ArticleInternational journal of molecular sciences2023
Machine Learning and Single-Cell Analysis Identify Molecular Features of IPF-Associated Fibroblast Subtypes and Their Implications on IPF Prognosis.
Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 16 citations in OpenAlex.
- Identification of papillary thyroid carcinoma-associated epithelial cell subpopulations and diagnostic biomarkers: integrating machine learning with single-cell analysis.Translational cancer research · 2026Article
- Plasma proteomic and machine learning models for differentiating idiopathic pulmonary fibrosis and connective tissue disease-associated interstitial lung disease: findings from a prospective cohort.Respiratory research · 2026Article
- Screening Autophagy-Related DKD Biomarkers Based on Bulk RNA and Single-Cell Analysis and Uncovering Their Regulatory Mechanisms in DKD Renal Fibrosis.Journal of diabetes research · 2026Article
- Mesenchymal stem cells and derived extracellular vesicles in major respiratory diseases: from multifaceted molecular mechanisms to clinical perspectives.Frontiers in cell and developmental biology · 2026Review
- Artificial intelligence in idiopathic pulmonary fibrosis: advances, challenges and future directions.The European respiratory journal · 2026Review
- Idiopathic Pulmonary Fibrosis: Cellular Heterogeneity, Mechanisms, and Therapeutic Implications.MedComm · 2025Review
- Integrated bulk and single-cell transcriptomics identify RELB, S100A9, and SOCS1 as key autophagy-endoplasmic reticulum stress genes linking T2DM with MAFLD.Scientific reports · 2025Article
- Exploring the Cellular and Molecular Landscape of Idiopathic Pulmonary Fibrosis: Integrative Multi-Omics and Single-Cell Analysis.Biomedicines · 2025Article
- Exploring the biological functions and immune regulatory roles of IRAK3, TNFRSF1A, CX3CR1, and JUNB in T2DM combined with MAFLD: integrated bioinformatics and single-cell analysis.Frontiers in immunology · 2025Article
- An Overview of the Role of Genetic factors in Idiopathic Pulmonary Fibrosis: Insights from Epidemiology to Prognosis.International journal of medical sciences · 2025Review
- Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC.Frontiers in immunology · 2025Article
- Prediction and immune landscape study of potentially key autophagy-related biomarkers in preeclampsia with gestational diabetes mellitus.Frontiers in immunology · 2025Article
- Prognostic model of fibroblasts in idiopathic pulmonary fibrosis by combined bulk and single-cell RNA-sequencing.Heliyon · 2024Article
- Novel AT2 Cell Subpopulations and Diagnostic Biomarkers in IPF: Integrating Machine Learning with Single-Cell Analysis.International journal of molecular sciences · 2024Article
- Do Ultrasound Lung Abnormalities Correlate to Biomarkers and Male Gender in Rheumatoid Arthritis Patients? A Monocentric Cross-Sectional Study.Journal of clinical medicine · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Idiopathic pulmonary fibrosis (IPF) is a devastating lung disease of unknown cause, and the involvement of fibroblasts in its pathogenesis is well recognized. However, a comprehensive understanding of fibroblasts' heterogeneity, their molecular characteristics, and their clinical relevance in IPF is lacking. In this study, we aimed to systematically classify fibroblast populations, uncover the molecular and biological features of fibroblast subtypes in fibrotic lung tissue, and establish an IPF-associated, fibroblast-related predictive model for IPF. Herein, a meticulous analysis of scRNA-seq data obtained from lung tissues of both normal and IPF patients was conducted to identify fibroblast subpopulations in fibrotic lung tissues. In addition, hdWGCNA was utilized to identify co-expressed gene modules associated with IPF-related fibroblasts. Furthermore, we explored the prognostic utility of signature genes for these IPF-related fibroblast subtypes using a machine learning-based approach. Two predominant fibroblast subpopulations, termed IPF-related fibroblasts, were identified in fibrotic lung tissues. Additionally, we identified co-expressed gene modules that are closely associated with IPF-fibroblasts by utilizing hdWGCNA. We identified gene signatures that hold promise as prognostic markers in IPF. Moreover, we constructed a predictive model specifically focused on IPF-fibroblasts which can be utilized to assess disease prognosis in IPF patients. These findings have the potential to improve disease prediction and facilitate targeted interventions for patients with IPF.
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Registered trials
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