SEARCH

SEARCH BY CITATION

Keywords:

  • E-selectin;
  • high-resolution melting curve;
  • Kawasaki disease;
  • single nucleotide polymorphism

Abstract

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References

Background:  Coronary artery lesions (CAL) are a serious complication of Kawasaki disease (KD). The increased serum E-selectin level during the acute phase of KD and the association of E-selectin gene (SELE) polymorphisms with the prevalence of coronary artery disease in adults suggest a possible association between SELE polymorphisms and the development of CAL in KD patients.

Methods:  The subjects consisted of 177 KD patients, including 59 with and 118 without CAL, and 305 healthy controls. Two single nucleotide polymorphisms (SNP) of SELE, 98G>T (rs1805193) and Ser128Arg (rs5361), were genotyped by direct sequencing and the high-resolution melting curve method, respectively. The allele distributions were assessed using the chi-squared test.

Results:  There were no significant differences in the T allele frequency at 98G>T between KD patients and controls (1.4% vs 1.0%, P= 0.55) or between KD patients with and without CAL (1.7% vs 1.3%, P= 0.77). Similarly, there were no differences in the distribution of the C allele (128Arg) at Ser128Arg between KD patients and controls (4.5% vs 3.4%, P= 0.40) or between KD patients with and without CAL (4.2% vs 4.7%, P= 0.86).

Conclusion:  Although no association was detected between these SELE polymorphisms and the prevalence of KD or the development of CAL, this may have been due to the study limitations, including a low frequency of the minor alleles and a small sample size. A larger-scale association study is needed in order for a definitive conclusion to be made as to whether these SNP are associated with susceptibility to KD or not.

Kawasaki disease (KD) is an acute, self-limiting systemic vasculitis syndrome that mainly affects small and medium-sized arteries, and is found primarily in infants and young children.1 The most important cause of morbidity and mortality in KD is coronary artery lesions (CAL) that occur in 15–25% of untreated patients with KD.2,3 The etiology of KD has not been fully elucidated, but it is thought to be a multifactorial disease involving both genetic and environmental factors in its onset and development.4

To date, a number of genetic association studies have been performed with KD patients for genes mainly involving the immune system or inflammatory reactions. For example, 27 genes encoding cytokines (e.g. interleukin [IL]-4, IL-6, IL-10, tumor necrosis factor [TNF]) or surface antigens (e.g. CD14, CD40, Fcgamma receptor [FCGR]2A, FCGR3A) are listed in relation to KD on the Genetic Association Database (http://geneticassociationdb.nih.gov/cgi-bin/index.cgi). Inositol 1,4,5-trisphosphate 3-kinase C (ITPKC) acts as a negative regulator of T-cell activation.4,5 Recently, a genome-wide association study (GWAS) demonstrated an association of an ITPKC polymorphism with KD, which confers both an increased risk of KD and an increased risk of CAL formation.5

The immune system is markedly activated during the acute phase of KD, accompanied by infiltration of neutrophils, lymphocytes and macrophages into the vascular wall.6 Selectins facilitate the adhesion of inflammatory cellular components to the activated vascular endothelium, and promote localized vascular inflammation.7 Among the selectins, E-selectin is considered to be the most important for the pathophysiology of coronary artery diseases, because its expression is limited on activated endothelial cells upon stimulation with inflammatory cytokines.8 Interestingly, the soluble E-selectin level has been reported to increase during the acute phase of KD.9 It was also reported that higher plasma E-selectin levels might predict the likelihood of CAL in patients with KD.10

A base substitution from adenine (A) to cytosine (C) in the coding region (561A>C) of the E-selectin gene (SELE) results in an amino acid exchange from serine to arginine at codon 128 (Ser128Arg). The polymorphism has been known to increase the ligand-binding function of the protein11 and to be associated with early-onset atherosclerosis.12 Furthermore, another base substitution of the gene from guanine (G) to thymine (T) in the 5′-untranslated region (98G>T) is associated with severe coronary artery diseases in adults.13 Although CAL contribute greatly to the morbidity and mortality of KD, the association of SELE polymorphisms with KD has not yet been investigated.

We hypothesized that either or both the 98G>T or Ser128Arg polymorphism of the SELE gene may be associated with KD and, in particular, with the predisposition to the development of CAL. We herein report the results of a genetic association study between these SELE polymorphisms and the prevalence of KD or the development of CAL among KD patients. We also report the use of a new method for rapid and accurate genotyping: high-resolution melting curve (HRM) analysis.

Methods

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References

Patients and controls

Patients with KD were recruited from three hospitals in the northern Kyushu area of Japan: Nagasaki University Hospital, Saga University Hospital and Kyushu University Hospital. A total of 177 KD patients (115 male, 62 female), ranging from 1 month to 12 years of age, were enrolled in the study. Among the 177 KD patients, 59 developed CAL. The data on coronary complications were retrieved from the patients' medical charts. CAL were defined according to the criteria of the Japanese Ministry of Health, Labor and Welfare as a diameter of the initial lumen >3 mm in children <5 years or >4 mm in children ≥5 years of age, or the initial diameter of a segment being at least 1.5-fold larger than that of an adjacent segment as determined on echocardiography.14,15

We also recruited 305 control subjects (71 male, 234 female), ranging from 39 to 86 years of age, who participated in the medical screening program in Goto City, Nagasaki Prefecture.

All of the experimental procedures were approved by the Committee for the Ethical Issues on Human Genome and Gene Analysis in Nagasaki University. The institutional ethics committee of Saga University and Kyushu University also approved the study, and the parents of all subjects gave written informed consent for the children's participation.

Polymorphisms of SELE

Target polymorphisms were retrieved from the Genetic Association Database (http://geneticassociationdb.nih.gov/) in relation to search terms of SELE and coronary artery with positive association. Consequently, two single nucleotide polymorphisms (SNP), rs1805193 and rs5361, were selected.

The SNP of SELE have been described in several different ways such as G98T and S128R (or 561A>C).8,13,16 The National Center for Biotechnology Information has assigned all registered SNP respective reference numbers in the dbSNP (http://www.ncbi.nlm.nih.gov/snp). For instance, S128R corresponded to rs5361 according to the official notation, and is located at codon 149 of SELE (reference mRNA number: NM_00450). To avoid confusion, we used the traditional description in this article. As shown in Table 1, the G98T and S128R SNP studied herein are equivalent to rs1805193 and rs5361, respectively. To discriminate between base substitution and amino acid change, we described 98G>T as rs1805193 and Ser128Arg as rs5361 (Table 1).

Table 1.  Functional SNP in E-selectin gene (SELE)11–13
Previous descriptiondbSNP IDBase substitutionMinor alleleAmino acid changeFunctional area of the gene or proteinCorrelated event(s)
  1. The reference SNP (rs) numbers are defined on the SNP database website (http://www.ncbi.nlm.nih.gov/snp/). Minor alleles of E-selectin gene are regarded as risk factors for coronary artery disease. EGF, epidermal growth factor; SNP, single nucleotide polymorphism.

G98Trs1805193c.-19G>TT allele(-)5′untranslated regionSevere coronary artery disease13
Ser128Arg (S128R)rs5361c.561A>CC allelep.S149RCoding region, EGF-like domain, increased ligand affinity11Early-onset atherosclerosis, coronary artery disease12

Isolation of genomic DNA

Genomic DNA was extracted from EDTA-preserved whole blood samples using the QIAamp DNA Blood Mini Kit (Qiagen, Tokyo, Japan). The concentration of the template DNA was approximately 30 ng/µL.

Genotyping of 98G>T (rs1805193)

All samples of cases and controls were genotyped for 98G>T with direct sequencing by means of capillarity electrophoresis on an automated sequencer 3130xl (Applied Biosystems, Foster City, CA, USA) using the BigDye ver.3.1 software program (Applied Biosystems). Resultant electropherograms were analyzed using ATGC ver.6 (Software Development, Tokyo, Japan) or Sequence Scanner ver.1.0 (Applied Biosystems). Genetic alterations were searched for, including not only the SNP genotyping, but also mutations and deletions/insertions in the untranslated exon of the gene. Human E-selectin genomic DNA sequences were retrieved from the UCSC genome browser, assembled in March 2006 (http://genome.ucsc.edu/). Primers were designed with the assistance of the Primer3 software program (http://frodo.wi.mit.edu/cgi-bin/primer3/primer3.cgi).

The primer sequences were as follows: forward, 5′-TGCCCAAAATCTTAGGATGC-3′; reverse, 5′-GGGAAGAACACATTGCAGGT-3′.

Genotyping of Ser128Arg (rs5361): HRM method

The Ser128Arg genotype of SELE was identified using an HRM method on a LightCycler480 Real-Time PCR system (Roche Diagnostics, Mannheim, Germany) with an intercalating dye, SYBR Green I. After polymerase chain reaction (PCR) amplification, the LightCycler480 can monitor the melting of the DNA with increasing temperature by measuring the decrease in fluorescence as SYBR Green I is released.

Primers for the HRM method need to be designed so that the product size is <150 bp. The following primer sets yielded a 61 bp PCR product containing the SNP position: forward, 5′-TTGATGGTCTCTACACATTCACC-3′ and reverse, 5′-CCGTAGCTGCCTGTACCAAT-3′. The PCR assays were carried out in a 384-well plate in volumes of 10 µL containing 30 ng template DNA, forward and reverse primers (1 mmol/L each), and 5 µL iQ SYBR Green Supermix 2x (Bio-Rad Laboratories, CA, USA). The PCR amplification consisted of an initial denaturation at 95°C for 120 s, followed by 55 cycles consisting of 95°C for 10 s, annealing at 55°C for 15 s, and extension at 72°C for 20 s. After amplification, a melting step was performed, consisting of 95°C for 60 s, cooling to 40°C for 60 s, 75°C for 5 s, and finally a slow rise in the temperature to 95°C at a rate of 0.02°C/s with continuous acquisition of fluorescence decline.

Fluorescence was measured continuously during the low-temperature ramp to monitor the dissociation of the fluorescein-labeled detection probe. The fluorescence signal (F) was plotted in real time against the temperature (T) to produce melting curves for each sample (F vs T). Melting curves were then converted to the derivative of the fluorescence with regard to temperature against the temperature (–(dF/dT) vs T).

To validate the HRM method, samples selected from the respective genotypes were subjected to direct sequencing with an automated sequencer 3130xl Genetic Analyzer (Applied Biosystems) as already mentioned. The primer sequences used were as follows: forward, 5′-AGGCATGCAGACCTGACTCT-3′; reverse, 5′-AGGATAGGTGGGCCTGAAAC-3′.

Statistical analysis

The genotyping data were analyzed by comparison of the allele frequencies. The allele frequencies between cases and controls were assessed with the chi-squared test, and the Fisher's exact test was also used when the number of alleles in the sample was <5. Odds ratios (OR) were calculated for disease susceptibility or severity in carriers of specific alleles. The 95% confidence intervals for the OR were also calculated. P < 0.05 (two-tailed) was considered to be significant. Calculations were performed with DrSPSS II for Windows (SPSS Japan, Tokyo, Japan).

Results

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References

Genotyping by HRM

Given that conventional methods to determine SNP are laborious and expensive, we first tried an HRM method that was recently established for the rapid and accurate genotyping of SNP. This method is based on the difference in melting temperatures of the PCR products due to a single nucleotide substitution. This procedure provided clearly distinguishable patterns of temperature curves for Ser/Ser homozygosity and Ser/Arg heterozygosity during Ser128Arg genotyping (Fig. 1). Arg/Arg homozygosity was not found in the present subjects. The accuracy of genotyping with the HRM method was confirmed on direct sequencing. Unfortunately, this procedure could not be successfully applied to investigation of 98G>T genotyping, therefore we performed direct sequencing for that SNP.

image

Figure 1. Identification of the Ser128Arg genotype of SELE by the high-resolution melting curve (HRM) method. The HRM method successfully distinguished between two genotypes: (a,b) A/A and (c,d) A/C according to the two different patterns of melting curves resulting from differences in the melting temperature due to the single nucleotide substitution from A to C. (a,c) Melting of the polymerase chain reaction (PCR) products with increasing temperatures was measured in proportion to the decrease in fluorescence as SYBR Green I was released. (b,d) The fluorescence signal (F) was plotted in real time against the temperature (T) to produce melting curves for each sample (F vs T). Melting curves were then converted to the derivative of the fluorescence with regard to the temperature against temperature (–(dF/dT) vs T).

Download figure to PowerPoint

Genotype 98G>T distribution

Genotyping of the 98G>T polymorphism in SELE by direct sequencing showed that GG, GT and TT constituted 169 (97.1%), five (2.9%) and 0 (0%) of 174 KD patients, and 295 (99.0%), 0 (0%) and three (1.0%) of 298 control subjects, respectively (Table 2). The 98G>T genotyping was unsuccessful in three of the 177 KD patients and in seven of the 305 controls. The T allele frequency in the KD patients was only 1.4%, which differed little from the 1.0% in the control subjects (Table 2). Among the KD patients, the T allele frequencies were 1.7% and 1.3% in the CAL-positive and -negative groups, respectively; there was no significant difference between the two groups (Table 3). In addition, we did not find any mutations in the 5′ untranslated region, which contained the SNP. The base positions of the region ranged from 167 969 201 to 167 969 527 of chromosome 1.

Table 2.  The allele frequencies in KD patients and controls
98G>TKD patients (n = 174)Controls (n = 298)OR (95%CI), P
  • Chi-squared test or Fisher's exact test. CI, confidence interval; KD, Kawasaki disease; OR, odds ratio.

G allele343590 
T allele561.43 (0.43–4.73), P = 0.55
Table 3.  The allele frequencies in coronary artery lesion (CAL) positive versus -negative KD patients
98G>TKD (n = 174) 
CAL (+) (n = 59)CAL (−) (n = 115)OR (95%CI), P
  1. CAL, coronary artery lesion; CI, confidence interval; KD, Kawasaki disease; OR, odds ratio.

G allele116227 
T allele231.30 (0.21–7.92), P = 0.77

Genotype Ser128Arg distribution

The frequencies of the Ser/Ser, Ser/Arg and Arg/Arg genotypes were 161 (91.0%), 16 (9.0%) and 0 (0%) in the 177 KD patients, respectively, and 284 (93.1%), 21 (6.9%) and 0 (0%) in the 305 control subjects, respectively (Table 4). No differences in the distribution of the C allele (128Arg) were found between the patients and controls (4.5% vs 3.4%, P= 0.40). Among the KD patients, the C allele frequencies were 4.2% and 4.7% in the CAL-positive and -negative groups, respectively. No significant differences were observed between the two groups (Table 5).

Table 4.  The allele frequencies in KD patients and controls
Ser128ArgKD patients (n = 177)Controls (n = 305)OR (95%CI), P
  • Chi-squared test or Fisher's exact test. CI, confidence interval; KD, Kawasaki disease; OR, odds ratio.

A (Ser) allele338589 
C (Arg) allele16211.33 (0.68–2.58), P = 0.40
Table 5.  The allele frequencies in coronary artery lesion (CAL) positive versus -negative KD patients
Ser128ArgKD (n = 177) 
CAL (+) (n = 59)CAL (−) (n = 118)OR (95%CI), P
  1. CAL, coronary artery lesion; CI, confidence interval; KD, Kawasaki disease; OR, odds ratio.

A (Ser) allele113225 
C (Arg) allele5110.91 (0.31–2.67), P = 0.86

The genotype distribution of the Ser128Arg polymorphism of SELE in both patients and control subjects did not deviate from Hardy-Weinberg equilibrium, but it may be worth mentioning that the minor allele frequencies in both groups were slightly higher than that (2.3%) reported in the HapMap database (http://www.ncbi.nlm.nih.gov/snp) for the Japanese population.

Discussion

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References

Kawasaki disease is a systemic immune-mediated vasculitis syndrome that often involves the coronary arteries.1–3 Endothelial dysfunction, followed by the infiltration of leukocytes from the circulating blood into the vascular wall, plays a crucial part in the progression to vasculitis. Leukocyte rolling and tethering along the endothelial surface is the first step in their adhesion to endothelial cells, and this is mediated by the selectin family of adhesion molecules.6 The selectin family includes three molecules: P-, L-, and E-selectins. E-selectin is expressed on endothelial cells after activation mediated by inflammatory cytokines such as IL-1 and TNF-α.6 Moreover, the soluble E-selectin level has been reported to increase during the acute phase of KD9 and to predict the likelihood of CAL in patients with KD.10 The Ser128Arg polymorphism of SELE, located in the epidermal growth factor (EGF)-like domain of the protein,16 is functional in that it increases the protein's ligand affinity.11 Therefore, it is reasonable to hypothesize that E-selectin polymorphisms may influence the prevalence of KD or the development of CAL in KD patients.

The present study examined the possible correlation between the SELE polymorphisms and KD, including either the prevalence of KD or the development of CAL in KD patients. To the best of our knowledge, this is the first report to study the possible association between E-selectin polymorphisms and KD. We investigated two SNP, 98G>T and Ser128Arg, which have been shown to be associated with an increased risk of coronary artery diseases in adults, but we did not find any association between these SNP and KD or the development of CAL in KD patients. The sample size, however, might not have been of sufficient size to investigate the SNP, because their minor allele frequencies were too low in the present subjects. Therefore, we cannot totally exclude the possibility that either of these SELE polymorphisms may influence the pathogenesis of KD, because the association might have been missed due to the limited sample size. Further trials are necessary to determine whether the 98G>T and/or Ser128Arg polymorphisms in SELE are associated with an increased risk of KD or for CAL in KD patients.

In the present study we used a recently established HRM method for Ser128Arg genotyping that has the advantages of simplicity of procedure, low cost and high accuracy. It may not work for all SNP, given that we failed to perform 98G>T genotyping by this method using several primer sets. But whenever feasible, it is worth setting up the HRM method for any SNP analysis.

Finally, there has been a trend to apply GWAS,17,18 which can assess hundreds to thousands of SNP per individual, to determine the genetic relationships with many diseases or traits. Although GWAS are powerful and usually do not require an understanding of the pathological mechanism of the disease in advance, it is well known that some statistical data mining processes such as Bonferroni correction, may restrict the identification of important pathophysiologically plausible SNP.19,20

Acknowledgments

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References

We are grateful to the patients and their parents for their participation in this research.

References

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. References