An Integrative Multiomics Framework for Identification of Therapeutic Targets in Pulmonary Fibrosis.
Muhammad ArifAbhishek BasuKaelin M WolfJoshua K ParkLenny PommerolleMadeline BeheeBernadette R GochuicoResat CinarPublished in: Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2023)
Pulmonary fibrosis (PF) is a heterogeneous disease with a poor prognosis. Therefore, identifying additional therapeutic modalities is required to improve outcome. However, the lack of biomarkers of disease progression hampers the preclinical to clinical translational process. Here, this work assesses and identifies progressive alterations in pulmonary function, transcriptomics, and metabolomics in the mouse lung at 7, 14, 21, and 28 days after a single dose of oropharyngeal bleomycin. By integrating multi-omics data, this work identifies two central gene subnetworks associated with multiple critical pathological changes in transcriptomics and metabolomics as well as pulmonary function. This work presents a multi-omics-based framework to establish a translational link between the bleomycin-induced PF model in mice and human idiopathic pulmonary fibrosis to identify druggable targets and test therapeutic candidates. This work also indicates peripheral cannabinoid receptor 1 (CB 1 R) antagonism as a rational therapeutic target for clinical translation in PF. Mouse Lung Fibrosis Atlas can be accessed freely at https://niaaa.nih.gov/mouselungfibrosisatlas.
Keyphrases
- pulmonary fibrosis
- single cell
- poor prognosis
- idiopathic pulmonary fibrosis
- genome wide
- long non coding rna
- mass spectrometry
- endothelial cells
- multiple sclerosis
- copy number
- big data
- interstitial lung disease
- rheumatoid arthritis
- bone marrow
- mesenchymal stem cells
- binding protein
- cell therapy
- genome wide identification
- drug induced
- oxidative stress
- data analysis
- chemotherapy induced