Autonomic-inflammatory crosstalk in diabetic atherogenesis: a neuroimmune triad (HRV-LMR-hsCRP) predicts carotid plaque risk in type 2 diabetes
摘要
Type 2 diabetes mellitus (T2D) is associated with a high risk of cardiovascular complications, including carotid atherosclerosis (CAS). This study aimed to investigate the link between CAS and T2D by identifying novel risk factors and examining the relationship between autonomic dysfunction (via heart rate variability, HRV) and systemic inflammation.
MethodsWe conducted a retrospective observational study of 232 T2D patients, categorized into three groups based on carotid ultrasound: normal arteries (n = 47), intima-media thickening (n = 49), and carotid plaques (n = 136). Differences in clinical and inflammatory markers across groups were analyzed. Independent risk factors for CAS were identified using multivariate logistic regression, and a predictive model was developed and evaluated by Receiver Operating Characteristic (ROC) curve analysis. To infer causality, a bidirectional two-sample Mendelian randomization (MR) analysis was performed using summary-level data from large-scale genome-wide association studies (GWAS).
ResultsSignificant differences were observed in age, insulin usage, and inflammatory markers (NLR, PLR, LMR) among the groups (all p < 0.05). Logistic regression identified age, SDNN (a measure of HRV), LMR, and hs-CRP as independent risk factors for CAS. The combined model integrating hs-CRP, SDNN, and LMR demonstrated exceptional predictive accuracy for CAS (AUC = 0.941; 95% CI: 0.912–0.969). MR analysis provided genetic evidence supporting a causal relationship between genetically predicted HRV reduction and increased carotid intima-media thickness.
ConclusionOur findings underscore the critical interplay between autonomic dysfunction and inflammation in the development of CAS in T2D. The proposed integrative model shows high potential for risk stratification. Future large-scale multicenter studies are warranted to validate these findings and elucidate the underlying mechanisms.