肺泡巨噬细胞在脓毒症合并ARDS中的作用机制及治疗潜力
The Mechanism of Action and Therapeutic Potential of Alveolar Macrophages in Sepsis Complicated with ARDS
DOI: 10.12677/acm.2026.161296, PDF,   
作者: 钟庆邦:赣南医科大学第一临床医学院,江西 赣州;朱宏泉*:赣南医科大学第一附属医院重症医学科,江西 赣州
关键词: 肺泡巨噬细胞脓毒症急性呼吸窘迫综合征动态表型精准分期靶向治疗Alveolar Macrophages Sepsis Acute Respiratory Distress Syndrome Dynamic Phenotypes Precise Staging Targeted Therapy
摘要: 脓毒症合并急性呼吸窘迫综合征(ARDS)是一种相当严重的临床病症,它的特征是死亡率较高,给患者的诊疗工作给予了极大挑战,AMs属于肺免疫系统里的关键构成部分,对于维持肺免疫稳态以及调节炎症反应起着非常重要的作用。近年来,研究发现AMs的表型具有高度动态性,其变化不仅反映了疾病的进展状态,也为精准分期和个体化治疗提供了可能。不过当前对于AMs动态表型调控机制的理解并不全面,精准分期方法还处在探索时期,针对AMs的靶向治疗策略同样面临着临床转化的挑战。本文对AMs在脓毒症合并ARDS里的动态表型以及功能变化做了系统综述,剖析了基于AMs表型的精准分期方法,并且总结了当前靶向治疗策略及其临床应用前景,借助整合最新的基础研究成果与临床研究成果,推动脓毒症合并ARDS的精准诊疗进程,为改善患者预后提供理论支撑和治疗新思路。
Abstract: Sepsis combined with acute respiratory distress syndrome (ARDS) is a rather serious clinical condition, characterized by a high mortality rate, which poses a great challenge to the diagnosis and treatment of patients. Alveolar macrophages are a key component of the pulmonary immune system and play a very important role in maintaining pulmonary immune homeostasis and regulating inflammatory responses. In recent years, studies have found that the phenotype of alveolar macrophages is highly dynamic. Their changes not only reflect the progression status of the disease but also provide the possibility for precise staging and individualized treatment. However, the current understanding of the dynamic phenotypic regulatory mechanism of alveolar macrophages is not comprehensive. The precise staging method is still in the exploration stage, and the targeted treatment strategy for alveolar macrophages also faces the challenge of clinical transformation. This article systematically reviews the dynamic phenotypes and functional changes of alveolar macrophages in sepsis complicated with ARDS, analyzes the precise staging methods based on the phenotypes of alveolar macrophages, and summarizes the current targeted treatment strategies and their clinical application prospects. By integrating the latest basic research results and clinical research results, we can promote the precise diagnosis and treatment process of sepsis complicated with ARDS, and provide theoretical support and new treatment ideas for improving the prognosis of patients.
文章引用:钟庆邦, 朱宏泉. 肺泡巨噬细胞在脓毒症合并ARDS中的作用机制及治疗潜力[J]. 临床医学进展, 2026, 16(1): 2363-2373. https://doi.org/10.12677/acm.2026.161296

参考文献

[1] Xu, Z., Zhang, K., Liu, D. and Fang, X. (2025) Predicting Mortality and Risk Factors of Sepsis Related ARDS Using Machine Learning Models. Scientific Reports, 15, Article No. 13509. [Google Scholar] [CrossRef] [PubMed]
[2] Wang, Y., Zhang, L., Xi, X. and Zhou, J. (2021) The Association between Etiologies and Mortality in Acute Respiratory Distress Syndrome: A Multicenter Observational Cohort Study. Frontiers in Medicine, 8, Article 739596. [Google Scholar] [CrossRef] [PubMed]
[3] Wang, D., Jia, H., Zheng, X., Xi, X., Zheng, Y. and Li, W. (2024) Attributable Mortality of ARDS among Critically Ill Patients with Sepsis: A Multicenter, Retrospective Cohort Study. BMC Pulmonary Medicine, 24, Article No. 110. [Google Scholar] [CrossRef] [PubMed]
[4] Lin, J., Gu, C., Sun, Z., Zhang, S. and Nie, S. (2024) Machine Learning-Based Model for Predicting the Occurrence and Mortality of Nonpulmonary Sepsis-Associated Ards. Scientific Reports, 14, Article No. 28240. [Google Scholar] [CrossRef] [PubMed]
[5] Wei, S., Shen, Z., Yin, Y., Cong, Z., Zeng, Z. and Zhu, X. (2023) Advances of Presepsin in Sepsis-Associated Ards. Postgraduate Medical Journal, 100, 209-218. [Google Scholar] [CrossRef] [PubMed]
[6] Charoensappakit, A., Sae-khow, K., Maneesow, P., Vutthikraivit, N., Doi, K., Pachinburavan, M., et al. (2025) Predictive Efficacy of Plasma Arginase 1 as a Novel Biomarker for Mechanical Ventilated Patients with Sepsis Induced Acute Respiratory Distress Syndrome: A Prospective Cohort Study. Respiratory Medicine, 246, Article ID: 108227. [Google Scholar] [CrossRef] [PubMed]
[7] Zhao, J., Tan, Y., Wang, L. and Shi, Y. (2020) Discriminatory Ability and Prognostic Evaluation of Presepsin for Sepsis-Related Acute Respiratory Distress Syndrome. Scientific Reports, 10, Article No. 9114. [Google Scholar] [CrossRef] [PubMed]
[8] Huang, L., Li, F., Gu, W. and Zhao, W. (2023) Clinical Value of the Serum Procalcitonin to Albumin Ratio in the Diagnosis and Prognosis of Sepsis-Associated ARDS Patients: A Retrospective Study. Annals of Clinical & Laboratory Science, 53, 946-958.
[9] Jones, T.K., Reilly, J.P., Anderson, B.J., Miano, T.A., Karanam, B., Ittner, C.A.G., et al. (2025) Soluble FMs-Like Tyrosine Kinase-1 Associates with Risk of Acute Respiratory Distress Syndrome and Mortality in Sepsis. Critical Care Explorations, 7, e1294. [Google Scholar] [CrossRef] [PubMed]
[10] Zhang, C., Huang, Q. and He, F. (2022) Correlation of Small Nucleolar RNA Host Gene 16 with Acute Respiratory Distress Syndrome Occurrence and Prognosis in Sepsis Patients. Journal of Clinical Laboratory Analysis, 36, e24516. [Google Scholar] [CrossRef] [PubMed]
[11] Bardají-Carrillo, M., Martín-Fernández, M., López-Herrero, R., Priede-Vimbela, J.M., Heredia-Rodríguez, M., Gómez-Sánchez, E., et al. (2024) Post-Operative Sepsis-Induced Acute Respiratory Distress Syndrome: Risk Factors for a Life-Threatening Complication. Frontiers in Medicine, 11, Article 1338542. [Google Scholar] [CrossRef] [PubMed]
[12] Yan, M., Tang, J., Liu, Y. and Hu, Z. (2025) Progress of Alveolar Macrophages in Biological Function and Acute Lung Injury/Acute Respiratory Distress Syndrome. Frontiers in Immunology, 16, Article 1683411. [Google Scholar] [CrossRef
[13] Alipanah-Lechner, N., Neyton, L., Sinha, P., Leroux, C., Bardillon, K., Carrillo, S.A., et al. (2025) Longitudinal Multi-Omic Signatures of ARDS and Sepsis Inflammatory Phenotypes Identify Pathways Associated with Mortality. Journal of Clinical Investigation. [Google Scholar] [CrossRef
[14] Song, L., Li, K., Chen, H. and Xie, L. (2024) Cell Cross-Talk in Alveolar Microenvironment: From Lung Injury to Fibrosis. American Journal of Respiratory Cell and Molecular Biology, 71, 30-42. [Google Scholar] [CrossRef] [PubMed]
[15] Little, I., Bersie, S., Redente, E.F., McCubbrey, A.L. and Tarling, E.J. (2025) Alveolar Macrophages: Guardians of the Alveolar Lipid Galaxy. Current Opinion in Lipidology, 36, 153-162. [Google Scholar] [CrossRef] [PubMed]
[16] Woo, Y.D., Jeong, D. and Chung, D.H. (2021) Development and Functions of Alveolar Macrophages. Molecules and Cells, 44, 292-300. [Google Scholar] [CrossRef] [PubMed]
[17] Malla, S., Sajeevan, K.A., Acharya, B., Chowdhury, R. and Saha, R. (2024) Dissecting Metabolic Landscape of Alveolar Macrophage. Scientific Reports, 14, Article No. 30383. [Google Scholar] [CrossRef] [PubMed]
[18] Wilson, M.E., McCandless, E.E., Olszewski, M.A. and Robinson, N.E. (2020) Alveolar Macrophage Phenotypes in Severe Equine Asthma. The Veterinary Journal, 256, Article ID: 105436. [Google Scholar] [CrossRef] [PubMed]
[19] Tamari, M., Del Bel, K.L., Ver Heul, A.M., Zamidar, L., Orimo, K., Hoshi, M., et al. (2024) Sensory Neurons Promote Immune Homeostasis in the Lung. Cell, 187, 44-61.e17. [Google Scholar] [CrossRef] [PubMed]
[20] Wang, D. and Cao, Q. (2022) SHP2 in Alveolar Macrophages Regulates Macrophage I Phenotype in Acute Lung Injury. International Journal of Toxicology, 41, 412-419. [Google Scholar] [CrossRef] [PubMed]
[21] Kang, J.S., Lee, Y., Lee, Y., Gil, D., Kim, M.J., Wood, C., et al. (2025) Generation of Induced Alveolar Assembloids with Functional Alveolar-Like Macrophages. Nature Communications, 16, Article No. 3346. [Google Scholar] [CrossRef] [PubMed]
[22] Beckmann, A., Grissmer, A., Meier, C. and Tschernig, T. (2020) Intercellular Communication between Alveolar Epithelial Cells and Macrophages. Annals of AnatomyAnatomischer Anzeiger, 227, Article ID: 151417. [Google Scholar] [CrossRef] [PubMed]
[23] Lim, P.N., Cervantes, M.M., Pham, L.K. and Rothchild, A.C. (2021) Alveolar Macrophages: Novel Therapeutic Targets for Respiratory Diseases. Expert Reviews in Molecular Medicine, 23, e18. [Google Scholar] [CrossRef] [PubMed]
[24] Feo-Lucas, L., Godio, C., Minguito de la Escalera, M., Alvarez-Ladrón, N., Villarrubia, L.H., Vega-Pérez, A., et al. (2023) Airway Allergy Causes Alveolar Macrophage Death, Profound Alveolar Disorganization and Surfactant Dysfunction. Frontiers in Immunology, 14, Article 1125984. [Google Scholar] [CrossRef] [PubMed]
[25] Huang, X., Cao, M. and Xiao, Y. (2023) Alveolar Macrophages in Pulmonary Alveolar Proteinosis: Origin, Function, and Therapeutic Strategies. Frontiers in Immunology, 14, Article 1195988. [Google Scholar] [CrossRef] [PubMed]
[26] Dong, Y., Arif, A.A., Guo, J., Ha, Z., Lee-Sayer, S.S.M., Poon, G.F.T., et al. (2020) CD44 Loss Disrupts Lung Lipid Surfactant Homeostasis and Exacerbates Oxidized Lipid-Induced Lung Inflammation. Frontiers in Immunology, 11, Article 29. [Google Scholar] [CrossRef] [PubMed]
[27] Jiang, W., Chen, Y., Yu, C., Zou, B., Lu, Y., Yang, Q., et al. (2024) Alveolar Epithelial Cells Shape Lipopolysaccharide‐induced Inflammatory Responses and Reprogramming of Alveolar Macrophages. European Journal of Immunology, 55, e2350378. [Google Scholar] [CrossRef] [PubMed]
[28] Kawasaki, T., Ikegawa, M. and Kawai, T. (2022) Antigen Presentation in the Lung. Frontiers in Immunology, 13, Article 860915. [Google Scholar] [CrossRef] [PubMed]
[29] Streeter, H.B. and Wraith, D.C. (2021) Manipulating Antigen Presentation for Antigen-Specific Immunotherapy of Autoimmune Diseases. Current Opinion in Immunology, 70, 75-81. [Google Scholar] [CrossRef] [PubMed]
[30] Yao, Y., Liu, Q., Adrianto, I., Wu, X., Glassbrook, J., Khalasawi, N., et al. (2020) Histone Deacetylase 3 Controls Lung Alveolar Macrophage Development and Homeostasis. Nature Communications, 11, Article No. 3822. [Google Scholar] [CrossRef] [PubMed]
[31] Zhang, S., Liu, Y., Zhang, X., Sun, Y. and Lu, Z. (2024) ANKRD22 Aggravates Sepsis-Induced ARDS and Promotes Pulmonary M1 Macrophage Polarization. Journal of Translational Autoimmunity, 8, Article ID: 100228. [Google Scholar] [CrossRef] [PubMed]
[32] Yu, J., Shang, C., Deng, X., Jia, J., Shang, X., Wang, Z., et al. (2024) Time-Resolved scRNA-Seq Reveals Transcription Dynamics of Polarized Macrophages with Influenza a Virus Infection and Antigen Presentation to T Cells. Emerging Microbes & Infections, 13, Article ID: 2387450. [Google Scholar] [CrossRef] [PubMed]
[33] Wang, S., Chen, Y., Hong, W., Li, B., Zhou, Y. and Ran, P. (2022) Chronic Exposure to Biomass Ambient Particulate Matter Triggers Alveolar Macrophage Polarization and Activation in the Rat Lung. Journal of Cellular and Molecular Medicine, 26, 1156-1168. [Google Scholar] [CrossRef] [PubMed]
[34] Hou, F., Xiao, J., Wang, H., Xiao, K., Yang, W., Zhao, D., et al. (2025) Alveolar Macrophage-Derived TGF-β Promotes Acute Lung Injury Recovery by Regulating Inflammatory Monocyte-Derived Macrophages. Journal of Advanced Research. [Google Scholar] [CrossRef
[35] Zhang, X., Luo, M., Zhang, J., Yao, Z., Zhu, J., Yang, S., et al. (2021) Carbon Nanotubes Promote Alveolar Macrophages toward M2 Polarization Mediated Epithelial-Mesenchymal Transition and Fibroblast-To-Myofibroblast Transdifferentiation. Nanotoxicology, 15, 588-604. [Google Scholar] [CrossRef] [PubMed]
[36] Farhat, A., Radhouani, M., Deckert, F., Zahalka, S., Pimenov, L., Fokina, A., et al. (2025) An Aging Bone Marrow Exacerbates Lung Fibrosis by Fueling Profibrotic Macrophage Persistence. Science Immunology, 10, eadk5041. [Google Scholar] [CrossRef] [PubMed]
[37] Chen, D., Wu, X., Yang, J. and Yu, L. (2019) Serum Plasminogen Activator Urokinase Receptor Predicts Elevated Risk of Acute Respiratory Distress Syndrome in Patients with Sepsis and Is Positively Associated with Disease Severity, Inflammation and Mortality. Experimental and Therapeutic Medicine, 18, 2984-2992.
[38] Zhang, J., Luo, Y., Wang, X., Zhu, J., Li, Q., Feng, J., et al. (2019) Global Transcriptional Regulation of STAT3-and MYC-Mediated Sepsis-Induced Ards. Therapeutic Advances in Respiratory Disease, 13. [Google Scholar] [CrossRef] [PubMed]
[39] Sun, M., Li, Y., Xu, G., Zhu, J., Lu, R., An, S., et al. (2024) Sirt3-Mediated Opa1 Deacetylation Protects against Sepsis-Induced Acute Lung Injury by Inhibiting Alveolar Macrophage Pro-Inflammatory Polarization. Antioxidants & Redox Signaling, 41, 1014-1030. [Google Scholar] [CrossRef] [PubMed]
[40] Liang, N., Wilson, C., Davis, B., Wolf, I., Qyli, T., Moy, J., et al. (2024) Modeling Lung Endothelial Dysfunction in Sepsis‐Associated ARDS Using a Microphysiological System. Physiological Reports, 12, e16134. [Google Scholar] [CrossRef] [PubMed]
[41] Feng, Z., Jing, Z., Li, Q., Chu, L., Jiang, Y., Zhang, X., et al. (2023) Exosomal STIMATE Derived from Type II Alveolar Epithelial Cells Controls Metabolic Reprogramming of Tissue-Resident Alveolar Macrophages. Theranostics, 13, 991-1009. [Google Scholar] [CrossRef] [PubMed]
[42] Tao, H., Xu, Y. and Zhang, S. (2022) The Role of Macrophages and Alveolar Epithelial Cells in the Development of Ards. Inflammation, 46, 47-55. [Google Scholar] [CrossRef] [PubMed]
[43] Bellani, G., Pham, T. and Laffey, J.G. (2020) Missed or Delayed Diagnosis of ARDS: A Common and Serious Problem. Intensive Care Medicine, 46, 1180-1183. [Google Scholar] [CrossRef] [PubMed]
[44] Sun, M., Zeng, Z., Xu, G., An, S., Deng, Z., Cheng, R., et al. (2023) Promoting Mitochondrial Dynamic Equilibrium Attenuates Sepsis-Induced Acute Lung Injury by Inhibiting Proinflammatory Polarization of Alveolar Macrophages. Shock, 60, 603-612. [Google Scholar] [CrossRef] [PubMed]
[45] Han, W., Tanjore, H., Liu, Y., Hunt, R.P., Gutor, S.S., Serezani, A.P.M., et al. (2023) Identification and Characterization of Alveolar and Recruited Lung Macrophages during Acute Lung Inflammation. The Journal of Immunology, 210, 1827-1836. [Google Scholar] [CrossRef] [PubMed]
[46] Kang, A., Ye, G., Afkhami, S., Aleithan, F., Singh, K., Dvorkin-Gheva, A., et al. (2024) LPS-Induced Lung Tissue-Resident Trained Innate Immunity Provides Differential Protection against Pneumococci and SARS-CoV-2. Cell Reports, 43, Article ID: 114849. [Google Scholar] [CrossRef] [PubMed]
[47] Yu, B., Jia, S., Chen, Y., Guan, R., Chen, S., Tang, W., et al. (2024) CXCL4 Deficiency Limits M4 Macrophage Infiltration and Attenuates Hyperoxia-Induced Lung Injury. Molecular Medicine, 30, Article No. 253. [Google Scholar] [CrossRef] [PubMed]
[48] Liang, J., Dai, W., Xue, S., Wu, F., Cui, E. and Pan, R. (2024) Recent Progress in Mesenchymal Stem Cell-Based Therapy for Acute Lung Injury. Cell and Tissue Banking, 25, 677-684. [Google Scholar] [CrossRef] [PubMed]
[49] Wang, F., Xie, C. and Wang, X. (2025) Mesenchymal Stem Cell Therapies for ARDS: Translational Promise and Challenges. Stem Cell Research & Therapy, 16, Article No. 504. [Google Scholar] [CrossRef
[50] Ruan, S., Huang, C., Chien, Y., Huang, C., Chien, J., Kuo, L., et al. (2021) Etiology-Associated Heterogeneity in Acute Respiratory Distress Syndrome: A Retrospective Cohort Study. BMC Pulmonary Medicine, 21, Article No. 183. [Google Scholar] [CrossRef] [PubMed]
[51] Sinha, P. and Bos, L.D. (2021) Pathophysiology of the Acute Respiratory Distress Syndrome: Insights from Clinical Studies. Critical Care Clinics, 37, 795-815. [Google Scholar] [CrossRef] [PubMed]
[52] Liao, Q., Pu, Y., Jin, X., Zhuang, Z., Xu, X., Ren, X., et al. (2023) Physiological and Clinical Variables Identify ARDS Classes and Therapeutic Heterogeneity to Glucocorticoids: A Retrospective Study. BMC Pulmonary Medicine, 23, Article No. 92. [Google Scholar] [CrossRef] [PubMed]
[53] Al-Husinat, L., Azzam, S., Al Sharie, S., Araydah, M., Battaglini, D., Abushehab, S., et al. (2025) A Narrative Review on the Future of ARDS: Evolving Definitions, Pathophysiology, and Tailored Management. Critical Care, 29, Article No. 88. [Google Scholar] [CrossRef] [PubMed]
[54] Wu, L., Lei, Q., Gao, Z. and Zhang, W. (2022) Research Progress on Phenotypic Classification of Acute Respiratory Distress Syndrome: A Narrative Review. International Journal of General Medicine, 15, 8767-8774. [Google Scholar] [CrossRef] [PubMed]
[55] Ma, W., Tang, S., Yao, P., Zhou, T., Niu, Q., Liu, P., et al. (2025) Advances in Acute Respiratory Distress Syndrome: Focusing on Heterogeneity, Pathophysiology, and Therapeutic Strategies. Signal Transduction and Targeted Therapy, 10, Article No. 75. [Google Scholar] [CrossRef] [PubMed]
[56] Doncheva, N.T., Palasca, O., Yarani, R., Litman, T., Anthon, C., Groenen, M.A.M., et al. (2021) Human Pathways in Animal Models: Possibilities and Limitations. Nucleic Acids Research, 49, 1859-1871. [Google Scholar] [CrossRef] [PubMed]
[57] Casel, M.A.B., Rollon, R.G. and Choi, Y.K. (2021) Experimental Animal Models of Coronavirus Infections: Strengths and Limitations. Immune Network, 21, e12. [Google Scholar] [CrossRef] [PubMed]
[58] Varona, L. and González-Recio, O. (2023) Invited Review: Recursive Models in Animal Breeding: Interpretation, Limitations, and Extensions. Journal of Dairy Science, 106, 2198-2212. [Google Scholar] [CrossRef] [PubMed]
[59] Kanwisher, N. (2025) Animal Models of the Human Brain: Successes, Limitations, and Alternatives. Current Opinion in Neurobiology, 90, Article ID: 102969. [Google Scholar] [CrossRef] [PubMed]
[60] Stensland, K.D., DePorto, K., Ryan, J., Kaffenberger, S., Reinstatler, L.S., Galsky, M., et al. (2021) Estimating the Rate and Reasons of Clinical Trial Failure in Urologic Oncology. Urologic Oncology: Seminars and Original Investigations, 39, 154-160. [Google Scholar] [CrossRef] [PubMed]
[61] Sarma, A., Calfee, C.S. and Ware, L.B. (2020) Biomarkers and Precision Medicine: State of the Art. Critical Care Clinics, 36, 155-165. [Google Scholar] [CrossRef] [PubMed]
[62] Wang, N., Huang, H., Tan, Y. and Zhang, N. (2025) Research Progress of Biomarkers for Sepsis and Precision Medicine. Emergency Medicine International, 2025, Article ID: 4585495. [Google Scholar] [CrossRef] [PubMed]
[63] Wal, A., Wal, P., Vig, H., Samad, A., Khandai, M. and Tyagi, S. (2024) A Systematic Review of Various In-Vivo Screening Models as Well as the Mechanisms Involved in Parkinson’s Disease Screening Procedures. Current Reviews in Clinical and Experimental Pharmacology, 19, 124-136. [Google Scholar] [CrossRef] [PubMed]
[64] Li, B., Zhang, Q., Liu, Y., Zhang, X., Cheng, D., Li, A., et al. (2021) Analysis of the Reasons for Screening Failure in Phase I Clinical Trials in China: A Retrospective Study of the Clinical Trials Screening Process. Annals of Translational Medicine, 9, 1564-1564. [Google Scholar] [CrossRef] [PubMed]
[65] Rivero-de-Aguilar, A., Pérez-Ríos, M., Ross, J.S., Mascareñas-García, M., Ruano-Raviña, A. and Varela-Lema, L. (2025) Determinants of Clinical Trial Failure in Multiple Sclerosis: Insights from ClinicalTrials.gov. [Google Scholar] [CrossRef