Evidence map›Paper›PMID 39622956›Full record

ArticleScientific reports2024

Identification of immune-related hub genes and potential molecular mechanisms involved in COVID-19 via integrated bioinformatics analysis.

Rui Zhu, Yaping Zhao, Hui Yin, Linfeng Shu, Yuhang Ma, Yingli Tao

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Rui Zhu *School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
Yaping Zhao *Department of Pharmacy, Shaoxing Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Shaoxing, 312000, China.
Hui YinAnimal Science and Technology College, Beijing University of Agriculture, Beijing, 102206, China.
Linfeng ShuSchool of Traditional Chinese Medicine, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Yuhang MaSchool of Traditional Chinese Medicine, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Yingli TaoDepartment of Reproductive Immunology, Tongde Hospital of Zhejiang Province, Hangzhou, 310012, China. taozi129@126.com.

Funding

Science and Technology Project of Traditional Chinese Medicine of Zhejiang Province 2023ZL328Science and Technology Project of Traditional Chinese Medicine of Zhejiang Province 2023ZL729Scientific Research Fund of Zhejiang Provincial Education Department 202251034
6 · The paper itself

Abstract

COVID-19, caused by the SARS-CoV-2 virus, poses significant health challenges worldwide, particularly due to severe immune-related complications. Understanding the molecular mechanisms and identifying key immune-related genes (IRGs) involved in COVID-19 pathogenesis is critical for developing effective prevention and treatment strategies. This study employed computational tools to analyze biological data (bioinformatics) and a method for inferring causal relationships based on genetic variations, known as Mendelian randomization (MR), to explore the roles of IRGs in COVID-19. We identified differentially expressed genes (DEGs) from datasets available in the Gene Expression Omnibus (GEO), comparing COVID-19 patients with healthy controls. IRGs were sourced from the ImmPort database. We conducted functional enrichment analysis, pathway analysis, and immune infiltration assessments to determine the biological significance of the identified IRGs. A total of 360 common differential IRGs were identified. Among these genes, CD1C, IL1B, and SLP1 have emerged as key IRGs with potential protective effects against COVID-19. Pathway enrichment analysis revealed that CD1C is involved in terpenoid backbone biosynthesis and Th17 cell differentiation, while IL1B is linked to B-cell receptor signaling and the NF-kappa B signaling pathway. Significant correlations were observed between key genes and various immune cells, suggesting that they influence immune cell modulation in COVID-19. This study provides new insights into the immune mechanisms underlying COVID-19, highlighting the crucial role of IRGs in disease progression. These findings suggest that CD1C and IL1B could be potential therapeutic targets. The integrated bioinformatics and MR analysis approach offers a robust framework for further exploring immune responses in COVID-19 patients, as well as for targeted therapy and vaccine development.

Indexed as

Computational BiologyCOVID-19Mendelian Randomization AnalysisSARS-CoV-2Gene Expression ProfilingGene Regulatory NetworksHumansBioinformaticsCOVID-19Immune infiltrationImmune-related genesMendelian randomizationPathway analysis

Identifiers

PMID39622956
PMCPMC11612211

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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 OpenQuestion graph.