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Genetic architecture of circulating lipid levels

Overview of attention for article published in European Journal of Human Genetics, March 2011
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1 tweeter

Citations

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19 Dimensions

Readers on

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62 Mendeley
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4 CiteULike
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1 Connotea
Title
Genetic architecture of circulating lipid levels
Published in
European Journal of Human Genetics, March 2011
DOI 10.1038/ejhg.2011.21
Pubmed ID
Authors

Ayşe Demirkan, Najaf Amin, Aaron Isaacs, Marjo-Riitta Jarvelin, John B Whitfield, Heinz-Erich Wichmann, Kirsten Ohm Kyvik, Igor Rudan, Christian Gieger, Andrew A Hicks, Åsa Johansson, Jouke-Jan Hottenga, Johannes J Smith, Sarah H Wild, Nancy L Pedersen, Gonneke Willemsen, Massimo Mangino, Caroline Hayward, André G Uitterlinden, Albert Hofman, Jacqueline Witteman, Grant W Montgomery, Kirsi H Pietiläinen, Taina Rantanen, Jaakko Kaprio, Angela Döring, Peter P Pramstaller, Ulf Gyllensten, Eco JC de Geus, Brenda W Penninx, James F Wilson, Fernando Rivadeneria, Patrik KE Magnusson, Dorret I Boomsma, Tim Spector, Harry Campbell, Birgit Hoehne, Nicholas G Martin, Ben A Oostra, Mark McCarthy, Leena Peltonen-Palotie, Yurii Aulchenko, Peter M Visscher, Samuli Ripatti, A Cecile JW Janssens, Cornelia M van Duijn

Abstract

Serum concentrations of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TGs) and total cholesterol (TC) are important heritable risk factors for cardiovascular disease. Although genome-wide association studies (GWASs) of circulating lipid levels have identified numerous loci, a substantial portion of the heritability of these traits remains unexplained. Evidence of unexplained genetic variance can be detected by combining multiple independent markers into additive genetic risk scores. Such polygenic scores, constructed using results from the ENGAGE Consortium GWAS on serum lipids, were applied to predict lipid levels in an independent population-based study, the Rotterdam Study-II (RS-II). We additionally tested for evidence of a shared genetic basis for different lipid phenotypes. Finally, the polygenic score approach was used to identify an alternative genome-wide significance threshold before pathway analysis and those results were compared with those based on the classical genome-wide significance threshold. Our study provides evidence suggesting that many loci influencing circulating lipid levels remain undiscovered. Cross-prediction models suggested a small overlap between the polygenic backgrounds involved in determining LDL-C, HDL-C and TG levels. Pathway analysis utilizing the best polygenic score for TC uncovered extra information compared with using only genome-wide significant loci. These results suggest that the genetic architecture of circulating lipids involves a number of undiscovered variants with very small effects, and that increasing GWAS sample sizes will enable the identification of novel variants that regulate lipid levels.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 2%
United Kingdom 1 2%
United States 1 2%
Unknown 59 95%

Demographic breakdown

Readers by professional status Count As %
Professor 13 21%
Student > Ph. D. Student 13 21%
Researcher 13 21%
Student > Master 5 8%
Professor > Associate Professor 5 8%
Other 12 19%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 44%
Medicine and Dentistry 15 24%
Unspecified 4 6%
Psychology 4 6%
Biochemistry, Genetics and Molecular Biology 3 5%
Other 8 13%
Unknown 1 2%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 June 2011.
All research outputs
#2,897,855
of 3,633,425 outputs
Outputs from European Journal of Human Genetics
#1,069
of 1,254 outputs
Outputs of similar age
#2,149,096
of 2,729,840 outputs
Outputs of similar age from European Journal of Human Genetics
#1,056
of 1,239 outputs
Altmetric has tracked 3,633,425 research outputs across all sources so far. This one is in the 2nd percentile – i.e., 2% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,254 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,239 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.