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Current Applications of Genetic Risk Scores to Cardiovascular Outcomes and Subclinical Phenotypes

Overview of attention for article published in Current Epidemiology Reports, July 2015
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Title
Current Applications of Genetic Risk Scores to Cardiovascular Outcomes and Subclinical Phenotypes
Published in
Current Epidemiology Reports, July 2015
DOI 10.1007/s40471-015-0046-4
Pubmed ID
Authors

Jennifer A. Smith, Erin B. Ware, Pooja Middha, Lisa Beacher, Sharon L. R. Kardia

Abstract

Genetic risk scores are a useful tool for examining the cumulative predictive ability of genetic variation on cardiovascular disease. Important considerations for creating genetic risk scores include the choice of genetic variants, weighting, and comparability across ethnicities. Genetic risk scores that use information from genome-wide meta-analyses can successfully predict cardiovascular outcomes and subclinical phenotypes, yet there is limited clinical utility of these scores beyond traditional cardiovascular risk factors in many populations. Novel uses of genetic risk scores include evaluating the genetic contribution of specific intermediate traits or risk factors to cardiovascular disease, risk prediction in high-risk populations, gene-by-environment interaction studies, and Mendelian randomization studies. Though questions remain about the ultimate clinical utility of the genetic risk score, further investigation in high-risk populations and new ways to combine genetic risk scores with traditional risk factors may prove to be fruitful.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 <1%
Uruguay 1 <1%
Unknown 111 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 21%
Researcher 17 15%
Student > Master 14 12%
Student > Bachelor 13 12%
Student > Postgraduate 10 9%
Other 27 24%
Unknown 8 7%
Readers by discipline Count As %
Medicine and Dentistry 40 35%
Biochemistry, Genetics and Molecular Biology 19 17%
Agricultural and Biological Sciences 18 16%
Nursing and Health Professions 7 6%
Computer Science 6 5%
Other 10 9%
Unknown 13 12%
Attention Score in Context

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 30 June 2015.
All research outputs
#15,851,587
of 23,552,911 outputs
Outputs from Current Epidemiology Reports
#1
of 1 outputs
Outputs of similar age
#155,926
of 264,876 outputs
Outputs of similar age from Current Epidemiology Reports
#1
of 1 outputs
Altmetric has tracked 23,552,911 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
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