Meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis

Abstract Publicly available ulcerative colitis (UC) gene expression datasets from observational studies and clinical trials include inherently heterogeneous disease characteristics and methodology. We used meta-analysis to identify a robust UC gene signature from inflamed biopsies. Eight gene expres...

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Autores principales:	Bryan Linggi, Vipul Jairath, Guangyong Zou, Lisa M. Shackelton, Dermot P. B. McGovern, Azucena Salas, Bram Verstockt, Mark S. Silverberg, Shadi Nayeri, Brian G. Feagan, Niels Vande Casteele
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/7837a75292a542ebb02f0ecb74810914
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spelling	oai:doaj.org-article:7837a75292a542ebb02f0ecb748109142021-12-02T17:24:11ZMeta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis10.1038/s41598-021-97366-52045-2322https://doaj.org/article/7837a75292a542ebb02f0ecb748109142021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-97366-5https://doaj.org/toc/2045-2322Abstract Publicly available ulcerative colitis (UC) gene expression datasets from observational studies and clinical trials include inherently heterogeneous disease characteristics and methodology. We used meta-analysis to identify a robust UC gene signature from inflamed biopsies. Eight gene expression datasets derived from biopsy tissue samples from noninflammatory bowel disease (IBD) controls and areas of active inflammation from patients with UC were publicly available. Expression- and meta-data were downloaded with GEOquery. Differentially expressed genes (DEG) in individual datasets were defined as those with fold change > 1.5 and a Benjamini–Hochberg adjusted P value < .05. Meta-analysis of all DEG used a random effects model. Reactome pathway enrichment analysis was conducted. Meta-analysis identified 946 up- and 543 down-regulated genes in patients with UC compared to non-IBD controls (1.2 and 1.7 times fewer up- and down-regulated genes than the median of the individual datasets). Top-ranked up- and down-regulated DEG were LCN2 and AQP8. Multiple immune-related pathways (e.g., ‘Chemokine receptors bind chemokine’ and ‘Interleukin-10 signaling’) were significantly up-regulated in UC, while ‘Biological oxidations’ and ‘Fatty acid metabolism’ were downregulated. A web-based data-mining tool with the meta-analysis results was made available ( https://premedibd.com/genes.html ). A UC inflamed biopsy disease gene signature was derived. This signature may be an unbiased reference for comparison and improve the efficiency of UC biomarker studies by increasing confidence for identification of disease-related genes and pathways.Bryan LinggiVipul JairathGuangyong ZouLisa M. ShackeltonDermot P. B. McGovernAzucena SalasBram VerstocktMark S. SilverbergShadi NayeriBrian G. FeaganNiels Vande CasteeleNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Bryan Linggi Vipul Jairath Guangyong Zou Lisa M. Shackelton Dermot P. B. McGovern Azucena Salas Bram Verstockt Mark S. Silverberg Shadi Nayeri Brian G. Feagan Niels Vande Casteele Meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis
description	Abstract Publicly available ulcerative colitis (UC) gene expression datasets from observational studies and clinical trials include inherently heterogeneous disease characteristics and methodology. We used meta-analysis to identify a robust UC gene signature from inflamed biopsies. Eight gene expression datasets derived from biopsy tissue samples from noninflammatory bowel disease (IBD) controls and areas of active inflammation from patients with UC were publicly available. Expression- and meta-data were downloaded with GEOquery. Differentially expressed genes (DEG) in individual datasets were defined as those with fold change > 1.5 and a Benjamini–Hochberg adjusted P value < .05. Meta-analysis of all DEG used a random effects model. Reactome pathway enrichment analysis was conducted. Meta-analysis identified 946 up- and 543 down-regulated genes in patients with UC compared to non-IBD controls (1.2 and 1.7 times fewer up- and down-regulated genes than the median of the individual datasets). Top-ranked up- and down-regulated DEG were LCN2 and AQP8. Multiple immune-related pathways (e.g., ‘Chemokine receptors bind chemokine’ and ‘Interleukin-10 signaling’) were significantly up-regulated in UC, while ‘Biological oxidations’ and ‘Fatty acid metabolism’ were downregulated. A web-based data-mining tool with the meta-analysis results was made available ( https://premedibd.com/genes.html ). A UC inflamed biopsy disease gene signature was derived. This signature may be an unbiased reference for comparison and improve the efficiency of UC biomarker studies by increasing confidence for identification of disease-related genes and pathways.
format	article
author	Bryan Linggi Vipul Jairath Guangyong Zou Lisa M. Shackelton Dermot P. B. McGovern Azucena Salas Bram Verstockt Mark S. Silverberg Shadi Nayeri Brian G. Feagan Niels Vande Casteele
author_facet	Bryan Linggi Vipul Jairath Guangyong Zou Lisa M. Shackelton Dermot P. B. McGovern Azucena Salas Bram Verstockt Mark S. Silverberg Shadi Nayeri Brian G. Feagan Niels Vande Casteele
author_sort	Bryan Linggi
title	Meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis
title_short	Meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis
title_full	Meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis
title_fullStr	Meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis
title_full_unstemmed	Meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis
title_sort	meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/7837a75292a542ebb02f0ecb74810914
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Meta-analysis of gene expression disease signatures in colonic biopsy tissue from patients with ulcerative colitis

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