PubMed

Characterization of the serum metabolome following radiation treatment in patients with high-grade gliomas. Radiat Oncol. 2016;11(1):51 Authors: Mörén L, Wibom C, Bergström P, Johansson M, Antti H, Bergenheim AT Abstract BACKGROUND: Glioblastomas progress rapidly making response evaluation using MRI insufficient since treatment effects are not detectable until months after initiation of treatment. Thus, there is a strong need for supplementary biomarkers that could provide reliable and early assessment of treatment efficacy. Analysis of alterations in the metabolome may be a source for identification of new biomarker patterns harboring predictive information. Ideally, the biomarkers should be found within an easily accessible compartment such as the blood. METHOD: Using gas-chromatographic- time-of-flight-mass spectroscopy we have analyzed serum samples from 11 patients with glioblastoma during the initial phase of radiotherapy. Fasting serum samples were collected at admittance, on the same day as, but before first treatment and in the morning after the second and fifth dose of radiation. The acquired data was analyzed and evaluated by chemometrics based bioinformatics methods. Our findings were compared and discussed in relation to previous data from microdialysis in tumor tissue, i.e. the extracellular compartment, from the same patients. RESULTS: We found a significant change in metabolite pattern in serum comparing samples taken before radiotherapy to samples taken during early radiotherapy. In all, 68 metabolites were lowered in concentration following treatment while 16 metabolites were elevated in concentration. All detected and identified amino acids and fatty acids together with myo-inositol, creatinine, and urea were among the metabolites that decreased in concentration during treatment, while citric acid was among the metabolites that increased in concentration. Furthermore, when comparing results from the serum analysis with findings in tumor extracellular fluid we found a common change in metabolite patterns in both compartments on an individual patient level. On an individual metabolite level similar changes in ornithine, tyrosine and urea were detected. However, in serum, glutamine and glutamate were lowered after treatment while being elevated in the tumor extracellular fluid. CONCLUSION: Cross-validated multivariate statistical models verified that the serum metabolome was significantly changed in relation to radiation in a similar pattern to earlier findings in tumor tissue. However, all individual changes in tissue did not translate into changes in serum. Our study indicates that serum metabolomics could be of value to investigate as a potential marker for assessing early response to radiotherapy in malignant glioma. PMID: 27039175 [PubMed - as supplied by publisher]

Metabolomic network analysis of estrogen-stimulated MCF-7 cells: a comparison of overrepresentation analysis, quantitative enrichment analysis and pathway analysis versus metabolite network analysis. Arch Toxicol. 2016 Apr 2; Authors: Maertens A, Bouhifd M, Zhao L, Odwin-DaCosta S, Kleensang A, Yager JD, Hartung T Abstract In the context of the Human Toxome project, mass spectroscopy-based metabolomics characterization of estrogen-stimulated MCF-7 cells was studied in order to support the untargeted deduction of pathways of toxicity. A targeted and untargeted approach using overrepresentation analysis (ORA), quantitative enrichment analysis (QEA) and pathway analysis (PA) and a metabolite network approach were compared. Any untargeted approach necessarily has some noise in the data owing to artifacts, outliers and misidentified metabolites. Depending on the chemical analytical choices (sample extraction, chromatography, instrument and settings, etc.), only a partial representation of all metabolites will be achieved, biased by both the analytical methods and the database used to identify the metabolites. Here, we show on the one hand that using a data analysis approach based exclusively on pathway annotations has the potential to miss much that is of interest and, in the case of misidentified metabolites, can produce perturbed pathways that are statistically significant yet uninformative for the biological sample at hand. On the other hand, a targeted approach, by narrowing its focus and minimizing (but not eliminating) misidentifications, renders the likelihood of a spurious pathway much smaller, but the limited number of metabolites also makes statistical significance harder to achieve. To avoid an analysis dependent on pathways, we built a de novo network using all metabolites that were different at 24 h with and without estrogen with a p value <0.01 (53) in the STITCH database, which links metabolites based on known reactions in the main metabolic network pathways but also based on experimental evidence and text mining. The resulting network contained a "connected component" of 43 metabolites and helped identify non-endogenous metabolites as well as pathways not visible by annotation-based approaches. Moreover, the most highly connected metabolites (energy metabolites such as pyruvate and alpha-ketoglutarate, as well as amino acids) showed only a modest change between proliferation with and without estrogen. Here, we demonstrate that estrogen has subtle but potentially phenotypically important alterations in the acyl-carnitine fatty acids, acetyl-putrescine and succinoadenosine, in addition to likely subtle changes in key energy metabolites that, however, could not be verified consistently given the technical limitations of this approach. Finally, we show that a network-based approach combined with text mining identifies pathways that would otherwise neither be considered statistically significant on their own nor be identified via ORA, QEA, or PA. PMID: 27039105 [PubMed - as supplied by publisher]

Effect of acupuncture and its influence on cerebral activity in functional dyspepsia patients: study protocol for a randomized controlled trial. Trials. 2016;17(1):183 Authors: Ko SJ, Park K, Kim J, Kim M, Kim JH, Lee J, Mohamed AZ, Yeo I, Kim J, Choi SM, Kim H, Park JW, Lee JH Abstract BACKGROUND: Functional dyspepsia (FD) is a prevalent gastric disorder that is difficult to manage due to lack of satisfactory treatments. Acupuncture has been studied with regard to the rising need for treating FD, but the mechanism verifying its efficacy has not yet been fully revealed. The aim of this study is to explore the efficacy and mechanism of acupuncture for FD compared with a sham group. METHODS/DESIGN: We describe a proposal for a randomized, assessor-blind, sham-controlled trial with 70 eligible participants who will be randomly allocated either into an acupuncture or a sham group. Participants in the acupuncture group will receive 10 sessions of real acupuncture treatment and those in the sham group will be treated with identical sessions using a Streitberger needle. Functional magnetic resonance imaging (fMRI) and metabolomics studies will be implemented before and after 4 weeks of treatment to investigate the mechanism of acupuncture. The primary outcome is a proportion of responders with adequate symptom relief and the secondary outcomes include the Nepean Dyspepsia Index - Korean version, Functional Dyspepsia-Related Quality of Life questionnaire, Ways of Coping Questionnaire, Coping Strategies Questionnaire, perception of bodily sensation questionnaire, State-Trait Anxiety Inventory, and the Center for Epidemiological Studies - Depression Scale. The outcomes will be evaluated before and after the treatment. DISCUSSION: This is the first large-scale trial evaluating the efficacy and mechanism of acupuncture with fMRI and metabolomic methods. We will compare real acupuncture with the Streitberger sham needle to verify the specific effect of acupuncture. The results of this trial are expected to be relevant evidences affecting policy and decision-makers associated with routine healthcare. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02358486 . Date of Registration: 21 January 2015. PMID: 27039086 [PubMed - as supplied by publisher]

Metabolomics by Gas Chromatography-Mass Spectrometry: Combined Targeted and Untargeted Profiling. Curr Protoc Mol Biol. 2016;114:30.4.1-30.4.32 Authors: Fiehn O Abstract Gas chromatography-mass spectrometry (GC-MS)-based metabolomics is ideal for identifying and quantitating small-molecule metabolites (<650 Da), including small acids, alcohols, hydroxyl acids, amino acids, sugars, fatty acids, sterols, catecholamines, drugs, and toxins, often using chemical derivatization to make these compounds sufficiently volatile for gas chromatography. This unit shows how GC-MS-based metabolomics allows integration of targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds. Complemented by database annotations using large spectral libraries and validated standard operating procedures, GC-MS can identify and semiquantify over 200 compounds from human body fluids (e.g., plasma, urine, or stool) per study. Deconvolution software enables detection of more than 300 additional unidentified signals that can be annotated through accurate mass instruments with appropriate data processing workflows, similar to untargeted profiling using liquid chromatography-mass spectrometry. GC-MS is a mature technology that uses not only classic detectors (quadrupole) but also target mass spectrometers (triple quadrupole) and accurate mass instruments (quadrupole-time of flight). This unit covers sample preparation from mammalian samples, data acquisition, quality control, and data processing. © 2016 by John Wiley & Sons, Inc. PMID: 27038389 [PubMed - as supplied by publisher]

Looking into aqueous humor through metabolomics spectacles - exploring its metabolic characteristics in relation to myopia. J Pharm Biomed Anal. 2016 Mar 18; Authors: Barbas-Bernardos C, Armitage EG, García A, Mérida S, Navea A, Bosch-Morell F, Barbas C Abstract Aqueous humor is the transparent fluid found in the anterior chamber of the eye that provides the metabolic requirements to the avascular tissues surrounding it. Despite the fact that metabolomics could be a powerful tool in the characterization of this biofluid and in revealing metabolic signatures of common ocular diseases such as myopia, it has never to our knowledge previously been applied in humans. In this research a novel method for the analysis of aqueous humor is presented to show its application in the characterization of this biofluid using CE-MS. The method was extended to a dual platform method (CE-MS and LC-MS) in order to compare samples from patients with different severities of myopia in order to explore the disease from the metabolic phenotype point of view. With this method, a profound knowledge of the metabolites present in human aqueous humor has been obtained: over 40 metabolites were reproducibly and simultaneously identified from a low volume of sample by CE-MS, including among others, a vast number of amino acids and derivatives. When this method was extended to study groups of patients with high or low myopia in both CE-MS and LC-MS, it has been possible to identify over 20 significantly different metabolite and lipid signatures that distinguish patients based on the severity of myopia. Among these, the most notable higher abundant metabolites in high myopia were aminooctanoic acid, arginine, citrulline and sphinganine while features of low myopia were aminoundecanoic acid, dihydro-retinoic acid and cysteinylglycine disulfide. This dual platform approach offered complementarity such that different metabolites were detected in each technique. Together the experiments presented provide a whelm of valuable information about human aqueous humor and myopia, proving the utility of non-targeted metabolomics for the first time in analyzing this type of sample and the metabolic phenotype of this disease. PMID: 27036676 [PubMed - as supplied by publisher]

Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis. Genome Med. 2016;8(1):34 Authors: Huang S, Chong N, Lewis NE, Jia W, Xie G, Garmire LX Abstract BACKGROUND: More accurate diagnostic methods are pressingly needed to diagnose breast cancer, the most common malignant cancer in women worldwide. Blood-based metabolomics is a promising diagnostic method for breast cancer. However, many metabolic biomarkers are difficult to replicate among studies. METHODS: We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. RESULTS: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. CONCLUSIONS: We have successfully developed a new type of pathway-based model to study metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease diagnosis. PMID: 27036109 [PubMed - as supplied by publisher]

Individual variability in human blood metabolites identifies age-related differences. Proc Natl Acad Sci U S A. 2016 Mar 28; Authors: Chaleckis R, Murakami I, Takada J, Kondoh H, Yanagida M Abstract Metabolites present in human blood document individual physiological states influenced by genetic, epigenetic, and lifestyle factors. Using high-resolution liquid chromatography-mass spectrometry (LC-MS), we performed nontargeted, quantitative metabolomics analysis in blood of 15 young (29 ± 4 y of age) and 15 elderly (81 ± 7 y of age) individuals. Coefficients of variation (CV = SD/mean) were obtained for 126 blood metabolites of all 30 donors. Fifty-five RBC-enriched metabolites, for which metabolomics studies have been scarce, are highlighted here. We found 14 blood compounds that show remarkable age-related increases or decreases; they include 1,5-anhydroglucitol, dimethyl-guanosine, acetyl-carnosine, carnosine, ophthalmic acid, UDP-acetyl-glucosamine,N-acetyl-arginine,N6-acetyl-lysine, pantothenate, citrulline, leucine, isoleucine, NAD(+), and NADP(+) Six of them are RBC-enriched, suggesting that RBC metabolomics is highly valuable for human aging research. Age differences are partly explained by a decrease in antioxidant production or increasing inefficiency of urea metabolism among the elderly. Pearson's coefficients demonstrated that some age-related compounds are correlated, suggesting that aging affects them concomitantly. Although our CV values are mostly consistent with those CVs previously published, we here report previously unidentified CVs of 51 blood compounds. Compounds having moderate to high CV values (0.4-2.5) are often modified. Compounds having low CV values, such as ATP and glutathione, may be related to various diseases because their concentrations are strictly controlled, and changes in them would compromise health. Thus, human blood is a rich source of information about individual metabolic differences. PMID: 27036001 [PubMed - as supplied by publisher]

A novel treatment of cystic fibrosis acting on-target: cysteamine plus epigallocatechin gallate for the autophagy-dependent rescue of class II-mutated CFTR. Cell Death Differ. 2016 Apr 1; Authors: Tosco A, De Gregorio F, Esposito S, De Stefano D, Sana I, Ferrari E, Sepe A, Salvadori L, Buonpensiero P, Di Pasqua A, Grassia R, Leone CA, Guido S, De Rosa G, Lusa S, Bona G, Stoll G, Maiuri MC, Mehta A, Kroemer G, Maiuri L, Raia V Abstract We previously reported that the combination of two safe proteostasis regulators, cysteamine and epigallocatechin gallate (EGCG), can be used to improve deficient expression of the cystic fibrosis transmembrane conductance regulator (CFTR) in patients homozygous for the CFTR Phe508del mutation. Here we provide the proof-of-concept that this combination treatment restored CFTR function and reduced lung inflammation (P<0.001) in Phe508del/Phe508del or Phe508del/null-Cftr (but not in Cftr-null mice), provided that such mice were autophagy-competent. Primary nasal cells from patients bearing different class II CFTR mutations, either in homozygous or compound heterozygous form, responded to the treatment in vitro. We assessed individual responses to cysteamine plus EGCG in a single-centre, open-label phase-2 trial. The combination treatment decreased sweat chloride from baseline, increased both CFTR protein and function in nasal cells, restored autophagy in such cells, decreased CXCL8 and TNF-α in the sputum, and tended to improve respiratory function. These positive effects were particularly strong in patients carrying Phe508del CFTR mutations in homozygosity or heterozygosity. However, a fraction of patients bearing other CFTR mutations failed to respond to therapy. Importantly, the same patients whose primary nasal brushed cells did not respond to cysteamine plus EGCG in vitro also exhibited deficient therapeutic responses in vivo. Altogether, these results suggest that the combination treatment of cysteamine plus EGCG acts 'on-target' because it can only rescue CFTR function when autophagy is functional (in mice) and improves CFTR function when a rescuable protein is expressed (in mice and men). These results should spur the further clinical development of the combination treatment.Cell Death and Differentiation advance online publication, 1 April 2016; doi:10.1038/cdd.2016.22. PMID: 27035618 [PubMed - as supplied by publisher]

Altered Mitochondrial Respiration and Other Features of Mitochondrial Function in Parkin-Mutant Fibroblasts from Parkinson's Disease Patients. Parkinsons Dis. 2016;2016:1819209 Authors: Haylett W, Swart C, van der Westhuizen F, van Dyk H, van der Merwe L, van der Merwe C, Loos B, Carr J, Kinnear C, Bardien S Abstract Mutations in the parkin gene are the most common cause of early-onset Parkinson's disease (PD). Parkin, an E3 ubiquitin ligase, is involved in respiratory chain function, mitophagy, and mitochondrial dynamics. Human cellular models with parkin null mutations are particularly valuable for investigating the mitochondrial functions of parkin. However, published results reporting on patient-derived parkin-mutant fibroblasts have been inconsistent. This study aimed to functionally compare parkin-mutant fibroblasts from PD patients with wild-type control fibroblasts using a variety of assays to gain a better understanding of the role of mitochondrial dysfunction in PD. To this end, dermal fibroblasts were obtained from three PD patients with homozygous whole exon deletions in parkin and three unaffected controls. Assays of mitochondrial respiration, mitochondrial network integrity, mitochondrial membrane potential, and cell growth were performed as informative markers of mitochondrial function. Surprisingly, it was found that mitochondrial respiratory rates were markedly higher in the parkin-mutant fibroblasts compared to control fibroblasts (p = 0.0093), while exhibiting more fragmented mitochondrial networks (p = 0.0304). Moreover, cell growth of the parkin-mutant fibroblasts was significantly higher than that of controls (p = 0.0001). These unanticipated findings are suggestive of a compensatory mechanism to preserve mitochondrial function and quality control in the absence of parkin in fibroblasts, which warrants further investigation. PMID: 27034887 [PubMed]

Improving the Sensitivity, Resolution, and Peak Capacity of Gradient Elution in Capillary Liquid Chromatography With Large-Volume Injections by Using Temperature-Assisted On-column Solute Focusing. Anal Chem. 2016 Apr 1; Authors: Wilson RE, Groskreutz SR, Weber SG Abstract Capillary HPLC (cLC) with gradient elution is the separation method of choice for the fields of proteomics and metabolomics. This is due to the complementary nature of cLC flow rates and electrospray or nanospray ionization mass spectrometry (ESI-MS). The small column diameters result in good mass sensitivity. Good concentration sensitivity is also possible by injection of relatively large volumes of solution and relying on solvent-based solute focusing. However, if the injection volume is too large or solutes are poorly retained during injection, volume overload occurs which leads to altered peak shapes, decreased sensitivity and lower peak capacity. Solutes that elute early even with the use of a solvent gradient are especially vulnerable to this problem. In this paper we describe a simple, automated instrumental method, Temperature-Assisted On-column Solute Focusing (TASF), that is capable of focusing large volume injections of small molecules and peptides under gradient conditions. By injecting a large sample volume while cooling a short segment of the column inlet at sub-ambient temperatures, solutes are concentrated into narrow bands at the head of the column. Rapidly raising the temperature of this segment of the column leads to separations with less peak broadening in comparison to solvent focusing alone. For large volume injections of both mixtures of small molecules and a bovine serum albumin tryptic digest, TASF improved the peak shape and resolution in chromatograms. TASF showed the most dramatic improvements with shallow gradients, which is particularly useful for biological applications. Results demonstrate the ability of TASF with gradient elution to improve the sensitivity, resolution, and peak capacity of volume overloaded samples beyond gradient compression alone. Additionally, we have developed and validated a double extrapolation method for predicting retention factors at extremes of temperature and mobile phase composition. Using this method, the effects of TASF can be predicted, allowing determination of the usefulness of this technique for a particular application. PMID: 27033165 [PubMed - as supplied by publisher]

Amino acid profiling as a method of discovering biomarkers for early diagnosis of cancer. Amino Acids. 2016 Mar 31; Authors: Simińska E, Koba M Abstract Cancer is one of the main causes of mortality in the world and its early detection significantly increases chances of patients' survival. High cancer mortality rate is caused mainly by late-stage diagnosis and lack of non-invasive and reliable methods for early diagnosis, such as plasma biomarkers. The incidence of cancers in the world still grows so it is crucial to develop a new, faster, high specificity and more sensitive diagnostic technologies. Several recent researchers indicate amino acids as a potential marker for cancer detection. An ideal cancer biomarker should be characterized by high specificity and sensitivity, reliability, ease of measurement and, what is important, ability to detect disease in its early stage. This study is focused on indicating metabolic amino acid profiling as a method of identifying biomarkers for cancer early detection and screening. Presented results are derived from the most recent studies where patients in early, often asymptomatic stages of disease constituted a large percentage of all the patients and, what is important, where researchers have observed alterations in these patients' amino acid profiles. This review is concentrated on analyzing studies on the most common cancers with high mortality rate. Inventing effective methods of early diagnosis is particularly important in case of such diseases. Research presented in this publication is focused on patients with lung, breast and colon cancer. In all analyzed cases, significant changes in the amino acid profile in cancer patients comparing to healthy controls were observed. This study indicates potential of amino acid profiling as method for early cancer detection. PMID: 27033065 [PubMed - as supplied by publisher]

Bioanalysis of endogenous bile acids by LC-MS utilizing stable isotope labeled analogues: The utility of stable isotope labeled (SIL) analogues in the bioanalysis of endogenous compounds by LC-MS applied to the study of bile acids in a metabolomics assay. Anal Biochem. 2016 Mar 28; Authors: Zheng JJ, Shields EE, Snow KJ, Nelson DM, Olah TV, Reily MD, Robertson DG, Shipkova PA, Stryker SA, Xin B, Drexler DM Abstract The growing field of biomarker bioanalysis by LC-MS is challenged with the selection of suitable matrices to construct relevant and valid calibration curves resulting in not only precise but also accurate data. While surrogate matrices are often employed with the associated concerns about the accuracy of the obtained data, presented here is an assay utilizing surrogate analytes in naïve biological matrices. This approach is illustrated with the analysis of endogenous bile acids (e-BAs) in serum and plasma using stable isotope labeled (SIL)-analogues as calibration standards to address the matrix concerns. Several deuterated BAs (d-BAs) were used as standards representing respectively grouped e-BAs with structural similarity allowing for the simultaneous bioanalysis of 16 e-BA. The utility of this LC-MS assay employing d-BAs is demonstrated with the analysis of samples resultant of a controlled metabolomics study where a cohort of rats were fed/fasted to investigate the change of e-BAs dependent on food consumption and fasting time. PMID: 27033006 [PubMed - as supplied by publisher]

Effects of Perfluorooctanoic Acid on Metabolic Profiles in Brain and Liver of Mouse Revealed by a High-throughput Targeted Metabolomics Approach. Sci Rep. 2016;6:23963 Authors: Yu N, Wei S, Li M, Yang J, Li K, Jin L, Xie Y, Giesy JP, Zhang X, Yu H Abstract Perfluorooctanoic acid (PFOA), a perfluoroalkyl acid, can result in hepatotoxicity and neurobehavioral effects in animals. The metabolome, which serves as a connection among transcriptome, proteome and toxic effects, provides pathway-based insights into effects of PFOA. Since understanding of changes in the metabolic profile during hepatotoxicity and neurotoxicity were still incomplete, a high-throughput targeted metabolomics approach (278 metabolites) was used to investigate effects of exposure to PFOA for 28 d on brain and liver of male Balb/c mice. Results of multivariate statistical analysis indicated that PFOA caused alterations in metabolic pathways in exposed individuals. Pathway analysis suggested that PFOA affected metabolism of amino acids, lipids, carbohydrates and energetics. Ten and 18 metabolites were identified as potential unique biomarkers of exposure to PFOA in brain and liver, respectively. In brain, PFOA affected concentrations of neurotransmitters, including serotonin, dopamine, norepinephrine, and glutamate in brain, which provides novel insights into mechanisms of PFOA-induced neurobehavioral effects. In liver, profiles of lipids revealed involvement of β-oxidation and biosynthesis of saturated and unsaturated fatty acids in PFOA-induced hepatotoxicity, while alterations in metabolism of arachidonic acid suggesting potential of PFOA to cause inflammation response in liver. These results provide insight into the mechanism and biomarkers for PFOA-induced effects. PMID: 27032815 [PubMed - as supplied by publisher]

Dissecting lipid metabolism in meibomian glands of humans and mice: An integrative study reveals a network of metabolic reactions not duplicated in other tissues. Biochim Biophys Acta. 2016 Mar 28; Authors: Butovich IA, McMahon A, Wojtowicz JC, Lin F, Mancini R, Itani K Abstract Lipids comprise the bulk of the meibomian gland secretion (meibum) which is produced by meibocytes. Complex arrays of lipogenic reactions in meibomian glands, which we collectively call meibogenesis, have not been explored on molecular level yet. Our goals were to elucidate the possible biosynthetic pathways that underlie the generation of meibum, reveal similarities in, and differences between, lipid metabolism in meibomian glands and other organs and tissues, and integrate meibomian gland studies into the field of general metabolomics. Specifically, we have conducted detailed analyses of human and mouse specimens using genomic, immunohistochemical, and lipidomic approaches. Among equally highly expressed genes found in meibomian glands of both species were those related to fatty acid elongation, branching, desaturation, esterification, reduction of fatty acids to alcohols, and cholesterol biosynthesis. Importantly, corresponding lipid products were detected in meibum of both species using lipidomic approaches. For the first time, a cohesive, unifying biosynthetic scheme that connects genomic, lipidomic, and immunohistochemical observations is outlined and discussed. PMID: 27032494 [PubMed - as supplied by publisher]

Related Articles -omic sciences: new horizons in food allergy. Curr Opin Allergy Clin Immunol. 2015 Jun;15(3):234-6 Authors: Fiocchi A, Wang J PMID: 25899698 [PubMed - indexed for MEDLINE]

Related Articles UHPLC-PDA-ESI-TOF/MS metabolic profiling of Arctostaphylos pungens and Arctostaphylos uva-ursi. A comparative study of phenolic compounds from leaf methanolic extracts. Phytochemistry. 2015 Jul;115:79-88 Authors: Panusa A, Petrucci R, Marrosu G, Multari G, Gallo FR Abstract The aim of this study was to get a rapid metabolic fingerprinting and to gain insight into the metabolic profiling of Arctostaphylos pungens H. B. K., a plant morphologically similar to Arctostaphylos uva-ursi (L.) Spreng. (bearberry) but with a lower arbutin (Arb) content. According to the European Pharmacopoeia the Arb content in the dried leaf of A. uva-ursi (L.) Spreng. must be at least 7% (wt/wt) but other species, like A. pungens, are unintentionally or fraudulently marketed instead of it. Therefore, methanolic leaf extracts of nine A. uva-ursi and six A. pungens samples labeled and marketed as "bearberry leaf" have been analyzed. A five-minute gradient with a UHPLC-PDA-ESI-TOF/MS on an Acquity BEH C18 (50×2.1 mm i.d.) 1.7 μm analytical column has been used for the purpose. A comprehensive assignment of secondary metabolites has been carried out in a comparative study of the two species. Among twenty-nine standards of natural compounds analyzed, fourteen have been identified, while other fifty-five metabolites have been tentatively assigned. Moreover, differences in both metabolic fingerprinting and profiling have been evidenced by statistical multivariate analysis. Specifically, main variations have been observed in the relative content for Arb, as expected, and for some galloyl derivative like tetra- and pentagalloylglucose more abundant in A. uva-ursi than in A. pungens. Furthermore, differences in flavonols profile, especially in myricetin and quercetin glycosilated derivatives, were observed. Based on principal component analysis myricetrin, together with a galloyl arbutin isomer and a disaccharide are herein proposed as distinctive metabolites for A. pungens. PMID: 25702282 [PubMed - indexed for MEDLINE]

Related Articles GC-MS-based plasma metabolomic investigations of morphine dependent rats at different states of euphoria, tolerance and naloxone-precipitated withdrawal. Metab Brain Dis. 2015 Jun;30(3):767-76 Authors: Liu R, Cheng J, Yang J, Ding X, Yang S, Dong F, Guo N, Liu S Abstract Long-term or excessive application of morphine leads to tolerance and addiction, which hindered its conventional applications as a drug. Although tremendous progress has been made on the mechanisms of morphine, crucial evidence elaborating the neurobiological basis of tolerance and dependence is still lacking. To further explore the physiological adaptions during morphine's application, a systematic screening of small molecules in blood has been carried out. The plasma of morphine dependent rats was collected at different time points with or without naloxone treatment, and was analyzed by gas chromatography-mass spectrometry (GC-MS). Partial least squares discriminate analysis (PLS-DA) and the Student's t Tests with the false discovery rate (FDR) correction were conducted on the normalized data for the distinction of groups and the identification of the most contributed metabolites. Clear separation is observed between different treatments, and 29 out of 41 metabolites changes significantly compared with the corresponding controls. The concentration of threonine, glycine, serine, beta-d-glucose and oxalic acid are consistently changed in all morphine treated groups compared with controls. Through this experiment we find characteristic metabolites in different dependent states and discuss the possible compensation effects. The interpretation of these metabolites would throw light on the biological effects of morphine and reveal the possibilities to become marker of morphine addiction. PMID: 25472920 [PubMed - indexed for MEDLINE]

Discovery of potential biomarkers with dose and time dependence in cisplatin-induced nephrotoxicity using metabolomics integrated with principal component-based area calculation (PCAC) strategy. Chem Res Toxicol. 2016 Mar 31; Authors: Zhang P, Chen J, Wang Y, Huang Y, Tian Y, Zhang Z, Xu F Abstract Cisplatin is a potent chemotherapeutic agent. However, its clinical usage is restricted by serious adverse effects, especially nephrotoxicity. In order to reveal the dose- and time-dependence in cisplatin-induced nephrotoxicity, mass spectrometry (MS)-based metabolomics integrated with principal component-based area calculation (PCAC) strategy was proposed in the present study. Area plots based on the first two principal components (PCs) of principal component analysis (PCA) model were first constructed. Then, the sums of cumulative areas under PC-T curves (AUCPC-T) were calculated. Finally, fold change of AUCPC-T (FCAUC) between experimental group and control group at different time point was calculated and used as indicative parameter. With PCAC approach, dose- and time-dependence of cisplatin-induced metabolic change was quantitatively confirmed for the first time. Furthermore, twenty-seven potential biomarkers with dose- and time-dependence related to nephrotoxicity induced by cisplatin were screened out and tentatively identified. Metabolic pathways interrupted by cisplatin mainly included energy metabolism, amino acid metabolism and lipid metabolism. PMID: 27030963 [PubMed - as supplied by publisher]

Immunological off-target effects of imatinib. Nat Rev Clin Oncol. 2016 Mar 31; Authors: Zitvogel L, Rusakiewicz S, Routy B, Ayyoub M, Kroemer G Abstract Around 15 years ago, imatinib mesylate (Gleevec(®) or Glivec(®), Novartis, Switzerland) became the very first 'targeted' anticancer drug to be clinically approved. This drug constitutes the quintessential example of a successful precision medicine that has truly changed the fate of patients with Philadelphia-chromosome-positive chronic myeloid leukaemia (CML) and gastrointestinal stromal tumours by targeting the oncogenic drivers of these diseases, BCR-ABL1 and KIT and/or PDGFR, mutations in which lead to gain of function of tyrosine kinase activities. Nonetheless, the aforementioned paradigm might not fully explain the clinical success of this agent in these diseases. Growing evidence indicates that the immune system has a major role both in determining the therapeutic efficacy of imatinib (and other targeted agents) and in restraining the emergence of escape mutations. In this Review, we re-evaluate the therapeutic utility of imatinib in the context of the anticancer immunosurveillance system, and we discuss how this concept might inform on novel combination regimens that include imatinib with immunotherapies. PMID: 27030078 [PubMed - as supplied by publisher]

Plasma Biomarkers of Poor Muscle Quality in Older Men and Women from the Baltimore Longitudinal Study of Aging. J Gerontol A Biol Sci Med Sci. 2016 Mar 30; Authors: Moaddel R, Fabbri E, Khadeer MA, Carlson OD, Gonzalez-Freire M, Zhang P, Semba RD, Ferrucci L Abstract Aging is characterized by progressive decline in muscle mass, strength, and quality all of which contribute to functional impairment, falls, mobility disability, and frailty. Circulating factors may provide clues on the mechanisms for decline in muscle quality with aging. Characterizing the metabolic profile associated with reduced muscle quality in older persons could have important translational implications for the early identification of subjects at high risk of developing sarcopenia and the identification of targets for new preventive strategies and treatments. In a pilot cross-sectional, case-control study nested in the Baltimore Longitudinal Study on Aging, we compared circulating metabolites between 79 participants with low muscle quality ratio and 79 controls with high muscle quality, matched by age, sex, and height. The concentrations of 180 metabolites were determined by LC MS/MS, using the Biocrates p180 system, a targeted metabolomics approach. Participants with low muscle quality had significantly higher levels of leucine, isoleucine, tryptophan, serotonin, and methionine, while those with high muscle quality had significantly lower levels of putrescine and the selected phophatidylcholine (PCs) and lysoPCs. The results of this study open a new road for future investigations aimed at identifying new metabolic pathways involved in the decline of muscle quality with aging. PMID: 27029859 [PubMed - as supplied by publisher]