Machine learning assisted immune profiling of COPD identifies a unique emphysema subtype independent of GOLD stage
Natalie Bordag, Katharina Jandl, Ayu Hutami Syarif, Jürgen Gindlhuber, Diana Schnoegl, Ayse Ceren Mutgan, Vasile Foris, Konrad Hoetzenecker, Panja Maria Boehm, Robab Breyer-Kohansal, Katarina Zeder, Gregor Gorkiewicz, Francesca Polverino, Slaven Crnkovic, Grazyna Kwapiszewska

TL;DR
This study uses machine learning to identify a new COPD subtype linked to severe emphysema, independent of traditional disease staging.
Contribution
A novel COPD immune subtype (EIS) is identified using machine learning and multiomics data, independent of GOLD stage.
Findings
COPD immune profiles show a shift toward adaptive immune cells.
A new COPD subtype (EIS) is associated with severe emphysema and distinct immune markers.
EIS features increased antigen-presenting cells, mast cells, and CD8+ T cells.
Abstract
Chronic obstructive pulmonary disease (COPD) is a severe, progressive, and heterogeneous disease with a poor outcome. Inflammation plays a central role in disease pathogenesis; however, the interplay between immune changes and disease heterogeneity has been difficult to unravel. We performed a multilevel immunoinflammatory characterization of patients with COPD using flow cytometry, cytokine profiling, single-cell, or spatial transcriptomics in combination with machine learning algorithms. Our cross-cohort analysis demonstrated shared skewing of immune profiles in COPD lungs toward adaptive immune cells. We furthermore identified a subgroup of patients with COPD with a distinct immune profile, characterized by increased antigen-presenting cells, mast cells, and CD8+ cells, and circulating IL-1β, IFN-β, and GM-CSF, that were associated with increased emphysema severity and decreased gas…
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Taxonomy
TopicsChronic Obstructive Pulmonary Disease (COPD) Research · Respiratory Support and Mechanisms · Respiratory viral infections research
