Endothelial dysfunction can be regarded as the earliest feature of vascular aging and may occur in individuals without traditional risk factors for cardiovascular disease. Once present, endothelial dysfunction is known to increase the risk for atherosclerosis, cardiovascular diseases and complications such as stroke or death. Identification of individuals with early features of vascular aging remains challenging and has fuelled investigative efforts to associated biologic, imaging, and digital markers with endothelial dysfunction. This review highlights emerging and traditional methods to identify patients with early endothelial dysfunction and summarizes available and experimental therapies aimed at mitigating the vascular aging process.

Background: A subset of individuals with major depressive disorder (MDD) have a high burden of cardiovascular risk factors and cerebral small‐vessel disease, implicating vascular disease in the development of depression. Cross‐sectional studies demonstrate a link between endothelial dysfunction and MDD, but the prospective association between peripheral endothelial dysfunction (PED) and an incident diagnosis of MDD is unknown. Methods and Results: Patients undergoing a baseline assessment of cardiovascular risk were evaluated for PED using reactive hyperemia–peripheral arterial tonometry (≤1.8 consistent with PED). Patient medical records were reviewed to identify those who underwent a formal clinical evaluation of MDD after the index PED evaluation. The frequency of PED was compared in those with and without MDD. Logistic regression analyses were performed to assess the association between baseline PED and incident MDD. Between January 2006 and December 2020, 1614 patients underwent testing for PED. Four hundred eighty‐four (30.1%) patients underwent a formal evaluation for MDD after (0–15 years) the index procedure (mean±SD age, 52.8±13.8 years; 65.2% women). Of these, 157 (32.4%) had PED and 108 (31.0%) were diagnosed with MDD. Individuals with MDD had a higher frequency of PED (40.2% versus 30.2%; P =0.034) compared with those without MDD. In multivariable analyses, PED was significantly associated with MDD (odds ratio, 2.3 [95% CI, 1.4–3.8]; P <0.001). Conclusions: PED is significantly associated with incident MDD. Thus, PED may be a useful marker to identify individuals at increased risk of depression who may benefit from more frequent and earlier management strategies.

Background: Inadequate preventive dental care may contribute to inflammatory conditions such as periodontitis, increasing cardiovascular disease risk. Artificial intelligence–enabled electrocardiography (AI‐ECG) algorithms accurately estimate cardiovascular disease risk. We investigated the association between inadequate preventive dental care and the AI‐ECG–estimated risk of atrial fibrillation, aortic stenosis, low ejection fraction, cardiac amyloid, cardiovascular aging, and all‐cause mortality. Methods: We retrospectively analyzed 266 637 Mayo Clinic patients (2018–2024) who completed a Social Determinants of Health Survey and had an ECG performed within 1 year of survey completion. AI‐ECG algorithms generated continuous risk scores (0 or 1) for atrial fibrillation, aortic stenosis, low ejection fraction, and amyloid. Cardiac aging was assessed by delta age, calculated as AI‐ECG–estimated physiological age minus the chronological age. Associations with preventive dental care were analyzed using logistic regression. Cox regression evaluated dental care predictiveness on all‐cause mortality. Results: Among 266 637 individuals (mean age, 59.5±16.4 years; 51.1% women), 49 918 (18.7%) reported inadequate preventive dental care. These individuals had higher delta age and increased AI‐ECG–predicted risks of atrial fibrillation, aortic stenosis, amyloid, and reduced ejection fraction (all P <0.001). In multivariable logistic regression models including all AI‐ECG scores, inadequate preventive dental care was associated with higher probabilities of low ejection fraction (odds ratio [OR], 1.80 [95% CI, 1.69–1.91]), atrial fibrillation (OR, 1.10 [95% CI, 1.04–1.17]), aortic stenosis (OR, 1.90 [95% CI, 1.64–2.20]), amyloid (OR, 1.18 [95% CI, 1.12–1.25]), and higher delta age (OR, 1.03 [95% CI, 1.02–1.03]) (all P <0.001). Inadequate preventive dental care predicted all‐cause mortality after adjusting for demographics, risk factors, and AI‐ECG algorithms (HR, 1.45 [95% CI, 1.38–1.53], P <0.001). Conclusions: Inadequate preventive dental care is associated with subclinical cardiovascular disease. AI‐ECG algorithms may facilitate cardiovascular risk stratification among individuals with limited preventive dental care access.