Pulmonary Administration of GW0742, a High-Affinity Peroxisome Proliferator-Activated Receptor Agonist, Repairs Collapsed Alveoli in an Elastase-Induced Mouse Model of Emphysema

Autor: Tomoki Motomura, Chikamasa Yamashita, Michiko Horiguchi, Tomomi Akita, Kaori Abe, Yuki Oiso, Chihiro Ozawa
Rok vydání: 2016
Předmět:
Zdroj: Biological & Pharmaceutical Bulletin. 39:778-785
ISSN: 1347-5215
0918-6158
Popis: Pulmonary emphysema is a disease in which lung alveoli are irreversibly damaged, thus compromising lung function. Our previous study revealed that all-trans-retinoic acid (ATRA) induces the differentiation of human lung alveolar epithelial type 2 progenitor cells and repairs the alveoli of emphysema model mice. ATRA also reportedly has the ability to activate peroxisome proliferator-activated receptor (PPAR) β/δ. A selective PPARβ/δ ligand has been reported to induce the differentiation of human keratinocytes during wound repair. Here, we demonstrate that treatment using a high-affinity PPARβ/δ agonist, GW0742, reverses the lung tissue damage induced by elastase in emphysema-model mice and improves respiratory function. Mice treated with elastase, which collapsed their alveoli, were then treated with either 10% dimethyl sulfoxide (DMSO) in saline (control group) or GW0742 (1.0 mg/kg twice a week) by pulmonary administration. Treatment with GW0742 for 2 weeks increased the in vivo expression of surfactant proteins A and D, which are known alveolar type II epithelial cell markers. GW0742 treatment also shortened the average distance between alveolar walls in the lungs of emphysema model mice, compared with a control group treated with 10% DMSO in saline. Treatment with GW0742 for 3 weeks also improved tissue elastance (cm H2O/mL), as well as the ratio of the forced expiratory volume in the first 0.05 s to the forced vital capacity (FEV 0.05/FVC). In each of these experiments, GW0742 treatment reversed the damage caused by elastase. In conclusion, PPARβ/δ agonists are potential therapeutic agents for pulmonary emphysema.
Databáze: OpenAIRE