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Interaction between polyphenols intake and PON1 gene variants on markers of cardiovascular disease: a nutrigenetic observational study

Overview of attention for article published in Journal of Translational Medicine, June 2016
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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 (73rd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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Title
Interaction between polyphenols intake and PON1 gene variants on markers of cardiovascular disease: a nutrigenetic observational study
Published in
Journal of Translational Medicine, June 2016
DOI 10.1186/s12967-016-0941-6
Pubmed ID
Authors

Federica Rizzi, Costanza Conti, Elena Dogliotti, Annalisa Terranegra, Erika Salvi, Daniele Braga, Flavia Ricca, Sara Lupoli, Alessandra Mingione, Francesca Pivari, Caterina Brasacchio, Matteo Barcella, Martina Chittani, Francesca D’Avila, Maurizio Turiel, Monica Lazzaroni, Laura Soldati, Daniele Cusi, Cristina Barlassina

Abstract

Paraoxonase 1 (PON1) gene polymorphisms and polyphenols intake have been reported independently associated to lipid profile and susceptibility to atherosclerosis and cardiovascular disease. However, the interaction between these factors remains to be investigated. We performed an observational nutrigenetic study to examine whether the interaction between polyphenols and anthocyanins intake and PON1 genetic variants can modulate biomarkers of cardiovascular health in an Italian healthy population. We recruited 443 healthy volunteers who participated in the EC funded ATHENA project (AnThocyanin and polyphenols bioactive for Health Enhancement through Nutritional Advancement). Data collection included detailed demographic, clinical, dietary, lifestyle, biochemical and genetic data. Polyphenols and anthocyanins intake was measured by 24 h dietary recall repeated three times a year in order to get seasonal variations. We tested the interaction between 18 independent tagging SNPs in PON1 gene and polyphenols intake on HDL, LDL, cholesterol, triglycerides and atherogenic index of plasma. Without considering the genetic background, we could not observe significant differences in the lipid profile between high and low polyphenols and anthocyanins intake. Using a nutrigenetic approach, we identified protective genotypes in four independent polymorphisms that, at Bonferroni level (p ≤ 0.0028), present a significant association with increased HDL level under high polyphenols and anthocyanins intake, compared to risk genotypes (rs854549, Beta = 4.7 per C allele; rs854552, Beta = 5.6 per C allele; rs854571, Beta = 3.92 per T allele; rs854572, Beta = 3.94 per C allele). We highlight the protective role of genetic variants in PON1 towards cardiovascular risk under high polyphenols and anthocyanins consumption. PON1 variants could represent novel biomarkers to stratify individuals who might benefit from targeted dietary recommendation for health promotion and strategies of preventive medicine.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 1 1%
Unknown 76 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 17%
Student > Bachelor 11 14%
Researcher 10 13%
Student > Ph. D. Student 10 13%
Student > Postgraduate 7 9%
Other 11 14%
Unknown 15 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 19%
Medicine and Dentistry 13 17%
Nursing and Health Professions 8 10%
Agricultural and Biological Sciences 6 8%
Pharmacology, Toxicology and Pharmaceutical Science 3 4%
Other 13 17%
Unknown 19 25%
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 27 January 2023.
All research outputs
#5,764,180
of 23,622,736 outputs
Outputs from Journal of Translational Medicine
#904
of 4,189 outputs
Outputs of similar age
#92,944
of 355,067 outputs
Outputs of similar age from Journal of Translational Medicine
#19
of 110 outputs
Altmetric has tracked 23,622,736 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 4,189 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done well, scoring higher than 78% 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 355,067 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 73% of its contemporaries.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.