# Understanding Dysregulated Crosstalk Between Regulatory T Cells and Lung Dendritic Cells in the Pathogenesis of Chronic Obstructive Pulmonary Disease

> **NIH NIH F31** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $39,112

## Abstract

Chronic obstructive pulmonary disease (COPD) is a highly prevalent lung disease and is the 4th leading cause
of death in the world. COPD results from inhalation of oxidants, such as cigarette smoke, which causes
inflammatory cell infiltration and lung destruction. COPD is a progressive disease leading to significant
morbidity and mortality. There are no therapies to halt the decline in lung function. Our long-term goal is to
understand the mechanisms underlying COPD pathogenesis so that we can develop an immunotherapy to
stop disease progression. T regulatory cells (Tregs) decreased in the lungs of smokers with COPD compared
to smokers without COPD. Lung dendritic cells (DCs), which are able to polarize T cells to become Tregs or T
effector cells (Teff), are more mature in COPD, suggesting that they have a pro-inflammatory as opposed to a
tolerogenic phenotype. We hypothesize that in COPD, the increased number of mature pro-inflammatory DCs
are driving T cells towards Teff phenotype, whereas under normal conditions, tolerogenic DCs would be more
likely to promote induction of Tregs. In return, Tregs can modulate DC phenotype and function, suggesting
that subtle crosstalk feedback mechanisms are involved in the regulation of DC and Treg. However, no studies
have looked at whether dysregulated crosstalk between Treg and DC populations contributes to COPD
pathogenesis. Our specific aims are: 1) to demonstrate that COPD is associated with a shift from tolerogenic to
pro-inflammatory DCs; 2) to show that pro-inflammatory DCs preferentially polarize T cells towards a Teff
phenotype compared to tolerogenic DCs; and 3) to provide evidence that the transfer of Tregs will restore the
number of tolerogenic DCs in the lung. This proposal will utilize an established murine cigarette-smoke based
COPD model and also excess human lung tissue from consented patients undergoing clinically-indicated lung
surgeries, both with and without COPD. This allows us to conduct translational research and take
observations from human samples to the mouse model where we can answer more mechanistic questions.
Despite the abundance of clinical trials related to Treg therapy, there are currently no similar trials looking at
Tregs in patients with COPD. Successful completion of this proposal will fill critical gaps in knowledge and
provide pre-clinical data in support of exploring Treg therapy for COPD patients. This proposal will take place
with the combined resources of the University of Michigan and the VA Ann Arbor Healthcare System (the
physical location of the laboratory). There are world-class facilities at both locations. The VA houses a murine
smoke-exposure facility, Microscopy Core, and FACSAria sorter, and all equipment and space needed to
conduct the research. Many members of the Immunology Graduate Program have labs at the VA, making for
a robust scientific environment. The training plan developed to successfully complete this proposal includes
advanced training in a...

## Key facts

- **NIH application ID:** 10460830
- **Project number:** 1F31HL163872-01
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Dawit Mengistu
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $39,112
- **Award type:** 1
- **Project period:** 2022-05-16 → 2025-07-15

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10460830

## Citation

> US National Institutes of Health, RePORTER application 10460830, Understanding Dysregulated Crosstalk Between Regulatory T Cells and Lung Dendritic Cells in the Pathogenesis of Chronic Obstructive Pulmonary Disease (1F31HL163872-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10460830. Licensed CC0.

---

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