PubMed

Quantitative Analysis of Cancer Metabolism: From pSIRM to MFA. Recent Results Cancer Res. 2016;207:207-20 Authors: Zasada C, Kempa S Abstract Metabolic reprogramming is a required step during oncogenesis and essential for cellular proliferation. It is triggered by activation of oncogenes and loss of tumor suppressor genes. Beside the combinatorial events leading to cancer, common changes within the central metabolism are reported. Increase of glycolysis and subsequent lactic acid formation has been a focus of cancer metabolism research for almost a century. With the improvements of bioanalytical techniques within the last decades, a more detailed analysis of metabolism is possible and recent studies demonstrate a wide range of metabolic rearrangements in various cancer types. However, a systematic and mechanistic understanding is missing thus far. Therefore, analytical and computational tools have to be developed allowing for a dynamic and quantitative analysis of cancer metabolism. In this chapter, we outline the application of pulsed stable isotope resolved metabolomics (pSIRM) and describe the interface toward computational analysis of metabolism. PMID: 27557540 [PubMed - in process]

Tissue-Based Metabolomics to Analyze the Breast Cancer Metabolome. Recent Results Cancer Res. 2016;207:157-75 Authors: Budczies J, Denkert C Abstract Mass spectrometry and nuclear magnetic resonance-based metabolomics have been developed into mature technologies that can be utilized to analyze hundreds of biological samples in a high-throughput manner. Over the past few years, both technologies were utilized to analyze large cohorts of fresh frozen breast cancer tissues. Metabolite biomarkers were shown to separate breast cancer tissues from normal breast tissues with high sensitivity and specificity. Furthermore, the metabolome differed between hormone receptor positive (HR+) and hormone receptor negative (HR-) breast cancer, but was unchanged in HER2+ tumors compared to HER2- tumors. New metabolism-related biomarkers were discovered including the 4-aminobutyrate aminotransferase ABAT, where low mRNA expression led to an accumulation of beta-alanine and shortened relapse-free survival. The glutamate-to-glutamine ratio (GGR) represents another new biomarker that was increased in 88 % of HR- tumors and 56 % of HR+ tumors compared to normal breast tissues. The GGR might help to stratify patients for the treatment with specific glutaminase inhibitors that were recently developed and are currently being tested in phase I clinical studies. Surprisingly, 2-hydroxyglutarate (2-HG), initially found to accumulate in isocitrate dehydrogenase (IDH) mutated gliomas and leukemias and described as an oncometabolite, was detected to be drastically increased in several breast carcinomas in the absence of IDH mutations. In summary, metabolomics analysis of breast cancer tissues is a reliable method and has produced many new biological insights that may impact breast cancer diagnostics and treatment over the coming years. PMID: 27557538 [PubMed - in process]

Related Articles A Randomized Placebo Controlled Trial of Ibuprofen for Respiratory Syncytial Virus Infection in a Bovine Model. PLoS One. 2016;11(4):e0152913 Authors: Walsh P, Behrens N, Carvallo Chaigneau FR, McEligot H, Agrawal K, Newman JW, Anderson M, Gershwin LJ Abstract BACKGROUND: Respiratory syncytial virus (RSV) is the most common cause of bronchiolitis and hospital admission in infants. An analogous disease occurs in cattle and costs US agriculture a billion dollars a year. RSV causes much of its morbidity indirectly via adverse effects of the host response to the virus. RSV is accompanied by elevated prostaglandin E2 (PGE2) which is followed by neutrophil led inflammation in the lung. Ibuprofen is a prototypical non-steroidal anti-inflammatory drug that decreases PGE2 levels by inhibiting cyclooxygenase. HYPOTHESES: We hypothesized that treatment of RSV with ibuprofen would decrease PGE2 levels, modulate the immune response, decrease clinical illness, and decrease the histopathological lung changes in a bovine model of RSV. We further hypothesized that viral replication would be unaffected. METHODS: We performed a randomized placebo controlled trial of ibuprofen in 16 outbred Holstein calves that we infected with RSV. We measured clinical scores, cyclooxygenase, lipoxygenase and endocannabinoid products in plasma and mediastinal lymph nodes and interleukin (Il)-4, Il-13, Il-17 and interferon-γ in mediastinal lymph nodes. RSV shedding was measured daily and nasal Il-6, Il-8 and Il-17 every other day. The calves were necropsied on Day 10 post inoculation and histology performed. RESULTS: One calf in the ibuprofen group required euthanasia on Day 8 of infection for respiratory distress. Clinical scores (p<0.01) and weight gain (p = 0.08) seemed better in the ibuprofen group. Ibuprofen decreased cyclooxygenase, lipoxygenase, and cytochrome P450 products, and increased monoacylglycerols in lung lymph nodes. Ibuprofen modulated the immune response as measured by narrowed range of observed Il-13, Il-17 and IFN-γ gene expression in mediastinal lymph nodes. Lung histology was not different between groups, and viral shedding was increased in calves randomized to ibuprofen. CONCLUSIONS: Ibuprofen decreased PGE2, modulated the immune response, and improved clinical outcomes. However lung histopathology was not affected and viral shedding was increased. PMID: 27073858 [PubMed - indexed for MEDLINE]

Related Articles Non-invasive metabolomic profiling of embryo culture media and morphology grading to predict implantation outcome in frozen-thawed embryo transfer cycles. J Assist Reprod Genet. 2015 Nov;32(11):1597-605 Authors: Li X, Xu Y, Fu J, Zhang WB, Liu SY, Sun XX Abstract PURPOSE: Assessment of embryo viability is a crucial component of in vitro fertilization and currently relies largely on embryo morphology and cleavage rate. Because morphological assessment remains highly subjective, it can be unreliable in predicting embryo viability. This study investigated the metabolomic profiling of embryo culture media using near-infrared (NIR) spectroscopy for predicting the implantation potential of human embryos in frozen-thawed embryo transfer (FET) cycles. METHODS: Spent embryo culture media was collected on day 4 after thawed embryo transfer (n = 621) and analysed using NIR spectroscopy. Viability scores were calculated using a predictive multivariate algorithm of fresh embryos with known pregnancy outcomes. RESULTS: The mean viability indices of embryos resulting in clinical pregnancy following FET were significantly higher than those of non-implanted embryos and differed between the 0, 50, and 100 % implantation groups. Notably, the 0 % group index was significantly lower than the 100 % implantation group index (-0.787 ± 0.382 vs. 1.064 ± 0.331, P < 0.01). To predict implantation outcomes, we examined the area under the ROC curve (AUCROC), which was significantly higher for the viability than for the morphology score (0.94 vs. 0.55; P < 0.01); however, the AUCROCs for the composite and viability scores did not differ significantly (0.92 vs. 0.94; P > 0.05). CONCLUSIONS: NIR metabolomic profiling of thawed embryo culture media is independent of morphology and correlates with embryo implantation potential in FET cycles. The viability score alone or in conjunction with morphologic grading is a more objective marker for implantation outcome in FET cycles than morphology alone. PMID: 26463877 [PubMed - indexed for MEDLINE]

Roostocks/Scion/Nitrogen Interactions Affect Secondary Metabolism in the Grape Berry. Front Plant Sci. 2016;7:1134 Authors: Habran A, Commisso M, Helwi P, Hilbert G, Negri S, Ollat N, Gomès E, van Leeuwen C, Guzzo F, Delrot S Abstract The present work investigates the interactions between soil content, rootstock, and scion by focusing on the effects of roostocks and nitrogen supply on grape berry content. Scions of Cabernet Sauvignon (CS) and Pinot Noir (PN) varieties were grafted either on Riparia Gloire de Montpellier (RGM) or 110 Richter (110R) rootstock. The 4 rooststock/scion combinations were fertilized with 3 different levels of nitrogen after fruit set. Both in 2013 and 2014, N supply increased N uptake by the plants, and N content both in vegetative and reproductory organs. Rootstock, variety and year affected berry weight at harvest, while nitrogen did not affect significantly this parameter. Grafting on RGM consistently increased berry weight compared to 110R. PN consistently produced bigger berries than CS. CS berries were heavier in 2014 than in 2013, but the year effect was less marked for PN berries. The berries were collected between veraison and maturity, separated in skin and pulp, and their content was analyzed by conventional analytical procedures and untargeted metabolomics. For anthocyanins, the relative quantitation was fairly comparable with both LC-MS determination and HPLC-DAD, which is a fully quantitative technique. The data show complex responses of the metabolite content (sugars, organic acids, amino acids, anthocyanins, flavonols, flavan-3-ols/procyanidins, stilbenes, hydroxycinnamic, and hydroxybenzoic acids) that depend on the rootstock, the scion, the vintage, the nitrogen level, the berry compartment. This opens a wide range of possibilities to adjust the content of these compounds through the choice of the roostock, variety and nitrogen fertilization. PMID: 27555847 [PubMed]

Soil Fungal:Bacterial Ratios Are Linked to Altered Carbon Cycling. Front Microbiol. 2016;7:1247 Authors: Malik AA, Chowdhury S, Schlager V, Oliver A, Puissant J, Vazquez PG, Jehmlich N, von Bergen M, Griffiths RI, Gleixner G Abstract Despite several lines of observational evidence, there is a lack of consensus on whether higher fungal:bacterial (F:B) ratios directly cause higher soil carbon (C) storage. We employed RNA sequencing, protein profiling and isotope tracer techniques to evaluate whether differing F:B ratios are associated with differences in C storage. A mesocosm (13)C labeled foliar litter decomposition experiment was performed in two soils that were similar in their physico-chemical properties but differed in microbial community structure, specifically their F:B ratio (determined by PLFA analyses, RNA sequencing and protein profiling; all three corroborating each other). Following litter addition, we observed a consistent increase in abundance of fungal phyla; and greater increases in the fungal dominated soil; implicating the role of fungi in litter decomposition. Litter derived (13)C in respired CO2 was consistently lower, and residual (13)C in bulk SOM was higher in high F:B soil demonstrating greater C storage potential in the F:B dominated soil. We conclude that in this soil system, the increased abundance of fungi in both soils and the altered C cycling patterns in the F:B dominated soils highlight the significant role of fungi in litter decomposition and indicate that F:B ratios are linked to higher C storage potential. PMID: 27555839 [PubMed]

Plasma metabolic profile delineates roles for neurodegeneration, pro-inflammatory damage and mitochondrial dysfunction in the FMR1 premutation. Biochem J. 2016 Aug 23; Authors: Giulivi C, Napoli E, Tassone F, Halmai J, Hagerman R Abstract Carriers of premutation CGG expansions in the fragile X mental retardation 1 ( FMR1 ) gene are at higher risk of developing a late-onset neurodegenerative disorder named Fragile X-tremor ataxia syndrome (FXTAS). Given that mitochondrial dysfunction has been identified in fibroblasts, PBMC and brain samples from carriers as well as in animal models of the premutation and that mitochondria are at the center of intermediary metabolism, the aim of this study was to provide a complete view of the metabolic pattern by uncovering plasma metabolic perturbations in premutation carriers. To this end, metabolic profiles were evaluated in plasma from 23 premutation individuals and 16 age- and sex- matched controls. Among the affected pathways, mitochondrial dysfunction was associated with a Warburg-like shift with increases in lactate levels and altered Krebs' intermediates, neurotransmitters, markers of neurodegeneration, and increases in oxidative stress-mediated damage to biomolecules. The number of CGG repeats correlated with a subset of plasma metabolites, which are implicated in mitochondrial disorders but also in other neurological diseases such as Parkinson's, Alzheimer's and Huntington's diseases. For the first time, the identified pathways shed light on disease mechanisms contributing to morbidity of the premutation, with the potential of assessing metabolites in longitudinal studies as indicators of morbidity or disease progression, especially at the early pre-clinical stages. PMID: 27555610 [PubMed - as supplied by publisher]

Targeting the endocannabinoid system: future therapeutic strategies. Drug Discov Today. 2016 Aug 20; Authors: Aizpurua-Olaizola O, Elezgarai I, Rico I, Zarandona I, Etxebarria N, Usobiaga A Abstract The endocannabinoid system (ECS) is involved in many physiological regulation pathways in the human body, which makes this system the target of many drugs and therapies. In this review, we highlight the latest studies regarding the role of the ECS and the drugs that target it, with a particular focus on the basis for the discovery of new cannabinoid-based drugs. In addition, we propose some key steps, such as the creation of a cannabinoid-receptor interaction matrix (CRIM) and the use of metabolomics, towards the development of improved and more specific drugs for each relevant disease. PMID: 27554802 [PubMed - as supplied by publisher]

Is there a role for stool metabolomics in cystic fibrosis? Pediatr Int. 2016 Aug;58(8):808-11 Authors: Kaakoush NO, Pickford R, Jaffe A, Ooi CY Abstract A number of studies utilizing metabolomics have focused on the pathophysiology of cystic fibrosis (CF) lung disease. Here, we performed fecal metabolomics on pancreatic insufficient (PI) and sufficient (PS) children with CF and compared them with healthy controls (HC). Fecal metabolomics can differentiate between PS-CF and PI-CF. We identified a potential biomarker of disease severity or cystic fibrosis transmembrane conductance regulator function (m/z, 463.247; retention time, 0.570717 min) that discriminates between HC versus PS-CF versus PI-CF. We also identified lipoyl-GMP as a potential novel inflammatory biomarker, and elevation in fecal glycerol 1,2-didodecanoate 3-tetradecanoate may provide clues to the pathogenesis of intestinal inflammation. For the first time, we demonstrate the potential applications of fecal metabolomics in CF. PMID: 27553892 [PubMed - in process]

A Japanese case of β-ureidopropionase deficiency with dysmorphic features. Brain Dev. 2016 Aug 20; Authors: Akiyama T, Shibata T, Yoshinaga H, Kuhara T, Nakajima Y, Kato T, Maeda Y, Ohse M, Oka M, Kageyama M, Kobayashi K Abstract β-Ureidopropionase deficiency is a rare autosomal recessive disease affecting the last step of pyrimidine degradation, and it is caused by a mutation in the UPB1 gene. Approximately 30 cases have been reported to date, with a phenotypical variability ranging from asymptomatic to severe neurological illness. Non-neurological symptoms have been rarely reported. We describe a case of this disease with developmental delay and dysmorphic features. Gas chromatography-mass spectrometry-based urine metabolomics demonstrated significant (⩾+4.5 standard deviation after logarithmic transformation) elevations of β-ureidopropionic acid and β-ureidoisobutyric acid, strongly suggesting a diagnosis of β-ureidopropionase deficiency. Subsequent quantitative analysis of pyrimidines by liquid chromatography-tandem mass spectrometry supported this finding. Genetic testing of the UPB1 gene confirmed compound heterozygosity of a novel mutation (c.976C>T) and a previously-reported mutation (c.977G>A) that is common in East Asians. β-Ureidopropionase deficiency is probably underdiagnosed, considering a wide phenotypical variability, non-specific neurological presentations, and an estimated prevalence of 1/5000-6000. Urine metabolomics should be considered for patients with unexplained neurological symptoms. PMID: 27553092 [PubMed - as supplied by publisher]

Related Articles Mitochondrial and nuclear DNA matching shapes metabolism and healthy ageing. Nature. 2016 Jul 28;535(7613):561-5 Authors: Latorre-Pellicer A, Moreno-Loshuertos R, Lechuga-Vieco AV, Sánchez-Cabo F, Torroja C, Acín-Pérez R, Calvo E, Aix E, González-Guerra A, Logan A, Bernad-Miana ML, Romanos E, Cruz R, Cogliati S, Sobrino B, Carracedo Á, Pérez-Martos A, Fernández-Silva P, Ruíz-Cabello J, Murphy MP, Flores I, Vázquez J, Enríquez JA Abstract Human mitochondrial DNA (mtDNA) shows extensive within population sequence variability. Many studies suggest that mtDNA variants may be associated with ageing or diseases, although mechanistic evidence at the molecular level is lacking. Mitochondrial replacement has the potential to prevent transmission of disease-causing oocyte mtDNA. However, extension of this technology requires a comprehensive understanding of the physiological relevance of mtDNA sequence variability and its match with the nuclear-encoded mitochondrial genes. Studies in conplastic animals allow comparison of individuals with the same nuclear genome but different mtDNA variants, and have provided both supporting and refuting evidence that mtDNA variation influences organismal physiology. However, most of these studies did not confirm the conplastic status, focused on younger animals, and did not investigate the full range of physiological and phenotypic variability likely to be influenced by mitochondria. Here we systematically characterized conplastic mice throughout their lifespan using transcriptomic, proteomic,metabolomic, biochemical, physiological and phenotyping studies. We show that mtDNA haplotype profoundly influences mitochondrial proteostasis and reactive oxygen species generation,insulin signalling, obesity, and ageing parameters including telomere shortening and mitochondrial dysfunction, resulting in profound differences in health longevity between conplastic strains. PMID: 27383793 [PubMed - indexed for MEDLINE]

Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods. Curr Opin Biotechnol. 2016 Aug 20;43:17-24 Authors: Bingol K, Brüschweiler R Abstract Metabolomics continues to make rapid progress through the development of new and better methods and their applications to gain insight into the metabolism of a wide range of different biological systems from a systems biology perspective. Customization of NMR databases and search tools allows the faster and more accurate identification of known metabolites, whereas the identification of unknowns, without a need for extensive purification, requires new strategies to integrate NMR with mass spectrometry, cheminformatics, and computational methods. For some applications, the use of covalent and non-covalent attachments in the form of labeled tags or nanoparticles can significantly reduce the complexity of these tasks. PMID: 27552705 [PubMed - as supplied by publisher]

GC-MS metabolomics analysis of mesenchymal stem cells treated with copper oxide nanoparticles. Toxicol Mech Methods. 2016 Aug 23;:1-9 Authors: Murgia A, Mancuso L, Manis C, Caboni P, Cao G Abstract Human exposure to copper oxide (CuO) nanoparticles (NPs) is rapidly increasing and for this reason reliable toxicity test systems are urgently needed. Recently, the acute cytotoxicity of CuO NPs using the new toxicity test based on human bone marrow mesenchymal stem cells (hBMMSCs) has been evaluated. It was shown that CuO NPs are much more toxic when compared to CuO microparticles (MPs). Several studies associate CuO toxicity to a possible alteration of reactive oxygen species (ROS) system. Unluckily, the mechanism that causes the toxicity is still not clear. In this work, the polar metabolite pool of treated cells, at the corresponding IC50 value, for CuO micro and NPs has been studied by gas chromatography coupled to mass spectrometry (GC-MS) and multivariate statistical data analysis. By the same means, differences due to different treatments, on samples, were investigated. Results of discriminant analysis were considered with the aim of finding the relevant metabolites unique for each class. Serine, glyceric acid, and succinic acid were upregulated on samples treated with CuO microparticles, while glutamine was the only discriminant metabolite for the class of samples treated with nanoparticles. PMID: 27552400 [PubMed - as supplied by publisher]

Metabolic profile and pharmacokinetics of Polyphyllin I, an anticancer candidate, in rats by UPLC-QTOF-MS/MS and LC-TQ-MS/MS. Biomed Chromatogr. 2016 Aug 23; Authors: Liu YC, Zhu H, Shakya S, Wu JW Abstract Polyphyllin I (PPI), a natural steroidal saponin originated from rihzome of Paris polyphylla, is recognized as one of potential anticancer candidates. Previous pharmacokinetics study showed that the oral bioavailability of PPI was very low, which suggested that certain amount of PPI might be metabolized in vivo. However, up to date, information regarding the final metabolic fates of PPI was very limited. In this study, metabolites of PPI and their pharmacokinetics in rats were investigated using UPLC-QTOF-MS/MS and LC-TQ-MS/MS. A total of seven putative metabolites, including six phase I and one phase II metabolites, were detected and identified with three exact structures through comparing with authentic standards for the first time. Oxidation, deglycosylation and glucuronidation were found to be the major metabolic processes of the compound in rats. Pharmacokinetics of Prosapogenin A (PSA), Trillin (TRL) and Diosgenin (DSN), three deglycosylation metabolites of PPI with definite anti-cancer effects, were further studied, which suggested that the metabolites underwent a prolonged absorption and slower elimination after intragastric administration of PPI at the dose of 500 mg/kg. This study provides valuable and new information on the metabolic fate of PPI, which will be helpful in further understanding its mechanism of action. PMID: 27552088 [PubMed - as supplied by publisher]

Nanoflow-nanospray mass spectrometry metabolomics reveals disruption of the urinary metabolite profiles of HIV-positive patients on combination antiretroviral therapy. J Acquir Immune Defic Syndr. 2016 Aug 16; Authors: Chetwynd AJ, Samarawickrama A, Vera JH, Bremner SA, Abdul-Sada A, Gilleece Y, Holt SG, Hill EM Abstract BACKGROUND: The use of combination antiretroviral therapy (cART) has substantially improved the outlook for patients with HIV infection. However, lifelong exposure to cART is also associated with adverse metabolic changes and an enhanced risk of renal, hepatic and cardiovascular dysfunction. This study investigated disruptions of the urinary metabolome of cART-exposed patients, thereby furthering our understanding of some of the side effects of pharmaceutical intervention. METHODS: HIV-positive patients were recruited from an HIV clinic and divided into cART-naïve and cART-exposed groups. HIV-negative patients were recruited from a sexual health clinic. All 89 subjects were white males. Targeted biochemistry analyses were performed on plasma samples. Urine samples were collected following an overnight fast and analysed with a highly sensitive untargeted metabolomic method using nanoflow/nanospray liquid chromatography-time of flight mass spectrometry. Datasets were analysed using projection modelling to detect metabolite markers of cART exposure. RESULTS: Metabolites or parent compounds of all cART drugs were detected in urine extracts of all but one of the cART-exposed patients confirming adherence to the pharmaceutical regimen. Analysis of urine samples from patients on cART revealed significant reductions in selected bile acids, lipid, nucleoside and androgen metabolites. However, plasma concentrations of free or conjugated testosterone were unchanged indicating possible disruption of androgen transport or excretion in urine of patients on cART. CONCLUSIONS: Discovery-based metabolomics reveals the potential to identify novel markers of cART intervention and metabolite disruption in HIV-positive patients, which may enable the efficacy, compliance and side effects of these pharmaceutical mixtures to be investigated. PMID: 27552076 [PubMed - as supplied by publisher]

Regulatory network analysis reveals novel regulators of seed desiccation tolerance in Arabidopsis thaliana. Proc Natl Acad Sci U S A. 2016 Aug 22; Authors: González-Morales SI, Chávez-Montes RA, Hayano-Kanashiro C, Alejo-Jacuinde G, Rico-Cambron TY, de Folter S, Herrera-Estrella L Abstract Desiccation tolerance (DT) is a remarkable process that allows seeds in the dry state to remain viable for long periods of time that in some instances exceed 1,000 y. It has been postulated that seed DT evolved by rewiring the regulatory and signaling networks that controlled vegetative DT, which itself emerged as a crucial adaptive trait of early land plants. Understanding the networks that regulate seed desiccation tolerance in model plant systems would provide the tools to understand an evolutionary process that played a crucial role in the diversification of flowering plants. In this work, we used an integrated approach that included genomics, bioinformatics, metabolomics, and molecular genetics to identify and validate molecular networks that control the acquisition of DT in Arabidopsis seeds. Two DT-specific transcriptional subnetworks were identified related to storage of reserve compounds and cellular protection mechanisms that act downstream of the embryo development master regulators LEAFY COTYLEDON 1 and 2, FUSCA 3, and ABSCICIC ACID INSENSITIVE 3. Among the transcription factors identified as major nodes in the DT regulatory subnetworks, PLATZ1, PLATZ2, and AGL67 were confirmed by knockout mutants and overexpression in a desiccation-intolerant mutant background to play an important role in seed DT. Additionally, we found that constitutive expression of PLATZ1 in WT plants confers partial DT in vegetative tissues. PMID: 27551092 [PubMed - as supplied by publisher]

Metabolomic biosignature differentiates melancholic depressive patients from healthy controls. BMC Genomics. 2016;17:669 Authors: Liu Y, Yieh L, Yang T, Drinkenburg W, Peeters P, Steckler T, Narayan VA, Wittenberg G, Ye J Abstract BACKGROUND: Major depressive disorder (MDD) is a heterogeneous disease at the level of clinical symptoms, and this heterogeneity is likely reflected at the level of biology. Two clinical subtypes within MDD that have garnered interest are "melancholic depression" and "anxious depression". Metabolomics enables us to characterize hundreds of small molecules that comprise the metabolome, and recent work suggests the blood metabolome may be able to inform treatment decisions for MDD, however work is at an early stage. Here we examine a metabolomics data set to (1) test whether clinically homogenous MDD subtypes are also more biologically homogeneous, and hence more predictiable, (2) devise a robust machine learning framework that preserves biological meaning, and (3) describe the metabolomic biosignature for melancholic depression. RESULTS: With the proposed computational system we achieves around 80 % classification accuracy, sensitivity and specificity for melancholic depression, but only ~72 % for anxious depression or MDD, suggesting the blood metabolome contains more information about melancholic depression.. We develop an ensemble feature selection framework (EFSF) in which features are first clustered, and learning then takes place on the cluster centroids, retaining information about correlated features during the feature selection process rather than discarding them as most machine learning methods will do. Analysis of the most discriminative feature clusters revealed differences in metabolic classes such as amino acids and lipids as well as pathways studied extensively in MDD such as the activation of cortisol in chronic stress. CONCLUSIONS: We find the greater clinical homogeneity does indeed lead to better prediction based on biological measurements in the case of melancholic depression. Melancholic depression is shown to be associated with changes in amino acids, catecholamines, lipids, stress hormones, and immune-related metabolites. The proposed computational framework can be adapted to analyze data from many other biomedical applications where the data has similar characteristics. PMID: 27549765 [PubMed - in process]

A survey of metabolic changes in potato leaves by NMR-based metabolic profiling in relation to resistance to late blight disease under field conditions. Magn Reson Chem. 2016 Aug 23; Authors: Tomita S, Ikeda S, Tsuda S, Someya N, Asano K, Kikuchi J, Chikayama E, Ono H, Sekiyama Y Abstract Non-targeted nuclear magnetic resonance (NMR)-based metabolic profiling was applied to potato leaves to survey metabolic changes associated with late blight resistance under field conditions. Potato plants were grown in an experimental field and the compound leaves with no visible symptoms were collected from 20 cultivars/lines at two sampling time points: (i) the time of initial presentation of symptoms in susceptible cultivars and (ii) 12 days before this initiation. (1) H NMR spectra of the foliar metabolites soluble in deuterium oxide- or methanol-d4 -based buffers were measured and used for multivariate analysis. Principal component analysis for six cultivars at symptom initiation showed a class separation corresponding to their levels of late blight resistance. This separation was primarily explained by higher levels of malic acid, methanol, and rutin and a lower level of sucrose in the resistant cultivars than in the susceptible ones. Partial least squares regression revealed that the levels of these metabolites were strongly associated with the disease severity measured in this study under field conditions. These associations were observed only for the leaves harvested at the symptom initiation stage, but not for those collected 12 days beforehand. Subsequently, a simple, alternative enzymatic assay for l-malic acid was used to estimate late blight resistance, as a model for applying the potential metabolic marker obtained. This study demonstrated the potential of metabolomics for field-grown plants in combination with targeted methods for quantifying marker levels, moving towards marker-assisted screening of new cultivars with durable late blight resistance. PMID: 27549366 [PubMed - as supplied by publisher]

Variant rs10911021 that associates with coronary heart disease in type 2 diabetes, is associated with lower concentrations of circulating HDL cholesterol and large HDL particles but not with amino acids. Cardiovasc Diabetol. 2016;15(1):115 Authors: Beaney KE, Cooper JA, McLachlan S, Wannamethee SG, Jefferis BJ, Whincup P, Ben-Shlomo Y, Price JF, Kumari M, Wong A, Ong K, Hardy R, Kuh D, Kivimaki M, Kangas AJ, Soininen P, Ala-Korpela M, Drenos F, Humphries SE, UCLEB consortium Abstract AIMS: An intergenic locus on chromosome 1 (lead SNP rs10911021) was previously associated with coronary heart disease (CHD) in type 2 diabetes (T2D). Using data from the UCLEB consortium we investigated the relationship between rs10911021 and CHD in T2D, whether rs10911021 was associated with levels of amino acids involved in the γ-glutamyl cycle or any conventional risk factors (CRFs) for CHD in the T2D participants. METHODS: Four UCLEB studies (n = 6531) had rs10911021 imputation, CHD in T2D, CRF and metabolomics data determined using a nuclear magnetic resonance based platform. RESULTS: The expected direction of effect between rs10911021 and CHD in T2D was observed (1377 no CHD/160 CHD; minor allele OR 0.80, 95 % CI 0.60-1.06) although this was not statistically significant (p = 0.13). No association between rs10911021 and CHD was seen in non-T2D participants (11218 no CHD/1274 CHD; minor allele OR 1.00 95 % CIs 0.92-1.10). In T2D participants, while no associations were observed between rs10911021 and the nine amino acids measured, rs10911021 was associated with HDL-cholesterol (p = 0.0005) but the minor "protective" allele was associated with lower levels (-0.034 mmol/l per allele). Focusing more closely on the HDL-cholesterol subclasses measured, we observed that rs10911021 was associated with six large HDL particle measures in T2D (all p < 0.001). No significant associations were seen in non-T2D subjects. CONCLUSIONS: Our findings are consistent with a true association between rs10911021 and CHD in T2D. The protective minor allele was associated with lower HDL-cholesterol and reductions in HDL particle traits. Our results indicate a complex relationship between rs10911021 and CHD in T2D. PMID: 27549350 [PubMed - in process]

Urine metabolomic profiling of children with respiratory tract infections in the emergency department: a pilot study. BMC Infect Dis. 2016;16(1):439 Authors: Adamko DJ, Saude E, Bear M, Regush S, Robinson JL Abstract BACKGROUND: Clinicians lack objective tests to help determine the severity of bronchiolitis or to distinguish a viral from bacterial causes of respiratory distress. We hypothesized that children with respiratory syncytial virus (RSV) infection would have a different metabolomic profile compared to those with bacterial infection or healthy controls, and this might also vary with bronchiolitis severity. METHODS: Clinical information and urine-based metabolomic data were collected from healthy age-matched children (n = 37) and those admitted to hospital with a proven infection (RSV n = 55; Non-RSV viral n = 16; bacterial n = 24). Nuclear magnetic resonance (NMR) measured 86 metabolites per urine sample. Partial least squares discriminant analysis (PLS-DA) was performed to create models of separation. RESULTS: Using a combination of metabolites, a strong PLS-DA model (R2 = 0.86, Q2 = 0.76) was created differentiating healthy children from those with RSV infection. This model had over 90 % accuracy in classifying blinded infants with similar illness severity. Two other models differentiated length of hospitalization and viral versus bacterial infection. CONCLUSION: While the sample sizes remain small, this is the first report suggesting that metabolomic analysis of urine samples has the potential to become a diagnostic aid. Future studies with larger sample sizes are required to validate the utility of metabolomics in pediatric patients with respiratory distress. PMID: 27549246 [PubMed - in process]