Search: onr:"swepub:oai:DiVA.org:umu-131170" > A transcriptome-dri...
Fältnamn | Indikatorer | Metadata |
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000 | 04528naa a2200697 4500 | |
001 | oai:DiVA.org:umu-131170 | |
003 | SwePub | |
008 | 170207s2017 | |||||||||||000 ||eng| | |
009 | oai:prod.swepub.kib.ki.se:135162020 | |
024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1311702 URI |
024 | 7 | a https://doi.org/10.1164/rccm.201512-2452OC2 DOI |
024 | 7 | a http://kipublications.ki.se/Default.aspx?queryparsed=id:1351620202 URI |
040 | a (SwePub)umud (SwePub)ki | |
041 | a engb eng | |
042 | 9 SwePub | |
072 | 7 | a ref2 swepub-contenttype |
072 | 7 | a art2 swepub-publicationtype |
100 | 1 | a Kuo, Chih-Hsi Scott4 aut |
245 | 1 0 | a A transcriptome-driven analysis of epithelial brushings and bronchial biopsies to define asthma phenotypes in U-BIOPRED |
264 | 1 | c 2017 |
338 | a print2 rdacarrier | |
520 | a RATIONALE AND OBJECTIVES: Asthma is a heterogeneous disease driven by diverse immunologic and inflammatory mechanisms. We used transcriptomic profiling of airway tissues to help define asthma phenotypes.METHODS: The transcriptome from bronchial biopsies and epithelial brushings of 107 moderate-to-severe asthmatics were annotated by gene-set variation analysis (GSVA) using 42 gene-signatures relevant to asthma, inflammation and immune function. Topological data analysis (TDA) of clinical and histological data was used to derive clusters and the nearest shrunken centroid algorithm used for signature refinement.RESULTS: 9 GSVA signatures expressed in bronchial biopsies and airway epithelial brushings distinguished two distinct asthma subtypes associated with high expression of T-helper type 2 (Th-2) cytokines and lack of corticosteroid response (Group 1 and Group 3). Group 1 had the highest submucosal eosinophils, high exhaled nitric oxide (FeNO) levels, exacerbation rates and oral corticosteroid (OCS) use whilst Group 3 patients showed the highest levels of sputum eosinophils and had a high BMI. In contrast, Group 2 and Group 4 patients had an 86% and 64% probability of having non-eosinophilic inflammation. Using machine-learning tools, we describe an inference scheme using the currently-available inflammatory biomarkers sputum eosinophilia and exhaled nitric oxide levels along with OCS use that could predict the subtypes of gene expression within bronchial biopsies and epithelial cells with good sensitivity and specificity.CONCLUSION: This analysis demonstrates the usefulness of a transcriptomic-driven approach to phenotyping that segments patients who may benefit the most from specific agents that target Th2-mediated inflammation and/or corticosteroid insensitivity. | |
650 | 7 | a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Lungmedicin och allergi0 (SwePub)302192 hsv//swe |
650 | 7 | a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Respiratory Medicine and Allergy0 (SwePub)302192 hsv//eng |
653 | a severe asthma | |
653 | a corticosteroid insensitivity | |
653 | a T-helper type 2 | |
653 | a exhaled nitric oxide | |
653 | a gene set variation analysis | |
700 | 1 | a Pavlidis, Stelios4 aut |
700 | 1 | a Loza, Matthew4 aut |
700 | 1 | a Baribaud, Fred4 aut |
700 | 1 | a Rowe, Anthony4 aut |
700 | 1 | a Pandis, Ioannis4 aut |
700 | 1 | a Hoda, Uruj4 aut |
700 | 1 | a Rossios, Christos4 aut |
700 | 1 | a Sousa, Ana4 aut |
700 | 1 | a Wilson, Susan J4 aut |
700 | 1 | a Howarth, Peter4 aut |
700 | 1 | a Dahlen, Barbrou Karolinska Institutet4 aut |
700 | 1 | a Dahlen, Sven-Eriku Karolinska Institutet4 aut |
700 | 1 | a Chanez, Pascal4 aut |
700 | 1 | a Shaw, Dominick4 aut |
700 | 1 | a Krug, Norbert4 aut |
700 | 1 | a Sandström, Thomasu Umeå universitet,Medicin4 aut0 (Swepub:umu)thsa0001 |
700 | 1 | a De Meulder, Bertrand4 aut |
700 | 1 | a Lefaudeux, Diane4 aut |
700 | 1 | a Fowler, Stephen4 aut |
700 | 1 | a Fleming, Louise4 aut |
700 | 1 | a Corfield, Julie4 aut |
700 | 1 | a Auffray, Charles4 aut |
700 | 1 | a Sterk, Peter J4 aut |
700 | 1 | a Djukanovic, Ratko4 aut |
700 | 1 | a Guo, Yike4 aut |
700 | 1 | a Adcock, Ian M4 aut |
700 | 1 | a Chung, Kian Fan4 aut |
710 | 2 | a Karolinska Institutetb Medicin4 org |
773 | 0 | t American Journal of Respiratory and Critical Care Medicineg 194:4, s. 443-455q 194:4<443-455x 1073-449Xx 1535-4970 |
856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-131170 |
856 | 4 8 | u https://doi.org/10.1164/rccm.201512-2452OC |
856 | 4 8 | u http://kipublications.ki.se/Default.aspx?queryparsed=id:135162020 |
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