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Associations of the hypertension-related single nucleotide polymorphism rs11191548 with high-density lipoprotein cholesterol and leptin in Chinese children

Overview of attention for article published in BMC Medical Genomics, January 2018
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Title
Associations of the hypertension-related single nucleotide polymorphism rs11191548 with high-density lipoprotein cholesterol and leptin in Chinese children
Published in
BMC Medical Genomics, January 2018
DOI 10.1186/s12881-018-0523-y
Pubmed ID
Authors

Lijun Wu, Liwang Gao, Xiaoyuan Zhao, Meixian Zhang, Jianxin Wu, Jie Mi

Abstract

The genome-wide association study has founded hypertension-related single nucleotide polymorphism (SNP) rs11191548 near CYP17A1 encoding a key enzyme involved in steroid metabolism, but the molecular mechanisms are not understood and the associations of the SNP with hypertension-related traits are not fully described, especially in children. The aim of the present study is to investigate the associations between the SNP and two hypertension-related traits, lipids and leptin. We genotyped the SNP in Beijing Child and Adolescent Metabolic Syndrome (BCAMS) study. A total of 3503 children participated in the study. The SNP rs11191548 was significantly associated with high-density lipoprotein cholesterol (HDL) (P = 0.014 and 0.028, respectively) and leptin (P = 0.011 and 0.026, respectively) under an additive model after adjustment for age, gender, and systolic blood pressure (SBP) or diastolic blood pressure (DBP). There was a statistically significant association of rs11191548 with high leptin after adjustment for age, gender, and SBP or DBP. The P-values remain significant after correction for multiple testing. We demonstrate for the first time that the SNP rs11191548 near CYP17A1 is associated with HDL and leptin in Chinese children. These novel findings provide important evidence that HDL and leptin maybe possibly mediate the process of CYP17A1 involved in hypertension.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 17%
Student > Master 4 17%
Student > Postgraduate 2 9%
Professor > Associate Professor 2 9%
Student > Ph. D. Student 2 9%
Other 3 13%
Unknown 6 26%
Readers by discipline Count As %
Medicine and Dentistry 7 30%
Biochemistry, Genetics and Molecular Biology 3 13%
Pharmacology, Toxicology and Pharmaceutical Science 2 9%
Agricultural and Biological Sciences 2 9%
Nursing and Health Professions 1 4%
Other 2 9%
Unknown 6 26%
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 18 January 2018.
All research outputs
#20,663,600
of 25,382,440 outputs
Outputs from BMC Medical Genomics
#1,682
of 2,444 outputs
Outputs of similar age
#345,294
of 451,641 outputs
Outputs of similar age from BMC Medical Genomics
#35
of 56 outputs
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