PubMed

Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine. Methods Mol Biol. 2016;1386:253-281 Authors: Aurich MK, Thiele I Abstract Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine. PMID: 26677187 [PubMed - as supplied by publisher]

Comprehensive analysis of serum metabolites in gestational diabetes mellitus by UPLC/Q-TOF-MS. Anal Bioanal Chem. 2015 Dec 16; Authors: Liu T, Li J, Xu F, Wang M, Ding S, Xu H, Dong F Abstract Gestational diabetes mellitus (GDM) refers to the first sign or onset of diabetes mellitus during pregnancy rather than progestation. In recent decades, more and more research has focused on the etiology and pathogenesis of GDM in order to further understand GDM progress and recovery. Using an advanced metabolomics platform based on ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS), we explored the changes in serum metabolites between women with GDM and healthy controls during and after pregnancy. Some significant differences were discovered using multivariate analysis including partial least-squares discriminant analysis (PLS-DA) and orthogonal PLS-DA (OPLS-DA). The dysregulated metabolites were further compared and verified in several databases to understand how these compounds might function as potential biomarkers. Analyses of the metabolic pathways associated with these potential biomarkers were subsequently explored. A total of 35 metabolites were identified, contributing to GDM progress to some extent. The identified biomarkers were involved in some important metabolic pathways including glycine, serine, and threonine metabolism; steroid hormone biosynthesis; tyrosine metabolism; glycerophospholipid metabolism; and fatty acid metabolism. The above mentioned metabolic pathways mainly participate in three major metabolic cycles in humans, including lipid metabolism, carbohydrate metabolism, and amino acid metabolism. In this pilot study, the valuable comprehensive analysis gave us further insight into the etiology and pathophysiology of GDM, which might benefit the feasibility of a rapid, accurate diagnosis and reasonable treatment as soon as possible but also prevent GDM and its related short- and long-term complications. PMID: 26677023 [PubMed - as supplied by publisher]

Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.). J Sci Food Agric. 2015 Dec 17; Authors: Zhen S, Dong K, Deng X, Zhou J, Xu X, Han C, Zhang W, Xu Y, Wang Z, Yan Y Abstract BACKGROUND: Metabolites in wheat grains greatly influence nutritional values. Wheat provides proteins, minerals, B-group vitamins and dietary fiber to human. These metabolites are important to the health of human. However, the metabolome of the grain during the development of bread wheat has not been studied. RESULTS: In the present work, we analyzed the first dynamic metabolome of the developing grain of the elite Chinese bread wheat cultivar Zhongmai 175. We used a non-targeted gas chromatography-mass spectrometry (GC-MS) for metabolite profiling. In total, 74 metabolites were identified over the grain developmental stages. Metabolite-metabolite correlation analysis revealed that the metabolism of amino acids, carbohydrates, organic acids, amines and lipids, was interrelated. An integrated metabolic map revealed a distinct regulatory profile. Our results provide information that can be used by metabolic engineers and molecular breeders to improve wheat grain quality. CONCLUSIONS: Our metabolome approach identified dynamic changes in metabolite levels, and correlations among such levels, in developing seeds. The comprehensive metabolic map may be useful when breeding programs seek to improve grain quality. Our work highlights the utility of GC/MS-based metabolomics, in conjunction with univariate and multivariate data analysis, when it is sought to understand metabolic changes in developing seeds. PMID: 26676564 [PubMed - as supplied by publisher]

Understanding Metabolomics in Biomedical Research. Endocrinol Metab (Seoul). 2015 Dec 9; Authors: Kim SJ, Kim SH, Kim JH, Hwang S, Yoo HJ Abstract The term "omics" refers to any type of specific study that provides collective information on a biological system. Representative omics includes genomics, proteomics, and metabolomics, and new omics is constantly being added, such as lipidomics or glycomics. Each omics technique is crucial to the understanding of various biological systems and complements the information provided by the other approaches. The main strengths of metabolomics are that metabolites are closely related to the phenotypes of living organisms and provide information on biochemical activities by reflecting the substrates and products of cellular metabolism. The transcriptome does not always correlate with the proteome, and the translated proteome might not be functionally active. Therefore, their changes do not always result in phenotypic alterations. Unlike the genome or proteome, the metabolome is often called the molecular phenotype of living organisms and is easily translated into biological conditions and disease states. Here, we review the general strategies of mass spectrometry-based metabolomics. Targeted metabolome or lipidome analysis is discussed, as well as nontargeted approaches, with a brief explanation of the advantages and disadvantages of each platform. Biomedical applications that use mass spectrometry-based metabolomics are briefly introduced. PMID: 26676338 [PubMed - as supplied by publisher]

Serum metabolomics analysis of rat after intragastric infusion of Pu-erh theabrownin. J Sci Food Agric. 2015 Dec 17; Authors: Liu J, Peng CX, Gao B, Gong JS Abstract BACKGROUND: To study the effects of Pu-erh theabrownin (TB) (Mw > 50kDa) on the metabolism of rats serum by nuclear magnetic resonance (NMR)-based metabolomics and identify candidate marker metabolites associated with Pu-erh TB and, thus, provide fundamental information for better understanding the metabolism of Pu-erh tea in animals. RESULTS: The TB infusion induced different changes in endogenous serum metabolites depending on the type of diet. Compared with the control group, the TB infusion group showed significantly reduced serum glycine and choline levels, as well as significantly increased taurine, carnitine, and HDL (all p<0.05). Compared with the high lipid group, the high lipid-TB infusion group exhibited significantly reduced LDL and acetate levels, as well as significantly increased inositol, carnitine, and glycine levels (all p<0.05). CONCLUSION: Examination of the variations of these differential expressed metabolites and their individual functions revealed that, the TB extract accelerated the lipid catabolism in rats and might affect the glucose metabolism. Of these, the carnitine level significantly increased after intragastric infusion of TB regardless of the type of diet, and carnitine palmitoyltransferases Ι and ΙΙ activities have significantly changed, suggesting carnitine may be a candidate serum marker for tracking the metabolism of TB in rats. PMID: 26676261 [PubMed - as supplied by publisher]

Studying the effect of storage conditions on the metabolite content of red wine using HILIC LC-MS based metabolomics. Food Chem. 2016 Apr 15;197(Pt B):1331-1340 Authors: Arapitsas P, Corte AD, Gika H, Narduzzi L, Mattivi F, Theodoridis G Abstract The main aim of this work was to develop an untargeted normal phase LC-MS method, starting from a targeted method already validated for the analysis of 135 polar metabolites. Since the LC instrument and column were the same, most of the chromatographic conditions remained identical, while the adaptations focused on maintaining the ionic strength of the eluents constant. The sample preparation was simplified and the effectiveness of LC-MS for long batches was evaluated, in order to record the maximum number of metabolites with good chromatographic resolution and the best MS stability and accuracy. The method was applied to study the influence of storage conditions on wine composition. Slightly sub-optimum storage conditions had a major impact on the polar metabolite fingerprint of the red wines analysed and the markers revealed included phenolics, vitamins and metabolites indentified in wine for the first time (4-amino-heptanedioic acid and its ethyl ester). PMID: 26675875 [PubMed - as supplied by publisher]

Cholinergic Neurotransmission in the Posterior Insular Cortex Is Altered in Preclinical Models of Neuropathic Pain: Key Role of Muscarinic M2 Receptors in Donepezil-Induced Antinociception. J Neurosci. 2015 Dec 16;35(50):16418-16430 Authors: Ferrier J, Bayet-Robert M, Dalmann R, El Guerrab A, Aissouni Y, Graveron-Demilly D, Chalus M, Pinguet J, Eschalier A, Richard D, Daulhac L, Marchand F, Balayssac D Abstract Neuropathic pain is one of the most debilitating pain conditions, yet no therapeutic strategy has been really effective for its treatment. Hence, a better understanding of its pathophysiological mechanisms is necessary to identify new pharmacological targets. Here, we report important metabolic variations in brain areas involved in pain processing in a rat model of oxaliplatin-induced neuropathy using HRMAS (1)H-NMR spectroscopy. An increased concentration of choline has been evidenced in the posterior insular cortex (pIC) of neuropathic animal, which was significantly correlated with animals' pain thresholds. The screening of 34 genes mRNA involved in the pIC cholinergic system showed an increased expression of the high-affinity choline transporter and especially the muscarinic M2 receptors, which was confirmed by Western blot analysis in oxaliplatin-treated rats and the spared nerve injury model (SNI). Furthermore, pharmacological activation of M2 receptors in the pIC using oxotremorine completely reversed oxaliplatin-induced mechanical allodynia. Consistently, systemic treatment with donepezil, a centrally active acetylcholinesterase inhibitor, prevented and reversed oxaliplatin-induced cold and mechanical allodynia as well as social interaction impairment. Intracerebral microdialysis revealed a lower level of acetylcholine in the pIC of oxaliplatin-treated rats, which was significantly increased by donepezil. Finally, the analgesic effect of donepezil was markedly reduced by a microinjection of the M2 antagonist, methoctramine, within the pIC, in both oxaliplatin-treated rats and spared nerve injury rats. These findings highlight the crucial role of cortical cholinergic neurotransmission as a critical mechanism of neuropathic pain, and suggest that targeting insular M2 receptors using central cholinomimetics could be used for neuropathic pain treatment. SIGNIFICANCE STATEMENT: Our study describes a decrease in cholinergic neurotransmission in the posterior insular cortex in neuropathic pain condition and the involvement of M2 receptors. Targeting these cortical muscarinic M2 receptors using central cholinomimetics could be an effective therapy for neuropathic pain treatment. PMID: 26674867 [PubMed - as supplied by publisher]

Human Breast Milk and Infant Formulas Differentially Modify the Intestinal Microbiota in Human Infants and Host Physiology in Rats. J Nutr. 2015 Dec 16; Authors: Liu Z, Roy NC, Guo Y, Jia H, Ryan L, Samuelsson L, Thomas A, Plowman J, Clerens S, Day L, Young W Abstract BACKGROUND: In the absence of human breast milk, infant and follow-on formulas can still promote efficient growth and development. However, infant formulas can differ in their nutritional value. OBJECTIVE: The objective of this study was to compare the effects of human milk (HM) and infant formulas in human infants and a weanling rat model. METHODS: In a 3 wk clinical randomized controlled trial, babies (7- to 90-d-old, male-to-female ratio 1:1) were exclusively breastfed (BF), exclusively fed Synlait Pure Canterbury Stage 1 infant formula (SPCF), or fed assorted standard formulas (SFs) purchased by their parents. We also compared feeding HM or SPCF in weanling male Sprague-Dawley rats for 28 d. We examined the effects of HM and infant formulas on fecal short chain fatty acids (SCFAs) and bacterial composition in human infants, and intestinal SCFAs, the microbiota, and host physiology in weanling rats. RESULTS: Fecal Bifidobacterium concentrations (mean log copy number ± SEM) were higher (P = 0.003) in BF (8.17 ± 0.3) and SPCF-fed infants (8.29 ± 0.3) compared with those fed the SFs (6.94 ± 0.3). Fecal acetic acid (mean ± SEM) was also higher (P = 0.007) in the BF (5.5 ± 0.2 mg/g) and SPCF (5.3 ± 2.4 mg/g) groups compared with SF-fed babies (4.3 ± 0.2 mg/g). Colonic SCFAs did not differ between HM- and SPCF-fed rats. However, cecal acetic acid concentrations were higher (P = 0.001) in rats fed HM (42.6 ± 2.6 mg/g) than in those fed SPCF (30.6 ± 0.8 mg/g). Cecal transcriptome, proteome, and plasma metabolite analyses indicated that the growth and maturation of intestinal tissue was more highly promoted by HM than SPCF. CONCLUSIONS: Fecal bacterial composition and SCFA concentrations were similar in babies fed SPCF or HM. However, results from the rat study showed substantial differences in host physiology between rats fed HM and SPCF. This trial was registered at Shanghai Jiào tong University School of Medicine as XHEC-C-2012-024. PMID: 26674765 [PubMed - as supplied by publisher]

Hepatotoxicity and nephrotoxicity induced by the chlorpyrifos and chlorpyrifos-methyl metabolite, 3,5,6-trichloro-2-pyridinol, in orally exposed mice. Sci Total Environ. 2015 Dec 8;544:507-514 Authors: Deng Y, Zhang Y, Lu Y, Zhao Y, Ren H Abstract 3,5,6-Trichloro-2-pyridinol (TCP) is a primary degradation product of chlorpyrifos and chlorpyrifos-methyl. TCP has longer half-life in soil and greater solubility in water than its parent compound, and cause wide contamination in environments. However, studies about the toxic effects of TCP are limited and outdate. In this study, 5mg/kg/day, 50mg/kg/day, and 150mg/kg/day TCP were given to male mice through gavage for four weeks. As a result, the final body weights of TCP treated groups were significantly lower than control, and the relative organ weights of the liver and kidney were significantly higher than that of control. In addition, NMR-based metabolomics was used to investigate the toxic effects of TCP. It was found that a total of 39 serum metabolites were significantly changed in the TCP-treated groups, and these metabolites are related to hepatotoxicity and nephrotoxicity. These results were also confirmed by histopathology, serum biochemical, and oxidative stress analysis. In addition, metabolic disturbances due to TCP exposure were also observed based on altered metabolites. As far as we know, these results are the first to show the metabolomic toxicity of TCP, which warrants further research. PMID: 26674679 [PubMed - as supplied by publisher]

Metabolomics of dates (Phoenix dactylifera) reveals a highly dynamic ripening process accounting for major variation in fruit composition. BMC Plant Biol. 2015;15(1):291 Authors: Diboun I, Mathew S, Al-Rayyashi M, Elrayess M, Torres M, Halama A, Méret M, Mohney RP, Karoly ED, Malek J, Suhre K Abstract BACKGROUND: Dates are tropical fruits with appreciable nutritional value. Previous attempts at global metabolic characterization of the date metabolome were constrained by small sample size and limited geographical sampling. In this study, two independent large cohorts of mature dates exhibiting substantial diversity in origin, varieties and fruit processing conditions were measured by metabolomics techniques in order to identify major determinants of the fruit metabolome. RESULTS: Multivariate analysis revealed a first principal component (PC1) significantly associated with the dates' countries of production. The availability of a smaller dataset featuring immature dates from different development stages served to build a model of the ripening process in dates, which helped reveal a strong ripening signature in PC1. Analysis revealed enrichment in the dry type of dates amongst fruits with early ripening profiles at one end of PC1 as oppose to an overrepresentation of the soft type of dates with late ripening profiles at the other end of PC1. Dry dates are typical to the North African region whilst soft dates are more popular in the Gulf region, which partly explains the observed association between PC1 and geography. Analysis of the loading values, expressing metabolite correlation levels with PC1, revealed enrichment patterns of a comprehensive range of metabolite classes along PC1. Three distinct metabolic phases corresponding to known stages of date ripening were observed: An early phase enriched in regulatory hormones, amines and polyamines, energy production, tannins, sucrose and anti-oxidant activity, a second phase with on-going phenylpropanoid secondary metabolism, gene expression and phospholipid metabolism and a late phase with marked sugar dehydration activity and degradation reactions leading to increased volatile synthesis. CONCLUSIONS: These data indicate the importance of date ripening as a main driver of variation in the date metabolome responsible for their diverse nutritional and economical values. The biochemistry of the ripening process in dates is consistent with other fruits but natural dryness may prevent degenerative senescence in dates following ripening. Based on the finding that mature dates present varying extents of ripening, our survey of the date metabolome essentially revealed snapshots of interchanging metabolic states during ripening empowering an in-depth characterization of underlying biology. PMID: 26674306 [PubMed - as supplied by publisher]

UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz). J Integr Bioinform. 2015;12(4):280 Authors: Moresco R, Uarrota VG, Pereira A, Tomazzoli MM, Nunes ED, Peruch LA, Gazzola J, Costa C, Rocha M, Maraschin M Abstract In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in β-carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis-β-carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition. PMID: 26673931 [PubMed - as supplied by publisher]

A roadmap for the XCMS family of software solutions in metabolomics. Curr Opin Chem Biol. 2015 Dec 10;30:87-93 Authors: Mahieu NG, Genenbacher JL, Patti GJ Abstract Global profiling of metabolites in biological samples by liquid chromatography/mass spectrometry results in datasets too large to evaluate manually. Fortunately, a variety of software programs are now available to automate the data analysis. Selection of the appropriate processing solution is dependent upon experimental design. Most metabolomic studies a decade ago had a relatively simple experimental design in which the intensities of compounds were compared between only two sample groups. More recently, however, increasingly sophisticated applications have been pursued. Examples include comparing compound intensities between multiple sample groups and unbiasedly tracking the fate of specific isotopic labels. The latter types of applications have necessitated the development of new software programs, which have introduced additional functionalities that facilitate data analysis. The objective of this review is to provide an overview of the freely available bioinformatic solutions that are either based upon or are compatible with the algorithms in XCMS, which we broadly refer to here as the 'XCMS family' of software. These include CAMERA, credentialing, Warpgroup, metaXCMS, X(13)CMS, and XCMS Online. Together, these informatic technologies can accommodate most cutting-edge metabolomic applications and offer unique advantages when compared to the original XCMS program. PMID: 26673825 [PubMed - as supplied by publisher]

[Application of ultra high performance liquid chromatography-mass spectrometry to metabolomics study of drug-induced hepatotoxicity]. Se Pu. 2015 Jul;33(7):683-90 Authors: Liu X, Liu Y, Cheng M, Xiao H Abstract Drug-induced hepatotoxicity is a worldwide health issue. And diagnosing the injury in the early stage is still a challenge in clinic. In this study, pattern recognition analysis of the ultra high performance liquid chromatography-mass spectrometry (UPLC-MS) of hepatocytes HL7702 was performed to develop differential metabolites related to hepatotoxicity induced by hepatotoxicants, including carbon tetrachloride (CCl4), acetaminophen (APAP), emodin, aristolochic acid (AA) and triptolide. Hepatocytes injuries were induced by 48 h of treatment with CCl4 (4 mmol/L), APAP (6.5 mmol/L), emodin (14 μmol/L), AA (35 μmol/L) and triptolide (18 nmol/L), separately. Global metabolomics profiling, multivariate analysis and database searching were performed to discover common differential metabolites for live injury. The positive hepatoprotective drug, bifendate, was used to repair triptolide induced hepatocytes injury, and bifendate-induced changes of hepatotoxicity-related metabolites were investigated. In the results, fatty acid oxidation and cellular oxidative stress-related metabolites, including nicotinamide adenine dinucleotide and glutathione were significantly changed between the control and hepatotoxicant-treated groups, and after treatment with bifendate, those perturbed metabolites all partly returned to normal level. In conclusion, we discovered potential hepatotoxicity-related metabolites that could be used to evaluate hepatotoxicity induced by chemicals, drugs and traditional Chinese medicines. This study also proved that metabolomics is one of the effective tools to investigate drug-induced hepatotoxicity. PMID: 26672195 [PubMed - in process]

16 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2015/12/17PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

62 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2015/12/15PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

NMR-Based Metabolomics Reveal a Recovery from Metabolic Changes in the Striatum of 6-OHDA-Induced Rats Treated with Basic Fibroblast Growth Factor. Mol Neurobiol. 2015 Dec 9; Authors: Zheng H, Zhao L, Xia H, Xu C, Wang D, Liu K, Lin L, Li X, Yan Z, Gao H Abstract Basic fibroblast growth factor (bFGF) has a potential role in the treatment of Parkinson's disease (PD) due to its neurotrophic effect on dopaminergic neurons. To address the metabolic mechanisms of bFGF administration on PD, we have analyzed the metabolic profiles in the striatum of 6-hydroxydopamine (6-OHDA)-induced PD rats after the treatment with bFGF using (1)H NMR spectroscopy and partial least squares-discriminant analysis (PLS-DA). In the present study, we found that bFGF treatment can effectively recover PD-induced loss of tyrosine hydroxylase (TH)-positive neurons in the substantia nigra. Metabolomic analyses reveal that PLS-DA failed to discriminate between the control and bFGF groups, indicating that the metabolic difference between these two groups was negligible. However, reliable PLS-DA models can be developed between control and PD groups as well as between PD and bFGF groups, which is attributed to changes in a series of metabolites including GABA, glutamate (Glu), glutamine (Gln), lactate, N-acetylaspartate, creatine, taurine, and myo-inositol. ANOVA results show that the levels of all these metabolites were significantly increased in PD rats relative to normal rats, while PD-induced increase can be significantly reduced to normal levels after bFGF administration. In conclusion, our results suggest that a recovery from PD-induced metabolic disorders may be achieved by bFGF treatment, involving Gln/Glu-GABA cycle, energy metabolism, osmoregulation, and inflammation. PMID: 26650045 [PubMed - as supplied by publisher]

"OMIC" tumor markers for breast cancer: A review. Pak J Med Sci. 2015 Sep-Oct;31(5):1256-1262 Authors: Hadi NI, Jamal Q Abstract Breast cancer is a global health issue, and as the tumor burden increases, we need to come up with newer, better technologies which are convenient, cheap, rapid, sensitive with a high specificity. Technological advancements in the field of cancer biomarker has led to the development of techniques such as mass spectrometric analysis and microarray analysis in which genes, proteins and hundreds and thousands of metabolites can be identified with the emergence of genomics, proteomics and metabolomics. This research is focused on finding biomarkers for diagnosis, prognosis, staging, treatment response and targets for chemotherapy, generating a panel of markers which provide better clinical information compared to a single marker in the panel. This review briefly summarizes application of genomics and proteomics followed by key concepts and applications of metabolomics in breast cancer, with the conclusion that an integration of the three "OMIC" technologies may hold the key to future biomarker discovery. SOURCES OF DATA STUDY SELECTION: The information for this review was collected by searching the Google Scholar and PubMed database for English articles published in the period from 2002 to 2015. The search terms included "biomarkers in breast cancer" along with the following search terms: "genomics", "proteomics", "metabolomics", "breast cancer", "mass spectrometry", "molecular markers" and "cancer biomarker". We have endeavored to quote only the primary sources. Titles and abstracts of retrieved studies were assessed first followed by selection and retrieval of selected full text articles. PMID: 26649025 [PubMed - as supplied by publisher]

Long-term neural and physiological phenotyping of a single human. Nat Commun. 2015;6:8885 Authors: Poldrack RA, Laumann TO, Koyejo O, Gregory B, Hover A, Chen MY, Gorgolewski KJ, Luci J, Joo SJ, Boyd RL, Hunicke-Smith S, Simpson ZB, Caven T, Sochat V, Shine JM, Gordon E, Snyder AZ, Adeyemo B, Petersen SE, Glahn DC, Reese Mckay D, Curran JE, Göring HH, Carless MA, Blangero J, Dougherty R, Leemans A, Handwerker DA, Frick L, Marcotte EM, Mumford JA Abstract Psychiatric disorders are characterized by major fluctuations in psychological function over the course of weeks and months, but the dynamic characteristics of brain function over this timescale in healthy individuals are unknown. Here, as a proof of concept to address this question, we present the MyConnectome project. An intensive phenome-wide assessment of a single human was performed over a period of 18 months, including functional and structural brain connectivity using magnetic resonance imaging, psychological function and physical health, gene expression and metabolomics. A reproducible analysis workflow is provided, along with open access to the data and an online browser for results. We demonstrate dynamic changes in brain connectivity over the timescales of days to months, and relations between brain connectivity, gene expression and metabolites. This resource can serve as a testbed to study the joint dynamics of human brain and metabolic function over time, an approach that is critical for the development of precision medicine strategies for brain disorders. PMID: 26648521 [PubMed - in process]

A combined proteomics and metabolomics approach to assess the effects of gold nanoparticles in vitro. Nanotoxicology. 2015 Dec 9;:1-59 Authors: Gioria S, Lobo Vicente J, Barboro P, La Spina R, Tomasi G, Urbán P, Kinsner-Ovaskainen A, Rossi F, Chassaigne H Abstract Omics technologies, such as proteomics or metabolomics, have to date been applied in the field of nanomaterial safety assessment to a limited extent. To address this dearth, we developed an integrated approach combining the two techniques to study the effects of two sizes, 5 and 30 nm, of gold nanoparticles (AuNPs) in Caco-2 cells. We observed differences in cells exposed for 72 h to each size of AuNPs: 61 responsive (up/down-regulated) proteins were identified and 35 metabolites in the cell extract tentatively annotated. Several altered biological pathways were highlighted by integrating the obtained multi-omics data with bioinformatic tools. This provided a unique set of molecular information on the effects of nanomaterials at cellular level. This information was supported by complementary data obtained by immunochemistry, microscopic analysis and multiplexed assays. A part from increasing our knowledge on how the cellular processes and pathways are affected by nanomaterials (NMs), these findings could be used to identify specific biomarkers of toxicity or to support the safe-by-design concept in the development of new nanomedicines. PMID: 26647645 [PubMed - as supplied by publisher]

METABOLOMICS IN MEDICAL SCIENCES--TRENDS, CHALLENGES AND PERSPECTIVES. Acta Pol Pharm. 2015 Jul-Aug;72(4):629-41 Authors: Klupczyńska A, Dereziński P, Kokot ZJ Abstract Metabolomics is the latest of the "omic" technologies that involves comprehensive analysis of small molecule metabolites of an organism or a specific biological sample. Metabolomics provides an insight into the cell status and describes an actual health condition of organisms. Analysis of metabolome offers a unique opportunity to study the influence of genetic variation, disease, applied treatment or diet on endogenous metabolic state of organisms. There are many areas that might benefit from metabolomic research. In the article some applications of this novel "omic" technology in the field of medical sciences are presented. One of the most popular aims of metabolomic studies is biomarker discovery. Despite using the state-of-art analytical techniques along with advanced bioinformatic tools, metabolomic experiments encounter numerous difficulties and pitfalls. Challenges that researchers in the field of analysis of metabolome have to face include i.a., technical limitations, bioinformatic challenges and integration with other "omic" sciences. One of the grand challenges for studies in the field of metabolomics is to tackle the problem of data analysis, which is probably the most time consuming stage of metabolomic workflow and requires close collaboration between analysts, clinicians and experts in chemometric analysis. Implementation of metabolomics into clinical practice will be dependent on establishment of standardized protocols in analytical performance and data analysis and development of fit-for-purpose biomarker method validation. Metabolomics allows to achieve a sophisticated level of information about biological systems and opens up new perspectives in many fields of medicine, especially in oncology. Apart from its extensive cognitive significance, metabolomics manifests also a practical importance as it may lead to design of new non-invasive, sensitive and specific diagnostic techniques and development of new therapies. PMID: 26647618 [PubMed - in process]