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Common disease signatures from gene expression analysis in Huntington’s disease human blood and brain

Overview of attention for article published in Orphanet Journal of Rare Diseases, August 2016
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  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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Title
Common disease signatures from gene expression analysis in Huntington’s disease human blood and brain
Published in
Orphanet Journal of Rare Diseases, August 2016
DOI 10.1186/s13023-016-0475-2
Pubmed ID
Authors

Eleni Mina, Willeke van Roon-Mom, Kristina Hettne, Erik van Zwet, Jelle Goeman, Christian Neri, Peter A.C. ’t Hoen, Barend Mons, Marco Roos

Abstract

Huntington's disease (HD) is a devastating brain disorder with no effective treatment or cure available. The scarcity of brain tissue makes it hard to study changes in the brain and impossible to perform longitudinal studies. However, peripheral pathology in HD suggests that it is possible to study the disease using peripheral tissue as a monitoring tool for disease progression and/or efficacy of novel therapies. In this study, we investigated if blood can be used to monitor disease severity and progression in brain. Since previous attempts using only gene expression proved unsuccessful, we compared blood and brain Huntington's disease signatures in a functional context. Microarray HD gene expression profiles from three brain regions were compared to the transcriptome of HD blood generated by next generation sequencing. The comparison was performed with a combination of weighted gene co-expression network analysis and literature based functional analysis (Concept Profile Analysis). Uniquely, our comparison of blood and brain datasets was not based on (the very limited) gene overlap but on the similarity between the gene annotations in four different semantic categories: "biological process", "cellular component", "molecular function" and "disease or syndrome". We identified signatures in HD blood reflecting a broad pathophysiological spectrum, including alterations in the immune response, sphingolipid biosynthetic processes, lipid transport, cell signaling, protein modification, spliceosome, RNA splicing, vesicle transport, cell signaling and synaptic transmission. Part of this spectrum was reminiscent of the brain pathology. The HD signatures in caudate nucleus and BA4 exhibited the highest similarity with blood, irrespective of the category of semantic annotations used. BA9 exhibited an intermediate similarity, while cerebellum had the least similarity. We present two signatures that were shared between blood and brain: immune response and spinocerebellar ataxias. Our results demonstrate that HD blood exhibits dysregulation that is similar to brain at a functional level, but not necessarily at the level of individual genes. We report two common signatures that can be used to monitor the pathology in brain of HD patients in a non-invasive manner. Our results are an exemplar of how signals in blood data can be used to represent brain disorders. Our methodology can be used to study disease specific signatures in diseases where heterogeneous tissues are involved in the pathology.

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X Demographics

The data shown below were collected from the profiles of 6 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 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 92 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 19%
Student > Ph. D. Student 14 15%
Student > Bachelor 12 13%
Student > Master 10 11%
Student > Postgraduate 6 6%
Other 16 17%
Unknown 17 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 26%
Neuroscience 12 13%
Medicine and Dentistry 12 13%
Agricultural and Biological Sciences 9 10%
Computer Science 4 4%
Other 10 11%
Unknown 22 24%
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 03 August 2016.
All research outputs
#5,905,662
of 22,881,964 outputs
Outputs from Orphanet Journal of Rare Diseases
#726
of 2,628 outputs
Outputs of similar age
#101,094
of 366,376 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#8
of 31 outputs
Altmetric has tracked 22,881,964 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 2,628 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has gotten more attention than average, scoring higher than 71% 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 366,376 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 71% of its contemporaries.
We're also able to compare this research output to 31 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 74% of its contemporaries.