ESR1 gene polymorphisms PvuII (rs2234693T&gt;C) and XbaI (rs9340799A&gt;G) may not be directly correlated with cardiovascular disease risk

Jiang, Ning; Yang, Guang; Peng, C.L.

doi:10.4238/2015.october.29.14

Cited by 8 publications

(10 citation statements)

References 38 publications

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“…Meta-analyses that combine the results of single-gene association studies provide an opportunity to obtain more robust effect sizes. In the last decade, meta-analyses were related to atrial fibrillation, MRI-defined brain infarct, ischemic stroke, and susceptibility to any type of atherosclerotic CVD, such as coronary artery disease, acute coronary syndrome, or ischemic heart diseases ( 129 – 135 ). It is worth mentioning that meta-analyses may be biased: publication bias, population stratification, control selection bias, and lack of genotype blinding exist, thus results should be interpreted with caution.…”

Section: Resultsmentioning

confidence: 99%

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

Fiatal

Ádány

2018

Front. Public Health

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BackgroundAlthough 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.MethodsSeveral 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.”ResultsThe 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.ConclusionCurrently, 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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Section: Resultsmentioning

confidence: 99%

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

Fiatal

Ádány

2018

Front. Public Health

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“…For example, ESR1, an essential member of the nuclear hormone receptor super family, plays significant roles in vascular wall physiology and function (Gao et al, 2014). ESR1 is also involved in pathological processes including breast cancer, endometrial cancer, and diabetes (Jiang et al, 2015). Single-nucleotide polymorphisms in the ESR1 gene were related to hypertension, CAD, and diabetes (Jiang et al, 2015).…”

Section: Network Analysis Identifies Common Genes Associated With Obementioning

confidence: 99%

“…ESR1 is also involved in pathological processes including breast cancer, endometrial cancer, and diabetes (Jiang et al, 2015). Single-nucleotide polymorphisms in the ESR1 gene were related to hypertension, CAD, and diabetes (Jiang et al, 2015). Previous studies showed that ESR1 polymorphisms PvuII (rs2234693T>C) and XbaI (rs9340799A>G) predicted the risk of CVD (Jiang et al, 2015).…”

Section: Network Analysis Identifies Common Genes Associated With Obementioning

confidence: 99%

“…Single-nucleotide polymorphisms in the ESR1 gene were related to hypertension, CAD, and diabetes (Jiang et al, 2015). Previous studies showed that ESR1 polymorphisms PvuII (rs2234693T>C) and XbaI (rs9340799A>G) predicted the risk of CVD (Jiang et al, 2015). In hypogonadal men, the rs2207396 variant in ESR1 gene was strongly correlated with diabetes susceptibility (Linnér et al, 2013).…”

Section: Network Analysis Identifies Common Genes Associated With Obementioning

confidence: 99%

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Network analysis identifies common genes associated with obesity in six obesity-related diseases

Wang

Wnag

et al. 2017

J. Zhejiang Univ. Sci. B

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Obesity has been reported to be associated with many diseases. However, common obesity-induced biological processes have not been evaluated across these diseases. We identified genes associated with obesity and obesity-related diseases, and used them to construct protein‒protein interaction networks. We also analyzed gene ontology (GO) in those genes overlapping between obesity and disease. Our work identifies gene modules common to obesity and obesity-related diseases, which can provide a basis for understanding the process of how obesity induces disease.

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“…However, single nucleotide polymorphisms (SNPs) in ESRα are considerably different in populations belonging to different ethnicities and geographical locations; therefore, the results of domestic and international studies, and even those conducted in populations from various geographic regions belonging to the same ethnic group, are quite inconsistent. Recently, Jiang et al (2015) conducted a meta-analysis to determine the correlation between ESRα polymorphisms and cardiovascular disease (CVD) and reported that the two were not associated. Therefore, the association between ESRα polymorphisms and CVD remains to be elucidated.…”

Section: Introductionmentioning

confidence: 99%

Correlation between polymorphisms in the estrogen receptor α gene and coronary heart disease: A meta-analysis

Zhou

Chen

2016

Genet. Mol. Res.

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ABSTRACT. The aim of this study was to conduct a systematic evaluation the correlation between polymorphisms in the estrogen receptor α gene (ESRα) and coronary heart disease susceptibility. Casecontrol studies until August 2015 analyzing the correlation between the ESRα PvuII T/C polymorphism and coronary heart disease were obtained from various electronic databases (CBM, CNKI, Wanfang Data, VIP, and MEDLINE, Cochrane Library, Embase, Springer, and Ovid. The data obtained from these studies were evaluated and valid data was extracted. A meta-analysis was performed using RevMan 5.0. Eleven cases, comprising 1742 patients with coronary heart disease and 2012 controls, that conformed to the inclusion criteria set in this study were extracted. The results of our meta-analysis indicated that the C and T alleles, the TC+CC and TT genotypes, and the CC and TT+TC genotypes did not differ significantly. The results of this meta-analysis confirmed that there was no correlation between polymorphisms in ESRα and coronary heart disease susceptibility in the Chinese population.

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ESR1 gene polymorphisms PvuII (rs2234693T>C) and XbaI (rs9340799A>G) may not be directly correlated with cardiovascular disease risk

Cited by 8 publications

References 38 publications

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

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

Network analysis identifies common genes associated with obesity in six obesity-related diseases

Correlation between polymorphisms in the estrogen receptor α gene and coronary heart disease: A meta-analysis

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