NMR-based metabolomics associated with chronic kidney disease in humans and animals: a one health perspective.


Journal

Molecular and cellular biochemistry
ISSN: 1573-4919
Titre abrégé: Mol Cell Biochem
Pays: Netherlands
ID NLM: 0364456

Informations de publication

Date de publication:
Nov 2021
Historique:
received: 20 05 2021
accepted: 07 07 2021
pubmed: 28 7 2021
medline: 4 2 2022
entrez: 27 7 2021
Statut: ppublish

Résumé

Chronic kidney disease (CKD) is a renal dysfunction that can lead to high rates of mortality and morbidity, particularly when coupled with late diagnosis. CKD has become a major health problem due to its challenging detection at early stages when clear symptoms are yet to be presented. Thus, CKD is likely to be identified when the substantive conditions of the disease are manifest. In order to address the development of the disease and provide necessary treatments at the initial stage, the investigation of new biomarkers and metabolites associated with early detection of CKD are needed. Identified metabolites could be used to confirm the presence of the disease, obtain information on its mechanism and facilitate the development of novel pharmaceutical treatments. Such metabolites may be detected from biofluids and tissues using a range of analytical techniques. There are a number of metabolites that have been identified by mass spectrometry at high sensitivities, whilst the detection of metabolites directly from biofluids using NMR could present a more rapid way to expand our understanding of this disease. This review is focused on NMR-based metabolomics associated with CKD in humans and animals.

Identifiants

pubmed: 34312783
doi: 10.1007/s11010-021-04222-1
pii: 10.1007/s11010-021-04222-1
pmc: PMC8473349
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

4133-4137

Informations de copyright

© 2021. The Author(s).

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Auteurs

Elena Hunter (E)

Nottingham Trent University, Brackenhurst Lane, Southwell, NG25 0QF, UK.

Benita Percival (B)

Nottingham Trent University, Brackenhurst Lane, Southwell, NG25 0QF, UK.

Zeeshan Ahmad (Z)

De Montfort University, The Gateway, Leicester, LE1 9BH, UK.

Ming-Wei Chang (MW)

Nanotechnology and Integrated Bioengineering Centre, University of Ulster, Jordanstown Campus, Newtownabbey, Northern Ireland, UK.

John A Hunt (JA)

Nottingham Trent University, Brackenhurst Lane, Southwell, NG25 0QF, UK.

Séverine Tasker (S)

Friars Gate, Linnaeus Veterinary Limited, Solihull, B90 4BN, UK.

Luisa De Risio (L)

Nottingham Trent University, Brackenhurst Lane, Southwell, NG25 0QF, UK.
Friars Gate, Linnaeus Veterinary Limited, Solihull, B90 4BN, UK.

Philippe B Wilson (PB)

Nottingham Trent University, Brackenhurst Lane, Southwell, NG25 0QF, UK. philippe.wilson@ntu.ac.uk.

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Classifications MeSH