# Novel methods to sub-phenotype patients with pulmonary hypertension due to chronic lung disease with implications for treatment

> **NIH NIH F32** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2022 · $80,746

## Abstract

PROJECT SUMMARY/ABSTRACT
Pulmonary hypertension (PH) is a heterogeneous disorder characterized by elevated pulmonary artery pressure
and is a frequent complication of chronic lung diseases, including chronic obstructive pulmonary disease and
interstitial lung disease. Despite significant impairment in quality of life and elevated mortality risk associated
with lung disease-PH, there is a single FDA approved therapy, which is appropriate for only a small subset of
patients. For this reason, drugs approved for pulmonary arterial hypertension (PAH) are frequently used off-
label. Clinical trials evaluating the efficacy of PAH therapy in lung disease-PH have by-and-large demonstrated
no consistent benefit. However, cumulative data suggest a signal towards clinical improvement in certain lung
disease-PH subgroups. Small sample size and heterogeneity of patient inclusion in these trials limit
understanding of which lung disease-PH patients per se may benefit from repurposing existing PAH therapies.
Therefore, efforts to sub-phenotype lung disease-PH patients and decipher heterogeneity of treatment effect are
critical to improving outcomes for at-risk patients. The Veteran’s Health Administration (VA) is the largest
integrated national health system, and includes a patient population enriched for lung disease-PH in whom off-
label prescribing of PAH therapies is common. To this end, leveraging a national cohort of Veterans with lung
disease-PH established by my sponsor, I propose the study, “Novel methods to sub-phenotype patients with
pulmonary hypertension due to chronic lung disease with implications for treatment.” This study includes two
foundational steps towards unraveling the heterogeneous diagnosis of lung disease-PH to advance treatments:
1) characterize sub-phenotypes of lung disease-PH using cluster analysis and 2) explore how treatment
outcomes vary across lung disease-PH sub-phenotypes. The first objective will be achieved through the
application of k-means cluster analysis to physiologic and functional variables relevant to the diagnosis of lung
disease-PH and assessment of disease severity. The second objective will be achieved through within cluster
Cox proportional hazard assessments of acute respiratory, renal and right heart failure or death. These aims are
directly in line with one major research priority of the NHLBI, to identify disease sub-phenotypes and patients
likely to respond to disease-specific treatments. Completion of this proposal will advance the field of lung
disease-PH by identifying sub-phenotypes of patients to then refine patient enrollment in clinical trials, advance
therapeutic options and improve disease survival. The skills I anticipate gaining through this mentored project
across three academic institutions, Boston University Medical Center, Boston Veteran Affairs Center for
Healthcare Organization & Implementation Research and The Division of Cardiovascular Medicine at Brigham
and Women’s Hospital/Harvard Med...

## Key facts

- **NIH application ID:** 10465554
- **Project number:** 1F32HL164090-01
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** SHELSEY WEINSTEIN JOHNSON
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $80,746
- **Award type:** 1
- **Project period:** 2022-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10465554

## Citation

> US National Institutes of Health, RePORTER application 10465554, Novel methods to sub-phenotype patients with pulmonary hypertension due to chronic lung disease with implications for treatment (1F32HL164090-01). Retrieved via AI Analytics 2026-06-04 from https://api.ai-analytics.org/grant/nih/10465554. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*
