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Transcriptome-Wide Analysis Identifies Novel Associations With Blood Pressure

Overview of attention for article published in Hypertension (Highwire), October 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

twitter
9 tweeters
facebook
1 Facebook page

Citations

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7 Dimensions

Readers on

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18 Mendeley
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Title
Transcriptome-Wide Analysis Identifies Novel Associations With Blood Pressure
Published in
Hypertension (Highwire), October 2017
DOI 10.1161/hypertensionaha.117.09458
Pubmed ID
Authors

Tanja Zeller, Claudia Schurmann, Katharina Schramm, Christian Müller, Soonil Kwon, Philipp S. Wild, Alexander Teumer, David Herrington, Arne Schillert, Licia Iacoviello, Adelheid Kratzer, Annika Jagodzinski, Mahir Karakas, Jingzhong Ding, Johannes T. Neumann, Kari Kuulasmaa, Christian Gieger, Tim Kacprowski, Renate B. Schnabel, Michael Roden, Simone Wahl, Jerome I. Rotter, Francisco Ojeda, Maren Carstensen-Kirberg, David-Alexandre Tregouet, Marcus Dörr, Thomas Meitinger, Karl J. Lackner, Petra Wolf, Stephan B. Felix, Ulf Landmesser, Simona Costanzo, Andreas Ziegler, Yongmei Liu, Uwe Völker, Walter Palmas, Holger Prokisch, Xiuqing Guo, Christian Herder, Stefan Blankenberg, Georg Homuth

Abstract

Hypertension represents a major cardiovascular risk factor. The pathophysiology of increased blood pressure (BP) is not yet completely understood. Transcriptome profiling offers possibilities to uncover genetics effects on BP. Based on 2 populations including 2549 individuals, a meta-analyses of monocytic transcriptome-wide profiles were performed to identify transcripts associated with BP. Replication was performed in 2 independent studies of whole-blood transcriptome data including 1990 individuals. For identified candidate genes, a direct link between long-term changes in BP and gene expression over time and by treatment with BP-lowering therapy was assessed. The predictive value of protein levels encoded by candidate genes for subsequent cardiovascular disease was investigated. Eight transcripts (CRIP1, MYADM, TIPARP, TSC22D3, CEBPA, F12, LMNA, and TPPP3) were identified jointly accounting for up to 13% (95% confidence interval, 8.7-16.2) of BP variability. Changes in CRIP1, MYADM, TIPARP, LMNA, TSC22D3, CEBPA, and TPPP3 expression associated with BP changes-among these, CRIP1 gene expression was additionally correlated to measures of cardiac hypertrophy. Assessment of circulating CRIP1 (cystein-rich protein 1) levels as biomarkers showed a strong association with increased risk for incident stroke (hazard ratio, 1.06; 95% confidence interval, 1.03-1.09; P=5.0×10(-5)). Our comprehensive analysis of global gene expression highlights 8 novel transcripts significantly associated with BP, providing a link between gene expression and BP. Translational approaches further established evidence for the potential use of CRIP1 as emerging disease-related biomarker.

Twitter Demographics

The data shown below were collected from the profiles of 9 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 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 44%
Unspecified 3 17%
Student > Bachelor 2 11%
Professor 2 11%
Student > Postgraduate 1 6%
Other 2 11%
Readers by discipline Count As %
Unspecified 7 39%
Biochemistry, Genetics and Molecular Biology 5 28%
Medicine and Dentistry 3 17%
Agricultural and Biological Sciences 2 11%
Social Sciences 1 6%
Other 0 0%

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 31 October 2017.
All research outputs
#2,946,287
of 12,077,989 outputs
Outputs from Hypertension (Highwire)
#1,078
of 4,565 outputs
Outputs of similar age
#78,978
of 267,946 outputs
Outputs of similar age from Hypertension (Highwire)
#29
of 76 outputs
Altmetric has tracked 12,077,989 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 4,565 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. 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 267,946 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 76 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 60% of its contemporaries.