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Application of Single-Nucleotide Polymorphism-Related Risk Estimates in Identification of Increased Genetic Susceptibility to Cardiovascular Diseases: A Literature Review

Overview of attention for article published in Frontiers in Public Health, January 2018
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Title
Application of Single-Nucleotide Polymorphism-Related Risk Estimates in Identification of Increased Genetic Susceptibility to Cardiovascular Diseases: A Literature Review
Published in
Frontiers in Public Health, January 2018
DOI 10.3389/fpubh.2017.00358
Pubmed ID
Authors

Szilvia Fiatal, Róza Ádány

Abstract

Although largely preventable, cardiovascular diseases (CVDs) are the biggest cause of death worldwide. Common complex cardiovascular disorders (e.g., coronary heart disease, hypertonia, or thrombophilia) result from a combination of genetic alterations and environmental factors. Recent advances in the genomics of CVDs have fostered huge expectations about future use of susceptibility variants for prevention, diagnosis, and treatment. Our aim was to summarize the latest developments in the field from a public health perspective focusing on the applicability of data on single-nucleotide polymorphisms (SNPs), through a systematic review of studies from the last decade on genetic risk estimating for common CVDs. Several keywords were used for searching the PubMed, Embase, CINAHL, and Web of Science databases. Recent advances were summarized and structured according to the main public health domains (prevention, early detection, and treatment) using a framework suggested recently for translational research. This framework includes four recommended phases: "T1. From gene discovery to candidate health applications; T2. From health application to evidence-based practice guidelines; T3. From evidence-based practice guidelines to health practice; and T4. From practice to population health impacts." The majority of translation research belongs to the T1 phase "translation of basic genetic/genomic research into health application"; there are only a few population-based impacts estimated. The studies suggest that an SNP is a poor estimator of individual risk, whereas an individual's genetic profile combined with non-genetic risk factors may better predict CVD risk among certain patient subgroups. Further research is needed to validate whether these genomic profiles can prospectively identify individuals at risk to develop CVDs. Several research gaps were identified: little information is available on studies suggesting "Health application to evidence-based practice guidelines"; no study is available on "Guidelines to health practice." It was not possible to identify studies that incorporate environmental or lifestyle factors in the risk estimation. Currently, identifying populations having a larger risk of developing common CVDs may result in personalized prevention programs by reducing people's risk of onset or disease progression. However, limited evidence is available on the application of genomic results in health and public health practice.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 13 19%
Student > Master 10 14%
Student > Ph. D. Student 8 12%
Student > Postgraduate 5 7%
Researcher 5 7%
Other 7 10%
Unknown 21 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 19%
Medicine and Dentistry 7 10%
Nursing and Health Professions 4 6%
Agricultural and Biological Sciences 3 4%
Social Sciences 3 4%
Other 14 20%
Unknown 25 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 April 2022.
All research outputs
#7,297,728
of 23,020,670 outputs
Outputs from Frontiers in Public Health
#2,407
of 10,275 outputs
Outputs of similar age
#149,937
of 440,194 outputs
Outputs of similar age from Frontiers in Public Health
#49
of 99 outputs
Altmetric has tracked 23,020,670 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 10,275 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 10.0. 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 440,194 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 65% of its contemporaries.
We're also able to compare this research output to 99 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.