Relationship between Copper, Zinc, and Copper-to-Zinc Ratio in Hair and Severity of Coronary Artery Disease according to the SYNTAX Score.
Ewelina Anna DziedzicJakub S GąsiorAgnieszka TuzimekEwa CzestkowskaJoanna BeckBeata JaczewskaElżbieta ZgnilecAndrzej OsieckiMirosław KwaśnyMarek J DąbrowskiWacław KochmanPublished in: Biology (2023)
Coronary artery disease (CAD) continues to be a foremost contributor to global mortality, and the quest for modifiable risk factors could improve prophylactic strategies. Recent studies suggest a significant role of zinc (Zn) and copper (Cu) deficiency in atheromatous plaque formation. Furthermore, hair was previously described as a valuable source of information on elemental burden during the 6-8 week period before sampling. The aim of this study was to investigate the possibility of correlation between the extent of CAD evaluated with the SYNergy Between PCI With TAXUS and the Cardiac Surgery (SYNTAX) score with Cu and Zn content in hair samples, as well as with the Cu/Zn ratio in a cohort of 130 patients. Our findings describe a statistically significant inverse correlation between Cu content and the Cu/Zn ratio in hair samples and the extent of CAD. In contrast, no significant correlation was found between Zn content and the extent of CAD. Considering the scarcity of existing data on the subject, the analysis of hair samples could yield a novel insight into elemental deficiencies and their potential influence on CAD extent.
Keyphrases
- coronary artery disease
- oxide nanoparticles
- cardiovascular events
- percutaneous coronary intervention
- heavy metals
- risk factors
- coronary artery bypass grafting
- cardiac surgery
- aqueous solution
- end stage renal disease
- metal organic framework
- chronic kidney disease
- ejection fraction
- acute kidney injury
- healthcare
- acute myocardial infarction
- magnetic resonance
- magnetic resonance imaging
- clinical trial
- st elevation myocardial infarction
- risk assessment
- machine learning
- computed tomography
- social media
- artificial intelligence
- contrast enhanced