Sputum Exosomal microRNAs as Non-Invasive Biomarkers in COPD: A Cross-Sectional Study
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Population
2.2. Sample Collection and Processing
2.3. Exosome Isolation and Characterization
2.4. RNA Extraction and miRNA Quantification
2.5. Panel Selection by Bioinformatic Analyses in COPD
2.6. Statistical Analysis
3. Results
3.1. Participant Characteristics
3.2. Exosome Verification
3.3. Differential miRNA Expression
3.4. Diagnostic Performance for COPD Detection
3.5. Diagnostic Performance for COPD Stage Discrimination
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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| Parameters | COPD Patients (n = 20) | Controls (n = 10) | p-Value |
|---|---|---|---|
| Gender | |||
| Males, n (%) | 19 (95) | 9 (90) | 0.569 |
| Females, n (%) | 1 (5) | 1 (10) | |
| Age (years) | 70 ± 8 | 65 ± 5 | 0.342 |
| BMI (Kg/m2) | 31 ± 6 | 28 ± 7 | 0.423 |
| Comorbidities, yes, n (%) | |||
| Arterial Hypertension yes, n (%) | 18 (90) | 5 (50) | 0.140 |
| Hyperlipidemia yes, n (%) | 15 (70) | 5 (50) | 0.240 |
| Diabetes mellitus (%) | 4 (20%) | 1 (10%) | 0.640 |
| Coronary artery disease (%) | 3 (15%) | 1 (10%) | 0.990 |
| Obstructive sleep apnea yes, n (%) | 10 (50) | 3 (30) | 0.321 |
| Depression yes, n (%) | 9 (45) | 2 (20) | 0.150 |
| Smoking status | |||
| Former smokers | 18 (90) | 5 (50) | <0.001 |
| Never smokers | 2 (10) | 5 (50) | 0.100 |
| Pack-years | 77 ± 42 | 8 ± 2 | 0.001 |
| FEV1/FVC | 66 ± 5 | 76 ± 2 | 0.001 |
| FEV1 (L) | 1.95 ± 0.68 | 3.05 ± 0.52 | <0.001 |
| FEV1 (%) | 72 ± 8 | 110 ± 2 | 0.001 |
| GOLD stage | - | - | |
| Stage I, n (%) | 10 (50) | ||
| Stage II, n (%) | 9 (45) | ||
| Stage III, n (%) | 1(5) | ||
| Stage IV, n (%) | 0 (0) | ||
| CAT score | 16 ± 9 | - | - |
| Εxacerbation the last year, yes, n (%) | 6 (30) | - | - |
| Hospitalization the last year, yes, n (%) | 6 (30) | - | - |
| miRNA | COPD Patients (Mean ± SD) | Controls (Mean ± SD) | Fold Change (COPD vs. Controls) | 95% CI for Expression (COPD vs. Controls) * | p-Value |
|---|---|---|---|---|---|
| miR-21 | 0.3795 ± 0.5783 | 0.2017 ± 0.03061 | 3.4 | 0.12–0.64 vs. 0.18–0.22 | <0.001 |
| miR-155 | 0.5500 ± 0.2572 | 1.040 ± 0.2875 | 0.35 | 0.43–0.67 vs. 0.86–1.22 | 0.002 |
| miR-126 | 0.3467 ± 0.09689 | 1.114 ± 0.5377 | 0.42 | 0.30–0.39 vs. 0.80–1.42 | 0.009 |
| miR-223 | 1.894 ± 4.445 | 1.040 ± 0.2802 | 2.1 | 0.00–3.79 vs. 0.86–1.22 | 0.004 |
| miR-146a | 0.8018 ± 0.6598 | 1.107 ± 0.4374 | 0.28 | 0.49–1.12 vs. 0.87–1.35 | 0.006 |
| Biomarker(s) | AUC | 95% CI | p-Value | Optimal Cut-Off (Probability) | Sensitivity (%) | Specificity (%) |
|---|---|---|---|---|---|---|
| miR-21 | 0.340 | 0.14–0.54 | 0.321 | 0.431 | 55 | 60 |
| miR-155 | 0.730 | 0.53–0.93 | 0.012 | 0.318 | 80 | 80 |
| miR-126 | 0.480 | 0.26–0.70 | 0.790 | 0.385 | 65 | 70 |
| miR-223 | 0.610 | 0.39–0.82 | 0.208 | 0.412 | 60 | 70 |
| miR-146a | 0.700 | 0.49–0.91 | 0.030 | 0.345 | 75 | 75 |
| Biomarker(s) | AUC | 95% CI | p-Value | Sensitivity (%) | Specificity (%) |
|---|---|---|---|---|---|
| miR-155 + miR-126 | 0.805 | 0.65–0.96 | 0.004 | 85 | 85 |
| miR-155 + miR-146a | 0.812 | 0.66–0.97 | 0.003 | 85 | 90 |
| miR-155 + miR-126 + miR-146a | 0.841 | 0.69–0.98 | 0.001 | 90 | 95 |
| miR-155 + miR-126 + miR-146a + miR-223 | 0.845 | 0.71–0.98 | 0.001 | 90 | 95 |
| miRNA | AUC | 95% CI | p-Value | Optimal Cut-Off | Sensitivity | Specificity |
|---|---|---|---|---|---|---|
| miR-21 | 0.595 | 0.38–0.81 | 0.320 | 0.45 | 40.0% | 90.0% |
| miR-155 | 0.600 | 0.38–0.82 | 0.298 | 0.60 | 66.7% | 70.0% |
| miR-126 | 0.728 | 0.50–0.96 | 0.028 | 0.32 | 100% | 60.0% |
| miR-223 | 0.583 | 0.36–0.80 | 0.378 | 0.29 | 100% | 30.0% |
| miR-146a | 0.478 | 0.25–0.71 | 0.790 | 0.24 | 100% | 20.0% |
| Biomarker(s) | AUC | 95%CI | p-Value | Sensitivity (%) | Specificity (%) |
|---|---|---|---|---|---|
| miR-155 + miR-223 + miR-146a | 0.778 | 0.57–0.99 | 0.016 | 55.6 | 100 |
| miR-155 + miR-146a | 0.744 | 0.52–0.96 | 0.031 | 55.6 | 100 |
| miR-155 + miR-126 + miR-146a | 0.778 | 0.57–0.99 | 0.016 | 66.7 | 90 |
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Kotsiou, O.S.; Tsilioni, I.; Tsingene, A.; Katsanaki, A.; Balatsos, N.A.A.; Rouka, E.; Daniil, Z.; Gourgoulianis, K.I. Sputum Exosomal microRNAs as Non-Invasive Biomarkers in COPD: A Cross-Sectional Study. Biomedicines 2025, 13, 3027. https://doi.org/10.3390/biomedicines13123027
Kotsiou OS, Tsilioni I, Tsingene A, Katsanaki A, Balatsos NAA, Rouka E, Daniil Z, Gourgoulianis KI. Sputum Exosomal microRNAs as Non-Invasive Biomarkers in COPD: A Cross-Sectional Study. Biomedicines. 2025; 13(12):3027. https://doi.org/10.3390/biomedicines13123027
Chicago/Turabian StyleKotsiou, Ourania S., Irene Tsilioni, Aikaterini Tsingene, Aikaterini Katsanaki, Nikolaos A. A. Balatsos, Erasmia Rouka, Zoe Daniil, and Konstantinos I. Gourgoulianis. 2025. "Sputum Exosomal microRNAs as Non-Invasive Biomarkers in COPD: A Cross-Sectional Study" Biomedicines 13, no. 12: 3027. https://doi.org/10.3390/biomedicines13123027
APA StyleKotsiou, O. S., Tsilioni, I., Tsingene, A., Katsanaki, A., Balatsos, N. A. A., Rouka, E., Daniil, Z., & Gourgoulianis, K. I. (2025). Sputum Exosomal microRNAs as Non-Invasive Biomarkers in COPD: A Cross-Sectional Study. Biomedicines, 13(12), 3027. https://doi.org/10.3390/biomedicines13123027

