Proteomic signatures characterized by inflammatory signaling and metabolic processes have divergent associations with 30-year incidence of coronary artery disease in type 1 diabetes: the Pittsburgh Epidemiology of Diabetes Complications cohort.

IF 15.6 1区 医学 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS
J Zhou, J C Mychaleckyj, F Haddad, T Costacou, T J Orchard, R G Miller
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引用次数: 0

Abstract

Background: While inflammation is hypothesized to be a possible driver of the excess coronary artery disease (CAD) observed in type 1 diabetes, prior biomarker studies have focused on candidate proteins, overlooking the complex systemic processes underlying atherosclerosis. We thus applied a high-throughput proteomics approach to identify proteins prospectively associated with CAD in type 1 diabetes. We further hypothesized inflammatory proteins would partially mediate the effect of glycemic exposure on CAD risk.

Methods: We measured 184 circulating proteins (Olink CVD II and III panels) in earliest available serum samples from the Pittsburgh Epidemiology of Diabetes Complications cohort of childhood-onset (< 17 years) type 1 diabetes (n = 417, baseline mean age 30, mean diabetes duration 22 years). Protein modules were identified using weighted correlation network analysis. Prospective associations between modules (per eigenvalue SD) and 30-year incident hard CAD (hCAD; CAD death, nonfatal myocardial infarction, revascularization, or blockage ≥ 50%) were estimated in Cox models. Causal mediation analysis estimated mediation of the HbA1c-hCAD association by the modules.

Results: Incident hCAD occurred in 151 participants (36.2%). We identified three protein modules: one comprising 56 proteins, enriched for TNF/Notch signaling, T-cell activation, and necroptosis; another comprising 33 proteins, enriched for lipid catabolism, epithelial cell apoptosis, vitamin D response; and a third comprising 33 proteins, enriched for hemostasis, wound healing, and vascular growth factors. After adjusting for traditional covariates and HbA1c, greater abundance of proteins in the first module was associated with increased hCAD incidence (HR = 1.35, 95% CI: 1.06-1.72, p = 0.014) while the second module was protective (HR = 0.82, 95% CI: 0.70-0.96, p = 0.017). The third module was not associated with hCAD (HR = 1.03, 95%CI: 0.86-1.23, p = 0.751). The first module mediated 14% of the total HbA1c effect on hCAD.

Conclusions: In this prospective analysis of a type 1 diabetes cohort, a protein signature characterized by inflammatory signaling partially mediated the effect of hyperglycemia on hCAD, while a signature characterized by metabolic processes including lipid catabolism and hormone response was associated with hCAD protection independent of glycemia. These findings move beyond single-marker associations, identifying distinct protein signatures that warrant further study as intervention targets for CAD prevention in type 1 diabetes.

以炎症信号和代谢过程为特征的蛋白质组学特征与1型糖尿病患者30年冠状动脉疾病发病率存在不同的关联:匹兹堡糖尿病并发症流行病学队列
背景:虽然炎症被假设为1型糖尿病中观察到的过量冠状动脉疾病(CAD)的可能驱动因素,但先前的生物标志物研究主要集中在候选蛋白上,忽视了动脉粥样硬化背后复杂的全身过程。因此,我们应用高通量蛋白质组学方法来鉴定与1型糖尿病CAD相关的蛋白质。我们进一步假设炎症蛋白会部分介导血糖暴露对冠心病风险的影响。方法:我们测量了来自匹兹堡糖尿病并发症流行病学儿童发病队列的最早血清样本中的184种循环蛋白(Olink CVD II和III组)(结果:151名参与者(36.2%)发生了hCAD事件)。我们确定了三种蛋白质模块:一种包含56种蛋白质,富含TNF/Notch信号,t细胞活化和坏死性坏死;另一种包含33种蛋白质,富含脂质分解代谢、上皮细胞凋亡和维生素D反应;第三种含有33种蛋白质,富含止血、伤口愈合和血管生长因子。在调整了传统协变量和HbA1c后,第一个模块中蛋白质的丰度越高,hCAD发病率越高(HR = 1.35, 95% CI: 1.06-1.72, p = 0.014),而第二个模块则具有保护作用(HR = 0.82, 95% CI: 0.70-0.96, p = 0.017)。第三个模块与hCAD无关(HR = 1.03, 95%CI: 0.86-1.23, p = 0.751)。第一个模块介导了HbA1c对hCAD总影响的14%。结论:在这项对1型糖尿病队列的前瞻性分析中,以炎症信号为特征的蛋白质信号部分介导了高血糖对hCAD的影响,而以代谢过程为特征的信号,包括脂质分解代谢和激素反应,与不依赖于血糖的hCAD保护有关。这些发现超越了单一标志物的关联,确定了不同的蛋白质特征,值得进一步研究作为1型糖尿病冠心病预防的干预靶点。
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来源期刊
Cardiovascular Diabetology
Cardiovascular Diabetology 医学-内分泌学与代谢
CiteScore
12.30
自引率
15.10%
发文量
240
审稿时长
1 months
期刊介绍: Cardiovascular Diabetology is a journal that welcomes manuscripts exploring various aspects of the relationship between diabetes, cardiovascular health, and the metabolic syndrome. We invite submissions related to clinical studies, genetic investigations, experimental research, pharmacological studies, epidemiological analyses, and molecular biology research in this field.
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