The role of age-related genes in idiopathic pulmonary fibrosis and molecular docking analysis of their drug targets

Jan 21, 2026Frontiers in immunology

Age-related genes linked to idiopathic pulmonary fibrosis and their potential drug targets

AI simplified

Abstract

Comparative transcriptomic analysis identified 292 differentially expressed genes (DEGs) between (IPF) and control tissues.

  • Nineteen of the DEGs showed significant characteristics related to aging.
  • Ten hub genes were identified that play central roles in regulatory networks associated with and fibrotic remodeling.
  • Inulin and meclizine were nominated as drug candidates due to their stable binding with key genes.
  • Validation results indicated significant upregulation of specific genes consistent across both the external dataset and a murine model of pulmonary fibrosis.
  • The findings suggest potential pathways linking cellular aging processes to the progression of pulmonary fibrosis.

AI simplified

Key numbers

292
in
Identified between and control tissues.
19
Aging-Related Genes Identified
Exhibited dual senescence-fibrosis regulatory potential.

Key figures

Figure 1
Sequential bioinformatics steps for analyzing age-related genes in
Frames a clear stepwise approach to identify and validate age-related gene targets in pulmonary fibrosis research
fimmu-16-1697013-g001
  • Panel flowchart
    Starts with three transcriptomic datasets (GSE24206, GSE53845, GSE68239) containing IPF and normal samples
  • Panel flowchart
    Datasets merged and analyzed by and differential gene expression () with thresholds logFC=0.585 and p.val=0.05
  • Panel flowchart
    Intersection with age-related differential genes yields 19 DEGs identified by Venn diagram
  • Panel flowchart
    Functional enrichment analyses performed using , , and on 19 DEGs
  • Panel flowchart
    Protein-protein interaction () network constructed, with sub-network identified by and top 10 selected by
  • Panel flowchart
    Hub genes-drug interaction network constructed, followed by , validation with GSE10667 dataset, and experimental verification
  • Panel flowchart
    Genemina analysis performed on top hub genes
Figure 2
Transcriptomic data quality, gene expression patterns, and differential gene expression in datasets
Frames a clear contrast in gene expression patterns and across IPF datasets
fimmu-16-1697013-g002
  • Panel A
    plot of transcriptomic profiles before batch correction showing distinct clustering of the three datasets GSE24206, GSE53845, and GSE68239
  • Panel B
    PCA plot after batch correction showing overlapping clusters of the three datasets, indicating reduced batch effects
  • Panel C
    of 292 () across control and treated samples from the three datasets, with red indicating higher expression and blue indicating lower expression
  • Panel D
    showing DEGs with red dots for up-regulated genes and blue dots for down-regulated genes
Figure 3
Aging-related differential genes and their functional enrichment in
Highlights key aging-related genes linked to specific biological functions and pathways in pulmonary fibrosis
fimmu-16-1697013-g003
  • Panel A
    Venn diagram showing 19 aging-related differential genes identified by intersecting () and (DEG)
  • Panel B
    Gene Ontology () enrichment analysis of 19 aging-related genes grouped by biological process, cellular component, and molecular function categories with counts and p-values
  • Panel C
    pathway enrichment analysis of 19 aging-related genes highlighting metabolic and signaling pathways with counts and p-values
Figure 4
Aging-related gene interactions and expression patterns in patients versus controls
Highlights distinct gene expression and interaction patterns linked to aging in IPF, spotlighting key and their functions.
fimmu-16-1697013-g004
  • Panel A
    Protein-protein interaction () network of 17 aging-related , with nodes colored red or green indicating gene groups.
  • Panel B
    showing expression levels of the 17 genes across three independent IPF patient cohorts and controls, with color gradients representing expression intensity.
  • Panel C
    of hub genes constructed using , with node size indicating gene importance and colored segments representing associated biological functions.
Figure 5
Top 10 drugs linked to target genes from
Highlights key drugs with strong gene associations, spotlighting potential therapeutic targets in pulmonary fibrosis
fimmu-16-1697013-g005
  • Panel A
    Bubble plot showing top 10 drugs enriched by target genes with on x-axis; bicalutamide and ethanol have the highest gene ratios and smallest values (darkest red bubbles)
  • Panel B
    Network diagram linking target genes (gray nodes) to enriched drugs (colored nodes) with edges colored by drug category; node size indicates connection count
1 / 5

Full Text

What this is

  • This research investigates the role of age-related genes in () using transcriptomic data.
  • The study identifies key genes linked to and fibrotic processes in .
  • Potential therapeutic candidates, inulin and meclizine, were identified through molecular docking analysis.

Essence

  • Age-related genes CLU and LCN2 are significantly upregulated in , linking to lung fibrosis. Inulin and meclizine show promise as therapeutic candidates through their interactions with these genes.

Key takeaways

  • 292 differentially expressed genes (DEGs) were identified in tissues compared to controls, including 19 with aging-related characteristics. These genes are implicated in fibrotic remodeling and .
  • Molecular docking analysis revealed that inulin and meclizine bind to CLU and LCN2, respectively, suggesting their potential as therapeutic agents in .

Caveats

  • The anti-fibrotic effects of inulin and meclizine in remain to be experimentally validated. The study's sample size and single time point in animal experiments may limit the robustness of findings.
  • Clinical correlations between hub gene expression and patient outcomes are not established, and potential batch effects in transcriptomic data could introduce bias.

Definitions

  • idiopathic pulmonary fibrosis (IPF): A progressive lung disease characterized by excessive fibrotic tissue formation, leading to respiratory failure.
  • cellular senescence: A state of irreversible cell cycle arrest associated with aging, contributing to tissue dysfunction and disease.

AI simplified

what lands in your inbox each week:

  • 📚7 fresh studies
  • 📝plain-language summaries
  • direct links to original studies
  • 🏅top journal indicators
  • 📅weekly delivery
  • 🧘‍♂️always free