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(Circulation. 2004;109:2844-2849.)
© 2004 American Heart Association, Inc.

Clinical Investigation and Reports

G(–30)A Polymorphism in the Pancreatic Promoter of the Glucokinase Gene Associated With Angiographic Coronary Artery Disease and Type 2 Diabetes Mellitus

Winfried März, MD; Markus Nauck, MD; Michael M. Hoffmann, PhD; Dietmar Nagel, PhD; Bernhard O. Boehm, MD; Wolfgang Koenig, MD; Dietrich Rothenbacher, MD, MPH; Bernhard R. Winkelmann, MD

From the Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria (W.M.); Division of Clinical Chemistry, Department of Medicine, University Hospital, Freiburg, Germany (M.N., M.M.H.); Institute of Clinical Chemistry, General Hospital, Ludwigshafen, Germany (D.N.); Division of Endocrinology and Diabetes, Department of Medicine (B.O.B.), and Department of Internal Medicine II, Cardiology (W.K.), University of Ulm, Ulm, Germany; and Department of Epidemiology, German Center for Research on Ageing (D.R.), and Cooperation Unit Pharmacogenomics/Applied Genomics (B.R.W.), University of Heidelberg, Heidelberg, Germany.

Correspondence to Winfried März, MD, Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Auenbruggerplatz 15, 8036 Graz, Austria. E-mail winfried.maerz{at}klinikum-graz.at

Received June 3, 2003; de novo received October 27, 2003; revision received February 26, 2004; accepted March 2, 2004.

	Abstract

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Background— Type 2 diabetes mellitus (T2DM) increases the risk of coronary artery disease (CAD). A G(–30)A polymorphism in the ß-cell–specific promoter of glucokinase (GK-30PM) has been implicated in reduced pancreatic ß-cell function. Its impact on CAD has not been examined.

Methods and Results— The glucokinase G(–30)A variant was determined in 2567 patients with angiographic CAD and in 731 individuals in whom CAD had been ruled out by angiography. In carriers of the A allele, the adjusted OR of CAD was 1.39 (95% CI, 1.15 to 1.70). Corresponding ORs were 1.27 (95% CI, 1.02 to 1.59) and 1.92 (95% CI, 1.26 to 2.93) in individuals without and with T2DM, respectively. The prevalence of the A allele increased in parallel with the Friesinger coronary score. Patients with T2DM were more frequent among carriers of 1 A allele (OR, 1.17; 95% CI, 1.00 to 1.28). This association was stronger if CAD patients only were considered. The A allele was associated with higher glucose (fasting, P=0.002; 2 hours after oral glucose, P=0.017) and glycohemoglobin (HbA1c; P=0.002). Furthermore, presence of 1 A allele was negatively related to ß-cell function, estimated by ß percent (P=0.012) and by the ratios of proinsulin to insulin (P=0.025) and proinsulin to C peptide (P=0.019).

Conclusions— The A allele of the pancreatic promoter of glucokinase increases the risk of CAD in individuals with and without T2DM. Furthermore, at least in CAD, it is associated with an augmented prevalence of T2DM.

Key Words: coronary disease • diabetes mellitus • genetics • glucose • myocardial infarction

	Introduction

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Type 2 diabetes mellitus (T2DM) increases the risk of coronary artery disease (CAD). T2DM is characterized by impaired function of pancreatic ß cells, peripheral insulin resistance, and hepatic glucose overproduction.¹ Its occurrence is influenced by genetic factors.² Mutations in the gene encoding glucokinase (EC 2.7.1.1) were the first defects identified to affect glucose metabolism.³ Glucokinase is found in pancreatic ß cells, hepatocytes, and specific bone regions. Expression is controlled by 2 tissue-specific promoters.⁴ Pancreatic glucokinase serves as the sensor for glucose, which regulates insulin secretion.³ Allosteric activators of glucokinase improve hepatic glucose metabolism and the pancreatic insulin response to glucose.⁵ Mutations of the glucokinase gene account for 10% to 50% of the cases of maturity-onset diabetes of the young.³ In patients with late-onset T2DM, however, mutations of the glucokinase gene are rare.^6–9

A G(–30)A polymorphism in the ß-cell–specific promoter of glucokinase (GK-30PM) has been described.^7,8,10,11 In Japanese men but not in Finns,¹² this variant is associated with reduced ß-cell function and impaired glucose tolerance.^10,13 We examined whether GK-30PM was associated with angiographic CAD and altered glucose metabolism including T2DM.

	Methods

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Study Design and Participants
The Ludwigshafen Risk and Cardiovascular Health (LURIC) study includes white patients hospitalized for coronary angiography.¹⁴ Patients with type 1 diabetes mellitus were excluded from this analysis. Clinically relevant CAD was defined as the presence of a luminal narrowing (20% stenosis) in 1 of 15 coronary segments.¹⁵ Severity of CAD was quantified with the Friesinger score.¹⁶

To ensure that genotypes in the LURIC control subjects were representative of the general population, we examined white voluntary blood donors not reporting physician-diagnosed CAD.

Laboratory Procedures
Blood sampling and laboratory methods have been described elsewhere.¹⁴

Metabolic Studies
An oral glucose tolerance test was performed in individuals not previously diagnosed as having diabetes mellitus. Diabetes mellitus was diagnosed according to the American Diabetes Association (ADA).¹ Furthermore, individuals with a history of diabetes or treatment with oral antidiabetics or insulin were considered diabetic. Hepatic and whole-body insulin sensitivities were calculated as described.¹⁷ Pancreatic ß-cell function was estimated by the following formula: percent ß=20 · fasting plasma insulin concentration (mU/L)/[fasting plasma glucose concentration (mmol/L)–3.5].¹⁸ Subjects with LDL cholesterol levels >4.1 mmol/L, triglycerides >2.3 mmol/L, or HDL cholesterol <1 mmol/L were considered dyslipidemic.

Glucokinase G(–30)A Genotype
Genomic DNA was prepared from EDTA anticoagulated blood.¹⁴ GK-30PM was determined from polymerase chain reaction and restriction typing. The primers for amplification were 5'-TGCATGGCAGCTCTAATGAC-3' and 5'-ATTCTCCTGCCAGGGCTTAC-3'. Amplification products were digested with MwoI (New England BioLabs) and analyzed by agarose gel electrophoresis. The G allele yielded fragments of 82 and 25 bp; the A allele was not digested (107 bp).

Statistical Analysis
Continuous variables were compared between CAD patients and control subjects by ANOVA with adjustment for gender and age. Associations between categorical variables were examined by ² testing or logistic regression analysis, including covariables as indicated. In models assuming a codominant (additive) effect of the A allele, the genotypes GG, GA, and AA were coded as 0, 1, and 2, respectively. When a dominant effect was assumed, genotype GG was coded as 0, and GA and AA were combined as 1. When a recessive effect was assumed, genotypes GG and GA were coded as 0, and AA was coded as 1. Associations between genotypes and clinical and biochemical variables were evaluated by Kruskal-Wallis 1-way ANOVA or by the Mann-Whitney rank-sum test. The SPSS statistical package (SPSS Inc, version 11.0 for Windows) was used.

	Results

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Study Participants
CAD patients (n=2567) were significantly older than control subjects (n=731). Current or past smoking, T2DM, and hypertension were more prevalent in those with CAD. CAD patients were more often taking ß-blockers, ACE inhibitors, antiplatelet agents, and lipid-lowering drugs. CAD patients had higher systolic blood pressure (borderline significance after adjustment for age and gender), higher fasting glucose, higher triglycerides, and lower HDL cholesterol. LDL cholesterol concentrations did not significantly differ between the 2 groups because more CAD patients (57%) than control subjects received lipid-lowering drugs (18%) (Table 1).

View this table: [in this window] [in a new window]   TABLE 1. Characteristics of CAD Patients and Control Subjects

GK-30PM Associated With Angiographic CAD
The genotypes GA and AA and the A allele were more frequent in CAD than in control subjects (P<0.005; Figure 1). Individuals with the genotype GA had a 1.31-fold increased prevalence of CAD (P=0.004; Table 2). The OR for CAD of the combined GA and AA genotypes compared with the GG genotype was 1.34 (P=0.002). Adjustment for T2DM and cardiovascular risk factors did not substantially change these numbers (Table 2). When diabetics and nondiabetics were analyzed separately, the GA and the combined GA and AA genotypes remained associated with CAD after adjustment for other risk factors (Table 3). When we stratified into 4 groups according to both CAD and T2DM, the prevalence of the GA and AA genotypes combined was increased in CAD patients, regardless of the presence or absence of T2DM (Figure 2). The prevalence of the GA and AA genotypes combined increased in parallel to increasing quartiles of the Friesinger coronary score (Figure 3).

View larger version (53K): [in this window] [in a new window]   Figure 1. Prevalence of glucokinase G(–30)A genotypes (left) and glucokinase G(–30)A alleles (right) in male (top) and female (bottom) patients with (gray bars) and without (black bars) angiographic CAD (P<0.001).

View this table: [in this window] [in a new window]   TABLE 2. ORs for CAD According to GK-30PM

View this table: [in this window] [in a new window]   TABLE 3. ORs for CAD According to GK-30PM Promoter in Nondiabetics and Patients With T2DM

View larger version (13K): [in this window] [in a new window]   Figure 2. ORs (±95% CIs) for prevalence of combined GA and AA genotypes by presence and absence of CAD and T2DM. Squares indicate unadjusted ORs; triangles, ORs adjusted for age, gender, body mass index, smoking, hypertension, and dyslipidemia.

View larger version (21K): [in this window] [in a new window]   Figure 3. ORs (±95% CIs) for prevalence of combined GA and AA genotypes by quartiles of Friesinger score. Squares indicate unadjusted ORs; circles, ORs adjusted for T2DM; and triangles, ORs also adjusted for age, gender, body mass index, smoking, hypertension, and dyslipidemia.

CAD patients and control subjects differed significantly in age. In addition to adjusting for age, we selected male CAD patients <65 years of age and female CAD patients <73 years of age for comparison with the control group. This resulted in subgroups of 1054 and 483 male and female CAD patients 55.9±6.9 and 62.5±8.0 (mean±SD) years of age, respectively, matching the controls (see Table 1). This did not substantially affect any of the ORs for CAD (data not shown).

To verify whether the genotypes in the LURIC control group reflected the distribution in the general population, we examined 359 male and 120 female white voluntary blood donors 55.8±7.3 and 55.9±7.0 years of age, respectively. The prevalences of the glucokinase G(–30)A genotypes GG, GA, and AA in these subjects (69.7%, 26.9%, and 2.9%, respectively) were identical to those in the LURIC control subjects (70.5%, 25.0%, and 2.8%, respectively).

GK-30PM Associated With T2DM
Compared with the GG genotype, the presence of either GA or AA increased the risk of T2DM 1.2-fold. Carriers of the AA genotype had an 1.5-fold increased risk of T2DM compared with carriers of the GG genotype and of the combined GG and GA genotypes (Table 4). Adjustment for age, gender, and body mass index did not appreciably affect this association. Adjustment for CAD status decreased ORs, but the changes were small (Table 4). When CAD patients alone were analyzed, the association between GK-30PM and T2DM was slightly stronger than in the entire cohort. In the control subjects, however, there was no significant association with T2DM (data not shown). When we stratified into 4 groups according to both CAD and T2DM, the prevalence of the GA and AA genotypes combined was consistently increased in T2DM in the presence but not in the absence of CAD (Figure 2).

View this table: [in this window] [in a new window]   TABLE 4. ORs for T2DM According to GK-30PM

GK-30PM Associated With Glucose Metabolism
To investigate how glucose metabolism was related to GK-30PM, we analyzed 1998 individuals (60.5% of the entire study population) in whom an oral glucose tolerance test was performed who were not being treated with oral antidiabetics or insulin. This subgroup consisted of 830 subjects (41.5%) with normal glucose tolerance, 706 subjects (35.3%) with impaired glucose tolerance, and 462 subjects (23.1%) newly diagnosed as diabetic (Table 5). GK-30PM was significantly associated with glycohemoglobin and fasting glucose (P=0.006, P=0.003, nonparametric ANOVA, respectively). At 1 hour after oral glucose, carriers of the GA genotype had higher plasma glucose than carriers of the other genotypes, but the difference was not statistically significant. At 2 hours after the oral glucose, plasma glucose increased in parallel to the number of A alleles (P=0.05). Fasting insulin, C peptide, and proinsulin were not significantly affected by GK-30PM. The A allele dose-dependently decreased ß-cell function (percent ß). The ratio of proinsulin to insulin and the ratio of proinsulin to C peptide consistently increased in parallel to the number of A alleles, the differences being statistically significant when carriers of the A allele (GA plus AA) were compared with GG homozygotes. There was no correlation of GK-30PM with the ratio of C peptide to insulin, an index of hepatic insulin clearance, and calculated estimates of hepatic and whole-body insulin sensitivity.^17,19–21

View this table: [in this window] [in a new window]   TABLE 5. Effects of GK-30PM on Glucose and Insulin Metabolism

	Discussion

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Glucokinase is a rate-limiting factor in the regulation of the release of insulin from pancreatic ß cells. Mutations of the glucokinase gene are encountered in 10% to 50% of all patients presenting with maturity-onset diabetes of the young.³ Hence, glucokinase is an attractive drug target⁵ and candidate gene for T2DM or impaired glucose regulation.^{6–9,22–24} A substitution of G by A at position –30 of the ß-cell–specific promoter of the glucokinase gene has been identified.^7,8,10,11 Here, this polymorphism was related to markers of ß-cell function like percent ß and the ratios of proinsulin to insulin and of proinsulin to C peptide.²⁵ Thus, our results are in line with previous studies^10,13 but stand in contrast to a Finnish study.¹²

The A allele was associated with an increased risk of T2DM in the entire cohort and among CAD patients but not in control subjects. The latter may be related to the smaller size of the control group and the low prevalence of T2DM in this group. Furthermore, nongenetic factors promoting the development of T2DM on the background of the A allele may be more frequent in CAD patients than in control subjects. Other investigations could not show an association between GK-30PM and T2DM,^12,13,26,27 maybe because they completely disregarded the CAD status and may thus have missed an association in CAD patients. Another explanation for the discrepant findings relates to statistical power. On the basis of the assumption of relative frequencies of 0.67, 0.30, and 0.03 of the genotypes GG, GA, and AA, respectively, and of prevalences of 0.30, 0.34, and 0.41 of T2DM among carriers of these genotypes, the power of our study was 88% to reject the null hypothesis that the ORs were 1.0 for the GA and AA genotypes at =0.05. None of the comparisons of allele frequencies between T2DM and control subjects conducted so far has reached such a power.^12,13,26,27

The A allele increased the prevalence of CAD by 1.4-fold, which seems modest. This is not surprising, however, because recent research reveals that multiple variants, each having a small effect, will ultimately explain the largest fraction of the genetic component of CAD. Furthermore, as in prospective studies, established risk factors like smoking, T2DM, and hypertension increase the probability of CAD between 2.0- and 2.5-fold in the present study (data not shown). Thus, compared with these complex clinical phenotypes, GK-30PM may well be relevant.

Surprisingly, GK-30PM was consistently linked with CAD after adjustment for T2DM. The risk for CAD conferred by the A allele was even greater in T2DM than in nondiabetic individuals, suggesting that GK-30PM may help to stratify patients with T2DM with regard to vascular risk. The finding that GK-30PM was associated with CAD in nondiabetics may also reflect the fact that the ADA definition of diabetes used in this study is based mainly on fasting glucose, whereas GK-30PM might influence the dynamics of the postprandial regulation of glucose not detectable by fasting or markedly elevated postprandial glucose concentrations. Alternatively, one may speculate that an impaired release of insulin or a higher amount of proinsulin might alter vascular function independently of its influence on plasma glucose metabolism.

A limitation of this study is its cross-sectional design. Therefore, our findings need to be confirmed prospectively. Moreover, we exclusively enrolled individuals in whom coronary angiography was clinically indicated, which may have resulted in a referral bias. However, this investigation meets most of the criteria allowing interpretation of a case-control genetic study.²⁸ By restricting recruitment to white individuals at a single site, we avoided differences in ethnicity and genetic background. It is also a strength of our study that coronary status was assessed by angiography. Thus, we optimized phenotyping and ruled out that individuals with inapparent CAD were inadvertently allocated to the control group. We thoroughly monitored established CAD risk factors, which allowed us to control for confounding effects. The study also overcomes major limitations of previous research that originate mainly from the use of sample sizes too small to detect the subtle effects of genetic predictors. Finally, we provide evidence that the A allele compromises the insulin response to glucose. This finding might provide a mechanistic link between GK-30PM and atherosclerosis.

	Acknowledgments

 
The study was supported in part by research grants DFG SFB 518 and IZKF project A1, University of Ulm (Dr Boehm). We thank Sabine von Karger and Andrea Schwentek for technical assistance, as well as the LURIC Study Team, laboratory staff at the Ludwigs-hafen General Hospital, the University of Freiburg, and the University of Ulm (Germany).

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