Genetic effects of welding fumes on the development of respiratory system diseases. (May 2019)

• Record Type: Journal Article
• Authors: Rana, Humayan Kabir; Akhtar, Mst. Rashida; Islam, M. Babul; Ahmed, Mohammad Boshir; Liò, Pietro; Quinn, Julian M.W.; Huq, Fazlul; Moni, Mohammad Ali
• Is Part Of: Computers in biology and medicine. Volume 108(2019)
• Page Start: 142
• Page End: 149
• Publication Date: 2019-05
• Subjects: Welding fumes -- Respiratory system diseases -- Chronic bronchitis -- Asthma -- Pulmonary edema -- Lung cancer; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2019.04.004
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Background: The welding process releases potentially hazardous gases and fumes, mainly composed of metallic oxides, fluorides and silicates. Long term welding fume (WF) inhalation is a recognized health issue that carries a risk of developing chronic health problems, particularly respiratory system diseases (RSDs). Aside from general airway irritation, WF exposure may drive direct cellular responses in the respiratory system which increase risk of RSD, but these are not well understood. Methods: We developed a quantitative framework to identify gene expression effects of WF exposure that may affect RSD development. We analyzed gene expression microarray data from WF-exposed tissues and RSD-affected tissues, including chronic bronchitis (CB), asthma (AS), pulmonary edema (PE), lung cancer (LC) datasets. We built disease-gene (diseasome) association networks and identified dysregulated signaling and ontological pathways, and protein-protein interaction sub-network using neighborhood-based benchmarking and multilayer network topology. Results: We observed many genes with altered expression in WF-exposed tissues were also among differentially expressed genes (DEGs) in RSD tissues; for CB, AS, PE and LC there were 34, 27, 50 and 26 genes respectively. DEG analysis, using disease association networks, pathways, ontological analysis and protein-protein interaction sub-network suggest significant links between WF exposure and the development of CB, AS, PE and LC. Conclusions: Our network-based analysis and investigation of the genetic links of WFs and RSDs confirm a number of genes and gene products are plausible participants in RSD development. Our results are a significant resource to identify causal influences on the development of RSDs, particularly in the context of WF exposure.