Subclinical Inflammation and Endothelial Dysfunction in Young Patients with Diabetes: A Study from United Arab Emirates

Background The impact of obesity and dyslipidemia on cardiovascular health in adolescents and young adults with diabetes is incompletely understood. This study evaluated the effects of these co-morbidities on markers of inflammation and endothelial dysfunction in young patients with the disease. Methods The study investigated sets of inflammatory, endothelial, and adipocyte biomarkers in 79 patients with type 1 diabetes, 55 patients with type 2 diabetes, and 47 controls. Results Mean (±SD) age was 20±6 y (median = 17, range = 12–31). Patients with diabetes had higher levels of cytoadhesive molecules (sICAM-1 and sVCAM-1, p<0.001), adiponectin (p<0.001), and haptoglobin (p = 0.023). Their heart rate variability assessment revealed lower standard deviation of beat-to-beat intervals and lower total power (p≤0.019), reflecting autonomous nervous dysfunction. Hemoglobin A1c >8.0% (estimated average blood glucose >10 mmol/L) was associated with higher adiponectin (p<0.001) and obesity was associated with lower adiponectin (p<0.001); thus, obesity damped the effect of hyperglycemia on adiponectin. Obesity was associated with higher sICAM-1 (p≤0.015), tumor necrosis factor-α (TNFα), interleukin-6 (IL-6), and high-sensitivity C-reactive protein (hs-CRP), p<0.001. Similarly, high-density lipoprotein (HDL) <1.02 mmol/L was associated with higher sICAM-1, TNFα, IL-6, and hsCRP (p≤0.009) and lower adiponectin (p<0.001). Adiponectin correlated negatively with the inflammatory biomarkers in patients with diabetes. Conclusion Subclinical inflammation and endothelial dysfunction are common among young patients with diabetes. Poor diabetes control is associated with higher adiponectin. Obesity and dyslipidemia are associated with lower adiponectin and higher inflammatory and endothelial biomarkers. Intuitively, these predictors of cardiovascular disease are amenable to proper glycemic control, nutritional choices, and regular exercise.


Introduction
The rising rates of diabetes, obesity, atherogenic dyslipidemia, and cardiovascular disease (stroke and ischemic heart disease) impose serious health problems worldwide [1][2]. Children and young adults are especially vulnerable to complications of these disorders and are generally less engaged in health promoting and monitoring programs. Therefore, measures designed for preventing and treating obesity, dyslipidemia, and hypertension in children, adolescents, and young adults with diabetes are vital.
This study investigated sets of inflammatory and endothelial dysfunction biomarkers in young patients with diabetes. Its main purpose was to use established predictors of microvascular disease (tumor necrosis factor-α [TNFα], interleukin-6 [IL-6], high-sensitivity C-reactive protein [hs-CRP], soluble intercellular cytoadhesive molecule-1 [sICAM-1], soluble vascular cytoadhesive molecule-1 [sVCAM-1], and adiponectin) as screening tools for adverse effects of obesity and dyslipidemia in this age group [3][4]. ICAM-1 is a glycoprotein involved in tissue adhesion and is expressed in response to cytokines [5] and therefore, it has been used as a biomarker for inflammation [6]. Its circulating soluble form (sICAM-1) in the blood (normal, 150 ± 32 ng/mL) estimates levels in the tissue [5][6]. Adiponectin reduces free fatty acid levels and promotes lipid metabolism. This cardio-protective, adipocyte-derived cytokine improves insulin function and ameliorates inflammation and atherogenic disease [7]. Adiponectin is also known to modulate endothelial function [8]. Despite its proven importance, adiponectin is yet to be included in routine patient care.

Methods
This study involved UAE citizens (12 to 31 years of age) with diabetes. The study was approved by Al Ain Medical District Human Research Ethics Committee (AAMDHR 09/79) and Imperial College London Diabetes Centre Research Ethics Committee (REC 017). Written informed consent was obtained for each participant (or their parents if they were <18 years old) prior to study enrolment.
Patients were randomly recruited from three diabetes centers (Tawam Hospital, Al Ain Hospital, and Imperial College London Diabetes Centre) in Abu Dhabi region. The study had a two-stage sampling design, stratified by center and systematic sampling from each center. Even-numbered patients on appointment lists were selected. Healthy citizens (12 to 18 years of age) were also recruited from public schools and healthy citizens between 18 and 31 years were recruited from the UAE University. Following written approval from the UAE University, students were invited by email to take part in this study and those who responded positively were randomly selected from several colleges. School students were also selected randomly, using multistage sampling. Firstly, four male and four female schools were selected randomly from a list of middle and secondary schools from the list provided by Abu Dhabi Education Council.
Secondly, 2 classes from each grade were selected randomly from these schools. Thirdly, all students from these classes were approached to participate in the study and those who signed the study informed consent were enrolled. Assessments were performed at the diabetes centers (patients), schools (controls), and university (controls).
Patients with T1DM were receiving daily insulin since diagnosis; two patients were also receiving atorvastatin and one patient was receiving ezetimibe. Medications used by patients with T2DM included metformin (22 patients), metformin plus sitagliptin (three patients), metformin plus vildagliptin (one patient), sulfonylurea (nine patients), diet plus statin (nine patients), insulin (five patients), and diet plus exercise (six patients). Control participants were not receiving any regular medication.
All participants completed the study health questionnaire, physical examination, and laboratory assessments. They were interviewed by a trained nurse who performed examination and anthropometric measurements (weight, height, waist, and hip circumference). Fat mass and fat-free mass were measured using Tanita body composition analyzer (Tanita Corporation, Tokyo, Japan). Abnormal percent body fat ('obese') was set as 32% for females and 25% for males; otherwise, the values were considered 'average' [9]. Heart rate variability (HRV) was performed as previously reported [10]. HRV was recorded for 5 min using a handheld HRV device (Daily Care BioMedical Inc., Taiwan). Measurements were taken over 5 min after 20 min rest, with patient in supine position. Recordings were transferred to computer and data were automatically analyzed by HRV analysis software. Length of recording was selected in accordance with recommendations from the Task Force of the European Society of Cardiology and the North American Society of Pacing Electrophysiology (10). The ratio of power of low frequency band (ms 2 ) to power of high frequency band (ms 2 ), a measure of the overall balance between sympathetic and parasympathetic systems, was reported. Higher values reflected domination of the sympathetic system and lower ones reflected domination of the parasympathetic system. Total power (reflecting the overall autonomic activity) and SDNN (standard deviation of beat-to-beat, NN, intervals) were determined as previously described [10].
Weight was measured to the nearest 0.1 kg and height to the nearest 0.1 cm in a standing position without shoes and in light clothing using digital scales. Waist circumference was measured with upstretched tapes midpoint between the bottom of the rib cage and the tip of the iliac crest. Hip circumference was measured over minimal clothing at the level of the greatest protrusion of the gluteal muscles. Blood pressure was measured on the right arm at rest for 5 min. Three consecutive measures were obtained at one-minute intervals with a standard mercury sphygmomanometer with an appropriate cuff size.
Glucose, hemoglobin A1c (HbA1c), lipid profile, and creatinine were measured using an automated analyzer Integra 400 Plus (Roche Diagnostics, Mannheim, Germany). 25-Hydroxyvitamin D was measured by a chemi-luminescent assay with the automated analyzer Cobas e411 (Roche Diagnostic, Mannheim, Germany). The laboratory performed internal quality controls before running samples and participated in External Quality Assurance program through the College of American Pathologists Proficiency Testing.
The statistical analysis was performed using SPSS software version 21.0 (SPSS Inc., Chicago, USA). Measurements were compared across two groups using the Mann-Whitney-U test whenever the group sizes were small (<30) and the values were not normally distributed; otherwise, the independent sample t-test was used. Multiple groups (3) were compared using Kruskal-Wallis test whenever measurements were either not normally distributed or heteroscedastic (unequal variances); otherwise, one-way ANOVA was used. Independent-samples t-test (2-tailed, equal variances not assumed), one-way ANOVA (between groups), and nonparametric test (2 independent variables) Mann-Whitney-U test were used to compare groups. The normality and heteroscedasticity of the measurements were tested using Shapiro-Wilk test and Levene test, respectively. Data are presented as mean ± standard deviation (median) with P<0.05 (2-tailed) considered significant.

Results
One hundred and eighty-one subjects were recruited. Sixty four percent (116/181) of the participants had positive family history of diabetes, 42% (77/181) had positive family history of cardiovascular disease, and 6% (11/181) reported high blood pressure (two with T1DM, five with T2DM, and four controls). The anthropometric, laboratory, and clinical measurements are shown in Table 1. In patients with diabetes, the heart rate variability test revealed lower standard deviation of beat-to-beat intervals (SDNN) and lower total power, reflecting autonomic nervous dysfunction (Table 1). Although not significantly different between groups (p = 0.117), the LF:HF ratio between power of low and high frequency bands was higher in patients with diabetes compared to those in controls, indicating sympathetic domination (Table 1). SDNN correlated with sVCAM-1 (correlation coefficient, r = -230, p = 0.028). Patients with diabetes also had higher sICAM-1, sVCAM-1, haptoglobin, adiponectin, triglycerides, total cholesterol, LDL, ALT, and 25-hydroxyvitamin D compared to non-diabetic controls (Table 1). Therefore, aberrant cardiac markers and biochemical disturbances were present in these young patients with diabetes.
Distribution of the inflammatory biomarkers, cytoadhesive molecules, and adiponectin among patients and controls and their correlations with each other are shown in S1-S3 Figs. A schematic summary of the results is also shown in S1 File. In all studied participants (patients and controls), TNFα, IL-6, and haptoglobin correlated with hsCRP (R 2 0.565), S2

Discussion
Diabetes and obesity are common in UAE. Importantly, the prevalence of these disorders is increasing, particularly among children and young adults. To our knowledge, this is the first study that examined inflammation and endothelial dysfunction in this young population. This study shows that subclinical inflammation and endothelial dysfunction are highly prevalent in adolescents and young adults with diabetes (Table 1). It also shows significant correlations between these markers and excess body fat and dyslipidemia (primarily low HDL), Table 2. In addition, the heart rate variability test demonstrates autonomic nervous system dysfunction Table 3. Effects of excess fat on endothelial and inflammatory biomarkers and adiponectin in control subjects.
Cutoffs n* sICAM-1(ng/mL) sVCAM-1 (ng/mL) TNFα (pg/mL) IL-6 (pg/mL) hsCRPmg/L Adiponectin(μg/L)   (Table 2). Thus, obesity and dyslipidemia impose deleterious effects on the cardiovascular health of young patients with diabetes. These complications are amenable to prevention and management. These findings have important implications in the management of patients with obesity and diabetes and emphasize the need for early interventions. Recommendations should include regular monitoring of body fat accumulation and appropriate lifestyle changes. Prospective follow-up studies, however, are necessary to investigate the usefulness of these biochemical markers in the clinical care of these patients.
In keeping with studies in older patients, this study has shown that adiponectin correlates negatively with inflammatory biomarkers in young patients with diabetes (Table 4). Adiponectin is significantly lower in patients with BMI >30 kg/m 2 , abnormal body fat (obesity), HDL <1.02 mmol/L, and triglycerides >1.2 mmol/L ( Table 2). In contrast, this adipocyte-derived cytokine is significantly higher in patients with HbA1c >8% ( Table 2). The studied inflammatory and endothelial dysfunction biomarkers, on the other hand, did not significantly differ between patients with HbA1c >8% vs. 8% (Table 2). Excess body fat (BMI >30 kg/m 2 or increased percent body fat) is associated with higher sICAM-1, TNFα, IL-6, and hsCRP. A similar profile of increased sICAM and inflammatory biomarkers and decreased adiponectin is observed in patients with dyslipidemia (HDL <1.02 mmol/L, LDL >2.9 mmol/L, or triglyceride >1.2 mmol/L ( Table 2).
In one study, this adipocyte-derived secretory protein inhibited TNFα-induced expression of ICAM-1 and VCAM-1, and its circulating levels were lower in patients with coronary disease [8]. The reduced adiponectin in obesity, thus, promotes inflammatory cytokine-induced expression of cytoadhesive molecules. These results are consistent with our findings that excess body fat and dyslipidemia (low HDL) are associated with decreased adiponectin and increased sICAM and sVCAM (Tables 2 and 4).
Diabetes promotes endothelial cell inflammation. In a meta-analysis study, adiponectin levels were found to be higher in patients with T2DM and microvascular complications, such as albuminuria, neuropathy, and retinopathy [12]. Obesity also imposes this cluster of subclinical inflammation and endothelial dysfunction. Therefore, obesity and dyslipidemia are serious comorbid conditions in patients with diabetes at any age. Several biomarkers have been developed to monitor these processes, especially in high-risk patients. The current study supports their use in children and adolescents with diabetes.
Inflammation is an independent predictor of adverse events associated with diabetes [19][20]. Thus, the observed subclinical inflammation in young patients with diabetes and obesity (Tables 1 and 2) should be considered a sign of the disease and to activate early interventions. In a prospective 6-year follow-up study, biomarkers of inflammation and endothelial dysfunction were independent predictors of cardiovascular events in patients with T2DM with microalbuminuria [19]. TNFα, sICAM-1, and sVCAM-1 were either a determinant of or associated with cardiovascular disease all-cause mortality [19]. Children and adolescents with T1D also have significantly higher concentrations of sICAM-1, sVCAM-1, TNFα, IL-6 [21].
Metabolic syndrome is considered in patients with at least three of the five International Diabetes Federation criteria: (1)  In conclusion, significant biomarkers of inflammation (TNFα, IL-6, hsCRP, and haptoglobin) and endothelial dysfunction (sICAM-1 and sVCAM-1) are present in young patients with diabetes, obesity, and dyslipidemia. sICAM-1 is increased in patients with diabetes and correlates with other inflammatory biomarkers. The development of obesity and dyslipidemia needs to be carefully monitored and promptly treated in children and adolescents with diabetes.