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Metabolomics is a study of small molecules in the body and the associated metabolic pathways and is considered to provide a close link between organism's genotype and phenotype. As with other ‘omics’ techniques, metabolomic analysis generates large-scale and complex datasets. Therefore, various data analysis tools are needed to extract biologically relevant information. The data analysis workflows in metabolomics studies are generally complex and involve several steps. In this chapter, we highlight the concept of metabolomics workflow and discuss the data analysis strategies for metabolomics experiments. We also discuss the available tools that can assist in biological interpretation of metabolomics data. We also present an emerging approach of developing genome-scale metabolic models to study cellular metabolism.

BACKGROUND: Supplementation of formula with bovine milk fat globule membranes has been shown to narrow the gap in immunological and cognitive development between breast-fed and formula-fed infants. METHOD: In a double-blinded randomized controlled trial 160 formula-fed infants received an experimental formula (EF), supplemented with bovine milk fat globule membranes, or standard formula until 6 months of age. A breast-fed reference group was recruited. Lipidomic analyses were performed on plasma and erythrocyte membranes at 6 months and on serum at 4 and 12 months of age. RESULTS: At 6 months of age, we observed a significant separation in the plasma lipidome between the two formula groups, mostly due to differences in concentrations of sphingomyelins (SM), phosphatidylcholines (PC), and ceramides, and in the erythrocyte membrane lipidome, mostly due to SMs, PEs and PCs. Already at 4 months, a separation in the serum lipidome was evident where SMs and PCs contributed. The separation was not detected at 12 months. CONCLUSIONS: The effect of MFGM supplementation on the lipidome is likely part of the mechanisms behind the positive cognitive and immunological effects of feeding the EF previously reported in the same study population.

Aims Atorvastatin is known to both inhibit and induce the cytochrome P450 3A4 (CYP3A4) enzyme in vitro. Some clinical studies indicate that atorvastatin inhibits CYP3A4 but there are no well-controlled longer term studies that could evaluate the inducing effect of atorvastatin. We aimed to determine if atorvastatin induces or inhibits CYP3A4 activity as measured by the 4β-hydroxycholesterol to cholesterol ratio (4βHC : C).

In this paper, we study fundamental properties of the Self-Organizing Map (SOM) and the Generative Topographic Mapping (GTM), ramifications of the initialization of the algorithms and properties of the algorithms in the presence of missing data. We show that the commonly used principal component analysis (PCA) initialization of the GTM does not guarantee good learning results with high-dimensional data. Initializing the GTM with the SOM is shown to yield improvements in self-organization with three high-dimensional data sets: commonly used MNIST and ISOLET data sets and epigenomic ENCODE data set. We also propose a revision of handling missing data to the batch SOM algorithm called the Imputation SOM and show that the new algorithm is more robust in the presence of missing data. We benchmark the performance of the topographic mappings in the missing value imputation task and conclude that there are better methods for this particular task. Finally, we announce a revised version of the SOM Toolbox for Matlab with added GTM functionality.

Background/Aim Lipidomic and metabolomic techniques become more and more important in human health research. Recent developments in analytical techniques enable the investigation of high amounts of substances. The high numbers of metabolites and lipids that are detected with among others mass spectrometric techniques challenge in most cases the statistical processes to bring out stable and interpretable results. This study targets to use the novel non-established statistical method treelet transform (TT) to investigate high numbers of metabolites and lipids and to compare the results with the established method principal component analysis (PCA). Serum lipid and metabolite profiles are investigated regarding their association to anthropometric parameters associated to obesity. Methods From 226 participants of the EPIC (European Prospective Investigation into Cancer and Nutrition)-Potsdam study blood samples were investigated with an untargeted metabolomics approach regarding serum metabolites and lipids. Additionally, participants were surveyed anthropometrically to assess parameters of obesity, such as body mass index (BMI), waist-to-hip-ratio (WHR) and body fat mass. TT and PCA are used to generate treelet components (TCs) and factors summarizing serum metabolites and lipids in new, latent variables without too much loss of information. With partial correlations TCs and factors were associated to anthropometry under the control for relevant parameters, such as sex and age. Results TT with metabolite variables (p = 121) resulted in 5 stable and interpretable TCs explaining 18.9% of the variance within the data. PCA on the same variables generated 4 quite complex, less easily interpretable factors explaining 37.5% of the variance. TT on lipidomic data (p = 353) produced 3 TCs as well as PCA on the same data resulted in 3 factors; the proportion of explained variance was 17.8% for TT and 39.8% for PCA. In both investigations TT ended up with stable components that are easier to interpret than the factors from the PCA. In general, the generated TCs and factors were similar in their structure when the factors are considered regarding the original variables loading high on them. Both TCs and factors showed associations to anthropometric measures. Conclusions TT is a suitable statistical method to generate summarizing, latent variables in data sets with more variables than observations. In the present investigation it resulted in similar latent variables compared to the established method of PCA. Whereby less variance is explained by the summarizing constructs of TT compared to the factors of PCA, TCs are easier to interpret. Additionally the resulting TCs are quite stable in bootstrap samples.

International audience; Nuclear receptor PPARγ affects lipid metabolism in several tissues, but its role in intestinal lipid metabolism has not been explored. As alterations have been observed in the plasma lipid profile of ad libitum fed intestinal epithelium-specific PPARγ knockout mice (iePPARγKO), we submitted these mice to lipid gavage challenges. Within hours after gavage with long chain unsaturated fatty acid (FA)-rich canola oil, the iePPARγKO mice had higher plasma free FA levels and lower gastric inhibitory polypeptide levels than their wild-type (WT) littermates, and altered expression of incretin genes and lipid metabolism-associated genes in the intestinal epithelium. Gavage with the medium chain saturated FA-rich coconut oil did not result in differences between the two genotypes. Furthermore, the iePPARγKO mice did not exhibit defective lipid uptake and stomach emptying; however, their intestinal transit was more rapid than in WT mice. When fed a canola oil-rich diet for 4.5 months, iePPARγKO mice had higher body lean mass than the WT mice. We conclude that intestinal epithelium PPARγ is activated preferentially by long chain unsaturated FAs compared to medium chain saturated FAs. Furthermore, we hypothesize that the iePPARγKO phenotype originates from altered lipid metabolism and release in epithelial cells, as well as changes in intestinal motility.

To critically review current knowledge on the positive and negative predictive value of blood biomarkers for concussion; to illustrate the clinical and biological contexts that help evaluate the use of these markers in sport-related traumatic brain injuries (TBIs).This systematic review was performed in accordance with PRISMA guidelines. We reviewed the measurement, clinical utility, endpoint, and biological significance of blood biomarkers in concussion.A total of 4352 publications were identified. Twenty-six articles relating to blood biomarkers were included in the review. Four common blood biomarkers, namely S100B, tau, neuron-specific enolase (NSE), and glial fibrillary acidic protein (GFAP), were examined. Overall, the studies showed S100B measurement and use, either acutely or at several time points, can distinguish injured from noninjured patients with an uncertain degree of utility in predicting mortality. At present, S100B has largely become an acceptable biomarker of TBI; however, studies have begun to highlight the need to incorporate clinical symptoms instead of S100B concentration in isolation on the basis of inconsistent results and lack of specificity across published studies. Further research is needed to evaluate and validate the use of tau, NSE, and GFAP as a diagnostic aid in the management of concussion and TBI.At present, blood biomarkers have only a limited role in the evaluation and management of concussion. Although several biomarkers of brain injury have been identified, continued research is required. S100B holds promise as the most clinically useful diagnostic biomarker. Blood biomarkers, in combination with other clinical data, such as head computed tomography, would maximize the diagnostic accuracy. The methodological limitations evident in blood biomarker research results in the need for the clinical utility of blood biomarker use in concussion to be further explored.

The identification of an early biomarker of psychotic disorder is important as early treatment is associated with improved patient outcome. Metabolomic and lipidomic approaches in combination with multivariate statistical analysis were applied to identify plasma alterations in children (age 11) (38 cases vs 67 controls) and adolescents (age 18) (36 cases vs 117 controls) preceeding or coincident with the development of psychotic disorder (PD) at age 18 in the Avon Longitudinal Study of Parents and Children (ALSPAC). Overall, 179 lipids were identified at age 11, with 32 found to be significantly altered between the control and PD groups. Following correction for multiple comparisons, 8 of these lipids remained significant (lysophosphatidlycholines (LPCs) LPC(18:1), LPC(18:2), LPC(20:3); phosphatidlycholines (PCs) PC(32:2; PC(34:2), PC(36:4), PC(0-34-3) and sphingomyelin (SM) SM(d18:1/24:0)), all of which were elevated in the PD group. At age 18, 23 lipids were significantly different between the control and PD groups, although none remained significant following correction for multiple comparisons. In conclusion, the findings indicate that the lipidome is altered in the blood during childhood, long before the development of psychotic disorder. LPCs in particular are elevated in those who develop PD, indicating inflammatory abnormalities and altered phospholipid metabolism. These findings were not found at age 18, suggesting there may be ongoing alterations in the pathophysiological processes from prodrome to onset of PD. European Research Council Health Research Board Wellcome Trust UK Medical Council

Progression to AD is preceded by elevated levels of 2,4-dihydroxybutanoic acid (2,4-DHB), implicating hypoxia in early pathogenesis. Since hypoxia may play a role in multiple CNS disorders, we investigated serum metabolite profiles across three disorders, AD, Normal Pressure Hydrocephalus (NPH) and brain tumors (BT). Blood samples were collected from 27 NPH and 20 BT patients. The profiles of 21 metabolites were examined. Additionally, data from 37 AD patients and 46 controls from a previous study were analyzed together with the newly acquired data. No differences in 2,4-DHB were found across AD, NPH and BT samples. In the BT group, the fatty acids were increased as compared to HC and NPH groups, while the ketone body 3-hydroxybutyrate was increased as compared to AD. Glutamic acid was increased in AD as compared to the HC group. In the AD group, 3-hydroxybutyrate tended to be decreased with respect to all other groups (mean values −30% or more), but the differences were not statistically significant. Serine was increased in NPH as compared to BT. In conclusion, AD, NPH and BT have different metabolic profiles. This preliminary study may help in identifying the blood based markers that are specific to these three CNS diseases.

Summary Thyroid hormones (THs) act in the brain to modulate energy balance. We show that central triiodothyronine (T3) regulates de novo lipogenesis in liver and lipid oxidation in brown adipose tissue (BAT) through the parasympathetic (PSNS) and sympathetic nervous system (SNS), respectively. Central T3 promotes hepatic lipogenesis with parallel stimulation of the thermogenic program in BAT. The action of T3 depends on AMP-activated protein kinase (AMPK)-induced regulation of two signaling pathways in the ventromedial nucleus of the hypothalamus (VMH): decreased ceramide-induced endoplasmic reticulum (ER) stress, which promotes BAT thermogenesis, and increased c-Jun N-terminal kinase (JNK) activation, which controls hepatic lipid metabolism. Of note, ablation of AMPKα1 in steroidogenic factor 1 (SF1) neurons of the VMH fully recapitulated the effect of central T3, pointing to this population in mediating the effect of central THs on metabolism. Overall, these findings uncover the underlying pathways through which central T3 modulates peripheral metabolism., Graphical Abstract, Highlights • Central T3 regulates lipogenesis in liver via the parasympathetic nervous system • Central T3 regulates lipid oxidation in BAT via the sympathetic nervous system • Ablation of AMPK in SF1 neurons of the VMH recapitulates the effects of T3 • Hypothalamic JNK1 and ceramides/ER stress mediate T3 actions on liver and BAT, Martínez-Sánchez et al. show that thyroid hormones act in the hypothalamus to regulate hepatic lipogenesis and brown fat lipid oxidation via the parasympathetic and sympathetic nervous systems. These peripheral effects are orchestrated by two distinct signaling pathways in the VMH, JNK1 and ceramides/ER stress, which are under AMPK control.

Statins are the frontline in cholesterol reduction therapies; however, their use in combination with agents that possess complimentary mechanisms of action may achieve further reductions in low-density lipoprotein cholesterol. Thirty-nine patients were treated with either 80 mg simvastatin (n=20) or 10 mg simvastatin plus 10 mg ezetimibe (n=19) for 6 weeks. Dosing was designed to produce comparable low-density lipoprotein cholesterol reductions, while enabling assessment of potential simvastatin-associated pleiotropic effects. Baseline and post-treatment plasma were analyzed for lipid mediators (eg, eicosanoids and endocannabinoids) and structural lipids by liquid chromatography tandem mass spectrometry. After statistical analysis and orthogonal projections to latent structures multivariate modeling, no changes were observed in lipid mediator levels, whereas global structural lipids were reduced in response to both monotherapy ( R 2 Y =0.74; Q 2 =0.66; cross-validated ANOVA P =7.0×10 −8 ) and combination therapy ( R 2 Y =0.67; Q 2 =0.54; cross-validated ANOVA P =2.6×10 −5 ). Orthogonal projections to latent structures modeling identified a subset of 12 lipids that classified the 2 treatment groups after 6 weeks ( R 2 Y =0.65; Q 2 =0.61; cross-validated ANOVA P =5.4×10 −8 ). Decreases in the lipid species phosphatidylcholine (15:0/18:2) and hexosyl-ceramide (d18:1/24:0) were the strongest discriminators of low-density lipoprotein cholesterol reductions for both treatment groups ( q q =0.017). Shifts in lipid composition were similar for high-dose simvastatin and simvastatin/ezetimibe combination therapy, but the magnitude of the reduction was linked to simvastatin dosage. Simvastatin therapy did not affect circulating levels of lipid mediators, suggesting that pleiotropic effects are not associated with eicosanoid production. Only high-dose simvastatin reduced the relative proportion of sphingomyelin and ceramide to phosphatidylcholine ( q =0.008), suggesting a pleiotropic effect previously associated with a reduced risk of cardiovascular disease.

International audience; Clinical trials are needed to confirm the association between polyphenol consumption and lower incidence of chronic diseases observed in epidemiological studies. However, a reliable evaluation of polyphenol intake is complicated. An 8-week randomized controlled trial (78 subjects) was performed using two isoenergetic diets differing only for polyphenol contents. Then, urinary phenolic metabolite profiles were analysed using gas-chromatography with mass detection. Phenolic metabolites detected in 24-h-urine were hydroxylated phenolic acids with C1-C3 side chain in the group consuming polyphenol-rich diet. The intake of polyphenol-rich foods increases the excretion of phenolic metabolites in urine providing a profile, which may serve as compliance biomarker of polyphenol-rich diet.

Aims/hypothesis: Not all obese individuals display the metabolic disturbances commonly associated with excess fat accumulation. Mechanisms maintaining this ‘metabolically healthy obesity’ (MHO) are as yet unknown. We aimed to study different fat depots and transcriptional pathways in subcutaneous adipose tissue (SAT) as related to the MHO phenomenon. Methods: Sixteen rare young adult obesity-discordant monozygotic (MZ) twin pairs (intra-pair difference (∆) in BMI ≥3 kg/m2), aged 22.8–35.8 years, were examined for detailed characteristics of metabolic health (subcutaneous, intra-abdominal and liver fat [magnetic resonance imaging/spectroscopy]), OGTT, lipids, adipokines and C-reactive protein (CRP). Affymetrix U133 Plus 2.0 chips were used to analyse transcriptomics pathways related to mitochondrial function and inflammation in SAT. Results: Based on liver fat accumulation, two metabolically different subgroups emerged. In half (8/16) of the pairs (∆weight 17.1 ± 2.0 kg), the obese co-twin had significantly higher liver fat (∆718%), 78% increase in AUC insulin during OGTT and CRP, significantly more disturbance in the lipid profile and greater tendency for hypertension compared with the lean co-twin. In these obese co-twins, SAT expression of mitochondrial oxidative phosphorylation, branched-chain amino acid catabolism, fatty acid oxidation and adipocyte differentiation pathways were downregulated and chronic inflammation upregulated. In the other eight pairs (∆weight 17.4 ± 2.8 kg), the obese co-twin did not differ from the non-obese co-twin in liver fat (∆8%), insulin sensitivity, CRP, lipids, blood pressure or SAT transcriptomics. Conclusions/interpretation: Our results suggest that maintenance of high mitochondrial transcription and lack of inflammation in SAT are associated with low liver fat and MHO., Cited By :56; Export Date: 12 March 2018; ArticleFunding Agencies:Helsinki University Central HospitalBiomedicum HelsinkiJalmari and Rauha Ahokas (KHP)Finnish Medical Foundations Finnish Foundation for Cardiovascular Research Competitive Research Funding of the Pirkanmaa Hospital DistrictAcademy of Finland Centre of Excellence in Complex Disease GeneticsNational Institute of Alcohol Abuse and Alcoholism

Changes in cellular lipid metabolism are a common feature in most solid tumors, which occur already in early stages of the tumor progression. However, it remains unclear if the tumor-specific lipid changes can be detected at the level of systemic lipid metabolism. The objective of this study was to perform comprehensive analysis of lipids in breast cancer patient serum samples. Lipidomic profiling using an established analytical platform was performed in two cohorts of breast cancer patients receiving neoadjuvant chemotherapy. The analyses were performed for 142 patients before and after neoadjuvant chemotherapy, and the results before chemotherapy were validated in an independent cohort of 194 patients. The analyses revealed that in general the tumor characteristics are not reflected in the serum samples. However, there was an association of specific triacylglycerols (TGs) in patients' response to chemotherapy. These TGs containing mainly oleic acid (C18:1) were found in lower levels in those patients showing pathologic complete response before receiving chemotherapy. Some of these TGs were also associated with estrogen receptor status and overall or disease-free survival of the patients. The results suggest that the altered serum levels of oleic acid in breast cancer patients are associated with their response to chemotherapy.

The epidemic of obesity imposes unprecedented challenges on human adipose tissue (WAT) storage capacity that may benefit from adaptive mechanisms to maintain adipocyte functionality. Here, we demonstrate that changes in the regulatory feedback set point control of Insig1/SREBP1 represent an adaptive response that preserves WAT lipid homeostasis in obese and insulin-resistant states. In our experiments, we show that Insig1 mRNA expression decreases in WAT from mice with obesity-associated insulin resistance and from morbidly obese humans and in in vitro models of adipocyte insulin resistance. Insig1 downregulation is part of an adaptive response that promotes the maintenance of SREBP1 maturation and facilitates lipogenesis and availability of appropriate levels of fatty acid unsaturation, partially compensating the antilipogenic effect associated with insulin resistance. We describe for the first time the existence of this adaptive mechanism in WAT, which involves Insig1/SREBP1 and preserves the degree of lipid unsaturation under conditions of obesity-induced insulin resistance. These adaptive mechanisms contribute to maintain lipid desaturation through preferential SCD1 regulation and facilitate fat storage in WAT, despite on-going metabolic stress., Funding agencies:MRC Biotechnology and Biological Sciences Research CouncilEuropean Foundation for the Study of DiabetesIntegrative Pharmacology FundFritz Thyssen Foundation fellowship (Germany)National Institute for Health Research

Objective— Low high-density lipoprotein cholesterol (HDL-C) is associated with cardiometabolic pathologies. In this study, we investigate the biological pathways and individual genes behind low HDL-C by integrating results from 3 high-throughput data sources: adipose tissue transcriptomics, HDL lipidomics, and dense marker genotypes from Finnish individuals with low or high HDL-C (n=450). Approach and Results— In the pathway analysis of genetic data, we demonstrate that genetic variants within inflammatory pathways were enriched among low HDL-C associated single-nucleotide polymorphisms, and the expression of these pathways upregulated in the adipose tissue of low HDL-C subjects. The lipidomic analysis highlighted the change in HDL particle quality toward putatively more inflammatory and less vasoprotective state in subjects with low HDL-C, as evidenced by their decreased antioxidative plasmalogen contents. We show that the focal point of these inflammatory pathways seems to be the HLA region with its low HDL-associated alleles also associating with more abundant local transcript levels in adipose tissue, increased plasma vascular cell adhesion molecule 1 (VCAM1) levels, and decreased HDL particle plasmalogen contents, markers of adipose tissue inflammation, vascular inflammation, and HDL antioxidative potential, respectively. In a population-based look-up of the inflammatory pathway single-nucleotide polymorphisms in a large Finnish cohorts (n=11 211), no association of the HLA region was detected for HDL-C as quantitative trait, but with extreme HDL-C phenotypes, implying the presence of low or high HDL genes in addition to the population-genomewide association studies–identified HDL genes. Conclusions— Our study highlights the role of inflammation with a genetic component in subjects with low HDL-C and identifies novel cis -expression quantitative trait loci ( cis -eQTL) variants in HLA region to be associated with low HDL-C.

Children developing type 1 diabetes may have risk markers already in their umbilical cord blood. It is hypothesized that the risk for type 1 diabetes at an early age may be increased by a pathogenic pregnancy and be reflected in altered cord-blood composition. This study used metabolomics to test if the cord-blood lipidome was affected in children diagnosed with type 1 diabetes before 8 years of age. The present case-control study of 76 index children diagnosed with type 1 diabetes before 8 years of age and 76 healthy control subjects matched for HLA risk, sex, and date of birth, as well as the mother's age and gestational age, revealed that cord-blood phosphatidylcholines and phosphatidylethanolamines were significantly decreased in children diagnosed with type 1 diabetes before 4 years of age. Reduced levels of triglycerides correlated to gestational age in index and control children and to age at diagnosis only in the index children. Finally, gestational infection during the first trimester was associated with lower cord-blood total lysophosphatidylcholines in index and control children. In conclusion, metabolomics of umbilical cord blood may identify children at increased risk for type 1 diabetes. Low phospholipid levels at birth may represent key mediators of the immune system and contribute to early induction of islet autoimmunity., Funding agencies:Lund University Diabetes CentreAcademy of FinlandCentre of Excellence in Molecular Systems Immunology and Physiology Research 2012-2017 250114Childhood Diabetes FoundationSkane County Council for Research and DevelopmentUMAS Funds

Lipids have many central physiological roles including as structural components of cell membranes, energy storage sources and intermediates in signaling pathways. Lipid-related disturbances are known to underlie many diseases and their co-morbidities. The emergence of lipidomics has empowered researchers to study lipid metabolism at the cellular as well as physiological levels at a greater depth than was previously possible. The key challenges ahead in the field of lipidomics in medical research lie in the development of experimental protocols and in silico techniques needed to study lipidomes at the systems level. Clinical questions where lipidomics may have an impact in healthcare settings also need to be identified, both from the health outcomes and health economics perspectives. This article is part of a Special Issue entitled: BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

The MBOAT7 variant rs641738 alters hepatic phosphatidylinositols and increases severity of non-alcoholic fatty liver disease in humans

Background There is a need for early markers to track and predict the development of type 2 diabetes mellitus (T2DM) from the state of normal glucose tolerance through prediabetes. In this study we tested whether the plasma molecular lipidome has biomarker potential to predicting the onset of T2DM. Methods We applied global lipidomic profiling on plasma samples from well-phenotyped men (107 cases, 216 controls) participating in the longitudinal METSIM study at baseline and at five-year follow-up. To validate the lipid markers, an additional study with a representative sample of adult male population (n = 631) was also conducted. A total of 277 plasma lipids were analyzed using the lipidomics platform based on ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry. Lipids with the highest predictive power for the development of T2DM were computationally selected, validated and compared to standard risk models without lipids. Results A persistent lipid signature with higher levels of triacylglycerols and diacyl-phospholipids as well as lower levels of alkylacyl phosphatidylcholines was observed in progressors to T2DM. Lysophosphatidylcholine acyl C18:2 (LysoPC(18:2)), phosphatidylcholines PC(32:1), PC(34:2e) and PC(36:1), and triacylglycerol TG(17:1/18:1/18:2) were selected to the full model that included metabolic risk factors and FINDRISC variables. When further adjusting for BMI and age, these lipids had respective odds ratios of 0.32, 2.4, 0.50, 2.2 and 0.31 (all p < 0.05) for progression to T2DM. The independently-validated predictive power improved in all pairwise comparisons between the lipid model and the respective standard risk model without the lipids (integrated discrimination improvement IDI > 0; p < 0.05). Notably, the lipid models remained predictive of the development of T2DM in the fasting plasma glucose-matched subset of the validation study. Conclusion This study indicates that a lipid signature characteristic of T2DM is present years before the diagnosis and improves prediction of progression to T2DM. Molecular lipid biomarkers were shown to have predictive power also in a high-risk group, where standard risk factors are not helpful at distinguishing progressors from non-progressors., published version, peerReviewed

Background & Aims\ud \ud Use of targeted mass spectrometry (MS)-based methods is increasing in clinical chemistry laboratories. We investigate whether MS-based profiling of plasma improves noninvasive risk estimates of nonalcoholic steatohepatitis (NASH) compared with routinely available clinical parameters and patatin-like phospholipase domain-containing protein 3 (PNPLA3) genotype at rs738409.\ud \ud Methods\ud \ud We used MS-based analytic platforms to measure levels of lipids and metabolites in blood samples from 318 subjects who underwent a liver biopsy because of suspected NASH. The subjects were divided randomly into estimation (n = 223) and validation (n = 95) groups to build and validate the model. Gibbs sampling and stepwise logistic regression, which fulfilled the Bayesian information criterion, were used for variable selection and modeling.\ud \ud Results\ud \ud Features of the metabolic syndrome and the variant in PNPLA3 encoding I148M were significantly more common among subjects with than without NASH. We developed a model to identify subjects with NASH based on clinical data and PNPLA3 genotype (NASH Clin Score), which included aspartate aminotransferase (AST), fasting insulin, and PNPLA3 genotype. This model identified subjects with NASH with an area under the receiver operating characteristic of 0.792 (95% confidence interval, 0.726–0.859). We then used backward stepwise logistic regression analyses of variables from the NASH Clin Score and MS-based factors associated with NASH to develop the NASH ClinLipMet Score. This included glutamate, isoleucine, glycine, lysophosphatidylcholine 16:0, phosphoethanolamine 40:6, AST, and fasting insulin, along with PNPLA3 genotype. It identified patients with NASH with an area under the receiver operating characteristic of 0.866 (95% confidence interval, 0.820–0.913). The NASH ClinLipMet score identified patients with NASH with significantly higher accuracy than the NASH Clin Score or MS-based profiling alone.\ud \ud Conclusions\ud \ud A score based on MS (glutamate, isoleucine, glycine, lysophosphatidylcholine 16:0, phosphoethanolamine 40:6) and knowledge of AST, fasting insulin, and PNPLA3 genotype is significantly better than a score based on clinical or metabolic profiles alone in determining the risk of NASH.

Article, Sleep loss and insufficient sleep are risk factors for cardiometabolic diseases, but data on how insufficient sleep contributes to these diseases are scarce. These questions were addressed using two approaches: an experimental, partial sleep restriction study (14 cases and 7 control subjects) with objective verification of sleep amount, and two independent epidemiological cohorts (altogether 2739 individuals) with questions of sleep insufficiency. In both approaches, blood transcriptome and serum metabolome were analysed. Sleep loss decreased the expression of genes encoding cholesterol transporters and increased expression in pathways involved in inflammatory responses in both paradigms. Metabolomic analyses revealed lower circulating large HDL in the population cohorts among subjects reporting insufficient sleep, while circulating LDL decreased in the experimental sleep restriction study. These findings suggest that prolonged sleep deprivation modifies inflammatory and cholesterol pathways at the level of gene expression and serum lipoproteins, inducing changes toward potentially higher risk for cardiometabolic diseases., published version, peerReviewed

Non-alcoholic fatty liver disease (NAFLD) is a major risk factor leading to chronic liver disease and type 2 diabetes. Here we chart liver metabolic activity and functionality in NAFLD by integrating global transcriptomic data, from human liver biopsies, and metabolic flux data, measured across the human splanchnic vascular bed, within a genome-scale model of human metabolism. We show that an increased amount of liver fat induces mitochondrial metabolism, lipolysis, glyceroneogenesis and a switch from lactate to glycerol as substrate for gluconeogenesis, indicating an intricate balance of exacerbated opposite metabolic processes in glycemic regulation. These changes were associated with reduced metabolic adaptability on a network level in the sense that liver fat accumulation puts increasing demands on the liver to adaptively regulate metabolic responses to maintain basic liver functions. We propose that failure to meet excessive metabolic challenges coupled with reduced metabolic adaptability may lead to a vicious pathogenic cycle leading to the co-morbidities of NAFLD., Non-alcoholic fatty liver disease (NAFLD) is a risk factor for other types of liver diseases. Here, the authors integrate transcriptomic and metabolomic data from patients with NAFLD with a genome-scale metabolic model to paint a comprehensive picture of liver function in NAFLD.

Studies on metabolism of polyphenols have revealed extensive transformations in the carbon backbone by colonic microbiota; however, the influence of microbial and hepatic transformations on human urinary metabolites has not been explored. Therefore, the aims of this study were (1) to compare the in vitro microbial phenolic metabolite profile of foods and beverages with that excreted in urine of subjects consuming the same foodstuff and (2) to explore the role of liver on postcolonic metabolism of polyphenols by using in vitro hepatic models. A 24-h urinary phenolic metabolite profile was evaluated in 72 subjects participating in an 8-week clinical trial during which they were randomly assigned to diets differing for polyphenol content. Polyphenol-rich foods and beverages used in the clinical trial were subjected to human fecal microbiota in the in vitro colon model. Metabolites from green tea, one of the main components of the polyphenol-rich diet, were incubated with primary hepatocytes to highlight hepatic conversion of polyphenols. The analyses were performed using targeted gas chromatography with mass spectrometer (GCxGC-TOFMS:colon model; GC-MS: urine and hepatocytes). A significant correlation was found between urinary and colonic metabolites with C1-C3 side chain (P=.040). However, considerably higher amounts of hippuric acid, 3-hydroxybenzoic acid and ferulic acid were detected in urine than in the colon model. The hepatic conversion showed additional amounts of these metabolites complementing the gap between in vitro colon model and the in vivo urinary excretion. Therefore, combining in vitro colon and hepatic models may better elucidate the metabolism of polyphenols from dietary exposure to urinary metabolites. . KEYWORDS: In vitro colon model; Metabolism; Phenolic carbon backbone; Polyphenols; Primary hepatocytes

Aims/hypothesisVirally induced inflammatory responses, beta cell destruction and release of beta cell autoantigens may lead to autoimmune reactions culminating in type 1 diabetes. Therefore, viral capability to induce beta cell death and the nature of virus-induced immune responses are among key determinants of diabetogenic viruses. We hypothesised that enterovirus infection induces a specific gene expression pattern that results in islet destruction and that such a host response pattern is not shared among all enterovirus infections but varies between virus strains.MethodsThe changes in global gene expression and secreted cytokine profiles induced by lytic or benign enterovirus infections were studied in primary human pancreatic islet using DNA microarrays and viral strains either isolated at the clinical onset of type 1 diabetes or capable of causing a diabetes-like condition in mice.ResultsThe expression of pro-inflammatory cytokine genes (IL-1-α, IL-1-β and TNF-α) that also mediate cytokine-induced beta cell dysfunction correlated with the lytic potential of a virus. Temporally increasing gene expression levels of double-stranded RNA recognition receptors, antiviral molecules, cytokines and chemokines were detected for all studied virus strains. Lytic coxsackievirus B5 (CBV-5)-DS infection also downregulated genes involved in glycolysis and insulin secretion.Conclusions/interpretationThe results suggest a distinct, virus-strain-specific, gene expression pattern leading to pancreatic islet destruction and pro-inflammatory effects after enterovirus infection. However, neither viral replication nor cytotoxic cytokine production alone are sufficient to induce necrotic cell death. More likely the combined effect of these and possibly cellular energy depletion lie behind the enterovirus-induced necrosis of islets.

Summary Individuals with metabolic syndrome are at high risk of developing chronic kidney disease (CKD) through unclear pathogenic mechanisms. Obesity and diabetes are known to induce glucolipotoxic effects in metabolically relevant organs. However, the pathogenic role of glucolipotoxicity in the aetiology of diabetic nephropathy is debated. We generated a murine model, the POKO mouse, obtained by crossing the peroxisome proliferator-activated receptor gamma 2 (PPARγ2) knockout (KO) mouse into a genetically obese ob/ob background. We have previously shown that the POKO mice showed: hyperphagia, insulin resistance, hyperglycaemia and dyslipidaemia as early as 4 weeks of age, and developed a complete loss of normal β-cell function by 16 weeks of age. Metabolic phenotyping of the POKO model has led to investigation of the structural and functional changes in the kidney and changes in blood pressure in these mice. Here we demonstrate that the POKO mouse is a model of renal disease that is accelerated by high levels of glucose and lipid accumulation. Similar to ob/ob mice, at 4 weeks of age these animals exhibited glomerulomegaly, an increased urinary albumin:creatinine ratio and significantly increased blood pressure, but in contrast showed a significant increase in the renal hypertrophy index and an associated increase in p27Kip1 expression compared with their obese littermates. Moreover, at 4 weeks of age POKO mice showed insulin resistance, an alteration of lipid metabolism and glomeruli damage associated with significantly increased transforming growth factor beta (TGFβ) and parathyroid hormone-related protein (PTHrP) expression. At this age, levels of proinflammatory molecules, such as monocyte chemoattractant protein-1 (MCP-1), and fibrotic factors were also increased at the glomerular level compared with levels in ob/ob mice. At 12 weeks of age, renal damage was fully established. These data suggest an accelerated lesion through glucolipotoxic effects in the renal pathogenesis in POKO mice.

Optimal lipid storage and mobilization are essential for efficient adipose tissue. Nuclear receptor peroxisome proliferator-activated receptor γ (PPARγ) regulates adipocyte differentiation and lipid deposition, but its role in lipolysis and dysregulation in obesity is not well defined. This investigation aimed to understand the molecular impact of dysfunctional PPARγ on the lipolytic axis and to explore whether these defects are also confirmed in common forms of human obesity. For this purpose, we used the P465L PPARγ mouse as a model of dysfunctional PPARγ that recapitulates the human pparγ mutation (P467L). We demonstrated that defective PPARγ impairs catecholamine-induced lipolysis. This abnormal lipolytic response is exacerbated by a state of positive energy balance in leptin-deficient ob/ob mice. We identified the protein kinase A (PKA) network as a PPARγ-dependent regulatory node of the lipolytic response. Specifically, defective PPARγ is associated with decreased basal expression of prkaca (PKAcatα) and d-akap1, the lipase genes Pnplaz (ATGL) and Lipe (HSL), and lipid droplet protein genes fsp27 and adrp in vivo and in vitro. Our data indicate that PPARγ is required for activation of the lipolytic regulatory network, dysregulation of which is an important feature of obesity-induced insulin resistance in humans.

Breast cancer is the most frequent cancer and the leading cause of cancer‐related deaths in women worldwide. The prognosis of breast cancer is tightly correlated with the degree of spread beyond the primary tumour. Arachidonic acid (AA) and prostaglandin E2 (PGE2) are known to regulate tumour metastasis enabling epithelial–mesenchymal transition (EMT). However, the detailed role of 15‐hydroxyprostaglandin dehydrogenase (HPGD), the key enzyme degrading prostaglandin E2, remains unclear in breast cancer. Here, we show that HPGD mRNA is overexpressed in a subset of clinical breast cancers compared to normal breast tissue samples and that high HPGD mRNA expression associates with poor prognosis. Immunohistochemical staining of primary breast cancer and lymph node metastasis tissue samples confirmed high HPGD protein expression in 20% of the samples, as well as associated HPGD expression with aggressive characteristics, such as increased risk of disease relapse and shorter disease‐free survival. Results from cultured cells indicated abundant HPGD expression in highly metastatic breast cancer cells, and impairment of HPGD expression using RNA interference led to a significant decrease in transforming growth factor‐β signalling, in cellular arachidonic acid levels as well as in cell migration. Furthermore, gene expression microarray analysis followed by quantitative RT‐PCR validation showed that HPGD silencing decreased aryl hydrocarbon receptor signalling and induced mesenchymal‐epithelial transition. In conclusion, our results indicate that HPGD is highly expressed in metastatic and aggressive breast cancer and promotes EMT and migration in breast cancer cells.

The metabolome is sensitive to genetic and environmental factors contributing to complex diseases such as type 1 diabetes (T1D). Metabolomics is the study of biochemical and physiological processes involving metabolites. It is therefore one of the key platforms for the discovery and study of pathophysiological phenomena leading to T1D and the development of T1D-associated complications. Although the application of metabolomics in T1D research is still rare, metabolomic research has already advanced across the full spectrum, from disease progression to the development of diabetic complications. Metabolomic studies in T1D have contributed to an improved etiopathogenic understanding and demonstrated their potential in the clinic. For example, metabolomic data from recent T1D studies suggest that a specific metabolic profile, or metabotype, precedes islet autoimmunity and the development of overt T1D. These early metabolic changes are attributed to many biochemical pathways, thus suggesting a systemic change in metabolism which may be inborn. Based on this evidence, the role of the metabolome in the progression to T1D is therefore to facilitate specific biochemical processes associated with T1D, and to contribute to the development of a vulnerable state in which disease is more likely to be triggered. This may have important implications for the understanding of T1D pathophysiology and early disease detection and prevention.

Paula Vainio 1 , Laura Lehtinen 1 , Tuomas Mirtti 2,3,4 , Mika Hilvo 5 , Tuulikki Seppanen-Laakso 5 , Johannes Virtanen 1 , Anna Sankila 4 , Stig Nordling 4 , Johan Lundin 3 , Antti Rannikko 6 , Matej Oresic 5 , Olli Kallioniemi 1,3 and Kristiina Iljin 1 1 Medical Biotechnology, VTT Technical Research Centre of Finland, and Turku Centre for Biotechnology, University of Turku, Finland 2 Haartman Institute, Department of Pathology, University of Helsinki, Finland 3 Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland 4 HUSLAB, Department of Pathology, Helsinki University Central Hospital, Finland 5 Bio and Process Technology, VTT Technical Research Centre of Finland, Espoo, Finland 6 Department of Urology, Helsinki University Central Hospital, Finland Received: December 20, 2011; Accepted: December 22, 2011; Published: December 22, 2011; Keywords: Prostate cancer, PLA2G7, drug target, biomarker, statins Correspondence: Kristiina Iljin, email: // // Abstract Prostate cancer is the second leading cause of cancer mortality in men in developed countries. Due to the heterogeneous nature of the disease, design of novel personalized treatments is required to achieve efficient therapeutic responses. We have recently identified phospholipase 2 group VII ( PLA2G7 ) as a potential drug target especially in ERG oncogene positive prostate cancers. Here, the expression profile of PLA2G7 was studied in 1137 prostate cancer and 409 adjacent non-malignant prostate tissues using immunohistochemistry to validate its biomarker potential and putative association with disease progression. In order to reveal the molecular alterations induced by PLA2G7 impairment, lipidomic and gene expression profiling was performed in response to PLA2G7 silencing in cultured prostate cancer cells. Moreover, the antineoplastic effect of statins combined with PLA2G7 impairment was studied in prostate cancer cells to evaluate the potential of repositioning of in vivo compatible drugs developed for other indications towards anti-cancer purposes. The results indicated that PLA2G7 is a cancer-selective biomarker in 50 % of prostate cancers and associates with aggressive disease. The alterations induced by PLA2G7 silencing highlighted the potential of PLA2G7 inhibition as an anti-proliferative, pro-apoptotic and anti-migratorial therapeutic approach in prostate cancer. Moreover, the anti-proliferative effect of PLA2G7 silencing was potentiated by lipid-lowering statins in prostate cancer cells. Taken together, our results support the potential of PLA2G7 as a biomarker and a drug target in prostate cancer and present a rationale for combining PLA2G7 inhibition with the use of statins in prostate cancer management.

Changes in lipid metabolism are an important but not well-characterized hallmark of cancer. On the basis of our recent findings of lipidomic changes in breast cancer, we investigated glycerol-3-phosphate acyltransferase (GPAM), a key enzyme in the lipid biosynthesis of triacylglycerols and phospholipids. GPAM protein expression was evaluated and linked to metabolomic and lipidomic profiles in a cohort of human breast carcinomas. In addition, GPAM mRNA expression was analyzed using the GeneSapiens in silico transcriptiomics database. High cytoplasmic GPAM expression was associated with hormone receptor negative status (p = 0.013). On the protein (p = 0.048) and mRNA (p = 0.001) levels, increased GPAM expression was associated with a better overall survival. Metabolomic analysis by GC-MS showed that sn-glycerol-3-phosphate, the substrate of GPAM, was elevated in breast cancer compared to normal breast tissue. LC-MS based lipidomic analysis identified significantly higher levels of phospholipids, especially phosphatidylcholines in GPAM protein positive tumors. In conclusion, our results suggest that GPAM is expressed in human breast cancer with associated changes in the cellular metabolism, in particular an increased synthesis of phospholipids, the major structural component of cellular membranes.

AimsPeroxisome proliferator-activated receptor-γ coactivators PGC1α and PGC1β modulate mitochondrial biogenesis and energy homeostasis. The function of these transcriptional coactivators is impaired in obesity, insulin resistance, and type 2 diabetes. We searched for transcriptomic, lipidomic, and electrophysiological alterations in PGC1β−/− hearts potentially associated with increased arrhythmic risk in metabolic diseases.Methods and resultsMicroarray analysis in mouse PGC1β−/− hearts confirmed down-regulation of genes related to oxidative phosphorylation and the electron transport chain and up-regulation of hypertrophy- and hypoxia-related genes. Lipidomic analysis showed increased levels of the pro-arrhythmic and pro-inflammatory lipid, lysophosphatidylcholine. PGC1β−/− mouse electrocardiograms showed irregular heartbeats and an increased incidence of polymorphic ventricular tachycardia following isoprenaline infusion. Langendorff-perfused PGC1β−/− hearts showed action potential alternans, early after-depolarizations, and ventricular tachycardia. PGC1β−/− ventricular myocytes showed oscillatory resting potentials, action potentials with early and delayed after-depolarizations, and burst firing during sustained current injection. They showed abnormal diastolic Ca2+ transients, whose amplitude and frequency were increased by isoprenaline, and Ca2+ currents with negatively shifted inactivation characteristics, with increased window currents despite unaltered levels of CACNA1C RNA transcripts. Inwardly and outward rectifying K+ currents were all increased. Quantitiative RT-PCR demonstrated increased SCN5A, KCNA5, RYR2, and Ca2+-calmodulin dependent protein kinase II expression.ConclusionPGC1β−/− hearts showed a lysophospholipid-induced cardiac lipotoxicity and impaired bioenergetics accompanied by an ion channel remodelling and altered Ca2+ homeostasis, converging to produce a ventricular arrhythmic phenotype particularly during adrenergic stress. This could contribute to the increased cardiac mortality associated with both metabolic and cardiac disease attributable to lysophospholipid accumulation.

Infantile cardiomyopathies are devastating fatal disorders of the neonatal period or the first year of life. Mitochondrial dysfunction is a common cause of this group of diseases, but the underlying gene defects have been characterized in only a minority of cases, because tissue specificity of the manifestation hampers functional cloning and the heterogeneity of causative factors hinders collection of informative family materials. We sequenced the exome of a patient who died at the age of 10 months of hypertrophic mitochondrial cardiomyopathy with combined cardiac respiratory chain complex I and IV deficiency. Rigorous data analysis allowed us to identify a homozygous missense mutation in AARS2, which we showed to encode the mitochondrial alanyl-tRNA synthetase (mtAlaRS). Two siblings from another family, both of whom died perinatally of hypertrophic cardiomyopathy, had the same mutation, compound heterozygous with another missense mutation. Protein structure modeling of mtAlaRS suggested that one of the mutations affected a unique tRNA recognition site in the editing domain, leading to incorrect tRNA aminoacylation, whereas the second mutation severely disturbed the catalytic function, preventing tRNA aminoacylation. We show here that mutations in AARS2 cause perinatal or infantile cardiomyopathy with near-total combined mitochondrial respiratory chain deficiency in the heart. Our results indicate that exome sequencing is a powerful tool for identifying mutations in single patients and allows recognition of the genetic background in single-gene disorders of variable clinical manifestation and tissue-specific disease. Furthermore, we show that mitochondrial disorders extend to prenatal life and are an important cause of early infantile cardiac failure.

Activation of lipid metabolism is an early event in carcinogenesis and a central hallmark of many cancers. However, the precise molecular composition of lipids in tumors remains generally poorly characterized. The aim of the present study was to analyze the global lipid profiles of breast cancer, integrate the results to protein expression, and validate the findings by functional experiments. Comprehensive lipidomics was conducted in 267 human breast tissues using ultraperformance liquid chromatography/ mass spectrometry. The products of de novo fatty acid synthesis incorporated into membrane phospholipids, such as palmitate-containing phosphatidylcholines, were increased in tumors as compared with normal breast tissues. These lipids were associated with cancer progression and patient survival, as their concentration was highest in estrogen receptor–negative and grade 3 tumors. In silico transcriptomics database was utilized in investigating the expression of lipid metabolism related genes in breast cancer, and on the basis of these results, the expression of specific proteins was studied by immunohistochemistry. Immunohistochemical analyses showed that several genes regulating lipid metabolism were highly expressed in clinical breast cancer samples and supported also the lipidomics results. Gene silencing experiments with seven genes [ACACA (acetyl-CoA carboxylase α), ELOVL1 (elongation of very long chain fatty acid–like 1), FASN (fatty acid synthase), INSIG1 (insulin-induced gene 1), SCAP (sterol regulatory element–binding protein cleavage–activating protein), SCD (stearoyl-CoA desaturase), and THRSP (thyroid hormone–responsive protein)] indicated that silencing of multiple lipid metabolism–regulating genes reduced the lipidomic profiles and viability of the breast cancer cells. Taken together, our results imply that phospholipids may have diagnostic potential as well as that modulation of their metabolism may provide therapeutic opportunities in breast cancer treatment. Cancer Res; 71(9); 3236–45. ©2011 AACR.

The human colon contains a diverse microbial population which contributes to degradation and metabolism of food components. Drug metabolism in the colon is generally poorly understood. Metabolomics techniques and in vitro colon models are now available which afford detailed characterization of drug metabolites in the context of colon metabolism. The aim of this work was to identify novel drug metabolites of Simvastatin (SV) by using an anaerobic human in vitro colon model at body temperature coupled with systems biology platform, excluding the metabolism of the host liver and intestinal epithelia. Comprehensive two-dimensional gas chromatography with a time-of-flight mass spectrometry (GC*GC-TOFMS) was used for the metabolomic analysis. Metabolites showing the most significant differences in the active faecal suspension were elucidated in reference with SV fragmentation and compared with controls: inactive suspension or buffer with SV, or with active suspension alone. Finally, time courses of selected metabolites were investigated. Our data suggest that SV is degraded by hydrolytic cleavage of methylbutanoic acid from the SV backbone. Metabolism involves demethylation of dimethylbutanoic acid, hydroxylation/dehydroxylation and ß-oxidation resulting in the production of 2-hydroxyisovaleric acid (3-methyl-2-hydroxybutanoic acid), 3-hydroxybutanoic acid and lactic acid (2-hydroxypropanoic acid), and finally re-cyclisation of heptanoic acid (possibly de-esterified and cleaved methylpyranyl arm) to produce cyclohexanecarboxylic acid. Our study elucidates a pathway of colonic microbial metabolism of SV as well as demonstrates the applicability of the in vitro colon model and metabolomics to the discovery of novel drug metabolites from drug response profiles.

Data processing and identification of unknown compounds in comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC×GC/TOFMS) analysis is a major challenge, particularly when large sample sets are analyzed. Herein, we present a method for efficient treatment of large data sets produced by GC×GC/TOFMS implemented as a freely available open source software package, Guineu. To handle large data sets and to efficiently utilize all the features available in the vendor software (baseline correction, mass spectral deconvolution, peak picking, integration, library search, and signal-to-noise filtering), data preprocessed by instrument software are used as a starting point for further processing. Our software affords alignment of the data, normalization, data filtering, and utilization of retention indexes in the verification of identification as well as a novel tool for automated group-type identification of the compounds. Herein, different features of the software are studied in detail and the performance of the system is verified by the analysis of a large set of standard samples as well as of a large set of authentic biological samples, including the control samples. The quantitative features of our GC×GC/TOFMS methodology are also studied to further demonstrate the method performance and the experimental results confirm the reliability of the developed procedure. The methodology has already been successfully used for the analysis of several thousand samples in the field of metabolomics.

Multi-view learning studies how several views, different feature representations, of the same objects could be best utilized in learning. In other words, multi-view learning is analysis of co-occurrence data, where the observations are co-occurrences of samples in the views. Standard multi-view learning such as joint density modeling cannot be done in the absence of co-occurrence, when the views are observed separately and the identities of objects are not known. As a practical example, joint analysis of mRNA and protein concentrations requires mapping between genes and proteins. We introduce a data-driven approach for learning the correspondence of the observations in the different views, in order to enable joint analysis also in the absence of known co-occurrence. The method finds a matching that maximizes statistical dependency between the views, which is particularly suitable for multi-view methods such as canonical correlation analysis which has the same objective. We apply the method to translational metabolomics, to identify differences and commonalities in metabolic processes in different species or tissues. The metabolite identities and roles in the different species are not generally known, and it is necessary to search for a matching. In this paper we show, using different metabolomics measurement batches as the views so that the ground truth is known, that the metabolite identities can be reliably matched by a consensus of several matching solutions.

Aim:The Wnt/β-catenin signaling network offers potential targets to diagnose and uncouple obesity from its metabolic complications. In this study, we investigate the role of the Wnt antagonist, secreted frizzled-related protein 1 (SFRP1), in promoting adipogenesis in vitro and adipose tissue expansion in vivo.Methods:We use a combination of human and murine, in vivo and in vitro models of adipogenesis, adipose tissue expansion and obesity-related metabolic syndrome to profile the involvement of SFRP1.Results:SFRP1 is expressed in both murine and human mature adipocytes. The expression of SFRP1 is induced during in vitro adipogenesis, and SFRP1 is preferentially expressed in mature adipocytes in human adipose tissue. Constitutive ectopic expression of SFRP1 is proadipogenic and inhibits the Wnt/β-catenin signaling pathway. In vivo endogenous levels of adipose SFRP1 are regulated in line with proadipogenic states. However, in longitudinal studies of high-fat-diet-fed mice, we observed a dynamic temporal but biphasic regulation of endogenous SFRP1. In agreement with this profile, we observed that SFRP1 expression in human tissues peaks in patients with mild obesity and gradually falls in morbidly obese subjects.Conclusions:Our results suggest that SFRP1 is an endogenous modulator of Wnt/β-catenin signaling and participates in the paracrine regulation of human adipogenesis. The reduced adipose expression of SFRP1 in morbid obesity and its knock-on effect to prevent further adipose tissue expansion may contribute to the development of metabolic complications in these individuals.

Motivation: Analysis of variance (ANOVA)-type methods are the default tool for the analysis of data with multiple covariates. These tools have been generalized to the multivariate analysis of high-throughput biological datasets, where the main challenge is the problem of small sample size and high dimensionality. However, the existing multi-way analysis methods are not designed for the currently increasingly important experiments where data is obtained from multiple sources. Common examples of such settings include integrated analysis of metabolic and gene expression profiles, or metabolic profiles from several tissues in our case, in a controlled multi-way experimental setup where disease status, medical treatment, gender and time-series are usual covariates. Results: We extend the applicability area of multivariate, multi-way ANOVA-type methods to multi-source cases by introducing a novel Bayesian model. The method is capable of finding covariate-related dependencies between the sources. It assumes the measurements consist of groups of similarly behaving variables, and estimates the multivariate covariate effects and their interaction effects for the discovered groups of variables. In particular, the method partitions the effects to those shared between the sources and to source-specific ones. The method is specifically designed for datasets with small sample sizes and high dimensionality. We apply the method to a lipidomics dataset from a lung cancer study with two-way experimental setup, where measurements from several tissues with mostly distinct lipids have been taken. The method is also directly applicable to gene expression and proteomics. Availability: An R-implementation is available at http://www.cis.hut.fi/projects/mi/software/multiWayCCA/ Contact: ilkka.huopaniemi@tkk.fi; samuel.kaski@tkk.fi

Background and aims Whole-grain cereals and diets with a low glycemic index may protect against the development of type 2 diabetes and heart disease, but the mechanisms are poorly understood. We studied the effect of carbohydrate modification on serum metabolic profiles, including lipids and branched chain amino acids, and dependencies between these and specific gene expression pathways in adipose tissue. Methods and results Twenty subjects with metabolic syndrome were selected from the larger FUNGENUT study population, randomized either to a diet high in oat and wheat bread and potato (OWP) or rye bread and pasta (RP). Serum metabolomics analyses were performed using ultra-performance liquid chromatography coupled to electrospray ionization mass spectrometry (UPLC/MS), gas chromatography (GC) and UPLC. In the OWP group multiple proinflammatory lysophosphatidylcholines increased, while in the RP group docosahexaenoic acid (DHA 22:6n-3) increased and isoleucine decreased. mRNA expression of stress reactions- and adipose tissue differentiation-related genes were up-regulated in adipose tissue in the OWP group. In the RP group, however, pathways related to stress reactions and insulin signaling and energy metabolism were down-regulated. The lipid profiles had the strongest association with the changes in the adipose tissue differentiation pathway when using the elastic net regression model of the lipidomic profiles on selected pathways. Conclusion Our results suggest that the dietary carbohydrate modification alters the serum metabolic profile, especially in lysoPC species, and may, thus, contribute to proinflammatory processes which in turn promote adverse changes in insulin and glucose metabolism.

Background Psychotic patients are at high risk for developing obesity, metabolic syndrome and type 2 diabetes. These metabolic co-morbidities are hypothesized to be related to both treatment side-effects as well as to metabolic changes occurring during the psychosis. Earlier metabolomics studies have shown that blood metabolite levels are predictive of insulin resistance and type 2 diabetes in the general population as well as sensitive to the effects of antipsychotics. Here we aimed to identify the metabolite profiles predicting future weight gain and other metabolic abnormalities in psychotic patients. Methods We applied metabolomics to investigate serum metabolite profiles in a prospective study setting in 36 first-episode psychosis patients during the first year of the antipsychotic treatment and 19 controls. Two analytical platforms with broad analytical coverage were used. Molecular lipids were analysed by ultra-high performance liquid chromatography coupled to time-of-flight mass spectrometry (UHPLC_QTOFMS) and polar metabolites were analysed by two-dimensional gas chromatography coupled to TOFMS (GCxGC-TOFMS). Ongoing prospective metabolomics studies ae focusing on the subjects in at-risk mental state. Results While corroborating several earlier findings when comparing cases and controls and the effects of the antipsychotic medication, we also found that prospective weight gain in psychotic patients was associated with increased levels of triacylglycerols with low carbon number and double-bond count at baseline and independent of obesity, that is, lipids known to be associated with increased liver fat. Discussion The first-episode psychotic patients who rapidly gain weight in the follow-up have early metabolic disturbances which are associated with insulin resistance and fatty liver. Our studies suggest that metabolite profiles may be used to identify the psychotic patients most vulnerable to develop metabolic co-morbidities, and may point to a pharmacological approach to counteract the antipsychotic-induced weight gain.

Overall Abstract: Schizophrenia is associated with a reduced life expectancy of 15–20 years due to a high prevalence of cardiovascular disease and metabolic syndrome. Unhealthy lifestyles and pharmacological side effects have been suggested to be a major cause of excess mortality rates in patients with psychotic disorders. However, abnormal glucose homeostasis, hyperinsulinemia and accumulation of visceral fat are already detected in drug-naïve first episode psychosis (FEP) patients, independently of obesity. The aim of this symposium is to present the latest research on the theme of metabolic co-morbidities in psychotic disorders. Preliminary and published data from the symposium speakers suggests that FEP is associated with altered composition of gut microbiota, inflammation and lipid dysregulation including changes in the endocannabinoid system in the central nervous system. The studies presented in this symposium may offer new insights into the gut-brain axis in psychotic disorders as well as provide new evidence on the role of lipids as a potential underlying link between the aetiology of psychosis and the associated metabolic disturbances. All four speakers are principal investigators in the European FP7 project METSY, which aims to identify and evaluate multi-modal peripheral and neuroimaging markers that can predict and monitor psychotic and metabolic symptoms, with specific focus on metabolic co-morbidities in psychotic disorders. Oliver Howes will first introduce the topic, based on his recent meta-analysis (JAMA Psychiatry 2017; 74; 261–269) as well as present his recent research on neuroimaging of the endocannabinoid system in FEP. Jaana Suvisaari will present her recent research on gut microbiome and inflammation in FEP. The findings so far suggest that FEP patients have specifically altered gut microbiome composition and increased levels of inflammation. Tuulia Hyötyläinen will introduce the field of metabolomics in psychosis research and discuss the latest findings from at-risk mental state individuals and FEP patients. Recently published findings suggest that FEP patients who later rapidly gain weight are characterised by increased markers of liver fat at the baseline. Jarmo Hietala will present neuroimaging studies of the endocannabinoid system using PET and the [18F]FMPEP-d2 tracer, a CB1R radioligand. These studies suggest a major sex difference in the brain CB1 receptor system as well as clear evidence for a dysregulated endocannabinoid system in first-episode psychosis. Given the endocannabinoid system in the periphery promotes the development of fatty liver, the presented work together suggests that the endocannabinoid system may be the underlying link between the psychosis and the associated metabolic disturbances. This intriguing possibility with potential diagnostic and therapeutic implications will be discussed by the presenters. The discussant Matej Oresic is the coordinator of the METSY project.

Angiotensin II (Ang II) induces mitochondrial dysfunction. We tested whether Ang II alters the “metabolomic” profile. We harvested hearts from 8-week-old double transgenic rats harboring human renin and angiotensinogen genes (dTGRs) and controls (Sprague-Dawley), all with or without Ang II type 1 receptor (valsartan) blockade. We used gas chromatography coupled with time-of-flight mass spectrometry to detect 247 intermediary metabolites. We used a partial least-squares discriminate analysis and identified 112 metabolites that differed significantly after corrections (false discovery rate q P

The gut microbiota has recently been identified as an environmental factor that may promote metabolic diseases. To investigate the effect of gut microbiota on host energy and lipid metabolism, we compared the serum metabolome and the lipidomes of serum, adipose tissue, and liver of conventionally raised (CONV-R) and germ-free mice. The serum metabolome of CONV-R mice was characterized by increased levels of energy metabolites, e.g., pyruvic acid, citric acid, fumaric acid, and malic acid, while levels of cholesterol and fatty acids were reduced. We also showed that the microbiota modified a number of lipid species in the serum, adipose tissue, and liver, with its greatest effect on triglyceride and phosphatidylcholine species. Triglyceride levels were lower in serum but higher in adipose tissue and liver of CONV-R mice, consistent with increased lipid clearance. Our findings show that the gut microbiota affects both host energy and lipid metabolism and highlights its role in the development of metabolic diseases., Human Frontier of Science Program RGY64/2008 Swedish Research Council K2007-65X-20421-01-04 Lars Hierta's Foundation Nanna Svartz Foundation Fredrik and Ingrid Thurings Foundations Swedish Nutrition Foundation Vastra Gotalandsregionen

Thyroid hormones have widespread cellular effects; however it is unclear whether their effects on the central nervous system (CNS) contribute to global energy balance. Here we demonstrate that either whole-body hyperthyroidism or central administration of triiodothyronine (T3) decreases the activity of hypothalamic AMP-activated protein kinase (AMPK), increases sympathetic nervous system (SNS) activity and upregulates thermogenic markers in brown adipose tissue (BAT). Inhibition of the lipogenic pathway in the ventromedial nucleus of the hypothalamus (VMH) prevents CNS-mediated activation of BAT by thyroid hormone and reverses the weight loss associated with hyperthyroidism. Similarly, inhibition of thyroid hormone receptors in the VMH reverses the weight loss associated with hyperthyroidism. This regulatory mechanism depends on AMPK inactivation, as genetic inhibition of this enzyme in the VMH of euthyroid rats induces feeding-independent weight loss and increases expression of thermogenic markers in BAT. These effects are reversed by pharmacological blockade of the SNS. Thus, thyroid hormone-induced modulation of AMPK activity and lipid metabolism in the hypothalamus is a major regulator of whole-body energy homeostasis.

Ceramides may mediate saturated fat–induced insulin resistance, but there are no data comparing ceramide concentrations between human tissues. We therefore performed lipidomic analysis of human subcutaneous (SCfat) and intra‐abdominal (IAfat) adipose tissue, the liver, and serum in eight subjects. The liver contained (nmol/mg tissue) significantly more ceramides (1.5–3‐fold), sphingomyelins (7–8‐fold), phosphatidylethanolamines (10–11‐fold), lysophosphatidylcholines (7–12‐fold), less ether‐linked phosphatidylcholines (2–2.5‐fold) but similar amounts of diacylglycerols as compared to SCfat and IAfat. The amounts of ceramides and their synthetic precursors, such as palmitic (16:0) free fatty acids and sphingomyelins, differed considerably between the tissues. The liver contained proportionally more palmitic, stearic (18:0), and long polyunsaturated fatty acids than adipose tissues. Stearoyl‐CoA desaturase 1 (SCD1) activity reflected by serum, estimated from the 16:1/16:0‐ratio, was closely related to that in the liver (r = 0.86, P = 0.024) but not adipose tissues. This was also true for estimated elongase (18:1/16:1, r = 0.89, P = 0.01), and Δ5 (20:4/20:3, r = 0.89, P = 0.012) and Δ6 (18:3[n‐6]/18:2, r = 1.0, P < 0.001) desaturase activities. We conclude that the human liver contains higher concentrations of ceramides and saturated free fatty acids than either SCfat or IAfat.

Mass spectrometry (MS)-based metabolomics studies often require handling of both identified and unidentified metabolite data. In order to avoid bias in data interpretation, it would be of advantage for the data analysis to include all available data. A practical challenge in exploratory metabolomics analysis is therefore how to interpret the changes related to unidentified peaks. In this paper, we address the challenge by predicting the class membership of unknown peaks by applying and comparing multiple supervised classifiers to selected lipidomics datasets. The employed classifiers include k-nearest neighbours (k-NN), support vector machines (SVM), partial least squares and discriminant analysis (PLS-DA) and Naive Bayes methods which are known to be effective and efficient in predicting the labels for unseen data. Here, the class label predictions are sought for unidentified lipid profiles coming from high throughput global screening in Ultra Performance Liquid Chromatography Mass Spectrometry (UPLCTM/MS) experimental setup. Our investigation reveals that k-NN and SVM classifiers outperform both PLS-DA and Naive Bayes classifiers. Naive Bayes classifier perform poorly among all models and this observation seems logical as lipids are highly co-regulated and do not respect Naive Bayes assumptions of features being conditionally independent given the class. Common label predictions from k-NN and SVM can serve as a good starting point to explore full data and thereby facilitating exploratory studies where label information is critical for the data interpretation.

BackgroundLittle is known about the effect of fish consumption on gene expression of inflammation-related genes in immune cells in coronary heart disease (CHD).Aim of the studyWe sought to evaluate the effect of a fatty fish (FF) or a lean fish (LF) diet on the modulation of inflammatory and endothelial function-related genes in peripheral blood mononuclear cells (PBMCs) of subjects with CHD, and its association with serum fatty acid (FA) profile and lipid metabolic compounds.MethodsData from 27 patients randomized into an 8-week FF (n = 10; mean ± SD: 4.3 ± 0.4 portions of fish per week), LF (n = 11; 4.7 ± 1.1 portions of fish per week), or control diet (n = 6; 0.6 ± 0.4 portions of fish per week) were analyzed. The mRNA expression was measured using real-time PCR.ResultsThe effect of the intervention on the mRNA expression of the genes studied did not differ among groups. In the FF group, however, the decrease in arachidonic acid to eicosapentaenoic acid (AA:EPA) ratio in cholesterol ester and phospholipid fractions strongly correlated with the change in IL1B mRNA levels (r s = 0.60, P = 0.06 and r s = 0.86, P = 0.002, respectively). In the LF group, the decrease in palmitic acid and total saturated FAs in cholesterol esters correlated with the change in intercellular cell adhesion molecule-1 (ICAM1) expression (r s = 0.64, P = 0.04 for both). Circulating levels of soluble ICAM-1 decreased only in the LF group (P ConclusionsThe intake of FF or LF diet did not alter the expression of inflammatory and endothelial function-related genes in PBMCs of patients with CHD. However, the decrease in AA:EPA ratio in serum lipids in the FF group may induce an anti-inflammatory response at mRNA levels in PBMCs. A LF diet might benefit endothelial function, possibly mediated by the changes in serum FA composition.