Cargando…

Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis

BACKGROUND: Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). METHOD: RNA-sequencing-(RNA-seq)-based expression analysis of 377 ge...

Descripción completa

Detalles Bibliográficos
Autores principales: Shchetynsky, Klementy, Diaz-Gallo, Lina-Marcella, Folkersen, Lasse, Hensvold, Aase Haj, Catrina, Anca Irinel, Berg, Louise, Klareskog, Lars, Padyukov, Leonid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5288892/
https://www.ncbi.nlm.nih.gov/pubmed/28148290
http://dx.doi.org/10.1186/s13075-017-1220-5
_version_ 1782504411846672384
author Shchetynsky, Klementy
Diaz-Gallo, Lina-Marcella
Folkersen, Lasse
Hensvold, Aase Haj
Catrina, Anca Irinel
Berg, Louise
Klareskog, Lars
Padyukov, Leonid
author_facet Shchetynsky, Klementy
Diaz-Gallo, Lina-Marcella
Folkersen, Lasse
Hensvold, Aase Haj
Catrina, Anca Irinel
Berg, Louise
Klareskog, Lars
Padyukov, Leonid
author_sort Shchetynsky, Klementy
collection PubMed
description BACKGROUND: Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). METHOD: RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of “connector” genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. RESULTS: There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. CONCLUSION: Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13075-017-1220-5) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-5288892
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-52888922017-02-06 Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis Shchetynsky, Klementy Diaz-Gallo, Lina-Marcella Folkersen, Lasse Hensvold, Aase Haj Catrina, Anca Irinel Berg, Louise Klareskog, Lars Padyukov, Leonid Arthritis Res Ther Research Article BACKGROUND: Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). METHOD: RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of “connector” genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. RESULTS: There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. CONCLUSION: Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13075-017-1220-5) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-02 2017 /pmc/articles/PMC5288892/ /pubmed/28148290 http://dx.doi.org/10.1186/s13075-017-1220-5 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Shchetynsky, Klementy
Diaz-Gallo, Lina-Marcella
Folkersen, Lasse
Hensvold, Aase Haj
Catrina, Anca Irinel
Berg, Louise
Klareskog, Lars
Padyukov, Leonid
Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis
title Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis
title_full Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis
title_fullStr Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis
title_full_unstemmed Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis
title_short Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis
title_sort discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5288892/
https://www.ncbi.nlm.nih.gov/pubmed/28148290
http://dx.doi.org/10.1186/s13075-017-1220-5
work_keys_str_mv AT shchetynskyklementy discoveryofnewcandidategenesforrheumatoidarthritisthroughintegrationofgeneticassociationdatawithexpressionpathwayanalysis
AT diazgallolinamarcella discoveryofnewcandidategenesforrheumatoidarthritisthroughintegrationofgeneticassociationdatawithexpressionpathwayanalysis
AT folkersenlasse discoveryofnewcandidategenesforrheumatoidarthritisthroughintegrationofgeneticassociationdatawithexpressionpathwayanalysis
AT hensvoldaasehaj discoveryofnewcandidategenesforrheumatoidarthritisthroughintegrationofgeneticassociationdatawithexpressionpathwayanalysis
AT catrinaancairinel discoveryofnewcandidategenesforrheumatoidarthritisthroughintegrationofgeneticassociationdatawithexpressionpathwayanalysis
AT berglouise discoveryofnewcandidategenesforrheumatoidarthritisthroughintegrationofgeneticassociationdatawithexpressionpathwayanalysis
AT klareskoglars discoveryofnewcandidategenesforrheumatoidarthritisthroughintegrationofgeneticassociationdatawithexpressionpathwayanalysis
AT padyukovleonid discoveryofnewcandidategenesforrheumatoidarthritisthroughintegrationofgeneticassociationdatawithexpressionpathwayanalysis