Transcriptomic insight into the translational value of two murine models in human atopic dermatitis

Abstract This study sought to develop a novel diagnostic tool for atopic dermatitis (AD). Mouse transcriptome data were obtained via RNA-sequencing of dorsal skin tissues of CBA/J mice affected with contact hypersensitivity (induced by treatment with 1-chloro-2,4-dinitrobenzene) or brush stimulation...

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Autores principales:	Young-Won Kim, Eun-A Ko, Sung-Cherl Jung, Donghee Lee, Yelim Seo, Seongtae Kim, Jung-Ha Kim, Hyoweon Bang, Tong Zhou, Jae-Hong Ko
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1c49ef5e932a4699b0cb9617720251bb
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spelling	oai:doaj.org-article:1c49ef5e932a4699b0cb9617720251bb2021-12-02T16:36:03ZTranscriptomic insight into the translational value of two murine models in human atopic dermatitis10.1038/s41598-021-86049-w2045-2322https://doaj.org/article/1c49ef5e932a4699b0cb9617720251bb2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-86049-whttps://doaj.org/toc/2045-2322Abstract This study sought to develop a novel diagnostic tool for atopic dermatitis (AD). Mouse transcriptome data were obtained via RNA-sequencing of dorsal skin tissues of CBA/J mice affected with contact hypersensitivity (induced by treatment with 1-chloro-2,4-dinitrobenzene) or brush stimulation-induced AD-like skin condition. Human transcriptome data were collected from German, Swedish, and American cohorts of AD patients from the Gene Expression Omnibus database. edgeR and SAM algorithms were used to analyze differentially expressed murine and human genes, respectively. The FAIME algorithm was then employed to assign pathway scores based on KEGG pathway database annotations. Numerous genes and pathways demonstrated similar dysregulation patterns in both the murine models and human AD. Upon integrating transcriptome information from both murine and human data, we identified 36 commonly dysregulated differentially expressed genes, which were designated as a 36-gene signature. A severity score (AD index) was applied to each human sample to assess the predictive power of the 36-gene AD signature. The diagnostic power and predictive accuracy of this signature were demonstrated for both AD severity and treatment outcomes in patients with AD. This genetic signature is expected to improve both AD diagnosis and targeted preclinical research.Young-Won KimEun-A KoSung-Cherl JungDonghee LeeYelim SeoSeongtae KimJung-Ha KimHyoweon BangTong ZhouJae-Hong KoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Young-Won Kim Eun-A Ko Sung-Cherl Jung Donghee Lee Yelim Seo Seongtae Kim Jung-Ha Kim Hyoweon Bang Tong Zhou Jae-Hong Ko Transcriptomic insight into the translational value of two murine models in human atopic dermatitis
description	Abstract This study sought to develop a novel diagnostic tool for atopic dermatitis (AD). Mouse transcriptome data were obtained via RNA-sequencing of dorsal skin tissues of CBA/J mice affected with contact hypersensitivity (induced by treatment with 1-chloro-2,4-dinitrobenzene) or brush stimulation-induced AD-like skin condition. Human transcriptome data were collected from German, Swedish, and American cohorts of AD patients from the Gene Expression Omnibus database. edgeR and SAM algorithms were used to analyze differentially expressed murine and human genes, respectively. The FAIME algorithm was then employed to assign pathway scores based on KEGG pathway database annotations. Numerous genes and pathways demonstrated similar dysregulation patterns in both the murine models and human AD. Upon integrating transcriptome information from both murine and human data, we identified 36 commonly dysregulated differentially expressed genes, which were designated as a 36-gene signature. A severity score (AD index) was applied to each human sample to assess the predictive power of the 36-gene AD signature. The diagnostic power and predictive accuracy of this signature were demonstrated for both AD severity and treatment outcomes in patients with AD. This genetic signature is expected to improve both AD diagnosis and targeted preclinical research.
format	article
author	Young-Won Kim Eun-A Ko Sung-Cherl Jung Donghee Lee Yelim Seo Seongtae Kim Jung-Ha Kim Hyoweon Bang Tong Zhou Jae-Hong Ko
author_facet	Young-Won Kim Eun-A Ko Sung-Cherl Jung Donghee Lee Yelim Seo Seongtae Kim Jung-Ha Kim Hyoweon Bang Tong Zhou Jae-Hong Ko
author_sort	Young-Won Kim
title	Transcriptomic insight into the translational value of two murine models in human atopic dermatitis
title_short	Transcriptomic insight into the translational value of two murine models in human atopic dermatitis
title_full	Transcriptomic insight into the translational value of two murine models in human atopic dermatitis
title_fullStr	Transcriptomic insight into the translational value of two murine models in human atopic dermatitis
title_full_unstemmed	Transcriptomic insight into the translational value of two murine models in human atopic dermatitis
title_sort	transcriptomic insight into the translational value of two murine models in human atopic dermatitis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/1c49ef5e932a4699b0cb9617720251bb
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Transcriptomic insight into the translational value of two murine models in human atopic dermatitis

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