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A Meta-analysis of Gene Expression Signatures of Blood Pressure and Hypertension

Overview of attention for article published in PLoS Genetics, March 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

1 news outlet
24 tweeters
3 Facebook pages
1 Google+ user


62 Dimensions

Readers on

184 Mendeley
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A Meta-analysis of Gene Expression Signatures of Blood Pressure and Hypertension
Published in
PLoS Genetics, March 2015
DOI 10.1371/journal.pgen.1005035
Pubmed ID

Tianxiao Huan, Tõnu Esko, Marjolein J. Peters, Luke C. Pilling, Katharina Schramm, Claudia Schurmann, Brian H. Chen, Chunyu Liu, Roby Joehanes, Andrew D. Johnson, Chen Yao, Sai-xia Ying, Paul Courchesne, Lili Milani, Nalini Raghavachari, Richard Wang, Poching Liu, Eva Reinmaa, Abbas Dehghan, Albert Hofman, André G. Uitterlinden, Dena G. Hernandez, Stefania Bandinelli, Andrew Singleton, David Melzer, Andres Metspalu, Maren Carstensen, Harald Grallert, Christian Herder, Thomas Meitinger, Annette Peters, Michael Roden, Melanie Waldenberger, Marcus Dörr, Stephan B. Felix, Tanja Zeller, Ramachandran Vasan, Christopher J. O'Donnell, Peter J. Munson, Xia Yang, Holger Prokisch, Uwe Völker, Joyce B. J. van Meurs, Luigi Ferrucci, Daniel Levy


Genome-wide association studies (GWAS) have uncovered numerous genetic variants (SNPs) that are associated with blood pressure (BP). Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05). Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%-9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2). Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension.

Twitter Demographics

The data shown below were collected from the profiles of 24 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 184 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iceland 1 <1%
Switzerland 1 <1%
France 1 <1%
Italy 1 <1%
Uruguay 1 <1%
Colombia 1 <1%
Unknown 178 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 19%
Professor 33 18%
Unspecified 25 14%
Student > Ph. D. Student 21 11%
Student > Master 17 9%
Other 53 29%
Readers by discipline Count As %
Medicine and Dentistry 50 27%
Unspecified 41 22%
Biochemistry, Genetics and Molecular Biology 37 20%
Agricultural and Biological Sciences 35 19%
Neuroscience 3 2%
Other 18 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 26 December 2015.
All research outputs
of 12,091,691 outputs
Outputs from PLoS Genetics
of 6,176 outputs
Outputs of similar age
of 218,576 outputs
Outputs of similar age from PLoS Genetics
of 189 outputs
Altmetric has tracked 12,091,691 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,176 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.6. This one has done well, scoring higher than 89% 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 218,576 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.