New Biomarkers of Chronic Obstructive Airway Diseases: Impact on Differential Diagnosis, Therapeutic Strategies, and Prognosis in COPD. A literature review
DOI:
https://doi.org/10.12775/QS.2026.49.67995Keywords
COPD, Asthma-COPD Overlap (ACO), Biomarkers, EosinophilsAbstract
Chronic obstructive pulmonary disease (COPD) is a heterogeneous respiratory disorder whose diagnosis and differentiation from asthma remain challenging. The aim of this review was to present current biomarkers used in the diagnosis of COPD and to highlight promising directions for future research. A literature analysis covering the years 2020–2025 included biomarkers assessed in blood, urine, sputum, as well as genetic and molecular markers. The findings indicate that peripheral blood eosinophil counts and the neutrophil-to-lymphocyte ratio (NLR) are useful in predicting the risk of exacerbations and response to therapy. Serum proteomic and metabolomic analyses, together with urinary biomarkers, enable non-invasive patient phenotyping and early detection of exacerbations. Genetic and transcriptomic studies have identified key genes and inflammatory pathways relevant to disease pathogenesis, while the composition of the airway microbiome correlates with symptom severity and lung function. Integration of molecular, immunological, and microbiological data allows for precise patient phenotyping, supports personalized therapeutic strategies, and improves clinical outcomes. Biomarkers are becoming an important source of information in the differential diagnosis of COPD and asthma–COPD overlap (ACO), as well as in targeted treatment approaches.
References
1. GBD Chronic Respiratory Disease Collaborators. Prevalence and attributable health burden of chronic respiratory diseases, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Respir Med. 2020 Jun;8(6):585-596. doi: 10.1016/S2213-2600(20)30105-3. PMID: 32526187; PMCID: PMC7284317. https://doi.org/10.1016/s2213-2600(20)30105-3
2. Adeloye D, Song P, Zhu Y, Campbell H, Sheikh A, Rudan I; NIHR RESPIRE Global Respiratory Health Unit. Global, regional, and national prevalence of, and risk factors for, chronic obstructive pulmonary disease (COPD) in 2019: a systematic review and modelling analysis. Lancet Respir Med. 2022 May;10(5):447-458. doi: 10.1016/S2213-2600(21)00511-7. Epub 2022 Mar 10. PMID: 35279265; PMCID: PMC9050565. https://doi.org/10.1016/s2213-2600(21)00511-7
3. Adeloye D, Chua S, Lee C, Basquill C, Papana A, Theodoratou E, Nair H, Gasevic D, Sridhar D, Campbell H, Chan KY, Sheikh A, Rudan I; Global Health Epidemiology Reference Group (GHERG). Global and regional estimates of COPD prevalence: Systematic review and meta-analysis. J Glob Health. 2015 Dec;5(2):020415. doi: 10.7189/jogh.05.020415. PMID: 26755942; PMCID: PMC4693508. https://doi.org/10.7189/jogh.05.020415
4. Celli B, Fabbri L, Criner G, Martinez FJ, Mannino D, Vogelmeier C, Montes de Oca M, Papi A, Sin DD, Han MK, Agusti A. Definition and Nomenclature of Chronic Obstructive Pulmonary Disease: Time for Its Revision. Am J Respir Crit Care Med. 2022 Dec 1;206(11):1317-1325. doi: 10.1164/rccm.202204-0671PP. PMID: 35914087; PMCID: PMC9746870. https://doi.org/10.1164/rccm.202204-0671pp
5. World Health Organization. (2023, November 2). Chronic obstructive pulmonary disease (COPD). https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd)
6. Szczeklik, A., Gajewski, P. (Red.). (2024). Interna Szczeklika 2024. Medycyna Praktyczna.
7. Barnes PJ. Against the Dutch hypothesis: asthma and chronic obstructive pulmonary disease are distinct diseases. Am J Respir Crit Care Med. 2006 Aug 1;174(3):240-3; discussion 243-4. doi: 10.1164/rccm.2604008. PMID: 16864717. https://doi.org/10.1164/rccm.2604008
8. Global Initiative for Chronic Obstructive Lung Disease (GOLD). Global strategy for the dia- gnosis, management, and prevention of chronic obstructive pulmonary disease. Updated 2025. http://www.goldcopd.com
9. Schivo, M., Albertson, T. E., Haczku, A., Kenyon, N. J., Zeki, A. A., Kuhn, B. T., Louie, S., & Avdalovic, M. V. (2017). Paradigms in chronic obstructive pulmonary disease: phenotypes, immunobiology, and therapy with a focus on vascular disease. Journal of investigative medicine : the official publication of the American Federation for Clinical Research, 65(6), 953–963. https://doi.org/10.1136/jim-2016-000358
10. Christenson S. A. (2023). COPD Phenotyping. Respiratory care, 68(7), 871–880. https://doi.org/10.4187/respcare.11035
11. Xie, C., Wang, K., Yang, K., Zhong, Y., Gul, A., Luo, W., Yalikun, M., He, J., Chen, W., Xu, W., & Dong, J. (2025). Toward precision medicine in COPD: phenotypes, endotypes, biomarkers, and treatable traits. Respiratory research, 26(1), 274. https://doi.org/10.1186/s12931-025-03356-w
12. Fang H, Liu Y, Yang Q, Han S, Zhang H. Prognostic Biomarkers Based on Proteomic Technology in COPD: A Recent Review. Int J Chron Obstruct Pulmon Dis. 2023 Jun 30;18:1353-1365. doi: 10.2147/COPD.S410387. PMID: 37408604; PMCID: PMC10319291. https://doi.org/10.2147/copd.s410387
13. Zhang Z, Wang J, Li Y, Liu F, Chen L, He S, Lin F, Wei X, Fang Y, Li Q, Zhou J, Lu W. Proteomics and metabolomics profiling reveal panels of circulating diagnostic biomarkers and molecular subtypes in stable COPD. Respir Res. 2023 Mar 11;24(1):73. doi: 10.1186/s12931-023-02349-x. PMID: 36899372; PMCID: PMC10007826. https://doi.org/10.1186/s12931-023-02349-x
14. Liao SX, Wang YW, Sun PP, Xu Y, Wang TH. Prospects of neutrophilic implications against pathobiology of chronic obstructive pulmonary disease: Pharmacological insights and technological advances. Int Immunopharmacol. 2025 Jan 10;144:113634. doi: 10.1016/j.intimp.2024.113634. Epub 2024 Nov 21. PMID: 39577220. https://doi.org/10.1016/j.intimp.2024.113634
15. Huang Y, Niu Y, Wang X, Li X, He Y, Liu X. Identification of novel biomarkers related to neutrophilic inflammation in COPD. Front Immunol. 2024 May 30;15:1410158. doi: 10.3389/fimmu.2024.1410158. PMID: 38873611; PMCID: PMC11169582. https://doi.org/10.3389/fimmu.2024.1410158
16. Fang L, Zhu J, Fu D. Predictive value of neutrophil-lymphocyte ratio for all-cause mortality in patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis. BMC Pulm Med. 2025 Apr 29;25(1):206. doi: 10.1186/s12890-025-03677-y. PMID: 40301774; PMCID: PMC12039089. https://doi.org/10.1186/s12890-025-03677-y
17. Papaporfyriou A, Bakakos P, Hillas G, Papaioannou AI, Loukides S. Blood eosinophils in COPD: friend or foe? Expert Rev Respir Med. 2022 Jan;16(1):35-41. doi: 10.1080/17476348.2021.2011219. Epub 2021 Dec 3. PMID: 34821191.
18. Kang, H. S., Kim, S. K., Kim, Y. H., Kim, J. W., Lee, S. H., Yoon, H. K., & Rhee, C. K. (2021). The association between eosinophilic exacerbation and eosinophilic levels in stable COPD. BMC pulmonary medicine, 21(1), 74. https://doi.org/10.1186/s12890-021-01443-4
19. Zhang, Y., Liang, L. R., Zhang, S., Lu, Y., Chen, Y. Y., Shi, H. Z., & Lin, Y. X. (2020). Blood Eosinophilia and Its Stability in Hospitalized COPD Exacerbations are Associated with Lower Risk of All-Cause Mortality. International journal of chronic obstructive pulmonary disease, 15, 1123–1134. https://doi.org/10.2147/COPD.S245056
20. Liu, H., Xie, Y., Huang, Y., Luo, K., Gu, Y., Zhang, H., Xu, Y., & Chen, X. (2024). The association between blood eosinophils and clinical outcome of acute exacerbations of chronic obstructive pulmonary disease: A systematic review and meta-analysis. Respiratory medicine, 222, 107501. https://doi.org/10.1016/j.rmed.2023.107501
21. Kiani, A., Rahimi, F., Afaghi, S., Paat, M., Varharam, M., Dizaji, M. K., Dastoorpoor, M., & Abedini, A. (2023). Association of Upon-Diagnosis Blood Eosinophilic Count with Frequency and Severity of Annual Exacerbation in Chronic Obstructive Pulmonary Disease: A Prospective Longitudinal Analysis. Canadian respiratory journal, 2023, 8678702. https://doi.org/10.1155/2023/8678702
22. Pu, J., Yi, Q., Luo, Y., Wei, H., Ge, H., Liu, H., Li, X., Zhang, J., Pan, P., Zhou, H., Zhou, C., Yi, M., Cheng, L., Liu, L., Zhang, J., Peng, L., Aili, A., Liu, Y., Zhou, H., & MAGNET AECOPD Registry Investigators (2023). Blood Eosinophils and Clinical Outcomes in Inpatients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Prospective Cohort Study. International journal of chronic obstructive pulmonary disease, 18, 169–179. https://doi.org/10.2147/COPD.S396311
23. Citgez, E., van der Palen, J., van der Valk, P., Kerstjens, H. A. M., & Brusse-Keizer, M. (2021). Stability in eosinophil categorisation during subsequent severe exacerbations of COPD. BMJ open respiratory research, 8(1), e000960. https://doi.org/10.1136/bmjresp-2021-000960
24. Zinellu, A., Zinellu, E., Mangoni, A. A., Pau, M. C., Carru, C., Pirina, P., & Fois, A. G. (2022). Clinical significance of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in acute exacerbations of COPD: present and future. European respiratory review : an official journal of the European Respiratory Society, 31(166), 220095. https://doi.org/10.1183/16000617.0095-2022
25. Yao, C., Liu, X., & Tang, Z. (2017). Prognostic role of neutrophil-lymphocyte ratio and platelet-lymphocyte ratio for hospital mortality in patients with AECOPD. International journal of chronic obstructive pulmonary disease, 12, 2285–2290. https://doi.org/10.2147/COPD.S141760
26. Jiang, M., Yang, Y., & Wang, H. (2024). Stability of Neutrophil to Lymphocyte Ratio in Acute Exacerbation of Chronic Obstructive Pulmonary Disease and Its Relationship with Clinical Outcomes: A Retrospective Cohort Study. International journal of chronic obstructive pulmonary disease, 19, 2431–2441. https://doi.org/10.2147/COPD.S487063
27. Vu-Hoai, N., Ly-Phuc, D., Duong-Minh, N., Tran-Ngoc, N., & Nguyen-Dang, K. (2024). Predictive value of neutrophil-to-lymphocyte ratio for adverse outcomes in hospitalized patients with acute exacerbation of chronic obstructive pulmonary disease: A retrospective study. Medicine, 103(38), e39797. https://doi.org/10.1097/MD.0000000000039797
28. Feng, X., Xiao, H., Duan, Y., Li, Q., & Ou, X. (2023). Prognostic Value of Neutrophil to Lymphocyte Ratio for Predicting 90-Day Poor Outcomes in Hospitalized Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease. International journal of chronic obstructive pulmonary disease, 18, 1219–1230. https://doi.org/10.2147/COPD.S399671
29. Fang, H., Liu, Y., Yang, Q., Han, S., & Zhang, H. (2023). Prognostic Biomarkers Based on Proteomic Technology in COPD: A Recent Review. International journal of chronic obstructive pulmonary disease, 18, 1353–1365. https://doi.org/10.2147/COPD.S410387
30. Fawzy, A., Putcha, N., Raju, S., Woo, H., Lin, C. T., Brown, R. H., Williams, M. S., Faraday, N., McCormack, M. C., & Hansel, N. (2023). Urine and Plasma Markers of Platelet Activation and Respiratory Symptoms in COPD. Chronic obstructive pulmonary diseases (Miami, Fla.), 10(1), 22–32. https://doi.org/10.15326/jcopdf.2022.0326
31. Kim, H. Y., Lee, H. S., Kim, I. H., Kim, Y., Ji, M., Oh, S., Kim, D. Y., Lee, W., Kim, S. H., & Paik, M. J. (2022). Comprehensive Targeted Metabolomic Study in the Lung, Plasma, and Urine of PPE/LPS-Induced COPD Mice Model. International journal of molecular sciences, 23(5), 2748. https://doi.org/10.3390/ijms23052748
32. Yousuf, A. J., Parekh, G., Farrow, M., Ball, G., Graziadio, S., Wilson, K., Lendrem, C., Carr, L., Watson, L., Parker, S., Finch, J., Glover, S., Mistry, V., Porter, K., Duvoix, A., O'Brien, L., Rees, S., Lewis, K. E., Davis, P., & Brightling, C. E. (2025). Artificial neural network risk prediction of COPD exacerbations using urine biomarkers. ERJ open research, 11(3), 00797-2024. https://doi.org/10.1183/23120541.00797-2024
33. Shi, Y., Pu, S., Huang, N., & Wang, Y. (2025). Association Between Urinary Glyphosate Concentrations and Chronic Obstructive Pulmonary Disease in USA Participants: Evidence from NHANES 2013-2018. International journal of chronic obstructive pulmonary disease, 20, 883–894. https://doi.org/10.2147/COPD.S500429
34. Liu, J., Ran, Z., Wang, F., Xin, C., Xiong, B., & Song, Z. (2021). Role of pulmonary microorganisms in the development of chronic obstructive pulmonary disease. Critical reviews in microbiology, 47(1), 1–12. https://doi.org/10.1080/1040841X.2020.1830748
35. Su, L., Qiao, Y., Luo, J., Huang, R., Li, Z., Zhang, H., Zhao, H., Wang, J., & Xiao, Y. (2022). Characteristics of the sputum microbiome in COPD exacerbations and correlations between clinical indices. Journal of translational medicine, 20(1), 76. https://doi.org/10.1186/s12967-022-03278-x
36. Bahetjan, K., Yu-Xia, Lin, S., Aili, N., Yang, H., & Du, S. (2025). Analysis of the bronchoalveolar lavage fluid microbial flora in COPD patients at different lung function during acute exacerbation. Scientific reports, 15(1), 13179. https://doi.org/10.1038/s41598-025-96746-5
37. Yang, C. Y., Li, S. W., Chin, C. Y., Hsu, C. W., Lee, C. C., Yeh, Y. M., & Wu, K. A. (2021). Association of exacerbation phenotype with the sputum microbiome in chronic obstructive pulmonary disease patients during the clinically stable state. Journal of translational medicine, 19(1), 121. https://doi.org/10.1186/s12967-021-02788-4
38. Lin, Z., Xue, M., Lu, M., Liu, S., Jiang, Y., Yang, Q., Cui, H., Huang, X., Zheng, Z., & Sun, B. (2025). Multi-omics driven biomarker discovery and pathological insights into Pseudomonas aeruginosa pneumonia. BMC infectious diseases, 25(1), 745. https://doi.org/10.1186/s12879-025-11119-7
39. Lin, Z., Liu, S., Zhang, K., Feng, T., Luo, Y., Liu, Y., Sun, B., & Zhou, L. (2025). Molecular mechanisms and therapeutic targets of acute exacerbations of chronic obstructive pulmonary disease with Pseudomonas aeruginosa infection. Respiratory research, 26(1), 115. https://doi.org/10.1186/s12931-025-03185-x
40. Verceles, A. C., Bhat, P., Nagaria, Z., Martin, D., Patel, H., Ntem-Mensah, A., Hyun, S. W., Hahn, A., Jeudy, J., Cross, A. S., Lillehoj, E. P., & Goldblum, S. E. (2021). MUC1 ectodomain is a flagellin-targeting decoy receptor and biomarker operative during Pseudomonas aeruginosa lung infection. Scientific reports, 11(1), 22725. https://doi.org/10.1038/s41598-021-02242-x
41. Zhang Y, Sheng Y, Gao Y, Lin Y, Cheng B, Li H, Zhang L, Xu H. Exploration of the Pathogenesis of Chronic Obstructive Pulmonary Disease Caused by Smoking-Based on Bioinformatics Analysis and In Vitro Experimental Evidence. Toxics. 2023 Dec 7;11(12):995. doi: 10.3390/toxics11120995. PMID: 38133396; PMCID: PMC10747869. https://doi.org/10.3390/toxics11120995
42. Zhao J, Ge X, Li H, Jing G, Ma W, Fan Y, Chen J, Zhao Z, Hou J. Hub Genes PRPF19 and PPIB: Molecular Pathways and Potential Biomarkers in COPD. Int J Chron Obstruct Pulmon Dis. 2025 Jun 11;20:1865-1880. doi: 10.2147/COPD.S511696. PMID: 40524719; PMCID: PMC12168939.
43. Yu H, Guo W, Liu Y, Wang Y. Immune Characteristics Analysis and Transcriptional Regulation Prediction Based on Gene Signatures of Chronic Obstructive Pulmonary Disease. Int J Chron Obstruct Pulmon Dis. 2021 Nov 5;16:3027-3039. doi: 10.2147/COPD.S325328. PMID: 34764646; PMCID: PMC8577508. https://doi.org/10.2147/copd.s325328
44. Yang Y, Cao Y, Han X, Ma X, Li R, Wang R, Xiao L, Xie L. Revealing EXPH5 as a potential diagnostic gene biomarker of the late stage of COPD based on machine learning analysis. Comput Biol Med. 2023 Mar;154:106621. doi: 10.1016/j.compbiomed.2023.106621. Epub 2023 Jan 31. PMID: 36746116. https://doi.org/10.1016/j.compbiomed.2023.106621
45. Zhang Y, Xia R, Lv M, Li Z, Jin L, Chen X, Han Y, Shi C, Jiang Y, Jin S. Machine-Learning Algorithm-Based Prediction of Diagnostic Gene Biomarkers Related to Immune Infiltration in Patients With Chronic Obstructive Pulmonary Disease. Front Immunol. 2022 Mar 8;13:740513. doi: 10.3389/fimmu.2022.740513. PMID: 35350787; PMCID: PMC8957805. https://doi.org/10.3389/fimmu.2022.740513
46. Zhou, T. H., Zhou, X. X., Ni, J., Ma, Y. Q., Xu, F. Y., Fan, B., Guan, Y., Jiang, X. A., Lin, X. Q., Li, J., Xia, Y., Wang, X., Wang, Y., Huang, W. J., Tu, W. T., Dong, P., Li, Z. B., Liu, S. Y., & Fan, L. (2024). CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD. Military Medical Research, 11(1), 14. https://doi.org/10.1186/s40779-024-00516-9
47. Zhou, T., Zhou, X., Ni, J., Guan, Y., Jiang, X., Lin, X., Li, J., Xia, Y., Wang, X., Wang, Y., Huang, W., Tu, W., Dong, P., Li, Z., Liu, S., & Fan, L. (2024). A CT-Based Lung Radiomics Nomogram for Classifying the Severity of Chronic Obstructive Pulmonary Disease. International journal of chronic obstructive pulmonary disease, 19, 2705–2717. https://doi.org/10.2147/COPD.S483007
48. Zhou, X., Ma, Y., Zhou, T., Xie, X., Li, Y., Guan, Y., Wang, Y., Li, J., Zhang, H., Liu, S., & Fan, L. (2025). A computed tomography-based lung radiomics nomogram to identify acute exacerbation of chronic obstructive pulmonary disease: a multi-institutional validation study. Journal of thoracic disease, 17(10), 7762–7777. https://doi.org/10.21037/jtd-2025-972
49. Lin, X., Zhou, T., Ni, J., Li, J., Guan, Y., Jiang, X., Zhou, X., Xia, Y., Xu, F., Hu, H., Dong, Q., Liu, S., & Fan, L. (2024). CT-based whole lung radiomics nomogram: a tool for identifying the risk of cardiovascular disease in patients with chronic obstructive pulmonary disease. European radiology, 34(8), 4852–4863. https://doi.org/10.1007/s00330-023-10502-9
50. Lin, X., Zhou, T., Ni, J., Zhou, X., Guan, Y., Jiang, X., Xia, Y., Xu, F., Hu, H., Li, J., Zhang, J., Liu, S., Vliegenthart, R., & Fan, L. (2025). CT-Based radiomics nomogram of lung and mediastinal features to identify cardiovascular disease in chronic obstructive pulmonary disease: a multicenter study. BMC pulmonary medicine, 25(1), 121. https://doi.org/10.1186/s12890-025-03568-2
51. Hirai K, Shirai T, Shimoshikiryo T, Ueda M, Gon Y, Maruoka S, Itoh K. Circulating microRNA-15b-5p as a biomarker for asthma-COPD overlap. Allergy. 2021 Mar;76(3):766-774. doi: 10.1111/all.14520. Epub 2020 Aug 20. PMID: 32713026. https://doi.org/10.1111/all.14520
52. Chang YP, Tsai YH, Chen YM, Huang KT, Lee CP, Hsu PY, Chen HC, Lin MC, Chen YC. Upregulated microRNA-125b-5p in patients with asthma-COPD overlap mediates oxidative stress and late apoptosis via targeting IL6R/TRIAP1 signaling. Respir Res. 2024 Feb 1;25(1):64. doi: 10.1186/s12931-024-02703-7. PMID: 38302925; PMCID: PMC10835813. https://doi.org/10.1186/s12931-024-02703-7
53. Chang C, Huang K, Xu X, Duan R, Yu T, Chu X, Chen C, Li B, Yang T. MiR-23a-5p alleviates chronic obstructive pulmonary disease through targeted regulation of RAGE-ROS pathway. Respir Res. 2024 Feb 20;25(1):93. doi: 10.1186/s12931-024-02736-y. PMID: 38378600; PMCID: PMC10880325. https://doi.org/10.1186/s12931-024-02736-y
54. Shirai, T., Hirai, K., Gon, Y., Maruoka, S., Mizumura, K., Hikichi, M., Holweg, C., Itoh, K., Inoue, H., & Hashimoto, S. (2019). Combined Assessment of Serum Periostin and YKL-40 May Identify Asthma-COPD Overlap. The journal of allergy and clinical immunology. In practice, 7(1), 134–145.e1. https://doi.org/10.1016/j.jaip.2018.06.015
55. Wang, J., Lv, H., Luo, Z., Mou, S., Liu, J., Liu, C., Deng, S., Jiang, Y., Lin, J., Wu, C., Liu, X., He, J., & Jiang, D. (2018). Plasma YKL-40 and NGAL are useful in distinguishing ACO from asthma and COPD. Respiratory research, 19(1), 47. https://doi.org/10.1186/s12931-018-0755-6
56. Bersimbaev, R., Aripova, A., Bulgakova, O., Kussainova, А., Akparova, A., & Izzotti, A. (2021). The Plasma Levels of hsa-miR-19b-3p, hsa-miR-125b-5p, and hsamiR- 320c in Patients with Asthma, COPD and Asthma-COPD Overlap Syndrome (ACOS). MicroRNA (Shariqah, United Arab Emirates), 10(2), 130–138. https://doi.org/10.2174/2211536610666210609142859
57. Escamilla-Gil, J. M., Torres-Duque, C. A., Llinás-Caballero, K., Proaños-Jurado, N. J., De Vivero, M. M., Ramirez, J. C., Regino, R., Florez de Arco, L. T., Dennis, R., González-García, M., Caraballo, L., & Acevedo, N. (2025). Plasma Levels of CXCL9 and MCP-3 are Increased in Asthma-COPD Overlap (ACO) Patients. International journal of chronic obstructive pulmonary disease, 20, 1161–1174. https://doi.org/10.2147/COPD.S506517
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