Molecular endotypes predict differential response to immunosuppressant therapy in non-IPF interstitial lung disease. Academic Article uri icon

Overview

abstract

  • RATIONALE: Interstitial lung diseases (ILDs) are a clinically and biologically diverse group of disorders characterized by varying inflammation and fibrosis of the lung parenchyma. Immunosuppressant therapy is commonly used to treat non-idiopathic pulmonary fibrosis (non-IPF) ILD, but treatment response is variable and difficult to predict. OBJECTIVE: Identify and validate molecular endotypes of non-IPF ILD. METHODS: Twenty plasma proteins associated with inflammation were used to perform latent class analysis (LCA) in two observational non-IPF ILD cohorts (discovery n = 676; validation n = 585). Proteins were measured using a semi-quantitative Olink Explore 3072 platform. The primary outcome was three-year transplant-free survival. Weighted Cox regression was used to assess differential response to mycophenolate or azathioprine in each cohort according to molecular endotype classification. RESULTS: A two-class model best fit both cohorts (p < 0.01), with Class 2 comprising ∼30% of patients. Compared to Class 1, Class 2 was associated with significantly lower three-year transplant-free survival in both discovery (78% vs. 36%, p < 0.001) and validation (83% vs. 46%, p < 0.001) cohorts. Significant interaction between molecular endotype and immunosuppressant exposure was observed in both cohorts (discovery pinteraction=0.022; validation pinteraction=0.019), with survival benefit seen only in Class 2. In pooled analysis, similar trends were observed irrespective of ILD subtype. Pathway analysis supported enrichment of inflammatory signatures in Class 2. CONCLUSION: In this multicenter observational cohort study, we identified and validated two distinct molecular endotypes of non-IPF ILD with divergent outcomes and response to immunosuppressant therapy. These endotypes could inform precision medicine strategies and clinical trial design in ILD.

publication date

  • January 30, 2026

Identity

Digital Object Identifier (DOI)

  • 10.1093/ajrccm/aamag006

PubMed ID

  • 41738192