Increased levels of uric acid (UA) have been shown to be correlated with many clinical conditions. Uric acid may adversely affect the insulin signalling pathway inducing insulin resistance (IR). Several studies report the association between arterial stiffness (AS), an early indicator of atherosclerosis, and UA. The purpose of the present study was to evaluate the association between UA and AS, considering the potential role of IR. We enrolled 1114 newly diagnosed, never-treated hypertensive patients. Insulin resistance was assessed by the homeostatic model assessment (HOMA) index. Arterial stiffness was evaluated as the measurement of the carotid–femoral pulse wave velocity (PWV). The study cohort was divided into subgroups, according to increasing tertiles of UA. The mean values of UA were 5.2 ± 1.6 mg/dL in the overall population. Pulse wave velocity was linearly correlated with UA (p < 0.0001), HOMA (p < 0.0001), high sensitivity C-reactive protein (p < 0.0001), systolic blood pressure (p < 0.0001) and LDL cholesterol (p = 0.005). Uric acid was the strongest predictor of PWV and was associated with the highest risk for increased AS. The interaction analysis showed that the joint effect of increased UA and HOMA was significantly higher than that expected in the absence of interaction under the additive model, indicating that the two biomarkers synergically interacted for promoting vascular damage. Our data showed that UA interacted with IR to increase AS in a large cohort of newly diagnosed, never-treated hypertensive patients.

Background: Heart failure (HF) with preserved ejection fraction (HFpEF) represents a major comorbidity in the elderly and is associated with cognitive impairment (CoI) and type 2 diabetes mellitus (T2DM). In this context, there is an increase in oxidative stress and platelet activation biomarkers. The aim of this study was to evaluate the effects of 6 months’ treatment with SGLT2i on functional, mood-related, and cognitive aspects, assessed by performing a comprehensive geriatric assessment (CGA), and on oxidative stress and platelet activation biomarkers, in a cohort of HFpEF elderly patients with T2DM. We recruited 150 elderly outpatients (mean age 75.8 ± 7.4 years). Results: At six-month follow-up, there was a significant improvement in MMSE (p < 0.0001), MoCA (p < 0.0001), GDS score (p < 0.0001), and SPPB (p < 0.0001). Moreover, we observed a significant reduction in Nox-2 (p < 0.0001), 8-Isoprostane (p < 0.0001), Sp-Selectin (p < 0.0001), and Gp-VI (p < 0.0001). Considering ΔMMSE as the dependent variable, ΔE/e’, ΔNox-2, ΔHOMA, Δ8-Isoprostane, and ΔUricemia were associated for 59.6% with ΔMMSE. When ΔMoCA was considered as the dependent variable, ΔHOMA, ΔE/e’, Δ8-Isoprostane, ΔNox-2 and ΔUricemia were associated for 59.2%. Considering ΔGDS as the dependent variable, ΔHOMA, ΔNox-2, Δ8-Isoprostane, and ΔUricemia were associated with 41.6% of ΔGDS variation. Finally, ΔHOMA was the main predictor of ΔSPPB, which was associated with 21.3% with ΔSPPB, Δ8-Isoprostane, ΔNox-2, ΔE/e’, and ΔUricemia added another 24.1%. Conclusion: The use of SGLT2i in elderly patients with T2DM and HFpEF significantly contributes to improving CGA scales and biomarkers of OS and PA.

Vitamin D deficiency is linked to cardiac dysfunction, vascular remodeling, metabolic syndrome and insulin resistance (IR). The aim of the present study was to evaluate the association between vitamin D levels and cardiovascular (CV) organ damage in a large cohort of newly diagnosed treatment-naïve hypertensive patients, and the role of IR in this context. We enrolled 500 Caucasian individuals, without CV or renal complications. Subjects underwent a complete evaluation and measurements of vitamin D, standard laboratory determinations and instrumental examination, including echocardiography and applanation tonometry. Linear regression analyses were performed to assess the correlation between pulse wave velocity (PWV) and left ventricular mass index (LVMI) with different covariates. PWV was significantly correlated with age (p < 0.0001), LDL cholesterol (p < 0.0001), BMI (p = 0.001), pulse pressure (PP) (p = 0.005) and high sensitivity C-reactive protein (hs-CRP) (p = 0.006), while an inverse correlation was observed with vitamin D levels (p < 0.0001), Matsuda index (p < 0.0001) and estimated glomerular filtration ratio (e-GFR) (p = 0.006). LVMI significantly correlated with PP (p < 0.0001), hs-CRP (p < 0, 0001) and age (p = 0.001), while an inverse relationship was observed with vitamin D levels (p < 0.0001), Matsuda’s insulin sensitivity index (ISI) (p < 0.0001) and e-GFR (p < 0.0001). Vitamin D was the strongest predictor of PWV and LVMI, explaining, respectively, 28.3% and 19.1% of their variation. Our study suggests that low vitamin D might be a biomarker of end-organ damage.