Evidence map›Paper›PMID 36553589›Full record

ArticleGenes2022

Transcriptomic Profiling Unravels Novel Deregulated Gene Signatures Associated with Acute Myocardial Infarction: A Bioinformatics Approach.

Sanjay Kumar, Chun-Ming Shih, Lung-Wen Tsai, Rajni Dubey, Deepika Gupta, Tanmoy Chakraborty, Naveen Sharma, Abhishek Vikram Singh, Vishnu Swarup, Himanshu Narayan Singh

Open access · goldAbstract read
In one paragraph

Article in Genes, 2022. 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
0.5field-weighted citation impact, top 32% of its field
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, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. 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

10 authors at 5 institutions in 3 countries.

Sanjay KumarDepartment of Life Science, Sharda School of Basic Sciences and Research, Sharda University, Knowledge Park-III, Greater Noida 201310, India.ORCID 0000-0001-6296-0291
Chun-Ming ShihDivision of Cardiology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei 111031, Taiwan.
Lung-Wen TsaiDepartment of Medicine Research, Taipei Medical University Hospital, Taipei 111031, Taiwan.ORCID 0000-0002-3541-5834
Rajni DubeyDivision of Cardiology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei 111031, Taiwan.ORCID 0000-0002-0506-7744
Deepika GuptaDepartment of Neurology, All India Institute of Medical Sciences, New Delhi 110029, India.
Tanmoy ChakrabortyDepartment of Chemistry and Biochemistry, Sharda School of Basic Sciences and Research, Sharda University, Knowledge Park-III, Greater Noida 201310, India.
Naveen SharmaBiomedical Informatics Division, Indian Council of Medical Research, New Delhi 110029, India.
Abhishek Vikram SinghDepartment of Cardiology, Infinity Care Hospital, Varanasi 221002, India.
Vishnu SwarupDepartment of Neurology, All India Institute of Medical Sciences, New Delhi 110029, India.ORCID 0000-0003-0759-7818
Himanshu Narayan SinghDepartment of System Biology, University of Columbia Irving Medical Center, New York, NY 10032, USA.ORCID 0000-0003-4111-5165
Taipei Medical University Hospital · TWAll India Institute of Medical Sciences · INSharda University · INColumbia University Irving Medical Center · USIndian Council of Medical Research · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myocardial infarction (AMI) is a severe disease with elevated morbidity and mortality rate worldwide. This is attributed to great losses of cardiomyocytes, which can trigger the alteration of gene expression patterns. Although several attempts have been made to assess the AMI biomarkers, to date their role in rescuing myocardial injury remains unclear. Therefore, the current study investigated three independent microarray-based gene expression datasets from AMI patients (n = 85) and their age-sex-matched healthy controls (n = 70), to identify novel gene signatures that might be involved in cardioprotection. The differentially expressed genes (DEGs) were analyzed using 'GEO2R', and weighted gene correlation network analysis (WGCNA) was performed to identify biomarkers/modules. We found 91 DEGs, of which the number of upregulated and downregulated genes were 22 and 5, respectively. Specifically, we found that the deregulated genes such as ADOR-A3, BMP6, VPS8, and GPx3, may be associated with AMI. WGCNA revealed four highly preserved modules among all datasets. The 'Enrichr' unveiled the presence of miR-660 and STAT1, which is known to affect AMI severity. Conclusively, these genes and miRNA might play a crucial role the rescue of cardiomyocytes from severe damage, which could be helpful in developing appropriate therapeutic strategies for the management of AMI.

Indexed as

MicroRNAsMyocardial InfarctionBiomarkersComputational BiologyGene Expression ProfilingHumansTranscriptomeBiomarkersMicroRNAsMIRN660 microRNA, humanacute myocardial infarctioncardiovascular diseasedifferential expressed genesNOTCH1 signalingweighted gene correlation network analysis

Identifiers

PMID36553589
PMCPMC9777571
OpenAlexW4311995273

What Socratic holds

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Registered trials

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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.