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

Authors

  • Arefi Oskouie, Afsaneh Faculty of Paramedical Sciences, Department of Basic Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  • Eslami, Maryam Dept. of Physiology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
  • farrokhi Yekta, Reyhaneh Faculty of Paramedical Sciences, Department of Basic Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran-Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  • Goshadrou, Fatemeh Faculty of Paramedical Sciences, Department of Basic Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Abstract:

Introduction: The high prevalence of Alzheimerchr('39')s disease (AD) in todaychr('39')s 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 Alzheimerchr('39')s 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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Journal title

volume 23  issue 1

pages  105- 116

publication date 2021-01

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