Correlations of blood and brain NMR metabolomics with Alzheimer’s disease mouse models

Abstract Alzheimer’s disease (AD) is a complex, progressive neurodegenerative disorder, impacting millions of geriatric patients globally. Unfortunately, AD can only be diagnosed post-mortem, through the analysis of autopsied brain tissue in human patients. This renders early detection and counterin...

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Main Authors: Franz Knörnschild, Ella J. Zhang, Rajshree Ghosh Biswas, Marta Kobus, Jiashang Chen, Jonathan X. Zhou, Angela Rao, Joseph Sun, Xiaoyu Wang, Wei Li, Isabella H. Muti, Piet Habbel, Johannes Nowak, Zhongcong Xie, Yiying Zhang, Leo L. Cheng
Format: Article
Language:English
Published: Nature Publishing Group 2025-03-01
Series:Translational Psychiatry
Online Access:https://doi.org/10.1038/s41398-025-03293-8
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Summary:Abstract Alzheimer’s disease (AD) is a complex, progressive neurodegenerative disorder, impacting millions of geriatric patients globally. Unfortunately, AD can only be diagnosed post-mortem, through the analysis of autopsied brain tissue in human patients. This renders early detection and countering disease progression difficult. As AD progresses, the metabolomic profile of the brain and other organs can change. These alterations can be detected in peripheral systems (i.e., blood) such that biomarkers of the disease can be identified and monitored with minimal invasion. In this work, High-Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) spectroscopy is used to correlate biochemical changes in mouse brain tissues, from the cortex and hippocampus, with blood plasma. Ten micrograms of each brain tissue and ten microliters of blood plasma were obtained from 5XFAD Tg AD mice models (n = 15, 8 female, 7 male) and female C57/BL6 wild-type mice (n = 8). Spectral regions-of-interest (ROI, n = 51) were identified, and 121 potential metabolites were assigned using the Human Metabolome Database and tabulated according to their trends (increase/decrease, false discovery rate significance). This work identified several metabolites that impact glucose oxidation (lactic acid, pyruvate, glucose-6-phosphate), allude to oxidative stress resulting in brain dysfunction (L-cysteine, galactitol, propionic acid), as well as those interacting with other neural pathways (taurine, dimethylamine). This work also suggests correlated metabolomic changes within blood plasma, proposing an avenue for biomarker detection, ideally leading to improved patient diagnosis and prognosis in the future.
ISSN:2158-3188