Evidence map›Paper›PMID 38809349›Full record

ArticleCell biochemistry and biophysics2024

Integrative Bioinformatics Approaches to Uncover Hub Genes and Pathways Involved in Cardiovascular Diseases.

Awatef Salah, Fériel Bouzid, Wala Dhouib, Riadh Benmarzoug, Nesrine Triki, Ahmed Rebai, Najla Kharrat

Abstract read
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In one paragraph

Article in Cell biochemistry and biophysics, 2024. 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. Identification of potential biomarkers for coronary slow flow using untargeted metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2025
    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

7 authors.

Awatef SalahLaboratory of Molecular and Cellular Screening Processes, Centre of Biotechnology of Sfax, University of Sfax, Sfax, Tunisia. awatefsalah25@gmail.com.
Fériel BouzidLaboratory of Molecular and Cellular Screening Processes, Centre of Biotechnology of Sfax, University of Sfax, Sfax, Tunisia.
Wala DhouibLaboratory of Molecular and Cellular Screening Processes, Centre of Biotechnology of Sfax, University of Sfax, Sfax, Tunisia.
Riadh BenmarzougLaboratory of Molecular and Cellular Screening Processes, Centre of Biotechnology of Sfax, University of Sfax, Sfax, Tunisia.
Nesrine TrikiLaboratory of Molecular and Cellular Screening Processes, Centre of Biotechnology of Sfax, University of Sfax, Sfax, Tunisia.
Ahmed RebaiLaboratory of Molecular and Cellular Screening Processes, Centre of Biotechnology of Sfax, University of Sfax, Sfax, Tunisia.
Najla KharratLaboratory of Molecular and Cellular Screening Processes, Centre of Biotechnology of Sfax, University of Sfax, Sfax, Tunisia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular diseases (CVD) represent a significant global health challenge resulting from a complex interplay of genetic, environmental, and lifestyle factors. However, the molecular pathways and genetic factors involved in the onset and progression of CVDs remain incompletely understood. Here, we performed an integrative bioinformatic analysis to highlight specific genes and signaling pathways implicated in the pathogenesis of 80 CVDs. Differentially expressed genes (DEGs) were identified through the integrated analysis of microarray and GWAS datasets. Then, hub genes were identified after gene ontology functional annotation analysis and protein-protein internet (PPI) analysis. In addition, pathways were identified through KEGG and gene ontology enrichment analyses. A total of 821 hub genes related to 80 CVDs were identified, including 135 common and frequent CVD-associated genes. TNF, IL6, VEGFA, and TGFB.1 genes were the central core genes expressed in 50% or more of CVDs, confirming that the inflammation is a key pathological feature of CVDs. Analysis of hub genes by KEGG enrichment revealed predominant enrichment in 201 KEGG pathways, of which the AGE-RAGE signaling pathway in diabetic complications was identified as the common key KEGG implicated in 62 CVDs. In addition, the outcomes showed an overrepresentation in pathways categorized under human diseases, particularly in the subcategories of infectious diseases and cancers, which may be common risk factors for CVDs. In conclusion, this powerful approach for in silico fine-mapping of genes and pathways allowed the identification of determinant hubs genes and pathways implicated in the pathogenesis of CVDs which could be employed in developing more targeted and effective interventions for preventing, diagnosing, and treating CVDs. The function of these hub genes in CVDs needs further exploration to elucidate their biological characteristics.

Indexed as

Cardiovascular DiseasesComputational BiologySignal TransductionGene OntologyGene Regulatory NetworksGenome-Wide Association StudyHumansProtein Interaction MapsCardiovascular diseaseHub genesInflammationIn silicoPathways

Identifiers

PMID38809349

What Socratic holds

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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.