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Abstract

  1. Top of page
  2. Abstract
  3. Material AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. References

Smoothelin is a specific cytoskeletal protein that is associated with smooth muscle cells. The human SMTN gene encodes smoothelin-A and smoothelin-B, and studies using SMTN gene knockout mice have demonstrated that these animals develop hypertension. The aim of the present study was to investigate the association between the human SMTN gene and essential hypertension (EH) using a haplotype-based case-control study. This is the first study to assess the association between essential hypertension and this gene.

A total of 255 EH patients and 225 controls were genotyped for the five single-nucleotide polymorphisms (rs2074738, rs5997872, rs56095120, rs9621187 and rs10304) used as genetic markers for the human SMTN gene. Data were analyzed for three separate groups: total subjects, men and women.

Although there were no differences for genotype distributions, or the dominant and recessive model distributions noted for total subjects, men and women for all of the SNPs selected for the present study, for the total subjects group, the frequency of the G-C-A-C haplotype constructed with rs2074738-rs5997872-rs56095120-rs9621187 was significantly lower in the essential hypertension patients than in the controls (P = 0.002).

The G-C-A-C haplotype appears to be a useful protective marker of essential hypertension in Japanese, and the SMTN gene might also be a genetic marker for essential hypertension.

Smoothelin is a specific cytoskeletal protein that is associated with smooth muscle cells (SMCs). The two major isoforms in adult humans are smoothelin-A (approximately 59 kDa) and smoothelin-B (approximately 110 kDa) (van Eys et al. 1997; Wehrens et al. 1997). Smoothelin-A is abundant in visceral smooth muscle and is essential for functional contractility of the intestinal smooth muscle (Niessen et al. 2005). While smoothelin-B is specifically expressed in the vascular smooth muscle cells, its expression is particularly high in muscular arteries, is modest in elastic arteries, and is absent in the capillaries, pericytic venules and small veins (van der Loop et al. 1997). The human SMTN gene that encodes both smoothelin-A and smoothelin-B is located on chromosome 22q12.2 and consists of 21 exons. Smoothelin-B is encoded by 21 exons, whereas smoothelin-A transcription starts in the middle of exon 10 (Rensen et al. 2002)

Some researchers have indicated that a loss of smoothelin-B results in the disappearance of the contractile SMC phenotype in a variety of vascular disorders. (Bar et al. 2002; Maeng et al. 2003; Hao et al. 2006). Even though these researchers focused on smoothelin-B's role as a marker for the contractile SMCs, a complete understanding of its function remains unclear. Work in mice (Rensen et al. 2008) has demonstrated that interruption of the SMTN gene, which only codes smoothelin-B, is accompanied by an increase in the mean arterial pressure. Therefore, mutations in the SMTN gene or alterations in smoothelin-B levels appear to be correlated with hypertension. However, the association between the SMTN gene and essential hypertension (EH) in humans has yet to be clarified.

The aim of the present study was to investigate the relationship between EH and the human SMTN gene through a haplotype-based case-control study.

Material AND METHODS

  1. Top of page
  2. Abstract
  3. Material AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. References

Subjects

Subjects diagnosed with hypertension were recruited at the Nihon University Itabashi Hospital and other neighboring hospitals in Tokyo from 1993 to 2003. A total of 1123 patients who consistently had blood pressure of at least 140 mm Hg systolic and/or 90 mm Hg diastolic were diagnosed as being hypertensive (stage I of the WHO criteria) (Guidelines 1999). Genomic DNA was extracted from each of the patients, and was then stored until analyses were performed. For the strict case-control study in EH patients, subjects were diagnosed based on the following criteria: seated systolic BP (SBP) > 160 mm Hg and/or diastolic BP (DBP) > 100 mm Hg (stage II or stage III of WHO criteria) on three occasions within two months after the first BP reading. All EH subjects investigated in the present study had a familial history of EH. A family history of hypertension was defined as a prior diagnosis of hypertension in grandparents, uncles, aunts, parents or siblings. None of the EH patients were receiving any antihypertensive medications. After initial patient enrollment, plasma aldosterone levels and renin activity were determined in all subjects. Patients determined to have secondary hypertension, such as primary aldosteronism, were excluded from the present study. After the screening of the original group was completed, a total of 255 EH patients met the inclusion criteria and were enrolled in the study.

For the control group, a total of 225 normotensive (NT) age-matched healthy individuals (m/f ratio = 1.88) were enrolled. None of the controls had any family history of hypertension, and all subjects had SBP of < 130 mm Hg and DBP of < 85 mm Hg. Informed consent was obtained from each subject in accordance with the protocol approved by the Human Studies Committee of Nihon University (Yamaguchi et al. 2010).

Genotyping

There are 301 SNPs for the human SMTN gene listed in the National Center for Biotechnology Information (NCBI) SNP database Build 129 (< www.ncbi.nlm.nih.gav/SNP >). In the present study, we also screened the data for the Tag SNPs on the International HapMap Project website (< www.hapmap.org/index.html.jp >) (Aoi et al. 2010). We selected five SNPs as markers for the genetic association experiment (rs2074738, rs5997872, rs56095120, rs9621187 and rs10304), all of which had a MAF of more than 0.15 (Fig. 1). Selections were based on the SNP allelic frequency information that had been previously registered with NCBI, Celera Discovery System-Applied Biosystems and the International HapMap project. Of these SNPs, rs5997872 was located in the exon region, rs10304 was located in the 3′-UTR, and the other three SNPs were located in the intron regions. Because only three out of the five SNPs (rs2074738, rs5997872 and rs10304) were shown on the International HapMap Project website, we were unaware of the |D′|- and r2-values between the five SNPs prior to starting the present study. We designated the five SNPs as SNP1 (rs2074738, C_16164833_10), SNP2 (rs5997872, C_2628872_10), SNP3 (rs56095120, AHT95ID), SNP4 (rs9621187, AHVI3OL) and SNP5 (rs10304, AHS07PD). SNP genotyping was performed using a kit from Applied Biosystems (Foster City, CA).

image

Figure 1. Structure of the human SMTN gene. The gene consists of 21 exons (boxes) separated by 20 introns (lines; intergenic regions). Filled boxes indicate the coding regions, while arrows indicate the locations of single nucleotide polymorphisms (SNPs). kbp: kilo-base pairs.

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Blood samples were collected from all participants, and genomic DNA was extracted from peripheral blood leukocytes using the phenol and chloroform extraction method (Nakayama et al. 2001). Genotyping was performed using the TaqMan SNP Genotyping Assay (Applied Biosystems). TaqMan SNP Genotyping Assays were performed using the Taq amplification method (Aoi et al. 2010). In the first step of the 5′ nuclease assay, allele-specific fluorogenic probes are hybridized to the template. Subsequently, the 5′ nuclease activity of the Taq polymerase makes it possible for discrimination to occur during polymerase chain reaction (PCR). The probes contain a 3′ minor groove-binding group that hybridizes to single-stranded targets that have greater sequence specificity than ordinary DNA probes. This reduces nonspecific probe hybridization, which results in a low background fluorescence in the 5′ nuclease PCR assay (TaqMan; Applied Biosystems). Cleavage results in increased emission of a reporter dye. Each 5′ nuclease assay requires two unlabeled PCR primers and two allele-specific probes. Each probe is labeled with two reporter dyes at the 5′-end. In the present study, VIC and FAM were used as reporter dyes. The primers and probes used in the TaqMan SNP Genotyping Assays (Applied Biosystems) were selected based on information available at the ABI website (< http://myscience.applied biosystems.com >).

PCR amplification was performed using 2.5 µl of TaqMan Universal Master Mix and No AmpErase UNG (2×) (Applied Biosystems) in a 5-µl final reaction volume. Also in the reaction mixture were 2 ng of DNA, 2.375 µl of ultrapure water, 0.079 µl of Tris-EDTA (TE) buffer (1×), 0.046 µl of TaqMan SNP Genotyping Assay Mix (40×) containing a 331.2 nmol l−1 final concentration of primers, and a 73.6 nmol l−1 final concentration of probes. Thermal cycling conditions were as follows: 50°C for 2 min; 95°C for 10 min; 50 cycles of 95°C for 15 s; and 60°C for 1 min. Thermal cycling was performed using the GeneAmp 9700 system.

Each 96-well plate contained 80 DNA samples of an unknown genotype and four reaction mixtures containing reagents but no DNA (control). As outlined in the TaqMan Allelic Discrimination Guide (Applied Biosystems), control samples without DNA are required for the Sequence Detection System (SDS) 7700 signal processing. The plates were read on the SDS 7700 instrument using the end-point analysis mode of the SDS version 1.6.3 software package (Applied Biosystems). The genotypes were determined visually based on the dye-component fluorescent emission data depicted in the x-y scatter-plot of the SDS software. Genotypes were also determined automatically by the signal processing algorithms of the software. The results of each scoring method were saved in two separate output files for later comparison (Livak et al. 1995).

Biochemical analysis

We measured the plasma concentration of total cholesterol and the serum concentration of creatinine using standard methods employed by the Clinical Laboratory Dept of Nihon Univ. Hospital.

Based on our initial estimated sample size, the number of patients enrolled was considered to be sufficient for a gene polymorphism study. During our analyses, we obtained 90% power during the detection of disequilibrium at the 5% level of significance. Results of a previously published study confirmed that our sample sizes were appropriate for this type of case-control study (Olson and Wijsman 1994).

Statistical analysis

All continuous variables were expressed as means ± SD. Differences in continuous variables between EH patients and control subjects were analyzed using Mann–Whitney U-test. Differences in the categorical variables were analyzed using Fisher's exact test. Differences in distributions of genotypes and alleles between EH patients and control subjects were analyzed using Fisher's exact test. Based on the genotype data on genetic variations, we performed linkage disequilibrium (LD) and haplotype-based case-control analyses using the expectation maximization (EM) algorithm (Dempster et al. 1977) and the software SNPAlyze ver. 3.2 (Dynacom Co., Ltd., Yokohama, Japan). Pairwise LD analysis was performed using three SNP pairs. We used |D′|-values of > 0.5 to assign SNP locations to one haplotype block. SNPs with an r2-value of < 0.5 were selected as tagged. In the haplotype-based case-control analysis, haplotypes with a frequency of < 0.01 were excluded. The frequency distribution of the haplotypes was calculated by performing a permutation test using the bootstrap method. Statistical significance was established at P < 0.05. Statistical analyses were performed using SPSS software for Windows, ver. 12 (SPSS Inc.).

RESULTS

  1. Top of page
  2. Abstract
  3. Material AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. References

Table 1 shows the clinical characteristics of the study participants. Body mass index, SBP and DBP were significantly higher for the EH patients as compared to control subjects for total subjects, men and women. Pulse rate and incidence of diabetes were significantly higher for the EH patients as compared to the control subjects in total subjects and men. There were no significant differences for age, plasma concentration of creatinine, the plasma concentration of total cholesterol, or incidence of drinking, smoking and hyperlipidemia between the EH patients and control subjects.

Table 1.  Characteristics of study participants.
 TotalMen
 NTEHP-valueNTEHP-valueNTEHP-value
  1. EH, essential hypertension; NT, normotension; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure.

  2. Continuous variables were expressed as mean ± standard deviation. Categorical variables were expressed as percentage.

  3. The P-value of continuous variables was calculated by the Mann-Whitney U-test.

  4. The P-value of the categorical variables was calculated by Fisher’s exact test. *P < 0.05.

Number of subjects225255 147171 7884 
Age (years)52.7 ± 10.552.8 ± 9.00.10652.4 ± 8.452.5 ± 9.50.16853.1 ± 13.853.3 ± 7.80.250
BMI (kg/m2)22.6 ± 3.124.6 ± 3.5< 0.001*22.8 ± 3.024.5 ± 3.3< 0.001*22.3 ± 3.424.6 ± 4.0< 0.001*
SBP (mm Hg)112.3 ± 10.8165.9 ± 23.4< 0.001*112.3 ± 10.5162.5 ± 21.6< 0.001*112.3 ± 11.3172.8 ± 25.6< 0.001*
DBP (mm Hg)68.9 ± 8.2101.3 ± 15.6< 0.001*69.4 ± 8.0101.8 ± 15.2< 0.001*67.8 ± 8.4100.3 ± 16.4< 0.001*
Pulse (beats/min)72.8 ± 11.376.6 ± 14.40.008*71.6 ± 11.476.5 ± 14.90.01*75.0 ± 10.877.0 ± 13.60.223
Creatinine (mg/dl)0.8 ± 0.20.9 ± 0.70.1260.9 ± 0.21.0 ± 0.70.2500.7 ± 0.10.7 ± 0.40.549
Total cholesterol (mg/dl)201.7 ± 44.3204.6 ± 41.40.455196.4 ± 43.8200.2 ± 40.10.634211.8 ± 43.9213.7 ± 42.70.549
Hyperlipidemia (%)30.833.20.58927.028.90.70238.442.00.647
Diabetes (%)3.111.00.001*2.711.10.004*3.810.70.095
Drinking (%)61.565.40.45171.479.00.17640.039.20.930
Smoking (%)46.253.00.19654.662.40.22028.332.90.596

Table 2 shows the distribution of genotypes and alleles for the five SNPs. The genotype distribution of the other five SNPs were in good agreement with Hardy–Weinberg equilibrium (data not shown). For all of the SNPs selected for the present study, there were no differences in genotype distributions, or in the dominant and recessive model distributions noted for total subjects, men and women. Dominance and recessiveness of the models were defined by their frequencies among total subjects.

Table 2.  Genotype and allele distributions in normotensives and patients with EH.
   TotalMenWomen
   NTEHP-valueNTEHP-valueNTEHP-value
  1. NT, normotensives, EH, essential hypertensives;

Number of participants225255 147171 7884 
Variants
rs2074738GenotypeGG69 (0.307)80 (0.314) 43 (0.293)52 (0.304) 26 (0.333)28 (0.3333) 
(SNP1) CG107 (0.476)113 (0.443) 69 (0.469)81 (0.474) 38 (0.487)32 (0.381) 
  CC49 (0.218)62 (0.243)0.73135 (0.238)38 (0.222)0.93914 (0.179)24 (0.2857)0.223
 Dominant modelCC49 (0.218)62 (0.243) 35 (0.238)38 (0.222) 14 (0.179)24 (0.2857) 
  CC + CG176 (0.782)193 (0.757)0.511112 (0.762)133 (0.778)0.73764 (0.821)60 (0.7143)0.111
 Recessive modelGG69 (0.307)80 (0.314) 43 (0.293)52 (0.304) 26 (0.333)28 (0.3333) 
  GG + CG156 (0.693)175 (0.686)0.868104 (0.707)119 (0.696)0.82252 (0.667)56 (0.6667)1.000
 AlleleG245 (0.544)273 (0.535) 155 (0.527)185 (0.541) 90 (0.577)88 (0.5238) 
  C205 (0.456)237 (0.465)0.777139 (0.473)157 (0.459)0.72966 (0.423)80 (0.4762)0.337
rs5997872GenotypeCC190 (0.844)215 (0.843) 124 (0.844)144 (0.842) 66 (0.846)71 (0.8452) 
(SNP2) CT35 (0.156)40 (0.157) 23 (0.156)27 (0.158) 12 (0.154)13 (0.1548) 
  TT0 (0)0 (0)1.0000 (0)0 (0)1.0000 (0)0 (0)1.000
 Dominant modelTT0 (0)0 (0) 0 (0)0 (0) 0 (0)0 (0) 
  CC + CT225 (1)255 (1) 147 (1)171 (1) 78 (1)84 (1) 
 Recessive modelCC190 (0.844)215 (0.843) 124 (0.844)144 (0.842) 66 (0.846)71 (0.8452) 
  TT + CT35 (0.156)40 (0.157)0.96923 (0.156)27 (0.158)0.97212 (0.154)13 (0.1548)0.987
 AlleleC415 (0.922)470 (0.922) 271 (0.922)315 (0.921) 144 (0.923)155 (0.9226) 
  T35 (0.078)40 (0.078)0.97023 (0.078)27 (0.079)0.97312 (0.077)13 (0.0774)0.988
rs56095120GenotypeTT210 (0.938)236 (0.925) 137 (0.938)158 (0.924) 73 (0.936)78 (0.9286) 
(SNP3) AT13 (0.058)19 (0.075) 8 (0.055)13 (0.076) 5 (0.064)6 (0.0714) 
  AA1 (0.004)0 (0)0.4961 (0.007)0 (0)0.4920 (0)0 (0)1.000
 Dominant modelAA1 (0.004)0 (0) 1 (0.007)0 (0) 0 (0)0 (0) 
  AA + AT223 (0.996)255 (1)0.468145 (0.993)171 (1)0.46178 (1)84 (1) 
 Recessive modelTT210 (0.938)236 (0.925) 137 (0.938)158 (0.924) 73 (0.936)78 (0.9286) 
  TT + AT14 (0.063)19 (0.075)0.6059 (0.062)13 (0.076)0.6165 (0.064)6 (0.0714)0.853
 AlleleT433 (0.967)491 (0.963) 282 (0.966)329 (0.962) 151 (0.968)162 (0.9643) 
  A15 (0.033)19 (0.037)0.75310 (0.034)13 (0.038)0.8005 (0.032)6 (0.0357)0.856
rs9621187GenotypeTT216 (0.96)250 (0.98) 144 (0.98)169 (0.988) 72 (0.923)81 (0.9643) 
(SNP4) TC9 (0.04)5 (0.02) 3 (0.02)2 (0.012) 6 (0.077)3 (0.0357) 
  CC0 (0)0 (0)0.2770 (0)0 (0)0.6650 (0)0 (0)0.315
 Dominant modelCC0 (0)0 (0) 0 (0)0 (0) 0 (0)0 (0) 
  TT + TC225 (1)255 (1)147 (1)171 (1)78 (1)84 (1) 
 Recessive modelTT216 (0.96)250 (0.98) 144 (0.98)169 (0.988) 72 (0.923)81 (0.9643) 
  CC + TC9 (0.04)5 (0.02)0.1853 (0.02)2 (0.012)0.5346 (0.077)3 (0.0357)0.315
 AlleleT441 (0.98)505 (0.99) 291 (0.99)340 (0.994) 150 (0.962)165 (0.9821) 
  C9 (0.02)5 (0.01)0.1883 (0.01)2 (0.006)0.6676 (0.038)3 (0.0179)0.322
rs10304GenotypeGG67 (0.298)82 (0.322) 43 (0.293)51 (0.298) 24 (0.308)31 (0.369) 
(SNP5) AG119 (0.529)128 (0.502) 79 (0.537)91 (0.532) 40 (0.513)37 (0.4405) 
  AA39 (0.173)45 (0.176)0.82225 (0.17)29 (0.17)0.99414 (0.179)16 (0.1905)0.631
 Dominant modelAA39 (0.173)45 (0.176) 25 (0.17)29 (0.17) 14 (0.179)16 (0.1905) 
  AA + AG186 (0.827)210 (0.824)0.928122 (0.83)142 (0.83)0.99164 (0.821)68 (0.8095)0.857
 Recessive modelGG67 (0.298)82 (0.322) 43 (0.293)51 (0.298) 24 (0.308)31 (0.369) 
  GG + AG158 (0.702)173 (0.678)0.574104 (0.707)120 (0.702)0.91154 (0.692)53 (0.631)0.410
 AlleleG253 (0.562)292 (0.573) 165 (0.561)193 (0.564) 88 (0.564)99 (0.5893) 
  A197 (0.438)218 (0.427)0.747129 (0.439)149 (0.436)0.93768 (0.436)69 (0.4107)0.647

The |D′|-values between SNP1-SNP2, SNP1-SNP3, SNP1-SNP4 and SNP1-SNP5 were 1.000, 0.841, 1.000 and 0.962, respectively. These results indicate that all five SNPs were located in one haplotype block. The r2-values for the linkage disequilibrium patterns are presented in Table 3. Two SNPs (SNP1 and SNP5) were not simultaneously available for the performance of a haplotype-based case-control study, as the r2-values were beyond 0.5 for both of the SNPs. We selected SNP1 (rs2074738) for the haplotype-based case-control study because the MAF of SNP1 was higher than that of SNP5. Therefore, the haplotype-based case-control study was performed using four SNPs (SNP1-SNP2-SNP3-SNP4).

Table 3.  Pairewise linkage disequilibrium for the five SNPs.
  1. |D′| above the diagonal and r2 below the diagonal. The shadowed portion indicates |D′| > 0.5 and r2 > 0.5.

inline image

In the haplotype-based case-control analysis, overall P-values and individual P-values for each haplotype were calculated (Table 4). The overall P-value for total subjects exhibited a significant difference (P = 0.037). For total subjects, the frequency of the G-C-A-C haplotype established by SNP1-SNP2-SNP3-SNP4 was significantly lower for EH patients, as compared to control subjects (P = 0.002). There were no significant differences in overall distribution between EH patients and control subjects for either men or women.

Table 4.  Haplotype analysis in patients with EH and control subjects.
     Overall P-valueFrequency in total Frequency in men Frequency in women 
HaplotypeNo1No2No3No4TotalManWomenEH patientsControl subjectsP-valueEH patientsControl subjectsP-valueEH patientsControl subjectsP-value
  1. EH, essential hypertension; Haplotype with frequency > 0.01 were estimated using SNPAlyze software.

  2. P-value was calculated by permutation test using bootstrap method. *P < 0.05.

 SNP1SNP2SNP3SNP40.037*0.8790.734         
H1 G C A T    0.4960.4930.9350.5000.4900.7940.4760.5060.582
H2 C C A T    0.3930.3790.6770.3870.4060.6540.4020.3460.299
H3 C T A T    0.0750.0760.9540.0740.0730.9630.0730.0770.899
H4 G C T T    0.0360.0310.6610.0390.0320.6270.0310.0320.936
H5 G C A C    0.0000.0200.002*0.0180.0390.275

DISCUSSION

  1. Top of page
  2. Abstract
  3. Material AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. References

Although it has been more than 10 years since smoothelin was found in the chicken stomach, little is known about how it functions as an SMC protein (van Eys et al. 2007). Researchers have indicated that smoothelin-A and -B are only found in fully differentiated, contractile SMCs, both of which could be used as viable markers for the contractile phenotype of the SMCs (van der Loop et al. 1997; Jochen et al. 2001; Maeng et al. 2003; van der Heijden et al. 2004). A few studies have demonstrated that smoothelin-A and -B have a “calponin homology domain” that binds to α-smooth muscle actin in SMCs, which indicates that it plays an important role in the contraction process of SMCs (Korenbaum and Rivero 2002; Niessen et al. 2004). Research in mice (Rensen et al. 2008) has shown that there is an interesting relationship between smoothelin-B deficiencies and hypertension. When the gene that only encodes smoothelin-B is interrupted, the contractile capacity in mice was reduced as compared to wild mice. However, the basal mean arterial pressure was significantly higher in these mice when compared to controls. The characteristics seen in hypertensive Smtn-B2/2 mice include a normal cardiac output, hypertrophic heart and increased peripheral resistance. These characteristics are similar to those noted in patients with established hypertension. However, to date, there have been no association studies comparing EH and the SMTN genes. Therefore, this is the first study to use a haplotype to examine the association between the human SMTN gene and EH.

In the present study, we genotyped five SNPs in the SMTN gene in Japanese subjects, and then assessed the association between this gene and EH. Our results indicated that there were no significant differences in the overall distribution of the genotypic and allelic frequencies for these SNPs between the EH and control groups. Morris and Kaplan (2002) performed analyses that focused on individual SNPs in genes with multiple susceptibilities, particularly those in which the linkage disequilibria between the SNPs was weak. The authors found that when trying to determine a relationship between a genetic variation and phenotypes, haplotype-based case-control studies provided more information than case-control studies that only employed a single SNP (Stephens et al. 2001; Zhang et al. 2002). Thus, based on these previous findings that indicated that a haplotype analysis would be useful in assessing the association between haplotypes and multifactorial disorders such as EH (Naganuma et al. 2008), we attempted to perform a haplotype-based case-control study that examined the SMTN gene. The haplotype-based case-control study that used rs2074738-rs5997872-rs56095120-rs9621187 to examine the asso ciation demonstrated there was a significant difference. Thus, these results suggest that there is an association between EH and the SMTN gene. Unfortunately, it remains unknown as to whether the interruption of the SMTN gene affected blood pressure. Rensen et al. (2008) found that cardiac output, autonomic nervous system activity, and large-artery properties were not altered in smoothe lin-B-deficient mice, and thus, they hypothesized that the increased pressure may have originated from altered microvascular properties. As no significant differences were noted for the cardiac output between deficient mice and controls, peripheral vascular resistance can be regarded as being the main cause of the observed elevated blood pressure. Even so, other possible causes such as neuro humoral vasopressor systems, arterial relaxation properties, and the total number of vessels cannot be excluded at this time.

Based on our results, we concluded that the studied haplotype was a protective marker for EH. Other research studies have also reported on a possible protective gene for EH. Zhao et al. (2007) found that the occurrence rate of the 2850 T allele of the TNF-α gene was lower in patients with a hypertensive disorder that caused pregnancy complications. This suggests that the poly morphism may lower the susceptibility of pregnant women to pre-eclampsia, thereby protecting them from the disease. Ramirez-Lorca et al. (2007) genotyped two polymorphisms within the CYP19A1 gene; IVS4 rs11575899 and 3′UTR rs10046. A case-control analysis revealed that the IVS4_11 and 3′UTR_22 genotypes have a protective effect against diastolic hypertension, while haplotype 12 protects against hypertension. Chao et al. (1997) reported that delivery of the human tissue kallikrein gene into adult spontaneously hypertensive rats resulted in a sustained reduction of blood pressure. Overall, these results indicate that there are some genes or gene variations that can protect humans from hyper tension. While it appears that these beneficial genes are important for understanding the mechanisms of hypertension, finding and defining these anti-hypertensive genes remains a major challenge.

In conclusion, this is first time that correlations between the human SMTN gene and EH have been examined in the Japanese population. The present data indicate that the human SMTN gene is associated with EH and that there is a haplotype that may be a protective marker for Japanese patients with hypertension. There were some limitations associated with the present study. Case-control studies can sometimes exhibit pseudo-positive results due to sample scales. In the present study, our results indicated that there was a weak association between the SMTN gene and EH in Japanese. A replication study with a larger and/or another population is necessary in order to confirm the present results.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Material AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. References

We would like to thank Ms. K. Sugama for her technical assistance. This work was supported by grants from Toray Co., Ltd., and from the Ministry of Education, Culture, Sports, Science and Technology of Japan and (MEXT)- Supported Program for the Strategic Research Foundation at Private Universities, 2008 2012.

References

  1. Top of page
  2. Abstract
  3. Material AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  7. References