Literature DB >> 26965202

Emerging applications of metabolomics in drug discovery and precision medicine.

David S Wishart1,2,3.   

Abstract

Metabolomics is an emerging 'omics' science involving the comprehensive characterization of metabolites and metabolism in biological systems. Recent advances in metabolomics technologies are leading to a growing number of mainstream biomedical applications. In particular, metabolomics is increasingly being used to diagnose disease, understand disease mechanisms, identify novel drug targets, customize drug treatments and monitor therapeutic outcomes. This Review discusses some of the latest technological advances in metabolomics, focusing on the application of metabolomics towards uncovering the underlying causes of complex diseases (such as atherosclerosis, cancer and diabetes), the growing role of metabolomics in drug discovery and its potential effect on precision medicine.

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Year:  2016        PMID： 26965202     DOI： 10.1038/nrd.2016.32

Source DB:  PubMed          Journal:  Nat Rev Drug Discov        ISSN： 1474-1776            Impact factor:   84.694


  152 in total

1.  Metallomics: a new frontier in analytical chemistry.

Authors:  Joanna Szpunar
Journal:  Anal Bioanal Chem       Date:  2003-11-12       Impact factor: 4.142

2.  Personal genomes: The case of the missing heritability.

Authors:  Brendan Maher
Journal:  Nature       Date:  2008-11-06       Impact factor: 49.962

Review 3.  Glucose-regulated proteins in cancer: molecular mechanisms and therapeutic potential.

Authors:  Amy S Lee
Journal:  Nat Rev Cancer       Date:  2014-04       Impact factor: 60.716

Review 4.  Altered metabolism and newborn screening using tandem mass spectrometry: lessons learned from the bench to bedside.

Authors:  Donald H Chace; Alan R Spitzer
Journal:  Curr Pharm Biotechnol       Date:  2011-07       Impact factor: 2.837

Review 5.  Oncometabolites-driven tumorigenesis: From genetics to targeted therapy.

Authors:  Aurélie Morin; Eric Letouzé; Anne-Paule Gimenez-Roqueplo; Judith Favier
Journal:  Int J Cancer       Date:  2014-08-14       Impact factor: 7.396

6.  2-Hydroxyglutarate Inhibits ATP Synthase and mTOR Signaling.

Authors:  Xudong Fu; Randall M Chin; Laurent Vergnes; Heejun Hwang; Gang Deng; Yanpeng Xing; Melody Y Pai; Sichen Li; Lisa Ta; Farbod Fazlollahi; Chuo Chen; Robert M Prins; Michael A Teitell; David A Nathanson; Albert Lai; Kym F Faull; Meisheng Jiang; Steven G Clarke; Timothy F Cloughesy; Thomas G Graeber; Daniel Braas; Heather R Christofk; Michael E Jung; Karen Reue; Jing Huang
Journal:  Cell Metab       Date:  2015-07-16       Impact factor: 27.287

7.  MetaboAnalyst 3.0--making metabolomics more meaningful.

Authors:  Jianguo Xia; Igor V Sinelnikov; Beomsoo Han; David S Wishart
Journal:  Nucleic Acids Res       Date:  2015-04-20       Impact factor: 16.971

8.  COSMIC: exploring the world's knowledge of somatic mutations in human cancer.

Authors:  Simon A Forbes; David Beare; Prasad Gunasekaran; Kenric Leung; Nidhi Bindal; Harry Boutselakis; Minjie Ding; Sally Bamford; Charlotte Cole; Sari Ward; Chai Yin Kok; Mingming Jia; Tisham De; Jon W Teague; Michael R Stratton; Ultan McDermott; Peter J Campbell
Journal:  Nucleic Acids Res       Date:  2014-10-29       Impact factor: 16.971

Review 9.  Measuring the metabolome: current analytical technologies.

Authors:  Warwick B Dunn; Nigel J C Bailey; Helen E Johnson
Journal:  Analyst       Date:  2005-03-04       Impact factor: 4.616

10.  Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults.

Authors:  Peter Würtz; Pasi Soininen; Antti J Kangas; Tapani Rönnemaa; Terho Lehtimäki; Mika Kähönen; Jorma S Viikari; Olli T Raitakari; Mika Ala-Korpela
Journal:  Diabetes Care       Date:  2012-11-05       Impact factor: 19.112
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  299 in total

1.  Comprehensive metabolomic and proteomic analyses reveal candidate biomarkers and related metabolic networks in atrial fibrillation.

Authors:  Juntuo Zhou; Lijie Sun; Liwen Chen; Shuwang Liu; Lijun Zhong; Ming Cui
Journal:  Metabolomics       Date:  2019-06-21       Impact factor: 4.290

2.  A three-minute method for high-throughput quantitative metabolomics and quantitative tracing experiments of central carbon and nitrogen pathways.

Authors:  Travis Nemkov; Kirk C Hansen; Angelo D'Alessandro
Journal:  Rapid Commun Mass Spectrom       Date:  2017-04-30       Impact factor: 2.419

Review 3.  Metabolomics: A Primer.

Authors:  Xiaojing Liu; Jason W Locasale
Journal:  Trends Biochem Sci       Date:  2017-02-11       Impact factor: 13.807

4.  Isotope Labeling-Assisted Evaluation of Hydrophilic and Hydrophobic Liquid Chromatograph-Mass Spectrometry for Metabolomics Profiling.

Authors:  Boer Xie; Yuanyuan Wang; Drew R Jones; Kaushik Kumar Dey; Xusheng Wang; Yuxin Li; Ji-Hoon Cho; Timothy I Shaw; Haiyan Tan; Junmin Peng
Journal:  Anal Chem       Date:  2018-06-25       Impact factor: 6.986

5.  Metabolic alterations in triptolide-induced acute hepatotoxicity.

Authors:  Jie Zhao; Cen Xie; Xiyan Mu; Kristopher W Krausz; Daxesh P Patel; Xiaowei Shi; Xiaoxia Gao; Qiao Wang; Frank J Gonzalez
Journal:  Biomed Chromatogr       Date:  2018-07-04       Impact factor: 1.902

6.  Target-Decoy-Based False Discovery Rate Estimation for Large-Scale Metabolite Identification.

Authors:  Xusheng Wang; Drew R Jones; Timothy I Shaw; Ji-Hoon Cho; Yuanyuan Wang; Haiyan Tan; Boer Xie; Suiping Zhou; Yuxin Li; Junmin Peng
Journal:  J Proteome Res       Date:  2018-05-29       Impact factor: 4.466

7.  Metabolomics technology and bioinformatics for precision medicine.

Authors:  Rajeev K Azad; Vladimir Shulaev
Journal:  Brief Bioinform       Date:  2019-11-27       Impact factor: 11.622

8.  Sex and puberty-related differences in metabolomic profiles associated with adiposity measures in youth with obesity.

Authors:  Christoph Saner; Brooke E Harcourt; Ahwan Pandey; Susan Ellul; Zoe McCallum; Kung-Ting Kao; Celia Twindyakirana; Anke Pons; Erin J Alexander; Richard Saffery; David P Burgner; Markus Juonala; Matthew A Sabin
Journal:  Metabolomics       Date:  2019-05-03       Impact factor: 4.290

9.  Five Easy Metrics of Data Quality for LC-MS-Based Global Metabolomics.

Authors:  Xinyu Zhang; Jiyang Dong; Daniel Raftery
Journal:  Anal Chem       Date:  2020-09-14       Impact factor: 6.986

10.  Liver metabolomics in a mouse model of erythropoietic protoporphyria.

Authors:  Pengcheng Wang; Madhav Sachar; Grace L Guo; Amina I Shehu; Jie Lu; Xiao-Bo Zhong; Xiaochao Ma
Journal:  Biochem Pharmacol       Date:  2018-06-12       Impact factor: 5.858
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