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Association between osteoprotegerin gene polymorphisms and cardiovascular disease in type 2 diabetic patients

Overview of attention for article published in Genetics and Molecular Biology, May 2013
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Title
Association between osteoprotegerin gene polymorphisms and cardiovascular disease in type 2 diabetic patients
Published in
Genetics and Molecular Biology, May 2013
DOI 10.1590/s1415-47572013005000024
Pubmed ID
Authors

Changlei Guo, Fudong Hu, Shaoli Zhang, Yakun Wang, Hengdao Liu

Abstract

Osteoprotegerin (OPG) gene polymorphisms (T245G, T950C and G1181C) have been associated with osteoporosis and early predictors of cardiovascular disease. The aim of this study was to evaluate whether these polymorphisms contribute to cardiovascular disease (CVD) in type 2 diabetic patients. We performed a case-control study with 178 CVD subjects with diabetes and 312 diabetic patients without CVD to assess the impact of variants of the OPG gene on the risk of CVD. The OPG gene polymorphisms were analyzed by using the polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP). There was no significant association between the T245G and G1181C polymorphisms and CVD in the additive genetic model (OR = 0.96, 95% CI 0.64-1.45, p = 0.79; OR = 1.06, 95% CI 0.81-1.39, p = 0.65, respectively). However, the C allele of the T950C polymorphism was independently associated with a risk of CVD in type 2 diabetic patients in this genetic model (OR = 1.38, 95% CI 1.07-1.80, p = 0.01). This study provides evidence that the C allele of the T950C polymorphism is associated with increased risk of CVD in diabetic patients. However, well-designed prospective studies with a larger sample size are needed to validate these results.

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The data shown below were collected from the profiles of 3 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 27%
Lecturer 2 18%
Unspecified 1 9%
Researcher 1 9%
Professor > Associate Professor 1 9%
Other 0 0%
Unknown 3 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 27%
Medicine and Dentistry 2 18%
Unspecified 1 9%
Unknown 5 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 17 June 2013.
All research outputs
#16,046,765
of 25,373,627 outputs
Outputs from Genetics and Molecular Biology
#344
of 771 outputs
Outputs of similar age
#121,155
of 208,725 outputs
Outputs of similar age from Genetics and Molecular Biology
#3
of 9 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 771 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 51% 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 208,725 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.