Literature DB >> 33259618

Use of plasma-free amino acids as biomarkers for detecting and predicting disease risk.

Kenji Nagao1, Takeshi Kimura2.   

Abstract

This paper reviews developments regarding the use of plasma-free amino acid (PFAA) profiles as biomarkers for detecting and predicting disease risk. This work was initiated and first published in 2006 and was subsequently developed by Ajinomoto Co., Inc. After commercialization in 2011, PFAA-based tests were adopted in over 1500 clinics and hospitals in Japan, and numerous clinician-led studies have been performed to validate these tests. Evidence is accumulating that PFAA profiles can be used for diabetes prediction and evaluation of frailty; in particular, decreased plasma essential amino acids could contribute to the pathophysiology of severe frailty. Integration of PFAA evaluation as a biomarker and effective essential amino acid supplementation, which improves physical and mental functions in the elderly, could facilitate the development of precision nutrition, including personalized solutions. This present review provides the background for the technology as well as more recent clinical findings, and offers future possibilities regarding the implementation of precision nutrition.
© The Author(s) 2020. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  biomarkers; cancer; early detection; frailty; personalized solution; precision nutrition; type II diabetes

Mesh:

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Year:  2020        PMID: 33259618     DOI: 10.1093/nutrit/nuaa086

Source DB:  PubMed          Journal:  Nutr Rev        ISSN: 0029-6643            Impact factor:   7.110


  2 in total

1.  Assessment of Blood Plasma Free-amino Acid Levels in Infertile Men.

Authors:  Takayuki Sugiyama; Hiroshi Terada; Hideaki Miyake
Journal:  In Vivo       Date:  2021 May-Jun       Impact factor: 2.155

2.  Targeted metabolomics analysis of amino acids and acylcarnitines as risk markers for diabetes by LC-MS/MS technique.

Authors:  Shaghayegh Hosseinkhani; Babak Arjmand; Arezou Dilmaghani-Marand; Sahar Mohammadi Fateh; Hojat Dehghanbanadaki; Niloufar Najjar; Sepideh Alavi-Moghadam; Robabeh Ghodssi-Ghassemabadi; Ensieh Nasli-Esfahani; Farshad Farzadfar; Bagher Larijani; Farideh Razi
Journal:  Sci Rep       Date:  2022-05-19       Impact factor: 4.996

  2 in total

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