Back

Extracellular vesicle surface markers inform on COPD severity and mortality in COSYCONET

Martin, R.; Laakmann, K.; Pott, H.; Bertrams, W.; Hinz, L.; Burhorst, I.; Bals, R.; Herr, C.; Jung, A. L.; Alter, P.; Vogelmeier, C. F.; Rohde, G.; Schmeck, B.; Heider, D.

2026-07-02 respiratory medicine
10.64898/2026.06.30.26356923 medRxiv
Show abstract

Background: Chronic obstructive pulmonary disease (COPD) is a leading cause of global morbidity and mortality, and its heterogeneity demands better biomarkers of severity and progression risk. Extracellular vesicles (EVs) are promising blood-based biomarkers, but have not been examined for COPD severity and outcomes in a large multicentre cohort. Methods: We analysed 600 COSYCONET participants (up to 54 months of follow-up). EV surface markers were profiled with the MACSPlex EV Kit IO. Cross-sectional associations with severity (GOLD, FEV1) were primary (ordinal and linear regression); longitudinal trajectories and all-cause mortality were prespecified exploratory endpoints. Results: Six EV markers showed robust associations with cross-sectional severity: CD29, CD49e and CD31 increased with severity (a cell-adhesion/matrix-remodelling signal), whereas CD81 and CD8 decreased; HLA-ABC (increasing) was less specific. No marker was linked to FEV1 decline. After FDR correction, lower levels of three markers with higher 54-month mortality (all HR<1): CD25 (HR 0.77, 95% CI 0.65-0.90, q=0.018), CD56 (HR 0.75, 95% CI 0.63-0.89, q=0.018) and CD142 (HR 0.74, 95% CI 0.60-0.90, q=0.024). CD25 and CD142 also improved reclassification, CD56 did not; a CD25 + CD69 combination showed the largest incremental signal ({Delta}C 0.017, 95% CI 0.002-0.032, p=0.027). Conclusion: Circulating EV surface markers are associated with cross-sectional COPD severity. Exploratory analyses nominate CD25, CD142 and CD25 + CD69 as candidate prognostic markers requiring external validation, suggesting minimally invasive EV profiling could complement clinical assessment in COPD.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

1
European Respiratory Journal
59 papers in training set
Top 0.1%
21.8%
2
ERJ Open Research
47 papers in training set
Top 0.1%
15.0%
3
Thorax
35 papers in training set
Top 0.1%
11.8%
4
CHEST
14 papers in training set
Top 0.1%
6.7%
50% of probability mass above
5
American Journal of Respiratory and Critical Care Medicine
43 papers in training set
Top 0.1%
6.7%
6
Respiratory Research
21 papers in training set
Top 0.1%
6.2%
7
BMJ Open Respiratory Research
35 papers in training set
Top 0.2%
4.8%
8
American Journal of Respiratory Cell and Molecular Biology
43 papers in training set
Top 0.3%
2.4%
9
Nature Communications
5641 papers in training set
Top 42%
2.1%
10
eBioMedicine
183 papers in training set
Top 2%
1.9%
11
Journal of Cystic Fibrosis
15 papers in training set
Top 0.1%
1.7%
12
Scientific Reports
3612 papers in training set
Top 54%
1.7%
13
Journal of Allergy and Clinical Immunology
27 papers in training set
Top 0.3%
1.5%
14
Communications Medicine
113 papers in training set
Top 3%
1.5%
15
Annals of the American Thoracic Society
11 papers in training set
Top 0.2%
1.3%
16
American Journal of Physiology-Lung Cellular and Molecular Physiology
43 papers in training set
Top 0.5%
1.1%
17
PLOS ONE
5266 papers in training set
Top 58%
1.0%
18
JCI Insight
277 papers in training set
Top 8%
0.8%
19
Journal of Clinical Investigation
179 papers in training set
Top 6%
0.6%
20
Journal of Extracellular Vesicles
55 papers in training set
Top 0.8%
0.6%
21
Infection
15 papers in training set
Top 0.3%
0.6%
22
Journal of Cachexia, Sarcopenia and Muscle
33 papers in training set
Top 0.7%
0.6%
23
Life Science Alliance
285 papers in training set
Top 9%
0.6%
24
Cells
249 papers in training set
Top 9%
0.6%