# Clinical implications and Proteomics of Bronchiectasis Progression in Smokers

> **NIH NIH R01** · BRIGHAM AND WOMEN'S HOSPITAL · 2024 · $877,608

## Abstract

Project Summary/Abstract
Individuals with coexisting COPD and bronchiectasis have worse lung function, longer hospital stays, and an
increased risk of death. Bronchiectasis, a pathologic airway enlargement, is increasingly recognized in the US,
with 522,000 adults treated annually for bronchiectasis. Bronchiectasis is also a relevant abnormality in chronic
obstructive pulmonary disease (COPD), affecting up to 72% of these individuals. While the development of
advanced imaging methods has facilitated our understanding of COPD progression, a critical factor hampering
our ability to examine bronchiectasis progression fully is the lack of an objective imaging tool applicable in large
studies.
In this proposal, we will use objective, automated, artificial intelligence-based computed tomography (CT)
measures of bronchiectasis. Our overarching hypotheses are 1) our artificial intelligence-based CT measures
are effective in detecting bronchiectasis changes in smoking populations and determining its clinical
consequences; 2) our approach of defining proteomic biomarkers will help identify subjects at risk of structural
progression, and ultimately, inform clinical care. We will quantify the extent of enlarged airways, a measure of
bronchiectasis, on baseline and follow-up chest CT scans from smoking individuals participating in two well
characterized cohorts, the COPDGene and Evaluation of COPD Longitudinally to Identify Predictive Surrogate
End-points (ECLIPSE). In Aim 1, we will determine the association between pulmonary vascular changes and
longitudinal measures of radiographic bronchiectasis, gaining insight into pathogenesis. In Aim 2a, we will
determine changes in artificial intelligence-based CT measures of bronchiectasis and their association with
clinical measures of disease and lung-function trajectories; in Aim 2b, we will also determine clinical factors and
imaging features associated with the development and worsening of bronchiectasis on CT. In Aim 3, we will
determine blood-based proteomic biomarkers to identify bronchiectasis and its progression on CT.
This study will validate the effectiveness of our new AI-based imaging tool for determining bronchiectasis
progression; and proteomic biomarkers to identify subjects at risk of progression, which will inform the
development of new intervention strategies.

## Key facts

- **NIH application ID:** 10856193
- **Project number:** 1R01HL173017-01
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** Alejandro Diaz
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $877,608
- **Award type:** 1
- **Project period:** 2024-05-15 → 2028-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10856193

## Citation

> US National Institutes of Health, RePORTER application 10856193, Clinical implications and Proteomics of Bronchiectasis Progression in Smokers (1R01HL173017-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10856193. Licensed CC0.

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