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Stratification of asthma phenotypes by airway proteomic signatures

التفاصيل البيبلوغرافية
العنوان:	Stratification of asthma phenotypes by airway proteomic signatures
المؤلفون:	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
المساهمون:	Graduate School, AII - Inflammatory diseases, Pulmonology, Ear, Nose and Throat, Epidemiology and Data Science, APH - Methodology, Publica, Commission of the European Communities
المصدر:	Journal of allergy and clinical immunology, 144(1), 70-82. Mosby Inc. U-BIOPRED Study Group 2019, ' Stratification of asthma phenotypes by airway proteomic signatures ', The Journal of allergy and clinical immunology . https://doi.org/10.1016/j.jaci.2019.03.013Test
سنة النشر:	2019
مصطلحات موضوعية:	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
الوصف:	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
وصف الملف:	text; application/pdf
اللغة:	English
تدمد:	0091-6749
الوصول الحر:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2bf8073872c4d9f64ee0c931a0f1f91Test https://eprints.soton.ac.uk/429984Test/
حقوق:	OPEN
رقم الانضمام:	edsair.doi.dedup.....d2bf8073872c4d9f64ee0c931a0f1f91
قاعدة البيانات:	OpenAIRE

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/><searchLink fieldCode="AR" term="%22Onstein%2C+Susanne%22">Onstein, Susanne</searchLink><br /><searchLink fieldCode="AR" term="%22MacNee%2C+William%22">MacNee, William</searchLink><br /><searchLink fieldCode="AR" term="%22Bernardini%2C+Renato%22">Bernardini, Renato</searchLink><br /><searchLink fieldCode="AR" term="%22Bont%2C+Louis%22">Bont, Louis</searchLink><br /><searchLink fieldCode="AR" term="%22Wecksell%2C+Per-Ake%22">Wecksell, Per-Ake</searchLink> ) Array ( [Name] => Author [Label] => Contributors [Group] => Au [Data] => Graduate School<br />AII - Inflammatory diseases<br />Pulmonology<br />Ear, Nose and Throat<br />Epidemiology and Data Science<br />APH - Methodology<br />Publica<br />Commission of the European Communities ) Array ( [Name] => TitleSource [Label] => Source [Group] => Src [Data] => Journal of allergy and clinical immunology, 144(1), 70-82. Mosby Inc.<br />U-BIOPRED Study Group 2019, ' Stratification of asthma phenotypes by airway proteomic signatures ', The Journal of allergy and clinical immunology . https://doi.org/10.1016/j.jaci.2019.03.013 ) Array ( [Name] => DatePubCY [Label] => Publication Year [Group] => Date [Data] => 2019 ) Array ( [Name] => Subject [Label] => Subject Terms [Group] => Su [Data] => <searchLink fieldCode="DE" term="%220301+basic+medicine%22">0301 basic medicine</searchLink><br /><searchLink fieldCode="DE" term="%22Male%22">Male</searchLink><br /><searchLink fieldCode="DE" term="%22Proteomics%22">Proteomics</searchLink><br /><searchLink fieldCode="DE" term="%22Allergy%22">Allergy</searchLink><br /><searchLink fieldCode="DE" term="%22Proteome%22">Proteome</searchLink><br /><searchLink fieldCode="DE" term="%22Neutrophils%22">Neutrophils</searchLink><br /><searchLink fieldCode="DE" term="%22Respiratory+Medicine+and+Allergy%22">Respiratory Medicine and Allergy</searchLink><br /><searchLink fieldCode="DE" term="%22Transcriptome%22">Transcriptome</searchLink><br /><searchLink fieldCode="DE" term="%220302+clinical+medicine%22">0302 clinical medicine</searchLink><br /><searchLink fieldCode="DE" term="%22neutrophils%22">neutrophils</searchLink><br /><searchLink fieldCode="DE" term="%22Forced+Expiratory+Volume%22">Forced Expiratory Volume</searchLink><br /><searchLink fieldCode="DE" term="%22Immunology+and+Allergy%22">Immunology and Allergy</searchLink><br /><searchLink fieldCode="DE" term="%22CD44%22">CD44</searchLink><br /><searchLink fieldCode="DE" term="%22610+Medicine+%26+health%22">610 Medicine & health</searchLink><br /><searchLink fieldCode="DE" term="%22Lungmedicin+och+allergi%22">Lungmedicin och allergi</searchLink><br /><searchLink fieldCode="DE" term="%22phenotypes%22">phenotypes</searchLink><br /><searchLink fieldCode="DE" term="%22Middle+Aged%22">Middle Aged</searchLink><br /><searchLink fieldCode="DE" term="%22medicine%2Eanatomical%5Fstructure%22">medicine.anatomical_structure</searchLink><br /><searchLink fieldCode="DE" term="%22Phenotype%22">Phenotype</searchLink><br /><searchLink fieldCode="DE" term="%221107+Immunology%22">1107 Immunology</searchLink><br /><searchLink fieldCode="DE" term="%22Female%22">Female</searchLink><br /><searchLink fieldCode="DE" term="%22eosinophils%22">eosinophils</searchLink><br /><searchLink fieldCode="DE" term="%22medicine%2Esymptom%22">medicine.symptom</searchLink><br /><searchLink fieldCode="DE" term="%22Life+Sciences+%26+Biomedicine%22">Life Sciences & Biomedicine</searchLink><br /><searchLink fieldCode="DE" term="%22Adult%22">Adult</searchLink><br /><searchLink fieldCode="DE" term="%22Settore+BIO%2F14+-+FARMACOLOGIA%22">Settore BIO/14 - FARMACOLOGIA</searchLink><br /><searchLink fieldCode="DE" term="%22Immunology%22">Immunology</searchLink><br /><searchLink fieldCode="DE" term="%22Computational+biology%22">Computational biology</searchLink><br /><searchLink fieldCode="DE" term="%2203+medical+and+health+sciences%22">03 medical and health sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Young+Adult%22">Young Adult</searchLink><br /><searchLink fieldCode="DE" term="%22proteomics%22">proteomics</searchLink><br /><searchLink fieldCode="DE" term="%22Eosinophilia%22">Eosinophilia</searchLink><br /><searchLink fieldCode="DE" term="%22medicine%22">medicine</searchLink><br /><searchLink fieldCode="DE" term="%22Humans%22">Humans</searchLink><br /><searchLink fieldCode="DE" term="%22U-BIOPRED+Study+Group%22">U-BIOPRED Study Group</searchLink><br /><searchLink fieldCode="DE" term="%22Asthma%22">Asthma</searchLink><br /><searchLink fieldCode="DE" term="%22Aged%22">Aged</searchLink><br /><searchLink fieldCode="DE" term="%22Science+%26+Technology%22">Science & Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Microarray+analysis+techniques%22">Microarray analysis techniques</searchLink><br /><searchLink fieldCode="DE" term="%22business%2Eindustry%22">business.industry</searchLink><br /><searchLink fieldCode="DE" term="%22Sputum%22">Sputum</searchLink><br /><searchLink fieldCode="DE" term="%22biomarkers%22">biomarkers</searchLink><br /><searchLink fieldCode="DE" term="%22DEGRADATION%22">DEGRADATION</searchLink><br /><searchLink fieldCode="DE" term="%22Eosinophil%22">Eosinophil</searchLink><br /><searchLink fieldCode="DE" term="%22medicine%2Edisease%22">medicine.disease</searchLink><br /><searchLink fieldCode="DE" term="%22Eosinophils%22">Eosinophils</searchLink><br /><searchLink fieldCode="DE" term="%22EXACERBATIONS%22">EXACERBATIONS</searchLink><br /><searchLink fieldCode="DE" term="%22030104+developmental+biology%22">030104 developmental biology</searchLink><br /><searchLink fieldCode="DE" term="%22030228+respiratory+system%22">030228 respiratory system</searchLink><br /><searchLink fieldCode="DE" term="%22business%22">business</searchLink> ) Array ( [Name] => Abstract [Label] => Description [Group] => Ab [Data] => 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 ) Array ( [Name] => Format [Label] => File Description [Group] => SrcInfo [Data] => text; application/pdf ) Array ( [Name] => Language [Label] => Language [Group] => Lang [Data] => English ) Array ( [Name] => ISSN [Label] => ISSN [Group] => ISSN [Data] => 0091-6749 ) Array ( [Name] => URL [Label] => Access URL [Group] => URL [Data] => <link linkTarget="URL" linkTerm="https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2bf8073872c4d9f64ee0c931a0f1f91" linkWindow="_blank">https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2bf8073872c4d9f64ee0c931a0f1f91</link><br /><link linkTarget="URL" linkTerm="https://eprints.soton.ac.uk/429984/" linkWindow="_blank">https://eprints.soton.ac.uk/429984/</link> ) Array ( [Name] => Copyright [Label] => Rights [Group] => Cpyrght [Data] => OPEN ) Array ( [Name] => AN [Label] => Accession Number [Group] => ID [Data] => edsair.doi.dedup.....d2bf8073872c4d9f64ee0c931a0f1f91 )
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Array ( [Type] => issn-print [Value] => 00916749 ) [1] => Array ( [Type] => issn-locals [Value] => edsair ) [2] => Array ( [Type] => issn-locals [Value] => edsairFT ) ) ) ) ) ) )
IllustrationInfo