@misc{huang_chuang_luo_liu_lee_gordon_sun_pathak_lai_chen_et al._2020,
title={An integrated genome-wide model for hookah constituents-gene-pathway-disease relationships},
DOI={10.21203/rs.3.rs-127747/v1},
abstractNote={Abstract
Hookah smoking is becoming increasingly popular worldwide and recent epidemiological studies indicate that it is significantly associated with respiratory diseases, and could contain constituents more harmful than cigarette smoking. However, the gene expression alterations and mechanisms of disease development induced by the hookah constituents are still unclear. Here, we are the first to propose a new experimental design and use RNA sequencing to profile bronchial epithelial cells from different hookah smoking exposure conditions (GSE162386). For our hookah-smoking dataset, we developed an integrated genome-wide model, hierarchical-systems biology model (HiSBiM), to systematically investigate the effects of smoking hookah and to compare the biological pathways with public cigarette smoking datasets. Our results show that the infectious disease-related pathways were enriched in hookah smoking than in cigarette smoking, which could be due to polluted hookah devices or pathogen contaminated water filters. Furthermore, we investigate the subsystem and pathway differences in hookah smoking between charcoal and electronic heating ways. We observed that cardiovascular and atherosclerosis-related pathways were activated after exposure to charcoal combustion, which may relate to combustion components carbon monoxide and polyaromatic hydrocarbons. Overall, our results show that hookah smoking could involve a higher risk in several diseases than cigarette smoking and link the relations between hookah constituents to diseases. We believe that our HiSBiM is a useful integrated method for providing multiple-level valued insights for genome-wide analysis on various omics data sets.},
publisher={Research Square},
author={Huang, Sing-Han and Chuang, Yi-Hsuan and Luo, Yong-Chun and Liu, Wei-Ting and Lee, Jung-Yu and Gordon, Terry and Sun, Hong and Pathak, Nikhil and Lai, Wen-Sen and Chen, Lung-Chi and et al.},
year={2020},
month={Dec}
}