48 research outputs found

    ¹H NMR analysis of serum lipids

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    NMR protocol for determination of oxidation susceptibility of serum lipids and application of the protocol to a chocolate study

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    A protocol for determination of oxidation susceptibility of serum lipids based on proton nuclear magnetic resonance (1H NMR) spectroscopy is presented and compared to the commonly used spectrophotometric method. Even though there are methodological differences between these two methods, the NMR-based oxidation susceptibility correlates well (r2 = 0.73) with the lag time determined spectrophotometrically. In addition to the oxidizability of serum lipids, the NMR method provides also information about the lipid profile. The NMR oxidation assay was applied to the chocolate study including fasting serum samples (n = 45) from subjects who had consumed white (WC), dark (DC) or high-polyphenol chocolate (HPC) daily for 3 weeks. The oxidation susceptibility of serum lipids decreased in the HPC group, and there was a significant difference between the WC and HPC groups (P = 0.031). According to the random forest analysis, the consumption of the HPC chocolate induced changes to the amounts of HDL, phosphatidylcholine, sphingomyelin, and nervonic, docosahexaenoic and myristic acids. Furthermore, arachidonic, docosahexaenoic, docosapentaenoic and palmitic acids, gamma-glutamyl transferase, hemoglobin, HDL, phosphatidylcholine and choline containing phospholipids explained about 60% of the oxidation susceptibility values

    Metabolic profiling of alcohol consumption in 9778 young adults

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    Background: High alcohol consumption is a major cause of morbidity, yet alcohol is associated with both favourable and adverse effects on cardiometabolic risk markers. We aimed to characterize the associations of usual alcohol consumption with a comprehensive systemic metabolite profile in young adults. Methods: Cross-sectional associations of alcohol intake with 86 metabolic measures were assessed for 9778 individuals from three population-based cohorts from Finland (age 24-45 years, 52% women). Metabolic changes associated with change in alcohol intake during 6-year follow-up were further examined for 1466 individuals. Alcohol intake was assessed by questionnaires. Circulating lipids, fatty acids and metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays. Results: Increased alcohol intake was associated with cardiometabolic risk markers across multiple metabolic pathways, including higher lipid concentrations in HDL subclasses and smaller LDL particle size, increased proportions of monounsaturated fatty acids and decreased proportion of omega-6 fatty acids, lower concentrations of glutamine and citrate (P<0.001 for 56 metabolic measures). Many metabolic biomarkers displayed U-shaped associations with alcohol consumption. Results were coherent for men and women, consistent across the three cohorts and similar if adjusting for body mass index, smoking and physical activity. The metabolic changes accompanying change in alcohol intake during follow-up resembled the cross-sectional association pattern (R-2 = 0.83, slope = 0.7260.04). Conclusions: Alcohol consumption is associated with a complex metabolic signature, including aberrations in multiple biomarkers for elevated cardiometabolic risk. The metabolic signature tracks with long-term changes in alcohol consumption. These results elucidate the double-edged effects of alcohol on cardiovascular risk.Peer reviewe

    Effects of hormonal contraception on systemic metabolism : cross-sectional and longitudinal evidence

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    Background: Hormonal contraception is commonly used worldwide, but its systemic effects across lipoprotein subclasses, fatty acids, circulating metabolites and cytokines remain poorly understood. Methods: A comprehensive molecular profile (75 metabolic measures and 37 cytokines) was measured for up to 5841 women (age range 24-49 years) from three population-based cohorts. Women using combined oral contraceptive pills (COCPs) or progestin-only contraceptives (POCs) were compared with those who did not use hormonal contraception. Metabolomics profiles were reassessed for 869 women after 6 years to uncover the metabolic effects of starting, stopping and persistently using hormonal contraception. Results: The comprehensive molecular profiling allowed multiple new findings on the metabolic associations with the use of COCPs. They were positively associated with lipoprotein subclasses, including all high-density lipoprotein (HDL) subclasses. The associations with fatty acids and amino acids were strong and variable in direction. COCP use was negatively associated with albumin and positively associated with creatinine and inflammatory markers, including glycoprotein acetyls and several growth factors and interleukins. Our findings also confirmed previous results e.g. for increased circulating triglycerides and HDL cholesterol. Starting COCPs caused similar metabolic changes to those observed cross-sectionally: the changes were maintained in consistent users and normalized in those who stopped using. In contrast, POCs were only weakly associated with metabolic and inflammatory markers. Results were consistent across all cohorts and for different COCP preparations and different types of POC delivery. Conclusions: Use of COCPs causes widespread metabolic and inflammatory effects. However, persistent use does not appear to accumulate the effects over time and the metabolic perturbations are reversed upon discontinuation. POCs have little effect on systemic metabolism and inflammation.Peer reviewe

    Proof of concept for quantitative urine NMR metabolomics pipeline for large-scale epidemiology and genetics

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    Background:Quantitative molecular data from urine are rare in epidemiology and genetics. NMR spectroscopy could provide these data in high throughput, and it has already been applied in epidemiological settings to analyse urine samples. However, quantitative protocols for large-scale applications are not available. Methods:We describe in detail how to prepare urine samples and perform NMR experiments to obtain quantitative metabolic information. Semi-automated quantitative line shape fitting analyses were set up for 43 metabolites and applied to data from various analytical test samples and from 1004 individuals from a population-based epidemiological cohort. Novel analyses on how urine metabolites associate with quantitative serum NMR metabolomics data (61 metabolic measures; n = 995) were performed. In addition, confirmatory genome-wide analyses of urine metabolites were conducted (n = 578). The fully automated quantitative regression-based spectral analysis is demonstrated for creatinine and glucose (n = 4548). Results:Intra-assay metabolite variations were mostly <5%, indicating high robustness and accuracy of urine NMR spectroscopy methodology per se. Intra-individual metabolite variations were large, ranging from 6% to 194%. However, population-based inter-individual metabolite variations were even larger (from 14% to 1655%), providing a sound base for epidemiological applications. Metabolic associations between urine and serum were found to be clearly weaker than those within serum and within urine, indicating that urinary metabolomics data provide independent metabolic information. Two previous genome-wide hits for formate and 2-hydroxyisobutyrate were replicated at genome-wide significance. Conclusion:Quantitative urine metabolomics data suggest broad novelty for systems epidemiology. A roadmap for an open access methodology is provided

    Sphingomyelin is associated with kidney disease in type 1 diabetes (The FinnDiane Study)

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    Diabetic kidney disease, diagnosed by urinary albumin excretion rate (AER), is a critical symptom of chronic vascular injury in diabetes, and is associated with dyslipidemia and increased mortality. We investigated serum lipids in 326 subjects with type 1 diabetes: 56% of patients had normal AER, 17% had microalbuminuria (20 ≤ AER < 200 μg/min or 30 ≤ AER < 300 mg/24 h) and 26% had overt kidney disease (macroalbuminuria AER ≥ 200 μg/min or AER ≥ 300 mg/24 h). Lipoprotein subclass lipids and low-molecular-weight metabolites were quantified from native serum, and individual lipid species from the lipid extract of the native sample, using a proton NMR metabonomics platform. Sphingomyelin (odds ratio 2.53, P < 10−7), large VLDL cholesterol (odds ratio 2.36, P < 10−10), total triglycerides (odds ratio 1.88, P < 10−6), omega-9 and saturated fatty acids (odds ratio 1.82, P < 10−5), glucose disposal rate (odds ratio 0.44, P < 10−9), large HDL cholesterol (odds ratio 0.39, P < 10−9) and glomerular filtration rate (odds ratio 0.19, P < 10−10) were associated with kidney disease. No associations were found for polyunsaturated fatty acids or phospholipids. Sphingomyelin was a significant regressor of urinary albumin (P < 0.0001) in multivariate analysis with kidney function, glycemic control, body mass, blood pressure, triglycerides and HDL cholesterol. Kidney injury, sphingolipids and excess fatty acids have been linked in animal models—our exploratory approach provides independent support for this relationship in human patients with diabetes

    Metabolic profiling of pregnancy : cross-sectional and longitudinal evidence

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    Background: Pregnancy triggers well-known alterations in maternal glucose and lipid balance but its overall effects on systemic metabolism remain incompletely understood. Methods: Detailed molecular profiles (87 metabolic measures and 37 cytokines) were measured for up to 4260 women (24-49 years, 322 pregnant) from three population-based cohorts in Finland. Circulating molecular concentrations in pregnant women were compared to those in non-pregnant women. Metabolic profiles were also reassessed for 583 women 6 years later to uncover the longitudinal metabolic changes in response to change in the pregnancy status. Results: Compared to non-pregnant women, all lipoprotein subclasses and lipids were markedly increased in pregnant women. The most pronounced differences were observed for the intermediate-density, low-density and high-density lipoprotein triglyceride concentrations. Large differences were also seen for many fatty acids and amino acids. Pregnant women also had higher concentrations of low-grade inflammatory marker glycoprotein acetyls, higher concentrations of interleukin-18 and lower concentrations of interleukin-12p70. The changes in metabolic concentrations for women who were not pregnant at baseline but pregnant 6 years later (or vice versa) matched (or were mirror-images of) the cross-sectional association pattern. Cross-sectional results were consistent across the three cohorts and similar longitudinal changes were seen for 653 women in 4-year and 497 women in 10-year follow-up. For multiple metabolic measures, the changes increased in magnitude across the three trimesters. Conclusions: Pregnancy initiates substantial metabolic and inflammatory changes in the mothers. Comprehensive characterisation of normal pregnancy is important for gaining understanding of the key nutrients for fetal growth and development. These findings also provide a valuable molecular reference in relation to studies of adverse pregnancy outcomes.Peer reviewe

    Metabolomic Profiling of Statin Use and Genetic Inhibition of HMG-CoA Reductase

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    BACKGROUND Statins are first-line therapy for cardiovascular disease prevention, but their systemic effects across lipoprotein subclasses, fatty acids, and circulating metabolites remain incompletely characterized. OBJECTIVES This study sought to determine the molecular effects of statin therapy on multiple metabolic pathways. METHODS Metabolic profiles based on serum nuclear magnetic resonance metabolomics were quantified at 2 time points in 4 population-based cohorts from the United Kingdom and Finland (N = 5,590; 2.5 to 23.0 years of follow-up). Concentration changes in 80 lipid and metabolite measures during follow-up were compared between 716 individuals who started statin therapy and 4,874 persistent nonusers. To further understand the pharmacological effects of statins, we used Mendelian randomization to assess associations of a genetic variant known to mimic inhibition of HMG-CoA reductase (the intended drug target) with the same lipids and metabolites for 27,914 individuals from 8 population-based cohorts. RESULTS Starting statin therapy was associated with numerous lipoprotein and fatty acid changes, including substantial lowering of remnant cholesterol (80% relative to low-density lipoprotein cholesterol [LDL-C]), but only modest lowering of triglycerides (25% relative to LDL-C). Among fatty acids, omega-6 levels decreased the most (68% relative to LDL-C); other fatty acids were only modestly affected. No robust changes were observed for circulating amino acids, ketones, or glycolysis-related metabolites. The intricate metabolic changes associated with statin use closely matched the association pattern with rs12916 in the HMGCR gene (R-2 = 0.94, slope 1.00 +/- 0.03). CONCLUSIONS Statin use leads to extensive lipid changes beyond LDL-C and appears efficacious for lowering remnant cholesterol. Metabolomic profiling, however, suggested minimal effects on amino acids. The results exemplify how detailed metabolic characterization of genetic proxies for drug targets can inform indications, pleiotropic effects, and pharmacological mechanisms. (C) 2016 by the American College of Cardiology Foundation.Peer reviewe

    Semaphorin 4D promotes bone invasion in head and neck squamous cell carcinoma

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    Head and neck squamous cell carcinomas (HNSCCs) frequently invade the bones of the facial skeleton. Semaphorin 4D (Sema4D) is an axon guidance molecule produced by oligodendrocytes. Sema4D was also identified in the bone microenvironment and many cancer tissues including HNSCC. To date, however, the role of Sema4D in cancer-associated bone disease is still unknown. This is the first study to demonstrate the role of Sema4D in bone invasion of cancer. In the clinical tissue samples of bone lesion of HNSCC, Sema4D was detected at high levels, and its expression was correlated with insulin-like growth factor-I (IGF-I) expression. In vitro experiments showed that IGF-I regulates Sema4D expression and Sema4D increased proliferation, migration and invasion in HNSCC cells. Sema4D also regulated the expression of receptor activator of nuclear factor κβ ligand (RANKL) in osteoblasts, and this stimulated osteoclastgenesis. Furthermore, knockdown of Sema4D in HNSCC cells inhibited tumor growth and decreased the number of osteoclasts in a mouse xenograft model. Taken together, IGF-I-driven production of Sema4D in HNSCCs promotes osteoclastogenesis and bone invasion
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