This grant application addresses a significant health problem - Alzheimer?s disease (AD) - that affects ~5.3 million people in the US and 20-30 million worldwide. As the population ages, these numbers are anticipated to rise, stimulating an intense search for disease prevention and treatment therapies as well as for biomarkers allowing early identification of AD. The latter is very important due to the existence of a long pre-symptomatic period that can be used for the initiation of prevention trials of disease-modifying therapies in asymptomatic individuals, with the goal of preventing cognitive decline as opposed to treating of symptoms that are already present. The main goal of this study is to provide a groundwork for using the innovative MRI-based Gradient Echo Plural Contrast Imaging (GEPCI) technique for in vivo identifying early pathological changes in the AD brain. This technique, GEPCI, developed in our laboratory, provides surrogates for quantitative assessments of changes in the brain tissue structure at the cellular level and has been already successfully applied to evaluating tissue damage in multiple sclerosis and some psychiatric diseases. Our preliminary data, obtained on well-characterized research participants recruited from studies of aging and dementia at the Washington University Knight Alzheimer?s Disease Research Center, allowed us to demonstrate for the first time that in vivo MRI-based measurements obtained on a clinical MRI scanner can provide information on brain amyloid-? accumulation in human participants, and to distinguish between healthy control, preclinical and mild AD stages. Based on these results, we plan to achieve the following Specific Aims: 1.
Our Aim 1 is to develop a readily available, non-invasive quantitative in vivo MRI-based biomarker that can serve as a surrogate for amyloid-? accumulation in the brain (a primary role of A? in the development of Alzheimer's disease is now almost universally accepted). 2.
Our Aim 2 is to establish specific quantitative and spatial patterns of GEPCI metrics abnormalities that would distinguish between normal brain, preclinical AD, and very mild AD. 3.
Our Aim 3 is to establish the effect of early AD-related brain tissue damage (defined by GEPCI surrogate biomarkers) on cognitive performance and to test the hypothesis that the GEPCI metrics and/or changes in GEPCI metrics can be predictors of the disease progression. 4.
Our Aim 4 is to validate GEPCI measurements against direct neuropathology. The overarching goal of this proposal is to establish GEPCI as an in vivo non-invasive MRI technique available in a conventional clinical setting for screening population for preclinical AD pathology and clinical drug trials. GEPCI data are quantitative, reproducible and MRI scanner independent, thus allowing multi-center applications. The non-invasive nature of our approach is especially important since most of currently available biomarkers for identifying AD ?are invasive, to one degree or another (NIH PAR-15-359)?.
The objective of this proposal is to use an innovative Gradient Echo Plural Contrast Imaging technique invented in PI laboratory, for developing a widely accessible method for diagnosis of Alzheimer?s disease (AD) ? one of the major health problem in US and worldwide. As our approach is based on Magnetic Resonance Imaging that is widely available in the US and most foreign countries, is non-invasive, and does not require radiation exposure, it would open broad opportunities for screening populations for early signs of AD pathology when drug intervention can be most efficient, and provide a means of monitoring therapeutic efficacy in clinical drug trials.
|Wen, Jie; Goyal, Manu S; Astafiev, Serguei V et al. (2018) Genetically defined cellular correlates of the baseline brain MRI signal. Proc Natl Acad Sci U S A 115:E9727-E9736|
|Yablonskiy, Dmitriy A; Sukstanskii, Alexander L (2018) Lorentzian effects in magnetic susceptibility mapping of anisotropic biological tissues. J Magn Reson 292:129-136|
|Zhao, Yue; Raichle, Marcus E; Wen, Jie et al. (2017) In vivo detection of microstructural correlates of brain pathology in preclinical and early Alzheimer Disease with magnetic resonance imaging. Neuroimage 148:296-304|