Weighted gene co-expression network analysis of early-life PM₂.₅-Exposed lung transcriptome identifies key gene...

Area of Science:

• Environmental Health
• Developmental Biology
• Molecular Toxicology

Background:

• Early-life exposure to fine particulate matter (PM₂.₅), a common air pollutant, is linked to chronic respiratory diseases.
• The molecular mechanisms underlying PM₂.₅'s impact on lung development are not well understood.

Purpose of the Study:

• To investigate transcriptomic changes in the developing murine lung following intrauterine and early neonatal PM₂.₅ exposure.
• To identify specific molecular pathways and genes affected by PM₂.₅ during critical lung development stages.

Main Methods:

• Weighted Gene Co-expression Network Analysis (WGCNA) was applied to microarray data from mouse lungs at embryonic (E14.5, E18.5) and postnatal (P40) stages.
• Network analysis identified gene modules correlated with developmental progression and PM₂.₅ exposure.
• Functional enrichment analysis and identification of hub genes were performed.

Main Results:

• Developmental maturation, not PM₂.₅ exposure, was the primary driver of global lung transcriptomic variation.
• WGCNA identified gene modules involved in immune, metabolic, and cell cycle processes linked to lung development.
• Eleven PM₂.₅-associated hub genes, including Vnn1 and Fpr1, were identified within critical developmental networks, implicated in oxidative stress and immune modulation.

Conclusions:

• Early-life PM₂.₅ exposure does not globally disrupt lung transcriptomic architecture but selectively affects critical hub genes.
• This targeted sub-network vulnerability provides a mechanistic link between early environmental insults and the developmental programming of COPD susceptibility.
• The findings highlight specific molecular targets for understanding and potentially mitigating long-term respiratory dysfunction from air pollution.