C-Reactive Protein: The Quintessential Marker of Systemic Inflammation in Coronary Artery Disease-Advancing toward Precision Medicine.
Emanuel Amezcua-CastilloHector Gonzalez-PachecoArturo Sáenz-San MartínPablo Méndez-OcampoIván Gutierrez-MoctezumaFelipe MassóDaniel Sierra-LaraRashidi SpringallEmma RodríguezAlexandra Arias-MendozaLuis M Amezcua GuerraPublished in: Biomedicines (2023)
Atherosclerotic cardiovascular disease (CVD) remains the leading cause of mortality worldwide. While conventional risk factors have been studied and managed, CVD continues to pose a global threat. Risk scoring systems based on these factors have been developed to predict acute coronary syndromes and guide therapeutic interventions. However, traditional risk algorithms may not fully capture the complexities of individual patients. Recent research highlights the role of inflammation, particularly chronic low-grade inflammation, in the pathogenesis of coronary artery disease (CAD). C-reactive protein (CRP) is an inflammatory molecule that has demonstrated value as a predictive marker for cardiovascular risk assessment, both independently and in conjunction with other parameters. It has been incorporated into risk assessment algorithms, enhancing risk prediction and guiding therapeutic decisions. Pharmacological interventions with anti-inflammatory properties, such as statins, glucagon-like peptide-1 agonists, and interleukin-1 inhibitors, have shown promising effects in reducing both cardiovascular risks and CRP levels. This manuscript provides a comprehensive review of CRP as a marker of systemic inflammation in CAD. By exploring the current knowledge surrounding CRP and its implications for risk prediction and therapeutic interventions, this review contributes to the advancement of personalized cardiology and the optimization of patient care.
Keyphrases
- coronary artery disease
- risk assessment
- low grade
- cardiovascular events
- cardiovascular disease
- risk factors
- percutaneous coronary intervention
- oxidative stress
- human health
- machine learning
- physical activity
- acute coronary syndrome
- coronary artery bypass grafting
- end stage renal disease
- anti inflammatory
- ejection fraction
- healthcare
- heavy metals
- deep learning
- chronic kidney disease
- newly diagnosed
- metabolic syndrome
- aortic valve
- solid state
- breast cancer risk