| Literature DB >> 34970157 |
Kristina R Gopcevic1, Eugenia Gkaliagkousi2, János Nemcsik3,4, Ömür Acet5, M Rosa Bernal-Lopez6, Rosa M Bruno7, Rachel E Climie7,8,9, Nikolaos Fountoulakis10, Emil Fraenkel11, Antonios Lazaridis2, Petras Navickas12, Keith D Rochfort13, Agnė Šatrauskienė12,14, Jūratė Zupkauskienė12, Dimitrios Terentes-Printzios15.
Abstract
Impairment of the arteries is a product of sustained exposure to various deleterious factors and progresses with time; a phenomenon inherent to vascular aging. Oxidative stress, inflammation, the accumulation of harmful agents in high cardiovascular risk conditions, changes to the extracellular matrix, and/or alterations of the epigenetic modification of molecules, are all vital pathophysiological processes proven to contribute to vascular aging, and also lead to changes in levels of associated circulating molecules. Many of these molecules are consequently recognized as markers of vascular impairment and accelerated vascular aging in clinical and research settings, however, for these molecules to be classified as biomarkers of vascular aging, further criteria must be met. In this paper, we conducted a scoping literature review identifying thirty of the most important, and eight less important, biomarkers of vascular aging. Herein, we overview a selection of the most important molecules connected with the above-mentioned pathological conditions and study their usefulness as circulating biomarkers of vascular aging.Entities:
Keywords: cellular matrix; circulating biomarkers; epigenetics; inflammation; oxidative stress; vascular aging
Year: 2021 PMID: 34970157 PMCID: PMC8712891 DOI: 10.3389/fphys.2021.789690
Source DB: PubMed Journal: Front Physiol ISSN: 1664-042X Impact factor: 4.566
FIGURE 1Several circulating biomarkers which are proposed to mirror the major pathophysiological mechanisms that contribute to vascular aging in the vascular wall, namely inflammation/atherosclerosis, oxidative stress and genetics-epigenetics.
Extracellular matrix biomarkers as predictors of risk in CVD.
| Biomarker | Tissue | Clinical context | No. of subjects/type of the study/length of follow-up | Main findings | References |
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| Serum | Atherosclerosis | 260/cross-sectional study/– | Serum levels associated with plaque burden |
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| Plasma | Type 1 diabetes | 337/cohort/12.3 | Association with CVD |
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| Serum | CAD, MI | 7928/cohort/13 | Predictor of mortality |
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| Plasma | CVD | 1127/cohort/4.1 | Predictor of cardiovascular mortality | |
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| Serum | PAD | 187/cohort/2 | Increased levels associated with mortality |
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| Plasma | Atherosclerosis, CAD, T2DM | 1500/proximity extension assay technology/– | Plaque development |
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| Plasma | CVD | 389/prospective/2 | Predictive of all-cause death, MI and cardiac mortality |
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CAD, coronary artery disease; CVD, cardiovascular disease; PAD, peripheral artery disease; MI, myocardial infarction; T2DM, type 2 diabetes mellitus; –, no data.
Significance of several microRNAs (miRs) in vascular aging process (based on a systematic review by Navickas et al., 2016).
| Process | Type of microRNAs |
| Endothelial function and angiogenesis |
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| Vascular smooth muscle cell differentiation |
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| Communication between vascular smooth muscle |
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| Apoptosis |
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| Cardiac myocyte differentiation |
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| Repression of cardiac hypertrophy |
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