Evidence map›Paper›PMID 42900662›Full record

ArticlePLoS medicine2026

Plasma proteomic signatures of subclinical atherosclerosis progression for cardiovascular risk stratification: A cohort study.

Yani Huang, Ruixin Gao, Jianxin Li, Bin Yang, Keyong Huang, Shufeng Chen, Jie Cao, Xiaoqing Liu, Chong Shen, Ling Yu and 8 more

Abstract read
In one paragraph

Article in PLoS medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Yani HuangDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0009-0002-9580-7415
Ruixin GaoDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jianxin LiDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0001-9166-642X
Bin YangDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Keyong HuangDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Shufeng ChenDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jie CaoDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0009-0008-1912-4106
Xiaoqing LiuDivision of Epidemiology, Guangdong Provincial People's Hospital and Cardiovascular Institute, Guangzhou, China.ORCID https://orcid.org/0000-0003-0079-9716
Chong ShenDepartment of Epidemiology and Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.ORCID https://orcid.org/0000-0001-6447-6591
Ling YuDepartment of Cardiology, Fujian Provincial Hospital, Fuzhou, China.
Liancheng ZhaoDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Ying LiDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Dongsheng HuDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, Zhengzhou, China.ORCID https://orcid.org/0000-0002-9998-8041
Jianfeng HuangDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Bin LuDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Dongfeng GuDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0002-2781-7825
Fangchao LiuDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0001-6316-4481
Xiangfeng LuDepartment of Epidemiology, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0003-4088-2338

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundExisting risk stratification tools inadequately identify individuals with subclinical atherosclerosis (SA) who could benefit from early intervention. This study aimed to develop protein risk scores (ProtRSs) for SA progression and assess their incremental value for atherosclerotic cardiovascular disease (ASCVD) risk prediction. METHODS AND

findingsIn a community cohort consisting of 903 individuals undergoing repeated SA assessments (coronary artery calcium [CAC] or carotid plaque) over 6 years (2008-2009 to 2013-2014), protein biomarkers were selected from a panel of 117 proteins using least absolute shrinkage and selection operator (LASSO) regression to construct SA ProtRSs for CAC and plaque progression, respectively, and their predictive abilities for incident ASCVD risk were evaluated based on a guideline-recommended traditional risk score in a case-cohort of 1,835 individuals (2007-2008 to 2018-2021, median follow-up of 10.4 years). The ProtRSs each included 14 proteins for CAC and plaque progression, explaining 17.1% and 18.4% of respective variances. Effect sizes of these proteins on SA progression showed strong concordance with those on incident ASCVD (r  > 0.75). Each standard deviation increase in CAC and plaque ProtRSs was associated with hazard ratios of 1.36 (95% confidence interval [CI] [1.20,1.54]) and 1.38 (95% CI [1.23,1.54]) for ASCVD risk, respectively. Addition of the SA ProtRSs to the traditional risk score yielded a net reclassification improvement of 0.127 (p < 0.001). Importantly, 18.6% of traditional intermediate-risk individuals were reclassified into the high-risk category (10-year ASCVD event rate: 10.9%), indicating the need for preventive interventions, whereas 32.8% of traditional high-risk individuals were identified as having an even higher rate (13.7%), suggesting the requirement for intensified management. The main limitation is that the predictive value of ProtRSs warrants further large-scale external validation.

conclusionsSA ProtRSs of coronary calcification and carotid plaque progression may provide additional value over traditional risk assessment, highlighting their potential in refining risk stratification and guiding targeted intervention strategies.

Indexed as

AtherosclerosisCoronary Artery DiseaseProteomicsAgedBiomarkersCohort StudiesDisease ProgressionFemaleHumansMaleMiddle AgedPlaque, AtheroscleroticRisk AssessmentRisk FactorsBiomarkers

Identifiers

PMID42900662
PMCPMC13682661

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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 OpenQuestion graph.