Study population
A total of 107 patients (≥ 20 years of age) who visited the outpatient diabetic clinic at Kaohsiung Chang Gung Memorial Hospital (CGMH) in Taiwan were included in this study: 90 subjects with type 2 diabetes and 17 subjects with prediabetes. Exclusion criteria were moderate-to-severe heart failure (NYHA class III and IV), presence of any type of arrhythmia that prevents analysis of heart rate variability (HRV), or pacemaker implantation. This study was approved by the Ethics Committee of Chang Gung Memorial Hospital Institutional Review Board (201800388B0C501 and 201901363B0).
Baseline clinical and laboratory measurements
All patients underwent complete neurological and physical examinations on enrollment and at the follow-up visit at the outpatient clinic. A detailed medical history regarding prior use of medications was obtained from the patients and their families through standardized questions. Demographic data, including age, sex, duration of diabetes (years), body mass index (BMI), systolic and diastolic blood pressure (SBP and DSP, respectively), waist circumference (WC) during autonomic function testing, underlying diseases (hypertension, coronary artery disease, ischemic stroke, and diabetic retinopathy [DR]), and laboratory parameters, were obtained at baseline. MetS was evaluated according to the updated National Cholesterol Education Program/Adult Treatment Panel III criteria[21]. A subject who had at least three of the following components was defined as having MetS: 1) central obesity: WC ≥ 90 cm for men and ≥ 80 cm for women; 2) hypertension: SBP ≥ 130 mmHg or DBP ≥ 85 mmHg or drug treatment for hypertension; 3) fasting blood glucose ≥ 100 mg/dL or diagnosed diabetes; 4) abnormal high-density lipoprotein (HDL) level: HDL cholesterol level < 40 mg/dL for men and < 50 mg/dL for women or drug treatment for low HDL cholesterol (HDL-C); and 5) abnormal triglyceride (TG) level: TG level ≥ 150 mg/dL or drug treatment for high TGs. The cut-off values for obesity, based on BMI, should be much lower in Taiwan than in Western countries. We determined that the optimal cut-off values for our study were BMIs of 23.6 in men and 22.1 in women, and WCs of 80.5 cm in men and 71.5 cm in women may be more appropriate to define adult overweight or obesity in Taiwan[22].
Measuring IR
The homeostasis model assessment of insulin resistance (HOMA-IR index) was calculated by fasting glucose (in mmol/L) × fasting insulin (in mU/ml)/22.5. In our study, we defined IR as ≥ 2, based on the Taiwanese population[23]. Additionally, we used the TG/HDL ratio as a surrogate marker for IR[23].
Assessment of albuminuria and glomerular filtration rate
The estimated glomerular filtration rate (eGFR) in each patient was calculated using an equation for Chinese subjects, as previously described[24]. The normal rate of albumin excretion is less than 30 mg/day; therefore, persistent albumin excretion between 30 and 300 mg/day is classified as microalbuminuria and albumin excretion above 300 mg/day is considered macroalbuminuria[25].
Biochemical analysis
Blood samples were obtained by antecubital vein puncture in a fasting, non-sedative state between 09:00 and 10:00 AM in the control and study groups to exclude the possible influence of circadian variations. All blood samples were collected into Vacutainer SST tubes (BD, Franklin Lakes, NJ) and centrifuged at 3000 rpm for 10 minutes; subsequently, serum samples were collected and stored at − 80 °C in multiple aliquots, prior to biochemical measurement.
Serum levels of TGs, total cholesterol, HDL-C, low-density lipoprotein cholesterol, blood sugar, glycohemoglobin (HBA1c), and high-sensitive C-reactive protein (hs-CRP) were analyzed by the hospital’s central laboratory.
Biomarkers for oxidative stress
We evaluated the oxidative stress condition in all subjects by measuring the serum thiobarbituric acid-reactive substance (TBARS) and thiol levels. Serum TBARS levels were measured using a well-established method for detecting lipid peroxidation with a commercially available assay kit (Cayman Chemical, Ann Arbor, Michigan, USA). The Assay Kit was used according to the manufacturer's instructions, as previously described[26]. The values for the samples were calculated using a linear calibration curve, which was prepared using pure malondialdehyde-containing samples (range, 0–50 µmol/L).
The ability of anti-oxidative defense in response to increased oxidative damage was evaluated by measuring the serum levels of total reduced thiols because serum thiols are physiologic free radical scavengers. Serum total protein thiols were estimated by directly reacting thiols with 5,5-dithiobis 2-nitrobenzoic acid to form 5-thio-2-nitrobenzoic acid (TNB). The number of thiols in the sample was calculated based on absorbance, which was determined using the extinction coefficient of TNB (A412 = 13,600/M/cm).
ELISA Analysis for biomarkers of endothelial dysfunction and adipokines
Serum sICAM-1 and sVCAM-1 levels were assessed using commercially available ELISA kits (R & D Systems, Minneapolis, MN, USA), as previously described[27]. Leptin and adiponectin levels were evaluated in the quality-controlled central laboratory of the CGMH. Serum chemerin levels were assessed by duplicated determination with a commercially available ELISA kit (R&D Systems, Inc., Minneapolis, MN, USA), according to the manufacturer’s instructions, and the mean minimum detectable dose was 4.13 pg/mL.
Assessment and scoring of cardiovascular autonomic functions
All subjects underwent a standardized evaluation of cardiovascular autonomic function, as described by Low[28]. The test battery comprised the heart rate response to deep breathing (HR_DB), Valsalva ratio (VR), and 5-minute head-up tilt (HUT) tests. Orthostatic SBP change was defined as the difference between minimum SBP during HUT and baseline SBP. The detailed methodology for computing HR_DB and VR were based on a previous study[28]. The severity of CAN was assessed using the cardiovagal and adrenergic sub-scores of the CASS[29]. The CASS had a scale from 0 to 7 points in this study, and patients with a CASS score ≥ 2 were defined as having CAN (CASS-based)[30].
In addition, CARTs are considered gold-standard measures of autonomic function in patients with DM[14]. Parameters, which were computed as Ewing’s methods, included heart rate responses to deep breathing (E:I ratio), to standing (30:15 ratio), and to the Valsalva maneuver and blood pressure responses to standing[31], were often used by diabetologists. These autonomic parameters were also obtained, and the severity of CAN was quantitated by summation of points obtained from each of the four tests (CARTs score), where each test was given a point of 0 or 1, if it yielded normal or abnormal values. The CARTs provided a score of 0 to 4 points in this study. CAN was defined with the presence of at least two abnormal test results, i.e., CARTs score ≥ 2 (CARTs-based)[14].
Assessment of baroreflex sensitivity
A 5-minute resting recording of an EKG was obtained before the 5-minute HUT test. Non-invasive estimates of baroreflex sensitivity (BRS) were computed with the recording, using the sequence method of the Nevrokard BRS analysis program (Nevrokard, Slovenia). The following setting was used in computing BRS: 1) RR interval (RRI) variation greater than 5 ms; 2) SBP changes > 1 mmHg; 3) sequences longer than 3 beats; and 4) correlation coefficient > 0.85. Patient with both bradycardic (increase in SBP that caused an increase in RRI) and tachycardic sequences (decrease in SBP that caused a decrease in RRI) that fulfilled the criteria, were used in the analysis. Fluctuations of RRI and SBP were synchronous for some subjects, while in other subjects a time-lag between these two fluctuations was observed. Therefore, BRS was calculated using synchronous mode as well as shift mode from 1 to 6 heart beat shifts for each subject[32]. The mode with the largest number of slopes was selected, and the averaged slope of regression lines was used as the measure of BRS.
Parameters of HRV
The standard deviation of all normal R-R intervals (SDNN) was calculated using the 5-minute resting EKG recording as the time domain parameter for HRV. In addition, power spectral density analysis of HRV was also performed to obtain the parameters in the frequency domain. Three main spectral components were distinguished in a spectrum calculated from the 5-minute recording: high frequency (HF, 0.15–0.4 Hz), low frequency (LF, 0.04–0.15 Hz), and very low frequency (0–0.04 Hz). The components of LF and HF were computed both in absolute values of power (ms2) and in normalized unit (n.u.). The LF/HF ratio, regarded as an index of sympatho-vagal balance, was also calculated[33]. The above computing process was performed using Kubios HRV Standard version 3.2 (Kubios Oy, Finland)
Statistical analysis
Data are expressed as means ± standard derivations or medians (interquartile ranges). Categorical variables were compared using Chi-square or Fisher’s exact tests. Continuous variables that were not normally distributed by Kolmogorov–Smirnov test were logarithmically transformed to improve normality and compared. Five separate statistical analyses were performed. First, patients were stratified into two groups according to the presence or absence of CAN by the CASS-based method. Second, the risk factors for the presence of CAN, including sex and baseline characteristics, underlying diseases, and parameters of laboratory testing, were analyzed using stepwise logistic regression. Third, receiver operating characteristic (ROC) curves were generated for significant adipocytokines levels in the presence of CAN by both CASS-based and CARTs-based CAN. The area under the ROC curves (AUC) was calculated for the presence of CAN. Fourth, correlation analysis was used to evaluate the relationship between the CASS and variables that included age, diabetes duration, BMI, WC, SPB, and DSP, and peripheral blood studies for vascular risks. We also used correlation analysis to evaluate the relationship between leptin and variables related to vascular risk factors. Finally, stepwise models of multiple linear regression analysis were used to evaluate the influence of independent variables on the mean CASS and CARTS scores. All statistical analyses were conducted using the SAS software package, version 9.1 (2002, SAS Statistical Institute, Cary, North Carolina).