ERCC1 which affects lipids metabolism and actin dynamics in coal workers' pneumoconiosis is a candidate biomarker for early warning and diagnosis.

The single-nucleotide polymorphisms of genes related to DNA damage repair and inflammasomes and mutated gene expression in coal workers' pneumoconiosis (CWP) were analysed to identify the risk factors of CWP and potential biomarkers for early warning and diagnosis. Further, mutated gene pathways were analysed based on proteome and metabolome. Han Chinese male subjects were randomly selected and divided into 4 or 5 groups according to the process of CWP. MassARRAY was used to sequence single-nucleotide polymorphism genotypes. Mutated gene expression in plasma was tested using enzyme-linked immunosorbent assay (ELISA). Odds ratios (ORs) and receiver operating characteristic curves (ROC) were calculated. The serum different proteins and metabolites were identified by Ultra Performance Liquid Chromatography Quadrupole time of flight/Mass Spectrum (UPLC-Q-TOF/MS) and analysed using bioinformation software. As CWP progressed, the CC and CA genotypes of ERCC1 rs3212986 decreased and increased significantly, respectively. AA (OR = 3.016) and CA (OR = 2.130) genotypes were identified as risk factors for stage II. ERCC1 significantly decreased in processing of CWP. The cutoff value of ERCC1 was 5.265 pg/ml, with a sensitivity of 90.0% and specificity of 86.7%. ERCC1 had an indirect interaction with activator protein-1 and insulin and its pathways were mainly made with molecules related to lipid metabolism and actin dynamics. ERCC1 is a candidate biomarker for detection and precise intervention in CWP. If it reaches the threshold, workers will change other jobs in time and will not develop and diagnose as pneumoconiosis and will help the employers spend less money. Meanwhile, the signal molecules of ERCC1 pathway could be as a candidate target for drug discovery.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright: © 2024 Deng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)