You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci
|
|---|---|
| Published in |
American Journal of Human Genetics, October 2012
|
| DOI | 10.1016/j.ajhg.2012.08.032 |
| Pubmed ID | |
| Authors |
Folkert W. Asselbergs, Yiran Guo, Erik P.A. van Iperen, Suthesh Sivapalaratnam, Vinicius Tragante, Matthew B. Lanktree, Leslie A. Lange, Berta Almoguera, Yolande E. Appelman, John Barnard, Jens Baumert, Amber L. Beitelshees, Tushar R. Bhangale, Yii-Der Ida Chen, Tom R. Gaunt, Yan Gong, Jemma C. Hopewell, Toby Johnson, Marcus E. Kleber, Taimour Y. Langaee, Mingyao Li, Yun R. Li, Kiang Liu, Caitrin W. McDonough, Matthijs F.L. Meijs, Rita P.S. Middelberg, Kiran Musunuru, Christopher P. Nelson, Jeffery R. O’Connell, Sandosh Padmanabhan, James S. Pankow, Nathan Pankratz, Suzanne Rafelt, Ramakrishnan Rajagopalan, Simon P.R. Romaine, Nicholas J. Schork, Jonathan Shaffer, Haiqing Shen, Erin N. Smith, Sam E. Tischfield, Peter J. van der Most, Jana V. van Vliet-Ostaptchouk, Niek Verweij, Kelly A. Volcik, Li Zhang, Kent R. Bailey, Kristian M. Bailey, Florianne Bauer, Jolanda M.A. Boer, Peter S. Braund, Amber Burt, Paul R. Burton, Sarah G. Buxbaum, Wei Chen, Rhonda M. Cooper-DeHoff, L. Adrienne Cupples, Jonas S. deJong, Christian Delles, David Duggan, Myriam Fornage, Clement E. Furlong, Nicole Glazer, John G. Gums, Claire Hastie, Michael V. Holmes, Thomas Illig, Susan A. Kirkland, Mika Kivimaki, Ronald Klein, Barbara E. Klein, Charles Kooperberg, Kandice Kottke-Marchant, Meena Kumari, Andrea Z. LaCroix, Laya Mallela, Gurunathan Murugesan, Jose Ordovas, Willem H. Ouwehand, Wendy S. Post, Richa Saxena, Hubert Scharnagl, Pamela J. Schreiner, Tina Shah, Denis C. Shields, Daichi Shimbo, Sathanur R. Srinivasan, Ronald P. Stolk, Daniel I. Swerdlow, Herman A. Taylor, Eric J. Topol, Elina Toskala, Joost L. van Pelt, Jessica van Setten, Salim Yusuf, John C. Whittaker, A.H. Zwinderman, LifeLines Cohort Study, Sonia S. Anand, Anthony J. Balmforth, Gerald S. Berenson, Connie R. Bezzina, Bernhard O. Boehm, Eric Boerwinkle, Juan P. Casas, Mark J. Caulfield, Robert Clarke, John M. Connell, Karen J. Cruickshanks, Karina W. Davidson, Ian N.M. Day, Paul I.W. de Bakker, Pieter A. Doevendans, Anna F. Dominiczak, Alistair S. Hall, Catharina A. Hartman, Christian Hengstenberg, Hans L. Hillege, Marten H. Hofker, Steve E. Humphries, Gail P. Jarvik, Julie A. Johnson, Bernhard M. Kaess, Sekar Kathiresan, Wolfgang Koenig, Debbie A. Lawlor, Winfried März, Olle Melander, Braxton D. Mitchell, Grant W. Montgomery, Patricia B. Munroe, Sarah S. Murray, Stephen J. Newhouse, N. Charlotte Onland-Moret, Neil Poulter, Bruce Psaty, Susan Redline, Stephen S. Rich, Jerome I. Rotter, Heribert Schunkert, Peter Sever, Alan R. Shuldiner, Roy L. Silverstein, Alice Stanton, Barbara Thorand, Mieke D. Trip, Michael Y. Tsai, Pim van der Harst, Ellen van der Schoot, Yvonne T. van der Schouw, W.M. Monique Verschuren, Hugh Watkins, Arthur A.M. Wilde, Bruce H.R. Wolffenbuttel, John B. Whitfield, G. Kees Hovingh, Christie M. Ballantyne, Cisca Wijmenga, Muredach P. Reilly, Nicholas G. Martin, James G. Wilson, Daniel J. Rader, Nilesh J. Samani, Alex P. Reiner, Robert A. Hegele, John J.P. Kastelein, Aroon D. Hingorani, Philippa J. Talmud, Hakon Hakonarson, Clara C. Elbers, Brendan J. Keating, Fotios Drenos |
| Abstract |
Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids. |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 3 | 20% |
| United States | 3 | 20% |
| Peru | 1 | 7% |
| Grenada | 1 | 7% |
| Italy | 1 | 7% |
| Canada | 1 | 7% |
| Unknown | 5 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 53% |
| Scientists | 4 | 27% |
| Science communicators (journalists, bloggers, editors) | 2 | 13% |
| Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 273 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 1% |
| United Kingdom | 2 | <1% |
| France | 1 | <1% |
| Netherlands | 1 | <1% |
| Sweden | 1 | <1% |
| Unknown | 265 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 69 | 25% |
| Student > Ph. D. Student | 35 | 13% |
| Professor | 24 | 9% |
| Student > Master | 22 | 8% |
| Other | 20 | 7% |
| Other | 67 | 25% |
| Unknown | 36 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 63 | 23% |
| Agricultural and Biological Sciences | 59 | 22% |
| Biochemistry, Genetics and Molecular Biology | 55 | 20% |
| Computer Science | 11 | 4% |
| Psychology | 5 | 2% |
| Other | 24 | 9% |
| Unknown | 56 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 28 June 2015.
All research outputs
#2,688,339
of 25,837,817 outputs
Outputs from American Journal of Human Genetics
#1,443
of 5,955 outputs
Outputs of similar age
#18,667
of 194,118 outputs
Outputs of similar age from American Journal of Human Genetics
#13
of 60 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,955 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.5. This one has done well, scoring higher than 75% 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 194,118 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 89% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.