R01HL164380
Project Grant
Overview
Grant Description
Risk stratification for COPD exacerbations with CT analysis and multidimensional trajectory subtyping - project summary.
The natural disease course of chronic obstructive pulmonary disease (COPD) is punctuated by events, termed exacerbations, when symptoms are acutely worse. Exacerbations are costly and burdensome – they are associated with accelerated lung function decline, impaired health status, increased hospitalization, and increased mortality.
Evidence suggests that some individuals are particularly susceptible to exacerbations, but heterogeneity remains poorly understood. There is thus an urgent need to better delineate COPD heterogeneity and improve identification of groups at risk for these adverse outcomes as early as possible.
Our long-term goal is to use quantitative imaging and trajectory-based subtype analysis to delineate COPD subpopulations, enabling early identification of subpopulations at risk for adverse, long-term outcomes. We have developed CT biomarkers of pulmonary vascular pruning, cardiac morphology, emphysema subtypes, airway thickening, and skeletal muscle wasting in CT imaging. However, we have not performed an integrative analysis of these biomarkers that could better delineate homogeneous subgroups.
We have also developed a Bayesian trajectory algorithm that incorporates longitudinal data to identify distinct population subgroups with similar biomarker patterns while accounting for factors such as age and smoke exposure.
Our overall objective in this proposal is to use multidimensional trajectory analysis to evaluate novel CT biomarkers in terms of exacerbation risk-stratification. Our central hypothesis is that multidimensional trajectory analysis of pulmonary and extra-pulmonary CT biomarkers can identify subgroups with latent susceptibility to exacerbations.
The rationale for this work is that by identifying distinct trajectory subgroups using multiple CT biomarkers, we will better delineate COPD heterogeneity, leading to earlier, more precise risk-stratification – especially amongst those patients for whom CT imaging is the most reliably available data source, such as those who have undergone lung cancer CT screening.
Aim 1 focuses on the methodical assessment of our novel CT biomarkers in terms of COPD exacerbation risk stratification using trajectory analysis. Aim 2 focuses on using CT biomarkers and trajectory analysis to identify subgroups within a lung cancer screening cohort that are at risk for hospitalizations due to COPD exacerbations.
The approach is innovative, in our opinion, because it shifts focus from disease staging to identifying mechanistically similar subgroups (endotypes). The significance of these contributions will be an improved understanding of CT-assessed patterns of abnormality in cardio-pulmonary and extra-pulmonary systems and how these patterns present in trajectory subgroups at risk for adverse events.
In turn, we expect this to better enable detection of early disease manifestations and subtype characterization. We expect these contributions to enable further studies of the mechanistic differences between subgroups as well approaches to preempt costly acute events by identifying the early-stage manifestations of at-risk groups.
The natural disease course of chronic obstructive pulmonary disease (COPD) is punctuated by events, termed exacerbations, when symptoms are acutely worse. Exacerbations are costly and burdensome – they are associated with accelerated lung function decline, impaired health status, increased hospitalization, and increased mortality.
Evidence suggests that some individuals are particularly susceptible to exacerbations, but heterogeneity remains poorly understood. There is thus an urgent need to better delineate COPD heterogeneity and improve identification of groups at risk for these adverse outcomes as early as possible.
Our long-term goal is to use quantitative imaging and trajectory-based subtype analysis to delineate COPD subpopulations, enabling early identification of subpopulations at risk for adverse, long-term outcomes. We have developed CT biomarkers of pulmonary vascular pruning, cardiac morphology, emphysema subtypes, airway thickening, and skeletal muscle wasting in CT imaging. However, we have not performed an integrative analysis of these biomarkers that could better delineate homogeneous subgroups.
We have also developed a Bayesian trajectory algorithm that incorporates longitudinal data to identify distinct population subgroups with similar biomarker patterns while accounting for factors such as age and smoke exposure.
Our overall objective in this proposal is to use multidimensional trajectory analysis to evaluate novel CT biomarkers in terms of exacerbation risk-stratification. Our central hypothesis is that multidimensional trajectory analysis of pulmonary and extra-pulmonary CT biomarkers can identify subgroups with latent susceptibility to exacerbations.
The rationale for this work is that by identifying distinct trajectory subgroups using multiple CT biomarkers, we will better delineate COPD heterogeneity, leading to earlier, more precise risk-stratification – especially amongst those patients for whom CT imaging is the most reliably available data source, such as those who have undergone lung cancer CT screening.
Aim 1 focuses on the methodical assessment of our novel CT biomarkers in terms of COPD exacerbation risk stratification using trajectory analysis. Aim 2 focuses on using CT biomarkers and trajectory analysis to identify subgroups within a lung cancer screening cohort that are at risk for hospitalizations due to COPD exacerbations.
The approach is innovative, in our opinion, because it shifts focus from disease staging to identifying mechanistically similar subgroups (endotypes). The significance of these contributions will be an improved understanding of CT-assessed patterns of abnormality in cardio-pulmonary and extra-pulmonary systems and how these patterns present in trajectory subgroups at risk for adverse events.
In turn, we expect this to better enable detection of early disease manifestations and subtype characterization. We expect these contributions to enable further studies of the mechanistic differences between subgroups as well approaches to preempt costly acute events by identifying the early-stage manifestations of at-risk groups.
Awardee
Funding Goals
THE NATIONAL HEART, LUNG, AND BLOOD INSTITUTE (NHLBI) PROVIDES GLOBAL LEADERSHIP FOR A RESEARCH, TRAINING, AND EDUCATION PROGRAM TO PROMOTE THE PREVENTION AND TREATMENT OF HEART, LUNG, AND BLOOD DISEASES AND ENHANCE THE HEALTH OF ALL INDIVIDUALS SO THAT THEY CAN LIVE LONGER AND MORE FULFILLING LIVES. THE DIVISION OF LUNG DISEASES SUPPORTS RESEARCH AND RESEARCH TRAINING ON THE CAUSES, DIAGNOSIS, PREVENTION, AND TREATMENT OF LUNG DISEASES AND SLEEP DISORDERS. RESEARCH IS FUNDED THROUGH INVESTIGATOR-INITIATED AND INSTITUTE-INITIATED GRANT PROGRAMS AND THROUGH CONTRACT PROGRAMS IN AREAS INCLUDING ASTHMA, BRONCHOPULMONARY DYSPLASIA, CHRONIC OBSTRUCTIVE PULMONARY DISEASE, CYSTIC FIBROSIS, RESPIRATORY NEUROBIOLOGY, SLEEP AND CIRCADIAN BIOLOGY, SLEEP-DISORDERED BREATHING, CRITICAL CARE AND ACUTE LUNG INJURY, DEVELOPMENTAL BIOLOGY AND PEDIATRIC PULMONARY DISEASES, IMMUNOLOGIC AND FIBROTIC PULMONARY DISEASE, RARE LUNG DISORDERS, PULMONARY VASCULAR DISEASE, AND PULMONARY COMPLICATIONS OF AIDS AND TUBERCULOSIS. THE DIVISION IS RESPONSIBLE FOR MONITORING THE LATEST RESEARCH DEVELOPMENTS IN THE EXTRAMURAL SCIENTIFIC COMMUNITY AS WELL AS IDENTIFYING RESEARCH GAPS AND NEEDS, OBTAINING ADVICE FROM EXPERTS IN THE FIELD, AND IMPLEMENTING PROGRAMS TO ADDRESS NEW OPPORTUNITIES. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO STIMULATE TECHNOLOGICAL INNOVATION; USE SMALL BUSINESS TO MEET FEDERAL RESEARCH AND DEVELOPMENT NEEDS; FOSTER AND ENCOURAGE PARTICIPATION IN INNOVATION AND ENTREPRENEURSHIP BY SOCIALLY AND ECONOMICALLY DISADVANTAGED PERSONS; AND INCREASE PRIVATE-SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT FUNDING. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE TECHNOLOGICAL INNOVATION; FOSTER TECHNOLOGY TRANSFER THROUGH COOPERATIVE R&D BETWEEN SMALL BUSINESSES AND RESEARCH INSTITUTIONS, AND INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL R&D.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Boston,
Massachusetts
021156110
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 293% from $826,313 to $3,244,620.
Brigham & Womens Hospital was awarded
CT Analysis for COPD Exacerbation Risk Stratification
Project Grant R01HL164380
worth $3,244,620
from National Heart Lung and Blood Institute in April 2023 with work to be completed primarily in Boston Massachusetts United States.
The grant
has a duration of 4 years 10 months and
was awarded through assistance program 93.837 Cardiovascular Diseases Research.
The Project Grant was awarded through grant opportunity NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 4/6/26
Period of Performance
4/15/23
Start Date
2/29/28
End Date
Funding Split
$3.2M
Federal Obligation
$0.0
Non-Federal Obligation
$3.2M
Total Obligated
Activity Timeline
Transaction History
Modifications to R01HL164380
Additional Detail
Award ID FAIN
R01HL164380
SAI Number
R01HL164380-16756499
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Nonprofit With 501(c)(3) IRS Status (Other Than An Institution Of Higher Education)
Awarding Office
75NH00 NIH National Heart, Lung, and Blood Institute
Funding Office
75NH00 NIH National Heart, Lung, and Blood Institute
Awardee UEI
QN6MS4VN7BD1
Awardee CAGE
0W3J1
Performance District
MA-07
Senators
Edward Markey
Elizabeth Warren
Elizabeth Warren
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| National Heart, Lung, and Blood Institute, National Institutes of Health, Health and Human Services (075-0872) | Health research and training | Grants, subsidies, and contributions (41.0) | $826,313 | 100% |
Modified: 4/6/26