ArticleNature communications2025
Spatial single-cell atlas reveals regional variations in healthy and diseased human lung.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Developmental dynamics of ovine lung in health and cystic fibrosis at single-cell resolution.Functional & integrative genomics · 2026Article
- Review
- Spatial Immunology in Translation: Linking Immune Organisation to Therapeutic Outcome.Medical sciences (Basel, Switzerland) · 2026Review
- FGFR signaling establishes spatial gradients of secretory cell identities along the airway proximal-distal axis.Nature communications · 2026Article
- Integrative machine learning and single-cell analysis identifies nicotine-related diagnostic genes and myeloid remodeling in COPD.Frontiers in immunology · 2026Article
- Pulmonary neuroendocrine cells in pediatric asthma and bronchopulmonary dysplasia: neuroimmune-developmental mechanisms and translational implications.Frontiers in medicine · 2026Review
- Macrophage spatiotemporal plasticity in pulmonary diseases: decoding the niche at single-cell resolution.Frontiers in immunology · 2026Review
- Article
Corrections and comments
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Authors and funding
27 authors.
Funding
Abstract
Integration of scRNA-seq data from millions of cells revealed a high diversity of cell types in the healthy and diseased human lung. In a large and complex organ, constantly exposed to external agents, it is crucial to understand the influence of lung tissue topography or external factors on gene expression variability within cell types. Here, we apply three spatial transcriptomics approaches, to: (i) localize the majority of lung cell types, including rare epithelial cells within the tissue topography, (ii) describe consistent anatomical and regional gene expression variability within and across cell types, and (iii) reveal distinct cellular neighborhoods in specific anatomical regions and examine gene expression variations in them. We thus provide a spatially resolved tissue reference atlas in three representative regions of the healthy human lung. We further demonstrate its utility by defining previously unknown imbalances of epithelial cell type compositions in chronic obstructive pulmonary disease lungs. Our topographic atlas enables a precise description of characteristic regional cellular responses upon experimental perturbations or during disease progression.
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Registered trials
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