ArticleInternational journal of molecular sciences2024
Novel AT2 Cell Subpopulations and Diagnostic Biomarkers in IPF: Integrating Machine Learning with Single-Cell Analysis.
Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Targeting alveolar type II cell dysfunction in idiopathic pulmonary fibrosis: Molecular mechanisms and emerging therapeutic strategies (Review).International journal of molecular medicine · 2026Review
- A systematic review of artificial intelligence-based diagnosis models for idiopathic pulmonary fibrosis.Journal of thoracic disease · 2026Review
- IPF AT2 cells are stuck in transition and biophysically dysfunctional.bioRxiv : the preprint server for biology · 2026Article
- Idiopathic Pulmonary Fibrosis: Cellular Heterogeneity, Mechanisms, and Therapeutic Implications.MedComm · 2025Review
- Predictive and personalized approaches for idiopathic pulmonary fibrosis: a Wnt-related gene set scoring framework integrating single-cell sequencing, spatial transcriptomics, and machine learning for diagnosis and prognosis.Functional & integrative genomics · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
Idiopathic pulmonary fibrosis (IPF) is a long-term condition with an unidentified cause, and currently there are no specific treatment options available. Alveolar epithelial type II cells (AT2) constitute a heterogeneous population crucial for secreting and regenerative functions in the alveolus, essential for maintaining lung homeostasis. However, a comprehensive investigation into their cellular diversity, molecular features, and clinical implications is currently lacking. In this study, we conducted a comprehensive examination of single-cell RNA sequencing data from both normal and fibrotic lung tissues. We analyzed alterations in cellular composition between IPF and normal tissue and investigated differentially expressed genes across each cell population. This analysis revealed the presence of two distinct subpopulations of IPF-related alveolar epithelial type II cells (IR_AT2). Subsequently, three unique gene co-expression modules associated with the IR_AT2 subtype were identified through the use of hdWGCNA. Furthermore, we refined and identified IPF-related AT2-related gene (IARG) signatures using various machine learning algorithms. Our analysis demonstrated a significant association between high IARG scores in IPF patients and shorter survival times (
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