E-MTAB-1426 - Transcription profiling by array of left lungs from A/J mouse exposed to cigarette smoke to study the molecular networks behind emphysema/chronic obstrucive pulmonary disease (COPD)
Submitted on 1 December 2009, last updated on 9 May 2014, released on 14 May 2014
Chronic Obstructive Pulmonary Disease (COPD) is a respiratory disorder that is the result of extended exposure of the airways to noxious stimuli, principally cigarette smoke (CS). The mechanisms through which COPD evolves are not fully understood though it is believed that the disease process includes a genetic component since not all smokers develop COPD. To investigate the mechanism leading to the development of COPD/emphysema, we performed an experiment in which whole genome gene expression and several COPD-relevant biological endpoints (MMP-9, MMP activity, TIMP-1 and lung weight) were measured in lung tissue after exposure to two doses of CS for various periods of time. A novel and powerful method, known as reverse engineering and forward simulation (REFS(TM)), was employed to identify key molecular drivers by integrating gene expression data and 4 measured COPD-relevant endpoints. An ensemble of molecular networks was generated using REFS(TM). Simulations showed that this ensemble could successfully recover the measured experimental data for gene expression and measured COPD-relevant endpoints. This ensemble of networks was then further employed to simulate thousands of in silico gene knockdown experiments. Based on the in silico gene knockdown, thirty-three molecular key drivers for the above four COPD-relevant endpoints were identified, with the majority of them being enriched in inflammation, emphysema and COPD.
transcription profiling by array, compound treatment design, dose response design, in vivo, time series design
Discovery of Emphysema/COPD-relevant Molecular Networks from an A/J Mouse COPD Inhalation Study by Means of Reverse Engineering and Forward Simulation (REFS(TM)). Yang Xiang;Ulrike Kogel;Stephan Gebel;Michael J. Peck;Manuel C. Peitsch;Viatcheslav R. Akmaev;Boris Hayete;Jignesh Parikh;Lauren Young;John Caprice;Julia Hoeng;Iya Khalil.