Evidence map›Paper›PMID 38660376›Full record

ArticleFrontiers in molecular biosciences2024

Transcriptomic analysis identifies the shared diagnostic biomarkers and immune relationship between Atherosclerosis and abdominal aortic aneurysm based on fatty acid metabolism gene set.

Xuefeng Gu, Zhongxian Yu, Tianwei Qian, Yiqi Jin, Guoxiong Xu, Jiang Li, Jianfeng Gu, Ming Li, Ke Tao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

6 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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  4. Identification of genetic biomarkers of blood cholesterol levels using whole gene pathogenicity modelling.Mammalian genome : official journal of the International Mammalian Genome Society · 2025
    Article
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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

9 authors at 2 institutions in 1 country.

Xuefeng Gu *Department of General Surgery, Changshu Hospital Affiliated to Soochow University, Changshu, Jiangsu Province, China.
Zhongxian Yu *Department of General Surgery, Changshu Hospital Affiliated to Soochow University, Changshu, Jiangsu Province, China.
Tianwei QianDepartment of General Surgery, Changshu Hospital Affiliated to Soochow University, Changshu, Jiangsu Province, China.
Yiqi JinDepartment of General Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province, China.
Guoxiong XuDepartment of General Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province, China.
Jiang LiDepartment of General Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, Jiangsu Province, China.
Jianfeng GuDepartment of General Surgery, Changshu Hospital Affiliated to Soochow University, Changshu, Jiangsu Province, China.
Ming LiDepartment of General Surgery, Changshu Hospital Affiliated to Soochow University, Changshu, Jiangsu Province, China.
Ke TaoDepartment of General Surgery, Changshu Hospital Affiliated to Soochow University, Changshu, Jiangsu Province, China.
Soochow University · CNNanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Epidemiological research has demonstrated that there is a connection between lipid metabolism disorder and an increased risk of developing arteriosclerosis (AS) and abdominal aortic aneurysm (AAA). However, the precise relationship between lipid metabolism, AS, and AAA is still not fully understood. The objective of this study was to examine the pathways and potential fatty acid metabolism-related genes (FRGs) that are shared between AS and AAA. Methods: AS- and AAA-associated datasets were retrieved from the Gene Expression Omnibus (GEO) database, and the limma package was utilized to identify differentially expressed FRGs (DFRGs) common to both AS and AAA patients. Functional enrichment analysis was conducted on the (DFRGs), and a protein-protein interaction (PPI) network was established. The selection of signature genes was performed through the utilization of least absolute shrinkage and selection operator (LASSO) regression and random forest (RF). Subsequently, a nomogram was developed using the results of the screening process, and the crucial genes were validated in two separate external datasets (GSE28829 and GSE17901) as well as clinical samples. In the end, single-sample gene set enrichment analysis (ssGSEA) was utilized to assess the immune cell patterns in both AS and AAA. Additionally, the correlation between key crosstalk genes and immune cell was evaluated. Results: In comparison to control group, both AS and AAA patients exhibited a decrease in fatty acid metabolism score. We found 40 DFRGs overlapping in AS and AAA, with lipid and amino acid metabolism critical in their pathogenesis. PCBD1, ACADL, MGLL, BCKDHB, and IDH3G were identified as signature genes connecting AS and AAA. Their expression levels were confirmed in validation datasets and clinical samples. The analysis of immune infiltration showed that neutrophils, NK CD56dim cells, and Tem cells are important in AS and AAA development. Correlation analysis suggested that these signature genes may be involved in immune cell infiltration. Conclusion: The fatty acid metabolism pathway appears to be linked to the development of both AS and AAA. Furthermore, PCBD1, ACADL, MGLL, BCKDHB, and IDH3G have the potential to serve as diagnostic markers for patients with AS complicated by AAA.

Indexed as

abdominal aortic aneurysmAtherosclerosisbioinformaticsdiagnostic biomarkerlipid metabolism disorder

Identifiers

PMID38660376
PMCPMC11040089
OpenAlexW4394684833

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.