Intravascular imaging in cardiovascular ageing

Vascular aging and cardiovascular disease: pathophysiology and measurement in the coronary arteries

Age is a key risk factor for cardiovascular disease, including atherosclerosis. However, pathophysiological disease processes in the arteries are not an inevitable feature of aging. Large cohort studies with arterial phenotyping along with clinical and demographic data are essential to better understand factors related to the susceptibility or resilience to age-related vascular pathophysiology in humans. This review explores the mechanisms by which vascular structure and function alters with age, and how these changes relate to cardiovascular pathophysiology and disease. Features of vascular aging in the coronary arteries have historically been difficult to quantify pre-mortem due to their size and location. However, non-invasive imaging modalities including CT Coronary Angiogram are now being used to assess coronary vascular age, and further advances in imaging analysis such as the CT Fat Attenuation Index will help provide further measurement of features associated with coronary vascular aging. Currently, markers of vascular aging are not used as therapeutic targets in routine clinical practice, but non-pharmacological interventions including aerobic exercise and low salt diet, as well as anti-hypertensives have been demonstrated to reduce arterial stiffness. Advances in imaging technology, both in acquisition and advanced analysis, as well as harmonisation of measurements for researchers across the globe will be invaluable in understanding what constitutes healthy vascular aging and in identifying features of vascular aging that are associated with coronary artery disease and its adverse outcomes. Assessing such images in large cohorts can facilitate improved definitions of resilient and susceptible phenotypes to vascular aging in the coronary arteries. This is a critical step in identifying further risk factors and biomarkers within these groups and driving forward the development of novel therapies aimed at slowing or stopping age-related vascular changes in the coronary arteries.

Ageing- and AAA-associated differentially expressed proteins identified by proteomic analysis in mice

Background

Abdominal aortic aneurysm (AAA) is a disease of high prevalence in old age, and its incidence gradually increases with increasing age. There were few studies about differences in the circulatory system in the incidence of AAA, mainly because younger patients with AAA are fewer and more comorbid nonatherosclerotic factors.

Method

We induced AAA in ApoE^-/- male mice of different ages (10 or 24 weeks) and obtained plasma samples. After the top 14 most abundant proteins were detected, the plasma was analyzed by a proteomic study using the data-dependent acquisition (DDA) technique. The proteomic results were compared between different groups to identify age-related differentially expressed proteins (DEPs) in the circulation that contribute to AAA formation. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) network analyses were performed by R software. The top 10 proteins were determined with the MCC method of Cytoscape, and transcription factor (TF) prediction of the DEPs was performed with iRegulon (Cytoscape).

Results

The aortic diameter fold increase was higher in the aged group than in the youth group (p < 0.01). Overall, 92 DEPs related to age and involved in AAA formation were identified. GO analysis of the DEPs showed enrichment of the terms wounding healing, response to oxidative stress, regulation of body fluid levels, ribose phosphate metabolic process, and blood coagulation. The KEGG pathway analysis showed enrichment of the terms platelet activation, complement and coagulation cascades, glycolysis/gluconeogenesis, carbon metabolism, biosynthesis of amino acids, and ECM-receptor interaction. The top 10 proteins were Tpi1, Eno1, Prdx1, Ppia, Prdx6, Vwf, Prdx2, Fga, Fgg, and Fgb, and the predicted TFs of these proteins were Nfe2, Srf, Epas1, Tbp, and Hoxc8.

Conclusion

The identified proteins related to age and involved in AAA formation were associated with the response to oxidative stress, coagulation and platelet activation, and complement and inflammation pathways, and the TFs of these proteins might be potential targets for AAA treatments. Further experimental and biological studies are needed to elucidate the role of these age-associated and AAA-related proteins in the progression of AAA.