Red Blood Cell Distribution Width, Vascular Aging Biomarkers, and Endothelial Progenitor Cells for Predicting Vascular Aging and Diagnosing/Prognosing Age-Related Degenerative Arterial Diseases

Abstract

The emerging evidence emphasizes Red blood cell distribution width (RDW) as optimal prognostic biomarker for cardiovascular diseases. However, several clinical biases impede its clinical application. Recent recommendations suggest combining RDW with other biomarkers. Accordingly, we propose evaluating the wellrecognized biomarkers of vascular aging (i.e., the leukocyte telomere length and telomerase activity, and reduced levels of endothelial progenitor cells [EPCs]) with RDW, for predicting the risk for vascular aging and onset and prognosis of age-related degenerative arterial diseases, such as sporadic ascending aorta aneurysm (AAA), characterized to have an increased incidence in old people. Consequently, in this study (and for the first time), we simultaneously investigated the relationship between RDW values, systemic inflammatory molecules, mean values of leukocyte telomere length, telomerase activity and EPCs, and the risk for vascular aging and AAA onset and prognosis. To achieve this aim, we selected 80 old and 80 young healthy subjects and 80 AAA cases. Appropriate methodologies were used for assessing blood parameters, aorta alterations, genotyping, impairment of the leukocyte telomere length, and telomerase activity. The main findings obtained demonstrated that increased RDW values along with the augmented blood levels of high-sensitive C-reactive protein and the reduced mean values of both leukocyte telomere length, telomerase activity, and EPCs are independently associated with the high risk for both vascular aging and AAA onset and prognosis. They might be used as the best predictor biomarker profile for vascular aging, and for both diagnosis and outcome of sporadic AAA.

Red Cell Distribution Width is Associated with Future Incidence of Abdominal Aortic Aneurysm in a Population-Based Cohort Study

“…In a study from the NHANES, it was even reported that RDW was a better predictor of CHD mortality than high sensitivity C-reactive protein (hsCRP) 15 . In addition, in a cross-sectional study of patients diagnosed with aneurysms of the ascending aorta, positive correlations were also found between RDW values and systemic inflammatory molecules, including hsCRP, IL-6, TNF-α, MMP-2, and MMP-9 levels 16 . On the other hand, inflammation is suggested to be involved in the pathological processes of AAA 17,18 .…”

“…It is well known that blood clots can occur in aortic aneurysms due to altered flow conditions, and that such thrombi have potential biochemical and biomechanical effects on both blood components and the aortic wall 26,27 . AAA could also be associated with impaired endothelial function and other features of vascular aging 16 , which in turn, could cause mechanical stress to the erythrocytes. Hypothetically, early vascular changes in individuals with high risk of AAA could affect the life span of the red cells and thereby the RDW.…”

Antihypertensive therapy: controlling the processes of replicative cell senescence

“…Для этого были отобраны 80 пожилых (72±4,8 лет) и 80 молодых (26,2±3,4 лет) здоровых пациентов и 80 пациентов с сердечно-сосудистыми патологиями. Полученные основные результаты показали, что повышенные значения ширины распределения эритроцитов по объему наряду с повышенными уровнями высокочувствительного С-реактивного белка в крови и сниженные средние значения длины теломер в лейкоцитах, АТ и EPC независимо связаны с высоким риском старения сосудов [20].…”

Development and validation of risk prediction models for multiple cardiovascular diseases and Type 2 diabetes

“…Accurate risk assessment of an individual's propensity to develop CVDs is essential for personalized health care and primary prevention of these conditions. An increasing number of novel biomarkers have been linked to CVD risk [3][4][5][6][7][8][9][10][11][12][13][14], implying their critical role in precise risk assessment for heterogeneous CVDs. Current established functions for CVD risk stratification are either based only on conventional risk factors or include a limited number of biomarkers [15][16][17][18].…”