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Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases. | LitMetric

Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases.

Metabolites

Separation Science and Metabolomics Laboratory, Murdoch University, 90 South Street, Perth 6150, Australia.

Published: February 2019

AI Article Synopsis

  • The review covers the complexities of diagnosing and treating various kidney diseases, such as chronic kidney disease, diabetic nephropathy, and kidney cancer, while exploring their definitions, causes, epidemiology, and treatments.
  • A significant focus is placed on metabolomics, which involves studying small molecule biomarkers, to enhance diagnostic accuracy and understand the biochemical mechanisms behind these diseases.
  • The text discusses findings from studies using mass spectrometry-based metabolomics, highlighting specific metabolites that may serve as reliable indicators of kidney disease processes and suggesting their potential as biomarkers for further research.

Article Abstract

Diseases of the kidney are difficult to diagnose and treat. This review summarises the definition, cause, epidemiology and treatment of some of these diseases including chronic kidney disease, diabetic nephropathy, acute kidney injury, kidney cancer, kidney transplantation and polycystic kidney diseases. Numerous studies have adopted a metabolomics approach to uncover new small molecule biomarkers of kidney diseases to improve specificity and sensitivity of diagnosis and to uncover biochemical mechanisms that may elucidate the cause and progression of these diseases. This work includes a description of mass spectrometry-based metabolomics approaches, including some of the currently available tools, and emphasises findings from metabolomics studies of kidney diseases. We have included a varied selection of studies (disease, model, sample number, analytical platform) and focused on metabolites which were commonly reported as discriminating features between kidney disease and a control. These metabolites are likely to be robust indicators of kidney disease processes, and therefore potential biomarkers, warranting further investigation.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6410198PMC
http://dx.doi.org/10.3390/metabo9020034DOI Listing

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