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Disease-specific regulation of gene expression in a comparative analysis of juvenile idiopathic arthritis and inflammatory bowel disease

Overview of attention for article published in Genome Medicine, June 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (70th percentile)

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Title
Disease-specific regulation of gene expression in a comparative analysis of juvenile idiopathic arthritis and inflammatory bowel disease
Published in
Genome Medicine, June 2018
DOI 10.1186/s13073-018-0558-x
Pubmed ID
Authors

Angela Mo, Urko M. Marigorta, Dalia Arafat, Lai Hin Kimi Chan, Lori Ponder, Se Ryeong Jang, Jarod Prince, Subra Kugathasan, Sampath Prahalad, Greg Gibson

Abstract

The genetic and immunological factors that contribute to differences in susceptibility and progression between sub-types of inflammatory and autoimmune diseases continue to be elucidated. Inflammatory bowel disease and juvenile idiopathic arthritis are both clinically heterogeneous and known to be due in part to abnormal regulation of gene activity in diverse immune cell types. Comparative genomic analysis of these conditions is expected to reveal differences in underlying genetic mechanisms of disease. We performed RNA-Seq on whole blood samples from 202 patients with oligoarticular, polyarticular, or systemic juvenile idiopathic arthritis, or with Crohn's disease or ulcerative colitis, as well as healthy controls, to characterize differences in gene expression. Gene ontology analysis combined with Blood Transcript Module and Blood Informative Transcript analysis was used to infer immunological differences. Comparative expression quantitative trait locus (eQTL) analysis was used to quantify disease-specific regulation of transcript abundance. A pattern of differentially expressed genes and pathways reveals a gradient of disease spanning from healthy controls to oligoarticular, polyarticular, and systemic juvenile idiopathic arthritis (JIA); Crohn's disease; and ulcerative colitis. Transcriptional risk scores also provide good discrimination of controls, JIA, and IBD. Most eQTL are found to have similar effects across disease sub-types, but we also identify disease-specific eQTL at loci associated with disease by GWAS. JIA and IBD are characterized by divergent peripheral blood transcriptomes, the genetic regulation of which displays limited disease specificity, implying that disease-specific genetic influences are largely independent of, or downstream of, eQTL effects.

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The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 22%
Researcher 12 19%
Student > Bachelor 7 11%
Other 4 6%
Student > Postgraduate 3 5%
Other 9 14%
Unknown 15 23%
Readers by discipline Count As %
Medicine and Dentistry 19 30%
Biochemistry, Genetics and Molecular Biology 13 20%
Agricultural and Biological Sciences 5 8%
Neuroscience 3 5%
Computer Science 2 3%
Other 6 9%
Unknown 16 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 09 July 2018.
All research outputs
#5,796,460
of 23,577,654 outputs
Outputs from Genome Medicine
#999
of 1,466 outputs
Outputs of similar age
#97,730
of 330,240 outputs
Outputs of similar age from Genome Medicine
#19
of 27 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,466 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.9. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 330,240 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.