Alzheimer?s disease (AD) is an irreversible neurodegenerative disease with its underlying cause poorly under- stood. Although many research have been conducted to understand its pathological origin using advanced imaging technologies, current discoveries have mainly stemmed from studies on microscopic systems with lim- ited number of cells. While increasingly many evidences have indicated that the interaction among various groups of cells across the entire nervous system holds the key to those unanswered questions in AD, large- scale volumetric investigation are limited by current imaging technologies. First, microscale methods used in conventional histopathology, such as electron or light microscopy, require extensive tissue sectioning for thick samples, leading to prolonged imaging time and the di?culty of 3D reconstruction from 2D images due to tissue deformation. On the other end, insu?cient spatial resolution and limited molecular speci?city of macroscale approaches, such as MR/PET/CT, have made them less attractive for pathological studies. Thus, the goal of this project is to develop an optical imaging method that not only provides high resolution and molecular contrast suitable for the pathology of the nervous systems in AD mouse models, but also o?ers en- abling high-throughput for those large-scale investigations demanded by many of today?s AD research. This proposal plans to address the above imaging needs by creating coherent optical imaging apparatus to pro- vide the enabling high-throughput and high resolution, by developing new tissue processing methods to o?er the molecular contrast in intact tissues, by building computational tools to assist the biological interpretation of imaging results. The outcome of the proposed research is expected to be a set of new research tools that facilitate large-cohort studies on AD mouse models with brain-wide big-data acquisition and analysis. This mentored project is aimed to facilitate the PI (Dr. Jian Ren) to achieve his goal of obtaining research inde- pendence. Through the proposed research, the PI will obtain complementary expertise from his mentors, a team of leading scientists including Dr. Brett Bouma (optical imaging), Dr. Bradley Hyman (neurology and AD), Dr. Sangeeta Bhatia (nanomedicine and tissue engineering), Dr. Tayyaba Hasan (photodynamic ther- apy), Dr. Edward Boyden (neuroscience and optogenetics), and Dr. Bruce Fischl (computational neuroimag- ing and MRI). This combined technical strength will be integrated with training on career development skill, facilitating the transition of the PI to an independent investigator in the biomedical ?eld. The PI will con- duct this project mainly in the Wellman Center for Photomedicine at Massachusetts General Hospital, which is surrounded by several world-renowned universities and research institutions in both life and physical sci- ences. Leveraging the support from the PI?s mentors, he will have access to numerous research facilities at the greater community of Harvard and MIT. Enjoying this highly multidisciplinary and collaborative research environment, Dr. Jian Ren will undertake this mentored research and transition to his research independence.

Public Health Relevance

Alzheimer?s disease (AD) is an incurable neurodegenerative disease that progressively destroys patients? cogni- tive functions causing enormous social and economical impact. With its underlying cause poorly understood, new imaging technologies are in demand to provide more comprehensive etiological investigation of AD over large-scale complex nervous systems, such as whole brains. In this proposal, to address this unmet need, we are to develop advanced optical imaging tools that can enable 3D brain-wide visualization of AD pathology.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Career Transition Award (K99)
Project #
1K99AG059946-01
Application #
9583756
Study Section
Neuroscience of Aging Review Committee (NIA)
Program Officer
Wise, Bradley C
Project Start
2019-07-15
Project End
2021-06-30
Budget Start
2019-07-15
Budget End
2020-06-30
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114