Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0020538 (hypertension)
 170,190 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

AIMS. Blood pressure control is influenced by various genetic and environmental factors, and genetic susceptibility is important in the development of essential hypertension. Because the renin-angiotensin-aldosterone system (RAAS) has a key role in vasoconstriction, vasodilation, and sodium and electrolyte balance, it is central in blood pressure control and so is an appropriate target in hypertension treatments. The present study assessed the association of RAAS-related genes with blood pressure and hypertension in a Korean population. Single nucleotide polymorphisms (SNPs, n = 114) in nine RAAS-related genes (AGT, REN, ACE, ACE2, AGTR1, CYP11B2, NR3C2, MAS1, and CMA1) were assessed for their correlation with blood pressure and hypertension using genotype data of 8842 individuals from the Korea Association Resource subject pool. MAJOR FINDINGS. Linear regression analysis revealed a statistically significant association with blood pressure of 10 SNPs in six genes (ACE, ACE2, CYP11B2, NR3C2, MAS1, and CMA1). An additional hypertension case-control study identified 10 SNPs in NR3C2 and ACE that were linked to hypertension. PRINCIPAL CONCLUSION. Three SNPs (rs11737660, rs6810951, and rs10519963) in NR3C2 correlate with both blood pressure and hypertension. Genetic polymorphisms in RAAS-related genes appear to be associated with hypertension in a Korean population.
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PMID:Association between renin-angiotensin-aldosterone system-related genes and blood pressure in a Korean population. 2134 26

The renin-angiotensin-aldosterone system (RAAS) plays a key role in the regulation of blood pressure (BP). Mutations on the genes that encode components of the RAAS have played a significant role in genetic susceptibility to hypertension and have been intensively scrutinized. The identification of such probably causal mutations not only provides insight into the RAAS but may also serve as antihypertensive therapeutic targets and diagnostic markers. The methods for analyzing the SNPs from the huge dataset of SNPs, containing both functional and neutral SNPs is challenging by the experimental approach on every SNPs to determine their biological significance. To explore the functional significance of genetic mutation (SNPs), we adopted combined sequence and sequence-structure-based SNP analysis algorithm. Out of 3864 SNPs reported in dbSNP, we found 108 missense SNPs in the coding region and remaining in the non-coding region. In this study, we are reporting only those SNPs in coding region to be deleterious when three or more tools are predicted to be deleterious and which have high RMSD from the native structure. Based on these analyses, we have identified two SNPs of REN gene, eight SNPs of AGT gene, three SNPs of ACE gene, two SNPs of AT1R gene, three SNPs of CYP11B2 gene and three SNPs of CMA1 gene in the coding region were found to be deleterious. Further this type of study will be helpful in reducing the cost and time for identification of potential SNP and also helpful in selecting potential SNP for experimental study out of SNP pool.
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PMID:Combined sequence and sequence-structure-based methods for analyzing RAAS gene SNPs: a computational approach. 2487 1