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Perivascular adipose tissue as a source of therapeutic targets and clinical biomarkers. | LitMetric

AI Article Synopsis

  • Obesity is a key cardiovascular risk factor that involves different types of adipose tissue (AT) with varying roles, such as visceral AT promoting arterial plaque and subcutaneous AT serving mainly for energy storage.
  • The position paper presents a consensus on defining perivascular adipose tissue (PVAT) around coronary arteries and discusses its importance in regulating vascular health and its potential as a therapeutic target for cardiovascular diseases.
  • It emphasizes PVAT’s role as a 'biosensor' for vascular inflammation, highlighting new imaging technologies for non-invasive risk assessment and the future application of artificial intelligence to enhance cardiovascular preventive strategies.

Article Abstract

Obesity is a modifiable cardiovascular risk factor, but adipose tissue (AT) depots in humans are anatomically, histologically, and functionally heterogeneous. For example, visceral AT is a pro-atherogenic secretory AT depot, while subcutaneous AT represents a more classical energy storage depot. Perivascular adipose tissue (PVAT) regulates vascular biology via paracrine cross-talk signals. In this position paper, the state-of-the-art knowledge of various AT depots is reviewed providing a consensus definition of PVAT around the coronary arteries, as the AT surrounding the artery up to a distance from its outer wall equal to the luminal diameter of the artery. Special focus is given to the interactions between PVAT and the vascular wall that render PVAT a potential therapeutic target in cardiovascular diseases. This Clinical Consensus Statement also discusses the role of PVAT as a clinically relevant source of diagnostic and prognostic biomarkers of vascular function, which may guide precision medicine in atherosclerosis, hypertension, heart failure, and other cardiovascular diseases. In this article, its role as a 'biosensor' of vascular inflammation is highlighted with description of recent imaging technologies that visualize PVAT in clinical practice, allowing non-invasive quantification of coronary inflammation and the related residual cardiovascular inflammatory risk, guiding deployment of therapeutic interventions. Finally, the current and future clinical applicability of artificial intelligence and machine learning technologies is reviewed that integrate PVAT information into prognostic models to provide clinically meaningful information in primary and secondary prevention.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568001PMC
http://dx.doi.org/10.1093/eurheartj/ehad484DOI Listing

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