Metabolic Dysregulation in Idiopathic Pulmonary Fibrosis

Abstract

Idiopathic pulmonary fibrosis (IPF) is a fibroproliferative disorder limited to the lung. New findings, starting from our proteomics studies on IPF, suggest that systemic involvement with altered molecular mechanisms and metabolic disorder is an underlying cause of fibrosis. The role of metabolic dysregulation in the pathogenesis of IPF has not been extensively studied, despite a recent surge of interest. In particular, our studies on bronchoalveolar lavage fluid have shown that the renin-angiotensin-aldosterone system (RAAS), the hypoxia/oxidative stress response, and changes in iron and lipid metabolism are involved in onset of IPF. These processes appear to interact in an intricate manner and to be related to different fibrosing pathologies not directly linked to the lung environment. The disordered metabolism of carbohydrates, lipids, proteins and hormones has been documented in lung, liver, and kidney fibrosis. Correcting these metabolic alterations may offer a new strategy for treating fibrosis. This paper focuses on the role of metabolic dysregulation in the pathogenesis of IPF and is a continuation of our previous studies, investigating metabolic dysregulation as a new target for fibrosis therapy.

Keywords: idiopathic pulmonary fibrosis; iron metabolism; lipid metabolism; metabolic dysregulation; oxidative stress; renin–angiotensin–aldosterone system.

Figure 1

Schematic representation of the renin–angiotensin–aldosterone system (RAAS). AGT (ANGT) in green represent the dysregulated protein that we found with the proteomic analysis. In red and blue, the opposite effects of RAAS.

Figure 2

Schematic representation of the HIF1 signalling pathway. In green are highlighted the pathway maps identified by the proteomics and bioinformatics analyses. In red, the modulation and the effects in IPF. In orange, the involvement of the mitochondrial activity.

Figure 3

Schematic representation of the PPAR and JAK-STAT signalling pathways. In green are highlighted the proteins identified by the proteomics and bioinformatics analyses. In red, the modulation and the effects in IPF.

Figure 4

Protein interactome by MetaCore software correlating all the proteins reported in Table 1 in a hub-centric network. APOA1 in HDL, GSTP1, Alpha 1-antitrypsin, Angiotensinogen, APOC3 (red circles) are the central functional hubs i.e., the proteins with a high number of interactions with other modulators in the interactome. The red arrows indicate the inhibition, the green arrows mean inductions, and the grey arrows indicate a generic correlation. The teal highlighted lines indicate the well-known canonical molecular pathways. The relative figure legend is in Supplemental Material in Figure S1.

Figure 5

Enrichment analysis performed by the MetaCore software tool “Drug look up for your data”. Figure shows drugs related to the differential proteins reported in Table 1 considered a potential target of treatment.