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."
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."
Canderan G, Muehling LM, Kadl A, Ladd S, Bonham C, Cross CE, Lima SM, Yin X, Sturek JM, Wilson JM, Keshavarz B, Enfield KB, Ramani C, Bryant N, Murphy DD, Cheon IS, Solga M, Pramoonjago P, McNamara CA, Sun J, Utz PJ, Dolatshahi S, Irish JM, Woodfolk JA.
Distinct type 1 immune networks underlie the severity of restrictive lung disease after COVID-19.
Nat Immunol. 2025 Apr;26(4):595-606. doi: 10.1038/s41590-025-02110-0