3354Association of plasma concentration of trimethylamine N-oxide and ADP-induced platelet reactivity after a loading dose of clopidogrel 600 mg in patients undergoing elective PCI

Stratz, Christian; Gessner, Arne; Fromm, Martin F.; Hromek, Julia; Nuehrenberg, T; Hille, Laura; Neumann, Franz‐Josef; Hochholzer, Willibald; Trenk, Dietmar

doi:10.1093/eurheartj/ehy563.3354

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“…The cardiac system is a major site where these metabolites can give rise to severe health consequences by inducing cardiovascular diseases (CVDs) ( 30 – 32 ). TMAO has been realized to enhance plaque accumulation inside the arteries (atherosclerosis) ( 33 ), platelet reactivity and blood coagulation (thrombosis) potential ( 34 , 35 ), blockage of arteries in coronary artery disease ( 36 ), the risk of heart failure, vascular inflammation ( 37 , 38 ), as well as abdominal aortic aneurysm ( 39 ) ( Figure 1 ). Some studies have shown that elevated levels of TMAO could also increase the accumulation of macrophage cholesterol and upregulate several macrophage scavenger receptors associated with atherosclerosis ( 40 ) [for more information on gut phage-bacteria interplay and the interactions of bacterial metabolites in cardiometabolic diseases, see ( 41 )].…”

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confidence: 99%

Emerging computational paradigms to address the complex role of gut microbial metabolism in cardiovascular diseases

Aminian-Dehkordi

Valiei

Mofrad

2022

Front. Cardiovasc. Med.

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The human gut microbiota and its associated perturbations are implicated in a variety of cardiovascular diseases (CVDs). There is evidence that the structure and metabolic composition of the gut microbiome and some of its metabolites have mechanistic associations with several CVDs. Nevertheless, there is a need to unravel metabolic behavior and underlying mechanisms of microbiome-host interactions. This need is even more highlighted when considering that microbiome-secreted metabolites contributing to CVDs are the subject of intensive research to develop new prevention and therapeutic techniques. In addition to the application of high-throughput data used in microbiome-related studies, advanced computational tools enable us to integrate omics into different mathematical models, including constraint-based models, dynamic models, agent-based models, and machine learning tools, to build a holistic picture of metabolic pathological mechanisms. In this article, we aim to review and introduce state-of-the-art mathematical models and computational approaches addressing the link between the microbiome and CVDs.

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