1. Stratification of asthma phenotypes by airway proteomic signatures
- Author
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Schofield, James P. R., Burg, Dominic, Nicholas, Ben, Strazzeri, Fabio, Brandsma, Joost, Staykova, Doroteya, Folisi, Caterina, Bansal, Aruna T., Xian, Yang, Guo, Yike, Rowe, Anthony, Corfield, Julie, Wilson, Susan, Ward, Jonathan, Lutter, Rene, Shaw, Dominick E., Bakke, Per S., Caruso, Massimo, Dahlen, Sven-Erik, Fowler, Stephen J., Horvath, Ildiko, Howarth, Peter, Krug, Norbert, Montuschi, Paolo, Sanak, Marek, Sandstrom, Thomas, Sun, Kai, Pandis, Ioannis, Riley, John, Auffray, Charles, De Meulder, Bertrand, Lefaudeux, Diane, Sousa, Ana R., Adcock, Ian M., Chung, Kian Fan, Sterk, Peter J., Skipp, Paul J., Djukanovic, Ratko, Ahmed, H., Allen, D., Badorrek, P., Ballereau, S., Baribaud, F., Batuwitage, M. K., Bedding, A., Behndig, A. F., Berglind, A., Berton, A., Bigler, J., Boedigheimer, M. J., Bonnelykke, K., Brinkman, P., Bush, A., Campagna, D., Casaulta, C., Chaiboonchoe, A., Davison, T., De Meulder, B., Delin, I., Dennison, P., Dodson, P., El Hadjam, L., Erzen, D., Faulenbach, C., Fichtner, K., Fitch, N., Formaggio, E., Gahlemann, M., Galffy, G., Garissi, D., Garret, T., Gent, J., Guillmant-Farry, E., Henriksson, E., Hoda, U., Hohlfeld, J. M., Hu, X., James, A., Johnson, K., Jullian, N., Kerry, G., Klueglich, M., Knowles, R., Konradsen, J. R., Kretsos, K., Krueger, L., Lantz, A. -S, Larminie, C., Latzin, P., Lefaudeux, D., Lemonnier, N., Lowe, L. A., Lutter, R., Manta, A., Mazein, A., McEvoy, L., Menzies-Gow, A., Mores, N., Murray, C. S., Nething, K., Nihlen, U., Niven, R., Nordlund, B., Nsubuga, S., Pellet, J., Pison, C., Pratico, G., Puig Valls, M., Riemann, K., Rocha, J. P., Rossios, C., Santini, G., Saqi, M., Scott, S., Sehgal, N., Selby, A., Soderman, P., Sogbesan, A., Spycher, F., Stephan, S., Stokholm, J., Sunther, M., Szentkereszty, M., Tamasi, L., Tariq, K., Valente, S., van Aalderen, W. M., van Drunen, C. M., Van Eyll, J., Vyas, A., Yu, W., Zetterquist, W., Zolkipli, Z., Zwinderman, A. H., Adriaens, Nora, Aliprantis, Antonios, Alving, Kjell, Bakke, Per, Balgoma, David, Barber, Clair, Baribaud, Frederic, Bates, Stewart, Bautmans, An, Beleta, Jorge, Bochenek, Grazyna, Braun, Armin, Carayannopoulos, Leon, Rocha, Joao Pedro Carvalho da Purificacao, Chaleckis, Romanas, D'Amico, Arnaldo, De Alba, Jorge, De Lepeleire, Inge, Dekker, Tamara, Dijkhuis, Annemiek, Draper, Aleksandra, Edwards, Jessica, Emma, Rosalia, Ericsson, Magnus, Flood, Breda, Gallart, Hector, Gomez, Cristina, Gove, Kerry, Gozzard, Neil, Haughney, John, Hewitt, Lorraine, Hohlfeld, Jens, Holweg, Cecile, Hu, Richard, Hu, Sile, Kamphuis, Juliette, Kennington, Erika J., Kerry, Dyson, Knobel, Hugo, Kolmert, Johan, Kots, Maxim, Kuo, Scott, Kupczyk, Maciej, Lambrecht, Bart, Lone-Latif, Saeeda, Loza, Matthew J., Marouzet, Lisa, Martin, Jane, Masefield, Sarah, Mathon, Caroline, Meah, Sally, Meiser, Andrea, Metcalf, Leanne, Mikus, Maria, Miralpeix, Montse, Monk, Philip, Naz, Shama, Nilsson, Peter, Ostling, Jorgen, Pacino, Antonio, Palkonen, Susanna, Pavlidis, Stelios, Pennazza, Giorgio, Petren, Anne, Pink, Sandy, Postle, Anthony, Powell, Pippa, Rahman-Amin, Malayka, Rao, Navin, Ravanetti, Lara, Ray, Emma, Reinke, Stacey, Reynolds, Leanne, Robberechts, Martine, Roberts, Amanda, Russell, Kirsty, Rutgers, Michael, Santoninco, Marco, Schoelch, Corinna, Sjodin, Marcus, Smids, Barbara, Smith, Caroline, Smith, Jessica, Smith, Katherine M., Thorngren, John-Olof, Thornton, Bob, Thorsen, Jonathan, van de Pol, Marianne, van Geest, Marleen, Versnel, Jenny, Vink, Anton, Wald, Frans, Walker, Samantha, Weiszhart, Zsoka, Wetzel, Kristiane, Wheelock, Craig E., Wiegman, Coen, Williams, Sian, Wilson, Susan J., Woodcock, Ashley, Yang, Xian, Yeyasingham, Elizabeth, Prins, Jan-Bas, Gahlemann, Martina, Visintin, Luigi, Evans, Hazel, Puhl, Martine, Buzermaniene, Lina, Hudson, Val, Bond, Laura, de Boer, Pim, Widdershoven, Guy, Sigmund, Ralf, Supple, David, Hamerlijnck, Dominique, Negus, Jenny, Kamphuis, Julitte, Sergison, Lehanne, Onstein, Susanne, MacNee, William, Bernardini, Renato, Bont, Louis, Wecksell, Per-Ake, Graduate School, AII - Inflammatory diseases, Pulmonology, Ear, Nose and Throat, Epidemiology and Data Science, APH - Methodology, Publica, and Commission of the European Communities
- Subjects
0301 basic medicine ,Male ,Proteomics ,Allergy ,Proteome ,Neutrophils ,Respiratory Medicine and Allergy ,Transcriptome ,0302 clinical medicine ,neutrophils ,Forced Expiratory Volume ,Immunology and Allergy ,CD44 ,610 Medicine & health ,Lungmedicin och allergi ,phenotypes ,Middle Aged ,medicine.anatomical_structure ,Phenotype ,1107 Immunology ,Female ,eosinophils ,medicine.symptom ,Life Sciences & Biomedicine ,Adult ,Settore BIO/14 - FARMACOLOGIA ,Immunology ,Computational biology ,03 medical and health sciences ,Young Adult ,proteomics ,Eosinophilia ,medicine ,Humans ,U-BIOPRED Study Group ,Asthma ,Aged ,Science & Technology ,Microarray analysis techniques ,business.industry ,Sputum ,biomarkers ,DEGRADATION ,Eosinophil ,medicine.disease ,Eosinophils ,EXACERBATIONS ,030104 developmental biology ,030228 respiratory system ,business - Abstract
Background: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms. Objective: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification. Methods: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. Results: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms. Conclusion: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies. asthma proteomics biomarkers eosinophils neutrophils
- Published
- 2019