Literature DB >> 23210853

Metabolomics analysis for biomarker discovery: advances and challenges.

M S Monteiro1, M Carvalho, M L Bastos, P Guedes de Pinho.   

Abstract

Over the last decades there has been a change in biomedical research with the search for single genes, transcripts, proteins, or metabolites being substituted by the coverage of the entire genome, transcriptome, proteome, and metabolome with the "omics" approaches. The emergence of metabolomics, defined as the comprehensive analysis of all metabolites in a system, is still recent compared to other "omics" fields, but its particular features and the improvement of both analytical techniques and pattern recognition methods has contributed greatly to its increasingly use. The feasibility of metabolomics for biomarker discovery is supported by the assumption that metabolites are important players in biological systems and that diseases cause disruption of biochemical pathways, which are not new concepts. In fact, metabolomics, meaning the parallel assessment of multiple metabolites, has been shown to have benefits in various clinical areas. Compared to classical diagnostic approaches and conventional clinical biomarkers, metabolomics offers potential advantages in sensitivity and specificity. Despite its potential, metabolomics still retains several intrinsic limitations which have a great impact on its widespread implementation - these limitations in biological and experimental measurements. This review will provide an insight to the characteristics, strengths, limitations, and recent advances in metabolomics, always keeping in mind its potential application in clinical/ health areas as a biomarker discovery tool.

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Year:  2013        PMID: 23210853     DOI: 10.2174/092986713804806621

Source DB:  PubMed          Journal:  Curr Med Chem        ISSN: 0929-8673            Impact factor:   4.530


  55 in total

1.  Pharmacometabonomic Prediction of Busulfan Clearance in Hematopoetic Cell Transplant Recipients.

Authors:  Sandi L Navarro; Timothy W Randolph; Laura M Shireman; Daniel Raftery; Jeannine S McCune
Journal:  J Proteome Res       Date:  2016-07-20       Impact factor: 4.466

2.  Effect of dietary sodium restriction on human urinary metabolomic profiles.

Authors:  Kristen L Jablonski; Jelena Klawitter; Michel Chonchol; Candace J Bassett; Matthew L Racine; Douglas R Seals
Journal:  Clin J Am Soc Nephrol       Date:  2015-04-21       Impact factor: 8.237

Review 3.  Recent Trends in System-Scale Integrative Approaches for Discovering Protective Antigens Against Mycobacterial Pathogens.

Authors:  Aarti Rana; Shweta Thakur; Girish Kumar; Yusuf Akhter
Journal:  Front Genet       Date:  2018-11-27       Impact factor: 4.599

4.  Cognitive analysis of metabolomics data for systems biology.

Authors:  Erica L-W Majumder; Elizabeth M Billings; H Paul Benton; Richard L Martin; Amelia Palermo; Carlos Guijas; Markus M Rinschen; Xavier Domingo-Almenara; J Rafael Montenegro-Burke; Bradley A Tagtow; Robert S Plumb; Gary Siuzdak
Journal:  Nat Protoc       Date:  2021-01-22       Impact factor: 13.491

Review 5.  Biomarker development for hepatocellular carcinoma early detection: current and future perspectives.

Authors:  Shreya Sengupta; Neehar D Parikh
Journal:  Hepat Oncol       Date:  2017-11-17

Review 6.  NMR-based metabolomics studies of human prostate cancer tissue.

Authors:  Ana Rita Lima; Joana Pinto; Maria de Lourdes Bastos; Márcia Carvalho; Paula Guedes de Pinho
Journal:  Metabolomics       Date:  2018-06-18       Impact factor: 4.290

7.  Human liver tissue metabolic profiling research on hepatitis B virus-related hepatocellular carcinoma.

Authors:  Shu-Ye Liu; Rikki-Lei Zhang; Hua Kang; Zhi-Juan Fan; Zhi Du
Journal:  World J Gastroenterol       Date:  2013-06-14       Impact factor: 5.742

8.  1H NMR-based urine metabolomics for the evaluation of kidney injury in Wistar rats by 3-MCPD.

Authors:  Jian Ji; Lijuan Zhang; Hongxia Zhang; Chao Sun; Jiadi Sun; Hui Jiang; Mandour H Abdalhai; YinZhi Zhang; Xiulan Sun
Journal:  Toxicol Res (Camb)       Date:  2016-02-19       Impact factor: 3.524

9.  Hierarchical cluster analysis of technical replicates to identify interferents in untargeted mass spectrometry metabolomics.

Authors:  Lindsay K Caesar; Olav M Kvalheim; Nadja B Cech
Journal:  Anal Chim Acta       Date:  2018-03-19       Impact factor: 6.558

Review 10.  Urinary metabolites as noninvasive biomarkers of gastrointestinal diseases: A clinical review.

Authors:  Irene Sarosiek; Rudolf Schicho; Pedro Blandon; Mohammad Bashashati
Journal:  World J Gastrointest Oncol       Date:  2016-05-15
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