源自组织学的空间微域揭示用于增强特发性肺纤维化诊断的多组学生物标志物

Background: Idiopathic pulmonary fibrosis (IPF) is characterized by progressive alveolar injury and extensive tissue remodeling that generate pronounced spatial heterogeneity across affected lung regions. Distinct pathological programs often coexist within adjacent microenvironments, reflecting cellular interactions and molecular circuits that drive disease progression. Although histologic assessment of H&E-stained biopsies remains central to clinical diagnosis, current evaluations lack quantitative measures that connect visual pathology to underlying biology. Integrating spatial transcriptomics with quantitative histologic features enables higher-resolution characterization of heterogeneous disease regions and provides molecular context essential for accurate diagnostic interpretation. Methods: We applied a multi-omic analytic workflow using the SpaceIQ™ platform to the publicly available Xenium H&E and spatial transcriptomics dataset reported by Vannan et al., Nat. Genet. 2025. Unbiased cell typing was performed on H&E images and spatially aligned to cell-resolved gene expression. Spatial microdomains were derived from differential organization of inferred cell populations in IPF versus healthy tissue. Gene-feature associations were computed to identify molecular markers linked to pathology-associated microdomains. Candidate biomarkers were evaluated in an independent Visium dataset from Mayr et al., Sci. Adv. 2023 to assess reproducibility across platforms and cohorts. Results: Unbiased H&E-derived cell typing revealed finer structural organization within pathologist-annotated regions and captured subregional distinctions in fibrotic and non-fibrotic compartments. Spatial microdomains identified from cell-type arrangements distinguished IPF-specific architectural patterns and yielded gene signatures associated with epithelial dysregulation, inflammatory macrophages, and extracellular matrix remodeling. These signatures showed consistent enrichment in corresponding molecular niches within the validation cohort. Cross-cohort mapping further demonstrated reproducible cell-type differences and implicated conserved pathways involved in epithelial stress responses, fibroblast activation, and tissue remodeling. Conclusions: Integrating quantitative histologic features with spatial transcriptomics provides a robust framework for linking visual pathology to molecular mechanisms in IPF. Histology-derived microdomains reveal reproducible biological programs across independent cohorts and support the identification of clinically relevant biomarkers. This multi-omic approach enables more objective, biologically grounded interpretation of heterogeneous fibrotic regions and has the potential to improve diagnostic evaluation and patient stratification in IPF.