Evidence mapPaperPMID 39959637Full record

ArticleJournal of inflammation research2025

Identification of Potential Diagnostic Biomarkers of Carotid Atherosclerosis in Obese Populations.

Xize Wu, Jiaxiang Pan, Xue Pan, Jian Kang, Jiaqi Ren, Yuxi Huang, Lihong Gong, Yue Li

Abstract read
In one paragraph

Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Xize Wu *Graduate School, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110847, People's Republic of China.ORCID 0000-0002-0535-4583
Jiaxiang Pan *Department of Cardiology, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110032, People's Republic of China.
Xue Pan *Graduate School, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110847, People's Republic of China.
Jian KangGraduate School, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110847, People's Republic of China.
Jiaqi RenGraduate School, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110847, People's Republic of China.
Yuxi HuangGraduate School, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110847, People's Republic of China.
Lihong GongDepartment of Cardiology, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110032, People's Republic of China.
Yue LiDepartment of Cardiology, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, 110032, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to investigate the potential mechanisms and biomarkers between Obesity (OB) and carotid atherosclerosis (CAS). Methods: The GSE12828, GSE125771, GSE43292, and GSE100927 datasets were combined and normalized to obtain CAS-related differentially expressed genes (DEGs), and OB-related DEGs were obtained from the GSE151839 dataset and the GeneCards database. Unsupervised cluster analysis was conducted on CAS samples based on the DEGs of CAS and OB. Subsequently, immune infiltration analysis and gene set enrichment analysis (GESA) were performed. 61 machine learning models were developed to screen for Hub genes. The Single-gene GESA focused on calcium signaling pathway-related genes (CaRGs). Finally, high-fat diet-fed C57BL/6J ApoE Results: MMP9, PLA2G7, and SPP1 as regulators of the immune infiltration microenvironment in OB patients with CAS, and stratified CAS samples into subtypes with differences in metabolic pathways based on OB classification. Enrichment analysis indicated abnormalities in immune and inflammatory responses, the calcium signaling, and lipid response in obese CAS patients. The RF+GBM model identified CD52, CLEC5A, MMP9, and SPP1 as Hub genes. 15 CaRGs were up-regulated, and 12 were down-regulated in CAS and OB. PLCB2, PRKCB, and PLCG2 were identified as key genes in the calcium signaling pathway associated with immune cell infiltration. In vivo experiments showed that MMP9, PLA2G7, CD52, SPP1, FYB, and PLCB2 mRNA levels were up-regulated in adipose, aortic tissues and serum of OB and AS model mice, CLEC5A was up-regulated in aorta and serum, and PRKCB was up-regulated in adipose and serum. Conclusion: MMP9, PLA2G7, CD52, CLEC5A, SPP1, and FYB may serve as potential diagnostic biomarkers for CAS in obese populations. PLCB2 and PRKCB are key genes in the calcium signaling pathway in OB and CAS. These findings offer new insights into clinical management and therapeutic strategies for CAS in obese individuals.

Indexed as

bioinformaticscalcium signaling pathwaycarotid atherosclerosismachine learning modelobesityunsupervised clustering analysis

Identifiers

PMID39959637
PMCPMC11829119

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.