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Blood Pressure Loci Identified with a Gene-Centric Array

Overview of attention for article published in American Journal of Human Genetics, December 2011
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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 (77th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

3 tweeters
1 Facebook page
1 Wikipedia page


120 Dimensions

Readers on

131 Mendeley
3 CiteULike
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Blood Pressure Loci Identified with a Gene-Centric Array
Published in
American Journal of Human Genetics, December 2011
DOI 10.1016/j.ajhg.2011.10.013
Pubmed ID

Toby Johnson, Tom R. Gaunt, Stephen J. Newhouse, Sandosh Padmanabhan, Maciej Tomaszewski, Meena Kumari, Richard W. Morris, Ioanna Tzoulaki, Eoin T. O'Brien, Neil R. Poulter, Peter Sever, Denis C. Shields, Simon Thom, Sasiwarang G. Wannamethee, Peter H. Whincup, Morris J. Brown, John M. Connell, Richard J. Dobson, Philip J. Howard, Charles A. Mein, Abiodun Onipinla, Sue Shaw-Hawkins, Yun Zhang, George Davey Smith, Ian N.M. Day, Debbie A. Lawlor, Alison H. Goodall, F. Gerald Fowkes, Gonçalo R. Abecasis, Paul Elliott, Vesela Gateva, Peter S. Braund, Paul R. Burton, Christopher P. Nelson, Martin D. Tobin, Pim van der Harst, Nicola Glorioso, Hani Neuvrith, Erika Salvi, Jan A. Staessen, Andrea Stucchi, Nabila Devos, Xavier Jeunemaitre, Pierre-François Plouin, Jean Tichet, Peeter Juhanson, Elin Org, Margus Putku, Siim Sõber, Gudrun Veldre, Margus Viigimaa, Anna Levinsson, Annika Rosengren, Dag S. Thelle, Claire E. Hastie, Thomas Hedner, Wai K. Lee, Olle Melander, Björn Wahlstrand, Rebecca Hardy, Andrew Wong, Jackie A. Cooper, Jutta Palmen, Li Chen, Alexandre F.R. Stewart, George A. Wells, Harm-Jan Westra, Marcel G.M. Wolfs, Robert Clarke, Maria Grazia Franzosi, Anuj Goel, Anders Hamsten, Mark Lathrop, John F. Peden, Udo Seedorf, Hugh Watkins, Willem H. Ouwehand, Jennifer Sambrook, Jonathan Stephens, Juan-Pablo Casas, Fotios Drenos, Michael V. Holmes, Mika Kivimaki, Sonia Shah, Tina Shah, Philippa J. Talmud, John Whittaker, Chris Wallace, Christian Delles, Maris Laan, Diana Kuh, Steve E. Humphries, Fredrik Nyberg, Daniele Cusi, Robert Roberts, Christopher Newton-Cheh, Lude Franke, Alice V. Stanton, Anna F. Dominiczak, Martin Farrall, Aroon D. Hingorani, Nilesh J. Samani, Mark J. Caulfield, Patricia B. Munroe


Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
United Kingdom 2 2%
South Africa 1 <1%
Iran, Islamic Republic of 1 <1%
Sweden 1 <1%
Colombia 1 <1%
Unknown 122 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 24%
Student > Ph. D. Student 25 19%
Student > Master 14 11%
Student > Bachelor 11 8%
Unspecified 11 8%
Other 38 29%
Readers by discipline Count As %
Medicine and Dentistry 46 35%
Agricultural and Biological Sciences 39 30%
Unspecified 16 12%
Biochemistry, Genetics and Molecular Biology 11 8%
Mathematics 4 3%
Other 15 11%

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 08 December 2011.
All research outputs
of 12,272,424 outputs
Outputs from American Journal of Human Genetics
of 4,376 outputs
Outputs of similar age
of 234,577 outputs
Outputs of similar age from American Journal of Human Genetics
of 34 outputs
Altmetric has tracked 12,272,424 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 4,376 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.3. This one has gotten more attention than average, scoring higher than 54% 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 234,577 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 34 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 52% of its contemporaries.