Survey of potential diagnostic metabolite markers in serum of the rat model of Alzheimer’s disease using nuclear magnatic resonance (1H-NMR) technique

authors:

avatar F fgoshadrou@yahoo.com , avatar Reyhaneh Farrokhi-Yekta , avatar Afsaneh ArefiOskouie , * , avatar Maryam Eslami

Koomesh: Vol.23, issue 1; 105-116
published online: March 06, 2021
article type: issue_documents_importer
received: September 01, 2019
accepted: July 06, 2020

how to cite: fgoshadrou@yahoo.com F, Farrokhi-Yekta R, ArefiOskouie A, Eslami M. Survey of potential diagnostic metabolite markers in serum of the rat model of Alzheimer’s disease using nuclear magnatic resonance (1H-NMR) technique. koomesh. 2021;23(1):e153245. 

Abstract

Introduction: The high prevalence of Alzheimer;#39s disease (AD) in today;#39s societies indicates an urgent need for the development of methods that will help the early diagnosis of the disease. In this study, using proton nuclear magnetic resonance spectrometry (1H-NMR) metabolomics, identification of altered and distinct metabolites in serum of the rat model of AD was performed compared with healthy controls with the aim of introducing potential markers and to further understand the mechanisms of the AD. Materials and Methods: Serum samples from 25 adult male rats (10 healthy and 15 AD) were collected and their metabolites were extracted and analyzed using 1H-NMR technique. Differential metabolite profile was then determined by multivariate statistical analysis. The behavioral screening of the model rats was performed by the paired-associated learning method. Results: The results of the behavioral study showed the impairment of memory abilities in AD rats. Differential metabolites between the two groups were identified by multivariate analysis methods such as OPLS and Random Forest. Importantly, the results showed that there were differences in the pathways related to energy and amino acid metabolism between the control group and the Alzheimer;#39s model. Conclusion: This research opens new horizons to identify biomarkers and physiological pathways involved in Alzheimer’s disease. The introduced metabolites must be confirmed by further studies and might be used as candidate biomarkers for early detection of the disease.  

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