Title |
Associations of estradiol levels and genetic polymorphisms of inflammatory genes with the risk of ischemic stroke
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Published in |
Journal of Biomedical Science, March 2017
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DOI | 10.1186/s12929-017-0332-1 |
Pubmed ID | |
Authors |
Yi-Chen Hsieh, Fang-I Hsieh, Yih-Ru Chen, Chaur-Jong Hu, Jiann-Shing Jeng, Sung-Chun Tang, Nai-Fang Chi, Huey-Juan Lin, Li-Ming Lien, Giia-Sheun Peng, Hung-Yi Chiou, for the Formosa Stroke Genetic Consortium (FSGC) |
Abstract |
Estrogen plays an important role as an anti-inflammatory and neuroprotective agent in ischemic stroke. In this study, we analyzed the effect of a polygenic risk score (PRS) constructed using inflammatory genes and estradiol levels on the risk of ischemic stroke. This case-control study was conducted with 624 ischemic stroke patients and 624 age- and gender-matched controls. The PRS estimated the polygenic contribution of inflammatory genes from ischemic stroke susceptibility loci. Estradiol levels were measured using a radioimmunoassay. High and low estradiol levels were defined according to the log-transformed median estradiol levels in female and male controls. Subjects in the fourth quartile of the PRS had a significant 1.57-fold risk of ischemic stroke (95% confidence interval [CI], 1.12 ~ 2.19), after adjusting for covariates compared to individuals in the lowest quartile. Compared to individuals with high estradiol levels and a low PRS as the reference group, those exposed to low estradiol levels and a high PRS had an increased risk of ischemic stroke (odds ratio, 3.35; 95% CI, 1.79 ~ 6.28). Similar results were also observed in males when the analysis was stratified by gender. Our data suggest that the PRS can be useful in evaluating a high risk of ischemic stroke among patients, especially those exposed to low estradiol levels. |
X Demographics
Geographical breakdown
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United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 24 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 4 | 17% |
Student > Bachelor | 3 | 13% |
Professor | 3 | 13% |
Student > Ph. D. Student | 3 | 13% |
Professor > Associate Professor | 2 | 8% |
Other | 3 | 13% |
Unknown | 6 | 25% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 6 | 25% |
Medicine and Dentistry | 4 | 17% |
Neuroscience | 3 | 13% |
Agricultural and Biological Sciences | 1 | 4% |
Psychology | 1 | 4% |
Other | 1 | 4% |
Unknown | 8 | 33% |