R01AG077380
Project Grant
Overview
Grant Description
Digital Markers of Mobility in Daily Life to Track Progression in Newly Diagnosed Parkinson's Disease - Project Summary/Abstract
A critical limitation in the development of disease-modifying interventions for Parkinson's Disease (PD) and other neurodegenerative diseases is the lack of reliable, objective measures of disease progression. Walking and turning dysfunction appear early in Parkinson's Disease, and the use of inertial sensors to measure walking and turning may provide sensitive, objective markers of disease progression as well as decline in quality of life.
New wearable technology can provide reliable, objective measures of walking and turning that are feasible for clinical trials. However, quantifying walking and turning during unsupervised, daily life has the untapped potential to provide objective measures that are even more sensitive to disease progression, quality of life, and fall risk than current subjective clinical measures of mobility.
We predict that turning quality may be even more sensitive to the progression of disease in early PD than straight walking because of the added dynamic balance challenges.
Aim I: We will determine the most sensitive measures of mobility (daily life) in 100 people with early, untreated PD and 50 older control subjects. We hypothesize that unsupervised daily life mobility measures will be sensitive and specific for early PD.
Aim II: We will determine the measures of mobility in daily life most sensitive to disease progression. We hypothesize that turning characteristics during daily life, particularly variability of performance, will be the most sensitive mobility measures to change over 3 years in recently diagnosed people with PD.
Aim III: We will predict future falls based on daily life objective measures of walking and turning. We hypothesize that objective measures of daily life gait and turning quality will significantly improve the prediction of who will fall and time-to-first-fall compared to clinical measures (i.e., fall risk).
Identification of the most sensitive set of measures of mobility disability progression during real-life activities with wearable technology will provide quantifiable and objective outcome measures for testing the effectiveness of new disease-modifying therapies. Improved prognosis of mobility decline will also improve the timing of clinical interventions.
A critical limitation in the development of disease-modifying interventions for Parkinson's Disease (PD) and other neurodegenerative diseases is the lack of reliable, objective measures of disease progression. Walking and turning dysfunction appear early in Parkinson's Disease, and the use of inertial sensors to measure walking and turning may provide sensitive, objective markers of disease progression as well as decline in quality of life.
New wearable technology can provide reliable, objective measures of walking and turning that are feasible for clinical trials. However, quantifying walking and turning during unsupervised, daily life has the untapped potential to provide objective measures that are even more sensitive to disease progression, quality of life, and fall risk than current subjective clinical measures of mobility.
We predict that turning quality may be even more sensitive to the progression of disease in early PD than straight walking because of the added dynamic balance challenges.
Aim I: We will determine the most sensitive measures of mobility (daily life) in 100 people with early, untreated PD and 50 older control subjects. We hypothesize that unsupervised daily life mobility measures will be sensitive and specific for early PD.
Aim II: We will determine the measures of mobility in daily life most sensitive to disease progression. We hypothesize that turning characteristics during daily life, particularly variability of performance, will be the most sensitive mobility measures to change over 3 years in recently diagnosed people with PD.
Aim III: We will predict future falls based on daily life objective measures of walking and turning. We hypothesize that objective measures of daily life gait and turning quality will significantly improve the prediction of who will fall and time-to-first-fall compared to clinical measures (i.e., fall risk).
Identification of the most sensitive set of measures of mobility disability progression during real-life activities with wearable technology will provide quantifiable and objective outcome measures for testing the effectiveness of new disease-modifying therapies. Improved prognosis of mobility decline will also improve the timing of clinical interventions.
Funding Goals
NOT APPLICABLE
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Portland,
Oregon
972393011
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 383% from $622,056 to $3,003,314.
Oregon Health & Science University was awarded
Parkinson's Disease Progression Tracking with Wearable Technology
Project Grant R01AG077380
worth $3,003,314
from National Institute on Aging in September 2022 with work to be completed primarily in Portland Oregon United States.
The grant
has a duration of 4 years 8 months and
was awarded through assistance program 93.866 Aging Research.
The Project Grant was awarded through grant opportunity NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 6/5/26
Period of Performance
9/30/22
Start Date
5/31/27
End Date
Funding Split
$3.0M
Federal Obligation
$0.0
Non-Federal Obligation
$3.0M
Total Obligated
Activity Timeline
Transaction History
Modifications to R01AG077380
Additional Detail
Award ID FAIN
R01AG077380
SAI Number
R01AG077380-3782638655
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
75NN00 NIH National Insitute on Aging
Funding Office
75NN00 NIH National Insitute on Aging
Awardee UEI
NPSNT86JKN51
Awardee CAGE
0YUJ3
Performance District
OR-01
Senators
Jeff Merkley
Ron Wyden
Ron Wyden
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| National Institute on Aging, National Institutes of Health, Health and Human Services (075-0843) | Health research and training | Grants, subsidies, and contributions (41.0) | $1,240,648 | 100% |
Modified: 6/5/26