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Background:Polycystic ovary syndrome (PCOS) is a common reproductive disorder associated with metabolic disturbances including obesity, insulin resistance and diabetes mellitus. Here we investigate whether changes in the metabolic profile of PCOS women are driven by increased tendency to obesity or are specific features of PCOS related to increased testosterone levels.Design and methods:We conducted an NMR metabolomics association study of PCOS cases (n=145) and controls (n=687) nested in a population-based birth cohort (n=3127). Subjects were 31 years old at examination. The main analyses were adjusted for waist circumference (WC) as a proxy measure of central obesity. Subsequently, metabolite concentrations were compared between cases and controls within pre-defined WC strata. In each stratum, additional metabolomics association analyses with testosterone levels were conducted separately among cases and controls.Results:Overall, women with PCOS showed more adverse metabolite profiles than the controls. Four lipid fractions in different subclasses of very low density lipoprotein (VLDL) were associated with PCOS, after adjusting for WC and correction for multiple testing (P<0.002). In stratified analysis the PCOS women within large WC strata (⩾98 cm) had significantly lower high density lipoprotein (HDL) levels, Apo A1 and albumin values compared with the controls. Testosterone levels were significantly associated with VLDL and serum lipids in PCOS cases with large WC but not in the controls. The higher testosterone levels, adjusted for WC, associated adversely with insulin levels and HOMA IR in cases but not in the controls.Conclusions:Our findings show that both abdominal obesity and hyperandrogenism contribute to the dyslipidaemia and other metabolic traits of PCOS which all may negatively contribute to the long-term health of women with PCOS.

Understanding relationships between the structure and composition of molecular mixtures and their chemical properties is a main industrial aim. One central field of research is oil chemistry where the key question is how the molecular characteristics of composite hydrocarbon mixtures can be associated with the macroscopic properties of the oil products. Apparently these relationships are complex and often nonlinear and therefore call for advanced spectroscopic techniques. An informative and an increasingly used approach is two-dimensional nuclear magnetic resonance (2D NMR) spectroscopy. In the case of composite hydrocarbons the application of 2D NMR methodologies in a quantitative manner pose many technical difficulties, and, in any case, the resulting spectra contain many overlapping resonances that challenge the analytical work. Here, we present a general methodology, based on quantitative artificial neural network (ANN) analysis, to resolve overlapping information in 2D NMR spectra and to simultaneously assess the relative importance of multiple spectral variables on the sample properties. The results in a set of 2D NMR spectra of oil samples illustrate, first, that use of ANN analysis for quantitative purposes is feasible also in 2D and, second, that this methodology offers an intrinsic opportunity to assess the complex and nonlinear relationships between the molecular composition and sample properties. The presented ANN methodology is not limited to the analysis of NMR spectra but can also be applied in a manner similar to other (multidimensional) spectroscopic data.

Lipid droplets and membrane material are produced in the extracellular matrix of the arterial intima during atherogenesis. Both in vitro and in vivo experimentation suggests that fusion of modified LDL particles leads to formation of such lipid droplets. Here we applied proton NMR spectroscopy to probe surface phospholipids phosphatidylcholine (PC) and sphingomyelin (SM) of LDL particles during proteolytic degradation of apolipoprotein B-100 (apoB-100). Initiation of apoB-100 degradation was accompanied by the abruptly increased intensity of the choline -N(CH(3))(3) resonance of PC molecules, indicating disruption of their interactions with apoB-100. However, subsequent particle fusion was accompanied by a steady decrease in the intensity of the choline resonances of both PC and SM. Electron microscopy of the proteolyzed LDL revealed irregularly shaped multilamellar membranes attached to aggregates of fused particles. This suggests formation of membrane material with low hydration, in which some of the atomic motions are hindered. Characterization of the behavior of the surface lipids of LDL particles during apoB-100 degradation and other types of LDL modification will aid in understanding molecular mechanisms leading to fusion and generation of multilamellar membrane material in the arterial intima during atherogenesis.

Initiation of atherosclerosis is characterized by accumulation of aggregates of small lipid droplets and vesicles in the extracellular matrix of the arterial intima. The droplets and vesicles have features that suggest that they are formed from modified plasma-derived low density lipoprotein (LDL) particles. A variety of hydrolytic enzymes and prooxidative agents that could lead to extracellular assembly of LDL-derived droplets and vesicles are present in the arterial intima. In fact, in vitro studies have demonstrated that extensive oxidation of LDL and treatment of LDL with either proteolytic or lipolytic enzymes will induce LDL aggregation and fusion and treatment of LDL with cholesterol esterase will cause formation of vesicles. Fusion of LDL particles proceeds faster in vitro when they are bound to components of the extracellular matrix derived from the arterial intima, such as proteoglycans, and, depending on the type of modification, the strength of binding of modified LDL to the matrix components may either increase or decrease. In the present article, we discuss molecular mechanisms that provide clues as to how aggregated lipid droplets and vesicles may be derived from modified LDL particles. We also describe how these modified forms of LDL, by means of their trapping to the extracellular matrix, may lead to extracellular lipid accumulation in the arterial intima.

A semi‐automated, metabolite prior‐knowledge‐based, lineshape fitting analysis has been developed to assess the dynamic biochemical changes found in ex vivo31P NMR pig liver preservation studies. Due to the inherent experimental limitations of the ex vivostudy and the complexity of the composite phosphorus resonances, metabolite information obtained in vitrowas incorporated into the ex vivoanalysis. This approach has allowed complete metabolite analysis (phosphomonoesters, inorganic phosphate, phosphodiesters and nucleotide triphosphates) in over 2000 spectra in a fraction of the time compared with more conventional analysis methods. The developed analysis will enable complete and rapid assessment of the biochemical changes in ongoing cold preservation studies of the pig liver which will result in thousands of ex vivo31P NMR spectra. It is also envisaged that comparative studies on human donor livers will be carried out, in which this type of analysis would be the method of choice. Moreover, this kind of analysis approach could be advantageous in many complex in vivoNMR spectroscopy applications. Copyright © 1999 John Wiley & Sons, Ltd.

A semi-automated, metabolite prior-knowledge-based, lineshape fitting analysis has been developed to assess the dynamic biochemical changes found in ex vivo ³¹P NMR pig liver preservation studies. Due to the inherent experimental limitations of the ex vivo study and the complexity of the composite phosphorus resonances, metabolite information obtained in vitro was incorporated into the ex vivo analysis. This approach has allowed complete metabolite analysis (phosphomonoesters, inorganic phosphate, phosphodiesters and nucleotide triphosphates) in over 2000 spectra in a fraction of the time compared with more conventional analysis methods. The developed analysis will enable complete and rapid assessment of the biochemical changes in ongoing cold preservation studies of the pig liver which will result in thousands of ex vivo ³¹P NMR spectra. It is also envisaged that comparative studies on human donor livers will be carried out, in which this type of analysis would be the method of choice. Moreover, this kind of analysis approach could be advantageous in many complex in vivo NMR spectroscopy applications. Copyright © 1999 John Wiley & Sons, Ltd.

Studies of cholesteryl ester transfer protein (CETP) function in lipoprotein mixtures pose many difficulties by conventional biochemical methods. For instance, studies on the effects of CETP on the composition of apolipoprotein B containing lipoproteins (very low and low density lipoproteins) in lipoprotein mixtures are tedious due to repeated ultracentrifugational isolations and have thus rarely been performed. Here we present a new 1H NMR spectroscopy technique to assess the CETP function in lipoprotein mixtures. This technique does not require repeated physical isolations of the lipoprotein particles but uses mathematical separation of the fractions on the basis of biochemical prior knowledge based lineshape fitting analysis of specific lipid resonances in the 1H NMR spectra. The lipoproteins are separated according to their size related chemical shift which allows for distinct quantification between very low and low density lipoproteins, the two major apolipoprotein B containing fractions. The methodological basis of the technique is discussed here together with a demonstration that this kind of approach allows dynamic follow up of the lipid transfer reactions in complex lipoprotein and CETP mistures. The results revealed a consistent behaviour which corroborated the recent findings suggesting that the neutral lipid mass transfer among lipoproteins is not an equimolar heteroexchange (J. Lipid Res.36, 2574–2579, 1995). © 1997 John Wiley & Sons, Ltd.

Recent evidence suggests that fusion of low density lipoprotein (LDL) particles is a key process in the initial accumulation of lipid in the arterial intima. In order to gain a better understanding of this early event in the development of atherosclerosis, it would thus be necessary to characterize the process of LDL fusion in detail. Such studies, however, pose severe methodological difficulties, such as differentiation of particle fusion from aggregation. In this paper we describe the use of novel methodology, based on 1H NMR spectroscopy, to study lipoprotein particle fusion. To test the methodology, we chose proteolytic fusion of LDL particles, an in vitro model that has been well characterized in our laboratory. The spectroscopic data suggested that proteolysis of LDL with alpha-chymotrypsin induced slow initiation of fusion, which was followed by particle fusion at an increased rate. Moreover, 1H NMR spectroscopic data on different kinds of LDL interactions, for example, when LDL formed aggregates with antibodies against human apolipoprotein B-100, were obtained and compared with the electron microscopic characteristics of these preparations. An important finding was that limited aggregation of LDL particles did not disturb the 1H NMR spectroscopic parameters used for the detection of particle fusion and preserved the physico-chemical information on the particles. The 1H NMR methodology developed is sensitive to and specific for low density lipoprotein (LDL) fusion and may also allow for studies of the fate of LDL particles in other in vitro preparations that mimic the arterial interactions in vivo.

Studies of cholesteryl ester transfer protein (CETP) function in lipoprotein mixtures pose many difficulties by conventional biochemical methods. For instance, studies on the effects of CETP on the composition of apolipoprotein B containing lipoproteins (very low and low density lipoproteins) in lipoprotein mixtures are tedious due to repeated ultracentrifugational isolations and have thus rarely been performed. Here we present a new ¹H NMR spectroscopy technique to assess the CETP function in lipoprotein mixtures. This technique does not require repeated physical isolations of the lipoprotein particles but uses mathematical separation of the fractions on the basis of biochemical prior knowledge based lineshape fitting analysis of specific lipid resonances in the ¹H NMR spectra. The lipoproteins are separated according to their size related chemical shift which allows for distinct quantification between very low and low density lipoproteins, the two major apolipoprotein B containing fractions. The methodological basis of the technique is discussed here together with a demonstration that this kind of approach allows dynamic follow up of the lipid transfer reactions in complex lipoprotein and CETP mistures. The results revealed a consistent behaviour which corroborated the recent findings suggesting that the neutral lipid mass transfer among lipoproteins is not an equimolar heteroexchange (J. Lipid Res. 36, 2574–2579, 1995). © 1997 John Wiley & Sons, Ltd.

A new method is presented for absolute quantitation of lipid and protein contents of human lipoproteins directly from plasma. The method enables complete lipoprotein lipid profiles to be obtained in a total time of less than one hour. Absolute concentrations of triglycerides, phospholipids, total cholesterol, free cholesterol, esterified cholesterol, total proteins, and total masses can be estimated for the very low density (VLDL) and low density (LDL) lipoprotein fractions. For the high density lipoprotein (HDL) fraction all components except triglycerides can be quantitated. The method is a combination of 1H NMR spectroscopy and a sophisticated lineshape fitting analysis technique. In this paper we present the calibration of the method using 15 plasma samples followed by a double-blind test of 51 plasma samples from 43 individuals. In total, 66 plasma samples were analyzed. Comparison of the 1H NMR-based results with the data of the biochemical assays showed excellent agreement; the correlation coefficient for VLDL triglycerides was 0.98, for LDL cholesterol 0.88, and for HDL cholesterol 0.93. This method can be directly integrated to many kinds of biomedical NMR studies to offer additional biochemically important quantitative lipoprotein information, the measurement of which is usually too laborious by conventional biochemical methods and too high-priced to be adapted into the study protocols. Moreover, the method also has considerable potential to be developed for a routine clinical assay.

Efficient and relevant classification of clinical findings, i.e. diagnostic decision making, poses a major challenge in medicine. In relation to biomedical NMR spectroscopy the problem of classification is often accompanied by complex, heavily overlapping information. Self‐organizing map (SOM) analysis has been successfully applied in many areas of research and was thus also considered as a potential tool for NMR data analysis. In this paper we demonstrate how SOM analysis can be used for automated NMR data classification. Our goal was analysis of plasma lipoprotein lipids, a complex but biochemically well understood and specified system. The results illustrate that clinically relevant lipid classifications can be obtained from the SOM analysis of 1H NMR spectral information alone. The resulting maps were calibrated using independent biochemical lipid analyses and were found to produce excellent clustering of the plasma samples into clinically useful groups: normal, type IIa, IIb and IV hyperlipidaemias. In addition to this traditional classification, we also present results from SOM analysis in which the reference vectors of the map were calibrated for plasma total cholesterol and triglycerides and high and low density lipoprotein C; the plasma lipid parameters that are currently considered as the most useful indicators of coronary heart disease risk. In all, the present results indicate that SOM analysis can cope well with complex NMR spectral information and is thus likely to have an independent role in the area of biomedical NMR data analysis. © 1998 John Wiley & Sons, Ltd.

Efficient and relevant classification of clinical findings, i.e. diagnostic decision making, poses a major challenge in medicine. In relation to biomedical NMR spectroscopy the problem of classification is often accompanied by complex, heavily overlapping information. Self-organizing map (SOM) analysis has been successfully applied in many areas of research and was thus also considered as a potential tool for NMR data analysis. In this paper we demonstrate how SOM analysis can be used for automated NMR data classification. Our goal was analysis of plasma lipoprotein lipids, a complex but biochemically well understood and specified system. The results illustrate that clinically relevant lipid classifications can be obtained from the SOM analysis of ¹H NMR spectral information alone. The resulting maps were calibrated using independent biochemical lipid analyses and were found to produce excellent clustering of the plasma samples into clinically useful groups: normal, type IIa, IIb and IV hyperlipidaemias. In addition to this traditional classification, we also present results from SOM analysis in which the reference vectors of the map were calibrated for plasma total cholesterol and triglycerides and high and low density lipoprotein C; the plasma lipid parameters that are currently considered as the most useful indicators of coronary heart disease risk. In all, the present results indicate that SOM analysis can cope well with complex NMR spectral information and is thus likely to have an independent role in the area of biomedical NMR data analysis. © 1998 John Wiley & Sons, Ltd.

During atherogenesis, low density lipoprotein (LDL) particles bind to extracellular matrix proteoglycans in the arterial wall, become modified, and appear as aggregated and fused particles. Sphingomyelinase (SMase) and phospholipase A2 (PLA2) have been found in the arterial wall, and, moreover, lesional LDL shows signs of hydrolysis of both sphingomyelin and phosphatidylcholine. We have now studied the effects of these two lipolytic modifications on the aggregation and fusion of LDL particles by hydrolyzing the particles with Bacillus cereus SMase or bee venom PLA2. In addition, the binding strengths of the modified LDL to human aortic proteoglycans (PG) were analyzed on an affinity column. We found that SMase induced aggregation and fusion of LDL, but PLA2 induced only aggregation of the particles. In addition, the SMase-induced aggregation and fusion of LDL was promoted by pretreatment of LDL with PLA2. Determination of the binding strengths of the hydrolyzed LDL revealed that mere lipolysis of LDL without aggregation or fusion, either by SMase or PLA2, did not affect the binding of the particles to PG. Aggregation and fusion of lipolyzed LDL particles, however, increased their strength of binding to PG. Active lysine residues in apolipoprotein B-100 (apoB-100) appear to be involved in the binding of LDL to PG, and, in fact, quantitative 13C NMR analysis revealed that, in the fused LDL particles, the number of active lysine residues per apoB-100 moiety was increased. Moreover, aggregation and fusion of LDL increased the number of apoB-100 copies and, consequently, the number of active lysine residues per aggregate or fused particle. Our present findings therefore (i) show that treatment of LDL with SMase and PLA2 generates modified LDL particles, which then bind to human aortic PG with increased strength, and (ii) suggest that SMase- and PLA2-induced aggregation and fusion of LDL are potential mechanisms leading to focal retention of extracellular lipid in the arterial wall.