Alzheimer's disease (AD) is a leading cause of disability and death in the US and a major global public health problem. Time is running short if we wish to avert a global public health disaster with untold suffering, disruption of families, and severe challenges to health care systems and economies. Solutions will come only from innovative research. Genomic studies for late-onset AD (LOAD) have identified over 20 risk loci; however, translating the relevant molecules identified by genomics to AD-specific mechanistic pathways has been challenging. Our application, entitled ?The Phenotypic Landscape of Cognitive Decline Revealed by Next- Generation Multiplexed Ion Beam Imaging,? is highly responsive to this urgent scientific need by proposing a uniquely innovative molecular imaging platform called multiplexed ion beam imaging (MIBI) that will determine high dimensional protein interactions for AD-relevant molecules identified by genomics studies in normal and pathological states. Our proposal has three Specific Aims.
In Aim 1, we propose to analyze four regions in healthy aged brains: two sectors of the hippocampal pyramidal layer and from two isocortical regions. Next- generation MIBI instrumentation will be used to image simultaneously 30+ proteins that mark subtypes of neurons, synapses, and non-neuronal cells, while covering regulatory signaling, neuro-inflammatory components, and AD risk gene protein products with subcellular resolution.
In Aim 2, we propose to use the same multiplexed imaging methods in AD brain stratified by APOE genotype. We will analyze these data with statistical machine learning methods already established in our laboratory, similar to what we have done previously with different cancers and the immune system.
In Aim 3, using infrastructure we have already have established, we will create a web-based portal where all of the images from this study can be accessed, multi- color overlays generated ad hoc, and all the features we derive shared freely. We propose a transformative, collaborative approach to AD that leverages a long-standing NIA-funded longitudinal cohort and is highly responsive to the National Alzheimer's Plan. These novel insights will illuminate pathways that hold potential for new therapeutic targets and will create a shared research resource and analysis platform for the community of scientists committed to developing solutions for AD.

Public Health Relevance

AD is an age- and neurodegenerative related disease estimated to affect five million or more of the ageing American population by 2050. There is thus an urgent need to identify unique predictive signatures that correlate with developing AD. The overarching goal of this proposal is to generate a phenotypic landscape of cognitive decline, to understand modulation of cognitive decline during compensation and relate genetic predisposition to changes in phenotypic landscape defined by muti-parametric measurements using enabling technologies like multiplexed ion beam imaging (MIBI).

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
1R01AG056287-01
Application #
9360517
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Yang, Austin Jyan-Yu
Project Start
2017-08-01
Project End
2022-04-30
Budget Start
2017-08-01
Budget End
2018-04-30
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Stanford University
Department
Pathology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Hartmann, Felix J; Simonds, Erin F; Bendall, Sean C (2018) A Universal Live Cell Barcoding-Platform for Multiplexed Human Single Cell Analysis. Sci Rep 8:10770
Keren, Leeat; Bosse, Marc; Marquez, Diana et al. (2018) A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging. Cell 174:1373-1387.e19