# COPD Susceptibility, Heterogeneity, and Progression: Proteomics and Genetics

> **NIH NIH R01** · BRIGHAM AND WOMEN'S HOSPITAL · 2024 · $854,782

## Abstract

PROJECT SUMMARY
Although cigarette smoking is the major environmental risk factor for COPD, only a minority of smokers develops
clinically significant COPD; genetic factors influence this variability. COPD subjects have widely varying
contributions of emphysema and airway disease, and the biological determinants of COPD heterogeneity are
not well-defined. Protein biomarkers, which are biologically proximate to genetic variants, could play a critical
intermediate role in defining COPD genetics and heterogeneity. Our overall hypothesis is that functional genetic
variants lead to abnormal proteomic states that will allow identification of protein biomarkers relevant for the
development and heterogeneity of COPD. We will use mass spectrometry proteomics to provide comprehensive
assessment of available proteins and their proteoforms (including post-translational modifications) in 1054 lung
tissue samples from the Lung Tissue Research Consortium (LTRC), including 547 COPD cases and 507 control
subjects. Olink proteomics data (generated by TOPMed) will provide orthogonal proteomics data on the same
lung tissue biospecimens. Cellular deconvolution approaches using single cell and bulk RNA-Seq data will be
used to determine whether proteomic associations relate to changes in lung cellular composition. COPD
subtypes will be defined based on both clinical/imaging data and by using network-based stratification of the
proteomics data. We will verify potential plasma protein biomarkers of COPD and COPD subtypes by measuring
the top 100 lung tissue COPD-specific proteins in plasma samples from the same LTRC COPD cases and control
subjects. We will leverage existing LTRC multi-Omics data (including whole genome sequencing, RNA-Seq, and
DNA methylation) in conjunction with newly generated mass spectrometry and affinity-based proteomics data to
identify rare and common genetic determinants of COPD-related proteins and COPD. Machine learning and
network analysis will be used to integrate multi-Omics data to provide insight into COPD pathogenesis and
heterogeneity. Network relationships for several top COPD protein biomarkers will be functionally validated using
CRISPR-Cas9 approaches in primary lung cells. The identification and characterization of novel COPD protein
biomarkers may provide insights into COPD pathogenesis and tools for future clinical trials.

## Key facts

- **NIH application ID:** 10894822
- **Project number:** 5R01HL133135-07
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** Robert L Moritz
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $854,782
- **Award type:** 5
- **Project period:** 2017-04-12 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10894822

## Citation

> US National Institutes of Health, RePORTER application 10894822, COPD Susceptibility, Heterogeneity, and Progression: Proteomics and Genetics (5R01HL133135-07). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10894822. Licensed CC0.

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