Evidence map›Paper›PMID 40153770›Full record

ArticleMedicine2025

Identification of aberrantly expressed genes during aging in the mouse heart via integrated bioinformatics analysis.

Pianpian Huang, Jun Fu, Ji Hu, Yinghong Lei, Tingyu Wu, Ju Liu

Abstract read
In one paragraph

Article in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

6 authors.

Pianpian HuangDepartments of Geriatrics, Wuhan No. 1 Hospital, Wuhan, China.
Jun FuDepartments of Radiology, Wuhan No. 1 Hospital, Wuhan, China.
Ji HuDepartment of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yinghong LeiDepartments of Geriatrics, Wuhan No. 1 Hospital, Wuhan, China.
Tingyu WuDepartments of Geriatrics, Wuhan No. 1 Hospital, Wuhan, China.
Ju LiuDepartments of Geriatrics, Wuhan No. 1 Hospital, Wuhan, China.ORCID 0009-0001-0038-7626

Funding

Hubei Province Health Commission WJ2021F001The Natural Science Foundation of Hubei Province 2023AFB533Wuhan Natural Science Foundation Exploration Plan Key Clinical Research Projects in Municipal Medical Institutions 2024020801020392
6 · The paper itself

Abstract

Cardiovascular disease (CVD) represents a global problem and is associated with high levels of morbidity/mortality in the elderly (>65 years old). The present study aimed to identify the key candidate genes and pathways in cardiac aging via integrated bioinformatics analysis. The GSE43556 and GSE8146 gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs), defined as P < .05 and |log fold-change (FC)| >0.5, were identified. Functional enrichment and protein-protein interaction network construction were subsequently performed. First, 142 DEGs shared between the two GEO datasets were identified. Second, biological functional enrichment analysis illustrated that these DEGs mainly participate in "inflammatory response" and "monocarboxylic acid metabolic process." Moreover, Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the DEGs were mainly enriched in the PI3K-Akt signaling pathway. Subsequently, the association between the expression of DEGs in the aged heart was evaluated using the Search Tool for the Retrieval of Interacting Genes database and Cytoscape software. The present study elucidated the key genes and signaling pathways associated with cardiac aging, thus improving the understanding of the molecular mechanisms underlying cardiac aging. These identified genes may be used as molecular biomarkers for the diagnosis and treatment of cardiac aging.

Indexed as

AgingComputational BiologyHeartMyocardiumAnimalsDatabases, GeneticGene Expression ProfilingGene Regulatory NetworksMiceProtein Interaction MapsSignal Transduction

Identifiers

PMID40153770
PMCPMC11957657

What Socratic holds

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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.