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Yu FF, Rathnakar J, Ryder B, Hitt B, Kashmer OM, Sherry AD, Vinogradov E. Differentiation and characterization of healthy versus pathological tau using chemical exchange saturation transfer. NMR Biomed 2024:e5160. [PMID: 38646677 DOI: 10.1002/nbm.5160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 02/29/2024] [Accepted: 03/17/2024] [Indexed: 04/23/2024]
Abstract
Neurofibrillary tangles of tau constitute one of the key biological hallmarks of Alzheimer's disease. Currently, the assessment of regional tau accumulation requires intravenous administration of radioactive tracers for PET imaging. A noninvasive MRI-based solution would have significant clinical implications. Herein, we utilized an MRI technique known as chemical exchange saturation transfer (CEST) to determine the imaging signature of tau in both its monomeric and pathologic fibrillated conformations. Three sets of purified recombinant full-length (4R) tau protein were prepared for collection of CEST spectra using a 9.4 T NMR spectrometer at varying temperatures (25, 37, and 42 °C) and RF intensities (0.7, 1.0, 1.5, and 2.2 μT). Monomeric and fibrillated tau were readily distinguished based on their Z-spectrum profiles. Fibrillated tau demonstrated a less prominent peak at 3.5 ppm with additional peaks near 0.5 and 1.5 ppm. No significant differences were identified between fibrillated tau prepared using heparin versus seed-competent tau. In conclusion, monomeric and fibrillated tau can be readily detected and distinguished based on their CEST-derived Z-spectra, pointing to the potential utility of CEST-MRI as a noninvasive biomarker of regional pathologic tau accumulation in the brain. Further testing and validation in vitro and in vivo will be necessary before this can be applied clinically.
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Affiliation(s)
- Fang Frank Yu
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - James Rathnakar
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Bryan Ryder
- Center for Alzheimer's and Neurodegenerative Diseases, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Brian Hitt
- Center for Alzheimer's and Neurodegenerative Diseases, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Neurology, UCI Medical Center, Orange, California, USA
| | - Omar M Kashmer
- Center for Alzheimer's and Neurodegenerative Diseases, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - A Dean Sherry
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Department of Chemistry & Biochemistry, University of Texas at Dallas, Dallas, Texas, USA
| | - Elena Vinogradov
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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Swain A, Soni ND, Wilson N, Juul H, Benyard B, Haris M, Kumar D, Nanga RPR, Detre J, Lee VM, Reddy R. Early-stage mapping of macromolecular content in APP NL-F mouse model of Alzheimer's disease using nuclear Overhauser effect MRI. Front Aging Neurosci 2023; 15:1266859. [PMID: 37876875 PMCID: PMC10590923 DOI: 10.3389/fnagi.2023.1266859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 09/15/2023] [Indexed: 10/26/2023] Open
Abstract
Non-invasive methods of detecting early-stage Alzheimer's disease (AD) can provide valuable insight into disease pathology, improving the diagnosis and treatment of AD. Nuclear Overhauser enhancement (NOE) MRI is a technique that provides image contrast sensitive to lipid and protein content in the brain. These macromolecules have been shown to be altered in Alzheimer's pathology, with early disruptions in cell membrane integrity and signaling pathways leading to the buildup of amyloid-beta plaques and neurofibrillary tangles. We used template-based analyzes of NOE MRI data and the characteristic Z-spectrum, with parameters optimized for increase specificity to NOE, to detect changes in lipids and proteins in an AD mouse model that recapitulates features of human AD. We find changes in NOE contrast in the hippocampus, hypothalamus, entorhinal cortex, and fimbria, with these changes likely attributed to disruptions in the phospholipid bilayer of cell membranes in both gray and white matter regions. This study suggests that NOE MRI may be a useful tool for monitoring early-stage changes in lipid-mediated metabolism in AD and other disorders with high spatial resolution.
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Affiliation(s)
- Anshuman Swain
- School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Narayan D. Soni
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Neil Wilson
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Halvor Juul
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Blake Benyard
- School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Mohammad Haris
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Dushyant Kumar
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Ravi Prakash Reddy Nanga
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - John Detre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Center for Functional Neuroimaging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Virginia M. Lee
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Alzheimer’s Disease Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Ravinder Reddy
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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