Transcriptomic and proteomic profiling of young and old mice in the bleomycin model reveals high similarity.
Stephan KleeSergio Picart-ArmadaKathrin WengerGerald BirkKarsten QuastDaniel VeyelWolfgang RistCoralie VioletAndreas LuippoldChristian HaslingerMatthew ThomasFrancesc Fernandez-AlbertMarc KästlePublished in: American journal of physiology. Lung cellular and molecular physiology (2023)
The most common preclinical, in vivo model to study lung fibrosis is the bleomycin-induced lung fibrosis model in 2- to 3-mo-old mice. Although this model resembles key aspects of idiopathic pulmonary fibrosis (IPF), there are limitations in its predictability for the human disease. One of the main differences is the juvenile age of animals that are commonly used in experiments, resembling humans of around 20 yr. Because IPF patients are usually older than 60 yr, aging appears to play an important role in the pathogenesis of lung fibrosis. Therefore, we compared young (3 months) and old mice (21 months) 21 days after intratracheal bleomycin instillation. Analyzing lung transcriptomics (mRNAs and miRNAs) and proteomics, we found most pathways to be similarly regulated in young and old mice. However, old mice show imbalanced protein homeostasis as well as an increased inflammatory state in the fibrotic phase compared to young mice. Comparisons with published human transcriptomic data sets (GSE47460, GSE32537, and GSE24206) revealed that the gene signature of old animals correlates significantly better with IPF patients, and it also turned human healthy individuals better into "IPF patients" using an approach based on predictive disease modeling. Both young and old animals show similar molecular hallmarks of IPF in the bleomycin-induced lung fibrosis model, although old mice more closely resemble several features associated with IPF in comparison to young animals.
Keyphrases
- idiopathic pulmonary fibrosis
- high fat diet induced
- endothelial cells
- newly diagnosed
- ejection fraction
- middle aged
- single cell
- prognostic factors
- type diabetes
- interstitial lung disease
- stem cells
- randomized controlled trial
- high glucose
- mass spectrometry
- systemic sclerosis
- drug induced
- rna seq
- transcription factor
- cell therapy
- diabetic rats
- deep learning
- insulin resistance
- big data
- small molecule
- patient reported
- artificial intelligence