Alzheimer's disease (AD) is the most common cause of dementia affecting 36 million people worldwide. As the demographic transition in the developed countries progresses towards older population, the worsening ratio of workers per retirees and the growing number of patients with age-related illnesses such as AD will challenge the current healthcare systems and national economies. For these reasons AD has been identified as a health priority, and various methods for diagnosis and many candidates for therapies are under intense research. Even though there is currently no cure for AD, its effects can be managed. Today the significance of early and precise diagnosis of AD is emphasized in order to minimize its irreversible effects on the nervous system. When new drugs and therapies enter the market it is also vital to effectively identify the right candidates to benefit from these. The main objective of the PredictAD project was to find and integrate efficient biomarkers from heterogeneous patient data to make early diagnosis and to monitor the progress of AD in a more efficient, reliable and objective manner. The project focused on discovering biomarkers from biomolecular data, electrophysiological measurements of the brain and structural, functional and molecular brain images. We also designed and built a statistical model and a framework for exploiting these biomarkers with other available patient history and background data. We were able to discover several potential novel biomarker candidates and implement the framework in software. The results are currently used in several research projects, licensed to commercial use and being tested for clinical use in several trials.
Alzheimer's disease; early diagnosis; clinical decision support systems
We studied the combined effects of wholegrain, fish and bilberries on serum metabolic profile and lipid transfer protein activities in subjects with the metabolic syndrome.
Altogether 131 subjects (40–70 y, BMI 26–39 kg/m2) with impaired glucose metabolism and features of the metabolic syndrome were randomized into three groups with 12-week periods according to a parallel study design. They consumed either: a) wholegrain and low postprandial insulin response grain products, fatty fish 3 times a week, and bilberries 3 portions per day (HealthyDiet), b) wholegrain and low postprandial insulin response grain products (WGED), or c) refined wheat breads as cereal products (Control). Altogether 106 subjects completed the study. Serum metabolic profile was studied using an NMR-based platform providing information on lipoprotein subclasses and lipids as well as low-molecular-weight metabolites.
There were no significant differences in clinical characteristics between the groups at baseline or at the end of the intervention. Mixed model analyses revealed significant changes in lipid metabolites in the HealthyDiet group during the intervention compared to the Control group. All changes reflected increased polyunsaturation in plasma fatty acids, especially in n-3 PUFAs, while n-6 and n-7 fatty acids decreased. According to tertiles of changes in fish intake, a greater increase of fish intake was associated with increased concentration of large HDL particles, larger average diameter of HDL particles, and increased concentrations of large HDL lipid components, even though total levels of HDL cholesterol remained stable.
The results suggest that consumption of diet rich in whole grain, bilberries and especially fatty fish causes changes in HDL particles shifting their subclass distribution toward larger particles. These changes may be related to known protective functions of HDL such as reverse cholesterol transport and could partly explain the known protective effects of fish consumption against atherosclerosis.
The study was registered at ClinicalTrials.gov NCT00573781.
Saccharomyces cerevisiae is able to adapt to a wide range of external oxygen conditions. Previously, oxygen-dependent phenotypes have been studied individually at the transcriptional, metabolite, and flux level. However, the regulation of cell phenotype occurs across the different levels of cell function. Integrative analysis of data from multiple levels of cell function in the context of a network of several known biochemical interaction types could enable identification of active regulatory paths not limited to a single level of cell function.
The graph theoretical method called Enriched Molecular Path detection (EMPath) was extended to enable integrative utilization of transcription and flux data. The utility of the method was demonstrated by detecting paths associated with phenotype differences of S. cerevisiae under three different conditions of oxygen provision: 20.9%, 2.8% and 0.5%. The detection of molecular paths was performed in an integrated genome-scale metabolic and protein-protein interaction network.
The molecular paths associated with the phenotype differences of S. cerevisiae under conditions of different oxygen provisions revealed paths of molecular interactions that could potentially mediate information transfer between processes that respond to the particular oxygen availabilities.
Saccharomyces cerevisiae; Network biology; Molecular path finding; Data integration; Oxygen; Constraint-based modeling
We examined whether analysis of lipids by ultra-performance liquid chromatography (UPLC) coupled to MS allows the development of a laboratory test for non-alcoholic fatty-liver disease (NAFLD), and how a lipid-profile biomarker compares with the prediction of NAFLD and liver-fat content based on routinely available clinical and laboratory data.
We analysed the concentrations of molecular lipids by UPLC-MS in blood samples of 679 well-characterised individuals in whom liver-fat content was measured using proton magnetic resonance spectroscopy (1H-MRS) or liver biopsy. The participants were divided into biomarker-discovery (n = 287) and validation (n = 392) groups to build and validate the diagnostic models, respectively.
Individuals with NAFLD had increased triacylglycerols with low carbon number and double-bond content while lysophosphatidylcholines and ether phospholipids were diminished in those with NAFLD. A serum-lipid signature comprising three molecular lipids (‘lipid triplet’) was developed to estimate the percentage of liver fat. It had a sensitivity of 69.1% and specificity of 73.8% when applied for diagnosis of NAFLD in the validation series. The usefulness of the lipid triplet was demonstrated in a weight-loss intervention study.
The liver-fat-biomarker signature based on molecular lipids may provide a non-invasive tool to diagnose NAFLD, in addition to highlighting lipid molecular pathways involved in the disease.
Electronic supplementary material
The online version of this article (doi:10.1007/s00125-013-2981-2) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
Lipidomics; Mass spectrometry; Non-alcoholic fatty-liver disease
Breast cancer is the most common cancer in women worldwide, and the development of new technologies for better understanding of the molecular changes involved in breast cancer progression is essential. Metabolic changes precede overt phenotypic changes, because cellular regulation ultimately affects the use of small-molecule substrates for cell division, growth or environmental changes such as hypoxia. Differences in metabolism between normal cells and cancer cells have been identified. Because small alterations in enzyme concentrations or activities can cause large changes in overall metabolite levels, the metabolome can be regarded as the amplified output of a biological system. The metabolome coverage in human breast cancer tissues can be maximized by combining different technologies for metabolic profiling. Researchers are investigating alterations in the steady state concentrations of metabolites that reflect amplified changes in genetic control of metabolism. Metabolomic results can be used to classify breast cancer on the basis of tumor biology, to identify new prognostic and predictive markers and to discover new targets for future therapeutic interventions. Here, we examine recent results, including those from the European FP7 project METAcancer consortium, that show that integrated metabolomic analyses can provide information on the stage, subtype and grade of breast tumors and give mechanistic insights. We predict an intensified use of metabolomic screens in clinical and preclinical studies focusing on the onset and progression of tumor development.
breast cancer; metabolomics; lipidomics; biomarker analysis
Sugars are important nutrients for many animals, but are also proposed to contribute to overnutrition-derived metabolic diseases in humans. Understanding the genetic factors governing dietary sugar tolerance therefore has profound biological and medical significance. Paralogous Mondo transcription factors ChREBP and MondoA, with their common binding partner Mlx, are key sensors of intracellular glucose flux in mammals. Here we report analysis of the in vivo function of Drosophila melanogaster Mlx and its binding partner Mondo (ChREBP) in respect to tolerance to dietary sugars. Larvae lacking mlx or having reduced mondo expression show strikingly reduced survival on a diet with moderate or high levels of sucrose, glucose, and fructose. mlx null mutants display widespread changes in lipid and phospholipid profiles, signs of amino acid catabolism, as well as strongly elevated circulating glucose levels. Systematic loss-of-function analysis of Mlx target genes reveals that circulating glucose levels and dietary sugar tolerance can be genetically uncoupled: Krüppel-like transcription factor Cabut and carbonyl detoxifying enzyme Aldehyde dehydrogenase type III are essential for dietary sugar tolerance, but display no influence on circulating glucose levels. On the other hand, Phosphofructokinase 2, a regulator of the glycolysis pathway, is needed for both dietary sugar tolerance and maintenance of circulating glucose homeostasis. Furthermore, we show evidence that fatty acid synthesis, which is a highly conserved Mondo-Mlx-regulated process, does not promote dietary sugar tolerance. In contrast, survival of larvae with reduced fatty acid synthase expression is sugar-dependent. Our data demonstrate that the transcriptional network regulated by Mondo-Mlx is a critical determinant of the healthful dietary spectrum allowing Drosophila to exploit sugar-rich nutrient sources.
Diet displays extreme natural variation between animal species, which range from highly specialized carnivores, herbivores, and nectarivores to flexible dietary generalists. Humans are not identical in this respect either, but the genetic background likely defines the framework for a healthy diet. However, we understand poorly the genetic factors that define the spectrum of healthy diet for a given species or individual. Here we have explored the genetic basis of dietary sugar tolerance of Drosophila melanogaster. D. melanogaster is a generalist fruit breeder that feeds on micro-organisms on decaying fruits and vegetables with varying sugar content. However, mutants lacking the conserved Mondo-Mlx transcription factor complex display striking intolerance towards dietary sucrose, glucose, or fructose. This is manifested in the larvae by the inability to grow and pupate on sugar-rich food, including red grape, which belongs to the normal diet of wild D. melanogaster. Larvae lacking Mondo-Mlx show widespread metabolic imbalance, including highly elevated circulating glucose. Genome-wide gene expression analysis combined with systematic loss-of-function screening of Mlx targets reveal that the genetic network providing sugar tolerance includes a secondary transcriptional effector as well as regulators of glycolysis and detoxification of reactive metabolites.
Accumulating evidence indicates that the intestinal microbiota regulates our physiology and metabolism. Bacteria marketed as probiotics confer health benefits that may arise from their ability to affect the microbiota. Here high-throughput screening of the intestinal microbiota was carried out and integrated with serum lipidomic profiling data to study the impact of probiotic intervention on the intestinal ecosystem, and to explore the associations between the intestinal bacteria and serum lipids. We performed a comprehensive intestinal microbiota analysis using a phylogenetic microarray before and after Lactobacillus rhamnosus GG intervention. While a specific increase in the L. rhamnosus-related bacteria was observed during the intervention, no other changes in the composition or stability of the microbiota were detected. After the intervention, lactobacilli returned to their initial levels. As previously reported, also the serum lipid profiles remained unaltered during the intervention. Based on a high-resolution microbiota analysis, intake of L. rhamnosus GG did not modify the composition of the intestinal ecosystem in healthy adults, indicating that probiotics confer their health effects by other mechanisms. The most prevailing association between the gut microbiota and lipid profiles was a strong positive correlation between uncultured phylotypes of Ruminococcus gnavus-group and polyunsaturated serum triglycerides of dietary origin. Moreover, a positive correlation was detected between serum cholesterol and Collinsella (Coriobacteriaceae). These associations identified with the spectrometric lipidome profiling were corroborated by enzymatically determined cholesterol and triglyceride levels. Actinomycetaceae correlated negatively with triglycerides of highly unsaturated fatty acids while a set of Proteobacteria showed negative correlation with ether phosphatidylcholines. Our results suggest that several members of the Firmicutes, Actinobacteria and Proteobacteria may be involved in the metabolism of dietary and endogenous lipids, and provide a scientific rationale for further human studies to explore the role of intestinal microbes in host lipid metabolism.
Microbiota; Lipidomics; Probiotics; Lactobacillus rhamnosus GG; Gastrointestinal tract; Physiology; High-throughput profiling
Progression to type 1 diabetes is characterized by complex interactions of environmental, metabolic and immune system factors, involving both degenerative pathways leading to loss of pancreatic β-cells as well as protective pathways. The interplay between the degenerative and protective pathways may hold the key to disease outcomes, but no models have so far captured the two together. Here we propose a mathematical framework, an ordinary differential equation (ODE) model, which integrates metabolism and the immune system in early stages of disease process. We hypothesize that depending on the degree of regulation, autoimmunity may also play a protective role in the initial response to stressors. We assume that β-cell destruction follows two paths of loss: degenerative and autoimmune-induced loss. The two paths are mutually competing, leading to termination of the degenerative loss and further to elimination of the stress signal and the autoimmune response, and ultimately stopping the β-cell loss. The model describes well our observations from clinical and non-clinical studies and allows exploration of how the rate of β-cell loss depends on the amplitude and duration of autoimmune response.
Islet autoimmunity precedes type 1 diabetes and often initiates in childhood. Phenotypic variation in islet autoimmunity relative to the age of its development suggests heterogeneous mechanisms of autoimmune activation. To support this notion, we examined whether serum metabolite profiles differ between children with respect to islet autoantibody status and the age of islet autoantibody development.
RESEARCH DESIGN AND METHODS
The study analyzed 29 metabolites of amino acid metabolism and 511 lipids assigned to 12 lipid clusters in children, with a type 1 diabetic parent, who first developed autoantibodies at age 2 years or younger (n = 13), at age 8 years or older (n = 22), or remained autoantibody-negative, and were matched for age, date of birth, and HLA genotypes (n = 35). Ultraperformance liquid chromatography and mass spectroscopy were used to measure metabolites and lipids quantitatively in the first autoantibody-positive and matched autoantibody-negative serum samples and in a second sample after 1 year of follow-up.
Differences in the metabolite profiles were observed relative to age and islet autoantibody status. Independent of age-related differences, autoantibody-positive children had higher levels of odd-chain triglycerides and polyunsaturated fatty acid–containing phospholipids than autoantibody-negative children and independent of age at first autoantibody appearance (P < 0.0001). Consistent with our hypothesis, children who developed autoantibodies by age 2 years had twofold lower concentration of methionine compared with those who developed autoantibodies in late childhood or remained autoantibody-negative (P < 0.0001).
Distinct metabolic profiles are associated with age and islet autoimmunity. Pathways that use methionine are potentially relevant for developing islet autoantibodies in early infancy.
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.
Inflammation and increased ceramide concentrations characterise adipose tissue of obese women with high liver fat content compared to equally obese women with normal liver fat content. The present study characterises enzymes involved in ceramide metabolism in subcutaneous and intra-abdominal adipose tissue.
Pathways leading to increased ceramide concentrations in inflamed versus non-inflamed adipose tissue were investigated by quantifying expression levels of key enzymes involved in ceramide metabolism. Sphingomyelinases (sphingomyelin phosphodiesterases SMPD1-3) were investigated further using immunohistochemistry to establish their location within adipose tissue, and their mRNA expression levels were determined in subcutaneous and intra-abdominal adipose tissue from both non-obese and obese subject.
Gene expression levels of sphingomyelinases, enzymes that hydrolyse sphingomyelin to ceramide, rather than enzymes involved in de novo ceramide synthesis, were higher in inflamed compared to non-inflamed adipose tissue of obese women (with high and normal liver fat contents respectively). Sphingomyelinases were localised to both macrophages and adipocytes, but also to blood vessels and to extracellular regions surrounding vessels within adipose tissue. Expression levels of SMPD3 mRNA correlated significantly with concentrations of different ceramides and sphingomyelins. In both non-obese and obese subjects SMPD3 mRNA levels were higher in the more inflamed intra-abdominal compared to the subcutaneous adipose tissue depot.
Generation of ceramides within adipose tissue as a result of sphingomyelinase action may contribute to inflammation in human adipose tissue.
Adipose tissue; Ceramide; Human; Inflammation; Sphingomyelinase
Primary obesity and psychotic disorders are similar with respect to the associated changes in energy balance and co-morbidities, including metabolic syndrome. Such similarities do not necessarily demonstrate causal links, but instead suggest that specific causes of and metabolic disturbances associated with obesity play a pathogenic role in the development of co-morbid disorders, potentially even before obesity develops. Metabolomics – the systematic study of metabolites, which are small molecules generated by the process of metabolism – has been important in elucidating the pathways underlying obesity-associated co-morbidities. This review covers how recent metabolomic studies have advanced biomarker discovery and the elucidation of mechanisms underlying obesity and its co-morbidities, with a specific focus on metabolic syndrome and psychotic disorders. The importance of identifying metabolic markers of disease-associated intermediate phenotypes – traits modulated but not encoded by the DNA sequence – is emphasized. Such markers would be applicable as diagnostic tools in a personalized healthcare setting and might also open up novel therapeutic avenues.
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 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 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.
While beneficial health effects of fish and fish oil consumption are well documented, the incorporation of n-3 polyunsaturated fatty acids in plasma lipid classes is not completely understood. The aim of this study was to investigate the effect of fish oil supplementation on the plasma lipidomic profile in healthy subjects.
In a double-blinded randomized controlled parallel-group study, healthy subjects received capsules containing either 8 g/d of fish oil (FO) (1.6 g/d EPA+DHA) (n = 16) or 8 g/d of high oleic sunflower oil (HOSO) (n = 17) for seven weeks. During the first three weeks of intervention, the subjects completed a fully controlled diet period. BMI and total serum triglycerides, total-, LDL- and HDL-cholesterol were unchanged during the intervention period. Lipidomic analyses were performed using Ultra Performance Liquid Chromatography (UPLC) coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (QTOFMS), where 568 lipids were detected and 260 identified. Both t-tests and Multi-Block Partial Least Square Regression (MBPLSR) analysis were performed for analysing differences between the intervention groups. The intervention groups were well separated by the lipidomic data after three weeks of intervention. Several lipid classes such as phosphatidylcholine, phosphatidylethanolamine, lysophosphatidylcholine, sphingomyelin, phosphatidylserine, phosphatidylglycerol, and triglycerides contributed strongly to this separation. Twenty-three lipids were significantly decreased (FDR<0.05) in the FO group after three weeks compared with the HOSO group, whereas fifty-one were increased including selected phospholipids and triglycerides of long-chain polyunsaturated fatty acids. After seven weeks of intervention the two intervention groups showed similar grouping.
In healthy subjects, fish oil supplementation alters lipid metabolism and increases the proportion of phospholipids and triglycerides containing long-chain polyunsaturated fatty acids. Whether the beneficial effects of fish oil supplementation may be explained by a remodeling of the plasma lipids into phospholipids and triglycerides of long-chain polyunsaturated fatty acids needs to be further investigated.
Changes in energy metabolism of the cells are common to many kinds of tumors and are considered a hallmark of cancer. Gas chromatography followed by time-of-flight mass spectrometry (GC-TOFMS) is a well-suited technique to investigate the small molecules in the central metabolic pathways. However, the metabolic changes between invasive carcinoma and normal breast tissues were not investigated in a large cohort of breast cancer samples so far.
A cohort of 271 breast cancer and 98 normal tissue samples was investigated using GC-TOFMS-based metabolomics. A total number of 468 metabolite peaks could be detected; out of these 368 (79%) were significantly changed between cancer and normal tissues (p<0.05 in training and validation set). Furthermore, 13 tumor and 7 normal tissue markers were identified that separated cancer from normal tissues with a sensitivity and a specificity of >80%. Two-metabolite classifiers, constructed as ratios of the tumor and normal tissues markers, separated cancer from normal tissues with high sensitivity and specificity. Specifically, the cytidine-5-monophosphate / pentadecanoic acid metabolic ratio was the most significant discriminator between cancer and normal tissues and allowed detection of cancer with a sensitivity of 94.8% and a specificity of 93.9%.
For the first time, a comprehensive metabolic map of breast cancer was constructed by GC-TOF analysis of a large cohort of breast cancer and normal tissues. Furthermore, our results demonstrate that spectrometry-based approaches have the potential to contribute to the analysis of biopsies or clinical tissue samples complementary to histopathology.
Breast cancer; Metabolomics; Gas chromatography; Mass spectrometry; Cancer detection
Mice lacking Peroxisome Proliferator-Activated Receptor γ2 (PPARγ2) have unexpectedly normal glucose tolerance and mild insulin resistance. Mice lacking PPARγ2 were found to have elevated levels of Lipocalin prostaglandin D synthase (L-PGDS) expression in BAT and subcutaneous white adipose tissue (WAT). To determine if induction of L-PGDS was compensating for a lack of PPARγ2, we crossed L-PGDS KO mice to PPARγ2 KO mice to generate Double Knock Out mice (DKO). Using DKO mice we demonstrated a requirement of L-PGDS for maintenance of subcutaneous WAT (scWAT) function. In scWAT, DKO mice had reduced expression of thermogenic genes, the de novo lipogenic program and the lipases ATGL and HSL. Despite the reduction in markers of lipolysis in scWAT, DKO mice had a normal metabolic rate and elevated serum FFA levels compared to L-PGDS KO alone. Analysis of intra-abdominal white adipose tissue (epididymal WAT) showed elevated expression of mRNA and protein markers of lipolysis in DKO mice, suggesting that DKO mice may become more reliant on intra-abdominal WAT to supply lipid for oxidation. This switch in depot utilisation from subcutaneous to epididymal white adipose tissue was associated with a worsening of whole organism metabolic function, with DKO mice being glucose intolerant, and having elevated serum triglyceride levels compared to any other genotype. Overall, L-PGDS and PPARγ2 coordinate to regulate carbohydrate and lipid metabolism.
Syrah red grapes are used in the production of tannin-rich red wines. Tannins are high molecular weight molecules, proanthocyanidins (PAs), and poorly absorbed in the upper intestine. In this study, gut microbial metabolism of Syrah grape phenolic compounds was investigated.
Syrah grape pericarp was subjected to an enzymatic in vitro digestion model, and red wine and grape skin PA fraction were prepared. Microbial conversion was screened using an in vitro colon model with faecal microbiota, by measurement of short-chain fatty acids by gas chromatography (GC) and microbial phenolic metabolites using GC with mass detection (GC–MS). Red wine metabolites were further profiled using two-dimensional GC mass spectrometry (GCxGC-TOFMS). In addition, the effect of PA structure and dose on conversion efficiency was investigated by GC–MS.
Red wine exhibited a higher degree of C1–C3 phenolic acid formation than PA fraction or grape pericarp powders. Hydroxyphenyl valeric acid (flavanols and PAs as precursors) and 3,5-dimethoxy-4-hydroxybenzoic acid (anthocyanin as a precursor) were identified from the red wine metabolite profile. In the absence of native grape pericarp or red wine matrix, the isolated PAs were found to be effective in the dose-dependent inhibition of microbial conversions and short-chain fatty acid formation.
Metabolite profiling was complementary to targeted analysis. The identified metabolites had biological relevance, because the structures of the metabolites resembled fragments of their grape phenolic precursors or were in agreement with literature data.
Electronic supplementary material
The online version of this article (doi:10.1007/s00394-012-0391-8) contains supplementary material, which is available to authorized users.
Syrah grape; Red wine; Proanthocyanidins; In vitro colon conversions; Phenolic compounds; Short-chain fatty acids; Metabolite profiling
Obesity-associated insulin resistance is characterized by a state of chronic, low-grade inflammation that is associated with the accumulation of M1 proinflammatory macrophages in adipose tissue. Although different evidence explains the mechanisms linking the expansion of adipose tissue and adipose tissue macrophage (ATM) polarization, in the current study we investigated the concept of lipid-induced toxicity as the pathogenic link that could explain the trigger of this response.
RESEARCH DESIGN AND METHODS
We addressed this question using isolated ATMs and adipocytes from genetic and diet-induced murine models of obesity. Through transcriptomic and lipidomic analysis, we created a model integrating transcript and lipid species networks simultaneously occurring in adipocytes and ATMs and their reversibility by thiazolidinedione treatment.
We show that polarization of ATMs is associated with lipid accumulation and the consequent formation of foam cell–like cells in adipose tissue. Our study reveals that early stages of adipose tissue expansion are characterized by M2-polarized ATMs and that progressive lipid accumulation within ATMs heralds the M1 polarization, a macrophage phenotype associated with severe obesity and insulin resistance. Furthermore, rosiglitazone treatment, which promotes redistribution of lipids toward adipocytes and extends the M2 ATM polarization state, prevents the lipid alterations associated with M1 ATM polarization.
Our data indicate that the M1 ATM polarization in obesity might be a macrophage-specific manifestation of a more general lipotoxic pathogenic mechanism. This indicates that strategies to optimize fat deposition and repartitioning toward adipocytes might improve insulin sensitivity by preventing ATM lipotoxicity and M1 polarization.
The insulin/IGF signaling pathway is a highly conserved regulator of metabolism in flies and mammals, regulating multiple physiological functions including lipid metabolism. Although insulin signaling is known to regulate the activity of a number of enzymes in metabolic pathways, a comprehensive understanding of how the insulin signaling pathway regulates metabolic pathways is still lacking. Accepted knowledge suggests the key regulated step in triglyceride (TAG) catabolism is the release of fatty acids from TAG via the action of lipases. We show here that an additional, important regulated step is the activation of fatty acids for beta-oxidation via Acyl Co-A synthetases (ACS). We identify pudgy as an ACS that is transcriptionally regulated by direct FOXO action in Drosophila. Increasing or reducing pudgy expression in vivo causes a decrease or increase in organismal TAG levels respectively, indicating that pudgy expression levels are important for proper lipid homeostasis. We show that multiple ACSs are also transcriptionally regulated by insulin signaling in mammalian cells. In sum, we identify fatty acid activation onto CoA as an important, regulated step in triglyceride catabolism, and we identify a mechanistic link through which insulin regulates lipid homeostasis.
Type 2 diabetes, which is reaching epidemic proportions worldwide, is often associated with obesity and an imbalance in organismal lipid homeostasis. Therefore, understanding how insulin regulates lipid biosynthesis and breakdown is necessary. Surprisingly, the molecular mechanisms by which insulin regulates fatty acid catabolism are not entirely understood. We show here that insulin signaling regulates expression of acyl-CoA Synthetases (ACS). ACSs couple fatty acids to Coenzyme A, thereby activating them for subsequent biochemical reactions. In Drosophila, we find that insulin signaling modulates expression of one ACS called Pudgy, which activates fatty acids for beta-oxidation. Modulation of pudgy expression leads to changes in overall organismal lipid homeostasis. Likewise, we show that in mammalian cells insulin signaling regulates expression of a number of ACSs and that ACS expression modulates steady-state lipid levels.
Several theories have been proposed to conceptualize the pathological processes inherent to schizophrenia. The 'prostaglandin deficiency' hypothesis postulates that defective enzyme systems converting essential fatty acids to prostaglandins lead to diminished levels of prostaglandins, which in turn affect synaptic transmission.
Here we sought to determine the lipidomic profiles associated with schizophrenia in twin pairs discordant for schizophrenia as well as unaffected twin pairs. The study included serum samples from 19 twin pairs discordant for schizophrenia (mean age 51 ± 10 years; 7 monozygotic pairs; 13 female pairs) and 34 age and gender matched healthy twins as controls. Neurocognitive assessment data and gray matter density measurements taken from high-resolution magnetic resonance images were also obtained. A lipidomics platform using ultra performance liquid chromatography coupled to time-of-flight mass spectrometry was applied for the analysis of serum samples.
In comparison to their healthy co-twins, the patients had elevated triglycerides and were more insulin resistant. They had diminished lysophosphatidylcholine levels, which associated with decreased cognitive speed.
Our findings may be of pathophysiological relevance since lysophosphatidylcholines, byproducts of phospholipase A2-catalyzed phospholipid hydrolysis, are preferred carriers of polyunsaturated fatty acids across the blood-brain barrier. Furthermore, diminishment of lysophosphatidylcholines suggests that subjects at risk of schizophrenia may be more susceptible to infections. Their association with cognitive speed supports the view that altered neurotransmission in schizophrenia may be in part mediated by reactive lipids such as prostaglandins.
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.
Prostate cancer; PLA2G7; drug target; biomarker; statins
Because of the changes in demographic structure, the prevalence of Alzheimer's disease is expected to rise dramatically over the next decades. The progression of this degenerative and terminal disease is gradual, with the subclinical stage of illness believed to span several decades. Despite this, no therapy to prevent or cure Alzheimer's disease is currently available. Early disease detection is still important for delaying the onset of the disease with pharmacological treatment and/or lifestyle changes, assessing the efficacy of potential therapeutic agents, or monitoring disease progression more closely using medical imaging. Sensitive cerebrospinal-fluid-derived marker candidates exist, but given the invasiveness of sample collection their use in routine diagnostics may be limited. The pathogenesis of Alzheimer's disease is complex and poorly understood. There is thus a strong case for integrating information across multiple physiological levels, from molecular profiling (metabolomics, lipidomics, proteomics and transcriptomics) and brain imaging to cognitive assessments. To facilitate the integration of heterogeneous data, such as molecular and image data, sophisticated statistical approaches are needed to segment the image data and study their dependencies on molecular changes in the same individuals. Molecular profiling, combined with biophysical modeling of molecular assemblies associated with the disease, offer an opportunity to link the molecular pathway changes with cell- and tissue-level physiology and structure. Given that data acquired at different levels can carry complementary information about early Alzheimer's disease pathology, it is expected that their integration will improve early detection as well as our understanding of the disease.
Stable isotope tracers are used to assess metabolic flux profiles in living cells. The existing methods of measurement average out the isotopic isomer distribution in metabolites throughout the cell, whereas the knowledge of compartmental organization of analyzed pathways is crucial for the evaluation of true fluxes. That is why we accepted a challenge to create a software tool that allows deciphering the compartmentation of metabolites based on the analysis of average isotopic isomer distribution.
The software Isodyn, which simulates the dynamics of isotopic isomer distribution in central metabolic pathways, was supplemented by algorithms facilitating the transition between various analyzed metabolic schemes, and by the tools for model discrimination. It simulated 13C isotope distributions in glucose, lactate, glutamate and glycogen, measured by mass spectrometry after incubation of hepatocytes in the presence of only labeled glucose or glucose and lactate together (with label either in glucose or lactate). The simulations assumed either a single intracellular hexose phosphate pool, or also channeling of hexose phosphates resulting in a different isotopic composition of glycogen. Model discrimination test was applied to check the consistency of both models with experimental data. Metabolic flux profiles, evaluated with the accepted model that assumes channeling, revealed the range of changes in metabolic fluxes in liver cells.
The analysis of compartmentation of metabolic networks based on the measured 13C distribution was included in Isodyn as a routine procedure. The advantage of this implementation is that, being a part of evaluation of metabolic fluxes, it does not require additional experiments to study metabolic compartmentation. The analysis of experimental data revealed that the distribution of measured 13C-labeled glucose metabolites is inconsistent with the idea of perfect mixing of hexose phosphates in cytosol. In contrast, the observed distribution indicates the presence of a separate pool of hexose phosphates that is channeled towards glycogen synthesis.
Recent evidence from serum metabolomics indicates that specific metabolic disturbances precede β-cell autoimmunity in humans and can be used to identify those children who subsequently progress to type 1 diabetes. The mechanisms behind these disturbances are unknown. Here we show the specificity of the pre-autoimmune metabolic changes, as indicated by their conservation in a murine model of type 1 diabetes. We performed a study in non-obese prediabetic (NOD) mice which recapitulated the design of the human study and derived the metabolic states from longitudinal lipidomics data. We show that female NOD mice who later progress to autoimmune diabetes exhibit the same lipidomic pattern as prediabetic children. These metabolic changes are accompanied by enhanced glucose-stimulated insulin secretion, normoglycemia, upregulation of insulinotropic amino acids in islets, elevated plasma leptin and adiponectin, and diminished gut microbial diversity of the Clostridium leptum group. Together, the findings indicate that autoimmune diabetes is preceded by a state of increased metabolic demands on the islets resulting in elevated insulin secretion and suggest alternative metabolic related pathways as therapeutic targets to prevent diabetes.
We have recently found that distinct metabolic disturbances precede β-cell autoimmunity in children who later progress to type 1 diabetes (T1D). Here we performed a murine study using non-obese diabetic (NOD) mice that recapitulated the protocol used in human, followed up by independent studies where NOD mice were studied in relation to risk of diabetes progression. We found that young female NOD mice who later progress to autoimmune diabetes exhibit the same lipidomic pattern as prediabetic children. These metabolic changes are accompanied by enhanced glucose-stimulated insulin secretion, upregulation of insulinotropic amino acids in islets, elevated plasma leptin and adiponectin, and diminished gut microbial diversity of the Clostridium leptum subgroup. The metabolic phenotypes observed in our study could be relevant as end points for studies investigating T1D pathogenesis and/or responses to interventions. By proceeding from a clinical study via metabolomics and modeling to an experimental model using a similar study design, then evolving further to tissue-specific studies, we hereby also present a conceptually novel approach to reversed translation that may be useful in future therapeutic studies in the context of prevention and treatment of T1D as well as of other diseases characterized by long prodromal periods.
The mechanism behind the lowered postprandial insulin demand observed after rye bread intake compared to wheat bread is unknown. The aim of this study was to use the metabolomics approach to identify potential metabolites related to amino acid metabolism involved in this mechanism.
A sourdough fermented endosperm rye bread (RB) and a standard white wheat bread (WB) as a reference were served in random order to 16 healthy subjects. Test bread portions contained 50 g available carbohydrate. In vitro hydrolysis of starch and protein were performed for both test breads. Blood samples for measuring glucose and insulin concentrations were drawn over 4 h and gastric emptying rate (GER) was measured. Changes in the plasma metabolome were investigated by applying a comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry metabolomics platform (GC×GC-TOF-MS).
Plasma insulin response to RB was lower than to WB at 30 min (P = 0.004), 45 min (P = 0.002) and 60 min (P < 0.001) after bread intake, and plasma glucose response was significantly higher at time point 90 min after RB than WB intake (P = 0.045). The starch hydrolysis rate was higher for RB than WB, contrary to the in vitro protein digestibility. There were no differences in GER between breads. From 255 metabolites identified by the metabolomics platform, 26 showed significant postprandial relative changes after 30 minutes of bread intake (p and q values < 0.05). Among them, there were changes in essential amino acids (phenylalanine, methionine, tyrosine and glutamic acid), metabolites involved in the tricarboxylic acid cycle (alpha-ketoglutaric, pyruvic acid and citric acid) and several organic acids. Interestingly, the levels of two compounds involved in the tryptophan metabolism (picolinic acid, ribitol) significantly changed depending on the different bread intake.
A single meal of a low fibre sourdough rye bread producing low postprandial insulin response brings in several changes in plasma amino acids and their metabolites and some of these might have properties beneficial for health.
postprandial; rye bread; insulin; plasma metabolome; two-dimensional gas chromatography; gastric emptying rate