Abstract
Introduction
Asthma-chronic obstructive pulmonary disease (COPD) overlap, termed as ACO, is a complex heterogeneous disease without any clear diagnostic or therapeutic guidelines. The pathophysiology of the disease, its characteristic features, and existence as a unique disease entity remains unclear. Individuals with ACO have a faster lung function decline, more frequent exacerbations, and worse quality of life than those with COPD or asthma alone.
Objectives
The present study aims to determine whether ACO has a distinct metabolic profile in comparison to asthma and COPD.
Methods
Two different groups of patients were recruited as discovery (D) and validation (V) cohorts. Serum samples obtained from moderate and severe asthma patients diagnosed as per GINA guidelines [n = 34(D); n = 32(V)], moderate and severe COPD cases identified by GOLD guidelines [n = 30(D); 32(V)], ACO patients diagnosed by joint GOLD and GINA guidelines [n = 35(D); 40(V)] and healthy controls [n = 33(D)] were characterized using nuclear magnetic resonance (NMR) spectrometry.
Results
Multivariate and univariate analysis indicated that 12 metabolites [lipid, isoleucine, N-acetylglycoproteins (NAG), valine, glutamate, citric acid, glucose, l-leucine, lysine, asparagine, phenylalanine and histidine] were dysregulated in ACO patients when compared with both asthma and COPD. These metabolites were further validated in a fresh cohort of patients, which again exhibited a similar expression pattern.
Conclusions
Our findings suggest that ACO has an enhanced energy and metabolic burden associated with it as compared to asthma and COPD. It is anticipated that our results will stimulate researchers to further explore ACO and unravel the pathophysiological complexities associated with the disease.
Similar content being viewed by others
References
Adamko, D. J., Nair, P., Mayers, I., et al. (2015). Metabolomic profiling of asthma and chronic obstructive pulmonary disease: A pilot study differentiating diseases. Journal of Allergy and Clinical Immunology, 136(3), 571–580.
Alshabanat, A., Zafari, Z., Albanyan, O., et al. (2015). Asthma and COPD overlap syndrome (ACOS): A systematic review and meta analysis. PLoS ONE, 10(9), e0136065.
Banerjee, P., Dutta, M., Srivastava, S., et al. (2014). 1H NMR serum metabonomics for understanding metabolic dysregulation in women with idiopathic recurrent spontaneous miscarriage during implantation window. Journal of Proteome Research, 13(6), 3100–3106.
Bateman, E. D., Hurd, S. S., Barnes, P. J., et al. (2008). Global strategy for asthma management and prevention: GINA executive summary. European Respiratory Journal, 31(1), 143–178.
Bertini, I., Luchinat, C., Miniati, M., et al. (2014). Phenotyping COPD by 1H NMR metabolomics of exhaled breath condensate. Metabolomics, 10(2), 302–311.
Chang, C., Guo, Z. G., & He, B. (2015). Metabolic alterations in the sera of Chinese patients with mild persistent asthma: A GC-MS-based metabolomics analysis. Acta Pharmacologica Sinica, 36(11), 1356.
Cloarec, O., Dumas, M. E., Trygg, J., et al. (2005). Evaluation of the orthogonal projection on latent structure model limitations caused by chemical shift variability and improved visualization of biomarker changes in 1H NMR spectroscopic metabonomic studies. Analytical Chemistry, 77(2), 517–526.
Comhair, S. A., McDunn, J., Bennett, C., et al. (2015). Metabolomic endotype of asthma. The Journal of Immunology, 195(2), 643–650.
Committee for the Third Edition of the COPD guidelines of the Japanese respiratory society. (2010). Guidelines for the diagnosis and treatment of COPD (chronic obstructive pulmonary disease). (3rd ed.). www.jrs.or.jp/uploads/uploads/files/photos/765.pdf. Accessed 10 October 2016.
Cosio, B. G., Soriano, J. B., López-Campos, J. L., et al. (2016). Defining the asthma-COPD overlap syndrome in a COPD cohort. Chest, 149(1), 45–52.
Cukic, V., Lovre, V., & Dragisic, D. (2012). Asthma and chronic obstructive pulmonary disease (COPD)—differences and similarities. Materia Socio-Medica, 24(2), 100.
Ding, B., DiBonaventura, M., & Karlsson, N. (2016). Asthma-chronic obstructive pulmonary disease overlap syndrome in the urban Chinese population: Prevalence and disease burden using the 2010, 2012, and 2013 China national health and wellness surveys. International Journal of Chronic Obstructive Pulmonary Disease, 11, 1139.
Dutta, M., Joshi, M., & Srivastava, S. (2012). A metabonomics approach as a means for identification of potential biomarkers for early diagnosis of endometriosis. Molecular BioSystems, 8(12), 3281–3287.
Emwas, A. H. M. (2015). The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research. Metabonomics (pp. 161–193). New York: Humana Press.
Farrés, M., Platikanov, S., & Tsakovski, S. (2015). Comparison of the variable importance in projection (VIP) and of the selectivity ratio (SR) methods for variable selection and interpretation. Journal of Chemometrics, 29(10), 528–536.
Fortis, S., Lusczek, E. R., & Weinert, C. R. (2017). Metabolomics in COPD acute respiratory failure requiring noninvasive positive pressure ventilation. Canadian Respiratory Journal. https://doi.org/10.1155/2017/9480346.
Gibson, P. G., & McDonald, V. M. (2015). Asthma–COPD overlap 2015: now we are six. Thorax, 70(7), 683–691.
GINA-GOLD diagnosis of disease of chronic airflow limitation: Asthma, COPD and asthma-COPD overlap syndrome (ACOS). http://www.goldcopd.org/asthma-copd-overlap.html Last Accessed 10 September 2014.
Global initiative for asthma (gina). Global strategy for asthma management and prevention. Revised 2014. http://www.ginasthma.org. Accessed 10 September 2014.
Global strategy for the diagnosis, management and prevention of COPD, global initiative for chronic obstructive lung disease (GOLD). (2014). http://goldcopd.org/. Accessed 10 September 2014.
Hardin, M., Silverman, E. K., Barr, R. G., et al. (2011). The clinical features of the overlap between COPD and asthma. Respiratory Research, 12(1), 127.
Hirst, S. J., & Lee, T. H. (1998). Airway smooth muscle as a target of glucocorticoid action in the treatment of asthma. American Journal of Respiratory and Critical Care Medicine, 158(Supplement 2), S201–S206.
Johnson, C. H., Ivanisevic, J., & Siuzdak, G. (2016). Metabolomics: beyond biomarkers and towards mechanisms. Nature Reviews Molecular Cell Biology, 17(7), 451.
Jung, J., Kim, S. H., Lee, H. S., et al. (2013). Serum metabolomics reveals pathways and biomarkers associated with asthma pathogenesis. Clinical and Experimental Allergy, 43(4), 425–433.
Kao, C. C., Hsu, J. W. C., Bandi, V., et al. (2011). Glucose and pyruvate metabolism in severe chronic obstructive pulmonary disease. Journal of Applied Physiology, 112(1), 42–47.
Kauppi, P., Kupiainen, H., Lindqvist, A., et al. (2011). Overlap syndrome of asthma and COPD predicts low quality of life. Journal of Asthma, 48(3), 279–285.
Koblizek, V., Chlumsky, J., Zindr, V., et al. (2013). Chronic Obstructive Pulmonary Disease: official diagnosis and treatment guidelines of the Czech Pneumological and Physiological Society; a novel phenotypic approach to COPD with patient-oriented care. Biomedical Papers of the Medical Faculty of Palacky University in Olomouc, 157(2), 189–201.
Leung, J. M., & Sin, D. D. (2017). Asthma-COPD overlap syndrome: pathogenesis, clinical features, and therapeutic targets. BMJ, 358, j3772.
Levänen, B., Bhakta, N. R., Paredes, P. T., et al. (2013). Altered microRNA profiles in bronchoalveolar lavage fluid exosomes in asthmatic patients. Journal of Allergy and Clinical Immunology, 131(3), 894–903.
Litwack, G. (2017). Metabolism of amino acids. Human Biochemistry (1st ed., pp. 359–393). London: Academic Press.
Lourenço, A. B., Roque, F. C., Teixeira, M. C., et al. (2013). Quantitative 1H-NMR-metabolomics reveals extensive metabolic reprogramming and the effect of the aquaglyceroporin FPS1 in ethanol-stressed yeast cells. PLoS ONE, 8(2), e55439.
Maniscalco, M., Paris, D., Melck, D. J., et al. (2017). Coexistence of obesity and asthma determines a distinct respiratory metabolic phenotype. Journal of Allergy and Clinical Immunology, 139(5), 1536–1547.
Marsh, S. E., Travers, J., Weatherall, M., et al. (2008). Proportional classifications of COPD phenotypes. Thorax, 63(9), 761–767.
Meiboom, S., & Gill, D. (1958). Modified spin-echo method for measuring nuclear relaxation times. Review of Scientific Instruments, 29(8), 688–691.
Menezes, A. M. B., de Oca, M. M., Pérez-Padilla, R., et al. (2014). Increased risk of exacerbation and hospitalization in subjects with an overlap phenotype: COPD-asthma. Chest, 145(2), 297–304.
Montuschi, P., Paris, D., Melck, D., et al. (2012). NMR spectroscopy metabolomic profiling of exhaled breath condensate in patients with stable and unstable cystic fibrosis. Thorax, 67(3), 222–228.
Oh, J. Y., Lee, Y. S., Min, K. H., et al. (2018). Increased urinary l-histidine in patients with asthma–COPD overlap: a pilot study. International Journal of Chronic Obstructive Pulmonary Disease, 13, 1809.
Paris, D., Maniscalco, M., & Motta, A. (2018). Nuclear magnetic resonance-based metabolomics in respiratory medicine. European Respiratory Journal, 52(4), 1801107.
Patel, M. J., Batch, B. C., Svetkey, L. P., et al. (2013). Race and sex differences in small-molecule metabolites and metabolic hormones in overweight and obese adults. OMICS: A Journal of Integrative Biology, 17(12), 627–635.
Psychogios, N., Hau, D. D., Peng, J., et al. (2011). The human serum metabolome. PLoS ONE, 6(2), e16957.
Qin, X. Y., Wei, F., Tanokura, M., et al. (2013). The effect of acyclic retinoid on the metabolomic profiles of hepatocytes and hepatocellular carcinoma cells. PLoS ONE, 8(12), e82860.
Rabe, K. F., Hurd, S., Anzueto, A., et al. (2007). Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. American Journal of Respiratory and Critical Care Medicine, 176(6), 532–555.
Rodríguez, D. A., Alcarraz-Vizán, G., Díaz-Moralli, S., et al. (2012). Plasma metabolic profile in COPD patients: effects of exercise and endurance training. Metabolomics, 8(3), 508–516.
RoyChoudhury, S., Mishra, B. P., Khan, T., et al. (2016). Serum metabolomics of Indian women with polycystic ovary syndrome using 1 H NMR coupled with a pattern recognition approach. Molecular BioSystems, 12(11), 3407–3416.
Saude, E. J., Skappak, C. D., Regush, S., et al. (2011). Metabolomic profiling of asthma: diagnostic utility of urine nuclear magnetic resonance spectroscopy. Journal of Allergy and Clinical Immunology, 127(3), 757–764.
Schicho, R., Shaykhutdinov, R., Ngo, J., et al. (2012). Quantitative metabolomic profiling of serum, plasma, and urine by 1H NMR spectroscopy discriminates between patients with inflammatory bowel disease and healthy individuals. Journal of Proteome Research, 11(6), 3344–3357.
Sin, D. D., Miravitlles, M., Mannino, D. M., et al. (2016). What is asthma–COPD overlap syndrome? Towards a consensus definition from a round table discussion. European Respiratory Journal, 48(3), 664–673.
Soler-Cataluna, J. J., Cosío, B., Izquierdo, J. L., et al. (2012). Consensus document on the overlap phenotype COPD–asthma in COPD. Archivos de Bronconeumología (English Edition), 48(9), 331–337.
Subramani, E., Jothiramajayam, M., Dutta, M., et al. (2016). NMR-based metabonomics for understanding the influence of dormant female genital tuberculosis on metabolism of the human endometrium. Human Reproduction, 31(4), 854–865.
To, T., Zhu, J., Larsen, K., et al. (2016). Progression from asthma to chronic obstructive pulmonary disease. Is air pollution a risk factor? American Journal of Respiratory and Critical Care Medicine, 194(4), 429–438.
Trygg, J., & Wold, S. (2002). Orthogonal projections to latent structures (O-PLS). Journal of Chemometrics: A Journal of the Chemometrics Society, 16(3), 119–128.
Ubhi, B. K., Riley, J. H., Shaw, P. A., et al. (2012). Metabolic profiling detects biomarkers of protein degradation in COPD patients. European Respiratory Journal, 40(2), 345–355.
Wang, L., Tang, Y., Liu, S., et al. (2013). Metabonomic profiling of serum and urine by 1H NMR-based spectroscopy discriminates patients with chronic obstructive pulmonary disease and healthy individuals. PLoS ONE, 8(6), e65675.
Wang, C., Li, J. X., Tang, D., et al. (2017). Metabolic changes of different high-resolution computed tomography phenotypes of COPD after budesonide–formoterol treatment. International Journal of Chronic Obstructive Pulmonary Disease, 12, 3511.
Westerhuis, J. A., Hoefsloot, H. C., Smit, S., et al. (2008). Assessment of PLSDA cross validation. Metabolomics, 4(1), 81–89.
Wheelock, Å. M., & Wheelock, C. E. (2013). Trials and tribulations of ‘omics data analysis: assessing quality of SIMCA-based multivariate models using examples from pulmonary medicine. Molecular BioSystems, 9(11), 2589–2596.
Wheelock, C. E., Goss, V. M., Balgoma, D., et al. (2013). Application of’omics technologies to biomarker discovery in inflammatory lung diseases. European Respiratory Journal, 42(3), 802–825.
Wishart, D. S., Knox, C., Guo, A. C., et al. (2008). HMDB: a knowledgebase for the human metabolome. Nucleic Acids Research, 37(suppl_1), D603–D610.
Woodruff, P. G., Van Den Berge, M., Boucher, R. C., et al. (2017). American thoracic society/national heart, lung, and blood institute asthma-chronic obstructive pulmonary disease overlap workshop report. American Journal of Respiratory and Critical Care Medicine, 196(3), 375–381.
Xia, J., Mandal, R., Sinelnikov, I. V., et al. (2012). MetaboAnalyst 2.0—a comprehensive server for metabolomic data analysis. Nucleic Acids Research, 40((W1)), W127–W133.
Zeki, A. A., Schivo, M., Chan, A., et al. (2011). The asthma-COPD overlap syndrome: A common clinical problem in the elderly. Journal of Allergy. https://doi.org/10.1155/2011/861926.
Acknowledgements
Financial support by Government of India, Ministry of Human Resource Development (Grant No: F. NO. 4-23/2014-TS.I, Dt. 14-03-2014) and Department of Higher Education (SSLS project) and Department of Science and Technology (DST), Govt. of West Bengal (Grant No: 867(Sanc.)/ST/P/S&T/9G-17/2015, Dt. 15-01-2016) are acknowledged.
Author information
Authors and Affiliations
Contributions
NG, RB, SRC, PB and KC conceived and designed the study. NG, PC, DS, SS and MJ conducted experiments. NG, PC, ES and KC analyzed the data. NG, KC, SRC and PB wrote the paper. All authors critically revised, read, and approved the final version of manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
All procedures performed in the study involving human participants were done in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments.
Informed consent
Informed consent was obtained from all individual participants included in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Ghosh, N., Choudhury, P., Subramani, E. et al. Metabolomic signatures of asthma-COPD overlap (ACO) are different from asthma and COPD. Metabolomics 15, 87 (2019). https://doi.org/10.1007/s11306-019-1552-z
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11306-019-1552-z