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-1
- Bordag, N.
- Jandl, K.
- Syarif, A. H.
- Gindlhuber, J.
- Schnoegl, D.
- Mutgan, A. C.
- Foris, V.
- Hoetzenecker, K.
- Boehm, P. M.
- Breyer-Kohansal, R.
- Zeder, K.
- Gorkiewicz, G.
- Polverino, F.
- Crnkovic, S.
- Kwapiszewska, G.
- Marsh, L. M.
Keywords
- machine learning
- respiratory medicine
