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

Overview of attention for article published in Arthritis Research & Therapy, February 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

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1 blog
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Title
Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis
Published in
Arthritis Research & Therapy, February 2017
DOI 10.1186/s13075-017-1220-5
Pubmed ID
Authors

Klementy Shchetynsky, Lina-Marcella Diaz-Gallo, Lasse Folkersen, Aase Haj Hensvold, Anca Irinel Catrina, Louise Berg, Lars Klareskog, Leonid Padyukov

Abstract

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). 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. 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. 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 19%
Student > Master 9 15%
Student > Bachelor 7 12%
Other 6 10%
Student > Ph. D. Student 6 10%
Other 9 15%
Unknown 11 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 24%
Medicine and Dentistry 9 15%
Agricultural and Biological Sciences 4 7%
Computer Science 4 7%
Immunology and Microbiology 3 5%
Other 10 17%
Unknown 15 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 September 2019.
All research outputs
#3,534,454
of 25,382,440 outputs
Outputs from Arthritis Research & Therapy
#791
of 3,380 outputs
Outputs of similar age
#68,739
of 424,587 outputs
Outputs of similar age from Arthritis Research & Therapy
#13
of 44 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,380 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 424,587 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.