Evidence map›Paper›PMID 40059128›Full record

ArticleScientific reports2025

Elucidating the role of KCTD10 in coronary atherosclerosis: Harnessing bioinformatics and machine learning to advance understanding.

Xiaomei Hu, Fanqi Liang, Man Zheng, Juying Xie, Shanxi Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

5 authors.

Xiaomei HuCollege of Medical Imaging Laboratory and Rehabilitation, Xiangnan University, Chenzhou, 423000, Hunan, China.
Fanqi LiangThe First Affiliated Hospital of Hunan University of Traditional Chinese Medicine, Changsha, 410007, Hunan, China.
Man ZhengDongying People'S Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying, Shandong, 257091, People's Republic of China.
Juying Xie *College of Medical Imaging Laboratory and Rehabilitation, Xiangnan University, Chenzhou, 423000, Hunan, China. 597189746@qq.com.
Shanxi Wang *College of Medical Imaging Laboratory and Rehabilitation, Xiangnan University, Chenzhou, 423000, Hunan, China. evy_i@qq.com.

Funding

Hunan Youth Natural Science Foundation 2022JJ40316
6 · The paper itself

Abstract

Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly compromises vascular health and serves as a major contributor to cardiovascular diseases. KCTD10, a protein implicated in a variety of biological processes, has garnered significant attention for its role in cardiovascular diseases and metabolic regulation. As a member of the KCTD protein family, KCTD10 is characterized by the presence of a T1 domain that interacts with voltage-gated potassium channels, a critical interaction for modulating channel activity and intracellular signal transduction. In our study, KCTD10 was identified as a focal point through an integrative analysis of differentially expressed genes (DEGs) across multiple datasets (GSE43292 and GSE9820) from the GEO database, aligned with immune-related gene sets from the ImmPort database. Advanced analytical tools, including Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE), were employed to refine our gene selection. We further applied Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) to these gene sets, revealing significant enrichment in immune-related pathways. The relationship between KCTD10 expression and immune processes was examined using CIBERSORT and ESTIMATE algorithms to assess tumor microenvironment characteristics, suggesting increased immune cell infiltration associated with higher KCTD10 expression. Validation of these findings was conducted using data from the GSE9820 dataset. Among 10 DEGs linked with KCTD10, 13 were identified as hub genes through LASSO and SVM-RFE analyses. Functional assays highlighted KCTD10's role in enhancing viral defense mechanisms, cytokine production, and immune cascades. Notably, KCTD10 expression correlated positively with several immune cells, including naive CD4 + T cells, eosinophils, resting NK cells, neutrophils, M0 macrophages, and particularly M1 macrophages, indicating a significant association. This research elucidates the complex relationship between KCTD10 and AS, underscoring its potential as a novel biomarker for diagnosing and monitoring the disease. Our findings provide a solid foundation for further investigations, suggesting that targeting KCTD10-related pathways could markedly advance our understanding and management of AS, offering new avenues for therapeutic intervention.

Indexed as

Computational BiologyCoronary Artery DiseaseMachine LearningPotassium Channels, Voltage-GatedDatabases, GeneticGene Expression ProfilingHumansPotassium Channels, Voltage-GatedAutoimmune inflammatory disorderCoronary Atherosclerosis (AS)KCTD10Lasso regressionSVM-RFE

Identifiers

PMID40059128
PMCPMC11891306

What Socratic holds

Textmetadata
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.