Dataset Information

The Overlap of Lung Tissue Transcriptome of Smoke Exposed Mice with Human Smoking and COPD.

ABSTRACT: Genome-wide mRNA profiling in lung tissue from human and animal models can provide novel insights into the pathogenesis of chronic obstructive pulmonary disease (COPD). While 6 months of smoke exposure are widely used, shorter durations were also reported. The overlap of short term and long-term smoke exposure in mice is currently not well understood, and their representation of the human condition is uncertain. Lung tissue gene expression profiles of six murine smoking experiments (n?=?48) were obtained from the Gene Expression Omnibus (GEO) and analyzed to identify the murine smoking signature. The "human smoking" gene signature containing 386 genes was previously published in the lung eQTL study (n?=?1,111). A signature of mild COPD containing 7 genes was also identified in the same study. The lung tissue gene signature of "severe COPD" (n?=?70) contained 4,071 genes and was previously published. We detected 3,723 differentially expressed genes in the 6 month-exposure mice datasets (FDR <0.1). Of those, 184 genes (representing 48% of human smoking) and 1,003 (representing 27% of human COPD) were shared with the human smoking-related genes and the COPD severity-related genes, respectively. There was 4-fold over-representation of human and murine smoking-related genes (P?=?6.7?×?10-26) and a 1.4 fold in the severe COPD -related genes (P?=?2.3?×?10-12). There was no significant enrichment of the mice and human smoking-related genes in mild COPD signature. These data suggest that murine smoke models are strongly representative of molecular processes of human smoking but less of COPD.

SUBMITTER: Obeidat M

PROVIDER: S-EPMC6082828 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Overlap of Lung Tissue Transcriptome of Smoke Exposed Mice with Human Smoking and COPD.

Obeidat Ma'en M Dvorkin-Gheva Anna A Li Xuan X Bossé Yohan Y Brandsma Corry-Anke CA Nickle David C DC Hansbro Philip M PM Faner Rosa R Agusti Alvar A Paré Peter D PD Stampfli Martin R MR Sin Don D DD

Scientific reports 20180808 1

Genome-wide mRNA profiling in lung tissue from human and animal models can provide novel insights into the pathogenesis of chronic obstructive pulmonary disease (COPD). While 6 months of smoke exposure are widely used, shorter durations were also reported. The overlap of short term and long-term smoke exposure in mice is currently not well understood, and their representation of the human condition is uncertain. Lung tissue gene expression profiles of six murine smoking experiments (n = 48) were ...[more]

PMID: 30089872

Similar Datasets

Project description:BACKGROUND:Lung aging is characterized by a number of structural alterations including fibrosis, chronic inflammation and the alteration of inflammatory cell composition. Chronic exposure to cigarette smoke (CS) is known to induce similar alterations and may contribute to premature lung aging. Additionally, aging and CS exposure are associated with transcriptional alterations in the lung. The current work aims to explore the interaction between age- and CS- associated transcriptomic perturbations and develop a transcriptomic clock able to predict the biological age and the impact of external factors on lung aging. RESULTS:Our investigations revealed a substantial overlap between transcriptomic response to CS exposure and age-related transcriptomic alterations in the murine lung. Of particular interest is the strong upregulation of immunoglobulin genes with increased age and in response to CS exposure, indicating an important implication of B-cells in lung inflammation associated with aging and smoking. Furthermore, we used a machine learning approach based on Lasso regression to build a transcriptomic age model that can accurately predict chronological age in untreated mice and the deviations associated with certain exposures. Interestingly, CS-exposed-mice were predicted to be prematurely aged in contrast to mice exposed to fresh air or to heated tobacco products (HTPs). The accelerated aging rate associated with CS was reversed upon smoking cessation or switching to HTPs. Additionally, our model was able to predict premature aging associated with thoracic irradiation from an independent public dataset. CONCLUSIONS:Aging and CS exposure share common transcriptional alteration patterns in the murine lung. The massive upregulation of B-cell restricted genes during these processes shed light on the contribution of cell composition and particularly immune cells to the measured transcriptomic signal. Through machine learning approach, we show that gene expression changes can be used to accurately monitor the biological age and the modulations associated with certain exposures. Our findings also suggest that the premature lung aging is reversible upon the reduction of harmful exposures.

Dataset Information

The Overlap of Lung Tissue Transcriptome of Smoke Exposed Mice with Human Smoking and COPD.

Publications

The Overlap of Lung Tissue Transcriptome of Smoke Exposed Mice with Human Smoking and COPD.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure