Search

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.

Chronic obstructive pulmonary disease (COPD) is characterised by airway inflammation and progressive airflow limitation, whereas idiopathic pulmonary fibrosis (IPF) is characterised by a restrictive pattern due to fibrosis and impaired gas exchange. We undertook metabolomic analysis of blood samples in IPF, COPD and healthy controls (HC) to determine differences in circulating molecules and identify novel pathogenic pathways. An untargeted metabolomics using an ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometer (UHPLC-QTOF-MS) was performed to profile plasma of patients with COPD (n = 21), and IPF (n = 24) in comparison to plasma from healthy controls (HC; n = 20). The most significant features were identified using multiple database matching. One-way ANOVA and variable importance in projection (VIP) scores were also used to highlight metabolites that influence the specific disease groups. Non-polar metabolites such as fatty acids (FA) and membrane lipids were well resolved and a total of 4805 features were identified. The most prominent metabolite composition differences in lipid mediators identified at ∼2-3 fold higher in both diseases compared to HC were palmitoleic acid, oleic acid and linoleic acid; and dihydrotestosterone was lower in both diseases. We demonstrated that COPD and IPF were characterised by systemic changes in lipid constituents such as essential FA sampled from circulating plasma.

BackgroundIdiopathic pulmonary fibrosis (IPF) is a progressive lung disease in which circulatory biomarkers have the potential for guiding management in clinical practice. We assessed the prognostic role of serum biomarkers in three independent IPF cohorts: Australian Idiopathic Pulmonary Fibrosis Registry (AIPFR), Trent Lung Fibrosis (TLF) and Prospective Observation of Fibrosis in the Lung Clinical Endpoints (PROFILE).MethodsIn the AIPFR cohort, candidate proteins were assessed by ELISA as well as in an unbiased proteomic approach. LASSO (least absolute shrinkage and selection operator) regression was used to restrict the selection of markers that best accounted for the progressor phenotype at 1 year in the AIPFR cohort, and subsequently prospectively selected for replication in the validation TLF cohort and assessed retrospectively in the PROFILE cohort. Four significantly replicating biomarkers were aggregated into a progression index model based on tertiles of circulating concentrations.Results189 participants were included in the AIPFR cohort, 205 participants from the TLF cohort and 122 participants from the PROFILE cohort. Differential biomarker expression was observed by ELISA and replicated for osteopontin, matrix metallopeptidase-7, intercellular adhesion molecule-1 and periostin for those with a progressor phenotype at 1 year. Proteomic data did not replicate. The progression index in the AIPFR, TLF and PROFILE cohorts predicted risk of progression, mortality and progression-free survival. A statistical model incorporating the progression index demonstrated the capacity to distinguish disease progression at 12 months, which was increased beyond the clinical GAP (gender, age and physiology) score model alone in all cohorts, and significantly so within the incidence-based TLF and PROFILE cohorts.ConclusionA panel of circulatory biomarkers can provide potentially valuable clinical assistance in the prognosis of IPF patients.

Idiopathic pulmonary fibrosis (IPF) is a chronic disease characterised by progressive decline in pulmonary function. The rate of decline can vary, with some patients remaining stable over longer periods of time and others rapidly progressing [1]. tThe variable progression of this disease makes it difficult to elucidate pathogenic pathways involved in the initiation and progression of IPF. Advances in high-throughput gene-expression analyses have led to improvements in our understanding of disease biology and prognostic gene signatures. We hypothesise that IPF has a unique circulatory transcriptional profile compared to healthy controls, with additional differences between stable and progressive disease likely related to disease pathogenesis. Footnotes This manuscript has recently been accepted for publication in the European Respiratory Journal . It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article. Conflict of interest: Miss Clynick has nothing to disclose. Conflict of interest: Dr. Jo has nothing to disclose. Conflict of interest: Dr. Corte has nothing to disclose. Conflict of interest: Dr. Glaspole has nothing to disclose. Conflict of interest: Dr. Grainge has nothing to disclose. Conflict of interest: Dr. Hopkins has nothing to disclose. Conflict of interest: Dr. Reynolds has nothing to disclose. Conflict of interest: Dr. Chapman has nothing to disclose. Conflict of interest: Dr. Walters has nothing to disclose. Conflict of interest: Dr. Zappala has nothing to disclose. Conflict of interest: Dr. Keir has nothing to disclose. Conflict of interest: Dr. Cooper has nothing to disclose. Conflict of interest: Dr. Mahar has nothing to disclose. Conflict of interest: Dr. Ellis has nothing to disclose. Conflict of interest: Dr. Goh has nothing to disclose. Conflict of interest: Dr. Baltic has nothing to disclose. Conflict of interest: Miss Ryan has nothing to disclose. Conflict of interest: Dr. Tan has nothing to disclose. Conflict of interest: Dr. Moodley has nothing to disclose.

Idiopathic pulmonary fibrosis (IPF) is a chronic disease characterised by an overall poor prognosis. The rate of disease decline and progression to death can vary, with some patients remaining stable over longer periods of time and others displaying rapid progression [1, 2]. The highly heterogeneous nature of this disease makes it difficult to elucidate the pathways involved in the initiation and progression of IPF and what determines the clinical trajectory of these patients. Advances in high-throughput gene expression analyses have led to improvements in our understanding of disease biology with insights into prognostic and predictive gene signatures [3]. This study sought to characterise differences in gene expression profiles found in the circulation between “stable” and “progressive” IPF patients, to help identify relevant biomarkers that may provide insights into the pathogenesis of progressive IPF. Footnotes This manuscript has recently been accepted for publication in the European Respiratory Journal . It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article. Conflict of interest: Miss Clynick has nothing to disclose. Conflict of interest: Dr. Jo has nothing to disclose. Conflict of interest: Dr. Corte has nothing to disclose. Conflict of interest: Dr. Glaspole has nothing to disclose. Conflict of interest: Dr. Grainge has nothing to disclose. Conflict of interest: Dr. Hopkins has nothing to disclose. Conflict of interest: Dr. Reynolds has nothing to disclose. Conflict of interest: Dr. Chapman has nothing to disclose. Conflict of interest: Dr. Walters has nothing to disclose. Conflict of interest: Dr. Zappala has nothing to disclose. Conflict of interest: Dr. Keir has nothing to disclose. Conflict of interest: Dr. Cooper has nothing to disclose. Conflict of interest: Dr. Mahar has nothing to disclose. Conflict of interest: Dr. Ellis has nothing to disclose. Conflict of interest: Dr. Goh has nothing to disclose. Conflict of interest: Dr. Baltic has nothing to disclose. Conflict of interest: Miss Ryan has nothing to disclose. Conflict of interest: Dr. Tan has nothing to disclose. Conflict of interest: Dr. Moodley has nothing to disclose.