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Altered metabolic signature in Pre-Diabetic NOD Mice
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen. (Computational Life Science Cluster (CLiC))
Umeå universitet, Medicinska fakulteten, Institutionen för klinisk mikrobiologi.
Umeå Plant Science Center, Department of Forest Genetics and Plant Physiology, Swedish University of Agriculture Sciences, Umeå, Sweden.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen. (Computational Life Science Cluster (CLiC))
Vise andre og tillknytning
2012 (engelsk)Inngår i: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 7, nr 4, s. e35445-Artikkel i tidsskrift (Fagfellevurdert) 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.

sted, utgiver, år, opplag, sider
Public Library of Science , 2012. Vol. 7, nr 4, s. e35445-
HSV kategori
Identifikatorer
URN: urn:nbn:se:umu:diva-54276DOI: 10.1371/journal.pone.0035445ISI: 000305341600149PubMedID: 22514744OAI: oai:DiVA.org:umu-54276DiVA, id: diva2:517426
Merknad

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.

Tilgjengelig fra: 2012-04-23 Laget: 2012-04-23 Sist oppdatert: 2018-06-08bibliografisk kontrollert
Inngår i avhandling
1. Metabolic variation in autoimmune diseases
Åpne denne publikasjonen i ny fane eller vindu >>Metabolic variation in autoimmune diseases
2012 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Alternativ tittel[sv]
Metabolisk variation i autoimmuna sjukdomar
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.

sted, utgiver, år, opplag, sider
Umeå: Umeå Universitet, 2012. s. 47
Emneord
Rheumatoid Arthritis, Diabetes Mellitus type 1, Metabolic Profiling, Metabolomics, Chemometrics, Multivariate Data Analysis, Mass Spectrometry
HSV kategori
Forskningsprogram
biologisk kemi
Identifikatorer
urn:nbn:se:umu:diva-59475 (URN)978-91-7459-480-5 (ISBN)
Disputas
2012-10-05, KBC-huset, Lilla hörsalen (KB3A9), Umeå universitet, Umeå, 10:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2012-09-14 Laget: 2012-09-14 Sist oppdatert: 2018-06-08bibliografisk kontrollert
2. Metab-Immune analysis of the non-obese diabetic mouse
Åpne denne publikasjonen i ny fane eller vindu >>Metab-Immune analysis of the non-obese diabetic mouse
2016 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

Type 1A diabetes mellitus or T1D is a chronic disease characterized by T cell mediated destruction of the insulin producing β cells in the islets of Langerhans. The classical symptoms include high glucose levels in urine and blood, polyuria, and polydipsia. Complications associated with T1D include blindness, amputations, and end-stage renal disease, and premature death. The non-obese diabetic (NOD) mouse, first described in 1980, is widely used as a model organism for T1D. T1D disease in the NOD mouse shares a number of similarities to human T1D including dependence on genetic and environmental factors. More than 30 disease associated gene regions or loci (termed insulin dependent diabetes, or Idd, loci) have been associated with T1D development in NOD. For some of these Idds, the corresponding region in human has been linked to the development of T1D in human.

T1D, both in humans and mice, is recognized as a T cell mediated disease. However, many studies have shown the importance of both the metabolome and the immune system in the pathogenesis of the disease. Appearance of autoantibodies in the serum of patients is the first sign of pathogenesis. However, molecular and cellular events precede the immune attack on the β-cell immunity. It has been shown that patients who developed T1D have an altered metabolome prior to the appearance of autoantibodies. Although much is known about the pathogenesis of T1D, the contribution of the environment/immune factors triggering the disease is still to be revealed. 

In the present study both metabolic and immune deviations observed in the NOD mouse was analyzed. Serum metabolome analysis of the NOD mouse revealed striking resemblance to the human metabolic profile, with many metabolites in the TCA cycle significantly different from the non-diabetic control B6 mice. In addition, an increased level of glutamic acid was of the most distinguishing metabolite. A detailed bioinformatics analysis revealed various genes/enzymes to be present in the Idd regions. Compared to B6 mice, many of the genes correlated to the metabolic pathways, showed single nucleotide polymorphism (SNP), which can eventually affect the functionality of the protein. A genetic analysis of the increased glutamic acid revealed several Idd regions to be involved in this phenotype. The regions mapped in the genetic analysis harbor important enzymes and transporters related to glutamic acid. In-vitro islet culture with glutamic acid led to increased beta cell death indicating a toxic role of glutamic acid specifically towards insulin producing beta cells.

In the analysis of the immune system, B cells from NOD mice, which are known to express high levels of TACI, were stimulated with APRIL, a TACI ligand. This resulted in enhanced plasma cell differentiation accompanied with increased class switching and IgG production. NOD mice have previously been shown to react vigorously to T-dependent antigens upon immunization. In this study we confirmed this as NOD mice showed an enhanced and prolonged immune response to hen egg lysozyme. Thus, serum IgG levels were significantly increased in the NOD mice and were predominantly of the IgG1 subtype. Immunofluorescence analysis revealed increased number of germinal centers in the NOD mice. Transfer of purified B and T cells from NOD to an immune deficient mouse could reproduce the original phenotype as seen in the NOD mice.    

Collectively, this thesis has analyzed the metabolomics and immune deviations observed in the NOD mice.

sted, utgiver, år, opplag, sider
Umeå: Umeå University, 2016. s. 62
Serie
Umeå University medical dissertations, ISSN 0346-6612 ; 1777
Emneord
NOD mouse, Type 1 diabetes, B cells, glutamic acid, metabolomics
HSV kategori
Forskningsprogram
immunologi
Identifikatorer
urn:nbn:se:umu:diva-119444 (URN)978-91-7601-404-2 (ISBN)
Disputas
2016-05-13, A5_R0, Byg 6A, NUS, Umeå, 13:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2016-04-21 Laget: 2016-04-19 Sist oppdatert: 2018-06-07bibliografisk kontrollert

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