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Metabolic variation in autoimmune diseases
Umeå University, Faculty of Science and Technology, Department of Chemistry.
2012 (English)Doctoral thesis, comprehensive summary (Other academic)Alternative title
Metabolisk variation i autoimmuna sjukdomar (Swedish)
Abstract [en]

The human being and other animals contain immensely complex biochemical processes that govern their function on a cellular level. It is estimated that several thousand small molecules (metabolites) are produced by various biochemical pathways in humans. Pathological processes can introduce perturbations in these biochemical pathways which can lead to changes in the amounts of some metabolites.Developments in analytical chemistry have made it possible measure a large number metabolites in a single blood sample, which gives a metabolic profile. In this thesis I have worked on establishing and understanding metabolic profiles from patients with rheumatoid arthritis (RA) and from animal models of the autoimmune diseases diabetes mellitus type 1 (T1D) and RA.Using multivariate statistical methods it is possible to identify differences between metabolic profiles of different groups. As an example we identified differences between patients with RA and healthy volunteers. This can be used to elucidate the biochemical processes that are active in a given pathological condition.Metabolite concentrations are affected by a many other things than the presence or absence of a disease. Both genomic and environmental factors are known to influence metabolic profiles. A main focus of my work has therefore been on finding strategies for ensuring that the results obtained when comparing metabolic profiles were valid and relevant. This strategy has included repetition of experiments and repeated measurement of individuals’ metabolic profiles in order to understand the sources of variation.Finding the most stable and reproducible metabolic effects has allowed us to better understand the biochemical processes seen in the metabolic profiles. This makes it possible to relate the metabolic profile differences to pathological processes and to genes and proteins involved in these.The hope is that metabolic profiling in the future can be an important tool for finding biomarkers useful for disease diagnosis, for identifying new targets for drug design and for mapping functional changes of genomic mutations. This has the potential to revolutionize our understanding of disease pathology and thus improving health care.

Place, publisher, year, edition, pages
Umeå: Umeå Universitet , 2012. , 47 p.
Keyword [en]
Rheumatoid Arthritis, Diabetes Mellitus type 1, Metabolic Profiling, Metabolomics, Chemometrics, Multivariate Data Analysis, Mass Spectrometry
National Category
Natural Sciences
Research subject
biological chemistry
Identifiers
URN: urn:nbn:se:umu:diva-59475ISBN: 978-91-7459-480-5 (print)OAI: oai:DiVA.org:umu-59475DiVA: diva2:552452
Public defence
2012-10-05, KBC-huset, Lilla hörsalen (KB3A9), Umeå universitet, Umeå, 10:00 (English)
Opponent
Supervisors
Available from: 2012-09-14 Created: 2012-09-14 Last updated: 2012-09-14Bibliographically approved
List of papers
1. Diagnostic properties of metabolic perturbations in rheumatoid arthritis
Open this publication in new window or tab >>Diagnostic properties of metabolic perturbations in rheumatoid arthritis
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2011 (English)In: Arthritis Research & Therapy, ISSN 1478-6354, E-ISSN 1478-6362, Vol. 13, no 1, R19- p.Article in journal (Refereed) Published
Abstract [en]

INTRODUCTION: The aim of the study was to assess the feasibility of diagnosing early rheumatoid arthritis (RA) by measuring selected metabolic biomarkers. METHODS: We compared the metabolic profile of patients with RA with those of healthy controls and patients with psoriatic arthritis (PsoA). The metabolites were measured using two different chromatography-mass spectrometry platforms, thereby giving a broad overview of serum metabolites. The metabolic profiles of patient and control groups were compared using multivariate statistical analysis. The findings were validated in a follow-up study of RA patients and healthy volunteers. RESULTS: RA patients were diagnosed with a sensitivity of 93 % and a specificity of 70 % in a validation study using detection of 52 metabolites. Patients with RA or PsoA could be distinguished with a sensitivity of 90 % and a specificity of 94 %. Glyceric acid, D-ribofuranoise and hypoxanthine were increased in RA patients, whereas histidine, threonic acid, methionine, cholesterol, asparagine and threonine were all decreased when compared with healthy controls. CONCLUSIONS: Metabolite profiling (metabolomics) is a potentially useful technique for diagnosing RA. The predictive value was irrespective of the presence of antibodies against cyclic citrullinated peptides (ACPA).

National Category
Rheumatology and Autoimmunity Medicinal Chemistry
Research subject
Medicine
Identifiers
urn:nbn:se:umu:diva-40411 (URN)10.1186/ar3243 (DOI)21303541 (PubMedID)
Available from: 2011-02-23 Created: 2011-02-23 Last updated: 2017-12-11Bibliographically approved
2. Altered metabolic signature in Pre-Diabetic NOD Mice
Open this publication in new window or tab >>Altered metabolic signature in Pre-Diabetic NOD Mice
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2012 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 7, no 4, e35445- p.Article in journal (Refereed) Published
Abstract [en]

Altered metabolism proceeding seroconversion in children progressing to Type 1 diabetes has previously been demonstrated. We tested the hypothesis that non-obese diabetic (NOD) mice show a similarly altered metabolic profile compared to C57BL/6 mice. Blood samples from NOD and C57BL/6 female mice was collected at 0, 1, 2, 3, 4, 5, 6, 7, 9, 11, 13 and 15 weeks and the metabolite content was analyzed using GC-MS. Based on the data of 89 identified metabolites OPLS-DA analysis was employed to determine the most discriminative metabolites. In silico analysis of potential involved metabolic enzymes was performed using the dbSNP data base. Already at 0 weeks NOD mice displayed a unique metabolic signature compared to C57BL/6. A shift in the metabolism was observed for both strains the first weeks of life, a pattern that stabilized after 5 weeks of age. Multivariate analysis revealed the most discriminative metabolites, which included inosine and glutamic acid. In silico analysis of the genes in the involved metabolic pathways revealed several SNPs in either regulatory or coding regions, some in previously defined insulin dependent diabetes (Idd) regions. Our result shows that NOD mice display an altered metabolic profile that is partly resembling the previously observation made in children progressing to Type 1 diabetes. The level of glutamic acid was one of the most discriminative metabolites in addition to several metabolites in the TCA cycle and nucleic acid components. The in silico analysis indicated that the genes responsible for this reside within previously defined Idd regions.

Place, publisher, year, edition, pages
Public Library of Science, 2012
National Category
Endocrinology and Diabetes
Identifiers
urn:nbn:se:umu:diva-54276 (URN)10.1371/journal.pone.0035445 (DOI)000305341600149 ()22514744 (PubMedID)
Note

This work was supported by the Kempe Foundation, the Medical Faculty at Umeå University, Insamlingsstiftelsen at Umeå University, Magnus Bergvalls stiftelse, JDRF (1-2008-1011), and the Children Diabetes Foundation in Sweden. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Available from: 2012-04-23 Created: 2012-04-23 Last updated: 2017-12-07Bibliographically approved
3. Metabolic responses to change in disease activity during tumor necrosis factor inhibition in patients with rheumatoid arthritis
Open this publication in new window or tab >>Metabolic responses to change in disease activity during tumor necrosis factor inhibition in patients with rheumatoid arthritis
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2012 (English)In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 11, no 7, 3796-3804 p.Article in journal (Refereed) Published
Abstract [en]

Assessment of disease activity in patients with rheumatoid arthritis (RA) is of importance in the evaluation of treatment. The most important measure of disease activity is the Disease Activity Score counted in 28 joints (DAS28). In this study, we evaluated whether metabolic profiling could complement current measures of disease activity. Fifty-six patients, in two separate studies, were followed for two years after commencing anti-TNF therapy. DAS28 was assessed, and metabolic profiles were recorded at defined time points. Correlations between metabolic profile and DAS28 scores were analyzed using multivariate statistics. The metabolic responses to lowering DAS28 scores varied in different patients but could predict DAS28 scores at the individual and subgroup level models. The erythrocyte sedimentation rate (ESR) component in DAS28 was most correlated to the metabolite data, pointing to inflammation as the primary effect driving metabolic profile changes. Patients with RA had differing metabolic response to changes in DAS28 following anti-TNF therapy. This suggests that discovery of new metabolic biomarkers for disease activity will derive from studies at the individual and subgroup level. Increased inflammation, measured as ESR, was the main common effect seen in metabolic profiles from periods associated with high DAS28.

Keyword
anti-TNF treatment; rheumatoid arthritis; OPLS; metabolomics
National Category
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:umu:diva-56546 (URN)10.1021/pr300296v (DOI)22574709 (PubMedID)
Available from: 2012-06-20 Created: 2012-06-20 Last updated: 2017-12-07Bibliographically approved
4. Physiological metabolic differences between Ncf1 mutant and wild type mice
Open this publication in new window or tab >>Physiological metabolic differences between Ncf1 mutant and wild type mice
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

The Ncf1 gene is a major determinant of disease severity in experimental animal models of Rheumatoid Arthritis. The Ncf1 codes a protein that is important for regulating the activity of the NADPH oxidase (NOX2) complex. This complex produces reactive oxygen species (ROS) important both for killing off pathogens but also for regulating the immune response.Using metabolic profiling techniques we have found that mutation of the Ncf1 gene leads to alteration of the metabolic profile even without induction of inflammation, thus demonstrating a physiological role for the gene. Transgenic expression of Ncf1 in macrophages restored the metabolic profile so it was very similar to that seen in wild type animals. This indicates that macrophages have an immune regulatory role even outside inflammation.The metabolic differences between genotypes were subtle so the experiments were repeated to ensure validity of the results. The most stable metabolic effect across studies was an increase in free fatty acids in animals with functional NOX2 oxidation. This is likely due to production of immune regulatory compounds in the pathways initiated by phospholipase A2.

National Category
Natural Sciences
Research subject
biological chemistry
Identifiers
urn:nbn:se:umu:diva-59476 (URN)
Available from: 2012-09-14 Created: 2012-09-14 Last updated: 2012-09-14Bibliographically approved

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