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Inter-tissue coexpression network analysis reveals DPP4 as an important gene in heart to blood communication

Overview of attention for article published in Genome Medicine, February 2016
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Title
Inter-tissue coexpression network analysis reveals DPP4 as an important gene in heart to blood communication
Published in
Genome Medicine, February 2016
DOI 10.1186/s13073-016-0268-1
Pubmed ID
Authors

Quan Long, Carmen Argmann, Sander M. Houten, Tao Huang, Siwu Peng, Yong Zhao, Zhidong Tu, The GTEx Consortium, Jun Zhu

Abstract

Inter-tissue molecular interactions are critical to the function and behavior of biological systems in multicellular organisms, but systematic studies of interactions between tissues are lacking. Also, existing studies of inter-tissue interactions are based on direct gene expression correlations, which can't distinguish correlations due to common genetic architectures versus biochemical or molecular signal exchange between tissues. We developed a novel strategy to study inter-tissue interaction by removing effects of genetic regulation of gene expression (genetic decorrelation). We applied our method to the comprehensive atlas of gene expression across nine human tissues in the Genotype-Tissue Expression (GTEx) project to generate novel genetically decorrelated inter-tissue networks. From this we derived modules of genes important in inter-tissue interactions that are likely driven by biological signal exchange instead of their common genetic basis. Importantly we highlighted communication between tissues and elucidated gene activities in one tissue inducing gene expression changes in others. We reveal global unidirectional inter-tissue coordination of specific biological pathways such as protein synthesis. Using our data, we highlighted a clinically relevant example whereby heart expression of DPP4 was coordinated with a gene expression signature characteristic for whole blood proliferation, potentially impacting peripheral stem cell mobilization. We also showed that expression of the poorly characterized FOCAD in heart correlated with protein biosynthetic processes in the lung. In summary, this is the first resource of human multi-tissue networks enabling the investigation of molecular inter-tissue interactions. With the networks in hand, we may systematically design combination therapies that simultaneously target multiple tissues or pinpoint potential side effects of a drug in other tissues.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Unknown 48 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 24%
Student > Bachelor 7 14%
Student > Master 6 12%
Researcher 5 10%
Student > Doctoral Student 4 8%
Other 9 18%
Unknown 7 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 34%
Computer Science 7 14%
Agricultural and Biological Sciences 7 14%
Medicine and Dentistry 4 8%
Nursing and Health Professions 2 4%
Other 5 10%
Unknown 8 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 27 February 2016.
All research outputs
#14,417,947
of 24,598,501 outputs
Outputs from Genome Medicine
#1,291
of 1,517 outputs
Outputs of similar age
#199,314
of 410,309 outputs
Outputs of similar age from Genome Medicine
#35
of 42 outputs
Altmetric has tracked 24,598,501 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,517 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.2. This one is in the 14th percentile – i.e., 14% 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 410,309 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 50% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.