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Lipidomic analysis of variation in response to simvastatin in the Cholesterol and Pharmacogenetics Study

Overview of attention for article published in Metabolomics, April 2010
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

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20 patents
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2 Wikipedia pages

Citations

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96 Dimensions

Readers on

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117 Mendeley
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Title
Lipidomic analysis of variation in response to simvastatin in the Cholesterol and Pharmacogenetics Study
Published in
Metabolomics, April 2010
DOI 10.1007/s11306-010-0207-x
Pubmed ID
Authors

Rima Kaddurah-Daouk, Rebecca A. Baillie, Hongjie Zhu, Zhao-Bang Zeng, Michelle M. Wiest, Uyen Thao Nguyen, Steven M. Watkins, Ronald M. Krauss

Abstract

Statins are commonly used for reducing cardiovascular disease risk but therapeutic benefit and reductions in levels of low-density lipoprotein cholesterol (LDL-C) vary among individuals. Other effects, including reductions in C-reactive protein (CRP), also contribute to treatment response. Metabolomics provides powerful tools to map pathways implicated in variation in response to statin treatment. This could lead to mechanistic hypotheses that provide insight into the underlying basis for individual variation in drug response. Using a targeted lipidomics platform, we defined lipid changes in blood samples from the upper and lower tails of the LDL-C response distribution in the Cholesterol and Pharmacogenetics study. Metabolic changes in responders are more comprehensive than those seen in non-responders. Baseline cholesterol ester and phospholipid metabolites correlated with LDL-C response to treatment. CRP response to therapy correlated with baseline plasmalogens, lipids involved in inflammation. There was no overlap of lipids whose changes correlated with LDL-C or CRP responses to simvastatin suggesting that distinct metabolic pathways govern statin effects on these two biomarkers. Metabolic signatures could provide insights about variability in response and mechanisms of action of statins. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-010-0207-x) contains supplementary material, which is available to authorized users.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 3%
United Kingdom 2 2%
Czechia 1 <1%
Germany 1 <1%
Mexico 1 <1%
South Africa 1 <1%
Unknown 108 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 40 34%
Student > Ph. D. Student 21 18%
Other 10 9%
Student > Master 8 7%
Professor 6 5%
Other 21 18%
Unknown 11 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 29%
Medicine and Dentistry 25 21%
Biochemistry, Genetics and Molecular Biology 13 11%
Chemistry 9 8%
Pharmacology, Toxicology and Pharmaceutical Science 8 7%
Other 14 12%
Unknown 14 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 23 March 2021.
All research outputs
#1,998,153
of 22,790,780 outputs
Outputs from Metabolomics
#87
of 1,295 outputs
Outputs of similar age
#7,404
of 95,618 outputs
Outputs of similar age from Metabolomics
#1
of 5 outputs
Altmetric has tracked 22,790,780 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,295 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 93% 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 95,618 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them