There is detectable variation in the lipidomic profile between stable and progressive patients with idiopathic pulmonary fibrosis (IPF)

Abstract

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease characterized by fibrosis and progressive loss of lung function. The pathophysiological pathways involved in IPF are not well understood. Abnormal lipid metabolism has been described in various other chronic lung diseases including asthma and chronic obstructive pulmonary disease (COPD). However, its potential role in IPF pathogenesis remains unclear.

Methods: In this study, we used ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) to characterize lipid changes in plasma derived from IPF patients with stable and progressive disease. We further applied a data-independent acquisition (DIA) technique called SONAR, to improve the specificity of lipid identification.

Results: Statistical modelling showed variable discrimination between the stable and progressive subjects, revealing differences in the detection of triglycerides (TG) and phosphatidylcholines (PC) between progressors and stable IPF groups, which was further confirmed by mass spectrometry imaging (MSI) in IPF tissue.

Conclusion: This is the first study to characterise lipid metabolism between stable and progressive IPF, with results suggesting disparities in the circulating lipidome with disease progression.

Keywords: DIA; IPF; Lipids; MS; Plasma; SONAR.

Fig. 1

Total ion chromatograms for SONAR acquisitions in positive mode. The extracted ion chromatograms of spiked deuterium-labelled SPLASH LipidoMix standards in positive ion mode showing peaks corresponding to 15:0–18:1(d7) phosphatidylcholine (PC), 15:0–18:1(d7) phosphatidylethanolamine (PE), 15:0–18:1(d7) phosphatidylserine (PS), 15:0–18:1(d7) phosphatidylglycerol (PG), 15:0–18:1(d7) phosphatidylinositol (PI), 15:0–18:1(d7) phosphatidic acid (PA), 18:1(d7) lysophosphatidylcholine (LysoPC), 18:1(d7) lysophosphatidylethanolamine (LysoPE), 18:1(d7) cholesteryl ester (Chol Ester), 18:1(d7) monoglyceride (MG), 15:0–18:1(d7) diacylglycerol (DG), 15:0–18:1(d7)-15:0 triglyceride (TG), 18:1(d9) sphingomyelin (SM) and cholesterol (d7)

Fig. 2

Statistical modelling used to discriminate diseased experimental groups. a PCA score plots generated from all stable (black) and progressor (red) and QC (green) samples in both modes of acquisition. The clustering of the pooled QC samples in each acquisition modes were shown encircled in green. b The OPLS-DA and c S-plots show comparisons between stable (black) versus progressors (red) plasma samples in the aforementioned acquisition modes. The ten features of interest in each group (encircled in blue) were exported into Progenesis QI software for identification

Fig. 3

Extracted ion chromatograms and ion intensity maps of the lipid adducts generated by Mass Lynx and HD Imaging software, respectively. phosphatidylcholine (PC) and triglycerides (TG) were extracted and their associated adducts [M+NH₄]⁺, [M+K]⁺, [M+Na]⁺ and [M+H]⁺ are denoted by A, B, C and D, respectively