Diabetes Care
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Diabetes Care 29:2445-2451, 2006
DOI: 10.2337/dc06-0871
© 2006 by the American Diabetes Association
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Yamasaki, Y.
Right arrow Articles by Kuno, S.-i.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Yamasaki, Y.
Right arrow Articles by Kuno, S.-i.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Pathophysiology/Complications
Original Article

Combination of Multiple Genetic Risk Factors Is Synergistically Associated With Carotid Atherosclerosis in Japanese Subjects With Type 2 Diabetes

Yoshimitsu Yamasaki, MD, PHD1, Naoto Katakami, MD, PHD1, Ken’ya Sakamoto, MD, PHD1, Hideaki Kaneto, MD, PHD1, Munehide Matsuhisa, MD, PHD1, Hiroshi Sato, MD, PHD1, Masatsugu Hori, MD, PHD1, Masakazu Haneda, MD, PHD2, Atsunori Kashiwagi, MD, PHD3, Yasushi Tanaka, MD, PHD4, Ryuzo Kawamori, MD, PHD5 and Shin-ichi Kuno, PHD6,7

1 Department of Internal Medicine and Therapeutics, Osaka University Graduate School of Medicine, Osaka, Japan
2 Second Department of Medicine, Asahikawa Medical College, Asahikawa, Japan
3 Department of Medicine, Shiga University of Medical Science, Shiga, Japan
4 Division of Metabolism and Endocrinology, Department of Internal Medicine, St. Marianna University School of Medicine, Kawasaki, Japan
5 Department of Medicine, Metabolism and Endocrinology, Juntendo University School of Medicine, Tokyo, Japan
6 Translational Research Informatics Center, Foundation for Biomedical Research and Innovation, Kobe, Japan
7 Clinical Genome Informatics Center, Kobe University Graduate School of Medicine, Kobe, Japan

Address correspondence and reprint requests to Yoshimitsu Yamasaki, Internal Medicine and Therapeutics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita City, Osaka 565-0871, Japan. E-mail: yamasaki{at}medone.med.osaka-u.ac.jp


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS--
 CONCLUSIONS--
 References
 
OBJECTIVE— Several genetic risk factors, such as single nucleotide polymorphisms (SNPs), in candidate genes have been reported to be responsible for intima-media thickness (IMT), which is one of the surrogate end points of cardiovascular events. However, the synergistic effects of SNPs have not been evaluated in detail.

RESEARCH DESIGN AND METHODS— We measured the average IMT of the common and internal carotid artery in Japanese type 2 diabetic patients (n = 690) (>50 years old) using ultrasonography. We also determined their genotypes regarding 106 SNPs in candidate genes responsible for cardiovascular diseases. Among the 106 SNPs, we selected 40 common (frequency of minor allele ≥10%) SNPs. We compared the average IMT of subjects with and without any pairs of four genotypes selected from the 40 common SNPs.

RESULTS— The combination of methylen-tetrahydrofolate reductase 677 TT genotype and lymphotoxin-{alpha} (LTA) 252 GG genotype and that of ACE DD genotype and LTA 252 GG genotype were evaluated as responsible for a statistically significant (P = 2.7 x 10–9 and 3.5 x 10–6, respectively) increase in average IMT (mean [±SD] 1.54 ± 0.60 and 1.43 ± 0.58 mm, respectively) compared with those of the subjects without these combinations (1.04 ± 0.34 and 1.04 ± 0.34 mm, respectively). No single genotype was shown to be responsible for the statistically significant difference in average IMT after Bonferroni’s multiple comparison procedure.

CONCLUSIONS— The present analysis demonstrates an approach to evaluate combinations of multiple genetic risk factors that are synergistically associated with carotid atherosclerosis.

Abbreviations: IMT, intima-media thickness • LTA, lymphotoxin-{alpha} • MTHFR, methylene-tetrahydrofolate reductase • SNP, single nucleotide polymorphism • TNF, tumor necrosis factor


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESEARCH DESIGN AND METHODS
 RESULTS--
 CONCLUSIONS--
 References
 
In Westernized countries, a large proportion of the patients with diabetes die from cardiovascular diseases, mainly due to markedly advanced atherosclerosis (1). Although the risk of cardiovascular disease increases additively with the number of conventional risk factors, including diabetes, hypertension, and dyslipidemia, these conventional risk factors cannot fully account for the risk of cardiovascular diseases. Because atherosclerosis is a complex multifactorial and polygenic disorder that is thought to result from interactions among individual genetic risk factors and various environmental factors (2,3), to identify disease-susceptibility genes, genome-wide scanning of single nucleotide polymorphisms (SNPs) and candidate gene analyses have been performed. As a result, various single candidate genes and a locus involved in the predisposition to cardiovascular diseases have been identified (4–6). Although it is possible that some of these atherosclerosis-susceptibility gene polymorphisms are synergistically responsible for advanced atherosclerosis, few studies have reported on the involvement of a combination of potentially susceptible genes in cardiovascular diseases (6,7).

The objective of the present study was to identify specific combination(s) of single SNPs associated with carotid atherosclerosis of type 2 diabetic patients, which can be considered as a surrogate end point of cardiovascular events (8–10).


   RESEARCH DESIGN AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
RESULTS--
 CONCLUSIONS--
 References
 
The study enrolled type 2 diabetic subjects (n = 690, ≥50 years old) who visited the outpatient clinics of two participating hospitals (Osaka University Hospital and Juntendo University Hospital). The determination of type 2 diabetes was based on World Health Organization criteria. The patients’ characteristics are listed in Table 1. Smoking habit was evaluated as follows: value of 0 and 1 were assigned to subjects when the number of cigarettes per day x smoking years was <200 and ≥200, respectively.


View this table:
[in this window]
[in a new window]
  		Table 1— Patient characteristics

 
The study protocol was approved by the committees on the ethics of human research of Osaka University Graduate School of Medicine and Juntendo University School of Medicine.

Carotid atherosclerosis measurement
A series of ultrasonographic scannings of the carotid artery were performed using an echotomographic system (EUB-450; Hitachi Medico, Tokyo, Japan) with an electrical linear transducer (midfrequency of 7.5 MHz). All the images were photographed. The resolution limit of this system using 7.5 MHz was ~0.1 mm. The conventional B-mode imaging of the extracranial common carotid artery, the carotid bulb, and the internal carotid artery in the neck was performed bilaterally from three different longitudinal projections (i.e., anterior-oblique, lateral, and posterior-oblique) as well as the transverse projection, as reported previously (11,12). The carotid IMT was measured as the distance from the leading edge of the first echogenic line to the leading edge of the second echogenic line (13). Three determinations of IMT were conducted at the site of the greatest thickness and at two points, 1 cm upstream and 1 cm downstream from the site of the greatest thickness. These three values were averaged. The greatest value among the six averaged IMT (three from the left and three from the right) was used as the representative value (average IMT) for each individual. Physicians conducted all scans and different physicians performed the determinations of IMT using the photographs. The physicians were unaware of the clinical characteristics of the subjects. The reproducibility of the IMT measurements was examined by conducting another scan 1 week later on eight subjects. The mean difference in IMT between these two determinations was 0.01 mm and the SD was 0.04 mm, demonstrating good reproducibility of repeated measurements.

Assessment of other parameters
Fasting blood was withdrawn for analyses of serum total cholesterol, serum HDL cholesterol, serum triglyceride, plasma glucose, and HbA1c (A1C) levels by standard laboratory techniques. Blood pressure and BMIs were also measured. Examination for the occurrence of old myocardial infarction (major Q-QS changes) was performed based on the results of the resting 12-lead electrocardiogram and double Master two-step tests and the existence of previous symptoms of myocardial infarction (14).

Selection of SNPs
With the use of PubMed, we selected 106 candidate gene SNPs that are potentially associated with atherosclerosis, diabetes, hypertension, dyslipidemia, or diabetic microangiopathy (Table 2). Of these 106 polymorphisms, we selected 40 common SNPs in which the frequency of the minor allele was ≥10% of sample population.


View this table:
[in this window]
[in a new window]
  		Table 2— Polymorphisms of candidate genes analyzed (n = 106)

 
Genotyping of SNPs
Venous blood was collected from each subject and genomic DNA was isolated with a DNA isolation kit (Qiagen). The genotypes of the SNPs in each subject were determined with a fluorescence- or colorimetry-based allele-specific DNA-primer probe assay system (Toyobo Gene Analysis) as described in detail by Yamada et al. (5).

Statistical analysis
The data are expressed as means ± SD, and all statistical tests were two-sided. The Student’s t test was applied to compare the average IMT of subjects with and without the SNP genotype or the SNP combination.

Genotypes of 40 common SNPs were classified into two categories by four ways, including the major allele’s dominant model, minor allele’s dominant model, major allele’s recessive model, and minor allele’s recessive model. Then, 16 SNP combination models consisting of one combination from each category for the two SNPs and the set of the other combinations were also built. In each model, the continuous data of two of the categories were compared by Student’s t test. The categorical data of the two categories were compared by Pearson’s {chi}2 test. The data of age, systolic and diastolic blood pressure, and SNP combination as independent variables were also analyzed by multivariate regression analysis with the data of average IMT as a dependent variable. The association between SNP combination and the history of coronary heart disease was evaluated by the multiple logistic model.

Because the analyses were performed on the four models of 40 SNPs and 16 models of 780 SNP combinations, correction for multiple testing must be required. Bonferroni’s multiple comparison procedure was utilized for the correction and gave the corrected level of significance, 0.00031 [= 0.05/(40 x 4)] in the single SNP analyses and 4.01 x 10–6 [= 0.05/(40C2 x 16)] in the SNP combination analyses.

These statistical analyses were performed using the SAS statistical package (SAS/STAT 9.1; SAS Institute, Cary, NC).

Simulation for multiple comparisons
The significance level for multiple comparisons was evaluated also by simulation. In a simulation, the virtual average IMT values following the normal distribution with the mean of 1.05 and the SD of 0.35 from the whole enrolled members’ population were randomly assigned to all members. Next, the population of the enrolled members was randomly divided between the group with the genotypes’ combination (18) and the group without it (646 or 644) by 40C2x16 patterns. The simulations in which the P value by Student’s t test under the threshold (3.5 x 10–6 or 2.7 x 10–9) was observed at least once were regarded as false positive. The ratio of the false positive to the whole simulations was regarded as the P value for the whole analyses.


   RESULTS—
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS--
CONCLUSIONS--
 References
 
In the single SNP analyses, no SNPs were found to be significantly associated with average IMT (mean [±SD] 1.06 ± 0.35 mm) by Bonferroni’s multiple comparison procedure in any model, whereas the P values of the Student’s t test were less than the uncorrected level of significance (0.05) in seven SNPs, including the ACE DD genotype (1.13 ± 0.43 vs. 1.04 ± 0.34 mm, P = 0.03284), CD18 1323 CC and CT genotypes (1.07 ± 0.36 vs. 0.93 ± 0.24 mm, P = 0.01768), factor XII 46CC genotype (1.13 ± 0.40 vs. 1.05 ± 0.34 mm, P = 0.04173), glycoprotein Ia 807 TT and CT genotypes (1.08 ± 0.39 vs. 1.01 ± 0.29 mm, P = 0.01179), LTA 252 GG genotype (1.15 ± 0.42 vs. 1.04 ± 0.33 mm, P = 0.00109), methylene-tetrahydrofolate reductase (MTHFR) 677 TT genotype (1.15 ± 0.45 vs. 1.04 ± 0.33 mm, P = 0.00220), and vascular endothelial growth factor –634 GG genotype (1.10 ± 0.40 vs. 1.03 ± 0.33 mm, P = 0.01829).

Next, to investigate the association between average IMT and the combinations of potential susceptible genes, we compared the average IMT data of two categories classified by the combinations of SNP genotypes with Student’s t test. In 780 combinations of SNPs, only two genotype combinations including LTA 252 GG–MTFHR 677 TT (P = 2.7 x 10–9) and ACE DD–LTA 252 GG (P = 3.5 x 10–6) were found to be associated with a significant (P = 2.7 x 10–9 and 3.5 x 10–6, respectively) increase in average IMT (1.54 ± 0.60 and 1.43 ± 0.58 mm, respectively) compared with those of the subjects without these combinations (1.04 ± 0.34 and 1.04 ± 0.34 mm, respectively).

The characteristics of the patients with and without these two genotype combinations are shown in Table 3. The diabetic subjects with the combination of ACE DD and LTA 252 GG showed significantly higher systolic and diastolic blood pressure than those without this combination. However, multivariate regression analysis demonstrated that the combination of ACE DD and LTA 252 GG is still the independent determinant of average IMT (partial regression coefficient = 0.344 mm, F = 18.53, P = 0.00002) after adjustment of systolic and diastolic blood pressure. A multiple logistic model demonstrated that this genotype combination is significantly responsible for a high frequency of history of coronary heart disease (odds ratio 3.11 [95% CI 1.16–8.38], P = 0.0247).


View this table:
[in this window]
[in a new window]
  		Table 3— Patient characteristics of subjects with or without the two combinations of SNPs

 
The diabetic patients with the combination of LTA 252 GG and MTHFR 677 TT showed a significantly higher age and diastolic blood pressure than those without this combination (Table 3). However, multivariate regression analysis demonstrated that the combination of LTA 252 GG and MTHFR 677 TT is still the independent determinant of average IMT after adjustment of age and diastolic blood pressure (partial regression coefficient = 0.438 mm, F = 29.91, P = 6.43 x 10–8). A multiple logistic model demonstrated that this genotype combination was not significantly responsible for a high frequency of history of coronary heart disease.

Additionally, the P value for the each combination of genotypes was empirically evaluated by the simulation for multiple comparisons. The simulation indicated that P value of 3.5 x 10–6 for ACE DD and LTA 252 GG combination corresponded to the P value of 2.8 x 10–2 for the whole analysis, and P value of 2.7 x 10–9 for MTHFR 677 TT and LTA 252 GG combination was stricter than P value of 1.0 x 10–5 for the whole analysis.


   CONCLUSIONS—
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS--
 CONCLUSIONS--
References
 
In this study, we selected 106 candidate gene polymorphisms that may contribute to coronary heart disease, diabetes, and diabetes vascular complications. After genotyping of these candidate gene polymorphisms in all subjects, we found that 40 SNPs were relatively common (the frequency of the minor allele was ≥10%) in Japanese subjects with type 2 diabetes. Because multiple comparisons must be performed on these 40 SNPs in order to evaluate their association with carotid atherosclerosis, Bonferroni’s multiple comparison procedure was applied for statistical tests to control the family-wise type 1 error to <0.05.

In the single SNP analyses, we found that no single SNP genotypes were statistically significantly associated with carotid IMT after Bonferroni’s multiple comparison procedure. Although this procedure may be too strict to find out candidate SNP genotypes related to disease susceptibility, these results suggest the fact that any single candidate genotype is not critical in determining carotid IMT and that it is difficult to predict the risk of carotid atherosclerosis by simply diagnosing single SNP genotypes independently.

In the SNP combination analyses, two SNP combinations (MTHFR 677 TT genotype plus LTA 252 GG genotype and ACE DD genotype plus LTA 252 GG genotype) were found to be statistically (P < 4.01 x 10–6) significantly associated with carotid atherosclerosis in Japanese type 2 diabetic subjects after Bonferroni’s multiple comparison procedure.

LTA, formerly named tumor necrosis factor (TNF)-ß, is structurally similar to TNF-{alpha} and plays a crucial role in the inflammatory response by inducing monocyte migration and lymphocyte activation (4). Furthermore, reduction of atherosclerotic lesions was observed in LTA knockout mice but not in TNF-{alpha} knockout mice, suggesting that LTA is more important in the progression of atherosclerosis (15). It is known that the A252G polymorphism in the LTA gene is to an amino acid–coding polymorphism, leading to an increase of C-reactive protein, vascular cell adhesion molecule (VCAM)-1, and selectin E (4), all of which are closely associated with the inflammatory process and the progression of atherosclerosis. However, the association between the LTA polymorphism and the progression of atherosclerosis has yet to be reported. Hyperhomocysteinemia is well known to be an independent risk factor for atherosclerosis, and MTHFR is an enzyme that is involved in the remethylation of homocysteine to methionine (16,17). The MTHFR 677 TT genotype results in a reduction of MTHFR activity and an increase in serum homocysteine level, and thus is possibly involved in the progression of atherosclerosis (18,19). In this study, we could not find that the LTA 252 GG genotype or the MTHFR 677 TT genotype was significantly associated with average IMT. These results indicate that a polymorphism of each genotype alone is not enough to lead to a substantial progression of atherosclerosis and that it is very important to examine both polymorphisms when we estimate whether each subject is predisposed to atherosclerosis.

It is known that the insertion/deletion (I/D) polymorphism of the ACE gene is associated with the level of circulating ACE and that the highest plasma ACE levels are found in subjects with the DD genotype (20). Although the ACE I/D polymorphism possibly influences blood pressure regulation (21) and is involved in the progression of atherosclerosis, it still remains controversial as to whether this SNP actually contributes to the progression of atherosclerosis (20–25). In this study, this SNP was found not to be responsible for an increase in average IMT, and this SNP also did not affect systolic and diastolic blood pressures (data not shown). However, the combination of the ACE DD genotype and the LTA 252 GG genotype contributed to a statistically significant increase in average IMT, and the subjects with this combination showed significantly higher systolic and diastolic blood pressure. Under age-, systolic blood pressure–, and diastolic blood pressure–matched conditions, this combination was still associated with an increase in average IMT. In addition, this combination was significantly related with a high frequency of history of old myocardial infarction in these subjects. Although it remains unknown as to how such a combination of these gene polymorphisms exerts synergistic effects on carotid atherosclerosis and blood pressure, these results indicate that these two genotypes synergistically contribute to the progression of carotid atherosclerosis and predisposition of coronary heart disease partially by elevated blood pressure and that it is very important to examine these polymorphisms when we estimate the predisposition of each subject to atherosclerosis and coronary heart disease.

This cross-sectional study has shown that two synergistic combinations of SNPs predispose subjects with type 2 diabetes to carotid atherosclerosis and that one of these combinations is associated with coronary heart disease. A long-term follow-up study will be required to further establish these combinations of SNPs as responsible for an increased risk of carotid and coronary atherosclerosis.


   Acknowledgments
 
We are deeply indebted to Dr. Tadamitsu Kishimoto and Dr. Kouichi Yamanishi for their valuable suggestions. This work was partly supported by the Bio-Medical Cluster Project in Saito (northern part of Osaka prefecture), which is promoted by the Ministry of Education, Culture, Sports, Science and Technology, Japan.


   Footnotes
 
A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received for publication April 25, 2006. Accepted for publication August 4, 2006.


   References
TOP
 ABSTRACT
 INTRODUCTION
 RESEARCH DESIGN AND METHODS
 RESULTS--
 CONCLUSIONS--
 References
 

  1. Chait A, Bierman EL: Pathogenesis of macrovascular disease in diabetes. In Joslin’s Diabetes Mellitus. Kahn CR, Weir GC, Eds. Philadelphia, Lea & Febiger, 1994, p. 648–664
  2. Nabel EG: Cardiovascular disease. N Engl J Med 349:60–72, 2003[Free Full Text]
  3. Lusis AJ, Fogelman AM, Fonarow GC: Genetic basis of atherosclerosis. II. Clinical implications. Circulation 110:2066–2071, 2004[Free Full Text]
  4. Ozaki K, Ohnishi Y, Iida A, Sekine A, Yamada R, Tsunoda T, Sato H, Sato H, Hori M, Nakamura Y, Tanaka T: Functional SNPs in the lymphotoxin-{alpha} gene that are associated with susceptibility to myocardial infarction. Nat Genet 32:650–654, 2002[Medline]
  5. Yamada Y, Izawa H, Ichihara S, Takatsu F, Ishihara H, Hirayama H, Sone T, Tanaka M, Yokota M: Prediction of the risk of myocardial infarction from polymorphisms in candidate genes. N Engl J Med 347:1916–1923, 2002[Abstract/Free Full Text]
  6. Small KM, Wagoner LE, Levin AM, Kardia SL, Liggett SB: Synergistic polymorphisms of {alpha}1- and ß2c-adrenergic receptors and the risk of congestive heart failure. N Engl J Med 347:1135–1142, 2002[Abstract/Free Full Text]
  7. Nakata Y, Katsuya T, Rakugi H, Takami S, Sato N, Kamide K, Ohishi M, Miki T, HIgaki J, Ogihara T: Polymorphism of angiotensin converting enzyme, angiotensinogen, and apolipoprotein E genes in a Japanese population with cerebrovascular disease. Am J Hypertens 10:1391–1395, 1997[Medline]
  8. Chambless LE, Heiss G, Folsom AR, Rosamond W, Szklo M, Sharrett AR, Clegg LX: Association of coronary heart disease incidence with carotid arterial wall thickness and major risk factors: the Atherosclerosis Risk in Communities (ARIC) Study, 1987–1993. Am J Epidemiol 146:483–494, 1997[Abstract/Free Full Text]
  9. Hodis HN, Mack WJ, LaBree L, Selzer RH, Liu CR, Liu CH, Azen SP: The role of carotid arterial intima-media thickness in predicting clinical coronary events. Ann Intern Med 128:262–269, 1998[Abstract/Free Full Text]
  10. O’Leary DH, Polak JF, Kronmal RA, Manolio TA, Burke GL, Wolfson SK Jr, the Cardiovascular Health Study Collaborative Research Group: Carotid-artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults. N Engl J Med 340:14–22, 1999[Abstract/Free Full Text]
  11. Kawamori R, Yamasaki Y, Matsushima H, Nishizawa H, Nao K, Hougaku H, Maeda H, Handa N, Matsumoto M, Kamada T: Prevalence of carotid atherosclerosis in diabetic patients: ultrasound high-resolution B-mode imaging on carotid arteries. Diabetes Care 15:1290–1294, 1992[Abstract]
  12. Yamasaki Y, Kawamori R, Matsushima H, Nishizawa H, Kodama M, Kajimoto Y, Morishima T, Kamada T: Atherosclerosis in carotid artery of young IDDM patients monitored by ultrasound high-resolution B-mode imaging. Diabetes 43:634–639, 1994[Abstract]
  13. Pignoli P, Tremoli E, Poli A, Oreste P, Paoletti R: Intimal plus medial thickness of the arterial wall: a direct measurement with ultrasound imaging. Circulation 74:1399–1406, 1986[Abstract/Free Full Text]
  14. Simonson E, Keys A: The electrocardiographic exercise test: changes in scalar ECG and in mean spatial QRS and T vectors in two types of exercise: effect of absolute and relative body weight and comment on normal standards. Am Heart J 52:83–105, 1956[Medline]
  15. Schreyer SA, Vick GM, LeBoeuf RC: Loss of lymphotoxin-alpha but not tumor necrosis factor-alpha reduces atherosclerosis in mice. J Biol Chem 277:12364–12368, 2002[Abstract/Free Full Text]
  16. Robinson K, Mayer EL, Miller DP, Green R, van Lente F, Gupta A, Kottke-Marchant K, Savon SR, Selhub J, Nissen SE, Kutner M, Topol EJ, Jacobsen DW: Hyperhomocysteinemia and low pyridoxal phosphate: common and independent reversible risk factors for coronary artery disease. Circulation 92:2825–2830, 1995[Abstract/Free Full Text]
  17. Boushey CJ, Beresford SA, Omenn GS, Motulsky AG: A quantitative assessment of plasma homocysteine as a risk factor for vascular disease: probable benefits of increasing folic acid intakes. JAMA 274:1049–1057, 1995[Abstract]
  18. Christensen B, Frosst P, Lussier-Cacan S, Selhub J, Goyette P, Rosenblatt DS, Genest J Jr, Rozen R: Correlation of a common mutation in the methylenetetrahydrofolate reductase gene with plasma homocysteine in patients with premature coronary artery disease. Arterioscler Thromb Vasc Biol 17:569–573, 1997[Abstract/Free Full Text]
  19. Arai K, Yamasaki Y, Kajimoto Y, Watada H, Umayahara Y, Kodama M, Sakamoto K, Hori M: Association of methylenetetrahydrofolate reductase gene polymorphism with carotid arterial wall thickening and myocardial infarction risk in NIDDM. Diabetes 46:2102–2104, 1997[Medline]
  20. Rigat B, Hubert C, Alhenc-Gelas F, Cambien F, Corvol P, Soubrier F: An insertion/deletion polymorphism in angiotensin I-converting enzyme gene accounting for half the variance of serum enzyme levels. J Clin Invest 86:1343–1346, 1990[Medline]
  21. Frost D, Pfohl M, Clemens P, Haring HU, Beischer W: Evaluation of the insertion/deletion ACE gene polymorphism as a risk factor for carotid artery intima-media thickening and hypertension in young type 1 diabetic patients. Diabetes Care 21:836–840, 1998[Abstract]
  22. Mannami T, Katsuya T, Baba S, Inamoto N, Ishikawa K, Higaki J, Ogihara T, Ogata J: Low potentiality of angiotensin-converting enzyme gene insertion/deletion polymorphism as a useful predictive marker for carotid atherogenesis in a large general population of a Japanese city: the Suita Study. Stroke 32:1250–1256, 2001[Abstract/Free Full Text]
  23. Kogawa K, Nishizawa Y, Hosoi M, Kawagishi T, Maekawa K, Shoji T, Okuno Y, Horii H: Effect of polymorphism of apolipoprotein E and angiotensin-converting enzyme genes on arterial wall thickness. Diabetes 46:682–687, 1997[Abstract]
  24. Rasmussen LM, Ledet T: Aortic atherosclerosis in diabetes mellitus is associated with an insertion/deletion polymorphism in the angiotensin I-converting enzyme gene: no relation between the polymorphism and aortic collagen content. Diabetologia 39:696–700, 1996[Medline]
  25. Yamasaki Y, Tsujino T, Kodama M, Kajimoto Y: DD genotype of the ACE gene as an atherosclerosis-independent risk factor for myocardial infarction. Circulation 96:3782, 1997

Add to CiteULike CiteULike   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?



This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Request Permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Yamasaki, Y.
Right arrow Articles by Kuno, S.-i.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Yamasaki, Y.
Right arrow Articles by Kuno, S.-i.
Social Bookmarking
Add to CiteULike   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Diabetes Diabetes Care Clinical Diabetes Diabetes Spectrum