Signaling network of lipids as a comprehensive scaffold for omics data integration in sputum of COPD patients

https://doi.org/10.1016/j.bbalip.2015.07.005Get rights and content

Highlights

  • We integrated omics data on the lipid signaling network in sputum of COPD patients.

  • Sphingolipid, arachidonic acid, hypoxia and energy signaling are covered in SpLiCO.

  • There is an important crosstalk between the studied lipid signaling pathways.

  • Hypoxia strongly influences the downstream pathways as a primary distributing factor.

  • Lipid signaling is important in the pathogenesis of COPD in smokers and ex-smokers.

Abstract

Chronic obstructive pulmonary disease (COPD) is a heterogeneous and progressive inflammatory condition that has been linked to the dysregulation of many metabolic pathways including lipid biosynthesis. How lipid metabolism could affect disease progression in smokers with COPD remains unclear. We cross-examined the transcriptomics, proteomics, metabolomics, and phenomics data available on the public domain to elucidate the mechanisms by which lipid metabolism is perturbed in COPD. We reconstructed a sputum lipid COPD (SpLiCO) signaling network utilizing active/inactive, and functional/dysfunctional lipid-mediated signaling pathways to explore how lipid-metabolism could promote COPD pathogenesis in smokers. SpLiCO was further utilized to investigate signal amplifiers, distributers, propagators, feed-forward and/or -back loops that link COPD disease severity and hypoxia to disruption in the metabolism of sphingolipids, fatty acids and energy. Also, hypergraph analysis and calculations for dependency of molecules identified several important nodes in the network with modular regulatory and signal distribution activities. Our systems-based analyses indicate that arachidonic acid is a critical and early signal distributer that is upregulated by the sphingolipid signaling pathway in COPD, while hypoxia plays a critical role in the elevated dependency to glucose as a major energy source. Integration of SpLiCo and clinical data shows a strong association between hypoxia and the upregulation of sphingolipids in smokers with emphysema, vascular disease, hypertension and those with increased risk of lung cancer.

Introduction

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death globally, and is expected to take one billion lives by the end of the 21st century [1], [2]. The disease is characterized by irreversible reduction of the forced expiratory volume, and dynamic airflow obstruction [3]. Given the rise in the prevalence of COPD and its economic impact on medical expenditure, there is a strong and unmet need for improvement in its diagnosis and treatment [4]. Little is known about the exact pathophysiology of this complex and systemic disease, however, factors such as oxidative stress, alteration in immune responses, cell proliferation, apoptosis, and senescence are among some of the strong contributing factors in human COPD [3]. Although cigarette smoking is the most important risk factor for development of COPD, not all smokers develop the disease, indicating the existence of a complex genetic and environmental predisposition that plays a significant role in the pathogenesis of this disease. Furthermore, changing life-style and increased air pollution in most major cities are known contributing factors that worsen lung inflammatory diseases [5]. Therefore, a dissection of factors that play a role in the exacerbation and progression of the disease is needed for delivering better preventive strategies in COPD. Prior studies based on lung tissue, bronchial alveolar lavage fluid, sputum, blood and other bodily fluid samples from COPD patients have indicated that oxidative stress, inflammation and the protease–antiproteases imbalance are the three main molecular manifestations in COPD [6]. An important step toward understanding the biological mechanisms underlying the pathology of a complex disease is a refined understanding of its clinical heterogeneity that will improve diagnosis, define disease phenotypes and facilitate therapy. Therefore, we reasoned that a systemic approach to unravel the complex molecular pathways underpinning the disease could identify common metabolic and signaling elements in COPD pathogenesis.

Structural and physical properties of lipids are diverse and range from neutral molecules (e.g. triacylglycerols; TAGs, sterols) to polar molecules (e.g. glycerophospholipids; GPLs). Lipid metabolism plays many critical roles in biological processes, and perturbation of this signaling network has been shown to impair cell structure–function [7]. Dynamic anabolism and catabolism of lipids in response to dietary perturbations, energy metabolism (e.g. physical activity) and environmental factors (e.g. temperature, and infections) indicate their essential roles in local and systemic cellular functions. Mechanistic animal studies show that diets high in saturated fatty acids (SFAs, such as palmitic acid) and/or cholesterol are accompanied by infiltrating macrophages that secrete pro-inflammatory mediators that induce systemic inflammation [8]. Therefore, we hypothesized that changes in lipid signaling might be associated with structural and regulatory functions in the pathogenesis of COPD [9], [10].

We used data integration to provide comprehensive analysis that unified and illustrated the consensus of several heterogeneous experiments using diverse resources to increase confidence in the interpretation of the results. In this study, we performed a multilayer data analysis (transcriptome, proteome, metabolome and phenome) and integrated the results on a scaffold of the lipid signaling network that we termed SpLiCO (Sputum_Lipid_COPD). A four-way crosstalk in response to hypoxia, identified possible signaling pathways between cyclooxygenase, lipogenesis/lipolysis and sphingolipids that are critical distributor-, propagator- and amplifier-metabolites in impaired apoptosis and efferocytosis, cytokine signaling and inflammation.

Section snippets

Dataset

Literature search was performed in the PubMed database and about 1400 articles were archived using the keyword “sputum” in the title, and each of the words “chronic obstructive pulmonary disease”, “COPD”, “sputum”, “smoke”, “smokers”, “smoking”, “cigarette”, and “tobacco” within the abstract and vice versa. Articles were then filtered to only sputum reports for COPD patients (smokers and ex-smokers), from 1950 to 2015 (April, 25, 2015). Finally lipid metabolism and signaling-related reports at

Datasets and data analysis

We analyzed 2242 probes that were annotated as “lipid and fatty acid metabolism” in transcriptomics data available in the public domain obtained from the ECLIPSE study (Fig. 1). These data included 143 deposited chips from COPD ex-smokers, of which we selected 138 high quality slides for further analysis. This dataset included 69 samples of patients with Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage II, 56 stage III and 13 stage IV. No differentially expressed genes with

Discussion

COPD is a chronic, progressive and irreversible respiratory disease that is mainly caused by genetic and environmental interactions. Lipid mediators, as the leading factors in Th1 polarization of the immune cells, are a hallmark of human COPD. Furthermore, oxidative stress and inflammation are two important signaling pathways in COPD pathogenesis, which share lipids as key regulatory metabolites. However, reports regarding smoking-mediated lipid metabolism in COPD are limited [66], [67]. We

Conclusion

Currently, there are huge public low- and high-throughput data considering the disease, which need a systemic approach to be appropriately integrated and summarized. This study is a computational approach to summarizing a large quantity of already existing data regarding COPD, so as to get new perspectives of lipid mechanisms changing during COPD. For the first time, we extracted a large dataset available in the public domain, which included transcriptomics, proteomics, metabolomics and

Conflicts of interest

All authors report no conflicts of interest.

Acknowledgements

We would like to thank Professor Farrah Kheradmand for her great commitment, contribution and encouragement during the preparation of the manuscript.

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