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1.  Metabolic Regulation in Progression to Autoimmune Diabetes 
PLoS Computational Biology  2011;7(10):e1002257.
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.
Author Summary
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.
doi:10.1371/journal.pcbi.1002257
PMCID: PMC3203065  PMID: 22046124
2.  High Density Lipoprotein Structural Changes and Drug Response in Lipidomic Profiles following the Long-Term Fenofibrate Therapy in the FIELD Substudy 
PLoS ONE  2011;6(8):e23589.
In a recent FIELD study the fenofibrate therapy surprisingly failed to achieve significant benefit over placebo in the primary endpoint of coronary heart disease events. Increased levels of atherogenic homocysteine were observed in some patients assigned to fenofibrate therapy but the molecular mechanisms behind this are poorly understood. Herein we investigated HDL lipidomic profiles associated with fenofibrate treatment and the drug-induced Hcy levels in the FIELD substudy. We found that fenofibrate leads to complex HDL compositional changes including increased apoA-II, diminishment of lysophosphatidylcholines and increase of sphingomyelins. Ethanolamine plasmalogens were diminished only in a subgroup of fenofibrate-treated patients with elevated homocysteine levels. Finally we performed molecular dynamics simulations to qualitatively reconstitute HDL particles in silico. We found that increased number of apoA-II excludes neutral lipids from HDL surface and apoA-II is more deeply buried in the lipid matrix than apoA-I. In conclusion, a detailed molecular characterization of HDL may provide surrogates for predictors of drug response and thus help identify the patients who might benefit from fenofibrate treatment.
doi:10.1371/journal.pone.0023589
PMCID: PMC3160907  PMID: 21887280
3.  Association of Lipidome Remodeling in the Adipocyte Membrane with Acquired Obesity in Humans 
PLoS Biology  2011;9(6):e1000623.
The authors describe a new approach to studying cellular lipid profiles and propose a compensatory mechanism that may help maintain the normal membrane function of adipocytes in the context of obesity.
Identification of early mechanisms that may lead from obesity towards complications such as metabolic syndrome is of great interest. Here we performed lipidomic analyses of adipose tissue in twin pairs discordant for obesity but still metabolically compensated. In parallel we studied more evolved states of obesity by investigating a separated set of individuals considered to be morbidly obese. Despite lower dietary polyunsaturated fatty acid intake, the obese twin individuals had increased proportions of palmitoleic and arachidonic acids in their adipose tissue, including increased levels of ethanolamine plasmalogens containing arachidonic acid. Information gathered from these experimental groups was used for molecular dynamics simulations of lipid bilayers combined with dependency network analysis of combined clinical, lipidomics, and gene expression data. The simulations suggested that the observed lipid remodeling maintains the biophysical properties of lipid membranes, at the price, however, of increasing their vulnerability to inflammation. Conversely, in morbidly obese subjects, the proportion of plasmalogens containing arachidonic acid in the adipose tissue was markedly decreased. We also show by in vitro Elovl6 knockdown that the lipid network regulating the observed remodeling may be amenable to genetic modulation. Together, our novel approach suggests a physiological mechanism by which adaptation of adipocyte membranes to adipose tissue expansion associates with positive energy balance, potentially leading to higher vulnerability to inflammation in acquired obesity. Further studies will be needed to determine the cause of this effect.
Author Summary
Obesity is characterized by excess body fat, which is predominantly stored in the adipose tissue. When adipose tissue expands too much it stops storing lipid appropriately. The excess lipid accumulates in organs such as muscle, liver, and pancreas, causing metabolic disease. In this study, we aim to identify factors that cause adipose tissue to malfunction when it reaches its limit of expansion. We performed lipidomic analyses of human adipose tissue in twin pairs discordant for obesity—that is, one of the twins was lean and one was obese—but still metabolically healthy. We identified multiple changes in membrane phospholipids. Using computer modeling, we show that “lean” and “obese” membrane lipid compositions have the same physical properties despite their different compositions. We hypothesize that this represents allostasis—changes in lipid membrane composition in obesity occur to protect the physical properties of the membranes. However, protective changes cannot occur without a cost, and accordingly we demonstrate that switching to the “obese” lipid composition is associated with higher levels of adipose tissue inflammation. In a separate group of metabolically unhealthy obese individuals we investigated how the processes that regulate the “lean” and “obese” lipid profiles are changed. To determine how these lipid membrane changes are regulated we constructed an in silico network model that identified key control points and potential molecular players. We validated this network by performing genetic manipulations in cell models. Therapeutic targeting of this network may open new opportunities for the prevention or treatment of obesity-related metabolic complications.
doi:10.1371/journal.pbio.1000623
PMCID: PMC3110175  PMID: 21666801
4.  Dysregulation of lipid and amino acid metabolism precedes islet autoimmunity in children who later progress to type 1 diabetes 
The Journal of Experimental Medicine  2008;205(13):2975-2984.
The risk determinants of type 1 diabetes, initiators of autoimmune response, mechanisms regulating progress toward β cell failure, and factors determining time of presentation of clinical diabetes are poorly understood. We investigated changes in the serum metabolome prospectively in children who later progressed to type 1 diabetes. Serum metabolite profiles were compared between sample series drawn from 56 children who progressed to type 1 diabetes and 73 controls who remained nondiabetic and permanently autoantibody negative. Individuals who developed diabetes had reduced serum levels of succinic acid and phosphatidylcholine (PC) at birth, reduced levels of triglycerides and antioxidant ether phospholipids throughout the follow up, and increased levels of proinflammatory lysoPCs several months before seroconversion to autoantibody positivity. The lipid changes were not attributable to HLA-associated genetic risk. The appearance of insulin and glutamic acid decarboxylase autoantibodies was preceded by diminished ketoleucine and elevated glutamic acid. The metabolic profile was partially normalized after the seroconversion. Autoimmunity may thus be a relatively late response to the early metabolic disturbances. Recognition of these preautoimmune alterations may aid in studies of disease pathogenesis and may open a time window for novel type 1 diabetes prevention strategies.
doi:10.1084/jem.20081800
PMCID: PMC2605239  PMID: 19075291
5.  Triacylglycerol Fatty Acid Composition in Diet-Induced Weight Loss in Subjects with Abnormal Glucose Metabolism – the GENOBIN Study 
PLoS ONE  2008;3(7):e2630.
Background
The effect of weight loss on different plasma lipid subclasses at the molecular level is unknown. The aim of this study was to examine whether a diet-induced weight reduction result in changes in the extended plasma lipid profiles (lipidome) in subjects with features of metabolic syndrome in a 33-week intervention.
Methodology/Principal Findings
Plasma samples of 9 subjects in the weight reduction group and 10 subjects in the control group were analyzed using mass spectrometry based lipidomic and fatty acid analyses. Body weight decreased in the weight reduction group by 7.8±2.9% (p<0.01). Most of the serum triacylglycerols and phosphatidylcholines were reduced. The decrease in triacylglycerols affected predominantly the saturated short chain fatty acids. This decrease of saturated short chain fatty acid containing triacylglycerols correlated with the increase of insulin sensitivity. However, levels of several longer chain fatty acids, including arachidonic and docosahexanoic acid, were not affected by weight loss. Levels of other lipids known to be associated with obesity such as sphingolipids and lysophosphatidylcholines were not altered by weight reduction.
Conclusions/Significance
Diet-induced weight loss caused significant changes in global lipid profiles in subjects with abnormal glucose metabolism. The observed changes may affect insulin sensitivity and glucose metabolism in these subjects.
Trial Registration
ClinicalTrials.gov NCT00621205
doi:10.1371/journal.pone.0002630
PMCID: PMC2440352  PMID: 18612464
6.  PPAR gamma 2 Prevents Lipotoxicity by Controlling Adipose Tissue Expandability and Peripheral Lipid Metabolism 
PLoS Genetics  2007;3(4):e64.
Peroxisome proliferator activated receptor gamma 2 (PPARg2) is the nutritionally regulated isoform of PPARg. Ablation of PPARg2 in the ob/ob background, PPARg2−/− Lepob/Lepob (POKO mouse), resulted in decreased fat mass, severe insulin resistance, β-cell failure, and dyslipidaemia. Our results indicate that the PPARg2 isoform plays an important role, mediating adipose tissue expansion in response to positive energy balance. Lipidomic analyses suggest that PPARg2 plays an important antilipotoxic role when induced ectopically in liver and muscle by facilitating deposition of fat as relatively harmless triacylglycerol species and thus preventing accumulation of reactive lipid species. Our data also indicate that PPARg2 may be required for the β-cell hypertrophic adaptive response to insulin resistance. In summary, the PPARg2 isoform prevents lipotoxicity by (a) promoting adipose tissue expansion, (b) increasing the lipid-buffering capacity of peripheral organs, and (c) facilitating the adaptive proliferative response of β-cells to insulin resistance.
Author Summary
It is known that obesity is linked to type 2 diabetes, however how obesity causes insulin resistance and diabetes is not well understood. Some extremely obese people are not diabetic, while other less obese people develop severe insulin resistance and diabetes. We believe diabetes occurs when adipose tissue becomes “full,” and fat overflows into other organs such as liver, pancreas, and muscle, causing insulin resistance and diabetes. Peroxisome proliferator activated receptor gamma (PPARg) is essential for the development of adipose tissue and control of insulin sensitivity. PPARg2 is the isoform of PPARg regulated by nutrition. Here we investigate the role of PPARg2 under conditions of excess nutrients by removing the PPARg2 isoform in genetically obese mice, the POKO mouse. We report that removing PPARg2 decreases adipose tissue's capacity to expand and prevents the mouse from making as much fat as a normal obese mouse, despite eating similarly. Our studies suggest that PPARg plays an important antitoxic role when it is induced in liver, muscle, and beta cells by facilitating deposition of fat as relatively harmless lipids and thus prevents accumulation of toxic lipid species. We also show that PPARg2 may be involved in the adaptive response of beta cells to insulin resistance.
doi:10.1371/journal.pgen.0030064
PMCID: PMC1857730  PMID: 17465682
7.  Normalization method for metabolomics data using optimal selection of multiple internal standards 
BMC Bioinformatics  2007;8:93.
Background
Success of metabolomics as the phenotyping platform largely depends on its ability to detect various sources of biological variability. Removal of platform-specific sources of variability such as systematic error is therefore one of the foremost priorities in data preprocessing. However, chemical diversity of molecular species included in typical metabolic profiling experiments leads to different responses to variations in experimental conditions, making normalization a very demanding task.
Results
With the aim to remove unwanted systematic variation, we present an approach that utilizes variability information from multiple internal standard compounds to find optimal normalization factor for each individual molecular species detected by metabolomics approach (NOMIS). We demonstrate the method on mouse liver lipidomic profiles using Ultra Performance Liquid Chromatography coupled to high resolution mass spectrometry, and compare its performance to two commonly utilized normalization methods: normalization by l2 norm and by retention time region specific standard compound profiles. The NOMIS method proved superior in its ability to reduce the effect of systematic error across the full spectrum of metabolite peaks. We also demonstrate that the method can be used to select best combinations of standard compounds for normalization.
Conclusion
Depending on experiment design and biological matrix, the NOMIS method is applicable either as a one-step normalization method or as a two-step method where the normalization parameters, influenced by variabilities of internal standard compounds and their correlation to metabolites, are first calculated from a study conducted in repeatability conditions. The method can also be used in analytical development of metabolomics methods by helping to select best combinations of standard compounds for a particular biological matrix and analytical platform.
doi:10.1186/1471-2105-8-93
PMCID: PMC1838434  PMID: 17362505
8.  Bioinformatics strategies for lipidomics analysis: characterization of obesity related hepatic steatosis 
BMC Systems Biology  2007;1:12.
Background
Lipids are an important and highly diverse class of molecules having structural, energy storage and signaling roles. Modern analytical technologies afford screening of many lipid molecular species in parallel. One of the biggest challenges of lipidomics is elucidation of important pathobiological phenomena from the integration of the large amounts of new data becoming available.
Results
We present computational and informatics approaches to study lipid molecular profiles in the context of known metabolic pathways and established pathophysiological responses, utilizing information obtained from modern analytical technologies. In order to facilitate identification of lipids, we compute the scaffold of theoretically possible lipids based on known lipid building blocks such as polar head groups and fatty acids. Each compound entry is linked to the available information on lipid pathways and contains the information that can be utilized for its automated identification from high-throughput UPLC/MS-based lipidomics experiments. The utility of our approach is demonstrated by its application to the lipidomic characterization of the fatty liver of the genetically obese insulin resistant ob/ob mouse model. We investigate the changes of correlation structure of the lipidome using multivariate analysis, as well as reconstruct the pathways for specific molecular species of interest using available lipidomic and gene expression data.
Conclusion
The methodology presented herein facilitates identification and interpretation of high-throughput lipidomics data. In the context of the ob/ob mouse liver profiling, we have identified the parallel associations between the elevated triacylglycerol levels and the ceramides, as well as the putative activated ceramide-synthesis pathways.
doi:10.1186/1752-0509-1-12
PMCID: PMC1839890  PMID: 17408502

Results 1-8 (8)