4.6 Article

Metabolomics and the Diagnosis of Human Diseases - A Guide to the Markers and Pathophysiological Pathways Affected

期刊

CURRENT MEDICINAL CHEMISTRY
卷 21, 期 7, 页码 823-848

出版社

BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/0929867320666131119124056

关键词

Bone; cancer; cardiovascular disease; celiac disease; Crohn's disease; depression; diabetes; inborn errors of metabolism; metabolomics; neurological disease

资金

  1. CONSOLIDER-INGENIO [CSD2007-00063]
  2. Grupo de excelencia de la Region de Murcia [04486/GERM/06]
  3. CICYT project of the Spanish Ministry of Science and Innovation [AGL2011-23690]

向作者/读者索取更多资源

This review was designed as a handbook of metabolomic markers of high significance for a wide range of human diseases. This is the first report to collate results from recent studies in a format that allows ready identification of key metabolites by cross-comparisons of results from one disease to another. All the data presented in this work were obtained by previous research carried out exclusively during clinical trials in humans. Also, discussion of the pathophysiological pathways linked to the markers described is provided. The clinical assays focused on non-targeted or targeted metabolomics and metabolite profiling (focused assays which only refer to a limited array of known biomarkers, applying discriminatory and bioinformatic tools to them) as well as predictive modelling based on clinical trials. The data also highlight pathways and biological compounds that are disrupted at early stages of the diseases, in order to help elucidate target compounds and the pathophysiology of the considered diseases for early prognosis and diagnosis using noninvasive samples (saliva, sputum, serum, plasma, blood, urine, tissue, faecal water or faeces). In the tables, the candidate metabolites for biomarkers of diagnosis, or the biomarkers themselves, are detailed, indicating the type of sample in which they were detected and their up-or down-regulation (if calculated). The metabolites derived from each study have been filtered carefully, according to the analytical platform, and biostatistical discriminant analyses developed. Among the pool of data provided, those reaching a level of significance of p=0.05-0.0001, according to the Bonferroni correction, Steel-Dwass t- or Wilcoxon matched pair tests, are shown.

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