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Dietary restriction but not angiotensin II type 1 receptor blockade improves DNA damage-related vasodilator dysfunction in rapidly aging Ercc1Δ/- mice.(2017-08-01)DNA damage is an important contributor to endothelial dysfunction and age-related vascular disease. Recently, we demonstrated in a DNA repair-deficient, prematurely aging mouse model (Ercc1Δ/- mice) that dietary restriction (DR) strongly increases life- and health span, including ameliorating endothelial dysfunction, by preserving genomic integrity. In this mouse mutant displaying prominent accelerated, age-dependent endothelial dysfunction we investigated the signaling pathways involved in improved endothelium-mediated vasodilation by DR, and explore the potential role of the renin-angiotensin system (RAS). Ercc1Δ/- mice showed increased blood pressure and decreased aortic relaxations to acetylcholine (ACh) in organ bath experiments. Nitric oxide (NO) signaling and phospho-Ser1177-eNOS were compromised in Ercc1Δ/- DR improved relaxations by increasing prostaglandin-mediated responses. Increase of cyclo-oxygenase 2 and decrease of phosphodiesterase 4B were identified as potential mechanisms. DR also prevented loss of NO signaling in vascular smooth muscle cells and normalized angiotensin II (Ang II) vasoconstrictions, which were increased in Ercc1Δ/- mice. Ercc1Δ/- mutants showed a loss of Ang II type 2 receptor-mediated counter-regulation of Ang II type 1 receptor-induced vasoconstrictions. Chronic losartan treatment effectively decreased blood pressure, but did not improve endothelium-dependent relaxations. This result might relate to the aging-associated loss of treatment efficacy of RAS blockade with respect to endothelial function improvement. In summary, DR effectively prevents endothelium-dependent vasodilator dysfunction by augmenting prostaglandin-mediated responses, whereas chronic Ang II type 1 receptor blockade is ineffective.
Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis.(2017-10-15)The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction.