Sialylated Milk Oligosaccharides Promote Microbiota-Dependent Growth in Models of Infant Undernutrition.

Identifying interventions that more effectively promote healthy growth of children with undernutrition is a pressing global health goal. Analysis of human milk oligosaccharides (HMOs) from 6-month-postpartum mothers in two Malawian birth cohorts revealed that sialylated HMOs are significantly less abundant in those with severely stunted infants. To explore this association, we colonized young germ-free mice with a consortium of bacterial strains cultured from the fecal microbiota of a 6-month-old stunted Malawian infant and fed recipient animals a prototypic Malawian diet with or without purified sialylated bovine milk oligosaccharides (S-BMO). S-BMO produced a microbiota-dependent augmentation of lean body mass gain, changed bone morphology, and altered liver, muscle, and brain metabolism in ways indicative of a greater ability to utilize nutrients for anabolism. These effects were also documented in gnotobiotic piglets using the same consortium and Malawian diet. These preclinical models indicate a causal, microbiota-dependent relationship between S-BMO and growth promotion.

Metabolomic and genetic architecture of gestational diabetes subtypes.

AIMS/HYPOTHESIS: Physiological gestational diabetes mellitus (GDM) subtypes that may confer different risks for adverse pregnancy outcomes have been defined. The aim of this study was to characterise the metabolome and genetic architecture of GDM subtypes to address the hypothesis that they differ between GDM subtypes. METHODS: This was a cross-sectional study of participants in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study who underwent an OGTT at approximately 28 weeks' gestation. GDM was defined retrospectively using International Association of Diabetes and Pregnancy Study Groups/WHO criteria, and classified as insulin-deficient GDM (insulin secretion <25th percentile with preserved insulin sensitivity) or insulin-resistant GDM (insulin sensitivity <25th percentile with preserved insulin secretion). Metabolomic analyses were performed on fasting and 1 h serum samples in 3463 individuals (576 with GDM). Genome-wide genotype data were obtained for 8067 individuals (1323 with GDM). RESULTS: Regression analyses demonstrated striking differences between the metabolomes for insulin-deficient or insulin-resistant GDM compared to those with normal glucose tolerance. After adjustment for covariates, 33 fasting metabolites, including 22 medium- and long-chain acylcarnitines, were uniquely associated with insulin-deficient GDM; 23 metabolites, including the branched-chain amino acids and their metabolites, were uniquely associated with insulin-resistant GDM; two metabolites (glycerol and 2-hydroxybutyrate) were associated with the same direction of association with both subtypes. Subtype differences were also observed 1 h after a glucose load. In genome-wide association studies, variants within MTNR1B (rs10830963, p=3.43×10-18, OR 1.55) and GCKR (rs1260326, p=5.17×10-13, OR 1.43) were associated with GDM. Variants in GCKR (rs1260326, p=1.36×10-13, OR 1.60) and MTNR1B (rs10830963, p=1.22×10-9, OR 1.49) demonstrated genome-wide significant association with insulin-resistant GDM; there were no significant associations with insulin-deficient GDM. The lead SNP in GCKR, rs1260326, was associated with the levels of eight of the 25 fasting metabolites that were associated with insulin-resistant GDM and ten of 41 1 h metabolites that were associated with insulin-resistant GDM. CONCLUSIONS/INTERPRETATION: This study demonstrates that physiological GDM subtypes differ in their metabolome and genetic architecture. These findings require replication in additional cohorts, but suggest that these differences may contribute to subtype-related adverse pregnancy outcomes.

Circulating metabolic profile in idiopathic pulmonary fibrosis: data from the IPF-PRO Registry.

BACKGROUND: The circulating metabolome, reflecting underlying cellular processes and disease biology, has not been fully characterized in patients with idiopathic pulmonary fibrosis (IPF). We evaluated whether circulating levels of metabolites correlate with the presence of IPF, with the severity of IPF, or with the risk of clinically relevant outcomes among patients with IPF. METHODS: We analyzed enrollment plasma samples from 300 patients with IPF in the IPF-PRO Registry and 100 individuals without known lung disease using a set of targeted metabolomics and clinical analyte modules. Linear regression was used to compare metabolite and clinical analyte levels between patients with IPF and controls and to determine associations between metabolite levels and measures of disease severity in patients with IPF. Unadjusted and adjusted univariable Cox regression models were used to evaluate associations between circulating metabolites and the risk of mortality or disease progression among patients with IPF. RESULTS: Levels of 64 metabolites and 5 clinical analytes were significantly different between patients with IPF and controls. Among analytes with greatest differences were non-esterified fatty acids, multiple long-chain acylcarnitines, and select ceramides, levels of which were higher among patients with IPF versus controls. Levels of the branched-chain amino acids valine and leucine/isoleucine were inversely correlated with measures of disease severity. After adjusting for clinical factors known to influence outcomes, higher levels of the acylcarnitine C:16-OH/C:14-DC were associated with all-cause mortality, lower levels of the acylcarnitine C16:1-OH/C14:1DC were associated with all-cause mortality, respiratory death, and respiratory death or lung transplant, and higher levels of the sphingomyelin d43:2 were associated with the risk of respiratory death or lung transplantation. CONCLUSIONS: IPF has a distinct circulating metabolic profile characterized by increased levels of non-esterified fatty acids, long-chain acylcarnitines, and ceramides, which may suggest a more catabolic environment that enhances lipid mobilization and metabolism. We identified select metabolites that were highly correlated with measures of disease severity or the risk of disease progression and that may be developed further as biomarkers. TRIAL REGISTRATION: ClinicalTrials.gov; No: NCT01915511; URL: www. CLINICALTRIALS: gov .

Gut microbiome contributions to altered metabolism in a pig model of undernutrition.

The concept that gut microbiome-expressed functions regulate ponderal growth has important implications for infant and child health, as well as animal health. Using an intergenerational pig model of diet restriction (DR) that produces reduced weight gain, we developed a feature-selection algorithm to identify representative characteristics distinguishing DR fecal microbiomes from those of full-fed (FF) pigs as both groups consumed a common sequence of diets during their growth cycle. Gnotobiotic mice were then colonized with DR and FF microbiomes and subjected to controlled feeding with a pig diet. DR microbiomes have reduced representation of genes that degrade dominant components of late growth-phase diets, exhibit reduced production of butyrate, a key host-accessible energy source, and are causally linked to reduced hepatic fatty acid metabolism (ß-oxidation) and the selection of alternative energy substrates. The approach described could aid in the development of guidelines for microbiome stewardship in diverse species, including farm animals, in order to support their healthy growth.

Path-level interpretation of Gaussian graphical models using the pair-path subscore.

BACKGROUND : Construction of networks from cross-sectional biological data is increasingly common. Many recent methods have been based on Gaussian graphical modeling, and prioritize estimation of conditional pairwise dependencies among nodes in the network. However, challenges remain on how specific paths through the resultant network contribute to overall 'network-level' correlations. For biological applications, understanding these relationships is particularly relevant for parsing structural information contained in complex subnetworks. RESULTS: We propose the pair-path subscore (PPS), a method for interpreting Gaussian graphical models at the level of individual network paths. The scoring is based on the relative importance of such paths in determining the Pearson correlation between their terminal nodes. PPS is validated using human metabolomics data from the Hyperglycemia and adverse pregnancy outcome (HAPO) study, with observations confirming well-documented biological relationships among the metabolites. We also highlight how the PPS can be used in an exploratory fashion to generate new biological hypotheses. Our method is implemented in the R package pps, available at https://github.com/nathan-gill/pps . CONCLUSIONS: The PPS can be used to probe network structure on a finer scale by investigating which paths in a potentially intricate topology contribute most substantially to marginal behavior. Adding PPS to the network analysis toolkit may enable researchers to ask new questions about the relationships among nodes in network data.

A cell-nonautonomous mechanism of yeast chronological aging regulated by caloric restriction and one-carbon metabolism.

Caloric restriction (CR) improves health span and life span of organisms ranging from yeast to mammals. Understanding the mechanisms involved will uncover future interventions for aging-associated diseases. In budding yeast, Saccharomyces cerevisiae, CR is commonly defined by reduced glucose in the growth medium, which extends both replicative and chronological life span (CLS). We found that conditioned media collected from stationary-phase CR cultures extended CLS when supplemented into nonrestricted (NR) cultures, suggesting a potential cell-nonautonomous mechanism of CR-induced life span regulation. Chromatography and untargeted metabolomics of the conditioned media, as well as transcriptional responses associated with the longevity effect, pointed to specific amino acids enriched in the CR conditioned media (CRCM) as functional molecules, with L-serine being a particularly strong candidate. Indeed, supplementing L-serine into NR cultures extended CLS through a mechanism dependent on the one-carbon metabolism pathway, thus implicating this conserved and central metabolic hub in life span regulation.

A Multidimensional Bioinformatic Platform for the Study of Human Response to Surgery.

OBJECTIVE: To design and establish a prospective biospecimen repository that integrates multi-omics assays with clinical data to study mechanisms of controlled injury and healing. BACKGROUND: Elective surgery is an opportunity to understand both the systemic and focal responses accompanying controlled and well-characterized injury to the human body. The overarching goal of this ongoing project is to define stereotypical responses to surgical injury, with the translational purpose of identifying targetable pathways involved in healing and resilience, and variations indicative of aberrant peri-operative outcomes. METHODS: Clinical data from the electronic medical record combined with large-scale biological data sets derived from blood, urine, fecal matter, and tissue samples are collected prospectively through the peri-operative period on patients undergoing 14 surgeries chosen to represent a range of injury locations and intensities. Specimens are subjected to genomic, transcriptomic, proteomic, and metabolomic assays to describe their genetic, metabolic, immunologic, and microbiome profiles, providing a multidimensional landscape of the human response to injury. RESULTS: The highly multiplexed data generated includes changes in over 28,000 mRNA transcripts, 100 plasma metabolites, 200 urine metabolites, and 400 proteins over the longitudinal course of surgery and recovery. In our initial pilot dataset, we demonstrate the feasibility of collecting high quality multi-omic data at pre- and postoperative time points and are already seeing evidence of physiologic perturbation between timepoints. CONCLUSIONS: This repository allows for longitudinal, state-of-the-art geno-mic, transcriptomic, proteomic, metabolomic, immunologic, and clinical data collection and provides a rich and stable infrastructure on which to fuel further biomedical discovery.

Urine tricarboxylic acid cycle signatures of early-stage diabetic kidney disease.

INTRODUCTION: Urine tricarboxylic acid (TCA) cycle organic anions (OAs) are elevated in diabetes and may be biomarkers for diabetic kidney disease (DKD) progression. OBJECTIVES: We assessed associations of 10 urine TCA cycle OAs with estimated glomerular filtration rate (eGFR) and eGFR slope. METHODS: This study is ancillary to the Simultaneous Risk Factor Control Using Telehealth to SlOw Progression of Diabetic Kidney Disease (STOP-DKD) Trial-a randomized trial of pharmacist-led medication and behavior management in 281 patients with early to moderate DKD at Duke from 2014 to 2015. We used linear mixed models to assess associations of urine TCA cycle OAs with outcomes and modelled TCA cycle OAs as: (1) the average of z-scores for each OA; and (2) principal component (PC) scores derived by principal component analysis (PCA). Untargeted urine metabolomics were added for additional discovery. RESULTS: Among 132 participants with 24 h urine samples (50% men; 58% Black; mean age 64 years [SD 9]; mean eGFR 74 ml/min/1.73m2 [SD 21] and median urine albumin-to-creatinine [UACR] 20 mg/g [IQR 8-95]), PCA identified 3 OA metabolite PCs. Malate, fumarate, pyruvate, α-ketoglutarate, lactate, succinate and citrate/isocitrate loaded positively on PC1; methylsuccinate, ethylmalonate and succinate loaded positively on PC2; and methylmalonate, ethylmalonate and citrate/isocitrate loaded negatively on PC3. Over a median follow-up of 1.8 years (IQR, 1.2 to 2.2), higher average OA z-score was strongly associated with higher eGFR after covariate adjustment (p = 0.01), but not with eGFR slope (p = 0.9). Higher PC3, but not other PCs, was associated with lower eGFR (p < 0.001). Conditional random forests and smooth clipped absolute deviation models confirmed methylmalonate, citrate/isocitrate, and ethylmalonate, and added lactate as top ranked metabolites in models of baseline eGFR (R-squared 0.32 and 0.33, respectively). Untargeted urine metabolites confirmed association of urine TCA cycle OAs with kidney function. CONCLUSION: Thus, lower urine TCA cycle OAs, most notably lower methylmalonate, ethylmalonate and citrate/isocitrate, are potential indicators of kidney impairment in early stage DKD.

Metabolomic and genetic associations with insulin resistance in pregnancy.

AIMS/HYPOTHESIS: Our study aimed to integrate maternal metabolic and genetic data related to insulin sensitivity during pregnancy to provide novel insights into mechanisms underlying pregnancy-induced insulin resistance. METHODS: Fasting and 1 h serum samples were collected from women in the Hyperglycemia and Adverse Pregnancy Outcome study who underwent an OGTT at ∼28 weeks' gestation. We obtained targeted and non-targeted metabolomics and genome-wide association data from 1600 and 4528 mothers, respectively, in four ancestry groups (Northern European, Afro-Caribbean, Mexican American and Thai); 1412 of the women had both metabolomics and genome-wide association data. Insulin sensitivity was calculated using a modified insulin sensitivity index that included fasting and 1 h glucose and C-peptide levels after a 75 g glucose load. RESULTS: Per-metabolite and network analyses across the four ancestries identified numerous metabolites associated with maternal insulin sensitivity before and 1 h after a glucose load, ranging from amino acids and carbohydrates to fatty acids and lipids. Genome-wide association analyses identified 12 genetic variants in the glucokinase regulatory protein gene locus that were significantly associated with maternal insulin sensitivity, including a common functional missense mutation, rs1260326 (ß = -0.2004, p = 4.67 × 10-12 in a meta-analysis across the four ancestries). This SNP was also significantly associated with multiple fasting and 1 h metabolites during pregnancy, including fasting and 1 h triacylglycerols and 2-hydroxybutyrate and 1 h lactate, 2-ketoleucine/ketoisoleucine and palmitoleic acid. Mediation analysis suggested that 1 h palmitoleic acid contributes, in part, to the association of rs1260326 with maternal insulin sensitivity, explaining 13.7% (95% CI 4.0%, 23.3%) of the total effect. CONCLUSIONS/INTERPRETATION: The present study demonstrates commonalities between metabolites and genetic variants associated with insulin sensitivity in the gravid and non-gravid states and provides insights into mechanisms underlying pregnancy-induced insulin resistance. Graphical abstract.

Identification of Metabolic Changes in Ileum, Jejunum, Skeletal Muscle, Liver, and Lung in a Continuous I.V. Pseudomonas aeruginosa Model of Sepsis Using Nontargeted Metabolomics Analysis.

Sepsis is a multiorgan disease affecting the ileum and jejunum (small intestine), liver, skeletal muscle, and lung clinically. The specific metabolic changes in the ileum, jejunum, liver, skeletal muscle, and lung have not previously been investigated. Live Pseudomonas aeruginosa, isolated from a patient, was given via i.v. catheter to pigs to induce severe sepsis. Eighteen hours later, ileum, jejunum, medial gastrocnemius skeletal muscle, liver, and lung were analyzed by nontargeted metabolomics analysis using gas chromatography/mass spectrometry. The ileum and the liver demonstrated significant changes in metabolites involved in linoleic acid metabolism: the ileum and lung had significant changes in the metabolism of valine/leucine/isoleucine; the jejunum, skeletal muscle, and liver had significant changes in arginine/proline metabolism; and the skeletal muscle and lung had significant changes in aminoacyl-tRNA biosynthesis, as analyzed by pathway analysis. Pathway analysis also identified changes in metabolic pathways unique for different tissues, including changes in the citric acid cycle (jejunum), ß-alanine metabolism (skeletal muscle), and purine metabolism (liver). These findings demonstrate both overlapping metabolic pathways affected in different tissues and those that are unique to others and provide insight into the metabolic changes in sepsis leading to organ dysfunction. This may allow therapeutic interventions that focus on multiple tissues or single tissues once the relationship of the altered metabolites/metabolism to the underlying pathogenesis of sepsis is determined.

Maternal metabolites during pregnancy are associated with newborn outcomes and hyperinsulinaemia across ancestries.

AIMS/HYPOTHESIS: We aimed to determine the association of maternal metabolites with newborn adiposity and hyperinsulinaemia in a multi-ethnic cohort of mother-newborn dyads. METHODS: Targeted and non-targeted metabolomics assays were performed on fasting and 1 h serum samples from a total of 1600 mothers in four ancestry groups (Northern European, Afro-Caribbean, Mexican American and Thai) who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, underwent an OGTT at ~28 weeks gestation and whose newborns had anthropometric measurements at birth. RESULTS: In this observational study, meta-analyses demonstrated significant associations of maternal fasting and 1 h metabolites with birthweight, cord C-peptide and/or sum of skinfolds across ancestry groups. In particular, maternal fasting triacylglycerols were associated with newborn sum of skinfolds. At 1 h, several amino acids, fatty acids and lipid metabolites were associated with one or more newborn outcomes. Network analyses revealed clusters of fasting acylcarnitines, amino acids, lipids and fatty acid metabolites associated with cord C-peptide and sum of skinfolds, with the addition of branched-chain and aromatic amino acids at 1 h. CONCLUSIONS/INTERPRETATION: The maternal metabolome during pregnancy is associated with newborn outcomes. Maternal levels of amino acids, acylcarnitines, lipids and fatty acids and their metabolites during pregnancy relate to fetal growth, adiposity and cord C-peptide, independent of maternal BMI and blood glucose levels.

Hormonal and metabolic effects of carbohydrate restriction in children with Prader-Willi syndrome.

OBJECTIVE: Macronutrient regulation of hyperphagia and adiposity in Prader-Willi syndrome (PWS) is poorly understood. We compared fasting and postprandial concentrations of hormones and metabolites in eight PWS children (age 9-18 years) fed, in random order, low carbohydrate, high-fat (LC, 15% carb; 65% fat; 20% protein) and low-fat, high carbohydrate (LF, 65% carb, 15% fat, 20% protein) diets matched for calories and protein. METHODS: Participants were randomized to consume either the LC or LF diet during a first hospital admission and the second diet during a subsequent admission. Blood samples were obtained after overnight fasting and 1 hour after a mixed meal. RESULTS: Relative to subjects consuming the LF diet, subjects consuming the LC diet had: lower postprandial insulin concentrations (P = 0.02); higher fasting GLP-1 AND GIP concentrations and increased postprandial GLP-1 (P < 0.02); reduced ratio of fasting ghrelin to GLP-1 (P = 0.0078); increased FFA and fatty acid oxidation, as assessed by concentrations of even-chain acylcarnitines (P < 0.001); lower fasting TG and TG/HDL ratio (P < 0.01); and higher concentrations of branch chain amino acids (P < 0.01). There were no changes in glucose, PYY, or adiponectin. CRP, AST and ALT were all higher (P < 0.01) on the LC diet. CONCLUSIONS: Increases in GLP-1 with low carbohydrate feeding and reductions in the ratio of ghrelin to GLP-1 might limit food intake and improve glycaemic control in PWS. Other potential benefits of carbohydrate restriction may include fat mobilization and oxidation and reductions in the TG/HDL ratio, a marker of insulin resistance. However, increases in CRP, AST and ALT necessitate longer-term studies of low carbohydrate efficacy and safety.

SIRT3 deficiency and mitochondrial protein hyperacetylation accelerate the development of the metabolic syndrome.

Acetylation is increasingly recognized as an important metabolic regulatory posttranslational protein modification, yet the metabolic consequence of mitochondrial protein hyperacetylation is unknown. We find that high-fat diet (HFD) feeding induces hepatic mitochondrial protein hyperacetylation in mice and downregulation of the major mitochondrial protein deacetylase SIRT3. Mice lacking SIRT3 (SIRT3KO) placed on a HFD show accelerated obesity, insulin resistance, hyperlipidemia, and steatohepatitis compared to wild-type (WT) mice. The lipogenic enzyme stearoyl-CoA desaturase 1 is highly induced in SIRT3KO mice, and its deletion rescues both WT and SIRT3KO mice from HFD-induced hepatic steatosis and insulin resistance. We further identify a single nucleotide polymorphism in the human SIRT3 gene that is suggestive of a genetic association with the metabolic syndrome. This polymorphism encodes a point mutation in the SIRT3 protein, which reduces its overall enzymatic efficiency. Our findings show that loss of SIRT3 and dysregulation of mitochondrial protein acetylation contribute to the metabolic syndrome.

Metabolites predict cardiovascular disease events in persons living with HIV: a pilot case-control study.

Introduction: Persons living with HIV (PLWH) are at higher risk for cardiovascular disease (CVD) events than uninfected persons. Current risk-stratification methods to define PLWH at highest risk for CVD events are lacking. Methods: Using tandem flow injection mass spectrometry, we quantified plasma levels of 60 metabolites in 24 matched pairs of PLWH [1:1 with and without known coronary artery disease (CAD)]. Metabolite levels were reduced to interpretable factors using principal components analysis. Results: Factors derived from short-chain dicarboxylacylcarnitines (SCDA) (p = 0.08) and glutamine/valine (p = 0.003) were elevated in CAD cases compared to controls. Conclusion: SCDAs and glutamine/valine may be valuable markers of cardiovascular risk among persons living with HIV in the future, pending validation in larger cohorts.

Untargeted metabolomics analysis of ischemia-reperfusion-injured hearts ex vivo from sedentary and exercise-trained rats.

Introduction: The effects of exercise on the heart and its resistance to disease are well-documented. Recent studies have identified that exercise-induced resistance to arrhythmia is due to the preservation of mitochondrial membrane potential. Objectives: To identify novel metabolic changes that occur parallel to these mitochondrial alterations, we performed non-targeted metabolomics analysis on hearts from sedentary and exercise-trained rats challenged with isolated heart ischemia-reperfusion injury (I/R). Methods: Eight-week old Sprague-Dawley rats were treadmill trained 5 days/week for 6 weeks (exercise duration and intensity progressively increased to 1 h at 30 m/min up a 10.5% incline, 75-80% VO2max). The recovery of pre-ischemic function for sedentary rat hearts was 28.8 ± 5.4% (N = 12) compared to exercise trained hearts, which recovered 51.9% ± 5.7 (N = 14) (p < 0.001). Results: Non-targeted GC-MS metabolomics analysis of (1) sedentary rat hearts; (2) exercise-trained rat hearts; (3) sedentary rat hearts challenged with global ischemia-reperfusion (I/R) injury; and (4) exercise-trained rat hearts challenged with global I/R (10/group) revealed 15 statistically significant metabolites between groups by ANOVA using Metaboanalyst (p < 0.001). Enrichment analysis of these metabolites for pathway-associated metabolic sets indicated a > 10-fold enrichment for ammonia recycling and protein biosynthesis. Subsequent comparison of the sedentary hearts post-I/R and exercise-trained hearts post-I/R further identified significant differences in three metabolites (oleic acid, pantothenic acid, and campesterol) related to pantothenate and CoA biosynthesis (p ≤ 1.24E-05, FDR ≤ 5.07E-4). Conclusions: These studies shed light on novel mechanisms in which exercise-induced cardioprotection occurs in I/R that complement both the mitochondrial stabilization and antioxidant mechanisms recently described. These findings also link protein synthesis and protein degradation (protein quality control mechanisms) with exercise-linked cardioprotection and mitochondrial susceptibility for the first time in cardiac I/R.

Dietary Patterns among Asian Indians Living in the United States Have Distinct Metabolomic Profiles That Are Associated with Cardiometabolic Risk.

Background: Recent studies, primarily in non-Hispanic whites, suggest that dietary patterns have distinct metabolomic signatures that may influence disease risk. However, evidence in South Asians, a group with unique dietary patterns and a high prevalence of cardiometabolic risk, is lacking. Objective: We investigated the metabolomic profiles associated with 2 distinct dietary patterns among a sample of Asian Indians living in the United States. We also examined the cross-sectional associations between metabolomic profiles and cardiometabolic risk markers. Methods: We used cross-sectional data from 145 Asian Indians, aged 45-79 y, in the Metabolic Syndrome and Atherosclerosis in South Asians Living in America (MASALA) pilot study. Metabolomic profiles were measured from fasting serum samples. Usual diet was assessed by using a validated food-frequency questionnaire. We used principal components analysis to derive dietary and metabolomic patterns. We used adjusted general linear regression models to examine associations between dietary patterns, individual food groups, metabolite patterns, and cardiometabolic risk markers. Results: We observed 2 major principal components or metabolite clusters, the first comprised primarily of medium- to long-chain acylcarnitines (metabolite pattern 1) and the second characterized by branched-chain amino acids, aromatic amino acids, and short-chain acylcarnitines (metabolite pattern 2). A "Western/nonvegetarian" pattern was significantly and positively associated with metabolite pattern 2 (all participants: ß ± SE = 0.180 ± 0.090, P = 0.05; participants without type 2 diabetes: ß ± SE = 0.323 ± 0.090, P = 0.0005). In all participants, higher scores on metabolite pattern 2 were adversely associated with measures of glycemia (fasting insulin: ß ± SE = 2.91 ± 1.29, P = 0.03; 2-h insulin: ß ± SE = 22.1 ± 10.3, P = 0.03; homeostasis model assessment of insulin resistance: ß ± SE = 0.94 ± 0.42, P = 0.03), total adiponectin (ß ± SE = -1.46 ± 0.47, P = 0.002), lipids (total cholesterol: ß ± SE = 7.51 ± 3.45, P = 0.03; triglycerides: ß ± SE = 14.4 ± 6.67, P = 0.03), and a radiographic measure of hepatic fat (liver-to-spleen attenuation ratio: ß ± SE = -0.83 ± 0.42, P = 0.05). Conclusions: Our findings suggest that a "Western/nonvegetarian" dietary pattern is associated with a metabolomic profile that is related to an adverse cardiometabolic profile in Asian Indians. Public health efforts to reduce cardiometabolic disease burden in this high-risk group should focus on consuming a healthy plant-based diet.

Mixture model normalization for non-targeted gas chromatography/mass spectrometry metabolomics data.

BACKGROUND: Metabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based or large-scale clinical studies demands large numbers of subjects and therefore sample batching for gas-chromatography/mass spectrometry (GC/MS) non-targeted assays. When run over weeks or months, technical noise due to batch and run-order threatens data interpretability. Application of existing normalization methods to metabolomics is challenged by unsatisfied modeling assumptions and, notably, failure to address batch-specific truncation of low abundance compounds. RESULTS: To curtail technical noise and make GC/MS metabolomics data amenable to analyses describing biologically relevant variability, we propose mixture model normalization (mixnorm) that accommodates truncated data and estimates per-metabolite batch and run-order effects using quality control samples. Mixnorm outperforms other approaches across many metrics, including improved correlation of non-targeted and targeted measurements and superior performance when metabolite detectability varies according to batch. For some metrics, particularly when truncation is less frequent for a metabolite, mean centering and median scaling demonstrate comparable performance to mixnorm. CONCLUSIONS: When quality control samples are systematically included in batches, mixnorm is uniquely suited to normalizing non-targeted GC/MS metabolomics data due to explicit accommodation of batch effects, run order and varying thresholds of detectability. Especially in large-scale studies, normalization is crucial for drawing accurate conclusions from non-targeted GC/MS metabolomics data.

Associations of maternal BMI and insulin resistance with the maternal metabolome and newborn outcomes.

AIMS/HYPOTHESIS: Maternal obesity increases the risk for large-for-gestational-age birth and excess newborn adiposity, which are associated with adverse long-term metabolic outcomes in offspring, probably due to effects mediated through the intrauterine environment. We aimed to characterise the maternal metabolic milieu associated with maternal BMI and its relationship to newborn birthweight and adiposity. METHODS: Fasting and 1 h serum samples were collected from 400 European-ancestry mothers in the Hyperglycaemia and Adverse Pregnancy Outcome Study who underwent an OGTT at ∼28 weeks gestation and whose offspring had anthropometric measurements at birth. Metabolomics assays were performed using biochemical analyses of conventional clinical metabolites, targeted MS-based measurement of amino acids and acylcarnitines and non-targeted GC/MS. RESULTS: Per-metabolite analyses demonstrated broad associations with maternal BMI at fasting and 1 h for lipids, amino acids and their metabolites together with carbohydrates and organic acids. Similar metabolite classes were associated with insulin resistance with unique associations including branched-chain amino acids. Pathway analyses indicated overlapping and unique associations with maternal BMI and insulin resistance. Network analyses demonstrated collective associations of maternal metabolite subnetworks with maternal BMI and newborn size and adiposity, including communities of acylcarnitines, lipids and related metabolites, and carbohydrates and organic acids. Random forest analyses demonstrated contribution of lipids and lipid-related metabolites to the association of maternal BMI with newborn outcomes. CONCLUSIONS/INTERPRETATION: Higher maternal BMI and insulin resistance are associated with broad-based changes in maternal metabolites, with lipids and lipid-related metabolites accounting, in part, for the association of maternal BMI with newborn size at birth.

Evidence for Feedback Regulation Following Cholesterol Lowering Therapy in a Prostate Cancer Xenograft Model.

BACKGROUND: Epidemiologic data suggest cholesterol-lowering drugs may prevent the progression of prostate cancer, but not the incidence of the disease. However, the association of combination therapy in cholesterol reduction on prostate or any cancer is unclear. In this study, we compared the effects of the cholesterol lowering drugs simvastatin and ezetimibe alone or in combination on the growth of LAPC-4 prostate cancer in vivo xenografts. METHODS: Proliferation assays were conducted by MTS solution and assessed by Student's t-test. 90 male nude mice were placed on a high-cholesterol Western-diet for 7 days then injected subcutaneously with 1 × 105 LAPC-4 cells. Two weeks post-injection, mice were randomized to control, 11 mg/kg/day simvastatin, 30 mg/kg ezetimibe, or the combination and sacrificed 42 days post-randomization. We used a generalized linear model with the predictor variables of treatment, time, and treatment by time (i.e., interaction term) with tumor volume as the outcome variable. Total serum and tumor cholesterol were measured. Tumoral RNA was extracted and cDNA synthesized from 1 ug of total RNA for quantitative real-time PCR. RESULTS: Simvastatin directly reduced in vitro prostate cell proliferation in a dose-dependent, cell line-specific manner, but ezetimibe had no effect. In vivo, low continuous dosing of ezetimibe, delivered by food, or simvastatin, delivered via an osmotic pump had no effect on tumor growth compared to control mice. In contrast, dual treatment of simvastatin and ezetimibe accelerated tumor growth. Ezetimibe significantly lowered serum cholesterol by 15%, while simvastatin had no effect. Ezetimibe treatment resulted in higher tumor cholesterol. A sixfold induction of low density lipoprotein receptor mRNA was observed in ezetimibe and the combination with simvastatin versus control tumors. CONCLUSIONS: Systemic cholesterol lowering by ezetimibe did not slow tumor growth, nor did the cholesterol independent effects of simvastatin and the combined treatment increased tumor growth. Despite lower serum cholesterol, tumors from ezetimibe treated mice had higher levels of cholesterol. This study suggests that induction of low density lipoprotein receptor is a possible mechanism of resistance that prostate tumors use to counteract the therapeutic effects of lowering serum cholesterol. Prostate 77:446-457, 2017. © 2016 Wiley Periodicals, Inc.