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Joint associations of folate, homocysteine and MTHFR, MTR and MTRR gene polymorphisms with dyslipidemia in a Chinese hypertensive population: a cross-sectional study

Overview of attention for article published in Lipids in Health and Disease, September 2015
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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 (77th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

blogs
1 blog

Citations

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21 Dimensions

Readers on

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45 Mendeley
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Title
Joint associations of folate, homocysteine and MTHFR, MTR and MTRR gene polymorphisms with dyslipidemia in a Chinese hypertensive population: a cross-sectional study
Published in
Lipids in Health and Disease, September 2015
DOI 10.1186/s12944-015-0099-x
Pubmed ID
Authors

Wen-Xing Li, Wen-Wen Lv, Shao-Xing Dai, Ming-Luo Pan, Jing-Fei Huang

Abstract

Dyslipidemia is a well-established risk factor for cardiovascular disease. Serum lipids were affected by several gene polymorphisms, folate, homocysteine and other metabolite levels. We aim to investigate the effects of homocysteine metabolism enzyme polymorphisms (MTHTR C677T, MTHFR A1298C, MTR A2756G and MTRR A66G) and their interactions with folate, homocysteine on serum lipid levels in Chinese patients with hypertension. Participants were 480 hypertensive adults that enrolled in September to December 2005 from six different Chinese hospitals (Harbin, Shanghai, Shenyang, Beijing, Xi'an, and Nanjing). Known MTHFR C677T, MTHFR A1298C, MTR A2756G and MTRR A66G genotypes were determined by PCR-RFLP methods. Serum folate was measured by chemiluminescent immunoassay, homocysteine was measured by high-performance liquid chromatography, serum lipids parameters were determined by an automatic biochemistry analyzer, low-density lipoprotein was calculated by Friedewald's equation. Unitary linear regression model was used to assess the associations of gene polymorphisms, folate and homocysteine on serum lipid profiles. Unconditional logistic regression model was applied to test the interactions of folate, homocysteine and gene polymorphisms on dyslipidemia. No correlations between gene polymorphisms and homocysteine on serum lipid profiles. Compared with normal folate patients, patients with low folate showed higher odds of hypertriglyceridemia (OR = 2.02, 95 % CI: 1.25-3.25, P = 0.004) and low levels of high-density lipoprotein cholesterol (OR = 1.88, 95 % CI: 1.07-3.28, P = 0.027). Each of four gene polymorphisms (MTHTR C677T, MTHFR A1298C, MTR A2756G and MTRR A66G) combined with low folate showed higher odds of hypertriglyceridemia (P for trend: 0.049, 0.004, 0.007 and 0.005, respectively). MTHFR C677T and A1298C with low folate showed higher odds of low levels of high-density lipoprotein cholesterol (P for trend: 0.008 and 0.031). Low folate status and homocysteine metabolism gene polymorphisms (MTHTR C677T, MTHFR A1298C, MTR A2756G and MTRR A66G) may have a synergistic effect increased the incidence of dyslipidemia in Chinese hypertensive population.

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 20%
Researcher 6 13%
Student > Master 6 13%
Student > Postgraduate 4 9%
Student > Doctoral Student 4 9%
Other 10 22%
Unknown 6 13%
Readers by discipline Count As %
Medicine and Dentistry 12 27%
Nursing and Health Professions 6 13%
Biochemistry, Genetics and Molecular Biology 5 11%
Agricultural and Biological Sciences 5 11%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Other 5 11%
Unknown 9 20%

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 08 September 2015.
All research outputs
#1,012,165
of 6,305,233 outputs
Outputs from Lipids in Health and Disease
#100
of 585 outputs
Outputs of similar age
#43,969
of 195,065 outputs
Outputs of similar age from Lipids in Health and Disease
#5
of 32 outputs
Altmetric has tracked 6,305,233 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 585 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 82% 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 195,065 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.