Characterizing human postprandial metabolic response using multiway data analysis.

INTRODUCTION: Analysis of time-resolved postprandial metabolomics data can improve our understanding of the human metabolism by revealing similarities and differences in postprandial responses of individuals. Traditional data analysis methods often rely on data summaries or univariate approaches focusing on one metabolite at a time. OBJECTIVES: Our goal is to provide a comprehensive picture in terms of the changes in the human metabolism in response to a meal challenge test, by revealing static and dynamic markers of phenotypes, i.e., subject stratifications, related clusters of metabolites, and their temporal profiles. METHODS: We analyze Nuclear Magnetic Resonance (NMR) spectroscopy measurements of plasma samples collected during a meal challenge test from 299 individuals from the COPSAC2000 cohort using a Nightingale NMR panel at the fasting and postprandial states (15, 30, 60, 90, 120, 150, 240 min). We investigate the postprandial dynamics of the metabolism as reflected in the dynamic behaviour of the measured metabolites. The data is arranged as a three-way array: subjects by metabolites by time. We analyze the fasting state data to reveal static patterns of subject group differences using principal component analysis (PCA), and fasting state-corrected postprandial data using the CANDECOMP/PARAFAC (CP) tensor factorization to reveal dynamic markers of group differences. RESULTS: Our analysis reveals dynamic markers consisting of certain metabolite groups and their temporal profiles showing differences among males according to their body mass index (BMI) in response to the meal challenge. We also show that certain lipoproteins relate to the group difference differently in the fasting vs. dynamic state. Furthermore, while similar dynamic patterns are observed in males and females, the BMI-related group difference is observed only in males in the dynamic state. CONCLUSION: The CP model is an effective approach to analyze time-resolved postprandial metabolomics data, and provides a compact but a comprehensive summary of the postprandial data revealing replicable and interpretable dynamic markers crucial to advance our understanding of changes in the metabolism in response to a meal challenge.

Severity of Idiopathic Scoliosis Is Associated with Differential Methylation: An Epigenome-Wide Association Study of Monozygotic Twins with Idiopathic Scoliosis.

Epigenetic mechanisms may contribute to idiopathic scoliosis (IS). We identified 8 monozygotic twin pairs with IS, 6 discordant (Cobb angle difference > 10°) and 2 concordant (Cobb angle difference ≤ 2°). Genome-wide methylation in blood was measured with the Infinium HumanMethylation EPIC Beadchip. We tested for differences in methylation and methylation variability between discordant twins and tested the association between methylation and curve severity in all twins. Differentially methylated region (DMR) analyses identified gene promoter regions. Methylation at cg12959265 (chr. 7 DPY19L1) was less variable in cases (false discovery rate (FDR) = 0.0791). We identified four probes (false discovery rate, FDR < 0.10); cg02477677 (chr. 17, RARA gene), cg12922161 (chr. 2 LOC150622 gene), cg08826461 (chr. 2), and cg16382077 (chr. 7) associated with curve severity. We identified 57 DMRs where hyper- or hypo-methylation was consistent across the region and 28 DMRs with a consistent association with curve severity. Among DMRs, 21 were correlated with bone methylation. Prioritization of regions based on methylation concordance in bone identified promoter regions for WNT10A (WNT signaling), NPY (regulator of bone and energy homeostasis), and others predicted to be relevant for bone formation/remodeling. These regions may aid in understanding the complex interplay between genetics, environment, and IS.

Epigenome-wide cross-tissue correlation of human bone and blood DNA methylation - can blood be used as a surrogate for bone?

Difficulty in obtaining bone tissue is an obstacle to studying epigenetics to understand gene-environment interactions, and their role in disease pathogenesis. Blood is an obvious alternative and in this proof of principle study, our aim was to systematically investigate whether blood is a viable surrogate for bone. We measured epigenome-wide DNA methylation at 850 K CpG sites in matched trabecular bone and peripheral blood collected from the same patients at the same time-point (n = 12 women; 66-85y), to investigate the between-tissue correspondence. What constituted a CpG site with corresponding methylation in both tissues was stringently defined. Only sites highly correlated (r2 > 0.74; FDR q-value <0.05) and at least 80% similarity in methylation level (Δß <0.2) between paired samples were retained. In total, 28,549 CpG sites were similarly methylated in bone and blood. Between 33% and 49% of loci associated with bone phenotypes through GWAS were represented among these sites, and major pathways relevant to bone regulation were enriched. The results from this study indicate that blood can mirror the bone methylome and capture sites related to bone regulation. This study shows that in principal, peripheral blood is a feasible surrogate for bone tissue in DNA methylation investigations. As the first step, this will provide a platform for future studies in bone epigenetics, and possibly for larger-scale epidemiological studies.

Consumption of regular-fat vs reduced-fat cheese reveals gender-specific changes in LDL particle size - a randomized controlled trial.

BACKGROUND: Regular-fat cheese does not seem to increase low density lipoprotein cholesterol (LDL-C) concentrations compared to reduced-fat cheese. However, plasma LDL-C concentrations do not reflect levels and size of LDL particles, which might be a better predictor of cardiovascular risk. METHODS: The aim was to compare the effects of regular-fat cheese vs reduced-fat cheese and carbohydrate-rich foods on LDL particle size distribution in adults with ≥ 2 metabolic syndrome (MetS) risk factors. The study was part of a 12 weeks' randomized controlled trial in which subjects had been randomly allocated to 1 of 3 intervention groups; regular-fat cheese (REG), reduced-fat cheese (RED) or a no-cheese/carbohydrate (CHO) group. Subjects in the REG and RED groups consumed 80 g cheese/d per 10 MJ, whereas subjects in the CHO consumed bread and jam corresponding to 90 g/d and 25 g/d per 10 MJ, respectively. Fasting blood samples at wk. 0 (baseline) and wk. 12 were analyzed for LDL particle size distribution and cholesterol content using nuclear magnetic resonance (NMR) spectroscopy. RESULTS: A total of 85 subjects [mean ± SD age: 54.0 ± 12.8 y; BMI: 28.7 ± 3.6 kg/m2] completed the study. Overall, regular-fat cheese did not impact lipoprotein particle number and size differently than reduced-fat cheese. In men (n = 23), the REG diet decreased total LDL particle number (LDL-P, - 223.2 ± 91.1 nmol/l, P = 0.01) compared with the RED diet. The reduction was primarily in the medium-sized LDL fraction (- 128.5 ± 51.8 nmol/l, P = 0.01). In women (n = 62), the REG diet increased the concentration of cholesterol in the small high density lipoprotein (HDL) particles compared with the CHO diet (2.9 ± 1.0 mg/dl, P = 0.006). CONCLUSION: Overall, regular-fat cheese did not alter LDL particle size distribution compared to reduced-fat cheese after a 12 wk. intervention in subjects with ≥2 MetS risk factors. However, our results suggest that lipoprotein response to cheese intake is gender-specific. This warrants further investigation. TRIAL REGISTRATION: This trial was registered at Clinicaltrials.gov as NCT0261471. Registered 30 November 2015 - Retrospectively registered.

Toward Reliable Lipoprotein Particle Predictions from NMR Spectra of Human Blood: An Interlaboratory Ring Test.

Lipoprotein profiling of human blood by 1H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4-0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC).

Metabolic footprinting for investigation of antifungal properties of Lactobacillus paracasei.

Lactic acid bacteria with antifungal properties are applied for biopreservation of food. In order to further our understanding of their antifungal mechanism, there is an ongoing search for bioactive molecules. With a focus on the metabolites formed, bioassay-guided fractionation and comprehensive screening have identified compounds as antifungal. Although these are active, the compounds have been found in concentrations that are too low to account for the observed antifungal effect. It has been hypothesized that the formation of metabolites and consumption of nutrients during bacterial fermentations form the basis for the antifungal effect, i.e., the composition of the exometabolome. To build a more comprehensive view of the chemical changes induced by bacterial fermentation and the effects on mold growth, a strategy for correlating the exometabolomic profiles with mold growth was applied. The antifungal properties were assessed by measuring mold growth of two Penicillium strains on cell-free ferments of three strains of Lactobacillus paracasei pre-fermented in a chemically defined medium. Exometabolomic profiling was performed by reversed-phase liquid chromatography in combination with mass spectrometry in electrospray positive and negative modes. By multivariate data analysis, the three strains of Lb. paracasei were readily distinguished by the relative difference of their exometabolomes. The relative differences correlated with the relative growth of the two Penicillium strains. Metabolic footprinting proved to be a supplement to bioassay-guided fractionation for investigation of antifungal properties of bacterial ferments. Additionally, three previously identified and three novel antifungal metabolites from Lb. paracasei and their potential precursors were detected and assigned using the strategy.