Evidence map›Paper›PMID 42323884›Full record

ArticleAnnals of medicine2026

Plasma proteomics reveal SERPINA1 and CD59 as candidate biomarkers for COVID-19 severity stratification and prognosis prediction.

Zizhen Zhou, Qiwei Liu, Shuangshuang Ma, Anke Shi, Yuzhi Tao, Tianpeng Hu, Shengtao Yan, Yinong Chen, Xiaofan Ji, Lu Sun and 5 more

Abstract read
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Article in Annals of medicine, 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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

15 authors.

Zizhen ZhouState Key Laboratory of Respiratory Health and Multimorbidity, Department of Physiology, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Qiwei LiuState Key Laboratory of Respiratory Health and Multimorbidity, Department of Physiology, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Shuangshuang MaNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Anke ShiNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Yuzhi TaoNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Tianpeng HuDepartment of Emergency Medicine, China-Japan Friendship Hospital, Beijing, China.
Shengtao YanDepartment of Emergency Medicine, China-Japan Friendship Hospital, Beijing, China.
Yinong ChenNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Xiaofan JiNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Lu SunNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Hong ZhangState Key Laboratory of Respiratory Health and Multimorbidity, Department of Physiology, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Wanlu SongState Key Laboratory of Respiratory Health and Multimorbidity, Department of Physiology, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Zhu ZhangNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.
Peiran YangState Key Laboratory of Respiratory Health and Multimorbidity, Department of Physiology, Institute of Basic Medical Sciences & School of Basic Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Zhenguo ZhaiNational Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College; Department of Pulmonary and Critical Care Medicine, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China.ORCID 0000-0002-7096-8792

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19 has been closely associated with coagulation abnormalities. However, existing biomarkers, including D-dimer and fibrin degradation products (FDP), exhibit limited accuracy in stratifying disease severity and predicting long-term clinical outcomes.

objectivesThis study aimed to use proteomic analysis to identify plasma biomarkers associated with COVID-19 severity and prognosis, and validate their predictive utility for mortality and thromboembolic complications.

methodsPlasma proteomic profiles were analyzed across three COVID-19 severity classes. Differential expression analysis and functional analysis were performed. Clustering analysis was used to identify proteins correlated with disease severity. Candidate biomarkers were validated in an independent cohort. Predictive performance of the biomarkers for mortality, sepsis and venous thromboembolism was evaluated using bootstrap-corrected ROC analyses and multivariable regression analyses.

resultsProteomic analysis revealed progressive involvement of the coagulation and complement pathway with increasing disease severity. SERPINA1 and CD59 were identified as candidate biomarkers and exhibited significantly higher plasma levels in severe cases. Bootstrap-corrected ROC analyses demonstrated strong predictive performance: SERPINA1 achieved AUCs of 0.775 and 0.924 for 30-day and 12-month mortality, and CD59 achieved AUCs of 0.720 for sepsis; the combined model further improved prediction of 12-month mortality (AUC 0.946) and sepsis (AUC 0.904), outperforming D-dimer and FDP. Multivariable regression confirmed their independent prognostic value.

conclusionThis exploratory study identifies SERPINA1 and CD59 as candidate prognostic biomarkers in COVID-19, highlighting the role of coagulation and complement-related pathways in disease severity and warranting further prospective validation.

Indexed as

CD59 AntigensCOVID-19Plasminogen Activator Inhibitor 1Agedalpha 1-AntitrypsinBiomarkersFemaleFibrin Fibrinogen Degradation ProductsHumansMaleMiddle AgedPredictive Value of TestsPrognosisProteomicsSARS-CoV-2Sepsisalpha 1-AntitrypsinBiomarkersCD59 AntigensCD59 protein, humanFibrin Fibrinogen Degradation Productsfibrin fragment DPlasminogen Activator Inhibitor 1SERPINA1 protein, humanCoagulation markerCOVID-19mortality predictionproteomicsvenous thromboembolism

Identifiers

PMID42323884
PMCPMC13288725

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