A transcriptome-driven analysis of epithelial brushings and bronchial biopsies to define asthma phenotypes in U-BIOPRED

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Fältnamn	Indikatorer	Metadata
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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MEDICIN OCH HÄLSOVETENSKAP: MEDICIN OCH HÄLS ...; och Klinisk medicin; och Lungmedicin och ...

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