Dataset Information

Vascular PPARgamma controls circadian variation in blood pressure and heart rate through Bmal1.

ABSTRACT: Thiazolidinediones (TZDs) are PPARgamma activators that exhibit vasculoprotective properties. To determine the vascular function of PPARgamma, we analyzed Tie2Cre/flox and SM22Cre/flox mice. Unexpectedly, both knockout strains exhibited a significant reduction of circadian variations in blood pressure and heart rate in parallel with diminished variations in urinary norepinephrine/epinephrine excretion and impaired rhythmicity of the canonical clock genes, including Bmal1. PPARgamma expression in the aorta exhibited a robust rhythmicity with a more than 20-fold change during the light/dark cycle. Rosiglitazone treatment induced aortic expression of Bmal1 mRNA, and ChIP and promoter assays revealed that Bmal1 is a direct PPARgamma target gene. These studies have uncovered a role for vascular PPARgamma as a peripheral factor participating in regulation of cardiovascular rhythms.

SUBMITTER: Wang N

PROVIDER: S-EPMC5484540 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature

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Vascular PPARgamma controls circadian variation in blood pressure and heart rate through Bmal1.

Wang Ningning N Yang Guangrui G Jia Zhanjun Z Zhang Hui H Aoyagi Toshinori T Soodvilai Sunhapas S Symons J David JD Schnermann Jurgen B JB Gonzalez Frank J FJ Litwin Sheldon E SE Yang Tianxin T

Cell metabolism 20081201 6

Thiazolidinediones (TZDs) are PPARgamma activators that exhibit vasculoprotective properties. To determine the vascular function of PPARgamma, we analyzed Tie2Cre/flox and SM22Cre/flox mice. Unexpectedly, both knockout strains exhibited a significant reduction of circadian variations in blood pressure and heart rate in parallel with diminished variations in urinary norepinephrine/epinephrine excretion and impaired rhythmicity of the canonical clock genes, including Bmal1. PPARgamma expression in ...[more]

PMID: 19041764

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Project description:Within the intensive care unit (ICU), arterial blood pressure (ABP) is typically recorded at different (and sometimes uneven) sampling frequencies, and from different sensors, and is often corrupted by different artifacts and noise which are often non-Gaussian, nonlinear and nonstationary. Extracting robust parameters from such signals, and providing confidences in the estimates is therefore difficult and requires an adaptive filtering approach which accounts for artifact types.Using a large ICU database, and over 6000 hours of simultaneously acquired electrocardiogram (ECG) and ABP waveforms sampled at 125 Hz from a 437 patient subset, we documented six general types of ABP artifact. We describe a new ABP signal quality index (SQI), based upon the combination of two previously reported signal quality measures weighted together. One index measures morphological normality, and the other degradation due to noise. After extracting a 6084-hour subset of clean data using our SQI, we evaluated a new robust tracking algorithm for estimating blood pressure and heart rate (HR) based upon a Kalman Filter (KF) with an update sequence modified by the KF innovation sequence and the value of the SQI. In order to do this, we have created six novel models of different categories of artifacts that we have identified in our ABP waveform data. These artifact models were then injected into clean ABP waveforms in a controlled manner. Clinical blood pressure (systolic, mean and diastolic) estimates were then made from the ABP waveforms for both clean and corrupted data. The mean absolute error for systolic, mean and diastolic blood pressure was then calculated for different levels of artifact pollution to provide estimates of expected errors given a single value of the SQI.Our artifact models demonstrate that artifact types have differing effects on systolic, diastolic and mean ABP estimates. We show that, for most artifact types, diastolic ABP estimates are less noise-sensitive than mean ABP estimates, which in turn are more robust than systolic ABP estimates. We also show that our SQI can provide error bounds for both HR and ABP estimates.The KF/SQI-fusion method described in this article was shown to provide an accurate estimate of blood pressure and HR derived from the ABP waveform even in the presence of high levels of persistent noise and artifact, and during extreme bradycardia and tachycardia. Differences in error between artifact types, measurement sensors and the quality of the source signal can be factored into physiological estimation using an unbiased adaptive filter, signal innovation and signal quality measures.

Dataset Information

Vascular PPARgamma controls circadian variation in blood pressure and heart rate through Bmal1.

Publications

Vascular PPARgamma controls circadian variation in blood pressure and heart rate through Bmal1.

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