- Email: [email protected]
Transforming growth factor β1 T868C gene polymorphism is associated with cerebral infarction in Japanese patients with type 2 diabetes
diabetes research and clinical practice 94 (2011) e57–e60
Contents lists available at ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Brief report
Transforming growth factor b1 T868C gene polymorphism is associated with cerebral infarction in Japanese patients with type 2 diabetes N. Katakami a,b,*, H. Kaneto a, T. Osonoi c, K. Kawai d, F. Ishibashi e, K. Imamura f, H. Maegawa g, A. Kashiwagi h, H. Watada i, R. Kawamori j, I. Shimomura a, Y. Yamasaki k a
Department of Metabolic Medicine, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan Department of Metabolism and Atherosclerosis, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan c Naka Memorial Clinic, 745-5, Nakadai, Naka City, Ibaraki 311-0113, Japan d Kawai Clinic, 715-1, Higashihiratsuka, Tsukuba, Ibaraki 305-0812, Japan e Ishibashi Clinic, 1-9-41-2, Kushido, Hatsukaichi, Hiroshima 738-0033, Japan f Imamura Clinic, 2-1, Matsubara, Hirosaki, Aomori 036-8142, Japan g Division of Endocrinology and Metabolism, Department of Medicine, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2121, Japan h Shiga University of Medical Science Hospital, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan i Department of Medicine, Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, 2-1-1, Hongou, Bunkyo-ku, Tokyo 113-8431, Japan j Sportology Center, Juntendo University Graduate School of Medicine, 2-1-1, Hongou, Bunkyo-ku, Tokyo 113-8431, Japan k Center for Advanced Science and Innovation, Osaka University, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan b
article info
abstract
Article history:
It is likely that the C allele of the polymorphism at position 29 of the translated sequence of
Received 25 July 2011
transforming growth factor (TGF)-b1 gene, which codes a pleiotropic cytokine expressed in a
Accepted 1 August 2011
variety of cells, is a susceptibility allele for cerebral infarction in Japanese type 2 diabetic
Published on line 31 August 2011
patients. # 2011 Elsevier Ireland Ltd. All rights reserved.
Keywords: TGF-b1 Cerebral infarction Polymorphism Diabetes
* Corresponding author at: Department of Metabolic Medicine, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan. Tel.: +81 6 6879 3743; fax: +81 6 6879 3739. E-mail address: [email protected] (N. Katakami). 0168-8227/$ – see front matter # 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.diabres.2011.08.005
e58
1.
diabetes research and clinical practice 94 (2011) e57–e60
Introduction
Transforming growth factor (TGF)-b1, a pleiotropic cytokine expressed in a variety of cells, including platelets, connective, haematopoietic and endothelial tissue cells [1], has both pro-atherogenic and anti-atherogenic functions [2–10]. The T868C polymorphism (rs1982073), located at position 29 of the translated sequence of TGF-b1 gene, generates amino acid substitution at position 10 (Leu10Pro) in the signal peptide sequence and the C allele has been reported to be associated with an increased expression of TGF-b1mRNA and higher levels of serum TGF-b1 [11,12]. However, there have been very few studies on the association of this polymorphism and the risk of cerebral infarction (CI) and the results of these studies remain controversial [13,14]. In this study, therefore, we examined the relationship between TGF-b1 gene T868C polymorphism and CI in a large cohort of Japanese type 2 diabetic patients.
2.
Methods
Japanese type 2 diabetic subjects aged 40 attending the outpatient clinics of diabetes were asked to participate in this study. After all, a total of 3793 subjects were enrolled. The study protocol was approved by the committees on the ethics of human research of Osaka University Graduate School of Medicine. A written informed consent was obtained from all the participants.
Fasting blood samples were collected and HbA1c, serum total and HDL cholesterol, and triglyceride levels were measured. The determination of hypertension (defined as systolic blood pressure (SBP) 130 mmHg or diastolic blood pressure (DBP) 80 mmHg or having been treated for hypertension) and dyslipidemia (defined as serum LDL cholesterol 120 mg/dl or serum triglyceride (TG) 150 mg/dl or HDLcholesterol < 40 mg/dl or having been treated for dyslipidemia) was based on the Japan Diabetes Society’s criteria. The diagnosis of cerebral infarction was performed based on history, physical examination, and neuroimaging (CT, MRI, or both), according to the traditional World Health Organization criteria of stroke. The patients’ characteristics and their medication are listed in Table 1. The genotypes of the TGF-b1 gene T868C polymorphism were determined with a fluorescence- or colorimetry-based allele-specific DNA-primer probe assay system as previously described [15]. The average genotyping success rate was 99.7% and the genotyping accuracy was 100%, which was determined from the genotype concordance between 513 duplicate samples. In the major allele’s dominant and recessive genetic models, the associations between the polymorphism and variables were evaluated by the unpaired t test or x2 test. In the major allele’s additive genetic model, the associations between the polymorphism and variables were evaluated with the Cochran–Armitage test. Multiple logistic regression analyses were performed to evaluate the relationship between the prevalence of CI and the following variables: gender, age, smoking status, BMI, HbA1c, duration of diabetes, prevalence
Table 1 – Clinical characteristics of the subjects. T868C polymorphism of the TGF-b1 gene
Gender (female/male) Age (years) Duration of diabetes (years) Smoking (B.I. 200) Body mass index (kg/m2) HbA1C (%) Presence of hypertension (%) Presence of dyslipidemia (%) Treatment approach for diabetes Diet alone Using OHA Sulfonylureas Thiazolidinediones Biguanides Using insulin Treatment approach for dyslipidemia Using statins Using other drugs Presence of cerebral infarction (%)
Total (n = 3793)
T/T (n = 1003)
C/T (n = 1859)
Associations with the polymorphism
C/C (n = 931)
Dominant model
Recessive model
Additive model
1492/2301 61.5 8.4 8.0 7.5 1756 (46.2) 24.1 3.5 7.1 1.2 2846 (75.0) 2948 (77.7)
398/605 61.8 8.5 8.7 7.5 472 (47.1) 23.9 3.5 7.0 1.3 736 (73.4) 791 (78.9)
727/1132 62.0 8.4 8.5 7.9 849 (45.7) 24.0 3.5 7.1 1.3 1393 (74.9) 1430 (76.9)
367/564 61.9 8.2 8.6 8.0 435 (46.7) 24.0 3.5 7.0 1.2 714 (76.7) 727 (78.1)
NS NS NS NS NS NS NS NS
NS NS NS NS NS NS NS NS
NS NS NS NS NS NS NS NS
988 (26.0) 2388 (63.0) 1216 (32.1) 391 (10.3) 1139 (30.0) 866 (22.8)
282 (28.1) 608 (60.6) 307 (30.6) 94 (9.4) 279 (27.8) 221 (22.0)
474 (25.5) 1189 (64.0) 596 (32.1) 201 (10.8) 564 (30.3) 427 (23.0)
232 (24.9) 591 (63.5) 313 (33.6) 96 (10.3) 296 (21.8) 218 (23.4)
NS NS NS NS NS NS
NS NS NS NS NS NS
NS NS NS NS NS NS
1014 (26.7) 178 (4.7) 331 (8.7)
271 (27.0) 44 (4.4) 68 (6.8)
496 (26.7) 89 (4.8) 170 (9.1)
247 (26.5) 45 (4.8) 93 (10.0)
NS NS NS
NS NS p = 0.0109
NS NS p = 0.0117
Data are shown as numbers (%) or means SD. In the dominant and the recessive genetic models, quantitative data between 2 groups were compared by the 2-tailed unpaired t test and categorical data were analyzed with the x2 test. In the additive genetic model, the associations between the polymorphism and variables were evaluated with one-way ANOVA or the Cochran–Armitage test. p-values over 0.05 were displayed as NS. NS, not significant; B.I., Brinkman’s index; OHA, oral hypoglycemic agent.
diabetes research and clinical practice 94 (2011) e57–e60
Table 2 – Multivariate logistic regression analysis to identify independent determinants for cerebral infarction. Parameters Gender (female) Age (years) Body mass index (kg/m2) Duration of diabetes (years) HbA1c (%) Presence of hypertension Presence of dyslipidemia Smoking (B.I. 200) 868C allele
Odds ratio (95%CI) 0.82 1.13 1.03 0.91 0.98 2.37 0.99 1.81 1.23
(0.60–1.12) (1.11–1.15) (0.99–1.07) (0.89–0.93) (0.89–1.09) (1.66–3.38) (0.74–1.31) (1.34–2.45) (1.04–1.46)
p value NS <0.0001 NS <0.0001 NS <0.0001 NS 0.0001 0.0158
Multivariate logistic regression analysis was done for 3793 type 2 diabetic patients to select variables significantly associated with an increase in the risk of cerebral infarction. The threshold of statistical significance was defined as p < 0.05. NS, not significant; B.I., Brinkman’s index.
of hypertension, prevalence of dyslipidemia, and the number of C alleles of TGF-b1 T868C polymorphism. For these, the p value for the inclusion and exclusion of variables was set at 0.05.
3.
Results
Table 1 shows the general characteristics and the prevalence of CI of the subjects. The prevalence of the T868C genotypes was as follows: TT, 26.4%; CT, 49.0%; CC, 24.5%; and the genotype distribution was in Hardy–Weinberg equilibrium. The frequency of C allele was significantly higher in subjects with CI as compared to those without it (53.8% vs. 48.6%, p = 0.0109). The prevalence of CI tended to be higher as the number of C alleles increased [TT (6.8%), CT (9.1%), CC (10.0%), p value for trend = 0.0117] and was significantly higher in subjects with CC or CT genotype compared to those with TT genotype (9.4% vs. 6.8%, p = 0.0109). However, there were no associations between this polymorphism and the other parameters including gender, age, smoking status, BMI, HbA1c, duration of diabetes, presence of hypertension, presence of dyslipidemia, and administration of drugs. Furthermore, in a multiple logistic regression model, the number of C alleles was significantly associated with CI even after adjustment for conventional risk factors (odds ratio (OR) for 1-point increase in the number C allele = 1.23 with 95%CI 1.04–1.46, p = 0.0158) (Table 2). In addition, compared to the subjects without C alleles, the subjects with C alleles had a significantly higher risk of CI (OR 1.40 with 95%CI 1.04–1.87, p = 0.024) even after adjusting other clinical variables.
4.
Discussion
This is the first report to examine the relationship of TGF-b1 T868C polymorphism and CI in a large cohort of Japanese type 2 diabetic patients. The increased risk of CI associated with the presence of the C allele observed in the present study is in accordance with the functional studies showing that the C allele is associated with an increased expression of
e59
TGF-b1mRNA and serum TGF-b1 levels [11,12] and that high level of TGF-b1 accelerates the process of atherosclerosis and thrombosis leading to CI [7–10]. Our findings were consistent with the results of the Rotterdam study, a large population-based study on the Caucasian cohort, demonstrating that C allele carriers were at increased risk for CI when compared with noncarriers [13] but inconsistent with a case–control study in Korean subjects claiming that T allele might be a risk factor for ischemic stroke [14]. Differences in particular characteristics between the study samples may have accounted for the opposite results. Heterogeneities in the prevalence of the conventional risk factors for CI may have also contributed to the divergent results among the studies. Indeed, all subjects in the present study had type 2 diabetes and the prevalence of dyslipidemia was much higher as compared to the Korean study (77.7% vs. 22.2%). Ethnic difference may have also contributed to this discrepancy. It should be noted that a long-term follow-up study is necessary to confirm the hypothesis that this polymorphism affects the development of CI in Japanese type 2 diabetic subjects, since the present analysis was performed based on cross-sectional data. It should be also noted that the possibility exists that the positive association findings shown here were not based on real effects of SNP, but rather influenced by unknown differences in population ancestry between the case and control groups, although we consider the probability of false-positive inference attributable to population stratification rather small, because the subjects with and without CI were recruited from an ethnically homogeneous population. In conclusion, it is likely that the C allele of the TGF-b1 gene T868C polymorphism is a susceptibility allele for CI in Japanese type 2 diabetic patients.
Conflict of interest The authors declare that they have no conflict of interest.
references
[1] Blobe GC, Schiemann WP, Lodish HF. Role of transforming growth factor beta in human disease. N Engl J Med 2000;342:1350–8. [2] Singh NN, Ramji DP. The role of transforming growth factor-beta in atherosclerosis. Cytokine Growth Factor Rev 2006;17:487–99. [3] Metcalfe JC, Grainger DJ. Transforming growth factor-b and the protection from cardiovascular injury hypothesis. Biochem Soc Trans 1995;23:403–6. [4] Grainger DJ, Kemp PR, Liu AC, Lawn RM, Metcalfe JC. Activation of transforming growth factor-b is inhibited in transgenic apolipoprotein (a) mice. Nature 1994;370:460–2. [5] Robertson AK, Rudling M, Zhou X, Gorelik L, Flavell RA, Hansson GK. Disruption of TGF-b signaling in T cells accelerates atherosclerosis. J Clin Invest 2003;112:1342–50. [6] Cipollone F, Fazia M, Mincione G, Iezzi A, Pini B, Cuccurullo C, et al. Increased expression of transforming growth factor-b1 as a stabilizing factor in human atherosclerotic plaques. Stroke 2004;35:2253–7.
e60
diabetes research and clinical practice 94 (2011) e57–e60
[7] Nikol S, Isner JM, Pickering JG, Kearney M, Leclerc G, Weir L. Expression of transforming growth factor-b1 is increased in human vascular restenosis lesions. J Clin Invest 1992;90:1582–92. [8] Ohji T, Urano H, Shirahata A, Yamagishi M, Higashi K, Gotoh S, et al. Transforming growth factor-b1 and -b2 induce downmodulation of thrombomodulin in human umbilical vein endothelial cells. Thromb Haemost 1995;73:812–8. [9] Wolf YG, Rasmussen LM, Ruoslahti E. Antibodies against transforming growth factor-b1 suppress intimal hyperplasia in a rat model. J Clin Invest 1994;93:1172–8. [10] Kanzaki T, Tamura K, Takahashi K, Saito Y, Akikusa B, Oohashi H, et al. In vivo effect of TGF-b1: enhanced intimal thickening by administration of TGF-b1 in rabbit arteries injured with a balloon catheter. Arterioscler Thromb Vasc Biol 1995;15:1951–7. [11] Suthanthiran M, Li B, Song JO, Ding R, Sharma VK, Schwartz JE, et al. Transforming growth factor-b1
[12]
[13]
[14]
[15]
hyperexpression in African-American hypertensives: a novel mediator of hypertension and/or target organ damage. Proc Natl Acad Sci USA 2000;97:3479–84. Yokota M, Ichihara S, Lin TL, Nakashima N, Yamada Y. Association of a T29 > C polymorphism of the transforming growth factor-beta1 gene with genetic susceptibility to myocardial infarction in Japanese. Circulation 2000;101:2783–7. Sie MP, Uitterlinden AG, Bos MJ, Arp PP, Breteler MM, Koudstaal PJ, et al. TGF-beta 1 polymorphisms and risk of myocardial infarction and stroke: the Rotterdam Study. Stroke 2006;37:2667–71. Kim Y, Lee C. The gene encoding transforming growth factor beta 1 confers risk of ischemic stroke and vascular dementia. Stroke 2006;37:2843–5. Yamada Y, Izawa H, Ichihara S, Takatsu F, Ishihara H, Hirayama H, et al. Prediction of the risk of myocardial infarction from polymorphisms in candidate genes. N Engl J Med 2002;347:1916–23.
Contents lists available at ScienceDirect
Diabetes Research and Clinical Practice journ al h ome pa ge : www .elsevier.co m/lo cate/diabres
Brief report
Transforming growth factor b1 T868C gene polymorphism is associated with cerebral infarction in Japanese patients with type 2 diabetes N. Katakami a,b,*, H. Kaneto a, T. Osonoi c, K. Kawai d, F. Ishibashi e, K. Imamura f, H. Maegawa g, A. Kashiwagi h, H. Watada i, R. Kawamori j, I. Shimomura a, Y. Yamasaki k a
Department of Metabolic Medicine, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan Department of Metabolism and Atherosclerosis, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan c Naka Memorial Clinic, 745-5, Nakadai, Naka City, Ibaraki 311-0113, Japan d Kawai Clinic, 715-1, Higashihiratsuka, Tsukuba, Ibaraki 305-0812, Japan e Ishibashi Clinic, 1-9-41-2, Kushido, Hatsukaichi, Hiroshima 738-0033, Japan f Imamura Clinic, 2-1, Matsubara, Hirosaki, Aomori 036-8142, Japan g Division of Endocrinology and Metabolism, Department of Medicine, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2121, Japan h Shiga University of Medical Science Hospital, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan i Department of Medicine, Metabolism and Endocrinology, Juntendo University Graduate School of Medicine, 2-1-1, Hongou, Bunkyo-ku, Tokyo 113-8431, Japan j Sportology Center, Juntendo University Graduate School of Medicine, 2-1-1, Hongou, Bunkyo-ku, Tokyo 113-8431, Japan k Center for Advanced Science and Innovation, Osaka University, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan b
article info
abstract
Article history:
It is likely that the C allele of the polymorphism at position 29 of the translated sequence of
Received 25 July 2011
transforming growth factor (TGF)-b1 gene, which codes a pleiotropic cytokine expressed in a
Accepted 1 August 2011
variety of cells, is a susceptibility allele for cerebral infarction in Japanese type 2 diabetic
Published on line 31 August 2011
patients. # 2011 Elsevier Ireland Ltd. All rights reserved.
Keywords: TGF-b1 Cerebral infarction Polymorphism Diabetes
* Corresponding author at: Department of Metabolic Medicine, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan. Tel.: +81 6 6879 3743; fax: +81 6 6879 3739. E-mail address: [email protected] (N. Katakami). 0168-8227/$ – see front matter # 2011 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.diabres.2011.08.005
e58
1.
diabetes research and clinical practice 94 (2011) e57–e60
Introduction
Transforming growth factor (TGF)-b1, a pleiotropic cytokine expressed in a variety of cells, including platelets, connective, haematopoietic and endothelial tissue cells [1], has both pro-atherogenic and anti-atherogenic functions [2–10]. The T868C polymorphism (rs1982073), located at position 29 of the translated sequence of TGF-b1 gene, generates amino acid substitution at position 10 (Leu10Pro) in the signal peptide sequence and the C allele has been reported to be associated with an increased expression of TGF-b1mRNA and higher levels of serum TGF-b1 [11,12]. However, there have been very few studies on the association of this polymorphism and the risk of cerebral infarction (CI) and the results of these studies remain controversial [13,14]. In this study, therefore, we examined the relationship between TGF-b1 gene T868C polymorphism and CI in a large cohort of Japanese type 2 diabetic patients.
2.
Methods
Japanese type 2 diabetic subjects aged 40 attending the outpatient clinics of diabetes were asked to participate in this study. After all, a total of 3793 subjects were enrolled. The study protocol was approved by the committees on the ethics of human research of Osaka University Graduate School of Medicine. A written informed consent was obtained from all the participants.
Fasting blood samples were collected and HbA1c, serum total and HDL cholesterol, and triglyceride levels were measured. The determination of hypertension (defined as systolic blood pressure (SBP) 130 mmHg or diastolic blood pressure (DBP) 80 mmHg or having been treated for hypertension) and dyslipidemia (defined as serum LDL cholesterol 120 mg/dl or serum triglyceride (TG) 150 mg/dl or HDLcholesterol < 40 mg/dl or having been treated for dyslipidemia) was based on the Japan Diabetes Society’s criteria. The diagnosis of cerebral infarction was performed based on history, physical examination, and neuroimaging (CT, MRI, or both), according to the traditional World Health Organization criteria of stroke. The patients’ characteristics and their medication are listed in Table 1. The genotypes of the TGF-b1 gene T868C polymorphism were determined with a fluorescence- or colorimetry-based allele-specific DNA-primer probe assay system as previously described [15]. The average genotyping success rate was 99.7% and the genotyping accuracy was 100%, which was determined from the genotype concordance between 513 duplicate samples. In the major allele’s dominant and recessive genetic models, the associations between the polymorphism and variables were evaluated by the unpaired t test or x2 test. In the major allele’s additive genetic model, the associations between the polymorphism and variables were evaluated with the Cochran–Armitage test. Multiple logistic regression analyses were performed to evaluate the relationship between the prevalence of CI and the following variables: gender, age, smoking status, BMI, HbA1c, duration of diabetes, prevalence
Table 1 – Clinical characteristics of the subjects. T868C polymorphism of the TGF-b1 gene
Gender (female/male) Age (years) Duration of diabetes (years) Smoking (B.I. 200) Body mass index (kg/m2) HbA1C (%) Presence of hypertension (%) Presence of dyslipidemia (%) Treatment approach for diabetes Diet alone Using OHA Sulfonylureas Thiazolidinediones Biguanides Using insulin Treatment approach for dyslipidemia Using statins Using other drugs Presence of cerebral infarction (%)
Total (n = 3793)
T/T (n = 1003)
C/T (n = 1859)
Associations with the polymorphism
C/C (n = 931)
Dominant model
Recessive model
Additive model
1492/2301 61.5 8.4 8.0 7.5 1756 (46.2) 24.1 3.5 7.1 1.2 2846 (75.0) 2948 (77.7)
398/605 61.8 8.5 8.7 7.5 472 (47.1) 23.9 3.5 7.0 1.3 736 (73.4) 791 (78.9)
727/1132 62.0 8.4 8.5 7.9 849 (45.7) 24.0 3.5 7.1 1.3 1393 (74.9) 1430 (76.9)
367/564 61.9 8.2 8.6 8.0 435 (46.7) 24.0 3.5 7.0 1.2 714 (76.7) 727 (78.1)
NS NS NS NS NS NS NS NS
NS NS NS NS NS NS NS NS
NS NS NS NS NS NS NS NS
988 (26.0) 2388 (63.0) 1216 (32.1) 391 (10.3) 1139 (30.0) 866 (22.8)
282 (28.1) 608 (60.6) 307 (30.6) 94 (9.4) 279 (27.8) 221 (22.0)
474 (25.5) 1189 (64.0) 596 (32.1) 201 (10.8) 564 (30.3) 427 (23.0)
232 (24.9) 591 (63.5) 313 (33.6) 96 (10.3) 296 (21.8) 218 (23.4)
NS NS NS NS NS NS
NS NS NS NS NS NS
NS NS NS NS NS NS
1014 (26.7) 178 (4.7) 331 (8.7)
271 (27.0) 44 (4.4) 68 (6.8)
496 (26.7) 89 (4.8) 170 (9.1)
247 (26.5) 45 (4.8) 93 (10.0)
NS NS NS
NS NS p = 0.0109
NS NS p = 0.0117
Data are shown as numbers (%) or means SD. In the dominant and the recessive genetic models, quantitative data between 2 groups were compared by the 2-tailed unpaired t test and categorical data were analyzed with the x2 test. In the additive genetic model, the associations between the polymorphism and variables were evaluated with one-way ANOVA or the Cochran–Armitage test. p-values over 0.05 were displayed as NS. NS, not significant; B.I., Brinkman’s index; OHA, oral hypoglycemic agent.
diabetes research and clinical practice 94 (2011) e57–e60
Table 2 – Multivariate logistic regression analysis to identify independent determinants for cerebral infarction. Parameters Gender (female) Age (years) Body mass index (kg/m2) Duration of diabetes (years) HbA1c (%) Presence of hypertension Presence of dyslipidemia Smoking (B.I. 200) 868C allele
Odds ratio (95%CI) 0.82 1.13 1.03 0.91 0.98 2.37 0.99 1.81 1.23
(0.60–1.12) (1.11–1.15) (0.99–1.07) (0.89–0.93) (0.89–1.09) (1.66–3.38) (0.74–1.31) (1.34–2.45) (1.04–1.46)
p value NS <0.0001 NS <0.0001 NS <0.0001 NS 0.0001 0.0158
Multivariate logistic regression analysis was done for 3793 type 2 diabetic patients to select variables significantly associated with an increase in the risk of cerebral infarction. The threshold of statistical significance was defined as p < 0.05. NS, not significant; B.I., Brinkman’s index.
of hypertension, prevalence of dyslipidemia, and the number of C alleles of TGF-b1 T868C polymorphism. For these, the p value for the inclusion and exclusion of variables was set at 0.05.
3.
Results
Table 1 shows the general characteristics and the prevalence of CI of the subjects. The prevalence of the T868C genotypes was as follows: TT, 26.4%; CT, 49.0%; CC, 24.5%; and the genotype distribution was in Hardy–Weinberg equilibrium. The frequency of C allele was significantly higher in subjects with CI as compared to those without it (53.8% vs. 48.6%, p = 0.0109). The prevalence of CI tended to be higher as the number of C alleles increased [TT (6.8%), CT (9.1%), CC (10.0%), p value for trend = 0.0117] and was significantly higher in subjects with CC or CT genotype compared to those with TT genotype (9.4% vs. 6.8%, p = 0.0109). However, there were no associations between this polymorphism and the other parameters including gender, age, smoking status, BMI, HbA1c, duration of diabetes, presence of hypertension, presence of dyslipidemia, and administration of drugs. Furthermore, in a multiple logistic regression model, the number of C alleles was significantly associated with CI even after adjustment for conventional risk factors (odds ratio (OR) for 1-point increase in the number C allele = 1.23 with 95%CI 1.04–1.46, p = 0.0158) (Table 2). In addition, compared to the subjects without C alleles, the subjects with C alleles had a significantly higher risk of CI (OR 1.40 with 95%CI 1.04–1.87, p = 0.024) even after adjusting other clinical variables.
4.
Discussion
This is the first report to examine the relationship of TGF-b1 T868C polymorphism and CI in a large cohort of Japanese type 2 diabetic patients. The increased risk of CI associated with the presence of the C allele observed in the present study is in accordance with the functional studies showing that the C allele is associated with an increased expression of
e59
TGF-b1mRNA and serum TGF-b1 levels [11,12] and that high level of TGF-b1 accelerates the process of atherosclerosis and thrombosis leading to CI [7–10]. Our findings were consistent with the results of the Rotterdam study, a large population-based study on the Caucasian cohort, demonstrating that C allele carriers were at increased risk for CI when compared with noncarriers [13] but inconsistent with a case–control study in Korean subjects claiming that T allele might be a risk factor for ischemic stroke [14]. Differences in particular characteristics between the study samples may have accounted for the opposite results. Heterogeneities in the prevalence of the conventional risk factors for CI may have also contributed to the divergent results among the studies. Indeed, all subjects in the present study had type 2 diabetes and the prevalence of dyslipidemia was much higher as compared to the Korean study (77.7% vs. 22.2%). Ethnic difference may have also contributed to this discrepancy. It should be noted that a long-term follow-up study is necessary to confirm the hypothesis that this polymorphism affects the development of CI in Japanese type 2 diabetic subjects, since the present analysis was performed based on cross-sectional data. It should be also noted that the possibility exists that the positive association findings shown here were not based on real effects of SNP, but rather influenced by unknown differences in population ancestry between the case and control groups, although we consider the probability of false-positive inference attributable to population stratification rather small, because the subjects with and without CI were recruited from an ethnically homogeneous population. In conclusion, it is likely that the C allele of the TGF-b1 gene T868C polymorphism is a susceptibility allele for CI in Japanese type 2 diabetic patients.
Conflict of interest The authors declare that they have no conflict of interest.
references
[1] Blobe GC, Schiemann WP, Lodish HF. Role of transforming growth factor beta in human disease. N Engl J Med 2000;342:1350–8. [2] Singh NN, Ramji DP. The role of transforming growth factor-beta in atherosclerosis. Cytokine Growth Factor Rev 2006;17:487–99. [3] Metcalfe JC, Grainger DJ. Transforming growth factor-b and the protection from cardiovascular injury hypothesis. Biochem Soc Trans 1995;23:403–6. [4] Grainger DJ, Kemp PR, Liu AC, Lawn RM, Metcalfe JC. Activation of transforming growth factor-b is inhibited in transgenic apolipoprotein (a) mice. Nature 1994;370:460–2. [5] Robertson AK, Rudling M, Zhou X, Gorelik L, Flavell RA, Hansson GK. Disruption of TGF-b signaling in T cells accelerates atherosclerosis. J Clin Invest 2003;112:1342–50. [6] Cipollone F, Fazia M, Mincione G, Iezzi A, Pini B, Cuccurullo C, et al. Increased expression of transforming growth factor-b1 as a stabilizing factor in human atherosclerotic plaques. Stroke 2004;35:2253–7.
e60
diabetes research and clinical practice 94 (2011) e57–e60
[7] Nikol S, Isner JM, Pickering JG, Kearney M, Leclerc G, Weir L. Expression of transforming growth factor-b1 is increased in human vascular restenosis lesions. J Clin Invest 1992;90:1582–92. [8] Ohji T, Urano H, Shirahata A, Yamagishi M, Higashi K, Gotoh S, et al. Transforming growth factor-b1 and -b2 induce downmodulation of thrombomodulin in human umbilical vein endothelial cells. Thromb Haemost 1995;73:812–8. [9] Wolf YG, Rasmussen LM, Ruoslahti E. Antibodies against transforming growth factor-b1 suppress intimal hyperplasia in a rat model. J Clin Invest 1994;93:1172–8. [10] Kanzaki T, Tamura K, Takahashi K, Saito Y, Akikusa B, Oohashi H, et al. In vivo effect of TGF-b1: enhanced intimal thickening by administration of TGF-b1 in rabbit arteries injured with a balloon catheter. Arterioscler Thromb Vasc Biol 1995;15:1951–7. [11] Suthanthiran M, Li B, Song JO, Ding R, Sharma VK, Schwartz JE, et al. Transforming growth factor-b1
[12]
[13]
[14]
[15]
hyperexpression in African-American hypertensives: a novel mediator of hypertension and/or target organ damage. Proc Natl Acad Sci USA 2000;97:3479–84. Yokota M, Ichihara S, Lin TL, Nakashima N, Yamada Y. Association of a T29 > C polymorphism of the transforming growth factor-beta1 gene with genetic susceptibility to myocardial infarction in Japanese. Circulation 2000;101:2783–7. Sie MP, Uitterlinden AG, Bos MJ, Arp PP, Breteler MM, Koudstaal PJ, et al. TGF-beta 1 polymorphisms and risk of myocardial infarction and stroke: the Rotterdam Study. Stroke 2006;37:2667–71. Kim Y, Lee C. The gene encoding transforming growth factor beta 1 confers risk of ischemic stroke and vascular dementia. Stroke 2006;37:2843–5. Yamada Y, Izawa H, Ichihara S, Takatsu F, Ishihara H, Hirayama H, et al. Prediction of the risk of myocardial infarction from polymorphisms in candidate genes. N Engl J Med 2002;347:1916–23.