Literature DB >> 19191053

Metabolomics: unraveling the chemical individuality of common human diseases.

Sander M Houten1.   

Abstract

Sir Archibald Garrod is often referred to in recent perspectives on metabolomics because he was the first to recognize 'inborn errors of metabolism'. For decades, the determination of metabolites was the domain of those involved in the diagnosis of this class of inherited disorders. With the development of metabolomics, these methods to determine and analyze metabolites have been taken an exciting step forward and are now used to understand common human disease. This concept of looking at metabolites to solve the pathogenesis of human disease touches upon another concept developed by Garrod, known as 'chemical individuality'. Garrod proposed that each person is biochemically unique due to inherited differences in enzymes, which is reflected in disease predisposition. In a more contemporary perspective, this concept may be extended to chemical individuality of a human disease. This is the domain of metabolomics, which aims to determine as many metabolites as possible in samples from a cohort of individuals. Analysis of the results will identify changes in metabolites that correlate with the presence of certain afflictions. The next challenging step is then to determine whether these metabolites are only biomarkers for the presence of a disease or new leads to an unknown etiology.

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Year:  2009        PMID: 19191053     DOI: 10.1080/07853890902729794

Source DB:  PubMed          Journal:  Ann Med        ISSN: 0785-3890            Impact factor:   4.709


  9 in total

1.  Web-enabled and improved software tools and data are needed to measure nutrient intakes and physical activity for personalized health research.

Authors:  Phyllis J Stumbo; Rick Weiss; John W Newman; Jean A Pennington; Katherine L Tucker; Paddy L Wiesenfeld; Anne-Kathrin Illner; David M Klurfeld; Jim Kaput
Journal:  J Nutr       Date:  2010-10-27       Impact factor: 4.798

Review 2.  Emerging applications of metabolomics in drug discovery and precision medicine.

Authors:  David S Wishart
Journal:  Nat Rev Drug Discov       Date:  2016-03-11       Impact factor: 84.694

3.  Untargeted metabolomic approach to study the serum metabolites in women with polycystic ovary syndrome.

Authors:  Ying Yu; Panli Tan; Zhenchao Zhuang; Zhejiong Wang; Linchao Zhu; Ruyi Qiu; Huaxi Xu
Journal:  BMC Med Genomics       Date:  2021-08-20       Impact factor: 3.063

4.  Interrogating causal pathways linking genetic variants, small molecule metabolites, and circulating lipids.

Authors:  So-Youn Shin; Ann-Kristin Petersen; Simone Wahl; Guangju Zhai; Werner Römisch-Margl; Kerrin S Small; Angela Döring; Bernet S Kato; Annette Peters; Elin Grundberg; Cornelia Prehn; Rui Wang-Sattler; H-Erich Wichmann; Martin Hrabé de Angelis; Thomas Illig; Jerzy Adamski; Panos Deloukas; Tim D Spector; Karsten Suhre; Christian Gieger; Nicole Soranzo
Journal:  Genome Med       Date:  2014-03-28       Impact factor: 11.117

5.  Plasma lipidomics as a diagnostic tool for peroxisomal disorders.

Authors:  Katharina Herzog; Mia L Pras-Raves; Sacha Ferdinandusse; Martin A T Vervaart; Angela C M Luyf; Antoine H C van Kampen; Ronald J A Wanders; Hans R Waterham; Frédéric M Vaz
Journal:  J Inherit Metab Dis       Date:  2017-12-05       Impact factor: 4.982

Review 6.  Emerging Insights into the Metabolic Alterations in Aging Using Metabolomics.

Authors:  Sarika Srivastava
Journal:  Metabolites       Date:  2019-12-13

Review 7.  Advancing Cancer Treatment by Targeting Glutamine Metabolism-A Roadmap.

Authors:  Anna Halama; Karsten Suhre
Journal:  Cancers (Basel)       Date:  2022-01-22       Impact factor: 6.639

8.  UHPLC-MS-based metabolomics and chemoinformatics study reveals the neuroprotective effect and chemical characteristic in Parkinson's disease mice after oral administration of Wen-Shen-Yang-Gan decoction.

Authors:  Guoxue Zhu; Wang Wang; Chang Chen; Lili Tang; Yan Liang; Zhennian Zhang; Yan Lu; Yang Zhao
Journal:  Aging (Albany NY)       Date:  2021-08-02       Impact factor: 5.682

9.  Individual variability in human urinary metabolites identifies age-related, body mass index-related, and sex-related biomarkers.

Authors:  Tianling Wang; Lei Tang; Ruili Lin; Dian He; Yanqing Wu; Yang Zhang; Pingrong Yang; Junquan He
Journal:  Mol Genet Genomic Med       Date:  2021-07-22       Impact factor: 2.183

  9 in total

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