Scientists Create Cell Atlas Containing Gene Activity Information of More Than 300,000 Lung Cells from IPF and COPD Patients

Scientists created an online cell atlas containing information on the gene activity of more than 300,000 lung cells taken from patients with idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD).

The new atlas adds to the knowledge of the complex cellular and molecular mechanisms involved in both diseases, and may assist in the development of new therapies, investigators noted.

Analyses leading up to the creation of the cell atlas were reported in the study, “Single-cell RNA-seq reveals ectopic and aberrant lung-resident cell populations in idiopathic pulmonary fibrosis,” published in the journal Science Advances.

Although studies in animal models of lung disorders have led to important advances in the understanding of pulmonary fibrosis and COPD, the knowledge of the molecular and cellular mechanisms underlying these diseases is still limited.

In an effort to expand this knowledge, researchers at Yale School of Medicine and their colleagues set out to create a cell atlas containing the genetic profile of a large number of lung cells taken from patients with either IPF or COPD.

As a first step, researchers isolated individual cells from different parts of the lungs, and then used a technique called single-cell RNA sequencing (scRNA-seq) to examine all RNA molecules, or transcripts, produced from active genes on each individual cell.

Through this process, the team analyzed 312,928 cells taken from 32 patients with IPF and 18 with COPD, creating the largest single-cell gene expression (activity) dataset in patients with chronic lung disorders to date. As controls, cells from 28 donor lungs also were analyzed.

“This is a technological accomplishment and is a new perspective on the two diseases, but it is also the starting point for analysis that will lead to a better understanding of the disease and the development of therapy,” Ivan Rosas, MD, said in a news story. Rosas is chief of pulmonary, critical care and sleep medicine in the Department of Medicine at Baylor College of Medicine, and co-senior author of the study.

When investigators compared the different populations of cells isolated from patients, they found that cells lining the surface of the lungs (epithelial cells) in IPF patients were very different from those found in COPD patients. The team also discovered a new population of abnormal epithelial cells in the lungs of IPF patients that never had been described before.

Additionally, they found IPF patients had an excessive number of a sub-type of cells forming the lining of blood vessels in the lungs, called vascular endothelial cells.

“When we analyzed the data we were surprised by how dramatically different were cells obtained from patients with PF from all other lungs — we actually found cells that were not described before, and this may have significant implications on diagnosis and management for the disease,” said Naftali Kaminski, MD, chief of pulmonary, critical care and sleep medicine at Yale, and co-senior author of the study.

“The identification and detailed description of aberrant cell populations in the IPF lung may lead to identification of novel, cell type-specific therapies and biomarkers. Last, our IPF cell atlas provides an interactive and highly accessible resource to allow the exploration of cell specific changes in gene expression in lung health and disease and thus accelerate discovery and translation,” the researchers wrote.

Rosas began the study while at Harvard Medical School, and now will continue it at Baylor.

“Chronic lung diseases are one of the leading causes of morbidity and death in diagnosed patients, but this innovative technology is the starting point for more pointed research in terms of the pathogenesis and the mechanisms of the disease and also the potential therapy that could be derived from the information,” Rosas said.

The cell atlas is available to the public, allowing other researchers to conduct their own independent research based on these data.