BACKGROUND: Several studies have assessed the relationship between the angiotensin-converting enzyme (ACE) I/D or angiotensin II type 1 receptor (AT(1)R)-A C polymorphisms and blood pressure (BP). Since most data have been obtained in selected populations, the present study was performed in a healthy normotensive primary care population. OBJECTIVE: To investigate the individual effects of the aforementioned polymorphisms and their interaction on BP. METHODS: This cross-sectional study included 198 healthy subjects. Office BP was measured and polymorphisms were genotyped (polymerase chain reaction). Polymorphism interaction was tested using the following model: systolic blood pressure (SBP) (or diastolic blood pressure, DBP) = b(0)+ b(1)X + b(2)Y + b(3)XY, in which X and Y represent the polymorphisms' risk alleles. RESULTS: The ACE I/D polymorphism was associated with SBP (P = 0.002) and DBP (P = 0.004); highest pressures tracked with the DD genotype. Furthermore, in multiple linear regression analysis the ACE D allele was associated with SBP (P = 0.005) and DBP (P = 0.001), when adjusted for body mass index (BMI) and age. With respect to the AT(1)R-A C polymorphism, SBP was highest in the CC genotype (P = 0.025). In linear regression analysis the C allele was not associated with SBP. No synergistic effect of ACE D and AT(1)R C alleles on BP was found. Nevertheless, highest DBP tracked with the DDCC combination in comparison with other homozygous allele combinations (P = 0.030). CONCLUSIONS: This study confirmed an association of ACE I/D and AT(1)R-A C polymorphisms with BP in a healthy normotensive primary care population. Although synergistic effect of both polymorphisms on BP does not seem to be present, an additive effect on DBP is likely.
BACKGROUND: Several studies have assessed the relationship between the angiotensin-converting enzyme (ACE) I/D or angiotensin II type 1 receptor (AT(1)R)-A C polymorphisms and blood pressure (BP). Since most data have been obtained in selected populations, the present study was performed in a healthy normotensive primary care population. OBJECTIVE: To investigate the individual effects of the aforementioned polymorphisms and their interaction on BP. METHODS: This cross-sectional study included 198 healthy subjects. Office BP was measured and polymorphisms were genotyped (polymerase chain reaction). Polymorphism interaction was tested using the following model: systolic blood pressure (SBP) (or diastolic blood pressure, DBP) = b(0)+ b(1)X + b(2)Y + b(3)XY, in which X and Y represent the polymorphisms' risk alleles. RESULTS: The ACE I/D polymorphism was associated with SBP (P = 0.002) and DBP (P = 0.004); highest pressures tracked with the DD genotype. Furthermore, in multiple linear regression analysis the ACE D allele was associated with SBP (P = 0.005) and DBP (P = 0.001), when adjusted for body mass index (BMI) and age. With respect to the AT(1)R-A C polymorphism, SBP was highest in the CC genotype (P = 0.025). In linear regression analysis the C allele was not associated with SBP. No synergistic effect of ACE D and AT(1)R C alleles on BP was found. Nevertheless, highest DBP tracked with the DDCC combination in comparison with other homozygous allele combinations (P = 0.030). CONCLUSIONS: This study confirmed an association of ACE I/D and AT(1)R-A C polymorphisms with BP in a healthy normotensive primary care population. Although synergistic effect of both polymorphisms on BP does not seem to be present, an additive effect on DBP is likely.
Authors: Bruce E Blanchard; Gregory J Tsongalis; Margaux A Guidry; Lisa A LaBelle; Michelle Poulin; Amy L Taylor; Carl M Maresh; Joseph Devaney; Paul D Thompson; Linda S Pescatello Journal: Eur J Appl Physiol Date: 2006-02-09 Impact factor: 3.078
Authors: Praveen Sethupathy; Christelle Borel; Maryline Gagnebin; Gregory R Grant; Samuel Deutsch; Terry S Elton; Artemis G Hatzigeorgiou; Stylianos E Antonarakis Journal: Am J Hum Genet Date: 2007-07-12 Impact factor: 11.025
Authors: In Wook Hwang; Kicheol Kim; Bit Na Kwon; Hyung Jun Kim; Seung Hun Han; Noo Ri Lee; Eun Ji Choi; Hyun Ik Cho; Han Jun Jin Journal: Genes Genomics Date: 2018-09-10 Impact factor: 1.839
Authors: Linda S Pescatello; Debbie Turner; Nancy Rodriguez; Bruce E Blanchard; Gregory J Tsongalis; Carl M Maresh; Valerie Duffy; Paul D Thompson Journal: Nutr Metab (Lond) Date: 2007-01-04 Impact factor: 4.169
Authors: John P Forman; Naomi D L Fisher; Martin R Pollak; David G Cox; Stephan Tonna; Gary C Curhan Journal: J Clin Hypertens (Greenwich) Date: 2008-06 Impact factor: 3.738