2017-10-05 Created: 2017-10-05 Last updated: 2018-06-09Bibliographically approved
Bengtsson, A. A., Trygg, J., Wuttge, D. M., Sturfelt, G., Theander, E., Donten, M., . . . Lundstedt, T. (2016). Metabolic Profiling of Systemic Lupus Erythematosus and Comparison with Primary Sjögren’s Syndrome and Systemic Sclerosis. PLoS ONE, 11(7), Article ID e0159384.
Open this publication in new window or tab >>Metabolic Profiling of Systemic Lupus Erythematosus and Comparison with Primary Sjögren’s Syndrome and Systemic Sclerosis
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2016 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 7, article id e0159384Article in journal (Refereed) Published
Abstract [en]

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. 

Keywords
Systemic lupus erythematosus, Metabolites, Metabolomics, Biomarkers, Drug metabolism, Oxidative stress, Complement system, Rheumatology
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:umu:diva-124383 (URN)10.1371/journal.pone.0159384 (DOI)000380797500069 ()
Funder
Swedish Research Council, 2011-6044
Available from: 2016-08-08 Created: 2016-08-08 Last updated: 2018-06-07Bibliographically approved
Surowiec, I., Ärlestig, L., Rantapää-Dahlqvist, S. & Trygg, J. (2016). Metabolite and Lipid Profiling of Biobank Plasma Samples Collected Prior to Onset of Rheumatoid Arthritis. PLoS ONE, 11(10), Article ID e0164196.
Open this publication in new window or tab >>Metabolite and Lipid Profiling of Biobank Plasma Samples Collected Prior to Onset of Rheumatoid Arthritis
2016 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 10, article id e0164196Article in journal (Refereed) Published
Abstract [en]

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.

National Category
Chemical Sciences Rheumatology and Autoimmunity
Identifiers
urn:nbn:se:umu:diva-128917 (URN)10.1371/journal.pone.0164196 (DOI)000386203800012 ()27755546 (PubMedID)
Available from: 2016-12-19 Created: 2016-12-19 Last updated: 2018-06-09Bibliographically approved
Surowiec, I., Gjesdal, C. G., Jonsson, G., Norheim, K. B., Lundstedt, T., Trygg, J. & Omdal, R. (2016). Metabolomics study of fatigue in patients with rheumatoid arthritis na < ve to biological treatment. Rheumatology International, 36(5), 703-711
Open this publication in new window or tab >>Metabolomics study of fatigue in patients with rheumatoid arthritis na < ve to biological treatment
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2016 (English)In: Rheumatology International, ISSN 0172-8172, E-ISSN 1437-160X, Vol. 36, no 5, p. 703-711Article in journal (Refereed) Published
Abstract [en]

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.

Keywords
Rheumatoid arthritis, Fatigue, Metabolomics, Oxidative stress
National Category
Rheumatology and Autoimmunity
Identifiers
urn:nbn:se:umu:diva-121466 (URN)10.1007/s00296-016-3426-2 (DOI)000374567500012 ()
Available from: 2016-06-20 Created: 2016-06-02 Last updated: 2018-06-07Bibliographically approved
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