Machine learning assisted immune profiling of COPD identifies a unique emphysema subtype independent of GOLD stage

Summary: 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 performe...

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Main Authors: 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, Leigh Matthew Marsh
Format: Article
Language:English
Published: Elsevier 2025-07-01
Series:iScience
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Online Access:http://www.sciencedirect.com/science/article/pii/S2589004225012271
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author 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
Leigh Matthew Marsh
author_facet 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
Leigh Matthew Marsh
author_sort Natalie Bordag
collection DOAJ
description Summary: 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 exchange parameters independent of their GOLD-stage. Our findings suggest that unbiased immune profiling can refine disease classification and reveal inflammation-driven disease subtypes with potential relevance for prognosis and treatment strategies.
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spelling doaj-art-696f50d59e834e749c044ac7bfdc68992025-08-20T03:33:38ZengElsevieriScience2589-00422025-07-0128711296610.1016/j.isci.2025.112966Machine learning assisted immune profiling of COPD identifies a unique emphysema subtype independent of GOLD stageNatalie Bordag0Katharina Jandl1Ayu Hutami Syarif2Jürgen Gindlhuber3Diana Schnoegl4Ayse Ceren Mutgan5Vasile Foris6Konrad Hoetzenecker7Panja Maria Boehm8Robab Breyer-Kohansal9Katarina Zeder10Gregor Gorkiewicz11Francesca Polverino12Slaven Crnkovic13Grazyna Kwapiszewska14Leigh Matthew Marsh15Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Department of Dermatology and Venereology, Medical University of Graz, Graz, Styria 8010, AustriaLudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Division of Pharmacology, Otto Loewi Research Centre, Graz, Styria 8010, AustriaLudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Otto Loewi Research Centre, Lung Research Cluster, Medical University of Graz, Graz, Styria 8010, AustriaLudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Otto Loewi Research Centre, Lung Research Cluster, Medical University of Graz, Graz, Styria 8010, AustriaLudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, AustriaLudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Otto Loewi Research Centre, Lung Research Cluster, Medical University of Graz, Graz, Styria 8010, AustriaLudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA; Harvard Medical School, Boston, MA 02115, USA; Division of Pulmonology, Department of Internal Medicine, Medical University of Graz, Graz, Styria 8010, AustriaDepartment of Thoracic Surgery, Medical University of Vienna, Vienna, Vienna 1090, AustriaLudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Department of Thoracic Surgery, Medical University of Vienna, Vienna, Vienna 1090, AustriaLudwig Boltzmann Institute for Lung Health, Vienna, Vienna 1140, Austria; Department of Respiratory and Pulmonary Diseases, Vienna Healthcare Group, Clinic Hietzing, Vienna, Vienna 1090, AustriaLudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Division of Pulmonology, Department of Internal Medicine, Medical University of Graz, Graz, Styria 8010, Austria; University of Maryland, Institute of Health Computing, Bethesda, MD 20852, USADiagnostic and Research Institute of Pathology, Medical University of Graz, Graz, Styria 8010, AustriaBaylor College of Medicine, Department of Medicine, Houston, TX 77030, USALudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Otto Loewi Research Centre, Lung Research Cluster, Medical University of Graz, Graz, Styria 8010, Austria; Institute for Lung Health, Cardiopulmonary Institute, Member of the German Center for Lung Research, Justus-Liebig University Giessen, 35392 Giessen, GermanyLudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Otto Loewi Research Centre, Lung Research Cluster, Medical University of Graz, Graz, Styria 8010, Austria; Institute for Lung Health, Cardiopulmonary Institute, Member of the German Center for Lung Research, Justus-Liebig University Giessen, 35392 Giessen, GermanyLudwig Boltzmann Institute for Lung Vascular Research, Graz, Styria 8010, Austria; Otto Loewi Research Centre, Lung Research Cluster, Medical University of Graz, Graz, Styria 8010, Austria; Corresponding authorSummary: 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 exchange parameters independent of their GOLD-stage. Our findings suggest that unbiased immune profiling can refine disease classification and reveal inflammation-driven disease subtypes with potential relevance for prognosis and treatment strategies.http://www.sciencedirect.com/science/article/pii/S2589004225012271respiratory medicinemachine learning
spellingShingle 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
Leigh Matthew Marsh
Machine learning assisted immune profiling of COPD identifies a unique emphysema subtype independent of GOLD stage
iScience
respiratory medicine
machine learning
title Machine learning assisted immune profiling of COPD identifies a unique emphysema subtype independent of GOLD stage
title_full Machine learning assisted immune profiling of COPD identifies a unique emphysema subtype independent of GOLD stage
title_fullStr Machine learning assisted immune profiling of COPD identifies a unique emphysema subtype independent of GOLD stage
title_full_unstemmed Machine learning assisted immune profiling of COPD identifies a unique emphysema subtype independent of GOLD stage
title_short Machine learning assisted immune profiling of COPD identifies a unique emphysema subtype independent of GOLD stage
title_sort machine learning assisted immune profiling of copd identifies a unique emphysema subtype independent of gold stage
topic respiratory medicine
machine learning
url http://www.sciencedirect.com/science/article/pii/S2589004225012271
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