An important challenge in drug development for Alzheimer's Disease (AD), as well as many other neurological diseases, is the accurate pre-clinical predictability of the future clinical efficacy and side effects of the compound. The complexity of the neurological system makes it extremely difficult to infer impact of the candidate compound using surrogate in vitro information, ex vivo data, or simple animal behavior models. Our proposal aims to fundamentally transform this process through accurate disease circuit characterization along with in vivo full brain quantification of the drug administration impact longitudinally over time in the same animals utilizing the optogenetic functional magnetic resonance imaging (ofMRI) technology. ofMRI is a novel technology combining cell type specific, temporally precise optogenetic control with fMRI readouts. The first proof of concept study published by the PI demonstrated ofMRI technology's ability to accurately visualize brain-wide neural activity resulting from cell types specified by its genetic identity, cell body location, and axonal projection target. With further developments in ofMRI technology to achieve high-throughput, high spatial resolution, and awake scanning, the PI's lab has preliminary data showing the ability to characterize whole brain network response specifically associated with basal forebrain cholinergic neurons. Selective stimulation of cholinergic neurons in the basal forebrain with defined temporal patterns was shown to elicit widespread neural activity including the hippocampus and neocortex. Such direct functional visualization of the network activity with the ability to longitudinally track in vivo can be used o characterize the disease progress, actively identify novel target circuits, and also monitor how different doses and course of treatment impacts each individual animal over time with disease progress. This is in contrast with conventional ex vivo technology that relies on sacrificing a large number of animals at different time points, which increases variance, cost, and time while only obtaining passive, surrogate markers of function or difficult to reproduce behavioral tests. I this proposal, we will quantify network function across normal, and mutant APP mice to quantify network function changes associated with cholinergic neurons of the basal forebrain. With these quantifications, we aim to establish this approach as a new platform for quantitative drug design and evaluation. With the ability to observe network engagement associated with key neural circuit elements implicated in AD, we will identify the AD circuit mechanism and also test a candidate drug that has already shown good electrophysiological, behavioral, and anatomical efficacy.
We aim to demonstrate ofMRI-based observation of therapeutic effects. The prevention and/or reversal of AD-related circuit impairment could be fully or partially effective and we will e able to directly observe locations of the changes associated with specific neuronal populations in live animal brains during disease progression and drug therapy. Resting state fMRI studies will also be conducted in parallel to increase translational potential into clinical settings.

Public Health Relevance

One of the main challenges in drug development for Alzheimer's disease is the difficulty in accurate prediction of the efficacy and side effects of drg candidates before risky and costly human clinical trials. The complexity of the brain makes it extremely difficult to evaluate candidate compounds using traditional methodologies such as cell-based and simple animal behavior models. Our proposal aims to fundamentally transform this process by revealing the specific activity of relevant neuronal circuits during disease progression and drug administration in living subjects.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Multi-Year Funded Research Project Grant (RF1)
Project #
1RF1AG047666-01
Application #
8712022
Study Section
Special Emphasis Panel (ZAG1)
Program Officer
Refolo, Lorenzo
Project Start
2014-07-15
Project End
2019-06-30
Budget Start
2014-07-15
Budget End
2019-06-30
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Stanford University
Department
Neurology
Type
Schools of Medicine
DUNS #
City
Stanford
State
CA
Country
United States
Zip Code
94304
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