We had quarterly measured over a two year period: blood pressure via arm cuff, body weight, rectal temperature, and morphometric measurements including waist and hip circumferences, and blood pressure. Following collection of baseline data, 16 monkeys had been assigned to an atherogenic diet and 7 monkeys to a control diet. We have obtained measures of vascular stiffness: Doppler pulse wave velocity and applanation tonometry;morphologic characterization of atherosclerosis: CE-MRI;and blood chemistry measures: glucose, cholesterol, triglycerides, HDL, LDL, ox-LDL, CRP, MMPs, TIMPs, MTMMPs,MCP-1,TGF-beta1. After sacrifice, we harvested arterial tissue, including aorta: ascending and descending thoracic, aorta arches;carotid arteries: right and left;coronary arteries: left descending coronary, right coronary. These tissues will be analyzed in the levels of transcription, translation, distribution, activation for the previously mentioned biomolecules. In addition, we have isolated arterial endothelial and smooth muscle cells from these monkeys for in vitro studies. Results shows that pulse wave velocity (PWV) determined by ultrasound examination, and the intimal and medial thickness (IMT) determined by MRI, dynamically increased in monkeys with advancing age and high cholesterol diets. Histochemical observation and morphological analysis indicate that age increases intimal thickness and medial thickness along with atherosclerotic lesions in these domestic monkeys fed normal diets. Interestingly, age effects fat deposition within arterial walls in these domestic monkeys with high cholesterol diets. We will further define the molecular and cellular mechanisms of atherogenesis during aging via combinational analysis of parameters from blood biochemistry, echo, MRI, histopathological, and gene and protein expression of the aforementioned molecules. Young and old monkeys were divided into control group and groups treated with caloric restriction, high salt food and high cholesterol food. Comprehensive quantitative proteomic studies (8-plex iTRAQ and 2-D DIGE) were designed to analyze proteomic changes of carotid arteries in the different conditions. In ITRAQ experiments, a protein mixture from the young control group was used as common denominator in different experiments. The relative protein abundance of each animal can be compared and analyzed in all the animals. For 2-D DIGE experiment, each experiment compared 2 samples, the animals were paired in the following ways: young control vs old control, young control vs young treated, old control vs old treated. So far, we have finished one iTRAQ experiment, which gave protein abundance changes between young and old control monkeys. We have found 7 proteins are less abundant and 13 proteins are more abundant in old animals. For example, the proteins which are less abundant include Protein S100-A6 ,Isocitrate dehydrogenase NADP , Myelin P0 protein , Myosin-7, Aldo-keto reductase family 1 member B10, Protein S100-A4, Calmodulin and SPATS2-like protein . The proteins which are more abundant include Programmed cell death protein 6, Periostin , Apolipoprotein E, Erythrocyte band 7 integral membrane protein, Translation initiation factor IF-2 Complement component C9, Lactadherin( MFG-E8), Apolipoprotein C-I Vitronectin , Annexin A7, Cysteine and glycine-rich protein 2, Serine protease HTRA1,Serum amyloid P-component and Complement C1q tumor necrosis factor-related protein. In addition, we have also identified protein abundance changes using 2-D DIGE. More than 20 proteins spots have been found that have different abundance between protein extract of carotid arteries from young and old monkeys. The identification of the protein is in progress. Importantly, we have performed micro RNA array of carotid arteries in monkeys with or without high cholesterol diets. In brief, hybridization of Hy3-labeled RNA was performed on the miRCURY LNA miRNA microarray slide (version 11.0-other species), which contains 505 miRNA probes, including 473 monkey miRNA genes, spotted in quadruplicate. The microarray data normalized by Z score transformation were analyzed in the calculation of significant changes in gene expression changes between different samples and conditions. The statistic results show that there are totally 91 modified miRs, via a continuous age analysis (2-way ANOVA). 15 miRs significantly change with aging, 67 miRs are significantly different in abundance associated with high cholesterol diet treatment. microRNA array results were validated by real-time PCR. Expression of mature miRNAs was analyzed with the TaqMan MicroRNA Reverse Transcription Kit and TaqMan MicroRNA assays according to the instructions of the manufacturer (Applied Biosystems Inc). Part of PCR validation results showed that miR-21, miR-34a, miR-155, miR-210, miR-199a, miR-199a-3p, miR-423-5p, let-7i are indeed modulated with age and/or high cholesterol diet treatment. Studies of bioroles of those miRs in aging and atherosclerosis are in progress. Preliminary statistical analyses using a T test, showed that at baseline, cholesterol (p=0.39), triglycerides (p=0.64), and glucose (p=0.18) were not different between the control and treated group. At the second follow-up, cholesterol levels in the treated group were different from controls (p<0.0001) but triglycerides and glucose significance were not altered. The correlation of these parameters with other covariates found that at baseline, cholesterol was negatively associated with body weight in the controls but not in treated. There was a borderline significance with SBP and DBP again only in the controls. At the second follow-up glucose was related with bodyweight in the controls but not in the treated group. In a mixed models analyses, cholesterol, triglycerides and glucose were modeled separately using treatment group, first age and time as fixed effects along with their interaction terms. For cholesterol it was noted that the treatment group with time interaction was significant indicating that treatment on these monkeys over a period of time had an effect on cholesterol levels. In the glucose model, first age was a significant predictor while in the triglyceride model neither first age, nor time nor the treatment group and none of the interactions were significant. In addition to the blood chemistry, four imaging parameters, namely contrast enhancement, wall thickness, lumen diameter and T2thickest triad will be analyzed at the same time points as the other measures were done and correlate these parameters with the blood parameters to find associations at all time points. Delta will be calculated for each of the parameter and plotted as a function of age. Descriptive statistics, T tests, ANOVAs and plots will be used to explore these data. Multiple regression analyses will be run for each variable, with age, blood pressure variables, blood chemistry variables and other imaging variables for each time point. To allow each monkey to have its own intercept and slope, and deviate from the average line, mixed models analyses will be used to model these variables. Lastly tissues were obtained post-necropsy of these monkeys and measurements were made on ascending and descending aorta, abdominal aorta, intima-media thickness on normal segment and lesioned segments. These variables will also be incorporated in the analyses appropriately.

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National Institute on Aging (NIA)
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