Evidence map›Paper›PMID 38463581›Full record

ArticleAmerican journal of translational research2024

Transcriptomics data integration and analysis to uncover hallmark genes in hypertrophic cardiomyopathy.

Peng Chen, Warda Yawar, Ayesha Rida Farooqui, Saqib Ali, Nida Lathiya, Zeeshan Ghous, Rizwana Sultan, Majid Alhomrani, Saleh A Alghamdi, Abdulraheem Ali Almalki and 4 more

Abstract read
In one paragraph

Article in American journal of translational research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Interplay ofFrontiers in cardiovascular medicine · 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

14 authors.

Peng ChenDepartment of Cardiovascular Medicine, Taiyuan Central Hospital Taiyuan 030000, Shanxi, China.
Warda YawarDepartment of Emergency, PPHI Sindh, Karachi 74800, Pakistan.
Ayesha Rida FarooquiDepartment of Emergency, Abbasi Shaheed Hospital Karachi 74800, Pakistan.
Saqib AliDepartment of Computer Science, University of Agriculture Faisalabad 38040, Pakistan.
Nida LathiyaDepartment of Physiology, Jinnah Medical and Dental College, Sohail University Karachi 74800, Pakistan.
Zeeshan GhousDepartment of Cardiology, Punjab Institute of Cardiology Lahore 54000, Pakistan.
Rizwana SultanDepartment of Pathology, Faculty of Veterinary and Animal Sciences, Cholistan University of Veterinary and Animal Sciences Bahawalpur, Pakistan.
Majid AlhomraniDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University Taif 21944, Saudi Arabia.
Saleh A AlghamdiDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University Taif 21944, Saudi Arabia.
Abdulraheem Ali AlmalkiDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University Taif 21944, Saudi Arabia.
Ahmad A AlghamdiDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University Taif 21944, Saudi Arabia.
Naif ALSuhaymiDepartment of Emergency Medical Services, Faculty of Health Sciences - AlQunfudah, Umm Al-Qura University Mekkah, Saudi Arabia.
Muhammad Razi Ul Islam HashmiCardiothoracic ICU, Bahria International Hospital Rawalpindi, Pakistan.
Yasir HameedDepartment of Biotechnology, Institute of Biochemistry Biotechnology and Bioinformatics, The Islamia University of Bahawalpur Bahawalpur 63100, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionHypertrophic cardiomyopathy (HCM) is a heterogeneous disease that mainly affects the myocardium. In the current study, we aim to explore HCM-related hub genes through the analysis of differentially expressed genes (DEGs) between HCM and normal sample groups.

methodsThe GSE68316 and GSE36961 expression profiles were obtained from the Gene Expression Omnibus (GEO) database for the identification of DEGs, to explore hub genes, and to perform their expression analysis. Clinical HCM and control tissue samples were taken for expression and promoter methylation validation analysis via RNA-sequencing (RNA-seq) and targeted bisulfite sequencing (bisulfite-seq) analyses. Then, other different bioinformatics tools were employed to perform STRING, lncRNA-miRNA-mRNA regulatory networks, gene enrichment, and drug prediction analyses.

resultsIn total, the top 20 DEGs, including 10 up-regulated and 10 down-regulated, were obtained from GSE68316. Out of the 20 DEGs, we subsequently identified the 8 most important hub genes including 5 up-regulated genes (EPB42, UQCRH, CA1, PFDN5, and LSM5) and 3 down-regulated genes (RPS24, TNS1, and RPL26). Expression and promoter methylation dysregulation of these genes were further validated on clinical HCM samples paired with controls. Next, we further investigated hub genes' regulatory 6 miRNAs (has-mir-1-3p, has-mir-129-5p, has-mir-16-5p, has-mir-23b-3p, has-mir-27-3p, and has-mir-182-5p) and miRNAs regulatory 4 lncRNAs (NUTMB2-AS1, NEAT1, XIST, and GABPB1-AS1) in this study via the lncRNA-cricRNA-miRNA-mRNA regulatory network. Later on, gene enrichment analysis revealed that hub genes were enriched in various important pathways including Nitrogen metabolism, Ribosome, RNA degradation, Cardiac muscle contraction, and Coronavirus disease, etc. Finally, the drug prediction analysis highlighted different potential candidate drugs for altering the expression of hub genes in the treatment of HCM.

conclusionIn summary, the identification of key hub genes and their enrichment analysis in the current study may shed light on the mechanisms behind the occurrence and development of HCM.

Indexed as

DEGshub geneHypertrophic cardiomyopathymiRNA

Identifiers

PMID38463581
PMCPMC10918138

What Socratic holds

Textmetadata
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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.