PubMed

Identifying biomarkers for asthma diagnosis using targeted metabolomics approaches. Respir Med. 2016 Dec;121:59-66 Authors: Checkley W, Deza MP, Klawitter J, Romero KM, Klawitter J, Pollard SL, Wise RA, Christians U, Hansel NN Abstract BACKGROUND: The diagnosis of asthma in children is challenging and relies on a combination of clinical factors and biomarkers including methacholine challenge, lung function, bronchodilator responsiveness, and presence of airway inflammation. No single test is diagnostic. We sought to identify a pattern of inflammatory biomarkers that was unique to asthma using a targeted metabolomics approach combined with data science methods. METHODS: We conducted a nested case-control study of 100 children living in a peri-urban community in Lima, Peru. We defined cases as children with current asthma, and controls as children with no prior history of asthma and normal lung function. We further categorized enrollment following a factorial design to enroll equal numbers of children as either overweight or not. We obtained a fasting venous blood sample to characterize a comprehensive panel of targeted markers using a metabolomics approach based on high performance liquid chromatography-mass spectrometry. RESULTS: A statistical comparison of targeted metabolites between children with asthma (n = 50) and healthy controls (n = 49) revealed distinct patterns in relative concentrations of several metabolites: children with asthma had approximately 40-50% lower relative concentrations of ascorbic acid, 2-isopropylmalic acid, shikimate-3-phosphate, and 6-phospho-d-gluconate when compared to children without asthma, and 70% lower relative concentrations of reduced glutathione (all p < 0.001 after Bonferroni correction). Moreover, a combination of 2-isopropylmalic acid and betaine strongly discriminated between children with asthma (2-isopropylmalic acid ≤ 13 077 normalized counts/second) and controls (2-isopropylmalic acid > 13 077 normalized counts/second and betaine ≤ 16 47 121 normalized counts/second). CONCLUSIONS: By using a metabolomics approach applied to serum, we were able to discriminate between children with and without asthma by revealing different metabolic patterns. These results suggest that serum metabolomics may represent a diagnostic tool for asthma and may be helpful for distinguishing asthma phenotypes. PMID: 27888993 [PubMed - in process]

Reversed-phase separation methods for glycan analysis. Anal Bioanal Chem. 2016 Nov 25; Authors: Vreeker GC, Wuhrer M Abstract Reversed-phase chromatography is a method that is often used for glycan separation. For this, glycans are often derivatized with a hydrophobic tag to achieve retention on hydrophobic stationary phases. The separation and elution order of glycans in reversed-phase chromatography is highly dependent on the hydrophobicity of the tag and the contribution of the glycan itself to the retention. The contribution of the different monosaccharides to the retention strongly depends on the position and linkage, and isomer separation may be achieved. The influence of sialic acids and fucoses on the retention of glycans is still incompletely understood and deserves further study. Analysis of complex samples may come with incomplete separation of glycan species, thereby complicating reversed-phase chromatography with fluorescence or UV detection, whereas coupling with mass spectrometry detection allows the resolution of complex mixtures. Depending on the column properties, eluents, and run time, separation of isomeric and isobaric structures can be accomplished with reversed-phase chromatography. Alternatively, porous graphitized carbon chromatography and hydrophilic interaction liquid chromatography are also able to separate isomeric and isobaric structures, generally without the necessity of glycan labeling. Hydrophilic interaction liquid chromatography, porous graphitized carbon chromatography, and reversed-phase chromatography all serve different research purposes and thus can be used for different research questions. A great advantage of reversed-phase chromatography is its broad distribution as it is used in virtually every bioanalytical research laboratory, making it an attracting platform for glycan analysis. Graphical Abstract Glycan isomer separation by reversed phase liquid chromatography. PMID: 27888305 [PubMed - as supplied by publisher]

Metabolomic profile of children with recurrent respiratory infections. Pharmacol Res. 2016 Nov 22;: Authors: Bozzetto S, Pirillo P, Carraro S, Berardi M, Cesca L, Stocchero M, Giordano G, Zanconato S, Baraldi E Abstract Recurrent respiratory infections (RRI) represent a widespread condition which has a severe social and economic impact. Immunostimulants are used for their prevention. It is crucial to better characterize children with RRI to refine their diagnosis and identify effective personalized prevention strategies. Metabolomics is a high-dimensional biological method that can be used for hypothesis-free biomarker profiling, examining a large number of metabolites in a given sample using spectroscopic techniques. Multivariate statistical data analysis then enables us to infer which metabolic information is relevant to the biological characterization of a given physiological or pathological condition. This can lead to the emergence of new, sometimes unexpected metabolites, and hitherto unknown metabolic pathways, enabling the formulation of new pathogenetic hypotheses, and the identification of new therapeutic targets. The aim of our pilot study was to apply mass-spectrometry-based metabolomics to the analysis of urine samples from children with RRI, comparing these children's biochemical metabolic profiles with those of healthy peers. We also compared the RRI children's and healthy controls' metabolomic urinary profiles after the former had received pidotimod treatment for 3 months to see whether this immunostimulant was associated with biochemical changes in the RRI children's metabolic profile. 13 children (age range 3-6 yeas) with RRI and 15 matched per age healthy peers with no history of respiratory diseases or allergies were enrolled. Their metabolomic urine samples were compared before and after the RRI children had been treated with pidotimod for a period of 3 months. Metabolomic analyses on the urine samples were done using mass spectrometry combined with ultra-performance liquid chromatography (UPLC-MS). The resulting spectroscopic data then underwent multivariate statistical analysis and the most relevant variables characterizing the two groups were identified. Data modeling with post-transformation of PLS2-Discriminant Analysis (ptPLS2-DA) generated a robust model capable of discriminating the urine samples from children with RRI from those of healthy controls (R(2)=0.92,Q(2)CV7-fold=0.75, p-value<0.001). The dataset included 1502 time per mass variables, and 138 of them characterized the difference between the two groups. Thirty-five of these distinctive 138 variables persisted in the profiles of the children with RRI after pidotimod treatment. Metabolomics can discriminate children with RRI from healthy controls, suggesting that the former have a dysregulated metabolic profile. Among the variables characterizing children with RRI there are metabolites that may reflect the presence of a different microbiome. After pidotimod treatment, the metabolic profile of the children with RRI was no longer very different from that of the healthy controls, except for the persistence of some microbiome-related variables. We surmise that pidotimod partially "restores" the altered metabolic profile of children with RRI, without modifying the metabolites related to the composition of the gut microbiota. In the light of these results, we hypothesize a potential synergic effect of the combined use of immunostimulants and probiotics for the purpose of prevention in children with RRI. PMID: 27888158 [PubMed - as supplied by publisher]

Fab glycosylation of immunoglobulin G does not associate with improvement of rheumatoid arthritis during pregnancy. Arthritis Res Ther. 2016 Nov 25;18(1):274 Authors: Bondt A, Wuhrer M, Kuijper TM, Hazes JM, Dolhain RJ Abstract BACKGROUND: Changes in immunoglobulin G (IgG) constant domain (Fc) glycosylation are associated with changes in rheumatoid arthritis (RA) disease activity in response to pregnancy. Here, we sought to determine whether the same holds true for variable domain (Fab) glycosylation. METHODS: IgGs were captured from RA and control sera obtained before (RA only), during and after pregnancy, followed by Fc and Fab separation, glycan release, and mass spectrometric detection. In parallel, glycans from intact IgG were analysed. The data was used to calculate glycosylation traits, and to estimate the level of Fab glycosylation. RESULTS: The overall level of Fab glycosylation was increased in RA patients compared to controls, while no differences in Fab glycosylation patterns were found. For the Fc and intact IgG (Total) previously observed differences in galactosylation and bisection were confirmed. Furthermore, increased galactosylation of Fc and Total were associated with lower disease activity and autoantibody positivity. In addition, the change in Fc galactosylation associated with the change in disease activity during pregnancy and after delivery, while this was not the case for Fab. CONCLUSIONS: In contrast to changes in Fc glycosylation, changes in Fab glycosylation are not associated with improvement of RA during pregnancy and arthritis flare after delivery. PMID: 27887659 [PubMed - in process]

A new method of finding groups of coexpressed genes and conditions of coexpression. BMC Bioinformatics. 2016 Nov 25;17(1):486 Authors: Anand R, Ravichandran S, Chatterjee S Abstract BACKGROUND: To study a biological phenomenon such as finding mechanism of disease, common methodology is to generate the microarray data in different relevant conditions and find groups of genes co-expressed across conditions from such data. These groups might enable us to find biological processes involved in a disease condition. However, more detailed understanding can be made when information of a biological process associated with a particular condition is obtained from the data. Many algorithms are available which finds groups of co-expressed genes and associated conditions of co-expression that can help finding processes associated with particular condition. However, these algorithms depend on different input parameters for generating groups. For real datasets, it is difficult to use these algorithms due to unknown values of these parameters. RESULTS: We present here an algorithm, clustered groups, which finds groups of co-expressed genes and conditions of co-expression with minimal input from user. We used random datasets to derive a cutoff on the basis of which we filtered the resultant groups and showed that this can improve the relevance of obtained groups. We showed that the proposed algorithm performs better than other known algorithms on both real and synthetic datasets. We have also shown its application on a temporal microarray dataset by extracting biclusters and biological information hidden in those biclusters. CONCLUSIONS: Clustered groups is an algorithm which finds groups of co-expressed genes and conditions of co-expression using only a single parameter. We have shown that it works better than other existing algorithms. It can be used to find these groups in different data types such as microarray, proteomics, metabolomics etc. PMID: 27887568 [PubMed - in process]

A multi-omic approach to elucidate low-dose effects of xenobiotics in zebrafish (Danio rerio) larvae. Aquat Toxicol. 2016 Nov 18;182:102-112 Authors: Huang SS, Benskin JP, Veldhoen N, Chandramouli B, Butler H, Helbing CC, Cosgrove JR Abstract Regulatory-approved toxicity assays such as the OECD Fish Embryo Toxicity Assay (TG236) allow correlation of chemical exposure to adverse morphological phenotypes. However, these assays are ineffective in assessing sub-lethal (i.e. low-dose) effects, or differentiating between similar phenotypes induced by different chemicals. Inclusion of multi-omic analyses in studies investigating xenobiotic action provides improved characterization of biological response, thereby enhancing prediction of toxicological outcomes in whole animals in the absence of morphological effects. In the current study, we assessed perturbations in both the metabolome and transcriptome of zebrafish (Danio rerio; ZF) larvae exposed from 96 to 120h post fertilization to environmental concentrations of acetaminophen (APAP), diphenhydramine (DH), carbamazepine (CBZ), and fluoxetine (FLX); common pharmaceuticals with known mechanisms of action. Multi-omic responses were evaluated independently and integrated to identify molecular interactions and biological relevance of the responses. Results indicated chemical- and dose-specific changes suggesting differences in the time scale of transcript abundance and metabolite production. Increased impact on the metabolome relative to the transcriptome in FLX-treated animals suggests a stronger post-translational effect of the treatment. In contrast, the transcriptome showed higher sensitivity to perturbation in DH-exposed animals. Integration of 'omic' responses using multivariate approaches provided additional insights not obtained by independent 'omic' analyses and demonstrated that the most distinct overall response profiles were induced following low-dose exposure for all 4 pharmaceuticals. Importantly, changes in transcript abundance corroborated with predictions from metabolomic enrichment analyses and the identified perturbed biological pathways aligned with known xenobiotic mechanisms of action. This work demonstrates that a multi-omic toxicological approach, coupled with a sensitive animal model such as ZF larvae, can help characterize the toxicological relevance of acute low-dose chemical exposures. PMID: 27886581 [PubMed - as supplied by publisher]

Exploring the molecular basis of age-related disease comorbidities using a multi-omics graphical model. Sci Rep. 2016 Nov 25;6:37646 Authors: Zierer J, Pallister T, Tsai PC, Krumsiek J, Bell JT, Lauc G, Spector TD, Menni C, Kastenmüller G Abstract Although association studies have unveiled numerous correlations of biochemical markers with age and age-related diseases, we still lack an understanding of their mutual dependencies. To find molecular pathways that underlie age-related diseases as well as their comorbidities, we integrated aging markers from four different high-throughput omics datasets, namely epigenomics, transcriptomics, glycomics and metabolomics, with a comprehensive set of disease phenotypes from 510 participants of the TwinsUK cohort. We used graphical random forests to assess conditional dependencies between omics markers and phenotypes while eliminating mediated associations. Applying this novel approach for multi-omics data integration yields a model consisting of seven modules that represent distinct aspects of aging. These modules are connected by hubs that potentially trigger comorbidities of age-related diseases. As an example, we identified urate as one of these key players mediating the comorbidity of renal disease with body composition and obesity. Body composition variables are in turn associated with inflammatory IgG markers, mediated by the expression of the hormone oxytocin. Thus, oxytocin potentially contributes to the development of chronic low-grade inflammation, which often accompanies obesity. Our multi-omics graphical model demonstrates the interconnectivity of age-related diseases and highlights molecular markers of the aging process that might drive disease comorbidities. PMID: 27886242 [PubMed - in process]

Novel biomarker identification using metabolomic profiling to differentiate radiation necrosis and recurrent tumor following Gamma Knife radiosurgery. J Neurosurg. 2016 Nov 25;:1-9 Authors: Lu AY, Turban JL, Damisah EC, Li J, Alomari AK, Eid T, Vortmeyer AO, Chiang VL Abstract OBJECTIVE Following an initial response of brain metastases to Gamma Knife radiosurgery, regrowth of the enhancing lesion as detected on MRI may represent either radiation necrosis (a treatment-related inflammatory change) or recurrent tumor. Differentiation of radiation necrosis from tumor is vital for management decision making but remains difficult by imaging alone. In this study, gas chromatography with time-of-flight mass spectrometry (GC-TOF) was used to identify differential metabolite profiles of the 2 tissue types obtained by surgical biopsy to find potential targets for noninvasive imaging. METHODS Specimens of pure radiation necrosis and pure tumor obtained from patient brain biopsies were flash-frozen and validated histologically. These formalin-free tissue samples were then analyzed using GC-TOF. The metabolite profiles of radiation necrosis and tumor samples were compared using multivariate and univariate statistical analysis. Statistical significance was defined as p ≤ 0.05. RESULTS For the metabolic profiling, GC-TOF was performed on 7 samples of radiation necrosis and 7 samples of tumor. Of the 141 metabolites identified, 17 (12.1%) were found to be statistically significantly different between comparison groups. Of these metabolites, 6 were increased in tumor, and 11 were increased in radiation necrosis. An unsupervised hierarchical clustering analysis found that tumor had elevated levels of metabolites associated with energy metabolism, whereas radiation necrosis had elevated levels of metabolites that were fatty acids and antioxidants/cofactors. CONCLUSIONS To the authors' knowledge, this is the first tissue-based metabolomics study of radiation necrosis and tumor. Radiation necrosis and recurrent tumor following Gamma Knife radiosurgery for brain metastases have unique metabolite profiles that may be targeted in the future to develop noninvasive metabolic imaging techniques. PMID: 27885954 [PubMed - as supplied by publisher]

Urinary signature of pig carcasses with boar taint by liquid chromatography-high resolution mass spectrometry. Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2016 Nov 25; Authors: Jacob CC, Dervilly-Pinel G, Deceuninck Y, Gicquiau A, Chevillon P, Bonneau M, Le Bizec B Abstract Boar taint is an offensive odor that can occur while cooking pork or pork products and is identified in some uncastrated male pigs that have reached puberty. It is widely held that boar taint is the result of the accumulation in back-fat of two malodorous compounds: androstenone and skatole. The purpose of the present study was to assess a mass spectrometry-based metabolomics strategy to investigate the metabolic profile of urine samples from pig carcasses presenting low (untainted) and high (tainted) levels of androstenone and skatole in back fat. Urine samples were analyzed by LC-ESI(+)-HRMS. Discrimination between tainted and untainted animals was observed by application of multivariate statistical analysis, which allowed to highlight candidate urinary biomarkers. These urinary metabolites were positively correlated to androstenone and skatole levels in back fat. Therefore, the present study suggested that the measurement of these urinary metabolites might provide information with regard to androstenone and skatole levels in live pigs. PMID: 27885948 [PubMed - as supplied by publisher]

Metabolomic Analysis of Campylobacter jejuni by Direct-Injection Electrospray Ionization Mass Spectrometry. Methods Mol Biol. 2017;1512:189-197 Authors: Howlett RM, Davey MP, Kelly DJ Abstract Direct-injection mass spectrometry (DIMS) is a means of rapidly obtaining metabolomic phenotype data in both prokaryotes and eukaryotes. Given our generally poor understanding of Campylobacter metabolism, the high-throughput and relatively simple sample preparation of DIMS has made this an attractive technique for metabolism-related studies and hypothesis generation, especially when attempting to analyze metabolic mutants with no clear phenotype. Here we describe a metabolomic fingerprinting approach with sampling and extraction methodologies optimized for direct-injection electrospray ionization mass spectrometry (ESI-MS), which we have used as a means of comparing wild-type and isogenic mutant strains of C. jejuni with various metabolic blocks. PMID: 27885608 [PubMed - in process]

Whole genome sequence analysis of serum amino acid levels. Genome Biol. 2016 Nov 24;17(1):237 Authors: Yu B, de Vries PS, Metcalf GA, Wang Z, Feofanova EV, Liu X, Muzny DM, Wagenknecht LE, Gibbs RA, Morrison AC, Boerwinkle E Abstract BACKGROUND: Blood levels of amino acids are important biomarkers of disease and are influenced by synthesis, protein degradation, and gene-environment interactions. Whole genome sequence analysis of amino acid levels may establish a paradigm for analyzing quantitative risk factors. RESULTS: In a discovery cohort of 1872 African Americans and a replication cohort of 1552 European Americans we sequenced exons and whole genomes and measured serum levels of 70 amino acids. Rare and low-frequency variants (minor allele frequency ≤5%) were analyzed by three types of aggregating motifs defined by gene exons, regulatory regions, or genome-wide sliding windows. Common variants (minor allele frequency >5%) were analyzed individually. Over all four analysis strategies, 14 gene-amino acid associations were identified and replicated. The 14 loci accounted for an average of 1.8% of the variance in amino acid levels, which ranged from 0.4 to 9.7%. Among the identified locus-amino acid pairs, four are novel and six have been reported to underlie known Mendelian conditions. These results suggest that there may be substantial genetic effects on amino acid levels in the general population that may underlie inborn errors of metabolism. We also identify a predicted promoter variant in AGA (the gene that encodes aspartylglucosaminidase) that is significantly associated with asparagine levels, with an effect that is independent of any observed coding variants. CONCLUSIONS: These data provide insights into genetic influences on circulating amino acid levels by integrating -omic technologies in a multi-ethnic population. The results also help establish a paradigm for whole genome sequence analysis of quantitative traits. PMID: 27884205 [PubMed - in process]

Recent applications of metabolomics to advance microbial biofuel production. Curr Opin Biotechnol. 2016 Nov 21;43:118-126 Authors: Martien JI, Amador-Noguez D Abstract Biofuel production from plant biomass is a promising source of renewable energy [1]. However, efficient biofuel production involves the complex task of engineering high-performance microorganisms, which requires detailed knowledge of metabolic function and regulation. This review highlights the potential of mass-spectrometry-based metabolomic analysis to guide rational engineering of biofuel-producing microbes. We discuss recent studies that apply knowledge gained from metabolomic analyses to increase the productivity of engineered pathways, characterize the metabolism of emerging biofuel producers, generate novel bioproducts, enable utilization of lignocellulosic feedstock, and improve the stress tolerance of biofuel producers. PMID: 27883952 [PubMed - as supplied by publisher]

Circulating adipocyte-derived exosomal MicroRNAs associated with decreased insulin resistance after gastric bypass. Obesity (Silver Spring). 2016 Nov 24;: Authors: Hubal MJ, Nadler EP, Ferrante SC, Barberio MD, Suh JH, Wang J, Dohm GL, Pories WJ, Mietus-Snyder M, Freishtat RJ Abstract OBJECTIVE: Exosomes from obese adipose contain dysregulated microRNAs linked to insulin signaling, as compared with lean controls, providing a direct connection between adiposity and insulin resistance. This study tested the hypotheses that gastric bypass surgery and its subsequent weight loss would normalize adipocyte-derived exosomal microRNAs associated with insulin signaling and the associated metabolome related to glucose homeostasis. METHODS: African American female subjects with obesity (N = 6; age: 38.5 ± 6.8 years; BMI: 51.2 ± 8.8 kg/m(2) ) were tested before and 1 year after surgery. Insulin resistance (HOMA), serum metabolomics, and global microRNA profiles of circulating adipocyte-derived exosomes were evaluated via ANCOVA and correlational analyses. RESULTS: One year postsurgery, patients showed decreased BMI (-18.6 ± 5.1 kg/m(2) ; P < 0.001), ameliorated insulin resistance (HOMA: 1.94 ± 0.6 presurgery, 0.49 ± 0.1 postsurgery; P < 0.001), and altered metabolites including branched chain amino acids (BCAA). Biological pathway analysis of predicted mRNA targets of 168 surgery-responsive microRNAs (P < 0.05) identified the insulin signaling pathway (P = 1.27E-10; 52/138 elements), among others, in the data set. The insulin signaling pathway was also a target of 10 microRNAs correlated to changes in HOMA (P < 0.05; r > 0.4), and 48 microRNAs correlated to changes in BCAA levels. CONCLUSIONS: These data indicate that circulating adipocyte-derived exosomes are modified following gastric bypass surgery and correlate to improved postsurgery insulin resistance. PMID: 27883272 [PubMed - as supplied by publisher]

Effects of MeJA on Arabidopsis metabolome under endogenous JA deficiency. Sci Rep. 2016 Nov 24;6:37674 Authors: Cao J, Li M, Chen J, Liu P, Li Z Abstract Jasmonates (JAs) play important roles in plant growth, development and defense. Comprehensive metabolomics profiling of plants under JA treatment provides insights into the interaction and regulation network of plant hormones. Here we applied high resolution mass spectrometry based metabolomics approach on Arabidopsis wild type and JA synthesis deficiency mutant opr3. The effects of exogenous MeJA treatment on the metabolites of opr3 were investigated. More than 10000 ion signals were detected and more than 2000 signals showed significant variation in different genotypes and treatment groups. Multivariate statistic analyses (PCA and PLS-DA) were performed and a differential compound library containing 174 metabolites with high resolution precursor ion-product ions pairs was obtained. Classification and pathway analysis of 109 identified compounds in this library showed that glucosinolates and tryptophan metabolism, amino acids and small peptides metabolism, lipid metabolism, especially fatty acyls metabolism, were impacted by endogenous JA deficiency and exogenous MeJA treatment. These results were further verified by quantitative reverse transcription PCR (RT-qPCR) analysis of 21 related genes involved in the metabolism of glucosinolates, tryptophan and α-linolenic acid pathways. The results would greatly enhance our understanding of the biological functions of JA. PMID: 27883040 [PubMed - in process]

The mevalonate pathway regulates primitive streak formation via protein farnesylation. Sci Rep. 2016 Nov 24;6:37697 Authors: Okamoto-Uchida Y, Yu R, Miyamura N, Arima N, Ishigami-Yuasa M, Kagechika H, Yoshida S, Hosoya T, Nawa M, Kasama T, Asaoka Y, Alois RW, Elling U, Penninger JM, Nishina S, Azuma N, Nishina H Abstract The primitive streak in peri-implantation embryos forms the mesoderm and endoderm and controls cell differentiation. The metabolic cues regulating primitive streak formation remain largely unknown. Here we utilised a mouse embryonic stem (ES) cell differentiation system and a library of well-characterised drugs to identify these metabolic factors. We found that statins, which inhibit the mevalonate metabolic pathway, suppressed primitive streak formation in vitro and in vivo. Using metabolomics and pharmacologic approaches we identified the downstream signalling pathway of mevalonate and revealed that primitive streak formation requires protein farnesylation but not cholesterol synthesis. A tagging-via-substrate approach revealed that nuclear lamin B1 and small G proteins were farnesylated in embryoid bodies and important for primitive streak gene expression. In conclusion, protein farnesylation driven by the mevalonate pathway is a metabolic cue essential for primitive streak formation. PMID: 27883036 [PubMed - in process]

Plasma Metabolomics Implicate Modified Transfer RNAs and Altered Bioenergetics in the Outcome of Pulmonary Arterial Hypertension. Circulation. 2016 Nov 21;: Authors: Rhodes CJ, Ghataorhe P, Wharton J, Rue-Albrecht KC, Hadinnapola C, Watson G, Bleda M, Haimel M, Coghlan G, Corris PA, Howard LS, Kiely DG, Peacock AJ, Pepke-Zaba J, Toshner M, Wort SJ, Gibbs JS, Lawrie A, Gräf S, Morrell NW, Wilkins MR Abstract BACKGROUND: -Pulmonary arterial hypertension (PAH) is a heterogeneous disorder with high mortality. METHODS: -We conducted a comprehensive study of plasma metabolites using ultra-performance liquid chromatography mass-spectrometry to (1) identify patients at high risk of early death, (2) identify patients who respond well to treatment and (3) provide novel molecular insights into disease pathogenesis. RESULTS: -53 circulating metabolites distinguished well-phenotyped patients with idiopathic or heritable PAH (n=365) from healthy controls (n=121) following correction for multiple testing (p<7.3e-5) and confounding factors, including drug therapy, renal and hepatic impairment. A subset of 20/53 metabolites also discriminated PAH patients from disease controls (symptomatic patients without pulmonary hypertension, n=139). 62 metabolites were prognostic in PAH, with 36/62 independent of established prognostic markers. Increased levels of tRNA-specific modified nucleosides (N2,N2-dimethylguanosine, N1-methylinosine), TCA cycle intermediates (malate, fumarate), glutamate, fatty acid acylcarnitines, tryptophan and polyamine metabolites and decreased levels of steroids, sphingomyelins and phosphatidylcholines distinguished patients from controls. The largest differences correlated with increased risk of death and correction of several metabolites over time was associated with a better outcome. Patients who responded to calcium channel blocker therapy had metabolic profiles similar to healthy controls. CONCLUSIONS: -Metabolic profiles in PAH are strongly related to survival and should be considered part of the deep phenotypic characterisation of this disease. Our results support the investigation of targeted therapeutic strategies that seek to address the alterations in translational regulation and energy metabolism that characterize these patients. PMID: 27881557 [PubMed - as supplied by publisher]

Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences. Brief Bioinform. 2016 Nov 22;: Authors: Manzoni C, Kia DA, Vandrovcova J, Hardy J, Wood NW, Lewis PA, Ferrari R Abstract Advances in the technologies and informatics used to generate and process large biological data sets (omics data) are promoting a critical shift in the study of biomedical sciences. While genomics, transcriptomics and proteinomics, coupled with bioinformatics and biostatistics, are gaining momentum, they are still, for the most part, assessed individually with distinct approaches generating monothematic rather than integrated knowledge. As other areas of biomedical sciences, including metabolomics, epigenomics and pharmacogenomics, are moving towards the omics scale, we are witnessing the rise of inter-disciplinary data integration strategies to support a better understanding of biological systems and eventually the development of successful precision medicine. This review cuts across the boundaries between genomics, transcriptomics and proteomics, summarizing how omics data are generated, analysed and shared, and provides an overview of the current strengths and weaknesses of this global approach. This work intends to target students and researchers seeking knowledge outside of their field of expertise and fosters a leap from the reductionist to the global-integrative analytical approach in research. PMID: 27881428 [PubMed - as supplied by publisher]

A novel glucagon-like peptide 1/glucagon receptor dual agonist improves steatohepatitis and liver regeneration in mice. Hepatology. 2016 Nov 23;: Authors: Valdecantos MP, Pardo V, Ruiz L, Castro-Sánchez L, Lanzón B, Fernández-Millán E, García-Monzón C, Arroba AI, González-Rodríguez Á, Escrivá F, Carmen Á, Rupérez FJ, Barbas C, Konkar A, Naylor J, Hornigold D, Dos Santos A, Bednarek M, Grimsby J, Rondinone CM, Valverde ÁM Abstract BACKGROUND AND AIMS: Since non-alcoholic steatohepatitis (NASH) is associated with impaired liver regeneration, we investigated the effects of G49, a dual glucagon-like peptide-1(GLP-1)/glucagon (GCG) receptor agonist, on NASH and hepatic regeneration. METHODS: C57Bl/6 mice fed chow or methionine and choline-deficient (MCD) diet for one week were divided into 4 groups: C (chow diet), MCD (MCD diet), C+G49 (chow diet plus G49) and M+G49 (MCD diet plus G49). Mice fed high fat diet (HFD) for 10 weeks were divided in groups: HFD and H+G49 (HFD plus G49). Following 2 (MCD groups) or 3 (HFD groups) weeks of treatment with G49, partial hepatectomy (PH) was performed and all mice were maintained on the same treatment schedule for 2 additional weeks. Analysis of liver function, hepatic regeneration and comprehensive genomic and metabolic profiling was conducted. RESULTS: NASH was ameliorated in M+G49 group manifested by reduced inflammation, steatosis, oxidative stress, apoptosis and increased mitochondrial biogenesis. G49 treatment was also associated with replenishment of intrahepatic glucose due to enhanced gluconeogenesis and reduced glucose utilization via pentose phosphate cycle (PPC) and oxidative metabolism. Following PH, G49 treatment increased survival, restored cytokine-mediated priming phase and enhanced proliferative capacity and hepatic regeneration ratio in mice on MCD diet. NASH markers remained decreased in M+G49 mice after PH and glucose utilization was shifted to PPC and oxidative metabolism. G49 administered immediately after PH was also effective in alleviating the pathological changes induced by the MCD diet. Benefits on liver regeneration were also found in mice fed HFD and treated with G49. CONCLUSION: Dual acting GLP-1R/GCGR agonists such as G49 represent a novel therapeutic approach for patients with NASH and particularly in those requiring PH. This article is protected by copyright. All rights reserved. PMID: 27880981 [PubMed - as supplied by publisher]

Potential Antidepressant and Resilience Mechanism Revealed by Metabolomic Study on Peripheral Blood Mononuclear Cells of Stress Resilient Rats. Behav Brain Res. 2016 Nov 20;: Authors: Li J, Zhang SX, Wang W, Cheng K, Guo H, Rao CL, Yang DY, He Y, Zou DZ, Han Y, Zhao LB, Li PF, Xie P Abstract Resilience is an active coping response to stress, which plays a very important role in major depressive disorder study. The molecular mechanisms underlying such resilience are poorly understood. Peripheral blood mononuclear cells (PBMCs) were promising objects in unveiling the underlying pathogenesis of resilience. Hereby we carried out successive study on PBMCs metabolomics in resilient rats of chronic unpredictable mild stress (CUMS) model. A gas chromatography-mass spectrometry (GC-MS) metabolomic approach coupled with principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) was used to detect differential metabolites in PBMCs of resilient rats. Ingenuity Pathways Analysis (IPA) was applied for pathway analysis. A set of differential metabolites including Malic acid, Ornithine, L-Lysine, Stigmasterol, Oleic acid, γ-Tocopherol, Adenosine and N-Acetyl-D-glucosamine were significantly altered in resilient rats, meanwhile promoting antidepressant research. As revealed by IPA that aberrant energy metabolism, HIFα signaling, neurotransmitter, O-GlcNAcylation and cAMP signaling cascade in peripheral might be evolved in the pathogenesis of coping mechanism. The GC-MS based metabolomics may contribute to better understanding of resilience, as well as shedding light on antidepressant discovery. PMID: 27880890 [PubMed - as supplied by publisher]

Multi-omics analysis of serum samples demonstrates reprogramming of organ functions via systemic calcium mobilization and platelet activation in metastatic melanoma. Mol Cell Proteomics. 2016 Nov 22;: Authors: Muqaku B, Eisninger M, Meier SM, Tahir A, Prokop T, Haferkamp S, Slany A, Reichle A, Gerner C Abstract Pathophysiologies of cancer-associated syndroms such as cachexia are poorly understood and no routine biomarkers have been established, yet. Using shotgun proteomics, known marker molecules including PMEL, CRP, SAA and CSPG4 were found deregulated in patients with metastatic melanoma. Targeted analysis of 58 selected proteins with multiple reaction monitoring was applied for independent data verification. In three patients, two of which suffered from cachexia, a tissue damage signature was determined, consisting of nine proteins, PLTP, CD14, TIMP1, S10A8, S10A9, GP1BA, PTPRJ, CD44 and C4A, as well as increased levels of glycine and asparagine, and decreased levels of polyunsaturated phosphatidylcholine concentrations, as determined by targeted metabolomics. Remarkably, these molecules are known to be involved in key processes of cancer cachexia. Based on these results, we propose a model how metastatic melanoma may lead to reprogramming of organ functions via formation of platelet activating factors from long-chain polyunsaturated phosphatidylcholines under oxidative conditions and via systemic induction of intracellular calcium mobilization. Calcium mobilization in platelets was demonstrated to alterate levels of several of these marker molecules. Additionally, platelets from melanoma patients proved to be in a rather exhausted state, and platelet-derived eicosanoids implicated in tumor growth were found massively increased in blood from three melanoma patients. Platelets were thus identified as important source of serum protein and lipid alterations in late stage melanoma patients. As a result, the proposed model describes the crosstalk between lipolysis of fat tissue and muscle wasting mediated by oxidative stress, resulting in the metabolic deregulations characteristic for cachexia. PMID: 27879288 [PubMed - as supplied by publisher]