Bioactive lipid lysophosphatidic acid species are associated with disease progression in idiopathic pulmonary fibrosis

Abstract

Idiopathic pulmonary fibrosis (IPF) is a progressive disease with significant mortality. Prognostic biomarkers to identify rapid progressors are urgently needed to improve patient management. Since the lysophosphatidic acid (LPA) pathway has been implicated in lung fibrosis in preclinical models and identified as a potential therapeutic target, we aimed to investigate if bioactive lipid LPA species could be prognostic biomarkers that predict IPF disease progression. LPAs and lipidomics were measured in baseline placebo plasma of a randomized IPF-controlled trial. The association of lipids with disease progression indices were assessed using statistical models. Compared to healthy, IPF patients had significantly higher levels of five LPAs (LPA16:0, 16:1, 18:1, 18:2, 20:4) and reduced levels of two triglycerides species (TAG48:4-FA12:0, -FA18:2) (false discovery rate < 0.05, fold change > 2). Patients with higher levels of LPAs had greater declines in diffusion capacity of carbon monoxide over 52 weeks (P < 0.01); additionally, LPA20:4-high (≥median) patients had earlier time to exacerbation compared to LPA20:4-low (<median) patients (hazard ratio (95% CI)): 5.71 (1.17-27.72) (P = 0.031). Higher baseline LPAs were associated with greater increases in fibrosis in lower lungs as quantified by high-resolution computed tomography at week 72 (P < 0.05). Some of these LPAs were positively associated with biomarkers of profibrotic macrophages (CCL17, CCL18, OPN, and YKL40) and lung epithelial damage (SPD and sRAGE) (P < 0.05). In summary, our study established the association of LPAs with IPF disease progression, further supporting the role of the LPA pathway in IPF pathobiology.

Keywords: DLCO; Lysophosphatidic acid; exacerbation; idiopathic pulmonary fibrosis; mortality.

Fig. 1

Comparison of lipid levels between healthy controls and IPF. A multivariate linear regression model adjusted for age and sex was used to assess the differences in lipid levels between healthy controls and patients with IPF. The x-axis indicated log2(analyte abundance in IPF/analyte abundance in healthy controls), and the y-axis indicates −log10(adjusted P-value or false discovery rate of the multivariate regression). Yellow circles denote lipid species with false discovery rate <0.05; red circles denote lipid species with false discovery rate <0.05 and fold change >2.

Fig. 2

Baseline correlation of lipid species. Spearman’s rho value shown.

Fig. 3

Decline in DLCO percentage predicted and baseline biomarker levels. A multivariate linear regression model adjusted for the following covariates: age, sex, baseline FVC %pred, baseline DLCO %pred, and the geographical region was used to assess the association between (A) LPA and TAG and (B) protein biomarkers, with DLCO %pred decline calculated as slope, where the y-axis indicated the DLCO %pred change per year. ∗∗P < 0.01; ∗∗∗P < 0.001 of multivariate linear regressions.

Fig. 4

Decline in FVC percentage predicted and baseline biomarker levels. A multivariate linear regression model adjusted for the following covariates: age, sex, baseline FVC %pred, baseline DLCO %pred, and geographical region, was used to assess the association between (A) LPA and TAG and (B) protein biomarkers, with FVC %pred decline calculated as slope, where the y-axis indicated FVC %pred change per year. ∗P < 0.05; ∗∗∗P < 0.001 of multivariate linear regressions.

Fig. 5

Time to first exacerbation or respiratory hospitalization and baseline (A) lipid or (B) protein biomarker profile. Baseline biomarker profile was fitted to a Cox proportional hazards regression model adjusted for the following covariates: age, sex, baseline FVC %pred, baseline DLCO %pred, and geographical region. Multivariate linear regression P-values shown.

Fig. 6

Risk of mortality and baseline biomarker profile. The baseline biomarker profile was fitted to a multivariate logistic regression model adjusted for the following covariates: age, sex, baseline FVC %pred, baseline DLCO %pred, and geographical region. An odds ratio above 1 denotes higher odds of mortality in patients with higher levels (≥median) of biomarker compared to patients with lower levels (

Fig. 7

Fibrosis changes in left and right lower lungs by baseline (A and B) lipid and (C and D) protein biomarker profile. A multivariate linear regression model adjusted for the following covariates: age, sex, baseline FVC %pred, baseline DLCO %pred, and geographical region, was used to assess the association between (A and B) lipids, and (C and D) protein biomarkers with fibrosis change from baseline in the (A and C) left lower lungs, or (B and D) right lower lungs. #P < 0.1; ∗P < 0.05; ∗∗P < 0.01 of multivariate linear regressions.