Alzheimer's disease (AD) is involved in many biological and pathological processes. Neurochemical processes and changes causing the development of AD are of great interests for understanding the biology of AD and developing diagnosis and treatment monitoring. Currently AD diagnosis is mainly based on neuropsychological tests. One improvement that can be made is to use modern imaging technologies to look for the disease specific biomarkers. Nuclear magnetic resonance spectroscopy (NMR or MRS) is one of such techniques that can measure metabolites in the normal or disease affected brains. Therefore it has potential to reveal the neurochemical changes in AD. However, most of earlier studies suffered technological obstacles and provided limited metabolic information in AD. High resolution magic angle spinning (HRMAS) solid state NMR has been developed and tested in the investigation of metabolic changes in several brain diseases. This new method uses very small amount of intact tissue samples without destructive sample preparations, but offers the great resolution and quantitative data, extending our ability to discover AD metabolite markers. We believe that abnormal metabolic and neurochemical processes are closely related to the development and progression of AD. HRMAS NMR analysis of AD brains ex vivo may offer the great resolution and a quantitative approach to study underlying association of abnormal neurochemical processes associated to AD and to discover AD specific metabolite markers and profiles, which can be further tested in clinical AD imaging using in vivo MRS. We propose to develop a NMR/MRS based metabolomics approach that applies solid state HRMAS NMR to analysis of the control and AD brain tissue samples available at the Tissue Bank of Emory Alzheimer's Disease Research Center (ADRC) to identify potential AD specific metabolite profile and metabolite markers. Outcomes of ex vivo NMR analysis are MRS measurable AD specific metabolite profiles and markers which can be tested in patients using in vivo MRS in the sample volume selected from abnormal regions appeared in 18F-D-glucose (FDG) positron emission tomography (PET) image and high resolution structural MRI.
The Specific Aims of this project are following: 1. To obtain the metabolite profiles of control and AD brain tissues using HRMAS NMR followed by characterizing and quantifying metabolite for investigation of differences of metabolite profiles from the postmortem control and AD brains and from the different cortical areas of AD brains;2. To analyze neurochemical changes of AD brain by comparing the metabolite profiles of control and AD brains and to examine their correlation to immunohistochemical analysis and to determine the AD specific metabolic profile and potential NMR detectable AD metabolite markers using a statistical predictive model;3. To test whether AD specific metabolite profiles obtained from HRAMS NMR can be also found in controls and AD patients using sample regions determined by abnormal regions found in PET and MRI.
Nuclear magnetic resonance spectroscopy (NMR or MRS) is an analytical method that can characterize and measure chemicals, or metabolites, in the normal or disease affected brains and identify disease specific biomarkers. We propose to develop an NMR-MRS based metabolomics approach that applies High Resolution Magic Spin Angle (HRMAS) solid state NMR to analyze Alzheimer's disease (AD) brain tissue samples to identify AD specific metabolic markers, then to test those in AD patients using in vivo MRS. AD is a disease involved in many biological and pathological processes. Neurochemical processes and changes causing the development of amyloid plaques and AD are of great interests for understanding the biology of AD and its diagnosis and treatment. Combining the abilities of high resolution and quantitative analysis of biological samples ex vivo and imaging-guided non-invasive examination of live animals and human in vivo, this project is aimed to deliver a translational and clinical applicable metabolomics approach for improving the diagnosis and clinical management of AD.
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