Effects of chemical composition on the lung cell response to coal particles: Implications for coal workers' pneumoconiosis

Background and objective Coal mine dust has a complex and heterogeneous chemical composition. It has been suggested that coal particle chemistry plays a critical role in determining the pathogenesis of coal workers' pneumoconiosis (CWP). In this study, we aimed to establish the association betw...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Respirology (Carlton, Vic.) Vic.), 2022-06, Vol.27 (6), p.447-454
Hauptverfasser: Song, Yong, Southam, Katherine, Beamish, B. Basil, Zosky, Graeme R.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Background and objective Coal mine dust has a complex and heterogeneous chemical composition. It has been suggested that coal particle chemistry plays a critical role in determining the pathogenesis of coal workers' pneumoconiosis (CWP). In this study, we aimed to establish the association between the detrimental cellular response and the chemical composition of coal particles. Methods We sourced 19 real‐world coal samples. Samples were crushed prior to use to minimize the impact of particle size on the response and to ensure the particles were respirable. Key chemical components and inorganic compounds were quantified in the coal samples. The cytotoxic, inflammatory and pro‐fibrotic responses in epithelial cells, macrophages and fibroblasts were assessed following 24 h of exposure to coal particles. Principal component analysis (PCA) and stepwise regression were used to determine which chemical components of the coal particles were associated with the cell response. Results The cytotoxic, inflammatory and pro‐fibrotic response varied considerably between coal samples. There was a high level of collinearity in the cell responses and between the chemical compounds within the coal samples. PCA identified three factors that explained 75% of the variance in the cell response. Stepwise multiple regression analysis identified K2O (p 
ISSN:1323-7799
1440-1843
DOI:10.1111/resp.14246