Transcriptomics of interstitial lung disease: a systematic review and meta-analysis

Area of Science:

• Pulmonary Medicine
• Genomics
• Bioinformatics

Background:

• Gene expression studies offer insights into interstitial lung disease (ILD) mechanisms.
• Existing studies often have limited sample sizes and lack subtype comparisons.
• Transcriptomic signatures are crucial for understanding ILD heterogeneity.

Purpose of the Study:

• To identify and validate consensus transcriptomic signatures for ILD subtypes.
• To overcome limitations of small sample sizes and scarce between-subtype comparisons in ILD research.
• To develop robust classification models for fibrotic ILD subtypes.

Main Methods:

• Systematic review and meta-analysis of individual participant data from fibrotic ILD transcriptomics studies.
• Inclusion of bulk transcriptomics from adult human ILD samples, excluding single-cell studies.
• Integration of patient-level data from 43 studies using multivariable algorithms for model development.

Main Results:

• Identified validated transcriptomic signatures for idiopathic pulmonary fibrosis, hypersensitivity pneumonitis, nonspecific interstitial pneumonia, and systemic sclerosis-associated ILD.
• Achieved high diagnostic accuracy (AUCs ranging from 0.91 to 0.99) for individual ILD subtypes against controls.
• Developed novel signatures to discriminate idiopathic pulmonary fibrosis (AUC 0.71) and hypersensitivity pneumonitis (AUC 0.76) from other fibrotic ILDs.
• Discovered molecular endotypes associated with reduced lung function using unsupervised learning.

Conclusions:

• Presents the first systematic review and largest meta-analysis of fibrotic ILD transcriptomics.
• Identified reproducible transcriptomic signatures with significant clinical relevance for ILD subtypes.
• Highlights the potential of transcriptomics for ILD classification and understanding disease mechanisms.