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  • 1. Brandsma, Joost
    et al.
    Goss, Victoria M.
    Yang, Xian
    Bakke, Per S.
    Caruso, Massimo
    Chanez, Pascal
    Dahlén, Sven-Erik
    Fowler, Stephen J.
    Horvath, Ildiko
    Krug, Norbert
    Montuschi, Paolo
    Sanak, Marek
    Sandström, Thomas
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Avdelningen för medicin.
    Shaw, Dominick E.
    Chung, Kian Fan
    Singer, Florian
    Fleming, Louise J.
    Sousa, Ana R.
    Pandis, Ioannis
    Bansal, Aruna T.
    Sterk, Peter J.
    Djukanovic, Ratko
    Postle, Anthony D.
    Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers2018Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 14, nr 10, artikel-id 123Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Lung epithelial lining fluid (ELF)-sampled through sputum induction-is a medium rich in cells, proteins and lipids. However, despite its key role in maintaining lung function, homeostasis and defences, the composition and biology of ELF, especially in respect of lipids, remain incompletely understood.

    Objectives: To characterise the induced sputum lipidome of healthy adult individuals, and to examine associations between different ELF lipid phenotypes and the demographic characteristics within the study cohort.

    Methods: Induced sputum samples were obtained from 41 healthy non-smoking adults, and their lipid compositions analysed using a combination of untargeted shotgun and liquid chromatography mass spectrometry methods. Topological data analysis (TDA) was used to group subjects with comparable sputum lipidomes in order to identify distinct ELF phenotypes.

    Results: The induced sputum lipidome was diverse, comprising a range of different molecular classes, including at least 75 glycerophospholipids, 13 sphingolipids, 5 sterol lipids and 12 neutral glycerolipids. TDA identified two distinct phenotypes differentiated by a higher total lipid content and specific enrichments of diacyl-glycerophosphocholines, -inositols and -glycerols in one group, with enrichments of sterols, glycolipids and sphingolipids in the other. Subjects presenting the lipid-rich ELF phenotype also had significantly higher BMI, but did not differ in respect of other demographic characteristics such as age or gender.

    Conclusions: We provide the first evidence that the ELF lipidome varies significantly between healthy individuals and propose that such differences are related to weight status, highlighting the potential impact of (over)nutrition on lung lipid metabolism.

  • 2.
    Chorell, Elin
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Medicin. Norrlands University Hospital, Umeå University, Umeå, Sweden .
    Ryberg, Mats
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Medicin.
    Larsson, Christel
    Department of Food and Nutrition and Sport Science, University of Gothenburg, Gothenburg, Sweden.
    Sandberg, Susanne
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Medicin.
    Mellberg, Caroline
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Medicin.
    Lindahl, Bernt
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Yrkes- och miljömedicin.
    Antti, Henrik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Olsson, Tommy
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Medicin.
    Plasma metabolomic response to postmenopausal weight loss induced by different diets2016Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 12, nr 5, artikel-id 85Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background Menopause is associated with increased abdominal fat and increased risk of developing diabetes and cardiovascular disease. Objectives The present study evaluated the plasma metabolic response in relation to insulin sensitivity after weight loss via diet intervention. Methods This work includes two studies; i) Ten women on a 5 weeks Paleolithic-type diet (PD, 30 energy percent (E%) protein, 40 E% fat, 30 E% carbohydrates), ii) 55 women on 6 months of either PD or Nordic Nutrition Recommendations diet (NNR, 15 E% protein, 30 E% fat, and 55 E% carbohydrates). Plasma metabolic profiles were acquired at baseline and post diet using gas chromatography time-of-flight/mass spectrometry and investigated in relation to insulin sensitivity using multivariate bioinformatics. Results Both the PD and NNR diet resulted in significant weight loss, reduced waist circumference, improved serum lipid profiles, and improved insulin sensitivity. We detected a baseline metabolic profile that correlated significantly with insulin sensitivity, and of which components increased significantly in the PD group compared to NNR. Specifically, a significant increase in myo-inositol (MI), a second messenger of insulin action, and beta-hydroxybutyric acid (beta-HB)increased while dihomogamma-linoleic acid (DGLA) decreased in PD compared to NNR, which correlated with improved insulin sensitivity. We also detected a significant decrease in tyrosine and tryptophan, potential markers of insulin resistance when elevated in the circulation, with the PD but not the NNR. Conclusions Using metabolomics, we detected changes in the plasma metabolite profiles associated with weight loss in postmenopausal women by different diets. The metabolic profiles following 6 months of PD were linked to beneficial effects on insulin sensitivity compared to NNR.

  • 3. Dugas, Lara R.
    et al.
    Chorell, Elin
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Medicin.
    Plange-Rhule, Jacob
    Lambert, Estelle V.
    Cao, Guichan
    Cooper, Richard S.
    Layden, Brian T.
    Scholten, Denise
    Olsson, Tommy
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Medicin.
    Luke, Amy
    Goedecke, Julia H.
    Obesity-related metabolite profiles of black women spanning the epidemiologic transition2016Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 12, nr 3, artikel-id 45Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In developed countries, specific metabolites have been associated with obesity and metabolic diseases, e.g. type 2 diabetes. It is unknown whether a similar profile persists across populations of African-origin, at increased risk for obesity and related diseases. In a cross-sectional study of normal-weight and obese black women (33.3 +/- 6.3 years) from the US (N = 69, 65 % obese), South Africa (SA, N = 97, 49 % obese) and Ghana (N = 82, 33 % obese) serum metabolite profiles were characterized via gas chromatography-time of flight/mass spectrometry. In US and SA women, BMI correlated with branched-chain and aromatic amino acids, as well as dopamine and aminoadipic acid. The relationship between BMI and lipid metabolites differed by site; BMI correlated positively with palmitoleic acid (16: 1) in the US; negatively with stearic acid (18: 0) in SA, and positively with arachidonic acid (20: 4) in Ghana. BMI was also positively associated with sugar-related metabolites in the US; i.e. uric acid, and mannitol, and with glucosamine, glucoronic acid and mannitol in SA. While we identified a common amino acid metabolite profile associated with obesity in black women from the US and SA, we also found site-specific obesity-related metabolites suggesting that the local environment is a key moderator of obesity.

  • 4. Fages, Anne
    et al.
    Ferrari, Pietro
    Monni, Stefano
    Dossus, Laure
    Floegel, Anna
    Mode, Nicolle
    Johansson, Mattias
    Umeå universitet, Medicinska fakulteten, Enheten för biobanksforskning. International Agency for Research in Cancer (IARC-WHO), 150 Cours Albert Thomas, Lyon, France .
    Travis, Ruth C.
    Bamia, Christina
    Sánchez-Pérez, María-José
    Chiodini, Paolo
    Boshuizen, Hendriek C.
    Chadeau-Hyam, Marc
    Riboli, Elio
    Jenab, Mazda
    Elena-Herrmann, Bénédicte
    Investigating sources of variability in metabolomic data in the EPIC study: the Principal Component Partial R-square (PC-PR2) method2014Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 10, nr 6, s. 1074-1083Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The key goal of metabolomic studies is to identify relevant individual biomarkers or composite metabolic patterns associated with particular disease status or patho-physiological conditions. There are currently very few approaches to evaluate the variability of metabolomic data in terms of characteristics of individuals or aspects pertaining to technical processing. To address this issue, a method was developed to identify and quantify the contribution of relevant sources of variation in metabolomic data prior to investigation of etiological hypotheses. The Principal Component Partial R-square (PC-PR2) method combines features of principal component and of multivariable linear regression analyses. Within the European Prospective Investigation into Cancer and nutrition (EPIC), metabolic profiles were determined by H-1 NMR analysis on 807 serum samples originating from a nested liver cancer case-control study. PC-PR2 was used to quantify the variability of metabolomic profiles in terms of study subjects age, sex, body mass index, country of origin, smoking status, diabetes and fasting status, as well as factors related to sample processing. PC-PR2 enables the evaluation of important sources of variations in metabolomic studies within large-scale epidemiological investigations.

  • 5.
    Jonsson, Pär
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Wuolikainen, Anna
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Thysell, Elin
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Patologi.
    Chorell, Elin
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Medicin.
    Stattin, Pär
    Umeå universitet, Medicinska fakulteten, Institutionen för kirurgisk och perioperativ vetenskap, Urologi och andrologi.
    Wikström, Pernilla
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Patologi.
    Antti, Henrik
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Constrained randomization and multivariate effect projections improve information extraction and biomarker pattern discovery in metabolomics studies involving dependent samples2015Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 11, nr 6, s. 1667-1678Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Analytical drift is a major source of bias in mass spectrometry based metabolomics confounding interpretation and biomarker detection. So far, standard protocols for sample and data analysis have not been able to fully resolve this. We present a combined approach for minimizing the influence of analytical drift on multivariate comparisons of matched or dependent samples in mass spectrometry based metabolomics studies. The approach is building on a randomization procedure for sample run order, constrained to independent randomizations between and within dependent sample pairs (e.g. pre/post intervention). This is followed by a novel multivariate statistical analysis strategy allowing paired or dependent analyses of individual effects named OPLS-effect projections (OPLS-EP). We show, using simulated data that OPLS-EP gives improved interpretation over existing methods and that constrained randomization of sample run order in combination with an appropriate dependent statistical test increase the accuracy and sensitivity and decrease the false omission rate in biomarker detection. We verify these findings and prove the strength of the suggested approach in a clinical data set consisting of LC/MS data of blood plasma samples from patients before and after radical prostatectomy. Here OPLS-EP compared to traditional (independent) OPLS-discriminant analysis (OPLS-DA) on constrained randomized data gives a less complex model (3 versus 5 components) as well a higher predictive ability (Q2 = 0.80 versus Q2 = 0.55). We explain this by showing that paired statistical analysis detects 37 unique significant metabolites that were masked for the independent test due to bias, including analytical drift and inter-individual variation.

  • 6.
    Karlsborn, Tony
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för molekylärbiologi (Teknisk-naturvetenskaplig fakultet).
    Mahmud, A K M Firoj
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för molekylärbiologi (Teknisk-naturvetenskaplig fakultet).
    Tükenmez, Hasan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för molekylärbiologi (Teknisk-naturvetenskaplig fakultet).
    Byström, Anders S.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för molekylärbiologi (Teknisk-naturvetenskaplig fakultet).
    Loss of ncm5 and mcm5 wobble uridine side chains results in an altered metabolic profile2016Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 12, nr 12, artikel-id 177Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Introduction: The Elongator complex, comprising six subunits (Elp1p-Elp6p), is required for formation of 5-carbamoylmethyl (ncm(5)) and 5-methoxycarbonylmethyl (mcm(5)) side chains on wobble uridines in 11 out of 42 tRNA species in Saccharomyces cerevisiae. Loss of these side chains reduces the efficiency of tRNA decoding during translation, resulting in pleiotropic phenotypes. Overexpression of hypomodified tRNA(s2UUU)(Lys); tRNA(s2UUG)(Gln) and tRNA(s2UUC)(Glu), which in wild-type strains are modified with mcm(5)s(2)U, partially suppress phenotypes of an elp3 Delta strain. Objectives: To identify metabolic alterations in an elp3 Delta strain and elucidate whether these metabolic alterations are suppressed by overexpression of hypomodified tRNA(s2UUU)(Lys); tRNA(s2UUG)(Gln) and tRNA(s2UUC)(Glu). Method: Metabolic profiles were obtained using untargeted GC-TOF-MS of a temperature-sensitive elp3 Delta strain carrying either an empty low-copy vector, an empty high-copy vector, a low-copy vector harboring the wild-type ELP3 gene, or a high-copy vector overexpressing tRNA(s2UUU)(Lys); tRNA(s2UUG)(Gln) and tRNA(s2UUC)(Glu). The temperature sensitive elp3 Delta strain derivatives were cultivated at permissive (30 degrees C) or semi-permissive (34 degrees C) growth conditions. Results: Culturing an elp3 Delta strain at 30 or 34 degrees C resulted in altered metabolism of 36 and 46 %, respectively, of all metabolites detected when compared to an elp3D strain carrying the wild-type ELP3 gene. Overexpression of hypomodified tRNA(s2UUU)(Lys); tRNA(s2UUG)(Gln) and tRNA(s2UUC)(Glu) suppressed a subset of the metabolic alterations observed in the elp3 Delta strain. Conclusion: Our results suggest that the presence of ncm(5)- and mcm(5)-side chains on wobble uridines in tRNA are important for metabolic homeostasis.

  • 7. Lindahl, Anna
    et al.
    Heuchel, Rainer
    Forshed, Jenny
    Lehtio, Janne
    Lohr, Matthias
    Nordström, Anders
    Umeå universitet, Medicinska fakulteten, Institutionen för molekylärbiologi (Medicinska fakulteten).
    Discrimination of pancreatic cancer and pancreatitis by LC-MS metabolomics2017Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 13, nr 5, artikel-id 61Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Introduction Pancreatic ductal adenocarcinoma (PDAC) is the fifth most common cause of cancer-related death in Europe with a 5-year survival rate of <5%. Chronic pancreatitis (CP) is a risk factor for PDAC development, but in the majority of cases malignancy is discovered too late for curative treatment. There is at present no reliable diagnostic marker for PDAC available. Objectives The aim of the study was to identify single blood-based metabolites or a panel of metabolites discriminating PDAC and CP using liquid chromatography-mass spectrometry (LC-MS). Methods A discovery cohort comprising PDAC (n = 44) and CP (n = 23) samples was analyzed by LC-MS followed by univariate (Student's t test) and multivariate (orthogonal partial least squares-discriminant analysis (OPLS-DA)) statistics. Discriminative metabolite features were subject to raw data examination and identification to ensure high feature quality. Their discriminatory power was then confirmed in an independent validation cohort including PDAC (n = 20) and CP (n = 31) samples. Results Glycocholic acid, N-palmitoyl glutamic acid and hexanoylcarnitine were identified as single markers discriminating PDAC and CP by univariate analysis. OPLSDA resulted in a panel of five metabolites including the aforementioned three metabolites as well as phenylacetylglutamine (PAGN) and chenodeoxyglycocholate. Conclusion Using LC-MS-based metabolomics we identified three single metabolites and a five-metabolite panel discriminating PDAC and CP in two independent cohorts. Although further study is needed in larger cohorts, the metabolites identified are potentially of use in PDAC diagnostics.

  • 8. Orikiiriza, Judy
    et al.
    Surowiec, Izabella
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Lindquist, Elisabeth
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för molekylärbiologi (Teknisk-naturvetenskaplig fakultet).
    Bonde, Mari
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Magambo, Jimmy
    Muhinda, Charles
    Bergström, Sven
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för molekylärbiologi (Teknisk-naturvetenskaplig fakultet). Umeå universitet, Medicinska fakulteten, Molekylär Infektionsmedicin, Sverige (MIMS). Umeå universitet, Medicinska fakulteten, Umeå Centre for Microbial Research (UCMR).
    Trygg, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Normark, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen. Umeå universitet, Medicinska fakulteten, Umeå Centre for Microbial Research (UCMR). Umeå universitet, Medicinska fakulteten, Institutionen för klinisk mikrobiologi, Infektionssjukdomar. Umeå universitet, Medicinska fakulteten, Institutionen för molekylärbiologi (Medicinska fakulteten).
    Lipid response patterns in acute phase paediatric Plasmodium falciparum malaria2017Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 13, nr 4, artikel-id 41Artikel i tidskrift (Refereegranskat)
    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.

  • 9.
    Papazian, Stefano
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysiologisk botanik. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Umeå Plant Science Centre (UPSC).
    Girdwood, Tristan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysiologisk botanik. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Umeå Plant Science Centre (UPSC).
    Wessels, Bernard A.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysiologisk botanik. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Umeå Plant Science Centre (UPSC).
    Poelman, Erik H.
    Dicke, Marcel
    Moritz, Thomas
    Albrectsen, Benedicte R.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för fysiologisk botanik. Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Umeå Plant Science Centre (UPSC).
    Leaf metabolic signatures induced by real and simulated herbivory in black mustard (Brassica nigra)2019Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 15, nr 10, artikel-id 130Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Introduction The oxylipin methyl jasmonate (MeJA) is a plant hormone active in response signalling and defence against herbivores. Although MeJA is applied experimentally to mimic herbivory and induce plant defences, its downstream effects on the plant metabolome are largely uncharacterized, especially in the context of primary growth and tissue-specificity of the response. Objectives We investigated the effects of MeJA-simulated and real caterpillar herbivory on the foliar metabolome of the wild plant Brassica nigra and monitored the herbivore-induced responses in relation to leaf ontogeny. Methods As single or multiple herbivory treatments, MeJA- and mock-sprayed plants were consecutively exposed to caterpillars or left untreated. Gas chromatography (GC) and liquid chromatography (LC) time-of-flight mass-spectrometry (TOF-MS) were combined to analyse foliar compounds, including central primary and specialized defensive plant metabolites. Results Plant responses were stronger in young leaves, which simultaneously induced higher chlorophyll levels. Both MeJA and caterpillar herbivory induced similar, but not identical, accumulation of tricarboxylic acids (TCAs), glucosinolates (GSLs) and phenylpropanoids (PPs), but only caterpillar feeding led to depletion of amino acids. MeJA followed by caterpillars caused higher induction of defence compounds, including a three-fold increase in the major defence compound allyl-GSL (sinigrin). When feeding on MeJA-treated plants, caterpillars gained less weight indicative of the reduced host-plant quality and enhanced resistance. Conclusions The metabolomics approach showed that plant responses induced by herbivory extend beyond the regulation of defence metabolism and are tightly modulated throughout leaf development. This leads to a new understanding of the plant metabolic potential that can be exploited for future plant protection strategies.

  • 10.
    Surowiec, Izabella
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Johansson, Erik
    Sartorius Stedim Data Analytics AB, Umeå, Sweden.
    Torell, Frida
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Idborg, Helena
    Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
    Gunnarsson, Iva
    Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
    Svenungsson, Elisabet
    Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
    Jakobsson, Per-Johan
    Rheumatology Unit, Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
    Trygg, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen. Sartorius Stedim Data Analytics AB, Umeå, Sweden.
    Multivariate strategy for the sample selection and integration of multi-batch data in metabolomics2017Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 13, nr 10, artikel-id 114Artikel i tidskrift (Refereegranskat)
    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.

  • 11.
    Torell, Frida
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Bennett, Kate
    AcureOmics AB, Umeå, Sweden.
    Cereghini, Silvia
    Paris, France.
    Rännar, Stefan
    AcureOmics AB, Umeå, Sweden.
    Lundstedt-Enkel, Katrin
    AcureOmics AB, Umeå, Sweden; Uppsala, Sweden.
    Moritz, Thomas
    AcureOmics AB, Umeå, Sweden.
    Haumaitre, Cecile
    Paris, France.
    Trygg, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Lundstedt, Torbjörn
    AcureOmics AB, Umeå, Sweden.
    Tissue sample stability: thawing effect on multi-organ samples2016Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 12, nr 2, artikel-id 19Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Correct handling of samples is essential in metabolomic studies. Improper handling and prolonged storage of samples has unwanted effects on the metabolite levels. The aim of this study was to identify the effects that thawing has on different organ samples. Organ samples from gut, kidney, liver, muscle and pancreas were analyzed for a number of endogenous metabolites in an untargeted metabolomics approach, using gas chromatography time of flight mass spectrometry at the Swedish Metabolomics Centre, Umeå University, Sweden. Multivariate data analysis was performed by means of principal component analysis and orthogonal projection to latent structures discriminant analysis. The results showed that the metabolic changes caused by thawing were almost identical for all organs. As expected, there was a marked increase in overall metabolite levels after thawing, caused by increased protein and cell degradation. Cholesterol was one of the eight metabolites found to be decreased in the thawed samples in all organ groups. The results also indicated that the muscles are less susceptible to oxidation compared to the rest of the organ samples.

  • 12.
    Torell, Frida
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen. Karlsruhe Institute of Technology, Karlsruhe, Germany.
    Bennett, Kate
    Rännar, Stefan
    Lundstedt-Enkel, Katrin
    Lundstedt, Torbjörn
    Trygg, Johan
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    The effects of thawing on the plasma metabolome: evaluating differences between thawed plasma and multi-organ samples2017Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 13, nr 6, artikel-id 66Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Introduction: Post-collection handling, storage and transportation can affect the quality of blood samples. Pre-analytical biases can easily be introduced and can jeopardize accurate profiling of the plasma metabolome. Consequently, a mouse study must be carefully planned in order to avoid any kind of bias that can be introduced, in order not to compromise the outcome of the study. The storage and shipment of the samples should be made in such a way that the freeze–thaw cycles are kept to a minimum. In order to keep the latent effects on the stability of the blood metabolome to a minimum it is essential to study the effect that the post-collection and pre-analytical error have on the metabolome. Objectives: The aim of this study was to investigate the effects of thawing on the metabolic profiles of different sample types. Methods: In the present study, a metabolomics approach was utilized to obtain a thawing profile of plasma samples obtained on three different days of experiment. The plasma samples were collected from the tail on day 1 and 3, while retro-orbital sampling was used on day 5. The samples were analysed using gas chromatography time-of-flight mass spectrometry (GC TOF-MS). Results: The thawed plasma samples were found to be characterized by higher levels of amino acids, fatty acids, glycerol metabolites and purine and pyrimidine metabolites as a result of protein degradation, cell degradation and increased phospholipase activity. The consensus profile was thereafter compared to the previously published study comparing thawing profiles of tissue samples from gut, kidney, liver, muscle and pancreas. Conclusions: The comparison between thawed organ samples and thawed plasma samples indicate that the organ samples are more sensitive to thawing, however thawing still affected all investigated sample types.

  • 13.
    Wu, Junfang
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen. Umeå universitet, Medicinska fakulteten, Institutionen för farmakologi och klinisk neurovetenskap, Klinisk neurovetenskap.
    Wuolikainen, Anna
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Trupp, Miles
    Umeå universitet, Medicinska fakulteten, Institutionen för farmakologi och klinisk neurovetenskap, Klinisk neurovetenskap.
    Jonsson, Pär
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Kemiska institutionen.
    Marklund, Stefan L.
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Klinisk kemi.
    Andersen, Peter M.
    Umeå universitet, Medicinska fakulteten, Institutionen för farmakologi och klinisk neurovetenskap, Klinisk neurovetenskap.
    Forsgren, Lars
    Umeå universitet, Medicinska fakulteten, Institutionen för farmakologi och klinisk neurovetenskap, Klinisk neurovetenskap.
    Öhman, Anders
    Umeå universitet, Medicinska fakulteten, Institutionen för farmakologi och klinisk neurovetenskap, Klinisk neurovetenskap.
    NMR analysis of the CSF and plasma metabolome of rigorously matched amyotrophic lateral sclerosis, Parkinson's disease and control subjects2016Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 12, nr 6, artikel-id 101Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Introduction: Amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) are two severe neurodegenerative disorders for which the disease mechanisms are poorly understood and reliable biomarkers are absent.

    Objectives: To identify metabolite biomarkers for ALS and PD, and to gain insights into which metabolic pathways are involved in disease.

    Methods: Nuclear magnetic resonance (NMR) metabolomics was utilized to characterize the metabolite profiles of cerebrospinal fluid (CSF) and plasma from individuals in three age, gender, and sampling-date matched groups, comprising 22 ALS, 22 PD and 28 control subjects.

    Results: Multivariate analysis of NMR data generated robust discriminatory models for separation of ALS from control subjects. ALS patients showed increased concentrations of several metabolites in both CSF and plasma, these are alanine (CSF fold change = 1.22, p = 0.005), creatine (CSF-fc = 1.17, p = 0.001), glucose (CSF-fc = 1.11, p = 0.036), isoleucine (CSF-fc = 1.24, p = 0.002), and valine (CSF-fc = 1.17, p = 0.014). Additional metabolites in CSF (creatinine, dimethylamine and lactic acid) and plasma (acetic acid, glutamic acid, histidine, leucine, pyruvate and tyrosine) were also important for this discrimination. Similarly, panels of CSF-metabolites that discriminate PD from ALS and control subjects were identified.

    Conclusions: The results for the ALS patients suggest an affected creatine/creatinine pathway and an altered branched chain amino acid (BCAA) metabolism, and suggest links to glucose and energy metabolism. Putative metabolic markers specific for ALS (e.g. creatinine and lactic acid) and PD (e.g. 3-hydroxyisovaleric acid and mannose) were identified, while several (e.g. creatine and BCAAs) were shared between ALS and PD, suggesting some overlap in metabolic alterations in these disorders.

  • 14. Zivkovic, AM
    et al.
    Yang, J
    Hegedus, C
    Nording, Malin
    Department of Entomology, University of California, Davis, CA, USA.
    O´Sullivan, A
    Hogg, RJ
    Weiss, RH
    Bay, C
    Hammock, BD
    Serum oxylipin profiles in IgA nephropathy patients reflect kidney functional alterations2012Ingår i: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 8, nr 6, s. 1102-1113Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Immunoglobulin A nephropathy (IgAN) is a leading cause of chronic kidney disease, frequently associated with hypertension and renal inflammation. ω-3 fatty acids eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) in fish oil (FO) improve kidney function in animal models, but have inconsistent metabolic effects in humans. Oxylipin profiles in serum from IgAN patients supplemented with either FO or corn oil (CO) placebo were analyzed by liquid chromatography coupled to tandem mass spectrometry. EPA cyclooxygenase and lipoxygenase metabolites, and EPA and DHA epoxides and diols were increased in response to FO supplementation, as were total epoxides and epoxide/diol ratios. Several of these metabolites were drivers of separation as assessed by multivariate analysis of FO patients pre- vs. post-supplementation, including 17,18-dihydroxyeicosatrienoic acid, prostaglandin D3, prostagalandin E3, Resolvin E1, 12-hydroxyeicosapentaenoic acid, and 10(11)-epoxydocosapentaenoic acid. In patients whose proteinuria improved, plasma total oxylipins as well as several hydroxyoctadecadienoic acids, hydroxyeicosatetraenoic acids, and leukotriene B4 metabolites were among the metabolites that were significantly lower than in patients whose proteinuria either did not improve or worsened. These data support the involvement of oxylipins in the inflammatory component of IgAN as well as the potential use of oxylipin profiles as biomarkers and for assessing responsiveness to ω-3 fatty acid supplementation in IgAN patients.

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