Evidence map›Paper›PMID 38601162›Full record

ArticleFrontiers in immunology2024

Bioinformatics and system biology approach to identify the influences among COVID-19, influenza, and HIV on the regulation of gene expression.

Zhen Zhang, Hao Jin, Xu Zhang, Mei Bai, Kexin Zheng, Jing Tian, Bin Deng, Lingling Mao, Pengcheng Qiu, Bo Huang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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 1 country.

Zhen Zhang *Microbiology Laboratory Department, Jinzhou Center for Disease Control and Prevention, Jinzhou, Liaoning, China.
Hao Jin *Microbiology Laboratory Department, Jinzhou Center for Disease Control and Prevention, Jinzhou, Liaoning, China.
Xu Zhang *Microbiology Laboratory Department, Jinzhou Center for Disease Control and Prevention, Jinzhou, Liaoning, China.
Mei BaiMicrobiology Laboratory Department, Jinzhou Center for Disease Control and Prevention, Jinzhou, Liaoning, China.
Kexin ZhengMicrobiology Laboratory Department, Jinzhou Center for Disease Control and Prevention, Jinzhou, Liaoning, China.
Jing TianDepartment of Immunology, School of Basic Medical Science, Jinzhou Medical University, Jinzhou, Liaoning, China.
Bin DengLaboratory Department, Jinzhou Central Hospital, Jinzhou, Liaoning, China.
Lingling MaoInstitute for Prevention and Control of Infection and Infectious Diseases, Liaoning Provincial Center for Disease Control and Prevention, Shenyang, Liaoning, China.
Pengcheng QiuThoracic Surgery Department, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, China.
Bo HuangThoracic Surgery Department, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, China.
Jinzhou Central Hospital · CNLiaoning University of Technology · CNJinzhou Medical University · CNShenyang Center for Disease Control and Prevention · CNYingkou Institute of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Coronavirus disease (COVID-19), caused by SARS-CoV-2, has emerged as a infectious disease, coexisting with widespread seasonal and sporadic influenza epidemics globally. Individuals living with HIV, characterized by compromised immune systems, face an elevated risk of severe outcomes and increased mortality when affected by COVID-19. Despite this connection, the molecular intricacies linking COVID-19, influenza, and HIV remain unclear. Our research endeavors to elucidate the shared pathways and molecular markers in individuals with HIV concurrently infected with COVID-19 and influenza. Furthermore, we aim to identify potential medications that may prove beneficial in managing these three interconnected illnesses. Methods: Sequencing data for COVID-19 (GSE157103), influenza (GSE185576), and HIV (GSE195434) were retrieved from the GEO database. Commonly expressed differentially expressed genes (DEGs) were identified across the three datasets, followed by immune infiltration analysis and diagnostic ROC analysis on the DEGs. Functional enrichment analysis was performed using GO/KEGG and Gene Set Enrichment Analysis (GSEA). Hub genes were screened through a Protein-Protein Interaction networks (PPIs) analysis among DEGs. Analysis of miRNAs, transcription factors, drug chemicals, diseases, and RNA-binding proteins was conducted based on the identified hub genes. Finally, quantitative PCR (qPCR) expression verification was undertaken for selected hub genes. Results: The analysis of the three datasets revealed a total of 22 shared DEGs, with the majority exhibiting an area under the curve value exceeding 0.7. Functional enrichment analysis with GO/KEGG and GSEA primarily highlighted signaling pathways associated with ribosomes and tumors. The ten identified hub genes included Conclusion: This research provides valuable insights into shared molecular targets, signaling pathways, drug chemicals, and potential biomarkers for individuals facing the complex intersection of COVID-19, influenza, and HIV. These findings hold promise for enhancing the precision of diagnosis and treatment for individuals with HIV co-infected with COVID-19 and influenza.

Indexed as

COVID-19HIV InfectionsInfluenza, HumanMicroRNAsComputational BiologyGene Expression RegulationHumansSARS-CoV-2Transcription FactorsMicroRNAsTranscription FactorsCOVID-19differentially expressed genesdrug chemicalsHIVhub genesimmune infiltrationinfluenzaprotein-protein interaction networks

Identifiers

PMID38601162
PMCPMC11004287
OpenAlexW4393229482

What Socratic holds

Textmetadata
LicenceCC BY
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.