Discovery explains Long COVID breathing problems

(Press-News.org) Groundbreaking research from the University of Virginia School of Medicine has revealed crucial new insights into the immune systems of COVID-19 survivors, particularly those struggling with persistent breathing issues. The study shows that these patients have distinct changes in their immune system that link to the severity of their lung damage. This discovery holds promise for developing targeted treatments for the lung complications of Long COVID.

The researchers were struck by the diversity of immune patterns they discovered, and they say the findings highlight how varied the underlying drivers of Long COVID can be, even among patients with the same symptom.

A key innovation of the study was its ability to connect immune data from the blood with lung injury. For the first time, the team was able to differentiate immune patterns in patients suffering from more severe lung injury, offering a path toward more personalized and effective treatments.

“Long COVID is complex, with a variety of potential underlying causes. For this reason, understanding the immune response in patients with lung disease has been especially difficult,” said UVA Health’s Judith A. Woodfolk, MBChB, PhD, part of the Department of Medicine’s Division of Asthma, Allergy and Immunology. “Our findings reveal crucial differences in the blood that reflect the extent of lung damage. By analyzing many different immune measures, we can pinpoint potential targets that may not only predict who might experience worse outcomes but also help guide more tailored and effective treatments in the future.”

Understanding Long COVID

To dive deeper into the persistent respiratory symptoms of Long COVID, Woodfolk and her team examined extensive clinical and immune datasets from 110 patients at UVA Health’s Long COVID Clinic. Most had been hospitalized with severe COVID-19 before vaccines were available, and many had been on ventilators during their hospital stay.

Researchers used a form of artificial intelligence called machine learning to study long-term changes in patients’ T cells, a type of immune cell. Their analysis found marked differences in the numbers and types of T cells according to the severity of lung disease. After analyzing hundreds of additional cellular and molecular features, the team was able to link these changes in T cells to other important components of the immune system. This approach revealed strikingly different “immune landscapes” in patients with milder lung disease compared with more severe cases hallmarked by lung fibrosis (scarring).  

“By uncovering distinct immune patterns in patients who have different types of restrictive lung disease after infection, we can better understand the immune drivers of lung injury and how these patterns may reflect different stages of the same disease process,” Woodfolk said. “Our ability to distinguish immune changes linked to lung disease from those linked to other disorders typical of Long COVID also adds a new dimension to our understanding of this complex illness.”

“Our ultimate goal is to help patients by guiding new treatments that could stop or even reverse lung damage caused by COVID-19,” Woodfolk added “This study simply would not have been possible without the dedication of an exceptional team of physicians and scientists and the participation of patient volunteers. We’re excited to broaden our strategy into new areas so we can gain insight into other types of chronic lung diseases and inflammatory conditions.”

Findings Published

The researchers have published their findings in the scientific journal Nature Immunology. The research team consisted of Glenda Canderan, Lyndsey M. Muehling, Alexandra Kadl, Shay Ladd, Catherine Bonham, Claire E. Cross, Sierra M. Lima, Xihui Yin, Jeffrey M. Sturek, Jeffrey M. Wilson, Behnam Keshavarz, Kyle B. Enfield, Chintan Ramani, Naomi Bryant, Deborah D. Murphy, In Su Cheon, Michael Solga, Patcharin Pramoonjago, Coleen A. McNamara, Jie Sun, Paul J. Utz, Sepideh Dolatshahi, Jonathan M. Irish and Woodfolk.

The study was supported by the National Institutes of Health, grants U01 AI100799, R21 AI138077, R56 AI178669, T32 AI007496, T32 GM145443, CA226833, AG069264, AI147394, HL170961, AI176171 and AG090337; Vanderbilt-Ingram Cancer Center, grant P30 CA68485; the University of Virginia School of Medicine; UVA’s Global Infectious Diseases Institute; the UVA Manning COVID-19 Research Fund; the Henry Gustav Floren Trust; the Stanford Department of Medicine Team Science Program; and the Stanford Medicine Office of the Dean.

Woodfolk receives support for unrelated research from Regeneron. All the other scientists declared no financial interest in the work.

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