{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T16:52:26Z","timestamp":1786121546997,"version":"build-2736575974"},"reference-count":57,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T00:00:00Z","timestamp":1786060800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Med."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Chronic obstructive pulmonary disease (COPD) is a chronic pulmonary disease, with aging and secondhand smoke exposure serving as 2 major risk factors. Serum C-reactive protein (SCRP), a canonical marker of systemic inflammation, has been implicated in COPD progression, but its specific molecular signatures and pathogenic pathways in the context of aging and SHS have not been systematically delineated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Cross-sectional data from 7864 COPD patients in NHANES 2017\u20132020 were analyzed for exploration of SCRP association with aging male COPD pathogenesis exposure to SHS. Next, we leveraged bulk COPD public peripheral blood transcriptomic data (GSE248493, GSE55962) with Limma, WGCNA, and GSVA to identify SHS and SCRP (SS)-associated DEGs for COPD patients. Next, An interpretable 132 machine learning models, integrated with NMF analysis was then employed to establish a diagnostic model, categorize patient subgroups, and pinpoint a hub gene linked to the SS signature across multiple independent COPD bulk cohorts (GSE77344, GSE42057, integrated GSE1455871, and GSE126923). Using a COPD single-cell dataset (GSE167295), advanced analytical approaches, including scTenifoldKnk and AUCell, mapped the spatial and temporal evolution of SS-related hub molecular patterns in COPD pathogenesis. Candidate therapeutics were identified through deep learning framework (DrugReflector) and the cMAP database, followed by molecular docking analysis. Finally, hub gene expression was experimentally confirmed via q-RT-PCR in peripheral blood specimens collected from COPD patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>SCRP is potentially associated with COPD pathogenesis in aging and SHS exposure male group, and a SS-associated DEGs can guide diagnostic and molecular stratification models for COPD patients, and DDX41 can be considered as up-regulated pathogenic factor, which was mainly distributed in macrophage. Compound BRD-K19642661 was identified as a potential DDX41-targeting agent for COPD patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Integrating SS can be considered as clinical and molecular target for COPD risk prediction.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2026.1922619","type":"journal-article","created":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T05:28:50Z","timestamp":1786080530000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Decoding serum C-reactive protein-associated molecular patterns in aging and secondhand smoke exposure chronic obstructive pulmonary disease male patients: evidence from cross-sectional, multi-omic and clinical 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