ArticleJournal of translational medicine2025
Genetic insights into idiopathic pulmonary fibrosis: a multi-omics approach to identify potential therapeutic targets.
Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Multi-omics insights into the mechanisms and prognosis of IPF.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2026Review
- Next-Generation Sequencing in Pulmonary Fibrosis: Translational Promise and Current Clinical Limitations.Current issues in molecular biology · 2026Review
- Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications.Signal transduction and targeted therapy · 2026Review
- LncRNA HOXA11-AS promotes idiopathic pulmonary fibrosis progression via sponging miR-148a-3p and regulating SMAD2.Hereditas · 2026Article
- The scramblase anoctamin 9 controls the immune response in lymphocytes.Cellular and molecular life sciences : CMLS · 2026Article
- Network pharmacology and molecular docking reveal mechanisms of amiodarone-induced pulmonary fibrosis.Scientific reports · 2026Article
- Jiangtang Decoction for Type 2 Diabetes and NAFLD: Integrative AnalysisEndocrine, metabolic & immune disorders drug targets · 2026Article
- Multi-omics to study chronic respiratory diseases and viral infections.European respiratory review : an official journal of the European Respiratory Society · 2026Review
- Multi-omics approaches in idiopathic pulmonary fibrosis: from molecular mechanisms to therapeutic targets and precision medicine.Frontiers in pharmacology · 2026Review
- Idiopathic Pulmonary Fibrosis: Cellular Heterogeneity, Mechanisms, and Therapeutic Implications.MedComm · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Funding
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Abstract
objectiveTo identify potential therapeutic targets and evaluate the safety profiles for Idiopathic Pulmonary Fibrosis (IPF) using a comprehensive multi-omics approach.
methodWe integrated genomic and transcriptomic data to identify therapeutic targets for IPF. First, we conducted a transcriptome-wide association study (TWAS) using the Omnibus Transcriptome Test using Expression Reference Summary data (OTTERS) framework, combining plasma expression quantitative trait loci (eQTL) data with IPF Genome-Wide Association Studies (GWAS) summary statistics from the Global Biobank (discovery) and Finngen (duplication). We then applied Mendelian randomization (MR) to explore causal relationships. RNA-seq co-expression analysis (bulk, single-cell and spatial transcriptomics) was used to identify critical genes, followed by molecular docking to evaluate their druggability. Finally, phenome-wide MR (PheW-MR) using GWAS data from 679 diseases in the UK Biobank assessed the potential adverse effects of the identified genes.
resultWe identified 696 genes associated with IPF in the discovery dataset and 986 genes in the duplication dataset, with 126 overlapping genes through TWAS. MR analysis revealed 29 causal genes in the discovery dataset, with 13 linked to increased and 16 to decreased IPF risk. Summary data-based MR (SMR) confirmed six essential genes: ANO9, BRCA1, CCDC200, EZH1, FAM13A, and SFR1. Bulk RNA-seq showed FAM13A upregulation and SFR1 and EZH1 downregulation in IPF. Single-cell RNA-seq revealed gene expression changes across cell types. Molecular docking identified binding solid affinities for essential genes with respiratory drugs, and PheW-MR highlighted potential side effects.
conclusionWe identified six key genes-ANO9, BRCA1, CCDC200, EZH1, FAM13A, and SFR1-as potential drug targets for IPF. Molecular docking revealed strong drug affinities, while PheW-MR analysis highlighted therapeutic potential and associated risks. These findings offer new insights for IPF treatment and further investigation of potential side effects.
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