To analyze the relationship between renin-angiotensin-aldosterone system (RAAS) gene polymorphisms and susceptibility to essential hypertension (EH) in military secret service personnel. In October 2019, military secret service personnel (162 people) who were recuperating in a sanatorium from January to December 2017 were selected as the research subjects, all of whom were Han and male. The patients (79 people) who were diagnosed with EH according to the diagnostic criteria of hypertension in the "Chinese Guidelines for the Prevention and Treatment of Hypertension" (2016 Revised Edition) were the case group, and the people with normal blood pressure (83 people) were the control group. Occupational epidemiological investigation was conducted, 5 ml of fasting cubital venous blood was collected, genomic DNA was extracted by phenol-chloroform method, and RAAS gene polymorphism was detected by polymerase chain reaction-restriction fragment length polymorphism method. The distribution differences of genotype and allele frequency between groups were compared, and the relationship between genotype, allele frequency and EH was analyzed. The average age of military secret service personnel was (38.2±5.3) years old, and there was no statistical significance in the average age and the age distribution over 40 years old of the case group and the control group (>0.05) . There were significant differences in the distribution of AGT gene M235T locus, ACE gene I/D polymorphism genotype and allele between the case group and the control group (<0.05) . The TT genotype with AGT gene M235T locus (=3.28, 95%: 1.21-8.91) and DD genotype with ACE gene (=2.86, 95%: 1.17-7.00) were risk factors for EH in military secret service personnel. The TT genotype of AGT gene M235T and the DD genotype of ACE gene may be the susceptibility genotypes of military secret service personnel for EH.
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http://dx.doi.org/10.3760/cma.j.cn121094-20210202-00072 | DOI Listing |
Adv Sci (Weinh)
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Shanghai Frontiers Science Center of TCM Chemical Biology, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China.
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Dept Elect Engn, Coll Engn, Prince Sattam Bin Abdulaziz Univ, Al Kharj, Saudi Arabia.
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Department of Artificial Intelligence and Machine Learning, SNS College of Technology, Coimbatore 641035, India.
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