Distinct Metabolic Signatures Linked to High-Resolution Computed Tomography Radiographic Phenotypes in Stable and Progressive Fibrotic Lung Disease

TL;DR

This study links specific metabolic patterns to lung disease progression using high-resolution imaging and blood metabolite analysis.

Contribution

The integration of HRCT radiographic scores with metabolomic profiling reveals distinct metabolic signatures for stable versus progressive fibrotic lung disease.

Findings

Stable IPF/ILD is associated with moderate negative correlations between key metabolites and HRCT scores.

Progressive disease shows weak positive correlations between metabolites and HRCT scores, with distinct phospholipid and metabolite abundance patterns.

Metabolomic profiling combined with HRCT successfully differentiates stable from progressive fibrotic lung disease.

Abstract

Background: This study aimed to identify distinct metabolic signatures associated with disease progression by integrating high-resolution computed tomography (HRCT) visual scoring with comprehensive metabolomic profiling. Materials and Methods: This single-center, cross-sectional study enrolled 60 idiopathic pulmonary fibrosis/interstitial lung disease (IPF/ILD) patients with usual interstitial pneumonia pattern. Participants underwent standardized pulmonary function testing, HRCT imaging, and peripheral blood collection for metabolomic analysis using one-dimensional hydrogen nuclear magnetic resonance spectroscopy and ultra-high-performance liquid chromatography coupled to tandem mass spectrometry. Linear regression analysis integrated radiographic scores with metabolomic profiles, adjusted for multiple covariates. Results: Stable IPF/ILD exhibited moderate negative correlations between the six most significant metabolites and HRCT scores (r = −0.27 to −0.51), along with a high abundance of specific phospholipids (triacylglycerol, monoacylglycerol, phosphatidylglycerol, phosphatidylethanolamine, diacylglycerol), sphingomyelin, ceramide, and acylcarnitine. In contrast, progressive disease showed weak positive correlations between the six most significant metabolites and HRCT scores (r = 0.19–0.26), and moderate negative correlation between specific triacylglycerol species and HRCT scores (r = −0.37–0.4). Furthermore, metabolomic analysis in individuals with progressive disease revealed both high and low abundances of specific phospholipid species (including high and low triacylglycerol species, as well as low levels of phosphatidylglycerol, phosphatidylethanolamine, phosphatidylcholine, phosphatidylserine, and phosphatidylinositol), along with high levels of certain sphingomyelin, ceramide, taurine, and purine bases, and low levels of xanthine and lactic acid observed. Conclusions: Integration of systematic HRCT semi-quantitative scoring with metabolomic profiling successfully differentiated stable from progressive IPF/ILD through distinct molecular-radiographic signatures.

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