Sean E Corbett1, Matthew Nitzberg2, Elizabeth Moses3, Eric Kleerup4, Teresa Wang1, Catalina Perdomo3, Claudia Perdomo4, Gang Liu3, Xiaohui Xiao3, Hanqiao Liu3, David A Elashoff5, Daniel R Brooks6, George T O'Connor2, Steven M Dubinett4, Avrum Spira7, Marc E Lenburg1. 1. Bioinformatics Program, Boston University, Boston, MA; Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA. 2. Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA; Pulmonary Center, Boston University School of Medicine, Boston, MA. 3. Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA. 4. Division of Pulmonary and Critical Care Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA. 5. Department of Biostatistics, University of California, Los Angeles, CA. 6. Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA; Department of Epidemiology, Boston University School of Public Health, Boston, MA. 7. Bioinformatics Program, Boston University, Boston, MA; Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA; Pulmonary Center, Boston University School of Medicine, Boston, MA; Johnson & Johnson, Cambridge, MA. Electronic address: aspira@bu.edu.
Abstract
BACKGROUND: Although e-cigarette (ECIG) use has increased in the United States, their potential health effects remain uncertain. Understanding the effects of tobacco cigarette (TCIG) smoke on bronchial airway epithelial gene expression have previously provided insights into tobacco-related disease pathogenesis. Identifying the impact of ECIGs on airway gene expression could provide insights into their potential long-term health effects. We sought to compare the bronchial airway gene-expression profiles of former TCIG smokers now using ECIGs with the profiles of former and current TCIG smokers. METHODS: We performed gene-expression profiling of bronchial epithelial cells collected from current TCIG smokers (n = 9), current ECIG users who are former TCIG smokers (n = 15), and former TCIG smokers (n = 21). We then compared our findings with previous studies of the effects of TCIG use on bronchial epithelium, as well an in vitro model of ECIG exposure. RESULTS: Among 3,165 genes whose expression varied between the three study groups (q < 0.05), we identified 468 genes altered in ECIG users relative to former smokers (P < .05). Seventy-nine of these genes were up- or down-regulated concordantly among ECIG and TCIG users. We did not detect ECIG-associated gene-expression changes in known pathways associated with TCIG usage. Genes downregulated in ECIG users are enriched among the genes most downregulated by exposure of airway epithelium to ECIG vapor in vitro. CONCLUSIONS: ECIGs induce both distinct and shared patterns of gene expression relative to TCIGs in the bronchial airway epithelium. The concordance of the genes altered in ECIG users and in the in vitro study suggests that genes altered in ECIG users are likely to be changed as the direct effect of ECIG exposure.
BACKGROUND: Although e-cigarette (ECIG) use has increased in the United States, their potential health effects remain uncertain. Understanding the effects of tobacco cigarette (TCIG) smoke on bronchial airway epithelial gene expression have previously provided insights into tobacco-related disease pathogenesis. Identifying the impact of ECIGs on airway gene expression could provide insights into their potential long-term health effects. We sought to compare the bronchial airway gene-expression profiles of former TCIG smokers now using ECIGs with the profiles of former and current TCIG smokers. METHODS: We performed gene-expression profiling of bronchial epithelial cells collected from current TCIG smokers (n = 9), current ECIG users who are former TCIG smokers (n = 15), and former TCIG smokers (n = 21). We then compared our findings with previous studies of the effects of TCIG use on bronchial epithelium, as well an in vitro model of ECIG exposure. RESULTS: Among 3,165 genes whose expression varied between the three study groups (q < 0.05), we identified 468 genes altered in ECIG users relative to former smokers (P < .05). Seventy-nine of these genes were up- or down-regulated concordantly among ECIG and TCIG users. We did not detect ECIG-associated gene-expression changes in known pathways associated with TCIG usage. Genes downregulated in ECIG users are enriched among the genes most downregulated by exposure of airway epithelium to ECIG vapor in vitro. CONCLUSIONS: ECIGs induce both distinct and shared patterns of gene expression relative to TCIGs in the bronchial airway epithelium. The concordance of the genes altered in ECIG users and in the in vitro study suggests that genes altered in ECIG users are likely to be changed as the direct effect of ECIG exposure.
Authors: Katrina Steiling; Maarten van den Berge; Kahkeshan Hijazi; Roberta Florido; Joshua Campbell; Gang Liu; Ji Xiao; Xiaohui Zhang; Grant Duclos; Eduard Drizik; Huiqing Si; Catalina Perdomo; Charles Dumont; Harvey O Coxson; Yuriy O Alekseyev; Don Sin; Peter Pare; James C Hogg; Annette McWilliams; Pieter S Hiemstra; Peter J Sterk; Wim Timens; Jeffrey T Chang; Paola Sebastiani; George T O'Connor; Andrea H Bild; Dirkje S Postma; Stephen Lam; Avrum Spira; Marc E Lenburg Journal: Am J Respir Crit Care Med Date: 2013-05-01 Impact factor: 21.405
Authors: Stefan Pierrou; Per Broberg; Rory A O'Donnell; Krzysztof Pawłowski; Robert Virtala; Eva Lindqvist; Audrey Richter; Susan J Wilson; Gilbert Angco; Sebastian Möller; Håkan Bergstrand; Witte Koopmann; Elisabet Wieslander; Per-Erik Strömstedt; Stephen T Holgate; Donna E Davies; Johan Lund; Ratko Djukanovic Journal: Am J Respir Crit Care Med Date: 2006-12-07 Impact factor: 21.405
Authors: Neil R Hackett; Marcus W Butler; Renat Shaykhiev; Jacqueline Salit; Larsson Omberg; Juan L Rodriguez-Flores; Jason G Mezey; Yael Strulovici-Barel; Guoqing Wang; Lukas Didon; Ronald G Crystal Journal: BMC Genomics Date: 2012-02-29 Impact factor: 3.969
Authors: Edward Y Chen; Christopher M Tan; Yan Kou; Qiaonan Duan; Zichen Wang; Gabriela Vaz Meirelles; Neil R Clark; Avi Ma'ayan Journal: BMC Bioinformatics Date: 2013-04-15 Impact factor: 3.169
Authors: Sara Trifunovic; Katarina Smiljanić; Albert Sickmann; Fiorella A Solari; Stoimir Kolarevic; Aleksandra Divac Rankov; Mila Ljujic Journal: Respir Res Date: 2022-07-15
Authors: Anne M van der Does; Rashad M Mahbub; Pieter S Hiemstra; Alen Faiz; Dennis K Ninaber; Senani N H Rathnayake; Wim Timens; Maarten van den Berge; Hananeh Aliee; Fabian J Theis; Martijn C Nawijn Journal: Respir Res Date: 2022-09-02
Authors: Abby C Lee; Jaideep Chakladar; Wei Tse Li; Chengyu Chen; Eric Y Chang; Jessica Wang-Rodriguez; Weg M Ongkeko Journal: Int J Mol Sci Date: 2020-07-31 Impact factor: 5.923
Authors: Xuefei Cao; Jayme P Coyle; Rui Xiong; Yiying Wang; Robert H Heflich; Baiping Ren; William M Gwinn; Patrick Hayden; Liying Rojanasakul Journal: In Vitro Cell Dev Biol Anim Date: 2020-11-11 Impact factor: 2.723