| 1. |
- Jonsson, Pär, et al.
(författare)
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Predictive metabolite profiling applying hierarchical multivariate curve resolution to GC-MS data : a potential tool for multi-parametric diagnosis
- 2006
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Ingår i: Journal of Proteome Research. - : American Chemical Society. - 1535-3893 .- 1535-3907. ; 5:6, s. 1407-1414
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Tidskriftsartikel (refereegranskat)abstract
- A method for predictive metabolite profiling based on resolution of GC-MS data followed by multivariate data analysis is presented and applied to three different biofluid data sets (rat urine, aspen leaf extracts, and human blood plasma). Hierarchical multivariate curve resolution (H-MCR) was used to simultaneously resolve the GC-MS data into pure profiles, describing the relative metabolite concentrations between samples, for multivariate analysis. Here, we present an extension of the H-MCR method allowing treatment of independent samples according to processing parameters estimated from a set of training samples. Predictions or inclusion of the new samples, based on their metabolite profiles, into an existing model could then be carried out, which is a requirement for a working application within, e.g., clinical diagnosis. Apart from allowing treatment and prediction of independent samples the proposed method also reduces the time for the curve resolution process since only a subset of representative samples have to be processed while the remaining samples can be treated according to the obtained processing parameters. The time required for resolving the 30 training samples in the rat urine example was approximately 13 h, while the treatment of the 30 test samples according to the training parameters required only approximately 30 s per sample (approximately 15 min in total). In addition, the presented results show that the suggested approach works for describing metabolic changes in different biofluids, indicating that this is a general approach for high-throughput predictive metabolite profiling, which could have important applications in areas such as plant functional genomics, drug toxicity, treatment efficacy and early disease diagnosis.
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| 2. |
- Wuolikainen, Anna, 1980-
(författare)
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Metabolomics studies of ALS : a multivariate search for clues about a devastating disease
- 2009
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Amyotrophic lateral sclerosis (ALS), also known as Charcot’s disease, motor neuron disease (MND) and Lou Gehrig’s disease, is a deadly, adult-onset neurodegenerative disorder characterized by progressive loss of upper and lower motor neurons, resulting in evolving paresis of the linked muscles. ALS is defined by classical features of the disease, but may present as a wide spectrum of phenotypes. About 10% of all ALS cases have been reported as familial, of which about 20% have been associated with mutations in the gene encoding for CuZn superoxide dismutase (SOD1). The remaining cases are regarded as sporadic. Research has advanced our understanding of the disease, but the cause is still unknown, no reliable diagnostic test exists, no cure has been found and the current therapies are unsatisfactory. Riluzole (Rilutek®) is the only registered drug for the treatment of ALS. The drug has shown only a modest effect in prolonging life and the mechanism of action of riluzole is not yet fully understood. ALS is diagnosed by excluding diseases with similar symptoms. At an early stage, there are numerous possible diseases that may present with similar symptoms, thereby making the diagnostic procedure cumbersome, extensive and time consuming with a significant risk of misdiagnosis. Biomarkers that can be developed into diagnostic test of ALS are therefore needed. The high number of unsuccessful attempts at finding a single diseasespecific marker, in combination with the complexity of the disease, indicates that a pattern of several markers is perhaps more likely to provide a diagnostic signature for ALS. Metabolomics, in combination with chemometrics, can be a useful tool with which to study human disease. Metabolomics can screen for small molecules in biofluids such as cerebrospinal fluid (CSF) and chemometrics can provide structure and tools in order to handle the types of data generated from metabolomics. In this thesis, ALS has been studied using a combination of metabolomics and chemometrics. Collection and storage of CSF in relation to metabolite stability have been extensively evaluated. Protocols for metabolomics on CSF samples have been proposed, used and evaluated. In addition, a new feature of data processing allowing new samples to be predicted into existing models has been tested, evaluated and used for metabolomics on blood and CSF. A panel of potential biomarkers has been generated for ALS and subtypes of ALS. An overall decrease in metabolite concentration was found for subjects with ALS compared to their matched controls. Glutamic acid was one of the metabolites found to be decreased in patients with ALS. A larger metabolic heterogeneity was detected among SALS cases compared to FALS. This was also reflected in models of SALS and FALS against their respective matched controls, where no significant difference from control was found for SALS while the FALS samples significantly differed from their matched controls. Significant deviating metabolic patterns were also found between ALS subjects carrying different mutations in the gene encoding SOD1.
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| 3. |
- Wuolikainen, Anna, 1980-, et al.
(författare)
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Optimization of procedures for collecting and storing of CSF for studying the metabolome in ALS
- 2009
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Ingår i: Amyotrophic Lateral Sclerosis. - : Informa UK Limited. - 1748-2968 .- 1471-180X. ; 10:4, s. 229-236
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Tidskriftsartikel (refereegranskat)abstract
- There is a need for biomarkers for early diagnosis, development and evaluation of treatment efficacy in amyotrophic lateral sclerosis (ALS). We aimed to investigate if pre-analytical factors induce artefacts in metabolomic data of cerebrospinal fluid (CSF) from patients with ALS. CSF from 16 patients was studied using a statistical experimental design protocol with the following parameters: storage temperature (-80 degrees C/ - 20 degrees C), type of collection tube (polypropylene/polystyrene), and time delay from collecting to freezing (0, 10, 30, 90, 150 min). Gas chromatography-mass spectrometry was used to analyse CSF from 12 of the patients while CSF from one patient was analysed with nuclear magnetic resonance spectroscopy. The extent of CO(2) evaporization from CSF collected in tubes of different sizes at different temperatures and with/without lid were studied in three addtional patients. We found that alterations in storage temperature affect the metabolite composition of CSF more than any other studied pre-analytical parameter. CO(2) evaporization may induce artefacts in the metabolome by increasing the pH. In conclusion, minimization of evaluated artefacts can be obtained by collecting the CSF directly into tubes with tightly sealed lids in N(2)(l) and after freezing transfer of the tubes to -80 degrees C to minimize evaporation of CO(2).
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