The Effect of SIRT1 Gene Polymorphisms on Ambulatory Blood Pressure of Hypertensive Patients in the Kazakh Population

Abstract

Objective: To investigate the effect of silent information regulator 1 (SIRT1) gene polymorphisms on ambulatory blood pressure in hypertensive patients. Methods: Three hundred forty hypertensive patients were recruited from January 2013 to January 2015. SIRT1 Tag single-nucleotide polymorphisms (SNPs; rs2273773, rs4746720, and rs7896005) were genotyped using a PCR-direct sequencing method, and the association between the SIRT1 gene SNPs and ambulatory blood pressure was analyzed. Results: After adjusting for confounding factors, patients with the rs2273773/CT+CC genotypes had lower 24-h systolic and diastolic blood pressures; there were no associations between rs4746720 and rs7896005 genotypes and blood pressure. Conclusion: The SIRT1 gene polymorphism (rs2273773) is significantly associated with ambulatory blood pressure level in Han Chinese patients with hypertension.

Introduction

Hypertension, a prevalent, noncontagious chronic disease, is the major risk factor of cardiovascular disease. Each year, around 3 million people died from cardiovascular diseases in China, at least half of which are associated with hypertension. At present, the population with hypertension exceeds 300 million and its incidence is still on the rise (CDC, 2012). Hypertension is also an age-related chronic disease and its incidence increases dramatically with aging (Dominguez et al., 2015; Erne et al., 2015; Fan et al., 2015; Ho et al., 2015; Marques-Vidal et al., 2015). It also exposes elderly patients with increased risk of target organ damage such as ischemic heart disease, stroke, renal failure, as well as aortic and peripheral artery diseases. Therefore, hypertension is a major cause of morbidity and mortality in the elderly population.

Currently, ambulatory blood pressure monitoring (ABPM) shows absolute advantages in the diagnosis and treatment of hypertension. It not only improves the diagnostic accuracy, avoids possible white coat hypertension, and detects occult hypertension but also records multiple parameters of blood pressure, which offers doctors rapid and convenient ways to know the trend and overall variation of blood pressure. This improvement will help predict risk of cardiovascular complications, cardiovascular mortality, and all-cause mortality (Flythe et al., 2015; Li et al., 2015; Ramesh et al., 2015; Valenti et al., 2015).

Silent information regulator 1 (SIRT1) is a NAD+-dependent deacetylase. It is involved in various activities, including DNA damage repair, cell cycle control, cell apoptosis inhibition, organism energy metabolism, mitochondrial function protection, inflammatory response, and resistance to oxidative stress. It is also reported to help keep cells alive and healthy and to extend the life span of mammals, thus being given the name “antiaging factor.” Recent studies showed that SIRT1 protein may exert a protective role on endothelial cells and hemostasis of vessels, which also indicated its potential in inhibiting blood pressure elevation (Carnevale et al., 2014; Kumar et al., 2014; Pazienza et al., 2014; Kaul et al., 2015; Kim et al., 2015). However, there is still lack of evidence demonstrating the relationship between the SIRT1 gene and changes in ABPM parameters.

In our study, we detected SIRT1 gene polymorphisms in 340 hypertensive patients and tried to investigate the association of SIRT1 and ambulatory blood pressure level in a genetic context.

Materials and Methods

Study participants

The study group consisted of 340 hypertensive patients who were admitted into our hospital and underwent ABPM from January 2013 to January 2015. All the patients were part of the Kazakh population from Xinjiang, West China. Two hundred fifty-one patients were male and 89 female. The mean age was 55.6±11.3 years. Informed consent was obtained from all participants.

Hypertension was diagnosed as systolic blood pressure (SBP)≥140 mmHg and/or diastolic blood pressure (DBP)≥90 mmHg, according to the criteria of 2010 guidelines for Prevention and Treatment of Hypertension in China. Patients with hypertension history and blood pressure lower than 140/90 mmHg with antihypertensive medication were also recruited. Patients with secondary hypertension, diabetes, coronary heart disease, autoimmune disease, cerebral infarction, congestive heart failure, urinary disease, infectious disease, tumor, severe liver or kidney dysfunction, patients who received systemic anti-inflammatory medication or immunosuppressants, and those who could not tolerate tests were excluded.

Method of 24-h ABPM

All participants received 24-h ABPM with the ABPM-04/05 ambulatory blood pressure monitor (Meditech). The participants were instructed to maintain their normal daily activities and keep a diary of these activities by professional technicians. Patients were told to relax their right upper arm and avoid movement when blood pressure measurement took place during deflation. The supine position was recommended when sleeping at night. Concerning ABPM, blood pressure was measured every 20 min from 6 a.m. to 22 p.m. and every 60 min from 22 p.m. to 6 a.m. the next day. Then, the recorded data were analyzed by automated computerized software when monitoring was finished and patients with greater than 80% effective blood pressure detection were recruited into our study. Twenty-four-hour ABPM analytic software was used to analyze the original data and obtain parameters of ambulatory blood pressure.

To calibrate the results, the monitor was checked and calibrated by the company's technical staff every month. In addition, blood pressure was measured using a manual mercury sphygmomanometer for each participant.

Mean blood pressure

Parameters, including 24-h mean systolic/diastolic blood pressure, mean day SBP/DBP, and mean night SBP/DBP, were recorded. Twenty-four-hour mean arterial pressure (MAP), 24-h mean pulse pressure (mPP), pulse pressure index, day MAP, day mPP, night MAP, and night mPP were further calculated. The normal value of mean blood pressure was recommended by WHO-ISH as follows: day mean blood pressure <135/85 mmHg, night mean blood pressure <125/75 mmHg, and 24-h mean blood pressure <130/80 mmHg. MAP and PP were calculated using the following formula: \documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland, xspace}\usepackage{amsmath, amsxtra}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document} \begin{align*}\hbox{MAP = DBP + 1 / 3 ( SBP} -\hbox{DBP )}\end{align*} \end{document} \documentclass{aastex}\usepackage{amsbsy}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{bm}\usepackage{mathrsfs}\usepackage{pifont}\usepackage{stmaryrd}\usepackage{textcomp}\usepackage{portland, xspace}\usepackage{amsmath, amsxtra}\pagestyle{empty}\DeclareMathSizes{10}{9}{7}{6}\begin{document} \begin{align*}\hbox{PP = SBP} - {\rm DBP}\end{align*} \end{document}

Diurnal rhythm of blood pressure fluctuation

The diurnal rhythm of blood pressure fluctuation was evaluated by nocturnal diastolic blood pressure fall (NDBPF) and nocturnal systolic blood pressure fall (NSBPF). The calculations were as follows: NDBPF=(night mean blood pressure − day mean blood pressure)/day mean blood pressure×100%.

Blood pressure variation

Standard deviation of blood pressure measured by 24-h ABPM was used as the long-time blood pressure variation index, including standard deviation of 24-h SBP and DBP.

Blood pressure load

Blood pressure load was represented with PTE% (the percentage of time when BP was above the threshold within the total measuring time) and PTD% (the percentage of time when BP was below the threshold within the total measuring time). The index included 24 h SBPPTE%, 24 h DBPPTE%, 24 h SBPPTD%, and 24 h DBPPTD%.

DNA extraction

The peripheral venous blood of participants was collected after fasting and distributed in EDTA tubes. The blood sample was separated into plasma and blood cells and stored at −80°C for further use. The DNA Extraction Kit produced by Tiangen Biotech Co., Ltd was used for extracting and purifying DNA.

Genotyping

Tag single-nucleotide polymorphisms (SNPs) were chosen using Haploview 4.2 software according to previous literature. Three tag SNPs (rs2273773, rs4746720, rs7896005) were finally used after selection. Primer was designed with Primer 5.0 as shown in Table 1.

Table 1.

Primer's Sequencing of Three Tag Single-Nucleotide Polymorphisms

Loci	Primers
rs2273773	F: 3′TCCTGGACAATTCCAGCCATCT5′
	R: 3′TCCACTTCTCGATGGCAGTCAG5′
rs4746720	F: 3′TTTTCAAAAAGCCATCGGAATGTT5′
	R: 3′AACCGAGTGCTCTCCCCACATA5′
rs7896005	F: 3′AAGGCTTAAAATTGGCCTGACTTAAAA5′
	R: 3′CAGGTATTCCACATGAAACAGACACC5′

For the PCR, DNA samples (1 μL) were amplified in a 20-μL volume consisting of 1× HotStarTaq buffer, 3.0 mM Mg²⁺, 0.3 mM dNTP, 1 UHotStarTaq polymerase (Qiagen, Inc.), and 2 μL primers. The PCR program consisted of an initial denaturation step at 95°C for 2 min followed by 11 cycles of denaturation at 94°C for 20 s, annealing at 65-0.5°C/cycle for 40 s, and extension at 72°C for 1.5 min; 24 cycles of denaturation at 94°C for 20 s, annealing at 59°C for 30 s, and extension at 72°C for 1.5 min; 72°C for 2 min; 4°C forever. The amplified products were genotyped using direct sequencing (the genotyping was performed by The Beijing Genomic Institute), as shown in Figure 1.

FIG. 1.

Genotyping results according to direct sequencing methods. Arrows indicated the polymorphism loci.

Statistical analysis

Statistical analysis was performed using SPSS software 16.0. All quantitative data are expressed as mean±SD and categorical data were represented by percentage. Data with skew distribution were log transformed before regression analysis. Pearson's correlation test was applied to determine the correlation between two variables (Spearman correlation test was used for categorical variables or variables with non-normal distribution). The association between SNP sites and parameters of ABPM was analyzed using logistic regression. The coefficient estimate was performed using the enter method. p-Value less than 0.05 was considered statistically significant.

Results

Demographic data

Table 2 shows patient characteristics, including age, gender, results of laboratory tests, and physical examinations.

Table 2.

The Characteristics of Participants

Indices	Mean±SD
Age (year)	55.6±11.3
Sex (M/F)	251/89
BMI (Kg/m²)	24.6±4.3
Glu (mM)	5.35±1.25
CRP (mg/dL)	1.93±0.89
TC (mM)	4.20±0.97
LDL-C (mM)	2.32±0.88
Smoking (n, %)	121 (35.6)
Drinking (n, %)	109 (32.1)

BMI, body-mass index; CRP, C-reactive protein; F, female; LDL-C, low-density lipoprotein cholesterol; M, male; SD, standard deviation; TC, total cholesterol.

Distribution of genotype

Statistical analysis showed that the distribution of genotype at the three selected SNP sites of SIRT1 gene was in compliance with the Hardy-Weinberg equilibrium (p>0.05), which indicated a good representative of the whole population (Table 3).

Table 3.

Distribution of Genotype and Allele

		Genotype (n, %)			Allele (n, %)
Loci	N	1/1	1/2	2/2	1	2
rs2273773	340	55 (16.2)	133 (39.1)	152 (44.7)	243 (35.7)	437 (64.3)
rs4746720	340	64 (18.8)	180 (52.9)	96 (28.3)	308 (45.3)	372 (54.7)
rs7896005	340	10 (2.9)	88 (25.9)	242 (71.2)	108 (15.9)	572 (84.1)

Difference in ABPM levels among different genotypes

Concerning rs2273773, the wild-type genotype was TT. Our analysis revealed that 24 h mSBP, dSBP, and dPP were significantly higher in the TT wild-type genotype carriers than rs2273773/CT+CC genotype carriers (Table 4). This finding demonstrated that rs2273773 polymorphism was associated with ABPM parameters in hypertensive patients. However, no association was found between the rs4746720 or rs7896005 polymorphism and ABPM parameters (data were not shown). After adjusting confounding factors, there was still a significant association between rs2273773 polymorphism and ABPM parameters 24 h mSBP, dSBP, and dPP in patients with hypertension (data were not shown).

Table 4.

The Relation Between Genotypes and Ambulatory Blood Pressure Monitoring

Indices	TT genotype (n=152)	TC+CC genotype (n=188)	p
24 h mSBP	130.2±10.9	127.4±10.2	0.033
24 h mDBP	64.9±11.6	63.1±12.7	0.086
24 h MAP	88.6±8.2	86.7±7.4	0.432
24 h mPP	66.6±8.1	65.4±8.2	0.554
dSBP	130.0±12.7	128.1±16.1	0.038
dDBP	66.5±8.1	65.9±8.2	0.103
dMAP	89.2±8.2	87.1±7.8	0.143
nSBP	130.2±12.4	128.4±16.3	0.101
nDBP	64.3±9.5	63.3±8.3	0.672
nMAP	86.2±10.3	85.2±8.4	0.342
nPP	65.1±11.4	63.7±12.6	0.012
24 h SBPSD	13.9±3.4	13.7±3.4	0.204
24 h DBPSD	8.7±2.7	7.5±1.6	0.105
NSBPF	0.20±8.2	0.30±8.1	0.091
NDBPF	2.4±2.3	2.7±4.1	0.220
24 h SBPPTE%	39.8±22.2	37.1±23.2	0.323
24 h DBPPTE%	10.6±11.7	9.7±10.8	0.110
24 h SBPPTD%	3.7±4.1	3.2±5.1	0.108
24 h DBPPTD%	39.1±21.2	40.2±23.1	0.249

dDBP, daytime diastolic blood pressure; dMAP, daytime mean arterial pressure; dSBP, delta systolic blood pressure; MAP, mean arterial pressure; mDBP, mean diastolic blood pressure; mPP, mean pulse pressure; mSBP, mean systolic blood pressure; nDBP, nocturnal diastolic blood pressure; NDBPF, nocturnal diastolic blood pressure fall; nMAP, nocturnal mean arterial pressure; nSBP, nocturnal systolic blood pressure; NSBPF, nocturnal systolic blood pressure fall.

Discussion

Hypertension is a complex genetic disease, whose development and progression is influenced by complex interactions among multiple minor genes and the environment. SNP, the DNA sequence variation caused by a single-nucleotide alteration in a genome, is one of the most common inheritable genetic variations. Its association with diseases is currently the focus for researches on complex disease pathogenesis. Our study showed an association between SIRT1 gene polymorphism and ABPM parameters in hypertensive patients by adopting this genetic technique. To our knowledge, this was the first report on association between SIRT1 SNPs and ABPM.

SIRT1 is a kind of nuclear protein and a member of NAD+deacetylase family. SIRT1 is highly conservative across species from archaebacteria to human species and it exists in almost all types of cells (Carnevale et al., 2014). SIRT1 is also called “antiaging factor,” as it is reported to extend the life span of mammals when calorie intake is restricted. At present, there is growing evidence that SIRT1 may exert direct protection on the cardiovascular system through inhibiting cardiac myocyte hypertrophy, endothelium dysfunction, and regulating angiogenesis and the angiotension level, in addition to its indirect protection effect through regulation of the sugar and lipid metabolism (Kumar et al., 2014; Pazienza et al., 2014; Kim et al., 2015).

However, there is currently no report on the association between SIRT1 SNPs and hypertension in elderly patients. Only one Japanese study found an association between SIRT gene SNPs and office blood pressure. The study included 1279 health check-up examinees and analyzed the relationship between rs2273773 variation and body-mass index, office SBP, DBP, as well as laboratory data (lipid panel, fasting glucose, liver function, CRP, etc.). Multivariate regression revealed that rs2273773/CC carrier of male subjects had significantly higher SBP and DBP than TT and CT carrier. The TT carrier of male subjects had a significantly higher fasting glucose and body fat ration than TC and CC carrier. Our results showed that in hypertensive patients, TT wild-type genotype carriers had significantly higher 24 h mSBP, dSBP, dPP than rs2273773/CT+CC carriers. This finding demonstrated rs2273773 polymorphism was associated with ABPM parameters. However, our study had different results with the Japanese study. Two possibilities were considered for the difference. First, the study population of the two studies was different. Genetic variation may have a varied effect across different races, regions, population, and even different genders. Second, different methods of blood pressure measurement were adopted. Our study used ABPM to measure SBP and DBP. ABPM was considered as a more accurate method to evaluate blood pressure, the vital sign with the most significant variation and fluctuation. The genetic variation of rs2273773, an SNP located in the extron region of SIRT gene, may have altered corresponding protein expressions and influenced blood vessel protection and blood pressure regulation. Therefore, it is of vital importance to investigate SNP rs2273773. In the future, a case-control study with a larger sample or experiments in vivo/vitro should be carried out to further elucidate the association between rs2273773 and blood pressure.

Limitations of the Study

There were several limitations in the present study. On one hand, we aimed to investigate the effect of SIRT1 gene polymorphisms on ambulatory blood pressure of hypertensive patients, but did not include the control subjects in the present study. On the other hand, the small sample size may overestimate the odds ratio value and 95% confidence interval.

Footnotes

Acknowledgments

This work was supported by the Xinjiang Natural Science Fund Project: Medical joint fund (2014211C089).

Author Disclosure Statement

No competing financial interests exist.

References

Carnevale

, Pallante

, Fardella

, et al. (2014) The angiogenic factor PlGF mediates a neuroimmune interaction in the spleen to allow the onset of hypertension. Immunity, 41:737-752.

Centers for Disease Control and Prevention (CDC) (2012) CDC grand rounds: dietary sodium reduction—time for choice. MMWR Morb Mortal Wkly Rep, 61:89-91.

Dominguez

, Penman-Aguilar

, Chang

, et al. (2015) Vital signs: leading causes of death, prevalence of diseases and risk factors, and use of health services among hispanics in the United States—2009-2013. MMWR Morb Mortal Wkly Rep, 64:469-478.

Erne

, Radovanovic

, Schoenenberger

, et al. (2015) Impact of hypertension on the outcome of patients admitted with acute coronary syndrome. J Hypertens, 33:860-867.

Fan

, Wang

, Zhang

, et al. (2015) Prevalence, awareness, treatment and control of hypertension in rural areas in North China in 2013. Zhonghua Yi Xue Za Zhi, 95:616-620.

Flythe

, Kshirsagar

, Falk

, Brunelli

(2015) Associations of posthemodialysis weights above and below target weight with all-cause and cardiovascular mortality. Clin J Am Soc Nephrol, 10:808-816.

, Zainal

, Lim

, et al. (2015) Voluntary cognitive screening: characteristics of participants in an Asian setting. Clin Interv Aging, 10:771-780.

Kaul

, Singh

, Bhanwer

(2015) The influence of ethnicity in the association of WC, WHR, hypertension and PGC-1α (Gly482Ser), UCP2-866 G/A and SIRT1-1400 T/C polymorphisms with T2D in the population of Punjab. Gene, 563:150-154.

Kim

, Hwang

, Kim

, et al. (2015) NAD(P)H:quinone oxidoreductase 1 activation reduces blood pressure through regulation of endothelial nitric oxide synthase acetylation in spontaneously hypertensive rats. Am J Hypertens, 28:50-57.

10.

Kumar

, Mohan

, Upadhyay

, et al. (2014) Identification of serum sirtuins as novel noninvasive protein markers for frailty. Aging Cell, 13:975-980.

11.

, Sheng

, Hu

, et al. (2015) The prevalence, incidence, management and risks of atrial fibrillation in an elderly Chinese population: a prospective study. BMC Cardiovasc Disord, 15:31.

12.

Marques-Vidal

, Waeber

, Vollenweider

(2015) Eligibility to treatment and economic effect of the implementation of the new US or European Society of Hypertension/European Society of Cardiology hypertension guidelines. J Hypertens, 33:868-873.

13.

Pazienza

, Pomara

, Cappello

, et al. (2014) The TRPA1 channel is a cardiac target of mIGF-1/SIRT1 signaling. Am J Physiol Heart Circ Physiol, 307:H939-H944.

14.

Ramesh

, Mann

, Holroyd-Leduc

, et al. (2015) The effect of hormone therapy on all-cause and cardiovascular mortality in women with chronic kidney disease: protocol for a systematic review and meta-analysis. Syst Rev, 4:44.

15.

Valenti

, Ó Hartaigh

, Heo

, et al. (2015) Long-term prognosis for individuals with hypertension undergoing coronary artery calcium scoring. Int J Cardiol, 187:534-540.