Published online Dec 15, 2023. doi: 10.4239/wjd.v14.i12.1754
Peer-review started: August 21, 2023
First decision: September 29, 2023
Revised: October 11, 2023
Accepted: November 3, 2023
Article in press: November 3, 2023
Published online: December 15, 2023
Processing time: 114 Days and 22.1 Hours
Coronary artery disease (CAD) is a widespread global health issue, responsible for a significant number of deaths. India bears a substantial burden, contributing to approximately one-fifth of CAD-related fatalities. The development of CAD has been closely linked to the accumulation of Nε-carboxymethyl-lysine (CML) in the heart muscle, a phenomenon associated with fibrosis. Understanding the role of CML in CAD development is crucial for combating this life-threatening condition.
This study is motivated by the need to shed light on the factors contributing to CAD, especially in the context of diabetes. CAD is a complex disease, and understanding its underlying mechanisms can help in early diagnosis and more effective management. Diabetes is a significant risk factor for CAD, and investigating the interplay between CML, inflammatory markers, and CAD in individuals with and without diabetes can provide valuable insights into its pathogenesis.
The primary objective of this research was to evaluate the impact of CML and inflammatory markers on the biochemical and cardiovascular characteristics of CAD patients, differentiating between diabetic and non-diabetes patients. The study aimed to identify potential links between CML, diabetes, and CAD and to assess if these factors could serve as predictive biomarkers.
To achieve these objectives, this study enrolled 200 consecutive CAD patients undergoing coronary angiography. The patients were categorized into two groups based on their serum glycosylated hemoglobin (HbA1c) levels, with diabetic CAD patients (group I) having HbA1c levels of ≥ 6.5 and non-diabetic CAD patients (group II) with HbA1c levels < 6.5. Various parameters, including lipoprotein levels, plasma HbA1c levels, CML, interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and nitric oxide levels, were analyzed to assess the differences between the two groups.
The study revealed several significant findings. Group I, comprising 81 males and 19 females, had a mean age of 54.2 ± 10.2 years, with a mean diabetes duration of 4.9 ± 2.2 years. Group II, consisting of 89 males and 11 females, had a mean age of 53.2 ± 10.3 years. Group I exhibited more severe CAD, with a higher percentage of patients suffering from triple vessel disease and more severe stenosis in the left anterior descending coronary artery compared to group II. Group I patients also had a larger left atrium diameter. Significantly, group I patients displayed higher levels of CML, TNF-α, and IL-6 and lower levels of nitric oxide compared to group II patients. The study also demonstrated strong correlations between CML and inflammatory markers, with CML showing a significant positive correlation with IL-6 (r = 0.596, P = 0.001) and TNF-α (r = 0.337, P = 0.001) and a negative correlation with nitric oxide (r=-4.16, P = 0.001). Odds ratio analysis indicated that patients with CML in the third quartile (264.43-364.31 ng/mL) were significantly associated with diabetic CAD at both unadjusted and adjusted levels when considering various covariates.
CML and inflammatory markers, particularly IL-6 and TNF-α, may play a significant role in the development of CAD, especially in individuals with diabetes. These findings suggest that CML and inflammatory markers can serve as potential biomarkers for predicting CAD, not only in diabetic patients but also in non-diabetic individuals. Understanding the mechanisms linking CML and inflammation to CAD provides valuable insights for improved CAD diagnosis, risk assessment, and management, which can ultimately contribute to reducing the burden of this life-threatening disease.
Future studies should explore interventions targeting CML and inflammatory markers to mitigate CAD risk. Investigating therapeutic strategies and diagnostic tools based on these biomarkers can aid in early CAD detection and personalized treatment, potentially reducing CAD-related mortality rates globally.