Evidence mapPaperPMID 41663970Full record

ArticleBMC cardiovascular disorders2026

Unraveling key genes and mitochondrial-related mechanisms of atherosclerosis severity: explorations based on interpretable machine learning.

De Zhao Kong, Xue Zhi Zhang, Yuan Yuan Zhou, Qun Wang, Yi Hui Pan, Yi Lu, Hui Ye, Xiong Yi Hong

Abstract read
In one paragraph

Article in BMC cardiovascular disorders, 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. Review
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.

De Zhao KongPeking University First Hospital, Beijing, China.
Xue Zhi ZhangPeking University First Hospital, Beijing, China. Zhang.xuezhi@263.net.
Yuan Yuan ZhouLiaoning University of Traditional Chinese Medicine, Shenyang, China. 2926749470@qq.com.
Qun WangLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Yi Hui PanLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Yi LuTiantai Hospital of Traditional Chinese Medicine, Taizhou, China.
Hui YePeking University First Hospital, Beijing, China.
Xiong Yi HongPeking University International Hospital, Beijing, China.

Funding

China Postdoctoral Science Foundation 2021M703618National Natural Science Foundation of China (NSFC) 81803978Science and Technology Research Project of the Department of Education of Liaoning Province L201713Shanxi Province Health Commission Traditional Chinese Medicine Research Project Plan 2025ZYYB087Shanxi Provincial Administration of Traditional Chinese Medicine Chinese Medicine Innovation Team Building Program zyytd2024030Shenyang Youth Science and Technology Innovation Talent Support Program RC200104The construction project of the Shanxi Province Key Laboratory, "Multidisciplinary Cross-Research Laboratory for the Prevention and Treatment of Diseases Caused by Damp-Heat Pathogens" zyyyjs2024026The Qi-Huang Scholar Chief Scientist Program of National Administration of Traditional Chinese Medicine Leading Talents Support Program (2021) National Administration of Traditional Chinese Medicine, Letter No. 6 [2022]Young Elite Scientists Sponsorship Program by CACM 2022-QNRC2-B05
6 · The paper itself

Abstract

backgroundDysfunctional mitochondria increase oxidative stress and inflammation, driving atherosclerosis. Understanding gene expression and regulatory mechanisms is crucial.

objectiveThis study aims to identify key mitochondrial dysfunction-related genes (MitoDEGs) associated with atherosclerotic plaque severity, elucidate their molecular mechanisms and immune-regulatory roles in disease progression, and validate pivotal biomarkers to provide mechanistic insights for personalized therapeutic strategies.

methodsWe utilized eight atherosclerotic plaque datasets (human samples) from GEO and mitochondrial gene data from MitoCarta3.0. Lasso Regression and the Shap algorithm were employed to identify key differentially expressed mitochondrial genes (MitoDEGs) for model construction. Enriched pathways were analyzed using GO and KEGG databases, and protein–protein interactions were explored with STRING and Cytoscape. Experimental validation was conducted using atherosclerosis mouse models and HUVEC cell models.

resultsThis study identified distinct and shared mitochondrial dysfunction-related genes (MitoDEGs) in carotid and peripheral atherosclerotic plaques. Key carotid-specific MitoDEGs included HK3 and BID, while peripheral-specific ones included RAC2 and TCL1A. Two common MitoDEGs, GZMB and PMAIP1, were found in both plaque types. Enrichment analyses revealed novel associations with mitochondrial pathways including apoptosis, p53 signaling, hexose metabolism, and protein serine/threonine kinase regulation. Importantly, these MitoDEGs are mechanistically linked to mitochondrial outer membrane integrity and metabolic reprogramming. Experimental validation confirmed the upregulation of core MitoDEGs (CASP1, BID, PMAIP1, and GZMB), highlighting their critical roles in mitochondrial dysfunction during atherosclerosis progression.

conclusionThis study underscores the critical role of mitochondrial dysfunction, mediated by specific MitoDEGs, in atherosclerosis progression. The identified genes modulate both mitochondrial apoptotic pathways and immune cell infiltration, contributing to plaque severity. These shared and location-specific MitoDEGs offer novel mechanistic insights and represent potential therapeutic targets for intervening in plaque development and achieving personalized management of atherosclerotic disease.

Indexed as

AtherosclerosisCarotid Artery DiseasesGenes, MitochondrialMachine LearningMitochondriaPlaque, AtheroscleroticAnimalsDatabases, GeneticDisease Models, AnimalGene Expression ProfilingGene Regulatory NetworksGenetic Predisposition to DiseaseHumansHuman Umbilical Vein Endothelial CellsMiceMice, Knockout, ApoEAtherosclerosisImmune infiltrationInterpretable machine learningMetabolic reprogrammingMitochondrial dysfunction

Identifiers

PMID41663970
PMCPMC12983607

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.