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- Forshed, Jenny, 1972-
(author)
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Processing and analysis of NMR data : Impurity determination and metabolic profiling
- 2005
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Doctoral thesis (other academic/artistic)abstract
- This thesis describes the use of nuclear magnetic resonance (NMR) spectrometry as an analytical tool. The theory of NMR spectroscopy in general and quantitative NMR spectrometry (qNMR) in particular is described and the instrumental properties and parameter setups for qNMR measurements are discussed. Examples of qNMR are presented by impurity determination of pharmaceutical compounds and analysis of urine samples from rats fed with either water or a drug (metabolic profiling). The instrumental parameter setup of qNMR and traditional data pre-treatments are examined. Spectral smoothing by convolution with a triangular function, which is an unusual application in this context, was shown to be successful regarding the sensitivity and robustness of the method in paper II. In addition, papers III and IV comprise the field of peak alignment, especially designed for 1H-NMR spectra of urine samples. This is an important preprocessing tool when multivariate analysis is to be applied. A novel peak alignment method was developed and compared to the traditional bucketing approach and a conceptually different alignment method.Univariate, multivariate, linear and nonlinear data analyses were applied to qNMR data. In papers I–II, calibration models were created to examine the potential of qNMR for these applications. The data analysis in papers III–VI was mainly explorative. The potential of data fusion and data correlation was examined in order to increase the possibilities of analysing the highly complex samples from metabolic profiling (papers V–VI). Data from LC/MS analysis of the same samples were used with the 1H-NMR data in different ways. Correlation analyses between the 1H-NMR data and the drug metabolites identified from the LC/MS data were also performed. In this process, data fusion proved to be a valuable tool.
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| 2. |
- Zheng, Ju-Sheng, et al.
(author)
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Association between plasma phospholipid saturated fatty acids and metabolic markers of lipid, hepatic, inflammation and glycaemic pathways in eight European countries : a cross-sectional analysis in the EPIC-InterAct study
- 2017
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In: BMC Medicine. - : BioMed Central. - 1741-7015. ; 15
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Journal article (peer-reviewed)abstract
- Background: Accumulating evidence suggests that individual circulating saturated fatty acids (SFAs) are heterogeneous in their associations with cardio-metabolic diseases, but evidence about associations of SFAs with metabolic markers of different pathogenic pathways is limited. We aimed to examine the associations between plasma phospholipid SFAs and the metabolic markers of lipid, hepatic, glycaemic and inflammation pathways. Methods: We measured nine individual plasma phospholipid SFAs and derived three SFA groups (odd-chain: C15:0 + C17:0, even-chain: C14:0 + C16:0 + C18:0, and very-long-chain: C20:0 + C22:0 + C23:0 + C24:0) in individuals from the subcohort of the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study across eight European countries. Using linear regression in 15,919 subcohort members, adjusted for potential confounders and corrected for multiple testing, we examined cross-sectional associations of SFAs with 13 metabolic markers. Multiplicative interactions of the three SFA groups with pre-specified factors, including body mass index (BMI) and alcohol consumption, were tested. Results: Higher levels of odd-chain SFA group were associated with lower levels of major lipids (total cholesterol (TC), triglycerides, apolipoprotein A-1 (ApoA1), apolipoprotein B (ApoB)) and hepatic markers (alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyl transferase (GGT)). Higher even-chain SFA group levels were associated with higher levels of low-density lipoprotein cholesterol (LDL-C), TC/high-density lipoprotein cholesterol (HDL-C) ratio, triglycerides, ApoB, ApoB/A1 ratio, ALT, AST, GGT and CRP, and lower levels of HDL-C and ApoA1. Very-long-chain SFA group levels showed inverse associations with triglycerides, ApoA1 and GGT, and positive associations with TC, LDL-C, TC/HDL-C, ApoB and ApoB/A1. Associations were generally stronger at higher levels of BMI or alcohol consumption. Conclusions: Subtypes of SFAs are associated in a differential way with metabolic markers of lipid metabolism, liver function and chronic inflammation, suggesting that odd-chain SFAs are associated with lower metabolic risk and even-chain SFAs with adverse metabolic risk, whereas mixed findings were obtained for very-long-chain SFAs. The clinical and biochemical implications of these findings may vary by adiposity and alcohol intake.
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