Associations of C-reactive protein, triglyceride–glucose index, and the C-reactive protein–triglyceride glucose index with multistate trajectories in the cardiovascular–renal–diabetes cluster

医学 接收机工作特性 内科学 星团(航天器) 协变量 冠状动脉疾病 糖尿病 肾脏疾病 心脏病学 分段线性函数 多发病率 非线性系统 统计 数学 2型糖尿病 比例危险模型 动脉粥样硬化性心血管疾病 分段 疾病 索引(排版) 灵敏度(控制系统) 接头(建筑物) 试验预测值 队列 曲线下面积 生命银行 Lasso(编程语言) 2型糖尿病
作者
H. L. Li,Liuyu Chen,Mengyi Wang,Wenke Cheng,Zhongyan Du,Yuli Huang
出处
期刊:Frontiers in Endocrinology [Frontiers Media]
卷期号:17: 1758467-1758467
标识
DOI:10.3389/fendo.2026.1758467
摘要

Objective: To investigate the associations of C-reactive protein (CRP), triglyceride-glucose (TyG) index, and their composite-the CRP-TyG index (CTI)-with sequential trajectories within the cardiovascular-renal-diabetes (CRD) cluster, including incident coronary artery disease (CAD), type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), and multimorbidity. Methods: We analyzed 333,698 participants from the UK Biobank who were free of CAD, T2DM, and CKD at baseline. CRP and TyG were assessed individually and jointly through the CTI. Multistate Cox models were applied to evaluate six predefined transitions within the CRD cluster, with multimorbidity defined as the coexistence of at least two of CAD, T2DM, and CKD. Potential nonlinearity was assessed using restricted cubic splines, and time-dependent effects were examined with piecewise analyses. Joint exposure analyses assessed synergistic effects of CRP and TyG, while receiver operating characteristic (ROC) curves compared the predictive performance of CRP, TyG, their combination, and CTI. Subgroup and sensitivity analyses were performed to test heterogeneity and robustness. Results: During a median follow-up of 15.31 years (IQR, 14.54-16.03 years), CTI was consistently associated with higher risks of CAD (HR per 1-SD: 1.23, 95% CI: 1.21-1.25), T2DM (1.88, 95% CI: 1.84-1.92), CKD (1.22, 95% CI: 1.19-1.25), and multimorbidity (1.59, 95% CI: 1.55-1.64), outperforming CRP and TyG individually. CTI exhibited trajectory-specific heterogeneity, with nonlinear associations observed in most baseline-to-disease transitions (P for nonlinearity <0.05) and predominantly linear associations during progression from single diseases to multimorbidity (all P for nonlinearity >0.05). Moreover, higher CTI was associated with a time-dependent cumulative increase in multimorbidity risk. In joint exposure analyses, participants with both high CRP and high TyG had the greatest risks across outcomes, including CAD (HR 1.48, 95% CI: 1.40-1.56), CKD (HR 1.52, 95% CI: 1.40-1.64), T2DM (HR 3.63, 95% CI: 3.35-3.93), and multimorbidity (HR 2.64, 95% CI: 2.47-2.82). Conclusions: CRP, TyG, and CTI were strongly associated with both the onset and progression of the cardiovascular-renal-diabetes cluster. By integrating metabolic and inflammatory risk signals, CTI outperformed its individual components, underscoring its clinical utility for refined risk stratification and for guiding early, stage-specific prevention strategies.
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