PubMed

Estimated Glomerular Filtration Rate From a Panel of Filtration Markers-Hope for Increased Accuracy Beyond Measured Glomerular Filtration Rate? Adv Chronic Kidney Dis. 2018 Jan;25(1):67-75 Authors: Inker LA, Levey AS, Coresh J Abstract The recent Kidney Disease Improving Global Outcomes 2012 CKD guidelines recommend estimating GFR from serum creatinine (eGFRcr) as a first-line test to assess kidney function and using cystatin C or measured glomerular filtration rate (GFR) as confirmatory tests. eGFRcr may be inaccurate in people with variation in muscle mass or diet, and eGFRcys is not more accurate than eGFRcr. eGFRcrcys is more accurate than either, but it is not independent of eGFRcr. Measured GFR is not practical and is susceptible to error due to variation in clearance methods and in the behavior of exogenous filtration markers. Over the past few years, we have hypothesized, and begun to test the hypothesis, that a panel of filtration markers (panel eGFR) from a single blood draw would require fewer demographic or clinical variables and could estimate GFR as accurately as measured GFR. In this article, we describe the conceptual background and rationale for this hypothesis and summarize our work thus far including evaluation of novel low-molecular-weight proteins and metabolites and then outline how we envision that such a panel could be used in clinical practice, research, and public health. PMID: 29499889 [PubMed - in process]

Metabolomics reveal optimal grain pre-processing (milling) toward rice koji fermentation. J Agric Food Chem. 2018 Mar 02;: Authors: Lee S, Lee DE, Singh D, Lee CH Abstract A time-correlated mass spectrometry (MS) based metabolic profiling was performed for rice koji made using the substrates with varying degrees of milling (DOM). Overall, 67 primary and secondary metabolites were observed as significantly discriminant among different samples. Notably, a higher abundance of carbohydrate (sugars, sugar alcohols, organic acids, phenolic acids) and lipid (fatty acids, lysophospholipids) derived metabolites with enhanced hydrolytic enzyme activities were observed for koji made with substrate's DOM 5-7, at 36 h. The antioxidant secondary metabolites (flavonoids and phenolic acid) were relatively higher in koji with substrate's DOM 0, followed by DOM 5 > 7 > 9 and 11, at 96 h. Hence, we conjecture that the rice substrate pre-processing between DOM 5-7 was potentially optimal toward koji fermentation with end-product being rich in distinctive organoleptic, nutritional, and functional metabolites. The study rationalizes the substrate pre-processing steps vital for commercial koji making. PMID: 29499610 [PubMed - as supplied by publisher]

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Related Articles speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification. PLoS Comput Biol. 2018 Mar 01;14(3):e1006018 Authors: Beirnaert C, Meysman P, Vu TN, Hermans N, Apers S, Pieters L, Covaci A, Laukens K Abstract Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq). PMID: 29494588 [PubMed - as supplied by publisher]

Related Articles An evolutionary learning and network approach to identifying key metabolites for osteoarthritis. PLoS Comput Biol. 2018 Mar 01;14(3):e1005986 Authors: Hu T, Oksanen K, Zhang W, Randell E, Furey A, Sun G, Zhai G Abstract Metabolomics studies use quantitative analyses of metabolites from body fluids or tissues in order to investigate a sequence of cellular processes and biological systems in response to genetic and environmental influences. This promises an immense potential for a better understanding of the pathogenesis of complex diseases. Most conventional metabolomics analysis methods exam one metabolite at a time and may overlook the synergistic effect of combining multiple metabolites. In this article, we proposed a new bioinformatics framework that infers the non-linear synergy among multiple metabolites using a symbolic model and subsequently, identify key metabolites using network analysis. Such a symbolic model is able to represent a complex non-linear relationship among a set of metabolites associated with osteoarthritis (OA) and is automatically learned using an evolutionary algorithm. Applied to the Newfoundland Osteoarthritis Study (NFOAS) dataset, our methodology was able to identify nine key metabolites including some known osteoarthritis-associated metabolites and some novel metabolic markers that have never been reported before. The results demonstrate the effectiveness of our methodology and more importantly, with further investigations, propose new hypotheses that can help better understand the OA disease. PMID: 29494586 [PubMed - as supplied by publisher]

Related Articles Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online. Nat Protoc. 2018 Apr;13(4):633-651 Authors: Forsberg EM, Huan T, Rinehart D, Benton HP, Warth B, Hilmers B, Siuzdak G Abstract Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LC)-mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5-10 min, depending on user experience; data processing typically takes 1-3 h, and data analysis takes ∼30 min. PMID: 29494574 [PubMed - in process]

Related Articles MycoKey Round Table Discussions of Future Directions in Research on Chemical Detection Methods, Genetics and Biodiversity of Mycotoxins. Toxins (Basel). 2018 Mar 01;10(3): Authors: Leslie JF, Lattanzio V, Audenaert K, Battilani P, Cary J, Chulze SN, De Saeger S, Gerardino A, Karlovsky P, Liao YC, Maragos CM, Meca G, Medina A, Moretti A, Munkvold G, Mulè G, Njobeh P, Pecorelli I, Perrone G, Pietri A, Palazzini JM, Proctor RH, Rahayu ES, Ramírez ML, Samson R, Stroka J, Sulyok M, Sumarah M, Waalwijk C, Zhang Q, Zhang H, Logrieco AF Abstract MycoKey, an EU-funded Horizon 2020 project, includes a series of "Roundtable Discussions" to gather information on trending research areas in the field of mycotoxicology. This paper includes summaries of the Roundtable Discussions on Chemical Detection and Monitoring of mycotoxins and on the role of genetics and biodiversity in mycotoxin production. Discussions were managed by using the nominal group discussion technique, which generates numerous ideas and provides a ranking for those identified as the most important. Four questions were posed for each research area, as well as two questions that were common to both discussions. Test kits, usually antibody based, were one major focus of the discussions at the Chemical Detection and Monitoring roundtable because of their many favorable features, e.g., cost, speed and ease of use. The second area of focus for this roundtable was multi-mycotoxin detection protocols and the challenges still to be met to enable these protocols to become methods of choice for regulated mycotoxins. For the genetic and biodiversity group, both the depth and the breadth of trending research areas were notable. For some areas, e.g., microbiome studies, the suggested research questions were primarily of a descriptive nature. In other areas, multiple experimental approaches, e.g., transcriptomics, proteomics, RNAi and gene deletions, are needed to understand the regulation of toxin production and mechanisms underlying successful biological controls. Answers to the research questions will provide starting points for developing acceptable prevention and remediation processes. Forging a partnership between scientists and appropriately-placed communications experts was recognized by both groups as an essential step to communicating risks, while retaining overall confidence in the safety of the food supply and the integrity of the food production chain. PMID: 29494529 [PubMed - in process]

Related Articles Development of a sheathless CE-ESI-MS interface. Electrophoresis. 2018 Mar 01;: Authors: Hirayama A, Abe H, Yamaguchi N, Tabata S, Tomita M, Soga T Abstract A sheath-flow interface is the most common ionization technique in CE-ESI-MS. However, this interface dilutes the analytes with the sheath liquid and decreases the sensitivity. In this study, we developed a sheathless CE-MS interface to improve sensitivity. The interface was fabricated by making small crack approximately 2 cm from the end of a capillary column fixed on a plastic plate, and then covering the crack with a dialysis membrane to prevent metabolite loss during separation. A voltage for CE separation was applied between the capillary inlet and the buffer reservoir. Under optimum conditions, 52 cationic metabolite standards were separated and selectively detected using MS. With a pressure injection of 5 kPa for 15 s (ca. 1.4 nL), the detection limits for the tested compounds were between 0.06 and 1.7 μmol/L (S/N = 3). The method was applied to analysis of cationic metabolites extracted from a small number (12,000) of cancer cells, and the number of peaks detected was about 2.5 times higher than when using conventional sheath-flow CE-MS. Because the interface is easy to construct, it is cost-effective and can be adapted to any commercially available capillaries. This method is a powerful new tool for highly sensitive CE-MS-based metabolomic analysis. This article is protected by copyright. All rights reserved. PMID: 29493797 [PubMed - as supplied by publisher]

Related Articles [Identification of biomarkers in urine of rats with spleen Qi deficiency and biological significance]. Zhongguo Zhong Yao Za Zhi. 2017 Dec;42(24):4855-4863 Authors: Liu WP, Li CY, Huang J, Liao JZ, Ma WJ, Chen HY, Rui W Abstract To identify biomarkers for spleen Qi deficiency by analyzing small molecule metabolites in urine, in order to expound the relationship between biomarkers and metabolic pathways. The spleen Qi deficiency model was established through dietary restriction and overstrain. All of the rats received D-xylose absorption experiment and blood routine test. Urine samples were collected in the next day. The urine samples were analyzed using UPLC-Q-TOF-MS to obtain the dataset of urine metabolic group. Principal component analysis (PCA), orthogonal partialleast squares-discriminant analysis (OPLS-DA) and other multivariate statistical methods were employed to evaluate the quality of the dataset and screen out potential biomarkers of spleen Qi deficiency. The results of D-xylose absorption and blood routine demonstrated that the spleen Qi deficiency model was successfully established. In positive ion mode and negative ion mode, PCA and OPLS-DA score plots could clearly distinguish model group and blank group. According to S-plot of OPLS-DA, VIP value, t-test and area under receiver operating characteristic curve (ROC), 24 biomarkers, including phenylalanine, succinic acid, aconitic acid, isocitrate acid, betaine, kynurenine, indole, creatine, creatinine, orotic acid, xanthine, and xanthurenic acid, were identified as associated with the spleen Qi deficiency, mainly involving energy metabolism, amino acid metabolism, tryptophan metabolism, purine metabolism and pyrimidine metabolism. Urine metabolomics method combined with online software package for data processing and analysis metabolic pathway can provide new methods and ideas for studies for spleen Qi deficiency and other traditional Chinese medicine symptoms. PMID: 29493158 [PubMed - in process]

Related Articles Explaining combinatorial effects of mycotoxins Deoxynivalenol and Zearalenone in mice with urinary metabolomic profiling. Sci Rep. 2018 Feb 28;8(1):3762 Authors: Ji J, Zhu P, Blaženović I, Cui F, Gholami M, Sun J, Habimana J, Zhang Y, Sun X Abstract Urine metabolic profiling of mice was conducted utilizing gas chromatography-mass spectrometry (GC-MS) to investigate the combinatory effect of mycotoxins deoxynivalenol (DON) and zearalenone (ZEN) on the metabolism of the mice. Experiments were conducted by means of five-week-old mice which were individually exposed to 2 mg/kg DON, 20 mg/kg ZEN and the mixture of DON and ZEN (2 mg/kg and 20 mg/kg, respectively). The intragastric administration was applied for three weeks and urine samples were collected for metabolic analysis. Univariate and multivariate analysis were applied to data matrix processing along with respective pathway analysis by MetaMapp and CytoScape. The results showed that the combined DON and ZEN administration resulted in lower significant changes, compared to the individual mycotoxin treated groups verified by heatmap. Metabolic pathways network mapping indicated that the combined mycotoxins treated groups showed a little effect on the metabolites in most pathways, especially in glucose metabolism and its downstream amino acid metabolism. In glucose metabolism, the content of galactose, mannitol, galactonic acid, myo-inositol, tagatose was drastically down-regulated. Furthermore, the organic acids, pyruvate, and amino acids metabolism displayed the same phenomenon. In conclusion, the combined DON/ZEN administration might lead to an "antagonistic effect" in mice metabolism. PMID: 29491435 [PubMed - in process]

Related Articles Metabolic determinants of sensitivity to phosphatidylinositol 3-kinase pathway inhibitor in small-cell lung carcinoma. Cancer Res. 2018 Feb 28;: Authors: Makinoshima H, Umemura S, Suzuki A, Nakanishi H, Maruyama A, Udagawa H, Mimaki S, Matsumoto S, Niho S, Ishii G, Tsuboi M, Ochiai A, Esumi H, Sasaki T, Goto K, Tsuchihara K Abstract Comprehensive genomic analysis has revealed that the PI3K/AKT/mTOR pathway is a feasible therapeutic target in small-cell lung carcinoma (SCLC). However, biomarkers to identify patients likely to benefit from inhibitors of this pathway have not been identified. Here we show that metabolic features determine sensitivity to the PI3K/mTOR dual inhibitor gedatolisib in SCLC cells. Substantial phosphatidyl lipid analysis revealed that a specific phosphatidylinositol (3,4,5)-trisphosphate (PIP3) subspecies lipid product: PIP3 (38:4) is predictive in assessing sensitivity to PI3K/mTOR dual inhibitor. Notably, we found that higher amounts of purine-related aqueous metabolites such as hypoxanthine, which are characteristic of SCLC biology, lead to resistance to PI3K pathway inhibition. In addition, the levels of the mRNA encoding hypoxanthine phosphoribosyl transferase 1 (HPRT1), a key component of the purine salvage pathway, differed significantly between SCLC cells sensitive or resistant to gedatolisib. Moreover, complementation with purine metabolites could reverse the vulnerability to targeting of the PI3K pathway in SCLC cells normally sensitive to gedatolisib. These results indicate that the resistance mechanism of PI3K pathway inhibitors is mediated by the activation of the purine salvage pathway, supplying purine resource to nucleotide biosynthesis. Metabolomics is a powerful approach for finding novel therapeutic biomarkers in SCLC treatment. PMID: 29490947 [PubMed - as supplied by publisher]

Aspirin Recapitulates Features of Caloric Restriction. Cell Rep. 2018 Feb 27;22(9):2395-2407 Authors: Pietrocola F, Castoldi F, Markaki M, Lachkar S, Chen G, Enot DP, Durand S, Bossut N, Tong M, Malik SA, Loos F, Dupont N, Mariño G, Abdelkader N, Madeo F, Maiuri MC, Kroemer R, Codogno P, Sadoshima J, Tavernarakis N, Kroemer G Abstract The age-associated deterioration in cellular and organismal functions associates with dysregulation of nutrient-sensing pathways and disabled autophagy. The reactivation of autophagic flux may prevent or ameliorate age-related metabolic dysfunctions. Non-toxic compounds endowed with the capacity to reduce the overall levels of protein acetylation and to induce autophagy have been categorized as caloric restriction mimetics (CRMs). Here, we show that aspirin or its active metabolite salicylate induce autophagy by virtue of their capacity to inhibit the acetyltransferase activity of EP300. While salicylate readily stimulates autophagic flux in control cells, it fails to further increase autophagy levels in EP300-deficient cells, as well as in cells in which endogenous EP300 has been replaced by salicylate-resistant EP300 mutants. Accordingly, the pro-autophagic activity of aspirin and salicylate on the nematode Caenorhabditis elegans is lost when the expression of the EP300 ortholog cpb-1 is reduced. Altogether, these findings identify aspirin as an evolutionary conserved CRM. PMID: 29490275 [PubMed - in process]

Metabolomic Markers of Essential Fatty Acids, Carnitine, and Cholesterol Metabolism in Adults and Adolescents with Phenylketonuria. J Nutr. 2018 Feb 01;148(2):194-201 Authors: Stroup BM, Nair N, Murali SG, Broniowska K, Rohr F, Levy HL, Ney DM Abstract Background: Individuals with phenylketonuria (PKU) have a risk of cognitive impairment and inflammation. Many follow a low-phenylalanine (low-Phe) diet devoid of animal protein in combination with medical foods (MFs). Objective: To assess lipid metabolism in participants with PKU consuming amino acid MFs (AA-MFs) or glycomacropeptide MFs (GMP-MFs), we conducted fatty acid and metabolomics analyses. Methods: We used subsets of fasting plasma and urine samples from our randomized crossover trial in which participants with early-treated classical and variant (milder) PKU consumed a low-Phe diet combined with AA-MFs or GMP-MFs for 3 wk each. Fatty acid profiles of red blood cell (RBC) membranes were determined for 25 adults (aged 18-49 y) with PKU and 143 control participants. Metabolomics analyses of plasma and urine samples were conducted by Metabolon for 9-10 adolescent and adult participants with PKU and for 15 control participants. Results: RBC fatty acid profiles were not significantly different with AA-MFs or GMP-MFs. PKU participants showed higher total n-6:n-3 (ω-6:ω-3) fatty acids (mean ± SD percentages of total fatty acids: AA-MF = 5.45% ± 1.07%; controls = 4.33%; P < 0.001) and lower docosahexaenoic acid (DHA; AA-MF = 3.21% ± 0.98%; controls = 3.70% ± 1.01%; P = 0.02) and eicosapentaenoic acid (AA-MF = 0.33% ± 0.12%; controls = 0.60% ± 0.43%; P < 0.001) in RBCs than did control participants. Despite higher carnitine intake from AA-MFs than GMP-MFs (mean ± SE intake: AA-MFs = 58.6 ± 5.3 mg/d; GMP-MFs = 0.3 ± 0.01 mg/d; P < 0.001), plasma concentrations of carnitine were similar and not different from those in the control group (AA-MF compared with GMP-MF, P = 0.73). AA-MFs resulted in higher urinary excretion of trimethylamine N-oxide (TMAO), which is synthesized by bacteria from carnitine, compared with GMP-MFs (mean ± SE scaled intensity-TMAO: AA-MFs = 1.2 ± 0.1, GMP-MFs = 0.9 ± 0.1; P = 0.005). Plasma deoxycarnitine was lower in PKU participants than in control participants, suggesting reduced carnitine biosynthesis in PKU (AA-MF = 0.9 ± 0.1; GMP-MF = 1.0 ± 0.1; controls = 1.3 ± 0.1; AA-MF compared with controls, P = 0.01; GMP-MF compared with controls, P = 0.04). Conclusions: Supplementation with DHA is needed in PKU. Carnitine supplementation of AA-MFs shows reduced bioavailability due, in part, to bacterial degradation to TMAO, whereas the bioavailability of carnitine is greater with prebiotic GMP-MFs. This trial was registered at www.clinicaltrials.gov as NCT01428258. PMID: 29490096 [PubMed - in process]

Joint Data Analysis in Nutritional Epidemiology: Identification of Observational Studies and Minimal Requirements. J Nutr. 2018 Feb 01;148(2):285-297 Authors: Pinart M, Nimptsch K, Bouwman J, Dragsted LO, Yang C, De Cock N, Lachat C, Perozzi G, Canali R, Lombardo R, D'Archivio M, Guillaume M, Donneau AF, Jeran S, Linseisen J, Kleiser C, Nöthlings U, Barbaresko J, Boeing H, Stelmach-Mardas M, Heuer T, Laird E, Walton J, Gasparini P, Robino A, Castaño L, Rojo-Martínez G, Merino J, Masana L, Standl M, Schulz H, Biagi E, Nurk E, Matthys C, Gobbetti M, de Angelis M, Windler E, Zyriax BC, Tafforeau J, Pischon T Abstract Background: Joint data analysis from multiple nutrition studies may improve the ability to answer complex questions regarding the role of nutritional status and diet in health and disease. Objective: The objective was to identify nutritional observational studies from partners participating in the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) Consortium, as well as minimal requirements for joint data analysis. Methods: A predefined template containing information on study design, exposure measurements (dietary intake, alcohol and tobacco consumption, physical activity, sedentary behavior, anthropometric measures, and sociodemographic and health status), main health-related outcomes, and laboratory measurements (traditional and omics biomarkers) was developed and circulated to those European research groups participating in the ENPADASI under the strategic research area of "diet-related chronic diseases." Information about raw data disposition and metadata sharing was requested. A set of minimal requirements was abstracted from the gathered information. Results: Studies (12 cohort, 12 cross-sectional, and 2 case-control) were identified. Two studies recruited children only and the rest recruited adults. All studies included dietary intake data. Twenty studies collected blood samples. Data on traditional biomarkers were available for 20 studies, of which 17 measured lipoproteins, glucose, and insulin and 13 measured inflammatory biomarkers. Metabolomics, proteomics, and genomics or transcriptomics data were available in 5, 3, and 12 studies, respectively. Although the study authors were willing to share metadata, most refused, were hesitant, or had legal or ethical issues related to sharing raw data. Forty-one descriptors of minimal requirements for the study data were identified to facilitate data integration. Conclusions: Combining study data sets will enable sufficiently powered, refined investigations to increase the knowledge and understanding of the relation between food, nutrition, and human health. Furthermore, the minimal requirements for study data may encourage more efficient secondary usage of existing data and provide sufficient information for researchers to draft future multicenter research proposals in nutrition. PMID: 29490094 [PubMed - in process]

Development of a Reverse Phase HPLC Retention Index Model for Non-Targeted Metabolomics Using Synthetic Compounds. J Chem Inf Model. 2018 Feb 28;: Authors: Hall LM, Hill DW, Bugden K, Cawley SM, Hall L, Chen MH, Grant DF Abstract The MolFind application has been developed as a non-targeted metabolomics chemometric tool to facilitate structure identification when HPLC biofluids analysis reveals a feature of interest. Here synthetic compounds are selected and measured to form the basis of a new, more accurate, HPLC retention index model for use with MolFind. We show that relatively inexpensive synthetic screening compounds with simple structures can be used to develop an artificial neural network model that is successful in making quality predictions for human metabolites. A total of 1955 compounds were obtained and measured for the model. A separate set of 202 human metabolites was used for independent validation. The new ANN model showed improved accuracy over previous models. The model, based on relatively simple compounds, was able to make quality predictions for complex compounds not similar to training data. Independent validation metabolites with feature combinations found in three or more training compounds were predicted with 97% sensitivity while metabolites with feature combinations found in less than three training compounds were predicted with >90% sensitivity. The study describes the method used to select synthetic compounds and new descriptors developed to encode the relationship between lipophilic molecular subgraphs and HPLC retention. Finally, we introduce the QRI (qualitative range of interest) modification of neural network back-propagation learning to generate models simultaneously based on quantitative and qualitative data. PMID: 29489351 [PubMed - as supplied by publisher]

Metabolomics analysis reveals an effect of homocysteine on arachidonic acid and linoleic acid metabolism pathway. Mol Med Rep. 2018 Feb 27;: Authors: Li B, Gao G, Zhang W, Li B, Yang C, Jiang X, Tian Y, Liang H Abstract An increase in serum homocysteine level has been associated with an increased risk of vascular disease; however, the biochemical mechanisms that underlie these effects remain largely unknown. The present study aimed to use high-performance liquid chromatography-mass spectrometry (HPLC‑MS) to demonstrate the effects of serum homocysteine on human blood metabolites. A total of 75 fasting serum samples were investigated in the present study. Using a threshold of 15 µmol/l serum homocysteine level, samples were divided into high‑ and low‑homocysteine groups, and the serum extracts were analyzed with an HPLC‑MS‑based method. A total of 269 features exhibited significant differences and correlation with serum homocysteine levels in the electrospray ionization‑positive [ESI(+)] mode, and 69 features were identified in the ESI(‑) mode between the two groups. The principal component analysis plot revealed a separation between the high‑ and the low‑homocysteine groups. Metabolite set enrichment analysis identified arachidonic acid metabolism and linoleic acid metabolism as the two pathways with significantly enriched differences. These results revealed that arachidonic acid and linoleic acid metabolism may be associated with serum homocysteine levels and may be involved in homocysteine-induced vascular disease. PMID: 29488618 [PubMed - as supplied by publisher]

A metabolomic study on early detection of steroid-induced avascular necrosis of the femoral head. Oncotarget. 2018 Jan 30;9(8):7984-7995 Authors: Ren X, Fan W, Shao Z, Chen K, Yu X, Liang Q Abstract The early and accurate diagnosis of steroid-induced avascular necrosis of the femoral head (SANFH) is appealing considering its irreversible progression and serious consequence for the patients. The purpose of this study was to investigate the metabolic change of SANFH for its early detection. Two stages were designed in this study, namely discovery and verification. Except the biochemical index anomaly and the accidental death, 30 adult healthy adult Japanese white rabbits were used for screening out the potential metabolites in discovery experiment and 13 rabbits were used in verification experiment. The femoral heads were assessed with magnetic resonance imaging and transmission electron microscopy. The metabolomic profiling of serum samples were analysis by UHPLC-MS/MS. Metabolomic cluster analysis enable us to differentiate the rabbits without and with injection of the glucocorticoid in 1 week even when there is no obvious abnormal symptom in behaviors or imaging diagnosis. The majority of differential metabolites were identified as phospholipids which were observed significant change after injection of glucocorticoid in 1, 2, 3 weeks. And the results obtained in verification experiment of 6 weeks showed that these differential metabolites exhibited consistent trends in late progression with that in early-stage. At the end of 6 weeks the damage of SANFH could be verified by pathological imaging. Therefore the finding of serum metabolite profile links to the progression of SANFH and provides the potential of early detection of SANFH. PMID: 29487708 [PubMed]

A metabolomics study of Qiliqiangxin in a rat model of heart failure: a reverse pharmacology approach. Sci Rep. 2018 Feb 27;8(1):3688 Authors: Fu J, Chang L, Harms AC, Jia Z, Wang H, Wei C, Qiao L, Tian S, Hankemeier T, Wu Y, Wang M Abstract The Chinese medicine Qiliqiangxin (QL) has been shown to have a protective role in heart failure. Here, we explore the underlying working mechanism of the key therapeutic component in QL using a rat model of heart failure. Heart failure after myocardial infarction was induced surgically and confirmed using echocardiography; a separate group of rats underwent sham surgery. The rats with heart failure were randomly assigned to receive QL, the angiotensin-converting enzyme inhibitor benazepril, or placebo groups. Blood samples were collected from the rats at four time points for up to 8 weeks and used for biochemical analysis and mass spectrometry‒based metabolomics profiling. In total, we measured nine well-known biochemical parameters of heart failure and 147 metabolites. In the rats with heart failure, QL significantly improved these biochemical parameters and metabolomics profiles, significantly increasing the cardioprotective parameter angiopoietin-like 4 and significantly lowering inflammation-related oxylipins and lysophosphatidic acids compared to benazepril. Mechanistically, QL may improve outcome in heart failure by controlling inflammatory process and cardiac hypertrophy. Clinical studies should be designed in order to investigate these putative mechanisms in patients. PMID: 29487344 [PubMed - in process]

Tailed giant Tupanvirus possesses the most complete translational apparatus of the known virosphere. Nat Commun. 2018 Feb 27;9(1):749 Authors: Abrahão J, Silva L, Silva LS, Khalil JYB, Rodrigues R, Arantes T, Assis F, Boratto P, Andrade M, Kroon EG, Ribeiro B, Bergier I, Seligmann H, Ghigo E, Colson P, Levasseur A, Kroemer G, Raoult D, La Scola B Abstract Here we report the discovery of two Tupanvirus strains, the longest tailed Mimiviridae members isolated in amoebae. Their genomes are 1.44-1.51 Mb linear double-strand DNA coding for 1276-1425 predicted proteins. Tupanviruses share the same ancestors with mimivirus lineages and these giant viruses present the largest translational apparatus within the known virosphere, with up to 70 tRNA, 20 aaRS, 11 factors for all translation steps, and factors related to tRNA/mRNA maturation and ribosome protein modification. Moreover, two sequences with significant similarity to intronic regions of 18 S rRNA genes are encoded by the tupanviruses and highly expressed. In this translation-associated gene set, only the ribosome is lacking. At high multiplicity of infections, tupanvirus is also cytotoxic and causes a severe shutdown of ribosomal RNA and a progressive degradation of the nucleus in host and non-host cells. The analysis of tupanviruses constitutes a new step toward understanding the evolution of giant viruses. PMID: 29487281 [PubMed - in process]

Metabolic characterization of human aqueous humor in the cataract progression after pars plana vitrectomy. BMC Ophthalmol. 2018 Feb 27;18(1):63 Authors: Ji Y, Rong X, Lu Y Abstract BACKGROUND: While pars plana vitrectomy (PPV) has become the third most commonly performed surgery in the world, it can also induce multiple post complications easily. Among them, cataract progression is the most frequent one that can lead to blindness eventually. METHODS: To understand the underlying mechanisms of post PPV cataract progression, we performed comprehensive metabolic characterization of aqueous humor (AH) samples from 20 cataract patients (10 post PPV complication and 10 none PPV cataract) by a non-targeted metabolomic analysis using gas chromatography combined with time-of-flight mass spectrometer (GC/TOF MS). RESULTS: A total of 263 metabolites were identified and eight of them are determined to be significantly different (VIP ≥ 1 and p ≤ 0.05) between post PPV group and none PPV control group. The significantly changed metabolites included glutaric acid and pelargonic acid that play key roles in the regulation of oxidative stress and inflammatory responses. Furthermore, we constructed a metabolic regulatory network in each group based on metabolite-metabolite correlations, which reveals key metabolic pathways and regulatory elements including amino acids and lipids metabolisms that are related to cataract progression. CONCLUSIONS: Altogether, this work discovered some potential metabolite biomarkers for post PPV cataract diagnostics, as well as casted some novel insights into the underlying mechanisms of cataract progression after PPV. PMID: 29486760 [PubMed - in process]