Alzheimer's disease (AD) is one of the greatest challenges facing our society. Finding a cure will almost certainly require gaining a better understanding of the biological mechanisms that cause AD and distinguishing their effects from aging and commonly comorbid non-AD pathologies. Furthermore, drug trials in AD can benefit from more powerful biomarkers, particularly biomarkers that can better identify individuals who have incipient preclinical AD pathology and are likely to progress to the active neurodegenerative phase of AD in a short timeframe, as well as biomarkers that can act as surrogate measures of outcome by measuring the effects of a drug on subtle changes in the brain's structural integrity. This project will address these challenges by focusing on the medial temporal lobe (MTL), the area of the brain where the earliest AD-related neuronal injury occurs. The project will use a combination of ex vivo and in vivo imaging, including ex vivo and in vivo imaging in the same subjects, to characterize the effects of AD and non-AD pathology on the MTL and to identify ?hot spots? in the MTL where changes observable on in vivo MRI are specific to AD pathology. Novel biomarkers of AD that leverage this information will be developed and evaluated using the recently funded Phase 3 of the Alzheimer's Disease Neuroimaging Initiative (ADNI3).
Aim 1 will image 80 intact MTL autopsy specimens using ultra high-resolution 9.4 Tesla MRI and serial histological imaging with immunohistochemical staining for tau, beta-amyloid, TDP43, and alpha-synuclein pathologies. Brains from these autopsies will also be assessed for evidence of cerebrovascular disease. Histology data will be co-registered to the MRI, and MRI of all specimens will be co-registered to a novel ex vivo MRI template. Statistical mapping in the template space will be used to describe spatial distributions of AD and non-AD pathologies, to characterize the morphological effects of these pathologies, and to identify regions of the MTL where changes in structural integrity (i.e., gray matter thickness) specifically correlate with AD pathology.
Aim 2 will extend prior work on automatic multi-atlas segmentation and quantification of MTL subregions in high-resolution T2-weighted in vivo MRI scans of the MTL with a novel atlas that combines ex vivo and in vivo imaging in the same subjects (n=40). This unique in vivo/ex vivo dataset will allow histological validation of MTL subregion segmentation protocols and algorithms, but will also serve as a conduit for mapping distributions of pathology and other rich information defined in the ex vivo template in Aim 1 into the space of in vivo imaging.
Aim 3 will develop in vivo imaging biomarkers based on the cross-sectional and longitudinal analysis of high-resolution T2-weighted in vivo MRI. These biomarkers will incorporate information on the patterns of AD and non-AD pathology in the MTL derived in Aim 1. The proposed biomarkers will be evaluated using high-resolution T2-weighted in vivo MRI in ADNI3 (which is being obtained from over 1000 ADNI3 participants) and compared to current state of the art MRI and PET-based AD biomarkers.
This project will provide new three-dimensional information about the extents of the damage to the brain in the earliest stages of Alzheimer's disease (AD), and how this damage is different from changes that happen with age and with other pathological conditions that are common in aging. This information will be used to develop new techniques for interpreting MRI scans of participants in clinical trials of disease-modifying therapies in early AD. If successful, the project will allow such clinical trials to recruit fewer subjects, track them for shorter periods of time, reducing their cost and therefore increasing the chance that a cure for AD can be found.
|Xie, Long; Das, Sandhitsu R; Wisse, Laura E M et al. (2018) Early Tau Burden Correlates with Higher Rate of Atrophy in Transentorhinal Cortex. J Alzheimers Dis 62:85-92|
|Adler, Daniel H; Wisse, Laura E M; Ittyerah, Ranjit et al. (2018) Characterizing the human hippocampus in aging and Alzheimer's disease using a computational atlas derived from ex vivo MRI and histology. Proc Natl Acad Sci U S A 115:4252-4257|
|Hadar, Peter N; Kini, Lohith G; Coto, Carlos et al. (2018) Clinical validation of automated hippocampal segmentation in temporal lobe epilepsy. Neuroimage Clin 20:1139-1147|
|Das, Sandhitsu R; Xie, Long; Wisse, Laura E M et al. (2018) Longitudinal and cross-sectional structural magnetic resonance imaging correlates of AV-1451 uptake. Neurobiol Aging 66:49-58|
|Wisse, L E M; Adler, D H; Ittyerah, R et al. (2017) Comparison of In Vivo and Ex Vivo MRI of the Human Hippocampal Formation in the Same Subjects. Cereb Cortex 27:5185-5196|
|Yushkevich, Paul A; Yang Gao; Gerig, Guido (2016) ITK-SNAP: An interactive tool for semi-automatic segmentation of multi-modality biomedical images. Conf Proc IEEE Eng Med Biol Soc 2016:3342-3345|