Identification of Metabolism-Associated Molecular Subtypes of Chronic Obstructive Pulmonary Disease

References

• Soriano JB, Kendrick PJ, Paulson KR, et al. Prevalence and attributable health burden of chronic respiratory diseases, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Respir Med. 2020;8(6):585–596. doi:10.1016/S2213-2600(20)30105-3
   PubMed Web of Science ®Google Scholar
• Barnes PJ. Inflammatory mechanisms in patients with chronic obstructive pulmonary disease. J Allergy Clin Immunol. 2016;138(1):16–27. doi:10.1016/j.jaci.2016.05.011
   PubMed Web of Science ®Google Scholar
• Thomsen M, Dahl M, Lange P, Vestbo J, Nordestgaard BG. Inflammatory biomarkers and comorbidities in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2012;186(10):982–988. doi:10.1164/rccm.201206-1113OC
   PubMed Web of Science ®Google Scholar
• Gan WQ, Man SFP, Senthilselvan A, Sin DD. Association between chronic obstructive pulmonary disease and systemic inflammation: a systematic review and a meta-analysis. Thorax. 2004;59(7):574–580. doi:10.1136/thx.2003.019588
   PubMed Web of Science ®Google Scholar
• Vestbo J, Anderson W, Coxson HO, et al. Evaluation of COPD longitudinally to identify predictive surrogate end-points (ECLIPSE). Eur Respir J. 2008;31(4):869–873. doi:10.1183/09031936.00111707
   PubMed Web of Science ®Google Scholar
• Li X, Cao X, Guo M, Xie M, Liu X. Trends and risk factors of mortality and disability adjusted life years for chronic respiratory diseases from 1990 to 2017: systematic analysis for the Global Burden of Disease Study 2017. BMJ. 2020;368:m234. doi:10.1136/bmj.m234
   PubMed Web of Science ®Google Scholar
• Hikichi M, Mizumura K, Maruoka S, Gon Y. Pathogenesis of chronic obstructive pulmonary disease (COPD) induced by cigarette smoke. J Thorac Dis. 2019;1:1. doi:10.21037/jtd.2019.10.43
   Web of Science ®Google Scholar
• Barnes PJ. Cellular and molecular mechanisms of asthma and COPD. Clin Sci (Lond). 2017;131(13):1541–1558. doi:10.1042/CS20160487
   PubMed Web of Science ®Google Scholar
• Golpe R, Martín-Robles I, Sanjuán-López P, et al. Differences in systemic inflammation between cigarette and biomass smoke-induced COPD. Int J Chronic Obstruct Pulmon Dis. 2017;12:2639–2646. doi:10.2147/COPD.S141068
   PubMed Web of Science ®Google Scholar
• Hlapčić I, Belamarić D, Bosnar M, Kifer D, Vukić Dugac A, Rumora L. Combination of systemic inflammatory biomarkers in assessment of chronic obstructive pulmonary disease: diagnostic performance and identification of networks and clusters. Diagnostics (Basel). 2020;10(12):1029. doi:10.3390/diagnostics10121029
   PubMedGoogle Scholar
• Selvarajah S, Todd I, Tighe PJ, et al. Multiple circulating cytokines are coelevated in chronic obstructive pulmonary disease. Mediators Inflamm. 2016;2016:3604842. doi:10.1155/2016/3604842
   PubMed Web of Science ®Google Scholar
• Garudadri S, Woodruff PG, Han MK, et al. Systemic markers of inflammation in smokers with symptoms despite preserved spirometry in SPIROMICS. Chest. 2019;155(5):908–917. doi:10.1016/j.chest.2018.12.022
   PubMed Web of Science ®Google Scholar
• Regan EA, Lynch DA, Curran-Everett D, et al. Clinical and radiologic disease in smokers with normal spirometry. JAMA Intern Med. 2015;175(9):1539–1549. doi:10.1001/jamainternmed.2015.2735
   PubMed Web of Science ®Google Scholar
• Han MK, Agusti A, Celli BR, et al. From GOLD 0 to pre-COPD. Am J Respir Crit Care Med. 2021;203(4):414–423. doi:10.1164/rccm.202008-3328PP
   PubMed Web of Science ®Google Scholar
• Lange P, Ahmed E, Lahmar ZM, Martinez FJ, Bourdin A. Natural history and mechanisms of COPD. Respirology (Carlton, Vic). 2021;26(4):298–321. doi:10.1111/resp.14007
   PubMed Web of Science ®Google Scholar
• Chang Y, Glass K, Liu Y-Y, et al. COPD subtypes identified by network-based clustering of blood gene expression. Genomics. 2016;107(2–3):51–58. doi:10.1016/j.ygeno.2016.01.004
   PubMed Web of Science ®Google Scholar
• Buck MD, Sowell RT, Kaech SM, Pearce EL. Metabolic instruction of immunity. Cell. 2017;169(4):570–586. doi:10.1016/j.cell.2017.04.004
   PubMed Web of Science ®Google Scholar
• Ran N, Pang Z, Gu Y, et al. An updated overview of metabolomic profile changes in chronic obstructive pulmonary disease. Metabolites. 2019;9(6):111. doi:10.3390/metabo9060111
   PubMed Web of Science ®Google Scholar
• Agarwal AR, Kadam S, Brahme A, et al. Systemic Immuno-metabolic alterations in chronic obstructive pulmonary disease (COPD). Respir Res. 2019;20(1):171. doi:10.1186/s12931-019-1139-2
   PubMedGoogle Scholar
• Kadam S, Ghosh B, Apte K, Brahme A, Salvi S, Agarwal A. Metabolic changes in peripheral blood mononuclear cells (PBMCs) of subjects with chronic obstructive pulmonary disease (COPD). Eur Respir J. 2017;50(suppl):61. doi:10.1183/1393003.congress-2017.PA3917
   Web of Science ®Google Scholar
• Bruzzaniti S, Bocchino M, Santopaolo M, et al. An immunometabolic pathomechanism for chronic obstructive pulmonary disease. Proc Natl Acad Sci USA. 2019;116(31):15625–15634. doi:10.1073/pnas.1906303116
   PubMed Web of Science ®Google Scholar
• Silva B, Lira F, Silva R, et al. Down-regulation of immunometabolism in severe COPD. Eur Respir J. 2017;50(suppl):61. doi:10.1183/1393003.congress-2017.PA2254
   Google Scholar
• Diao W, Labaki WW, Han MK, et al. Disruption of histidine and energy homeostasis in chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2019;14:2015–2025. doi:10.2147/COPD.S210598
   PubMed Web of Science ®Google Scholar
• Maselli DJ, Bhatt SP, Anzueto A, et al. Clinical epidemiology of COPD: insights from 10 years of the COPD Gene Study. Chest. 2019;156(2):228–238. doi:10.1016/j.chest.2019.04.135
   PubMed Web of Science ®Google Scholar
• Ragland MF, Benway CJ, Lutz SM, et al. Genetic advances in chronic obstructive pulmonary disease. Insights from COPDGene. Am J Respir Crit Care Med. 2019;200(6):677–690. doi:10.1164/rccm.201808-1455SO
   PubMed Web of Science ®Google Scholar
• Regan EA, Hokanson JE, Murphy JR, et al. Genetic epidemiology of COPD (COPDGene) study design. COPD. 2010;7(1):32–43. doi:10.3109/15412550903499522
   PubMedGoogle Scholar
• Possemato R, Marks KM, Shaul YD, et al. Functional genomics reveal that the serine synthesis pathway is essential in breast cancer. Nature. 2011;476(7360):346–350. doi:10.1038/nature10350
   PubMed Web of Science ®Google Scholar
• Kursa MB, Rudnicki WR, Feature selection with the Boruta package. J Stat Softw. 2010;36(i11):1–13. doi:10.18637/jss.v036.i11
   Web of Science ®Google Scholar
• Kursa MB. Robustness of random forest-based gene selection methods. BMC Bioinform. 2014;15(1):8. doi:10.1186/1471-2105-15-8
   PubMed Web of Science ®Google Scholar
• Monti S, Tamayo P, Mesirov J, Golub T. Consensus clustering: a resampling-based method for class discovery and visualization of gene expression microarray data. Mach Learn. 2003;52(1):91–118. doi:10.1023/A:1023949509487
   Web of Science ®Google Scholar
• Gu Z, Schlesner M, Hübschmann D. cola: an R/Bioconductor package for consensus partitioning through a general framework. Nucleic Acids Res. 2020;(gkaa1146). doi:10.1093/nar/gkaa1146
   Web of Science ®Google Scholar
• Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. PNAS. 2005;102(43):15545–15550. doi:10.1073/pnas.0506580102
   PubMed Web of Science ®Google Scholar
• Yu G, Wang L-G, Han Y, He Q-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5):284–287. doi:10.1089/omi.2011.0118
   PubMed Web of Science ®Google Scholar
• Yu G, He Q-Y. ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization. Mol Biosyst. 2016;12(2):477–479. doi:10.1039/c5mb00663e
   PubMedGoogle Scholar
• Kolde R, Laur S, Adler P, Vilo J. Robust rank aggregation for gene list integration and meta-analysis. Bioinformatics. 2012;28(4):573–580. doi:10.1093/bioinformatics/btr709
   PubMed Web of Science ®Google Scholar
• Miao Y-R, Zhang Q, Lei Q, et al. ImmuCellAI: a unique method for comprehensive T-cell subsets abundance prediction and its application in cancer immunotherapy. Advan Sci. 2020;7(7):1902880. doi:10.1002/advs.201902880
   Web of Science ®Google Scholar
• Singh D, Fox SM, Tal-Singer R, Bates S, Riley JH, Celli B. Altered gene expression in blood and sputum in COPD frequent exacerbators in the ECLIPSE cohort. PLoS One. 2014;9(9):e107381. doi:10.1371/journal.pone.0107381
   PubMed Web of Science ®Google Scholar
• Morrow JD, Qiu W, Chhabra D, et al. Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods. BMC Med Genomics. 2015;8(1):1. doi:10.1186/s12920-014-0072-y
   PubMedGoogle Scholar
• Ramasubramanian R, Kalhan R, Jacobs DR, et al. Lung function and gene expression of pathogen recognition pathway receptors: the cardia lung study. Sci Rep. 2020;10(1):1–8. doi:10.1038/s41598-020-65923-z
   PubMed Web of Science ®Google Scholar
• Castaldi PJ, Boueiz A, Yun J, et al. Machine learning characterization of COPD subtypes: insights from the COPDGene study. Chest. 2020;157(5):1147–1157. doi:10.1016/j.chest.2019.11.039
   PubMed Web of Science ®Google Scholar
• Wright KT, Giardina C, Vella AT. Therapeutic targeting of the inflammome. Biochem Pharmacol. 2014;92(2):184–191. doi:10.1016/j.bcp.2014.08.027
   PubMed Web of Science ®Google Scholar
• Halper-Stromberg E, Yun JH, Parker MM, et al. Systemic markers of adaptive and innate immunity are associated with chronic obstructive pulmonary disease severity and spirometric disease progression. Am J Respir Cell Mol Biol. 2018;58(4):500–509. doi:10.1165/rcmb.2017-0373OC
   PubMed Web of Science ®Google Scholar
• Geerdink JX, Simons SO, Pike R, Stauss HJ, Heijdra YF, Hurst JR. Differences in systemic adaptive immunity contribute to the ‘frequent exacerbator’ COPD phenotype. Respir Res. 2016;17(1):140. doi:10.1186/s12931-016-0456-y
   PubMedGoogle Scholar
• Nishimura M, Makita H, Nagai K, et al. Annual change in pulmonary function and clinical phenotype in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2012;185(1):44–52. doi:10.1164/rccm.201106-0992OC
   PubMed Web of Science ®Google Scholar
• Higashimoto Y, Iwata T, Okada M, Satoh H, Fukuda K, Tohda Y. Serum biomarkers as predictors of lung function decline in chronic obstructive pulmonary disease. Respir Med. 2009;103(8):1231–1238. doi:10.1016/j.rmed.2009.01.021
   PubMed Web of Science ®Google Scholar
• Takahashi M, Kizuka Y, Ohtsubo K, Gu J, Taniguchi N. Disease-associated glycans on cell surface proteins. Mol Aspects Med. 2016;51:56–70. doi:10.1016/j.mam.2016.04.008
   PubMed Web of Science ®Google Scholar
• Kamio K, Yoshida T, Gao C, et al. α1,6-Fucosyltransferase (Fut8) is implicated in vulnerability to elastase-induced emphysema in mice and a possible non-invasive predictive marker for disease progression and exacerbations in chronic obstructive pulmonary disease (COPD). Biochem Biophys Res Commun. 2012;424(1):112–117. doi:10.1016/j.bbrc.2012.06.081
   PubMed Web of Science ®Google Scholar
• Kamio K, Ishii T, Gao C, et al. Correlation Between Fut8 activity and airflow limitation in patients with Chronic Obstructive Pulmonary Disease (COPD) accompanied by the emphysematous phenotype. In: B42. COPD Pathogenesis: Cellular expression and protein responses. American Thoracic Society International Conference Abstracts; 2011; American Thoracic Society:A3013–A3013. doi:10.1164/ajrccm-conference.2011.183.1_MeetingAbstracts.A3013
   Google Scholar
• Lau KS, Partridge EA, Grigorian A, et al. Complex N-glycan number and degree of branching cooperate to regulate cell proliferation and differentiation. Cell. 2007;129(1):123–134. doi:10.1016/j.cell.2007.01.049
   PubMed Web of Science ®Google Scholar
• Fimognari FL, Scarlata S, Conte ME, Incalzi RA. Mechanisms of atherothrombosis in chronic obstructive pulmonary disease. Int J Chron Obstruct Pulmon Dis. 2008;3(1):89–96. doi:10.2147/copd.s1401
   PubMedGoogle Scholar
• Dennis EA, Norris PC. Eicosanoid storm in infection and inflammation. Nat Rev Immunol. 2015;15(8):511–523. doi:10.1038/nri3859
   PubMed Web of Science ®Google Scholar
• Lutz SM, Cho MH, Young K, et al. A genome-wide association study identifies risk loci for spirometric measures among smokers of European and African ancestry. BMC Genet. 2015;16:138. doi:10.1186/s12863-015-0299-4
   PubMed Web of Science ®Google Scholar
• Bordron A, Morel M, Bagacean C, et al. Hyposialylation must be considered to develop future therapies in autoimmune diseases. Int J Mol Sci. 2021;22(7):3402. doi:10.3390/ijms22073402
   PubMed Web of Science ®Google Scholar