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  • 1.
    Chorell, Elin
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Mapping the consequenses of physical exercise and nutrition on human health: A predictive metabolomics approach2011Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Human health is a complex and wide-ranging subject far beyond nutrition and physical exercise. Still, these factors have a huge impact on global health by their ability to prevent diseases and thus promote health. Thus, to identify health risks and benefits, it is necessary to reveal the underlying mechanisms of nutrition and exercise, which in many cases follows a complex chain of events. As a consequence, current health research is generating massive amounts of data from anthropometric parameters, genes, proteins, small molecules (metabolites) et cetera, with the intent to understand these mechanisms. For the study of health responses, especially related to physical exercise and nutrition, alterations in small molecules (metabolites) are in most cases immediate and located close to the phenotypic level and could therefore provide early signs of metabolic imbalances. Since there are roughly as many different responses to exercise and nutrients as there are humans, this quest is highly multifaceted and will benefit from an interpretation of treatment effects on a general as well as on an individual level. This thesis involves the application of chemometric methods to the study of global metabolic reactions, i.e. metabolomics, in a strategy coined predictive metabolomics. Via the application of predictive metabolomics an extensive hypothesis-free biological interpretation has been carried out of metabolite patterns in blood, acquired using gas chromatography-mass spectrometry (GC-MS), related to physical exercise, nutrition and diet, all in the context of human health. In addition, the chemometrics methodology have computational benefits concerning the extraction of relevant information from information-rich data as well as for interpreting general treatment effects and individual responses, as exemplified throughout this work. Health concerns all lifestages, thus this thesis presents a strategic framework in combination with comprehensive interpretations of metabolite patterns throughout life. This includes a broad range of human studies revealing metabolic patterns related to the impact of physical exercise, macronutrient modulation and different fitness status in young healthy males, short and long term dietary treatments in overweight post menopausal women as well as metabolic responses related to probiotics treatment and early development in infants. As a result, the studies included in the thesis have revealed metabolic patterns potentially indicative of an anti-catabolic response to macronutrients in the early recovery phase following exercise. Moreover, moderate differences in the metabolome associated with cardiorespiratory fitness level were detected, which could be linked to variation in the inflammatory and antioxidaive defense system. This work also highlighted mechanistic information that could be connected to dietary related weight loss in overweight and obese postmenopausal women in relation to short as well as long term dietary effects based on different macronutrient compositions. Finally, alterations were observed in metabolic profiles in relation to probiotics treatment in the second half of infancy, suggesting possible health benefits of probiotics supplementation at an early age.

     

  • 2.
    Chorell, Elin
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Karlsson, Frida
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    West, Christina
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Hernell, Olle
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    The impact of feeding Lactobacillus F19 during weaning: a study of the plasma metabolomeManuscript (preprint) (Other academic)
  • 3.
    Chorell, Elin
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Moritz, Thomas
    Branth, Stefan
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Svensson, Michael
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Sports Medicine.
    A predictive metabolomics evaluation of nutrition-modulated metabolic stress responses in human blood serum during the early recovery phase of strenuous physical exercise2009In: Journal of Proteome Research, ISSN 1535-3893, E-ISSN 1535-3907, Vol. 8, no 6, 2966-77 p.Article in journal (Refereed)
    Abstract [en]

    We have investigated whether postexercise ingestion of carbohydrates in combination with proteins generates a different systemic metabolic response, as compared to the sole ingestion of carbohydrate or water, in the early recovery phase following exercise. In addition, metabolic patterns related to fitness level were studied together with individual responses to nutritional modulation. Twenty-four male subjects were exposed to 90 min of ergometer-cycling. Each participant was subject to four identical test-sessions, including ingestion of one of four beverages (water, low-carbohydrate beverage, high-carbohydrate beverage, and low-carbohydrate−protein beverage (LCHO-P)) immediately after cycling. Blood was collected at six time points, one pre- and five postexercise. Extracted blood serum was subject to metabolomic characterization by gas chromatography/time-of-flight mass spectrometry (GC−TOF MS). Data was processed using hierarchical multivariate curve resolution (HMCR), and multivariate statistical analysis was carried out using orthogonal partial least-squares (OPLS). Predictive metabolomics, including predictive HMCR and OPLS classification, was applied to ensure efficient sample processing and validation of detected metabolic patterns. Separation of subjects in relation to ingested beverage was detected and interpreted. Pseudouridine was suggested as a novel marker for pro-anabolic effect following LCHO-P ingestion, which was supported by the detected decrease of the catabolic marker 3-methylhistidine. Separation of subjects according to fitness level was achieved, and nutritional modulation by LCHO-P was shown to improve the metabolic status of less fit subjects in the recovery phase. In addition, the potential of the methodology for detection of early signs of insulin resistance was also demonstrated.

  • 4.
    Chorell, Elin
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine. Norrlands University Hospital, Umeå University, Umeå, Sweden .
    Ryberg, Mats
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Larsson, Christel
    Department of Food and Nutrition and Sport Science, University of Gothenburg, Gothenburg, Sweden.
    Sandberg, Susanne
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Mellberg, Caroline
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Lindahl, Bernt
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Olsson, Tommy
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Plasma metabolomic response to postmenopausal weight loss induced by different diets2016In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 12, no 5, 85Article in journal (Refereed)
    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.

  • 5.
    Chorell, Elin
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Rydberg, Mats
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Larsson, Christel
    Umeå University, Faculty of Social Sciences, Department of Food and Nutrition.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Olsson, Tommy
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    A metabolomic evaluation of short and long term effects of different macronutrient intake in overweight and obese postmenopausal womenManuscript (preprint) (Other academic)
  • 6.
    Chorell, Elin
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Svensson, Michael
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Sports Medicine.
    Moritz, Thomas
    Swedish University of Agricultural Sciences.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Physical fitness level is reflected by alterations in the human plasma metabolome2012In: Molecular BioSystems, ISSN 1742-206X, Vol. 8, no 4, 1187-1196 p.Article in journal (Refereed)
    Abstract [en]

    An excessive energy intake combined with a low level of physical activity induces detrimental processes involved in disease development, e.g. type 2 diabetes and cardiovascular disease. However the underlying mechanisms for regulation of metabolic capacity and fitness status remain unclear. Metabolomics involves global studies of the metabolic reactions in an organism or cell. Thus hypotheses regarding biochemical events can be generated to increase the understanding of disease development and thereby aid in the development of novel treatments or preventions. We present the first standardized intervention study focusing on characterizing the human metabolome in relation to moderate differences in cardiorespiratory fitness. Gas chromatography-time of flight/mass spectrometry (GC-TOF/MS) was used to characterize 460 plasma samples from 27 individuals divided into two groups based on physical fitness level (VO2max). Multi- and univariate between group comparisons based on 197 metabolites were carried out in samples collected at rest prior to any intervention, over time following a nutritional load or a standardized exercise scheme, with and without nutritional load. We detected decreased levels of gamma-tocopherol (GT), a vitamin E isomer, in response to a high fitness level, whereas the opposite was seen for the alpha isomer (AT). In addition, the high fitness level was associated with elevated ω3-PUFA (DHA, 22:6ω3) and a decrease in ω6-PUFA (18:2ω6) as well as in saturated (16:0, 18:0), monounsaturated (18:1) and trans (16:1) fatty acids. We thus hypothesize that high fitness status induces an increased cardiorespiratory inflammatory and antioxidant defense system, more prone to deal with the inflammatory response following exercise and nutrition intake.

  • 7.
    Chorell, Elin
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Thysell, Elin
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Jonsson, Pär
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Eklund, Caroline
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences.
    Silfver, Anders
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences.
    Carlsson, Inga-Britt
    Umeå University, Faculty of Science and Technology, Umeå Plant Science Centre (UPSC).
    Lundgren, Krister
    Umeå University, Faculty of Science and Technology, Umeå Plant Science Centre (UPSC).
    Moritz, Thomas
    Umeå University, Faculty of Science and Technology, Umeå Plant Science Centre (UPSC).
    Svensson, Michael
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Sports Medicine.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    A Multivariate Screening Strategy for Investigating Metabolic Effects of Strenuous Physical Exercise in Human Serum2007In: Journal of Proteome Research, ISSN 1535-3893, Vol. 6, no 6, 2113-2120 p.Article in journal (Refereed)
    Abstract [en]

    A novel hypothesis-free multivariate screening methodology for the study of human exercise metabolism in blood serum is presented. Serum gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) data was processed using hierarchical multivariate curve resolution (H-MCR), and orthogonal partial least-squares discriminant analysis (OPLS-DA) was used to model the systematic variation related to the acute effect of strenuous exercise. Potential metabolic biomarkers were identified using data base comparisons. Extensive validation was carried out including predictive H-MCR, 7-fold full cross-validation, and predictions for the OPLS-DA model, variable permutation for highlighting interesting metabolites, and pairwise t tests for examining the significance of metabolites. The concentration changes of potential biomarkers were verified in the raw GC/TOFMS data. In total, 420 potential metabolites were resolved in the serum samples. On the basis of the relative concentrations of the 420 resolved metabolites, a valid multivariate model for the difference between pre- and post-exercise subjects was obtained. A total of 34 metabolites were highlighted as potential biomarkers, all statistically significant (p < 8.1E-05). As an example, two potential markers were identified as glycerol and asparagine. The concentration changes for these two metabolites were also verified in the raw GC/TOFMS data.The strategy was shown to facilitate interpretation and validation of metabolic interactions in human serum as well as revealing the identity of potential markers for known or novel mechanisms of human exercise physiology. The multivariate way of addressing metabolism studies can help to increase the understanding of the integrative biology behind, as well as unravel new mechanistic explanations in relation to, exercise physiology.

  • 8.
    Chorell, Elin
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Thysell, Elin
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Lindberg, Johan
    Schuppe-Koistinen, Ina
    Moritz, Thomas
    Jonsson, Pär
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Statistical multivariate metabolite profiling for aiding biomarker pattern detection and mechanistic interpretations in GC/MS based metabolomics2006In: Metabolomics, Vol. 2, no 4, 257-68 p.Article in journal (Refereed)
    Abstract [en]

    A strategy for robust and reliable mechanistic statistical modelling of metabolic responses in relation to drug induced toxicity is presented. The suggested approach addresses two cases commonly occurring within metabonomic toxicology studies, namely; 1) A pre-defined hypothesis about the biological mechanism exists and 2) No such hypothesis exists. GC/MS data from a liver toxicity study consisting of rat urine from control rats and rats exposed to a proprietary AstraZeneca compound were resolved by means of hierarchical multivariate curve resolution (H-MCR) generating 287 resolved chromatographic profiles with corresponding mass spectra. Filtering according to significance in relation to drug exposure rendered in 210 compound profiles, which were subjected to further statistical analysis following correction to account for the control variation over time. These dose related metabolite traces were then used as new observations in the subsequent analyses. For case 1, a multivariate approach, named Target Batch Analysis, based on OPLS regression was applied to correlate all metabolite traces to one or more key metabolites involved in the pre-defined hypothesis. For case 2, principal component analysis (PCA) was combined with hierarchical cluster analysis (HCA) to create a robust and interpretable framework for unbiased mechanistic screening. Both the Target Batch Analysis and the unbiased approach were cross-verified using the other method to ensure that the results did match in terms of detected metabolite traces. This was also the case, implying that this is a working concept for clustering of metabolites in relation to their toxicity induced dynamic profiles regardless if there is a pre-existing hypothesis or not. For each of the methods the detected metabolites were subjected to identification by means of data base comparison as well as verification in the raw data. The proposed strategy should be seen as a general approach for facilitating mechanistic modelling and interpretations in metabolomic studies.

  • 9.
    Chorell, Elin
    et al.
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Videhult, Frida Karlsson
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Hernell, Olle
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    West, Christina E
    Umeå University, Faculty of Medicine, Department of Clinical Sciences, Paediatrics.
    Impact of probiotic feeding during weaning on the serum lipid profile and plasma metabolome in infants2013In: British Journal of Nutrition, ISSN 0007-1145, E-ISSN 1475-2662, Vol. 110, no 1, 116-126 p.Article in journal (Refereed)
    Abstract [en]

    The gut microbiome interacts with the host in the metabolic response to diet, and early microbial aberrancies may be linked to the development of obesity and metabolic disorders later in life. Probiotics have been proposed to affect metabolic programming and blood lipid levels, although studies are lacking in infants. Here, we report on the lipid profile and global metabolic response following daily feeding of probiotics during weaning. A total of 179 healthy, term infants were randomised to daily intake of cereals with (n 89) or without (n 90) the addition of Lactobacillus paracasei ssp. paracasei F19 (LF19) 108 colony-forming units per serving from 4 to 13 months of age. Weight, length and skinfold thickness were monitored. Venous blood was drawn at 5·5 and 13 months of age for analysis of the serum lipid profile. In a subsample, randomly selected from each group, GC-time-of-flight/MS was used to metabolically characterise plasma samples from thirty-seven infants. A combination of multi- and univariate analysis was applied to reveal differences related to LF19 treatment based on 228 putative metabolites, of which ninety-nine were identified or classified. We observed no effects of probiotic feeding on anthropometrics or the serum lipid profile. However, we detected significantly lower levels of palmitoleic acid (16 : 1) (P < 0·05) and significantly higher levels of putrescine (P < 0·01) in LF19-treated infants. Palmitoleic acid is a major MUFA strongly linked to visceral obesity, while putrescine is a polyamine with importance for gut integrity. Whether the observed differences will have long-term health consequences are being followed.

  • 10.
    Chorell, Erik
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Chorell, Elin
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Efficient Synthesis of 2-Substituted Phthalimides from Phthalic Acids in One Step2013In: European Journal of Organic Chemistry, ISSN 1434-193X, E-ISSN 1099-0690, Vol. 2013, no 33, 7512-7516 p.Article in journal (Refereed)
    Abstract [en]

    Efficient procedures for synthesizing 2-substituted phthalimide (isoindole-1,3-dione) analogues starting from phthalic acids have been developed by using experimental design. The phthalimide central fragment frequently appears in biologically active compounds, materials, catalysts, and fluorescent probes, and therefore the development of general, fast, and convenient synthetic methods to this scaffold under neutral, acidic, and basic conditions would be attractive. After an initial screening, the use of acetonitrile, acetic acid, or pyridine in combination with microwave heating proved most promising. Experimental design was applied to these conditions to optimize the time, temperature, and concentration. This strategy has successfully generated synthetic methods that have been used to synthesize a series of phthalimides from phthalic acids and various amines or anilines in excellent yields. The developed methods have proven to be general, fast, convenient, and economic, and thus are expected to have broad utility to efficiently construct novel compounds for future biological and chemical applications.

  • 11. Dugas, Lara R.
    et al.
    Chorell, Elin
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Plange-Rhule, Jacob
    Lambert, Estelle V.
    Cao, Guichan
    Cooper, Richard S.
    Layden, Brian T.
    Scholten, Denise
    Olsson, Tommy
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Luke, Amy
    Goedecke, Julia H.
    Obesity-related metabolite profiles of black women spanning the epidemiologic transition2016In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 12, no 3, 45Article in journal (Refereed)
    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.

  • 12. Goedecke, J H
    et al.
    Chorell, Elin
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Livingstone, D E W
    Stimson, R H
    Hayes, P
    Adams, K
    Dave, J A
    Victor, H
    Levitt, N S
    Kahn, S E
    Seckl, J R
    Walker, B R
    Olsson, Tommy
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Glucocorticoid receptor gene expression in adipose tissue and associated metabolic risk in black and white South African women2015In: International Journal of Obesity, ISSN 0307-0565, E-ISSN 1476-5497, Vol. 39, no 2, 303-311 p.Article in journal (Refereed)
    Abstract [en]

    Background: Black women have lower visceral adipose tissue (VAT) but are less insulin sensitive than white women; the mechanisms responsible are unknown.

    Objective: The study aimed to test the hypothesis that variation in subcutaneous adipose tissue (SAT) sensitivity to glucocorticoids might underlie these differences.

    Methods: Body fatness (dual energy X-ray absorptiometry) and distribution (computerized tomography), insulin sensitivity (SI, intravenous and oral glucose tolerance tests), and expression of 11β-hydroxysteroid dehydrogenase-1 (11HSD1), hexose-6-phosphate dehydrogenase and glucocorticoid receptor-α (GRα), as well as genes involved in adipogenesis and inflammation were measured in abdominal deep SAT, superficial SAT and gluteal SAT (GLUT) depots of 56 normal-weight or obese black and white premenopausal South African (SA) women. We used a combination of univariate and multivariate statistics to evaluate ethnic-specific patterns in adipose gene expression and related body composition and insulin sensitivity measures.

    Results: Although 11HSD1 activity and mRNA did not differ by ethnicity, GRα mRNA levels were significantly lower in SAT of black compared with white women, particularly in the GLUT depot (0.52±0.21 vs 0.91±0.26 AU, respectively, P<0.01). In black women, lower SAT GRα mRNA levels were associated with increased inflammatory gene transcript levels and abdominal SAT area, and reduced adipogenic gene transcript levels, VAT/SAT ratio and SI. Abdominal SAT 11HSD1 activity associated with increased VAT area and decreased SI in white, but not in black women.

    Conclusions: In black SA women, downregulation of GRα mRNA levels with obesity and reduced insulin sensitivity, possibly via increased SAT inflammation, is associated with reduced VAT accumulation.

  • 13.
    Jonsson, Pär
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Wuolikainen, Anna
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Thysell, Elin
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Chorell, Elin
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Stattin, Pär
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Urology and Andrology.
    Wikström, Pernilla
    Umeå University, Faculty of Medicine, Department of Medical Biosciences, Pathology.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Constrained randomization and multivariate effect projections improve information extraction and biomarker pattern discovery in metabolomics studies involving dependent samples2015In: Metabolomics, ISSN 1573-3882, E-ISSN 1573-3890, Vol. 11, no 6, 1667-1678 p.Article in journal (Refereed)
    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.

  • 14.
    Kindahl, Tomas
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Chorell, Elin
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Chorell, Erik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Development and optimization of simple one-step methods for the synthesis of 4-amino-substituted 1,8-naphthalimides2014In: European Journal of Organic Chemistry, ISSN 1434-193X, E-ISSN 1099-0690, no 28, 6175-6182 p.Article in journal (Refereed)
    Abstract [en]

    The 1,8-naphthalimide central fragment can be found in a vast number of bioactive compounds and drugs in clinical trials, and can be recognized from their use as fluorescent probes. Of key importance for the fluorescent properties of the scaffold is the 4-amino substituent, which has also proven to be critical in several other chemical and biological applications. Because of the great interest in 1,8-naphthalimides in general, and 4-amino-substituted 1,8-naphthalimides in particular, we have developed and optimized one-step procedures with which to access these derivatives by using an experimental design approach. The multivariate studies of temperature, reaction time, and equivalents of substrates identified conditions with close to quantitative yields that could be applied to generate a range of 4-amino-substituted 1,8-naphthalimides in high yields.

  • 15.
    Thysell, Elin
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Chorell, Elin
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Svensson, Michael B
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Sports Medicine.
    Jonsson, Pär
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Validated and Predictive Processing of Gas Chromatography-Mass Spectrometry Based Metabolomics Data for Large Scale Screening Studies, Diagnostics and Metabolite Pattern Verification2012In: Metabolites, ISSN 2218-1989, Vol. 2, 796-817 p.Article in journal (Refereed)
    Abstract [en]

    The suggested approach makes it feasible to screen large metabolomics data, sample sets with retained data quality or to retrieve significant metabolic information from small sample sets that can be verified over multiple studies. Hierarchical multivariate curve resolution (H-MCR), followed by orthogonal partial least squares discriminant analysis (OPLS-DA) was used for processing and classification of gas chromatography/time of flight mass spectrometry (GC/TOFMS) data characterizing human serum samples collected in a study of strenuous physical exercise. The efficiency of predictive H-MCR processing of representative sample subsets, selected by chemometric approaches, for generating high quality data was proven. Extensive model validation by means of cross-validation and external predictions verified the robustness of the extracted metabolite patterns in the data. Comparisons of extracted metabolite patterns between models emphasized the reliability of the methodology in a biological information context. Furthermore, the high predictive power in longitudinal data provided proof for the potential use in clinical diagnosis. Finally, the predictive metabolite pattern was interpreted physiologically, highlighting the biological relevance of the diagnostic pattern. The suggested approach makes it feasible to screen large metabolomics data, sample sets with retained data quality or to retrieve significant metabolic information from small sample sets that can be verified over multiple studies. Hierarchical multivariate curve resolution (H-MCR), followed by orthogonal partial least squares discriminant analysis (OPLS-DA) was used for processing and classification of gas chromatography/time of flight mass spectrometry (GC/TOFMS) data characterizing human serum samples collected in a study of strenuous physical exercise. The efficiency of predictive H-MCR processing of representative sample subsets, selected by chemometric approaches, for generating high quality data was proven. Extensive model validation by means of cross-validation and external predictions verified the robustness of the extracted metabolite patterns in the data. Comparisons of extracted metabolite patterns between models emphasized the reliability of the methodology in a biological information context. Furthermore, the high predictive power in longitudinal data provided proof for the potential use in clinical diagnosis. Finally, the predictive metabolite pattern was interpreted physiologically, highlighting the biological relevance of the diagnostic pattern.

  • 16.
    Thysell, Elin
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Chorell, Elin
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Svensson, Michael B.
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Sports Medicine.
    Moritz, Thomas
    Jonsson, Pär
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Processing of mass spectrometry based metabolomics data for large scale screening studies and diagnosticsManuscript (preprint) (Other academic)
    Abstract [en]

    In mass spectrometry based metabolomics predictive data processing and sample classification based on representative sample subsets makes it possible to screen large sample banks or data sets in an efficient fashion regarding both data quality and processing time. This is a requirement for making use of high sensitivity and complexity metabolite data and to turn the metabolomics field into a competitive omics platform for biological interpretation and diagnostics. Predictive metabolomics by means of hierarchical multivariate curve resolution (H-MCR) followed by orthogonal partial least squares discriminant analysis (OPLS-DA) was used for the processing and classification of gas chromatography/time of flight mass spectrometry (GC/TOFMS) data characterizing human blood serum samples collected in a study of strenuous physical exercise. The efficiency of the predictive processing as a high throughput tool for generating high quality data is clearly proven and stated as a main benefit of the method. Extensive model validation schemes by means of cross validation and external predictions verified the robustness of the extracted systematic patterns in the data. Comparisons regarding the extracted metabolite patterns between models emphasized the reliability of the methodology in a biological information context. Furthermore, the high predictive power concerning longitudinal predictions provided proof for the diagnostic potential of the methodology. Finally, the predictive metabolite pattern was interpreted physiologically as well as verified in the literature, highlighting the biological relevance of the diagnostic pattern. The suggested approach makes it feasible to screen large data or sample sets with retained data quality and interpretation and to do this in a high throughput fashion. The method could be of value for sample bank mining, metabolome-wide association studies, verification of marker patterns and development of diagnostic systems.

  • 17.
    Thysell, Elin
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Chorell, Elin
    Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Medicine.
    Svensson, Michael
    Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences, Sports Medicine.
    Jonsson, Pär
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Validated and predictive processing of gas chromatography-mass spectra screening studies, diagnostics and metabolite pattern verification2012In: Metabolites, ISSN 2218-1989, E-ISSN 2218-1989, Vol. 2, no 4, 796-817 p.Article in journal (Refereed)
    Abstract [en]

    The suggested approach makes it feasible to screen large metabolomics data, sample sets with retained data quality or to retrieve significant metabolic information from small sample sets that can be verified over multiple studies. Hierarchical multivariate curve resolution (H-MCR), followed by orthogonal partial least squares discriminant analysis (OPLS-DA) was used for processing and classification of gas chromatography/time of flight mass spectrometry (GC/TOFMS) data characterizing human serum samples collected in a study of strenuous physical exercise. The efficiency of predictive H-MCR processing of representative sample subsets, selected by chemometric approaches, for generating high quality data was proven. Extensive model validation by means of cross-validation and external predictions verified the robustness of the extracted metabolite patterns in the data. Comparisons of extracted metabolite patterns between models emphasized the reliability of the methodology in a biological information context. Furthermore, the high predictive power in longitudinal data provided proof for the potential use in clinical diagnosis. Finally, the predictive metabolite pattern was interpreted physiologically, highlighting the biological relevance of the diagnostic pattern.

  • 18.
    Thysell, Elin
    et al.
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Pohjanen, Elin
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Lindberg, Johan
    Schuppe-Koistinen, Ina
    Moritz, Thomas
    Jonsson, Pär
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Antti, Henrik
    Umeå University, Faculty of Science and Technology, Department of Chemistry.
    Reliable Profile Detection in Comparative Metabolomics2007In: Omics, ISSN 1536-2310, E-ISSN 1557-8100, Vol. 11, no 2, 209-224 p.Article in journal (Refereed)
    Abstract [en]

    A strategy for processing of metabolomic GC/MS data is presented. By considering the relationship between quantity and quality of detected profiles, representative data suitable for multiple sample comparisons and metabolite identification was generated. Design of experiments (DOE) and multivariate analysis was used to relate the changes in settings of the hierarchical multivariate curve resolution (H-MCR) method to quantitative and qualitative characteristics of the output data. These characteristics included number of resolved profiles, chromatographic quality in terms of reproducibility between analytical replicates, and spectral quality defined by purity and number of spectra containing structural information. The strategy was exemplified in two datasets: one containing 119 common metabolites, 18 of which were varied according to a DOE protocol; and one consisting of rat urine samples from control rats and rats exposed to a liver toxin. It was shown that the performance of the data processing could be optimized to produce metabolite data of high quality that allowed reliable sample comparisons and metabolite identification. This is a general approach applicable to any type of data processing where the important processing parameters are known and relevant output data characteristics can be defined. The results imply that this type of data quality optimization should be carried out as an integral step of data processing to ensure high quality data for further modeling and biological evaluation. Within metabolomics, this degree of optimization will be of high importance to generate models and extract biomarkers or biomarker patterns of biological or clinical relevance.

1 - 18 of 18
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