Metabolomics analysis identifies sex-associated metabotypes of oxidative stress and the autotaxin-lysoPA axis in COPD

Shama Naz, Johan Kolmert, Mingxing Yang, Stacey N Reinke, Muhammad Anas Kamleh, Stuart Snowden, Tina Heyder, Bettina Levänen, David J Erle, C Magnus Sköld, Åsa M Wheelock, Craig E Wheelock, Shama Naz, Johan Kolmert, Mingxing Yang, Stacey N Reinke, Muhammad Anas Kamleh, Stuart Snowden, Tina Heyder, Bettina Levänen, David J Erle, C Magnus Sköld, Åsa M Wheelock, Craig E Wheelock

Abstract

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and a leading cause of mortality and morbidity worldwide. The aim of this study was to investigate the sex dependency of circulating metabolic profiles in COPD.Serum from healthy never-smokers (healthy), smokers with normal lung function (smokers), and smokers with COPD (COPD; Global Initiative for Chronic Obstructive Lung Disease stages I-II/A-B) from the Karolinska COSMIC cohort (n=116) was analysed using our nontargeted liquid chromatography-high resolution mass spectrometry metabolomics platform.Pathway analyses revealed that several altered metabolites are involved in oxidative stress. Supervised multivariate modelling showed significant classification of smokers from COPD (p=2.8×10-7). Sex stratification indicated that the separation was driven by females (p=2.4×10-7) relative to males (p=4.0×10-4). Significantly altered metabolites were confirmed quantitatively using targeted metabolomics. Multivariate modelling of targeted metabolomics data confirmed enhanced metabolic dysregulation in females with COPD (p=3.0×10-3) relative to males (p=0.10). The autotaxin products lysoPA (16:0) and lysoPA (18:2) correlated with lung function (forced expiratory volume in 1 s) in males with COPD (r=0.86; p<0.0001), but not females (r=0.44; p=0.15), potentially related to observed dysregulation of the miR-29 family in the lung.These findings highlight the role of oxidative stress in COPD, and suggest that sex-enhanced dysregulation in oxidative stress, and potentially the autotaxin-lysoPA axis, are associated with disease mechanisms and/or prevalence.

Conflict of interest statement

Conflict of interest: Disclosures can be found alongside this article at erj.ersjournals.com

Copyright ©ERS 2017.

Figures

FIGURE 1
FIGURE 1
Optimised orthogonal projections to latent structures discriminant analysis multivariate models using nontargeted metabolomics data. a) i) Scores plot of male smokers versus males with chronic obstructive pulmonary disease (COPD) (R2Y=0.49, Q2=0.38, p=4.0×10−4); ii) loadings of confirmed metabolites that were the most prominent for driving the separation between male smokers versus males with COPD. b) i) Scores plot of female smokers versus females with COPD (R2Y=0.73, Q2=0.65, p=2.4×10−7); ii) loadings of confirmed metabolites that were the most prominent for driving the separation of female smokers versus females with COPD. For ease of display, parts a ii) and b ii) exclude metabolites whose standard error crossed the x-axis. The complete list of loadings is shown in online supplementary figure E8. LysoPA: lyso-phosphatidic acid; HETE: hydroxyeicosatetraenoic acid; HDoHE: hydroxydocosahexaenoic acid; EpETrE: epoxyeicosatrienoic acid; HEDE: hydroxyeicosadienoic acid; AEA: N-arachidonoylethanolamine; OEA: N-oleoylethanolamine; EpODE: epoxyoctadecadienoic acid; PEA: N-palmitoylethanolamide; Asp-Leu: aspartic acid-leucine.
FIGURE 2
FIGURE 2
The lyso-phosphatidic acid (lysoPA)–autotaxin axis was attenuated in males with chronic obstructive pulmonary disease (COPD). a) Serum lysoPA (16:0) levels in smokers versus COPD; (b) serum lysoPA (18:2) levels in smokers versus COPD; (c) lysoPA (16:0) and lysoPA (18:2) metabolites correlated with lung function (forced expiratory volume in 1 s (FEV1)) in male COPD patients (r=0.84, p<0.0001). No correlation was observed in the corresponding female COPD population (r=0.44, p=0.15); (d) levels of miR-29b in bronchoalveolar lavage (BAL) cells from male and female smokers and COPD patients. Values for the other members of the miR-29 family are shown in online supplementary figure E6. LysoPA data are from the nontargeted metabolomics platform and are presented as log2 of arbitrary units (AU). RFU: relative fluorescence units; LLOQ: lower limit of quantification.
FIGURE 3
FIGURE 3
β-oxidation-related metabolite ratio of carnitine with acylcarnitines in relation to sex and disease status for smoking subjects. a) Ratio of carnitine with sum of the medium-chain carnitines; (b) ratio of carnitine with sum of the long-chain carnitines. Subjects are divided into smokers with normal lung function and smokers with chronic obstructive pulmonary disease (COPD). Significance was calculated using the nonparametric Mann–Whitney test. Data are from the targeted metabolomics method (Biocrates).
FIGURE 4
FIGURE 4
Serum levels of analytes involved in the arginine/nitric oxide pathway. a) Ratio of acetyl-ornithine to ornithine; (b) ratio of total arginine to the inferred activity of the nitric oxide synthase (NOS) enzyme expressed as arginine/(ornithine+citrulline); (c) ratio of endogenous NOS inhibitors (sum of asymmetric and symmetric dimethylarginine (ADMA + SDMA)) with arginine; and (d) concentration of the endogenous NOS inhibitor ADMA. Significance was calculated using the nonparametric Mann–Whitney test. Subjects are divided into smokers with normal lung function and smokers with chronic obstructive pulmonary disease (COPD). Data are from the targeted metabolomics method (Biocrates).
FIGURE 5
FIGURE 5
Representative pathway outline for the altered metabolites involved in oxidative stress metabolism in chronic obstructive pulmonary disease (COPD). (a) Fatty acid β-oxidation pathway; (b) purine degradation pathway; (c) Land's cycle/phospholipid metabolism. TCA: tricarboxylic acid; NADH: nicotinamide adenine dinucleotide; FADH2: flavin adenine dinucleotide; IMP: inosine monophosphate; NAPE-PLD: N-acyl phosphatidylethanolamine phospholipase D; lysoPA: lysophosphatidic acid.

References

    1. Mannino DM, Buist AS. Global burden of COPD: risk factors, prevalence, and future trends. Lancet 2007; 370: 765–773.
    1. Adamko DJ, Nair P, Mayers I, et al. . Metabolomic profiling of asthma and chronic obstructive pulmonary disease: a pilot study differentiating diseases. J Allergy Clin Immunol 2015; 136: 571–580.
    1. Snoeck-Stroband JB, Lapperre TS, Gosman MME, et al. . Chronic bronchitis sub-phenotype within COPD: inflammation in sputum and biopsies. Eur Respir J 2008; 31: 70–77.
    1. Han MK, Postma D, Mannino DM, et al. . Gender and chronic obstructive pulmonary disease: why it matters. Am J Respir Crit Care Med 2007; 176: 1179–1184.
    1. Sørheim IC, Johannessen A, Gulsvik A, et al. . Gender differences in COPD: are women more susceptible to smoking effects than men? Thorax 2010; 65: 480–485.
    1. Camp PG, Coxson HO, Levy RD, et al. . Sex differences in emphysema and airway disease in smokers. Chest 2009; 136: 1480–1488.
    1. Eisner MD, Anthonisen N, Coultas D, et al. . An official American Thoracic Society public policy statement: novel risk factors and the global burden of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2010; 182: 693–718.
    1. To T, Zhu J, Larsen K, et al. . Progression from asthma to chronic obstructive pulmonary disease. Is air pollution a risk factor? Am J Respir Crit Care Med 2016; 194: 429–438.
    1. Kurt OK, Zhang J, Pinkerton KE. Pulmonary health effects of air pollution. Curr Opin Pulm Med 2016; 22: 138–143.
    1. Valko M, Leibfritz D, Moncol J, et al. . Free radicals and antioxidants in normal physiological functions and human disease. Int J Biochem Cell Biol 2007; 39: 44–84.
    1. Vestbo J, Hurd SS, Agustí AG, et al. . Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 2013; 187: 347–365.
    1. Kohler M, Sandberg A, Kjellqvist S, et al. . Gender differences in the bronchoalveolar lavage cell proteome of patients with chronic obstructive pulmonary disease. J Allergy Clin Immunol 2013; 131: 743–751.
    1. Forsslund H, Mikko M, Karimi R, et al. . Distribution of T-cell subsets in BAL fluid of patients with mild to moderate COPD depends on current smoking status and not airway obstruction. Chest 2014; 145: 711–722.
    1. Karimi R, Tornling G, Forsslund H, et al. . Lung density on high resolution computer tomography (HRCT) reflects degree of inflammation in smokers. Respir Res 2014; 15: 23.
    1. Balgoma D, Yang M, Sjödin M, et al. . Linoleic acid-derived lipid mediators increase in a female-dominated subphenotype of COPD. Eur Respir J 2016; 47: 1645–1656.
    1. Reinke SN, Gallart-Ayala H, Gomez C, et al. . Metabolomics analysis identifies different metabotypes of asthma severity. Eur Respir J 2017; 49: 1601740.
    1. Wishart DS, Jewison T, Guo AC, et al. . HMDB 3.0 – the Human Metabolome Database in 2013. Nucleic Acids Res 2013; 41: D801–D807.
    1. Kamleh MA, Snowden SG, Grapov D, et al. . LC-MS metabolomics of psoriasis patients reveals disease severity-dependent increases in circulating amino acids that are ameliorated by anti-TNFα treatment. J Proteome Res 2015; 14: 557–566.
    1. Bijlsma S, Bobeldijk I, Verheij ER, et al. . Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation. Anal Chem 2006; 78: 567–574.
    1. Dunn WB, Wilson ID, Nicholls AW, et al. . The importance of experimental design and QC samples in large-scale and MS-driven untargeted metabolomic studies of humans. Bioanalysis 2012; 4: 2249–2264.
    1. Gromski PS, Xu Y, Kotze HL, et al. . Influence of missing values substitutes on multivariate analysis of metabolomics data. Metabolites 2014; 4: 433–452.
    1. Wheelock ÅM, Wheelock CE. Trials and tribulations of ’omics data analysis: assessing quality of SIMCA-based multivariate models using examples from pulmonary medicine. Mol Biosyst 2013; 9: 2589–2596.
    1. Wiklund S, Johansson E, Sjöström L, et al. . Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal Chem 2008; 80: 115–122.
    1. Kamburov A, Cavill R, Ebbels TM, et al. . Integrated pathway-level analysis of transcriptomics and metabolomics data with IMPaLA. Bioinformatics 2011; 27: 2917–2918.
    1. Molina-Pinelo S, Pastor MD, Suarez R, et al. . MicroRNA clusters: dysregulation in lung adenocarcinoma and COPD. Eur Respir J 2014; 43: 1740–1749.
    1. Osei ET, Florez-Sampedro L, Timens W, et al. . Unravelling the complexity of COPD by microRNAs: it's a small world after all. Eur Respir J 2015; 46: 807–818.
    1. Conickx G, Mestdagh P, Avila Cobos F, et al. . MicroRNA profiling reveals a role for microRNA-218-5p in the pathogenesis of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2017; 195: 43–56.
    1. Benipal B, Feinstein SI, Chatterjee S, et al. . Inhibition of the phospholipase A2 activity of peroxiredoxin 6 prevents lung damage with exposure to hyperoxia. Redox Biol 2015; 4: 321–327.
    1. Ben Moussa S, Rouatbi S, Saad HB. Incapacity, handicap, and oxidative stress markers of male smokers with and without COPD. Respir Care 2016; 61: 668–679.
    1. Conlon TM, Bartel J, Ballweg K, et al. . Metabolomics screening identifies reduced l-carnitine to be associated with progressive emphysema. Clin Sci 2016; 130: 273–287.
    1. Lommatzsch M, Cicko S, Müller T, et al. . Extracellular adenosine triphosphate and chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2010; 181: 928–934.
    1. Tam A, Churg A, Wright JL, et al. . Sex differences in airway remodeling in a mouse model of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2016; 193: 825–834.
    1. Aydin M, Altintas N, Cem Mutlu L, et al. . Asymmetric dimethylarginine contributes to airway nitric oxide deficiency in patients with COPD. Clin Respir J 2017; 11: 318–327.
    1. Ruzsics I, Nagy L, Keki S, et al. . l-Arginine pathway in COPD patients with acute exacerbation: a new potential biomarker. COPD 2016; 13: 139–145.
    1. Scott JA, Duongh M, Young AW, et al. . Asymmetric dimethylarginine in chronic obstructive pulmonary disease (ADMA in COPD). Int J Mol Sci 2014; 15: 6062–6071.
    1. Scott JA, North ML, Rafii M, et al. . Asymmetric dimethylarginine is increased in asthma. Am J Respir Crit Care Med 2011; 184: 779–785.
    1. Ricciardolo FL, Caramori G, Ito K, et al. . Nitrosative stress in the bronchial mucosa of severe chronic obstructive pulmonary disease. J Allergy Clin Immunol 2005; 116: 1028–1035.
    1. van Meeteren LA, Moolenaar WH. Regulation and biological activities of the autotaxin-LPA axis. Prog Lipid Res 2007; 46: 145–160.
    1. Van der Aar E, Fagard L, Desrivot J, et al. . Favorable human safety, pharmacokinetics and pharmacodynamics of the autotaxin inhibitor GLPG1690, a potential new treatment in COPD. Eur Respir J 2015; 46: Suppl. 59, OA484.
    1. Solberg OD, Ostrin EJ, Love MI, et al. . Airway epithelial miRNA expression is altered in asthma. Am J Respir Crit Care Med 2012; 186: 965–974.
    1. Cushing L, Kuang P, Lü J. The role of miR-29 in pulmonary fibrosis. Biochem Cell Biol 2015; 93: 109–118.
    1. Jiang H, Zhang G, Wu JH, et al. . Diverse roles of miR-29 in cancer (review). Oncol Rep 2014; 31: 1509–1516.
    1. Wu DW, Hsu NY, Wang YC, et al. . c-Myc suppresses microRNA-29b to promote tumor aggressiveness and poor outcomes in non-small cell lung cancer by targeting FHIT. Oncogene 2015; 34: 2072–2082.
    1. Nowak-Machen M, Lange M, Exley M, et al. . Lysophosphatidic acid generation by pulmonary NKT cell ENPP-2/autotaxin exacerbates hyperoxic lung injury. Purinergic Signal 2015; 11: 455–461.
    1. Chu X, Wei X, Lu S, et al. . Autotaxin-LPA receptor axis in the pathogenesis of lung diseases. Int J Clin Exp Med 2015; 8: 17117–17122.
    1. Park GY, Lee YG, Berdyshev E, et al. . Autotaxin production of lysophosphatidic acid mediates allergic asthmatic inflammation. Am J Respir Crit Care Med 2013; 188: 928–940.
    1. Ackerman SJ, Park GY, Christman JW, et al. . Polyunsaturated lysophosphatidic acid as a potential asthma biomarker. Biomark Med 2016; 10: 123–135.
    1. Pleli T, Martin D, Kronenberger B, et al. . Serum autotaxin is a parameter for the severity of liver cirrhosis and overall survival in patients with liver cirrhosis – a prospective cohort study. PLoS One 2014; 9: e103532.
    1. Knowlden S, Georas SN. The autotaxin-LPA axis emerges as a novel regulator of lymphocyte homing and inflammation. J Immunol 2014; 192: 851–857.
    1. Katoh A, Ikeda H, Murohara T, et al. . Platelet-derived 12-hydroxyeicosatetraenoic acid plays an important role in mediating canine coronary thrombosis by regulating platelet glycoprotein IIb/IIIa activation. Circulation 1998; 98: 2891–2898.
    1. Maskrey BH, Rushworth GF, Law MH, et al. . 12-hydroxyeicosatetraenoic acid is associated with variability in aspirin-induced platelet inhibition. J Inflamm 2014; 11: 33.
    1. Keune WJ, Hausmann J, Bolier R, et al. . Steroid binding to autotaxin links bile salts and lysophosphatidic acid signalling. Nat Commun 2016; 7: 11248.

Source: PubMed

3
Sottoscrivi