Evidence map›Paper›PMID 41639521›Full record

ArticleJournal of cardiovascular translational research2026

Single-cell Transcriptomic Profiling Reveals Diagnostic of T Cell-platelet Aggregates in Peripheral Blood for Coronary Vulnerable Plaques.

Diru Yao, Peina Meng, Bin Huang, Rongrong Wu, Zihan Lin, Kening Li, Lingxiang Wu, Peng Xia, Quanzhong Liu, Wei Wu and 3 more

Abstract read
In one paragraph

Article in Journal of cardiovascular translational 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.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Diru Yao *Department of Bioinformatics, Nanjing Medical University, Nanjing, 211166, China.
Peina Meng *Department of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China.
Bin HuangDepartment of Bioinformatics, Nanjing Medical University, Nanjing, 211166, China.
Rongrong WuDepartment of Bioinformatics, Nanjing Medical University, Nanjing, 211166, China.
Zihan LinDepartment of Bioinformatics, Nanjing Medical University, Nanjing, 211166, China.
Kening LiDepartment of Bioinformatics, Nanjing Medical University, Nanjing, 211166, China.
Lingxiang WuDepartment of Bioinformatics, Nanjing Medical University, Nanjing, 211166, China.
Peng XiaDepartment of Bioinformatics, Nanjing Medical University, Nanjing, 211166, China.
Quanzhong LiuDepartment of Bioinformatics, Nanjing Medical University, Nanjing, 211166, China.
Wei WuDepartment of Bioinformatics, Nanjing Medical University, Nanjing, 211166, China.
Shukui WangJiangsu Collaborative Innovation Center On Cancer Personalized Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China. shukwang@163.com.
Qianghu WangDepartment of Bioinformatics, Nanjing Medical University, Nanjing, 211166, China. wangqh@njmu.edu.cn.ORCID 0000-0002-3488-1059
Fei YeDepartment of Cardiology, Nanjing First Hospital, Nanjing Medical University, Nanjing, 210006, China. doctor_ye@126.com.

Funding

National Science Foundation 82372897National Science Foundation 91959113
6 · The paper itself

Abstract

Acute coronary syndrome, driven by vulnerable plaque (VP) instability, is a major cause of cardiovascular mortality. Current diagnostic methods for VPs are limited by invasiveness or low specificity, highlighting the need for non-invasive biomarkers. Using single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from coronary artery disease (CAD) patients with VPs and controls, we identified circulating T cell-platelet aggregates (TPAs) significantly enriched in VP patients and linked to plaque instability via pro-inflammatory pathways. Through high dimensional weighted gene co-expression network analysis, we discovered TPAs' hub genes and demonstrated their role in plaque destabilization. Furthermore, employing machine learning, including Boruta, least absolute shrinkage and selection operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), we screened for five blood biomarkers that can serve as diagnostic indicators for VPs. Our study demonstrates that TPAs are critically involved in VPs formation. Furthermore, we identified EPHB6, STAT1, RPL23, IKZF3 and AHCY as potential circulating biomarkers for non-invasive detection of VPs.

Indexed as

Blood PlateletsCoronary Artery DiseaseGene Expression ProfilingPlaque, AtheroscleroticRNA-SeqSingle-Cell AnalysisT-LymphocytesTranscriptomeAgedBiomarkersCase-Control StudiesFemaleHumansMaleMiddle AgedPredictive Value of TestsBiomarkersCoronary vulnerable plaqueDiagnostic biomarkerMachine learningScRNA-seqT cell-platelet aggregates

Identifiers

PMID41639521
PMCPMC12872752

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.