Effect of Family History of Type 2 Diabetes on the Intima-Media Thickness of the Common Carotid Artery in Normal-Weight, Overweight, and Obese Glucose-Tolerant Young Adults

This study included 401 subjects with NGT, aged 18–45 years, who were divided into two groups. The control group consisted of 213 subjects with no family history of type 2 diabetes (FH⁻) (defined as having neither parents nor relatives up to the third generation, i.e., grandparents, sons, daughters, uncles, aunts, and cousins, with type 2 diabetes). The FH⁻ group comprised 146 premenopausal women, 35 with normal weight (BMI 18.5–24.9 kg/m²) and 111 who were overweight and obese (BMI ≥25.0 kg/m²), and 67 men, 20 with normal weight and 47 who were overweight and obese. The second group consisted of 188 subjects with NGT and family history of type 2 diabetes (FH⁺) (defined as having one or both parents with type 2 diabetes). The FH⁺ group comprised 136 premenopausal women, 30 of normal weight and 106 who were overweight and obese, and 52 men, 17 of normal weight and 35 who were overweight and obese. NGT was defined according to the recommendations of the American Diabetes Association Expert Committee on the Classification and Diagnosis of Diabetes Mellitus (11).

Overweight and obese patients were recruited consecutively at the Outpatient Clinic of the Section on Internal Medicine, Endocrinology, and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari School of Medicine (Bari, Italy). Normal-weight subjects were healthy volunteers; those with family history of type 2 diabetes were recruited among offspring of patients with type 2 diabetes attending the Outpatient Clinic for the Study of Diabetes at the same institution, whereas those with no family history of type 2 diabetes were recruited among physicians and medical students. All parents of subjects enrolled in the study were alive at the beginning of the study. All individuals gave written informed consent to be included in the study, which was performed in accordance with the guidelines proposed in the Declaration of Helsinki.

To avoid confounding factors known to affect endothelial function, coagulation pathways, and/or glucose metabolism, the following subjects were not included in the study: smokers during the previous 12 months, subjects with diagnosed cardiovascular disease (coronary artery disease, arrhythmia, and heart failure), subjects with cerebrovascular disease (stroke and transient ischemic attack), subjects with peripheral vascular disease (claudicatio intermittens and/or absence of peripheral pulses), subjects with familial and/or severe dyslipidemia (triglycerides and/or total cholesterol >300 mg/dl), subjects with stable hypertension treated by drugs, and subjects with chronic hepatic, renal, or any other serious chronic disease. Subjects were also excluded if they were taking any kind of medications, including oral contraceptives. Finally, during the testing period, all subjects were asked to maintain their normal mixed diet and not to perform any sports activities.

Subjects were evaluated after an overnight fast and a 24-h period of abstinence from alcohol and vigorous physical exercise. A standard 75-g oral glucose tolerance test was performed in each subject enrolled in the study for evaluating glucose status and basal, 1-h postchallange, and 2-h postchallenge glucose concentrations. The systolic and diastolic blood pressure readings were recorded to the nearest 2 mmHg as the mean of two measurements with the subjects seated using a mercury sphygmomanometer with an appropriate cuff size. Central fat accumulation was evaluated by measuring the waist circumference, defined as the minimum circumference between the xiphoid process and the umbilicus.

Blood samples were drawn from an antecubital vein with a 19-gauge needle. Plasma concentrations of insulin were measured by radioimmunological assay using a commercially available kit (Behring, Scoppitto, Italy). Blood glucose levels were determined by the glucose-oxidase method (Sclavo, Siena, Italy). Total cholesterol, HDL cholesterol, and triglyceride levels were measured using enzymatic assays (Boehringer Mannheim, Diagnostica Mannheim, Mannheim, Germany). LDL cholesterol content was calculated by the Friedewald equation (LDL cholesterol = total cholesterol − [HDL cholesterol + triglycerides/5]). Insulin resistance was assessed by using the homeostasis model assessment (HOMA), based on a mathematical correlation between fasting plasma glucose and insulin levels (12).

Measurements of IMT-CCA were obtained from the far wall of the distal common carotid arteries (immediately proximal to the carotid bulb) and reported as the mean value for the bilateral measurement. This location was chosen a priori because of its demonstrated reproducibility, compared with measurements of IMT-CCA at other sites (13). All studies were performed on a single ultrasound machine (Hewlett-Packard Sonos 1000B) using a linear-array 8-MHz scan head with standardized image settings, including resolution mode, depth of field, gain, and transmit focus. Ultrasound study was performed in a standard fashion by an examiner who was specifically trained to perform the prescribed study examination. All sonograms were obtained with the patient in the supine position and the head turned slightly to the contralateral side. Each ultrasound examination was performed as an independent study, without any knowledge of the family history of type 2 diabetes. The near-field (intimal-luminal surface) and far-field (medial-adventitial) arterial wall borders were manually traced for measurement of minimal and maximal IMT-CCA. The precision and reliability of the ultrasound method was tested in a randomly selected subgroup of 21 arteries with paired images obtained on the same day. The mean difference in IMT-CCA between these images was 0.016 mm, and the intraclass correlation coefficient was 0.91 (P < 0.001). Paired IMT measurements in the same arteries showed a high degree of reproducibility; the mean difference in IMT was 0.021 mm, and the intraclass correlation coefficient was 0.96 (P < 0.001).

Statistical analyses were performed using the STATISTICA 6.0 for Windows software (StatSoft, Tulsa, OK). Results are presented as average and SEM for all parameters. The K-S test and the Lilliefors test for normality were performed to determine whether the wide range of BMI in each group, including normal weight, overweight, and obese subjects, could be a sign of bimodal distribution. Because both tests were not significant (P > 0.2), it could be argued that the three subgroups, i.e., normal weight, overweight, and obese, could be tested as a whole (data not shown). Student’s t test for independent samples was used to evaluate the differences between FH⁺ and FH⁻ individuals and between subjects with maternally and paternally inherited type 2 diabetes. The differences among subjects with no family history of type 2 diabetes, subjects with only one parent with type 2 diabetes, and subjects with both parents affected by type 2 diabetes were evaluated by one-way ANOVA. Pearson’s correlation coefficients were used to quantify the univariate associations among variables, and a multiple regression analysis was performed to test the joint effect of different variables on IMT-CCA as the dependent variable. Variables with a skewed distribution (plasma levels of triglycerides and insulin) were logarithmically transformed before analysis to improve the approximation to a Gaussian distribution. The minimal statistical significance was defined for P < 0.05.

General, anthropometric, biochemical, and ultrasonographic data of FH⁺ and FH⁻ individuals are presented in Table 1. IMT-CCA and both 1- and 2-h postchallenge glucose concentrations were significantly higher in FH⁺ than in FH⁻ subjects (P < 0.001, P < 0.01, and P < 0.01, respectively). The difference in IMT-CCA between FH⁺ and FH⁻ individuals was maintained also in the subgroup of normal-weight subjects (data not shown). No significant difference between the two groups was found for any of the other variables investigated, including age and BMI. Similarly, we could not find any difference either in IMT-CCA or anthropometric and metabolic variables between subjects with maternal versus paternal family history of type 2 diabetes (data not shown).

Figure 1 shows the results of the one-way ANOVA, performed to evaluate differences among subjects with no family history of diabetes (FH⁻, n = 213), subjects with only one diabetic parent (FH¹⁺, n = 169), and subjects with both parents affected by type 2 diabetes (FH²⁺, n = 19). Significant increases in IMT-CCA (F:14.58, P < 0.001) and in basal (F: 3.54, P < 0.05), 1-h postchallenge (F: 5.99, P < 0.01), and 2-h postchallenge glucose concentrations (F: 5.87, P < 0.01) were observed across the three subgroups. There was a tendency, even though not statistically significant (P = 0.055 and 0.066, respectively), for both BMI and waist circumference values to increase across the subgroups. On the other hand, age (one of the most powerful predictors of IMT-CCA) was not different across the above subgroups (P = 0.451).

The correlation coefficients between IMT-CCA and the other variables in all subjects (i.e., pooling FH⁺ and FH⁻ subjects) are shown in Table 2. IMT-CCA was positively correlated with age (P < 0.001), BMI (P < 0.001), waist circumference (P < 0.001), logarithmically transformed levels of triglycerides (P < 0.01), systolic and diastolic blood pressure levels (P < 0.01 and P < 0.001, respectively), basal, 1-h postchallenge, and 2-h postchallenge glucose concentrations (P < 0.001, P < 0.001, and P < 0.01, respectively), and HOMA for insulin resistance (HOMA_IR) (P < 0.05), and inversely associated with HDL cholesterol levels (P < 0.001). When IMT-CCA was considered as the dependent variable in a multiple regression analysis (fitted model: adjusted R² 0.241, F: 13.114, P < 0.001) with sex (categorical variable), family history of type 2 diabetes (categorical variable), age, BMI or waist circumference, plasma lipids (total cholesterol, HDL cholesterol, or logarithmically transformed triglycerides), systolic or diastolic blood pressure, logarithmically transformed insulin levels, and basal, 1-h postchallenge, or 2-h postchallenge glucose concentrations as independent variables, IMT-CCA maintained an independent association with family history of type 2 diabetes (P < 0.01), BMI (P < 0.01), waist circumference (P < 0.01), HDL concentrations (P < 0.01), diastolic blood pressure (P < 0.05), and fasting glucose levels (P < 0.01). Similarly, when HOMA_IR was entered into the regression model after excluding glucose and insulin levels (fitted model: adjusted R² 0.203, F: 4.613, P < 0.0001), IMT-CCA maintained an independent association with family history of type 2 diabetes (P < 0.01), BMI (P < 0.01), waist circumference (P < 0.01), diastolic blood pressure (P < 0.05), and HDL concentrations (P < 0.01) but not with HOMA_IR.

It is well established that the genetic predisposition to type 2 diabetes is associated with higher risk for CHD. We now show that normal-weight, overweight, and obese glucose-tolerant offspring of type 2 diabetic patients have higher IMT-CCA than age- and BMI-matched control subjects with no family history of type 2 diabetes. The role of the genetic predisposition to type 2 diabetes in influencing carotid atherosclerosis is strengthened by further observations. First, IMT-CCA was found to significantly increase across the three subgroups, in which the entire population was divided according to the absence of family history of type 2 diabetes, presence of type 2 diabetes in only one parent, or presence of type 2 diabetes in both parents. Second, IMT-CCA was still higher in FH⁺ than in FH⁻ individuals when only normal-weight subjects were considered in the statistical analysis, suggesting that the effect of family history of type 2 diabetes on the arterial wall may be independent of obesity.

IMT-CCA has been shown to be associated with prevalence of cardiovascular disease and atherosclerotic involvement of other arterial beds, including the coronary arteries (8), and to represent a strong predictor of both myocardial infarction and stroke (10,14), even in subjects with no history of cardiovascular disease (8). Furthermore, ample evidence has been provided that the increase in cardiovascular risk begins well before the onset of overt diabetes and that, at this time, metabolic disturbances contribute to macrovascular rather than microvascular complications (15). Therefore, the independent association between the genetic predisposition to type 2 diabetes and IMT-CCA in young healthy adults points to the fact that these subjects may be considered to be already affected by an early stage of atherosclerosis.

Because we found an independent association of IMT-CCA with fasting glucose concentrations and, furthermore, a gradual increase in basal, 1-h postchallenge, and 2-h postchallenge glucose concentrations according to the absence of family history of type 2 diabetes, presence of type 2 diabetes in only one parent, or presence of type 2 diabetes in both parents, respectively, we cannot rule out a harmful effect of slightly elevated glycemia on the vasculature, affecting endothelial function. Relevant to this concept, it should be noted that both fasting and postchallenge hyperglycemia are strong and independent risk factors for cardiovascular diseases also in nondiabetic subjects (16). Recently, Balletshofer et al. (6) reported that endothelial dysfunction is detectable in young normotensive first-degree relatives of subjects with type 2 diabetes. Because endothelial dysfunction represents an early disturbance in the development of atherosclerotic lesions (17), one could hypothesize that slightly elevated fasting and/or postprandial glucose concentrations, as found in this study in offspring of type 2 diabetic patients, can cause a loss of endothelial function, leading to an increase in IMT-CCA.

Noteworthy, no independent relationship was found between IMT-CCA and HOMA_IR. This is not surprising, because the association of insulin resistance with carotid atherosclerosis could be explained by its cosegregation with established CHD risk factors, such as obesity, visceral fat, hypertension, and low HDL cholesterol levels. We found that IMT-CCA is positively associated with BMI, waist circumference, and diastolic blood pressure and negatively related to HDL cholesterol. Together, these findings support the concept that genetic predisposition to type 2 diabetes may contribute to development of atherosclerosis in susceptible individuals per se and/or through an array of subtle associated abnormalities in body fat, glucose and lipid metabolism, and blood pressure.

In conclusion, the present study demonstrates that the IMT-CCA is significantly higher in young adult normal-weight, overweight, and obese glucose-tolerant first-degree relatives of type 2 diabetic patients compared with control subjects with no family history of diabetes. Therefore, this study indicates that genetic predisposition to type 2 diabetes may accelerate development of atherosclerosis and, potentially, increase the risk of CHD.