The Ethical Committee approved the protocol and informed written consent was obtained from all participants. All the investigations were performed in accordance with the principles of the Declaration of Helsinki.
The study group consisted of 462 Caucasian newly diagnosed hypertensive patients, 216 men and 246 women aged 49.6±12.2 years, participating in the Catanzaro Metabolic Risk factors Study. All subjects underwent physical examination and review of their medical history. Causes of secondary hypertension were excluded by appropriate clinical and biochemical tests. Other exclusion criteria were history or clinical evidence of coronary and valvular heart disease, congestive heart failure, peripheral vascular disease, chronic inflammatory diseases, anemia, gastrontestinal diseases with malabsorption, history of any malignant disease, history of alcohol or drug abuse, liver or kidney failure and diabetes already diagnosed. No patient had ever been treated with antihypertensive drugs. All subjects underwent anthropometrical evaluation with measurements of weight, height, and body mass index (BMI). After 12-h fasting, a 75 g oral glucose tolerance test (OGTT) was performed with 0, 30, 60, 90 and 120 minutes sampling for plasma glucose and insulin. Glucose tolerance status was defined on the basis of OGTT using the World Health Organization (WHO) criteria.
Blood Pressure Measurements
Measurements of clinic BP were obtained in the left arm of the patients, in supine position, after 5 min of quiet rest, with a aneroid sphygmomanometer. A mean value of at least three BP readings were taken in three different visits at least 2 weeks apart. Systolic and diastolic BP were recorded at the first appearance (phase I) and the disappearance (phase V) of Korotkoff sounds, respectively. A value of clinic systolic BP (SBP) ≥140 mmHg and/or diastolic BP (DBP) ≥90 mmHg identified patients as hypertensive according to current guidelines . In addition, pulse pressure (PP) was defined as the difference between SBP and DBP.
All blood samples were obtained after overnight fasting. Serum ferritin levels (10-290 ng/ml) were measured using an immunoturbidimetric assay (Roche Diagnostics, Indianapolis, IN, USA). The serum iron (50-150 µg/dl) was measured with a colorimetric method and transferrin (2-4 g/l) by a nephelometric assay , while the percentage of saturated transferrin iron binding capacity (TIBC) was measured using a colorimetric test (Roche Diagnostics, Cobas 8000, Switzerland). Hemoglobin was determined using an automated particle counter (Siemens Healthcare Diagnostics ADVIA® 120/2120 Haematology System, Milan, Italy).
Plasma glucose was measured by the glucose oxidation method (Beckman Glucose Analyzer II; Beckman Instruments, Milan, Italy). Triglyceride, total, low- (LDL) and high-density lipoprotein (HDL) cholesterol concentrations were evaluated by enzymatic methods (Roche, Basel, Switzerland). Serum insulin levels were determined by a chemiluminescence-based assay ((Immulite ®, Siemens, Italy).). Insulin sensitivity was evaluated using the Matsuda index [insulin sensitivity index (ISI)], calculated as follows: 10,000/square root of [fasting glucose (millimoles per liter) x fasting insulin (milliunits per liter)]*[mean glucose * mean insulin during OGTT]. The Matsuda index is strongly related to euglycemic hyperinsulinemic clamp that represents the gold standard test for measuring insulin sensitivity .
Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were determined using the alpha-ketoglutarate reaction, and g-glutamyltransferase (γGT) levels with the L-γ-glutamyl-3-carboxy-4-nitroanilide rate method (Roche, Basel, Switzerland). High sensitivity CRP (hsCRP) were measured by automated instrument (CardioPhase ® hsCRP, Milan, Italy). Finally, creatinine levels were measured by Jaffe methodology and estimated glomerular filtration rate (e-GFR) was computed by using the chronic kidney disease epidemiology (CKD-EPI) collaboration equation .
Arterial stiffness evaluation
All measurements were obtained using a validated system (Sphygmocor™; AtCor Medical, Sydney, Australia) that utilizes high-fidelity applanation tonometry (Millar) and an appropriate computer software for the evaluation of pressure wave (Sphygmocor™). At first, the pressure calibration was achieved by the non-invasive automatic recording of supine brachial artery BP in the dominant arm after a 30 minutes of rest (Dinamap Compact T; Johnson & Johnson Medical Ltd, Newport, UK). In particular, BP was measured five times over 10 minutes and the mean of the last three determinations was considered for calibration. On the radial artery of the dominant arm, the pressure wave was recorded as the average of single waves consecutively obtained for eight seconds. Pressure wave determinations were considered reliable only if the variation of peak and bottom pressures of pressure waves was <5%. The central pressure wave assessment was automatically derived from the radial measurements by a generalized transfer function . Moreover, central waveforms were evaluated to identify the time to peak/shoulder of the first (T1) and second (T2) pressure wave elements during systole. The pressure at the peak/shoulder of T1 was classified as outgoing pressure wave height (P1), the pressure at the peak/shoulder of T2 was defined as the reflected pressure wave height (P2), either as an absolute value or as percent of ejection duration. Augmentation pressure (AP) was defined as difference between P2–P1, and augmentation index (AI) as [AP/pulse pressure (PP)] * 100. Aortic pulse wave velocity (PWV) was measured from carotid and femoral pressure waveforms. Carotid to femoral transit time (ΔT) was calculated from the foot-to-foot time delay between carotid and femoral waveforms. The distance between the landmarks of the sternal notch and femoral artery was considered to evaluate the path length between the carotid and femoral arteries (L), and PWV calculated as L/ΔT.
Data are reported as mean and standard deviation or as absolute and percent frequency, as appropriate. Comparisons among more than two groups were performed by One Way ANOVA, followed by a Bonferroni post-hoc between-groups comparison. Chi-squared test was utilized for categorical variables. The association between continuous variables was assessed by Pearson product moment correlation coefficient (r) and p value. The relationship between gender and PWV was investigated by point biserial correlation coefficient and p value. As potential confounders for the relationship between ferritin and PWV we considered all variables listed in Table 1 and those associated with this biomarker with p<0.05 at univariate analyses (see last column in Table 1) were considered to be introduced into the multiple linear regression model. To avoid collinearity, we did not include iron and transferrin into the multiple liner regression model because these two variables lied into the same causal pathway between ferritin and PWV. Similarly, we did not adjust for insulin to avoid collinearity between this variable and the MATSUDA index. To assess the variance of PWV explained by each covariate into the model, we calculated the squared of the partial correlation coefficient. The effect modification by ferritin on the relationship between hs-CRP and PWV was investigated by introducing into the same linear regression model ferritin (the effect modifier), hs-CRP and their interaction term (ferritin * hsCRP) as well as a series of potential confounders. The estimated increase of PWV associated to a fixed increase in CRP (+1 mg/l) across quartiles of ferritin (36 ng/ml, 86 ng/ml, and 159 ng/ml) was investigated by the standard linear combination method . In multiple linear regression models, data were expressed as standardised regression coefficients (beta) and p value. All statistical analyses were performed using SPSS version 22 for Windows (Chicago, Illinois, USA) and STATA statistical package (version 13, Texas, USA).