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Gene-centric Association Signals for Lipids and Apolipoproteins Identified via the HumanCVD BeadChip

Overview of attention for article published in American Journal of Human Genetics, November 2009
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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 (72nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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8 patents
wikipedia
73 Wikipedia pages

Citations

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180 Dimensions

Readers on

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213 Mendeley
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1 CiteULike
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Title
Gene-centric Association Signals for Lipids and Apolipoproteins Identified via the HumanCVD BeadChip
Published in
American Journal of Human Genetics, November 2009
DOI 10.1016/j.ajhg.2009.10.014
Pubmed ID
Authors

Philippa J. Talmud, Fotios Drenos, Sonia Shah, Tina Shah, Jutta Palmen, Claudio Verzilli, Tom R. Gaunt, Jacky Pallas, Ruth Lovering, Kawah Li, Juan Pablo Casas, Reecha Sofat, Meena Kumari, Santiago Rodriguez, Toby Johnson, Stephen J. Newhouse, Anna Dominiczak, Nilesh J. Samani, Mark Caulfield, Peter Sever, Alice Stanton, Denis C. Shields, on behalf of the ASCOT investigators, Sandosh Padmanabhan, Olle Melander, Claire Hastie, Christian Delles, on behalf of the NORDIL investigators, Shah Ebrahim, Michael G. Marmot, George Davey Smith, Debbie A. Lawlor, Patricia B. Munroe, for the BRIGHT Consortium, Ian N. Day, Mika Kivimaki, John Whittaker, Steve E. Humphries, Aroon D. Hingorani

Abstract

Blood lipids are important cardiovascular disease (CVD) risk factors with both genetic and environmental determinants. The Whitehall II study (n=5592) was genotyped with the gene-centric HumanCVD BeadChip (Illumina). We identified 195 SNPs in 16 genes/regions associated with 3 major lipid fractions and 2 apolipoprotein components at p<10(-5), with the associations being broadly concordant with prior genome-wide analysis. SNPs associated with LDL cholesterol and apolipoprotein B were located in LDLR, PCSK9, APOB, CELSR2, HMGCR, CETP, the TOMM40-APOE-C1-C2-C4 cluster, and the APOA5-A4-C3-A1 cluster; SNPs associated with HDL cholesterol and apolipoprotein AI were in CETP, LPL, LIPC, APOA5-A4-C3-A1, and ABCA1; and SNPs associated with triglycerides in GCKR, BAZ1B, MLXIPL, LPL, and APOA5-A4-C3-A1. For 48 SNPs in previously unreported loci that were significant at p<10(-4) in Whitehall II, in silico analysis including the British Women's Heart and Health Study, BRIGHT, ASCOT, and NORDIL studies (total n>12,500) revealed previously unreported associations of SH2B3 (p<2.2x10(-6)), BMPR2 (p<2.3x10(-7)), BCL3/PVRL2 (flanking APOE; p<4.4x10(-8)), and SMARCA4 (flanking LDLR; p<2.5x10(-7)) with LDL cholesterol. Common alleles in these genes explained 6.1%-14.7% of the variance in the five lipid-related traits, and individuals at opposite tails of the additive allele score exhibited substantial differences in trait levels (e.g., >1 mmol/L in LDL cholesterol [approximately 1 SD of the trait distribution]). These data suggest that multiple common alleles of small effect can make important contributions to individual differences in blood lipids potentially relevant to the assessment of CVD risk. These genes provide further insights into lipid metabolism and the likely effects of modifying the encoded targets therapeutically.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 213 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
United Kingdom 3 1%
Netherlands 2 <1%
France 1 <1%
Spain 1 <1%
Switzerland 1 <1%
Unknown 200 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 48 23%
Student > Ph. D. Student 46 22%
Student > Bachelor 16 8%
Professor 15 7%
Professor > Associate Professor 13 6%
Other 47 22%
Unknown 28 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 58 27%
Medicine and Dentistry 42 20%
Biochemistry, Genetics and Molecular Biology 40 19%
Computer Science 8 4%
Chemistry 4 2%
Other 23 11%
Unknown 38 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 19 December 2023.
All research outputs
#5,446,994
of 25,374,647 outputs
Outputs from American Journal of Human Genetics
#2,421
of 5,879 outputs
Outputs of similar age
#21,645
of 108,542 outputs
Outputs of similar age from American Journal of Human Genetics
#21
of 41 outputs
Altmetric has tracked 25,374,647 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 5,879 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.3. This one has gotten more attention than average, scoring higher than 52% 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 108,542 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 72% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.