Evidence map›Paper›PMID 42801161›Full record

ArticleJournal of inflammation research2026

Identification of Immune-Inflammatory Endotypes in Early COPD Risk: A Cluster Analysis of Age-Associated Biomarkers.

Biying Wu, Min Yang, Xiaoying Hu, Wencai Ke, Qiudan Chen, Yong Lin

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Article in Journal of inflammation research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Biying Wu *Department of Clinical Laboratory Medicine, Shanghai Fifth People's Hospital, Fudan University, Shanghai, People's Republic of China.
Min Yang *Division of Endocrinology, Shanghai Fifth People's Hospital, Fudan University, Shanghai, People's Republic of China.
Xiaoying HuJiangchuan Community Health Service Center of Minhang District, Shanghai, People's Republic of China.
Wencai KeDepartment of Clinical Laboratory Medicine, Shanghai Fifth People's Hospital, Fudan University, Shanghai, People's Republic of China.
Qiudan ChenDepartment of Clinical Laboratory, Central Laboratory, Jing'an District Center Hospital of Shanghai, Fudan University, Shanghai, People's Republic of China.
Yong LinDepartment of Clinical Laboratory Medicine, Shanghai Fifth People's Hospital, Fudan University, Shanghai, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic obstructive pulmonary disease (COPD) is increasingly recognized as a highly heterogeneous syndrome rather than a single disease entity. Identifying biologically distinct endotypes is essential for early risk stratification and precision prevention. Immunosenescence-the age-related remodeling of the immune system-has been associated with COPD pathogenesis, but its heterogeneity remains poorly characterized. Methods: We employed a two-stage discovery‑validation design. The discovery cohort included 439 healthy adults (2019-2020), in whom age‑associated immune biomarkers were identified using Spearman correlation. The validation cohort comprised 89 community‑dwelling adults (2023-2024), including 34 healthy controls and 55 individuals at high risk for COPD (COPD‑SQ ≥ 16, preserved lung function). Biomarkers that were both age‑associated and differentially expressed between groups were selected for further analysis. To investigate the inherent heterogeneity of immune‑inflammatory profiles, we performed unsupervised k‑means clustering and principal component analysis (PCA) on these selected biomarkers in the validation cohort. The association between cluster membership and COPD high‑risk status was assessed using logistic regression. Results: Four cytokines (IL‑4, IL‑5, IL‑6, IL‑12p70) were significantly correlated with age and differentially elevated in the high‑risk group. Unsupervised clustering identified three distinct immune‑inflammatory endotypes: a high‑inflammatory endotype (n = 13, 100% high‑risk), a moderate‑inflammatory endotype (n = 29, 89.7% high‑risk), and a low‑inflammatory endotype (n = 45, 35.6% high‑risk). Using the low‑inflammatory endotype as reference, both high‑inflammatory (unadjusted Conclusion: This study identifies three distinct immune‑inflammatory endotypes in a community‑based population at risk for COPD, with the high‑ and moderate‑inflammatory endotypes showing strong, independent associations with high‑risk status. These findings reveal the biological heterogeneity of immunosenescence and provide a framework for endotype‑based risk stratification in early COPD. The results highlight the potential of cluster‑derived immune profiles to inform targeted prevention strategies.

Indexed as

chronic obstructive pulmonary diseasecluster analysisdisease heterogeneityendotypeimmunosenescencerisk stratification

Identifiers

PMID42801161
PMCPMC13615830

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.