Association of TOMM40 and SLC22A4 polymorphisms with ischemic stroke

  • Authors:
    • Yuichiro Yamase
    • Hideki Horibe
    • Chikara Ueyama
    • Tetsuo Fujimaki
    • Mitsutoshi Oguri
    • Kimihiko Kato
    • Masazumi Arai
    • Sachiro Watanabe
    • Yoshiji Yamada
  • View Affiliations

  • Published online on: April 29, 2015     https://doi.org/10.3892/br.2015.457
  • Pages:491-498
0

Abstract

Recent genome-wide association studies (GWASs) and their meta-analyses have identified various genes and loci underlying the predisposition to ischemic stroke or coronary artery disease in Caucasian populations. Given that ischemic stroke and coronary artery disease may have a shared genetic architecture, certain polymorphisms may confer genetic susceptibility to these two diseases. The aim of the present study was to examine the possible association of ischemic stroke with 29 single‑nucleotide polymorphisms (SNPs) previously identified by the meta‑analyses of GWASs as susceptibility loci for coronary artery disease. The study population comprised 3,187 Japanese individuals, including 894 subjects with ischemic stroke and 2,293 controls. The genotypes for the 29 SNPs of the 28 genes were determined by a method that combines the polymerase chain reaction and sequence‑specific oligonucleotide probes with suspension array technology. Comparisons of the allele frequencies by the χ2 test between subjects with ischemic stroke and controls revealed that rs9319428 (G→A) of the fms‑related tyrosine kinase 1 gene (P=0.0471), rs2075650 (G→A) of the translocase of outer mitochondrial membrane 40 homolog gene (TOMM40, P=0.0102) and rs273909 (T→C) of the solute carrier family 22, member 4 gene (SLC22A4, P=0.0097) were significantly (P<0.05) associated with the prevalence of ischemic stroke. Multivariable logistic regression analysis with adjustment for age, gender, body mass index, smoking status and the prevalence of hypertension, diabetes mellitus and dyslipidemia revealed that rs2075650 of TOMM40 (P=0.0443; recessive model; odds ratio=0.50) and rs273909 of SLC22A4 (P=0.0123; dominant model; odds ratio=0.45) were significantly associated with ischemic stroke with the minor G and C allele, respectively, being protective against this condition. TOMM40 and SLC22A4 may thus be susceptibility loci for ischemic stroke in Japanese individuals.

Introduction

Stroke is a complex multifactorial disorder that is believed to result from an interaction between a person's genetic background and various environmental factors (1,2). It is a common and serious condition, with ~795,000 individuals having experienced a new or recurrent stroke and ~130,000 fatalities having occurred from stroke-related causes in the United States in 2010 (3). The prevalence of stroke in the United States is ~6.8 million. Of all such events, 87% are ischemic stroke, 10% are intracerebral hemorrhage and 3% are subarachnoid hemorrhage (3). Despite recent advances in the treatment for the acute phase of stroke, stroke remains the leading cause of severe disability and the fourth leading cause of mortality, following heart disease, cancer and pulmonary disease in Western countries (35). The identification of biomarkers for stroke risk is important for risk prediction and intervention to avert future cerebrovascular events.

Ischemic stroke (particularly atherothrombotic cerebral infarction) and coronary artery disease are atherosclerotic diseases that share various aspects of their underlying pathogenesis, as well as several risk factors, including hypertension, dyslipidemia, diabetes mellitus and smoking. Twin and family studies have demonstrated that ischemic stroke and coronary artery disease are highly heritable (6,7) with evidence of a shared heritability for the two conditions (8). Recent genome-wide association studies (GWASs) and their meta-analyses have identified various genes and loci underlying the predisposition to ischemic stroke (913) or coronary artery disease (14,15) mainly in Caucasian populations. Among these genes and loci, some of the genetic variants that were originally detected to affect a risk of coronary artery disease were also associated with ischemic stroke (1618), suggesting a shared genetic architecture. Although ischemic stroke and coronary artery disease have been suggested to have a shared genetic architecture in Caucasian populations, the genes that confer susceptibility to the two conditions in Japanese individuals have not been identified definitively.

The aim of the present study was to examine the possible association of ischemic stroke in Japanese individuals with the 29 single-nucleotide polymorphisms (SNPs) previously identified as susceptibility loci for coronary artery disease by the meta-analyses of GWASs in Caucasian populations (14,15).

Materials and methods

Study population

The study subjects comprised 3,187 Japanese individuals (894 subjects with ischemic stroke and 2,293 controls) who either visited the outpatient clinics or were admitted to the participating hospitals (Gifu Prefectural Tajimi Hospital, Tajimi; Gifu Prefectural General Medical Center, Gifu; Inabe General Hospital, Inabe; Japanese Red Cross Nagoya First Hospital, Nagoya; Hirosaki University Hospital and Hirosaki Stroke Center, Hirosaki, Japan) between 2002 and 2012. The diagnosis of ischemic stroke was based on the occurrence of a new and abrupt focal neurological deficit, with neurological symptoms and signs persisting for >24 h; it was confirmed by positive findings in computed tomography or magnetic resonance imaging (or both) of the head. The type of stroke was determined according to the Classification of Cerebrovascular Diseases III (19). Individuals with cardiogenic embolic infarction, lacunar infarction alone, transient ischemic attack, moyamoya disease or cerebral venous sinus thrombosis were excluded from the study. Control individuals had no history of ischemic or hemorrhagic stroke, or other cerebral diseases; of coronary artery disease, aortic aneurysm, or peripheral arterial occlusive disease; or of other thrombotic, embolic or hemorrhagic disorders.

Hypertension was defined as individuals who either had systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg, or had been administered antihypertensive medication. Dyslipidemia was defined as individuals who had either a serum concentration of triglycerides of ≥1.65 mmol/l, a serum high-density lipoprotein (HDL)-cholesterol of <1.04 mmol/l, a serum low-density lipoprotein (LDL)-cholesterol of ≥3.64 mmol/l, or had been administered antidyslipidemic medication. Diabetes mellitus was defined as individuals who either had a fasting plasma glucose level of ≥6.93 mmol/l or blood glycosylated hemoglobin (hemoglobin A1c) content of ≥6.5%, or had been administered antidiabetes medication. Chronic kidney disease (CKD) was defined as individuals who had an estimated glomerular filtration rate (eGFR) of <60 ml min−1 1.73 m−2. The eGFR was calculated with the use of the simplified prediction equation derived from the modified version of that described in the Modification of Diet in Renal Disease study, as proposed by the Japanese Society of Nephrology: eGFR (ml/min/1.73 m2) = 194 × age (years)−0.287 × serum creatinine (mg/dl)−1.094 (x 0.739 if female) (20).

The study protocol complied with the Declaration of Helsinki and was approved by the Committees on the Ethics of Human Research of Mie University Graduate School of Medicine, Hirosaki University Graduate School of Medicine (Hirosaki, Japan) and the participating hospitals. Written informed consent was obtained from each participant.

Selection and genotyping of polymorphisms

The SNPs that were shown to be significantly associated with coronary artery disease or myocardial infarction were searched in Caucasian populations by the meta-analyses of GWASs (14,15). These SNPs were examined with the SNP database (dbSNP; National Center for Biotechnology Information, Bethesda, MD, USA; http://www.ncbi.nlm.nih.gov/SNP/) to find SNPs with a minor allele frequency of ≥0.015 in a Japanese population. A total of 29 SNPs (21) were selected and the possible association with ischemic stroke was examined.

Venous blood (7 ml) was collected into tubes containing 50 mmol/l ethylenediaminetetraacetic acid (disodium salt), the peripheral blood leukocytes were isolated and genomic DNA was extracted from these cells with a DNA extraction kit (Genomix; Talent, Trieste, Italy). Genotypes of SNPs were determined at G&G Science Co., Ltd. (Fukushima, Japan) by a method that combines the polymerase chain reaction and sequence-specific oligonucleotide probes with suspension array technology (Luminex, Austin, TX, USA). Primers, probes and other conditions for genotyping of SNPs examined in the study are as described previously (21). The overall call rate of 29 SNP genotyping was 99%. Detailed genotyping methodology was also as described previously (2224).

Statistical analysis

Quantitative data were compared between two groups by the Mann-Whitney U test, given that the data were not normally distributed (P<0.01 by the Kolmogorov-Smirnov and Lilliefors test). Categorical data were compared by the χ2 test. Allele frequencies were estimated by the gene counting method. Multivariable logistic regression analysis was performed with ischemic stroke as a dependent variable and independent variables including age, gender (0, female; 1, male), body mass index (BMI), smoking status (0 non-smoker; 1 current or former smoker), history of hypertension, diabetes mellitus and dyslipidemia (0 no history; 1 positive history), and each genotype; and the P-value, odds ratio and 95% confidence interval were calculated. Genotypes of each polymorphism were assessed according to dominant [0 AA; 1 AB+BB (A, major allele; B, minor allele)], recessive (0 AA+AB; 1 BB) and additive genetic models. Additive models comprised additive 1 (AB vs. AA) and 2 (BB vs. AA) models, which were analyzed simultaneously with a single statistical model. P<0.05 was considered to indicate a statistically significant difference. The statistical tests were performed with JMP version 5.1 and JMP Genomics version 6.0 software (SAS Institute Inc., Cary, NC, USA).

Results

Subject characteristics

The characteristics of the 3,187 study subjects are shown in Table I. Age, the frequency of men, the prevalence of smoking, hypertension, dyslipidemia, diabetes mellitus and CKD, as well as systolic and diastolic blood pressure, serum concentrations of triglycerides, LDL-cholesterol and creatinine, and fasting plasma glucose level were greater, whereas serum concentrations of HDL-cholesterol and eGFR were lower in subjects with ischemic stroke compared to the controls.

Table I.

Characteristics of subjects with ischemic stroke and the controls.

Table I.

Characteristics of subjects with ischemic stroke and the controls.

CharacteristicsIschemic strokeControlsP-value
No. of subjects8942,293
Age, years68.8±10.362.3±11.8<0.0001
Gender, % (male/female)61.6/38.444.7/55.3<0.0001
Body mass index, kg/m223.6±3.623.7±3.60.5420
Current or former smoker, %27.522.70.0148
Hypertension, %75.344.3<0.0001
Systolic blood pressure, mmHg152±28141±24<0.0001
Diastolic blood pressure, mmHg84±1779±14<0.0001
Dyslipidemia, %39.229.6<0.0001
Serum triglyceride, mmol/l1.60±1.011.50±1.100.0002
Serum HDL-cholesterol, mmol/l1.24±0.371.47±0.40<0.0001
Serum LDL-cholesterol, mmol/l3.13±0.923.02±0.850.0472
Diabetes mellitus, %42.720.0<0.0001
Fasting plasma glucose, mmol/l7.46±3.126.36±3.40<0.0001
Chronic kidney disease, %39.428.6<0.0001
Serum creatinine, µmol/l90.4±94.683.2±98.5<0.0001
eGFR, m/min/1.73 m266.6±23.270.4±23.2<0.0001

[i] Quantitative data are mean ± standard deviation. Hypertension: Systolic blood pressure of ≥140 mmHg or diastolic blood pressure of ≥90 mmHg (or both), or taking of antihypertensive medication. Dyslipidemia: A serum concentration of triglycerides of ≥1.65 mmol/l, a serum high-density lipoprotein (HDL)-cholesterol of <1.04 mmol/l, a serum low-density lipoproitein (LDL)-cholesterol of ≥3.64 mmol/l, or taking of antidyslipidemic medication. Diabetes mellitus: A fasting blood glucose level of ≥6.93 mmol/l or a blood glycosylated hemoglobin content of ≥6.5% (or both), or taking of antidiabetes medication. Chronic kidney disease: Estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m2. Quantitative data are compared between the two groups by the Mann-Whitney U test.

Comparisons of genotype distributions or allele frequencies

The genotype distributions and allele frequencies were compared by the χ2 test and revealed that 3 SNPs were significantly (P<0.05) associated with the prevalence of ischemic stroke (Table II). The genotype distributions and allele frequencies of rs2075650 of the translocase of outer mitochondrial membrane 40 homolog (TOMM40) gene and of rs273909 of the solute carrier family 22, member 4 (SLC22A4) gene were significantly associated with the prevalence of ischemic stroke. Allele frequencies of rs9319428 of the fms-related tyrosine kinase 1 gene (FLT1) were also significantly associated with ischemic stroke. These SNPs were further examined by multivariable logistic regression analysis with adjustment for covariates.

Table II.

Comparisons of genotype distributions and allele frequencies of rs9319428 of FLT1, rs2075650 of TOMM40 or rs273909 of SLC22A4 by the χ2 test between subjects with ischemic stroke and controls.

Table II.

Comparisons of genotype distributions and allele frequencies of rs9319428 of FLT1, rs2075650 of TOMM40 or rs273909 of SLC22A4 by the χ2 test between subjects with ischemic stroke and controls.

GenedbSNPPolymorphismIschemic stroke, n (%)Control, n (%)Call rate (%)P-value (genotype)P-value (allele)
FLT1rs9319428G→A 99.30.13190.0471a
GG331 (37.0)926 (40.8)
GA421 (47.1)1,021 (45.0)
AA142 (15.9)324 (14.3)
TOMM40rs2075650G→A 99.40.0043a0.0102a
AA640 (71.6)1,557 (68.4)
AG239 (26.7)629 (27.7)
GG15 (1.7)89 (3.9)
SLC22A4rs273909T→C 99.70.0232a0.0097a
TT872 (97.5)2,180 (95.5)
TC21 (2.4)101 (4.4)
CC1 (0.1)2 (0.1)

a P<0.05. FLT1, fms-related tyrosine kinase 1 gene; TOMM40, translocase of outer mitochondrial membrane 40 homolog gene; SLC22A4, solute carrier family 22, member 4 gene; dbSNP, single nucleotide polymorphism database.

Multivariable logistic regression analysis

The multivariable logistic regression analysis was performed with adjustment for age, gender, BMI, smoking status and the prevalence of hypertension, diabetes mellitus and dyslipidemia and revealed that rs2075650 of TOMM40 (recessive and additive 2 models) and rs273909 of SLC22A4 (dominant and additive 1 models), but not rs9319428 of FLT1, were significantly (P<0.05) associated with ischemic stroke, with the minor G and C alleles, respectively, being protective against this condition (Table III).

Table III.

Multivariable logistic regression analysis of the polymorphisms associated with ischemic stroke.

Table III.

Multivariable logistic regression analysis of the polymorphisms associated with ischemic stroke.

DominantRecessiveAdditive 1Additive 2




GenePolymorphismP-valueOR (95% CI)P-valueOR (95% CI)P-valueOR (95% CI)P-valueOR (95% CI)
FLT1rs9319428 (G→A)0.10221.20 (0.96–1.49)0.21001.20 (0.90–1.61)0.19621.16 (0.95–1.80)0.09711.31 (0.95–1.80)
TOMM40rs2075650 (G→A)0.10660.83 (0.65–1.04)0.0443a0.50 (0.24–0.95)0.28290.88 (0.69–1.11)0.0353a0.48 (0.24–0.92)
SLC22A4rs273909 (T→C)0.0123a0.45 (0.23–0.82)0.73960.01 (unstable-5.78)0.0158a0.46 (0.24–0.84)0.73810.01 (unstable-5.60)

a P<0.05. FLT1, fms-related tyrosine kinase 1 gene; TOMM40, translocase of outer mitochondrial membrane 40 homolog gene; SLC22A4, solute carrier family 22, member 4 gene; OR, odds ratio; CI, confidence interval. Multivariable logistic regression analysis was performed with adjustment for age, gender, body mass index, smoking status and the prevalence of hypertension, diabetes mellitus and dyslipidemia. Due to the low frequency of the C allele of rs273909, a lower value of 95% CI was unstable in a recessive or an additive 2 model.

Association of TOMM40 and SLC22A4 polymorphisms with the prevalence of the clinical phenotypes

Subsequently, the association of rs2075650 of TOMM40 or rs273909 of SLC22A4 to the prevalence of hypertension, dyslipidemia, diabetes mellitus or CKD was examined in all the subjects (Table IV). The rs2075650 of TOMM40 or rs273909 of SLC22A4 was significantly (P<0.05) associated with the prevalence of dyslipidemia (dominant model) or CKD (recessive model), respectively.

Table IV.

Associations of rs2075650 of TOMM40 or rs273909 of SLC22A4 with the prevalence of hypertension, dyslipidemia, diabetes mellitus or CKD as determined by the χ2 test.

Table IV.

Associations of rs2075650 of TOMM40 or rs273909 of SLC22A4 with the prevalence of hypertension, dyslipidemia, diabetes mellitus or CKD as determined by the χ2 test.

Clinical phenotypeGenotype, n (%)P-value (dominant)P-value (recessive)
TOMM40 (rs2075650)AAAGGG
  Hypertension
    Case1,169 (69.4)467 (27.7)48 (2.9)0.90670.1466
    Control1,028 (69.2)401 (27.0)56 (3.8)
  Dyslipidemia
    Case685 (66.8)301 (29.4)39 (3.8)0.0349a0.2531
    Control1,512 (70.5)567 (26.5)65 (3.0)
  Diabetes mellitus
    Case601 (71.6)212 (25.3)26 (3.1)0.09130.7288
    Control1,596 (68.5)656 (28.2)78 (3.3)
  CKD
    Case531 (69.2)206 (26.9)30 (3.9)0.72380.3235
    Control1,161 (70.0)447 (26.9)52 (3.1)
SLC22A4 (rs273909)TTTCCC
  Hypertension
    Case1,622 (96.0)66 (3.9)1 (0.1)0.92050.4911
    Control1,430 (96.1)56 (3.8)2 (0.1)
  Dyslipidemia
    Case982 (95.5)44 (4.3)2 (0.2)0.27870.2038
    Control2,070 (96.3)78 (3.6)1 (0.1)
  Diabetes mellitus
    Case811 (96.6)29 (3.4)0 (0.0)0.40200.2988
    Control2,241 (95.9)93 (4.0)3 (0.1)
  CKD
    Case738 (96.1)28 (3.6)2 (0.3)0.58810.0372a
    Control1,593 (95.6)73 (4.4)0 (0.0)

a P<0.05. Hypertension: Systolic blood pressure of ≥140 mmHg or diastolic blood pressure of ≥90 mmHg (or both), or taking of antihypertensive medication. Dyslipidemia: A serum concentration of triglycerides of ≥1.65 mmol/l, a serum high density lipoprotein-cholesterol of <1.04 mmol/l, a serum low density lipoproitein-cholesterol of ≥3.64 mmol/l, or taking of antidyslipidemic medication. Diabetes mellitus: A fasting blood glucose level of ≥6.93 mmol/l or a blood glycosylated hemoglobin content of ≥6.5% (or both), or taking of antidiabetes medication. CKD: Estimated glomerular filtration rate <60 ml/min/1.73 m2. TOMM40, translocase of outer mitochondrial membrane 40 homolog gene; SLC22A4, solute carrier family 22, member 4 gene; CKD, chronic kidney disease.

Association of TOMM40 and SLC22A4 polymorphisms with the prevalence with the clinical parameters

The associations of rs2075650 of TOMM40 or rs273909 of SLC22A4 were examined with the clinical parameters including systolic, diastolic and mean blood pressure, pulse pressure, serum concentrations of triglycerides, LDL-cholesterol, HDL-cholesterol, creatinine, fasting plasma glucose level and eGFR (Table V). To avoid the effects of medical treatment on clinical parameters, the corresponding controls were examined for hypertension, dyslipidemia, diabetes mellitus or CKD. The rs2075650 of TOMM40 was not associated with any clinical parameter, whereas rs273909 of SLC22A4 was associated with fasting plasma glucose level (recessive model).

Table V.

Associations of rs2075650 of TOMM40 or rs273909 of SLC22A4 with the clinical parameters among corresponding controls for hypertension, dyslipidemia, diabetes mellitus or chronic kidney disease.

Table V.

Associations of rs2075650 of TOMM40 or rs273909 of SLC22A4 with the clinical parameters among corresponding controls for hypertension, dyslipidemia, diabetes mellitus or chronic kidney disease.

Clinical parameterGenotypeP-value (dominant)P-value (recessive)
Controls for hypertension
  TOMM40 (rs2075650)AAAGGG
    Systolic blood pressure, mmHg121±11122±11116±100.95190.0782
    Diastolic blood pressure, mmHg71±971±969±120.58350.6733
    Mean blood pressure, mmHg88±988±985±100.74150.2788
    Pulse pressure, mmHg50±1151±1047±120.33840.2738
  SLC22A4 (rs273909)TTTCCC
    Systolic blood pressure, mmHg121±11126±101280.06590.6491
    Diastolic blood pressure, mmHg71±972±10780.81140.4374
    Mean blood pressure, mmHg88±990±9950.39470.3570
    Pulse pressure, mmHg50±1154±19500.08050.9611
Controls for dyslipidemia
  TOMM40 (rs2075650)AAAGGG
    Serum triglycerides, mmol/l1.27±0.741.31±0.721.33±0.660.15050.1883
    Serum LDL-cholesterol, mmol/l2.68±0.622.74±0.622.76±0.660.08110.4884
    Serum HDL-cholesterol, mmol/l1.39±0.391.37±0.371.30±0.380.38650.2344
  SLC22A4 (rs273909)TTTCCC
    Serum triglycerides, mmol/l1.29±0.741.18±0.57ND0.1587ND
    Serum LDL-cholesterol, mmol/l2.70±0.632.83±0.56ND0.1461ND
    Serum HDL-cholesterol, mmol/l1.38±0.391.40±0.36ND0.3983ND
Controls for diabetes mellitus
  TOMM40 (rs2075650)AAAGGG
    Fasting plasma glucose, mmol/l5.17±0.875.17±0.855.24±0.830.90550.5534
  SLC22A4 (rs273909)TTTCCC
    Fasting plasma glucose, mmol/l5.18±0.875.06±0.726.69±0.200.44050.0228a
Controls for chronic kidney disease
  TOMM40 (rs2075650)AAAGGG
    Serum creatinine, µmol/l61.1±12.960.8±12.364.0±12.30.96230.0783
    eGFR (ml/min/1.73 m2)80.6±16.680.0±20.779.6±17.50.20280.6268
  SLC22A4 (rs273909)TTTCCC
    Serum creatinine, µmol/l61.2±12.860.4±11.4ND0.6562ND
    eGFR (ml/min/1.73 m2)80.4±17.977.6±15.6ND0.7419ND

a P<0.05. LDL, low-density lipoprotein; HDL, high-density lipoprotein; eGFR, estimated glomerular filtration rate; ND, not determined; TOMM40, translocase of outer mitochondrial membrane 40 homolog gene; SLC22A4, solute carrier family 22, member 4 gene. Data are compared between the two groups (dominant or recessive model) by the Mann-Whitney U test.

Discussion

The association of 29 SNPs identified by the meta-analyses of GWASs for coronary artery disease in Caucasian populations (14,15) to the prevalence of ischemic stroke in Japanese individuals was examined. The present study showed that rs2075650 of TOMM40 and rs273909 of SLC22A4 were significantly associated with ischemic stroke with the minor G and C allele, respectively, being protective against this condition.

TOMM40 is located at chromosome 19q13 (NCBI Gene) and encodes a channel-forming subunit of multisubunit translocase of the outer mitochondrial membrane (TOM complex), which plays a role in cytoplasmic protein transport into the mitochondria (25,26). The rs2075650 of TOMM40 was shown to be associated with longevity, Alzheimer's disease and plasma concentrations of total cholesterol and C-reactive protein (2730). The previous study suggested that rs2075650 may increase a risk of carotid artery disease by promoting the formation of smaller, denser LDL particles (31). The present results showed that rs2075650 was associated with the prevalence of dyslipidemia but not to the serum lipid profiles, suggesting that the effect of this SNP on the development of dyslipidemia may not be significant.

The rs2075650 located in the intron 2 of TOMM40 (NCBI Gene) is a proxy of the SNPs that define alleles of the apolipoprotein E gene (APOE) (32). Given that the rs2075650 of TOMM40 is in strong linkage disequilibrium with rs429358 (C→T, Arg130Cys) of APOE, certain clinical implications may originate from APOE (27,32). Although the minor C allele of rs429358 of APOE was shown to be associated with the increased serum LDL-cholesterol level, as well as the increased risk of coronary artery disease and Alzheimer's disease (27,33,34), the association of this SNP with ischemic stroke has not been determined (35). The present study shows that rs2075650 of TOMM40 was associated with ischemic stroke with the minor G allele being protective against this condition, although the underlying molecular mechanism remains unclear.

SLC22A4, located at chromosome 5q31, is abundantly expressed in the kidney, skeletal muscle, bone marrow and trachea, and weakly expressed in numerous other organs (36). SLC22A4 encodes carnitine/organic cation transporter (OCTN1), which transports ergothioneine. Ergothioneine was shown to have antioxidative and cytoprotective functions (37,38) and to protect cardiovascular tissue against oxidative injury during ischemia and reperfusion (39). Ergothioneine decreased the expression of the adhesion molecules, including vascular cell adhesion molecule 1, intercellular adhesion molecule 1 and selectin E, and inhibited binding of monocytes to the endothelium (40). These observations suggest that the immunomodulatory effects of ergothioneine may be beneficial, owing to inhibition of the atherogenic action of pro-inflammatory cytokines and adhesion molecules (41,42). Several SNPs of SLC22A4 were shown to be associated with chronic inflammatory disease, such as Crohn's disease, ulcerative colitis, rheumatoid arthritis and type 1 diabetes mellitus (4346). In the present study, rs273909 was associated with the prevalence of CKD but not to the serum concentration of creatinine or eGFR. This SNP was also associated with fasting plasma glucose level but not to the prevalence of diabetes mellitus. These observations suggest that the effect of rs273909 on the development of CKD or diabetes mellitus may not be significant. The present study has now shown that rs273909 of SLC22A4 was significantly associated with ischemic stroke with the minor C allele being protective against this condition, although the underlying mechanism remains to be elucidated. The effect of rs273909 on the expression or molecular structure of OCTN1 also remains unknown.

The meta-analysis of GWASs has identified several loci that confer shared susceptibility to ischemic stroke and coronary artery disease in Caucasians (18). Among these loci, we have examined rs1122608 of the SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 4 gene and rs12413409 of the cyclin and CBS domain divalent metal cation transport mediator 2 gene. However, neither rs1122608 nor rs12413409 was associated with ischemic stroke in Japanese individuals. We previously showed that 6 genetic variants among the same 29 SNPs were associated with myocardial infarction in Japanese individuals (21), but no SNP was associated with ischemic stroke and myocardial infarction.

There were several limitations in the present study; i) given that the results were not replicated, validation of these findings is required in other independent subject panels or in other ethnic groups; ii) it is possible that rs2075650 of TOMM40 or rs273909 of SLC22A4 is in linkage disequilibrium with other polymorphisms in the same gene or in other nearby genes that are actually responsible for the development of ischemic stroke; and iii) the functional relevance of rs2075650 or rs273909 to pathogenesis of ischemic stroke remains to be elucidated.

In conclusion, TOMM40 and SLC22A4 may be susceptibility loci for ischemic stroke in Japanese individuals. Determination of the genotypes of these SNPs may prove informative for assessment of the genetic risk for ischemic stroke in such individuals.

Acknowledgements

The present study was supported by a Collaborative Research grant from the Gifu Prefectural General Medical Center (no. H24-26 to Y.Y.) and a Grant-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology of Japan (no. 24590746 to Y.Y.).

References

1 

Tournier-Lasserve E: New players in the genetics of stroke. N Engl J Med. 347:1711–1712. 2002. View Article : Google Scholar : PubMed/NCBI

2 

Bak S, Gaist D, Sindrup SH, Skytthe A and Christensen K: Genetic liability in stroke: A long-term follow-up study of Danish twins. Stroke. 33:769–774. 2002. View Article : Google Scholar : PubMed/NCBI

3 

Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Blaha MJ, Dai S, Ford ES, Fox CS, Franco S, et al: American Heart Association Statistics Committee and Stroke Statistics Subcommittee: Heart disease and stroke statistics - 2014 update: A report from the American Heart Association. Circulation. 129:e28–e292. 2014. View Article : Google Scholar : PubMed/NCBI

4 

Bonita R: Epidemiology of stroke. Lancet. 339:342–344. 1992. View Article : Google Scholar : PubMed/NCBI

5 

Warlow C, Sudlow C, Dennis M, Wardlaw J and Sandercock P: Stroke. Lancet. 362:1211–1224. 2003. View Article : Google Scholar : PubMed/NCBI

6 

Dichgans M: Genetics of ischaemic stroke. Lancet Neurol. 6:149–161. 2007. View Article : Google Scholar : PubMed/NCBI

7 

Roberts R and Stewart AF: The genetics of coronary artery disease. Curr Opin Cardiol. 27:221–227. 2012. View Article : Google Scholar : PubMed/NCBI

8 

Banerjee A, Lim CC, Silver LE, Welch SJ, Banning AP and Rothwell PM: Familial history of stroke is associated with acute coronary syndromes in women. Circ Cardiovasc Genet. 4:9–15. 2011. View Article : Google Scholar : PubMed/NCBI

9 

Ikram MA, Seshadri S, Bis JC, Fornage M, DeStefano AL, Aulchenko YS, Debette S, Lumley T, Folsom AR, van den Herik EG, et al: Genomewide association studies of stroke. N Engl J Med. 360:1718–1728. 2009. View Article : Google Scholar : PubMed/NCBI

10 

Matarín M, Brown WM, Scholz S, Simón-Sánchez J, Fung HC, Hernandez D, Gibbs JR, De Vrieze FW, Crews C, Britton A, et al: A genome-wide genotyping study in patients with ischaemic stroke: Initial analysis and data release. Lancet Neurol. 6:414–420. 2007. View Article : Google Scholar : PubMed/NCBI

11 

Yamada Y, Fuku N, Tanaka M, Aoyagi Y, Sawabe M, Metoki N, Yoshida H, Satoh K, Kato K, Watanabe S, et al: Identification of CELSR1 as a susceptibility gene for ischemic stroke in Japanese individuals by a genome-wide association study. Atherosclerosis. 207:144–149. 2009. View Article : Google Scholar : PubMed/NCBI

12 

Traylor M, Farrall M, Holliday EG, Sudlow C, Hopewell JC, Cheng YC, Fornage M, Ikram MA, Malik R, Bevan S, et al: Australian Stroke Genetics Collaborative, Wellcome Trust Case Control Consortium 2 (WTCCC2); International Stroke Genetics Consortium: Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE collaboration): A meta-analysis of genome-wide association studies. Lancet Neurol. 11:951–962. 2012. View Article : Google Scholar : PubMed/NCBI

13 

Holliday EG, Maguire JM, Evans TJ, Koblar SA, Jannes J, Sturm JW, Hankey GJ, Baker R, Golledge J, Parsons MW, et al: Australian Stroke Genetics Collaborative; International Stroke Genetics Consortium; Wellcome Trust Case Control Consortium 2: Common variants at 6p21.1 are associated with large artery atherosclerotic stroke. Nat Genet. 44:1147–1151. 2012. View Article : Google Scholar : PubMed/NCBI

14 

Schunkert H, König IR, Kathiresan S, Reilly MP, Assimes TL, Holm H, Preuss M, Stewart AF, Barbalic M, Gieger C, et al: Cardiogenics; CARDIoGRAM Consortium: Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat Genet. 43:333–338. 2011. View Article : Google Scholar : PubMed/NCBI

15 

Deloukas P, Kanoni S, Willenborg C, Farrall M, Assimes TL, Thompson JR, Ingelsson E, Saleheen D, Erdmann J, Goldstein BA, et al: CARDIoGRAMplusC4D Consortium; DIAGRAM Consortium; CARDIOGENICS Consortium; MuTHER Consortium; Wellcome Trust Case Control Consortium: Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet. 45:25–33. 2013. View Article : Google Scholar : PubMed/NCBI

16 

Gschwendtner A, Bevan S, Cole JW, Plourde A, Matarin M, Ross-Adams H, Meitinger T, Wichmann E, Mitchell BD, Furie K, et al: International Stroke Genetics Consortium: Sequence variants on chromosome 9p21.3 confer risk for atherosclerotic stroke. Ann Neurol. 65:531–539. 2009. View Article : Google Scholar : PubMed/NCBI

17 

Williams FM, Carter AM, Hysi PG, Surdulescu G, Hodgkiss D, Soranzo N, Traylor M, Bevan S, Dichgans M, Rothwell PM, et al: EuroCLOT Investigators; Wellcome Trust Case Control Consortium 2; MOnica Risk, Genetics, Archiving and Monograph; MetaStroke; International Stroke Genetics Consortium: Ischemic stroke is associated with the ABO locus: The EuroCLOT study. Ann Neurol. 73:16–31. 2013. View Article : Google Scholar : PubMed/NCBI

18 

Dichgans M, Malik R, König IR, Rosand J, Clarke R, Gretarsdottir S, Thorleifsson G, Mitchell BD, Assimes TL, Levi C, et al: METASTROKE Consortium; CARDIoGRAM Consortium; C4D Consortium; International Stroke Genetics Consortium: Shared genetic susceptibility to ischemic stroke and coronary artery disease: A genome-wide analysis of common variants. Stroke. 45:24–36. 2014. View Article : Google Scholar : PubMed/NCBI

19 

Special report from the National Institute of Neurological Disorders and Stroke. Classification of cerebrovascular diseases III. Stroke. 21:637–676. 1990. View Article : Google Scholar : PubMed/NCBI

20 

Matsuo S, Imai E, Horio M, Yasuda Y, Tomita K, Nitta K, Yamagata K, Tomino Y, Yokoyama H and Hishida A: Collaborators developing the Japanese equation for estimated GFR: Revised equations for estimated GFR from serum creatinine in Japan. Am J Kidney Dis. 53:982–992. 2009. View Article : Google Scholar : PubMed/NCBI

21 

Matsuoka R, Abe S, Tokoro F, et al: Association of six genetic variants with myocardial infarction. Int J Mol Med. 35:1451–1459. 2015.PubMed/NCBI

22 

Yamada Y, Nishida T, Ichihara S, Sawabe M, Fuku N, Nishigaki Y, Aoyagi Y, Tanaka M, Fujiwara Y, Yoshida H, et al: Association of a polymorphism of BTN2A1 with myocardial infarction in East Asian populations. Atherosclerosis. 215:145–152. 2011. View Article : Google Scholar : PubMed/NCBI

23 

Yamada Y, Nishida T, Ichihara S, et al: Identification of chromosome 3q28 and ALPK1 as susceptibility loci for chronic kidney disease in Japanese individuals by a genome-wide association study. J Med Genet. 50:410–418. 2013. View Article : Google Scholar : PubMed/NCBI

24 

Itoh Y, Mizuki N, Shimada T, Azuma F, Itakura M, Kashiwase K, Kikkawa E, Kulski JK, Satake M and Inoko H: High-throughput DNA typing of HLA-A, -B, -C and -DRB1 loci by a PCR-SSOP-Luminex method in the Japanese population. Immunogenetics. 57:717–729. 2005. View Article : Google Scholar : PubMed/NCBI

25 

Koehler CM, Merchant S and Schatz G: How membrane proteins travel across the mitochondrial intermembrane space. Trends Biochem Sci. 24:428–432. 1999. View Article : Google Scholar : PubMed/NCBI

26 

Humphries AD, Streimann IC, Stojanovski D, Johnston AJ, Yano M, Hoogenraad NJ and Ryan MT: Dissection of the mitochondrial import and assembly pathway for human Tom40. J Biol Chem. 280:11535–11543. 2005. View Article : Google Scholar : PubMed/NCBI

27 

Deelen J, Beekman M, Uh HW, et al: Genome-wide association study identifies a single major locus contributing to survival into old age; the APOE locus revisited. Aging Cell. 10:686–698. 2011. View Article : Google Scholar : PubMed/NCBI

28 

Feulner TM, Laws SM, Friedrich P, Wagenpfeil S, Wurst SH, Riehle C, Kuhn KA, Krawczak M, Schreiber S, Nikolaus S, et al: Examination of the current top candidate genes for AD in a genome-wide association study. Mol Psychiatry. 15:756–766. 2010. View Article : Google Scholar : PubMed/NCBI

29 

Aulchenko YS, Ripatti S, Lindqvist I, et al: ENGAGE Consortium: Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts. Nat Genet. 41:47–55. 2009. View Article : Google Scholar : PubMed/NCBI

30 

Reiner AP, Barber MJ, Guan Y, Ridker PM, Lange LA, Chasman DI, Walston JD, Cooper GM, Jenny NS, Rieder MJ, et al: Polymorphisms of the HNF1A gene encoding hepatocyte nuclear factor-1 alpha are associated with C-reactive protein. Am J Hum Genet. 82:1193–1201. 2008. View Article : Google Scholar : PubMed/NCBI

31 

Ronald J, Rajagopalan R, Ranchalis JE, Marshall JK, Hatsukami TS, Heagerty PJ and Jarvik GP: Analysis of recently identified dyslipidemia alleles reveals two loci that contribute to risk for carotid artery disease. Lipids Health Dis. 8:522009. View Article : Google Scholar : PubMed/NCBI

32 

Bekris LM, Lutz F and Yu CE: Functional analysis of APOE locus genetic variation implicates regional enhancers in the regulation of both TOMM40 and APOE. J Hum Genet. 57:18–25. 2012. View Article : Google Scholar : PubMed/NCBI

33 

Bennet AM, Di Angelantonio E, Ye Z, Wensley F, Dahlin A, Ahlbom A, Keavney B, Collins R, Wiman B, de Faire U, et al: Association of apolipoprotein E genotypes with lipid levels and coronary risk. JAMA. 298:1300–1311. 2007. View Article : Google Scholar : PubMed/NCBI

34 

Bagyinszky E, Youn YC, An SS and Kim S: The genetics of Alzheimer's disease. Clin Interv Aging. 9:535–551. 2014. View Article : Google Scholar : PubMed/NCBI

35 

Khan TA, Shah T, Prieto D, Zhang W, Price J, Fowkes GR, Cooper J, Talmud PJ, Humphries SE, Sundstrom J, et al: Apolipoprotein E genotype, cardiovascular biomarkers and risk of stroke: Systematic review and meta-analysis of 14,015 stroke cases and pooled analysis of primary biomarker data from up to 60,883 individuals. Int J Epidemiol. 42:475–492. 2013. View Article : Google Scholar : PubMed/NCBI

36 

Bleasby K, Castle JC, Roberts CJ, Cheng C, Bailey WJ, Sina JF, Kulkarni AV, Hafey MJ, Evers R, Johnson JM, et al: Expression profiles of 50 xenobiotic transporter genes in humans and pre-clinical species: A resource for investigations into drug disposition. Xenobiotica. 36:963–988. 2006. View Article : Google Scholar : PubMed/NCBI

37 

Mitsuyama H and May JM: Uptake and antioxidant effects of ergothioneine in human erythrocytes. Clin Sci (Lond). 97:407–411. 1999. View Article : Google Scholar : PubMed/NCBI

38 

Aruoma OI, Spencer JP and Mahmood N: Protection against oxidative damage and cell death by the natural antioxidant ergothioneine. Food Chem Toxicol. 37:1043–1053. 1999. View Article : Google Scholar : PubMed/NCBI

39 

Sakrak O, Kerem M, Bedirli A, Pasaoglu H, Akyurek N, Ofluoglu E and Gültekin FA: Ergothioneine modulates proinflammatory cytokines and heat shock protein 70 in mesenteric ischemia and reperfusion injury. J Surg Res. 144:36–42. 2008. View Article : Google Scholar : PubMed/NCBI

40 

Martin KR: The bioactive agent ergothioneine, a key component of dietary mushrooms, inhibits monocyte binding to endothelial cells characteristic of early cardiovascular disease. J Med Food. 13:1340–1346. 2010. View Article : Google Scholar : PubMed/NCBI

41 

Akanmu D, Cecchini R, Aruoma OI and Halliwell B: The antioxidant action of ergothioneine. Arch Biochem Biophys. 288:10–16. 1991. View Article : Google Scholar : PubMed/NCBI

42 

Cheah IK and Halliwell B: Ergothioneine; antioxidant potential, physiological function and role in disease. Biochim Biophys Acta. 1822:784–793. 2012. View Article : Google Scholar : PubMed/NCBI

43 

Peltekova VD, Wintle RF, Rubin LA, Amos CI, Huang Q, Gu X, Newman B, Van Oene M, Cescon D, Greenberg G, et al: Functional variants of OCTN cation transporter genes are associated with Crohn disease. Nat Genet. 36:471–475. 2004. View Article : Google Scholar : PubMed/NCBI

44 

Waller S, Tremelling M, Bredin F, Godfrey L, Howson J and Parkes M: Evidence for association of OCTN genes and IBD5 with ulcerative colitis. Gut. 55:809–814. 2006. View Article : Google Scholar : PubMed/NCBI

45 

Tokuhiro S, Yamada R, Chang X, Suzuki A, Kochi Y, Sawada T, Suzuki M, Nagasaki M, Ohtsuki M, Ono M, et al: An intronic SNP in a RUNX1 binding site of SLC22A4, encoding an organic cation transporter, is associated with rheumatoid arthritis. Nat Genet. 35:341–348. 2003. View Article : Google Scholar : PubMed/NCBI

46 

Santiago JL, Martínez A, de la Calle H, Fernández-Arquero M, Figueredo MA, de la Concha EG and Urcelay E: Evidence for the association of the SLC22A4 and SLC22A5 genes with type 1 diabetes: A case control study. BMC Med Genet. 7:542006. View Article : Google Scholar : PubMed/NCBI

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July 2015
Volume 3 Issue 4

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APA
Yamase, Y., Horibe, H., Ueyama, C., Fujimaki, T., Oguri, M., Kato, K. ... Yamada, Y. (2015). Association of TOMM40 and SLC22A4 polymorphisms with ischemic stroke. Biomedical Reports, 3, 491-498. https://doi.org/10.3892/br.2015.457
MLA
Yamase, Y., Horibe, H., Ueyama, C., Fujimaki, T., Oguri, M., Kato, K., Arai, M., Watanabe, S., Yamada, Y."Association of TOMM40 and SLC22A4 polymorphisms with ischemic stroke". Biomedical Reports 3.4 (2015): 491-498.
Chicago
Yamase, Y., Horibe, H., Ueyama, C., Fujimaki, T., Oguri, M., Kato, K., Arai, M., Watanabe, S., Yamada, Y."Association of TOMM40 and SLC22A4 polymorphisms with ischemic stroke". Biomedical Reports 3, no. 4 (2015): 491-498. https://doi.org/10.3892/br.2015.457