Similar Datasets
Project description: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 (CB1 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.
| S-EPMC10238219 | biostudies-literature
Project description:Pulmonary fibrosis (PF) is a progressive disease with a poor prognosis and lack of effective treatments. Therefore, identifying effective therapeutic modalities is required to improve outcome. However, the lack of predictive progressive disease biomarkers in the clinic causes a significant gap in the preclinical to clinical translational process. Here, we assessed and identified progressive alterations in pulmonary function, transcriptomics, and metabolomics in mice lungs at 7, 14, 21, and 28 days after a single dose of oropharyngeal bleomycin. By integrating multi-omics data, we identified two central gene subnetworks associated with multiple critical pathological changes in transcriptomics and metabolomics as well as pulmonary function. We presented 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. Our study also indicated peripheral CB1R antagonism as a rational therapeutic target for clinical translation in PF.
2023-04-11 | GSE213709 | GEO
Project description:Pulmonary fibrosis (PF) is a progressive disease with a poor prognosis and lack of effective treatments. Therefore, identifying effective therapeutic modalities is required to improve outcome. However, the lack of predictive progressive disease biomarkers in the clinic causes a significant gap in the preclinical to clinical translational process. Here, we assessed and identified progressive alterations in pulmonary function, transcriptomics, and metabolomics in mice lungs at 7, 14, 21, and 28 days after a single dose of oropharyngeal bleomycin. By integrating multi-omics data, we identified two central gene subnetworks associated with multiple critical pathological changes in transcriptomics and metabolomics as well as pulmonary function. We presented 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. Our study also indicated peripheral CB1R antagonism as a rational therapeutic target for clinical translation in PF.
2023-04-11 | GSE217814 | GEO
Project description:An integrative multiomics framework for identification of therapeutic targets in pulmonary fibrosis
| PRJNA900598 | ENA
Project description:An integrative multiomics framework for identification of therapeutic targets in pulmonary fibrosis [TimeSeries]
| PRJNA882100 | ENA
Project description:An integrative multiomics framework for identification of therapeutic targets in pulmonary fibrosis [CB1R KO]
| PRJNA900595 | ENA
Project description:There is a tremendous current interest in measuring multiple types of omics features (e.g., DNA sequences, RNA expressions, methylation profiles, metabolic profiles, protein expressions) on a large number of subjects. Although genotypes are typically available for all study subjects, other data types may be measured only on a subset of subjects due to cost or other constraints. In addition, quantitative omics measurements, such as metabolite levels and protein expressions, are subject to detection limits in that the measurements below (or above) certain thresholds are not detectable. In this article, we propose a rigorous and powerful approach to handle missing values and detection limits in integrative analysis of multiomics data. We relate quantitative omics variables to genetic variants and other variables through linear regression models and relate phenotypes to quantitative omics variables and other variables through generalized linear models. We derive the joint-likelihood for the two sets of models by allowing arbitrary patterns of missing values and detection limits for quantitative omics variables. We carry out maximum-likelihood estimation through computationally fast and stable algorithms. The resulting estimators are approximately unbiased and statistically efficient. An application to a major study on chronic obstructive lung disease yielded new biological insights.
| S-EPMC7951090 | biostudies-literature
Project description:Idiopathic pulmonary fibrosis (IPF) is a chronic fibrotic disease of the lung that is marked by progressive decline in pulmonary function and ultimately respiratory failure. Genetic and environmental risk factors have been identified that indicate injury to, and dysfunction of the lung epithelium is central to initiating the pathogenic process. Following injury to the lung epithelium, growth factors, matrikines and extracellular matrix driven signaling together activate a variety of repair pathways that lead to inflammatory cell recruitment, fibroblast proliferation and expansion of the extracellular matrix, culminating in tissue fibrosis. This tissue fibrosis then leads to changes in the biochemical and biomechanical properties of the extracellular matrix, which potentiate profibrotic mechanisms through a "feed-forward cycle." This review provides an overview of the interactions of the pathogenic mechanisms of IPF with a focus on epithelial-mesenchymal crosstalk and the extracellular matrix as a therapeutic target for idiopathic pulmonary fibrosis.
| S-EPMC6146058 | biostudies-literature
Project description:Alzheimer's disease (AD) is the most frequent cause of neurodegenerative dementia and affects nearly 50 million people worldwide. Early stage diagnosis of AD is challenging, and there is presently no effective treatment for AD. The specific genetic alterations and pathological mechanisms of the development and progression of dementia remain poorly understood. Therefore, identifying essential genes and molecular pathways that are associated with this disease's pathogenesis will help uncover potential treatments. In an attempt to achieve a more comprehensive understanding of the molecular pathogenesis of AD, we integrated the differentially expressed genes (DEGs) from six microarray datasets of AD patients and controls. We identified ATPase H+ transporting V1 subunit A (ATP6V1A), BCL2 interacting protein 3 (BNIP3), calmodulin-dependent protein kinase IV (CAMK4), TOR signaling pathway regulator-like (TIPRL), and the translocase of outer mitochondrial membrane 70 (TOMM70) as upregulated DEGs common to the five datasets. Our analyses revealed that these genes exhibited brain-specific gene co-expression clustering with OPA1, ITFG1, OXCT1, ATP2A2, MAPK1, CDK14, MAP2K4, YWHAB, PARK2, CMAS, HSPA12A, and RGS17. Taking the mean relative expression levels of this geneset in different brain regions into account, we found that the frontal cortex (BA9) exhibited significantly (p < 0.05) higher expression levels of these DEGs, while the hippocampus exhibited the lowest levels. These DEGs are associated with mitochondrial dysfunction, inflammation processes, and various pathways involved in the pathogenesis of AD. Finally, our blood-brain barrier (BBB) predictions using the support vector machine (SVM) and LiCABEDS algorithm and molecular docking analysis suggested that antrocin is permeable to the BBB and exhibits robust ligand-receptor interactions with high binding affinities to CAMK4, TOMM70, and T1PRL. Our results also revealed good predictions for ADMET properties, drug-likeness, adherence to Lipinskís rules, and no alerts for pan-assay interference compounds (PAINS) Conclusions: These results suggest a new molecular signature for AD parthenogenesis and antrocin as a potential therapeutic agent. Further investigation is warranted.
| S-EPMC8539161 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2012-11-27 | GSE34941 | GEO