Multiplex analysis of inflammatory proteins associated with risk of coronary artery disease in type-1 diabetes patients

BackgroundChronic uncontrolled hyperglycemia, a precursor to chronic low-grade inflammation, is a leading cause of coronary artery disease (CAD) due to plaque buildup in type-1 diabetes (T1D) patients. We evaluated levels of 22 inflammatory markers in cross-sectional serum samples from 1222 subjects to evaluate their potential as risk factors for CAD in T1D patients.HypothesisCirculating levels of markers of inflammation may be the risk factors for incident CAD.MethodsThe T1D subjects were divided into two groups: those without CAD (n = 1107) and with CAD (n = 115). Serum levels of proteins were assayed using multiplex immunoassays on a Luminex Platform. Differences between the two groups were made by univariate analysis. Multivariate logistic regression was used to ascertain the potential of proteins as risk factors for CAD. Influence of age, duration of diabetes, sex, hypertension, and dyslipidemia was determined in a stepwise manner. Serum levels of 22 proteins were combined into a composite score using Ridge regression for risk-based stratification.ResultsMean levels of CRP, IGFBP1, IGFBP2, insulin-like growth factors binding protein-6 (IGFBP6), MMP1, SAA, sTNFRI, and sTNFRII were elevated in CAD patients (n = 115) compared to T1D patients without CAD (nCAD, n = 1107). After adjusting for age, duration of diabetes, sex, hypertension, and dyslipidemia, higher levels of sTNFRI (odds ratio [OR] = 2.18, 1.1 x 10-3), sTNFRII (OR = 1.52, 1 x 10-2), and IGFBP6 (OR = 3.62, 1.8 x 10-3) were significantly associated with CAD. The composite score based on Ridge regression, was able to stratify CAD patients into low, medium, and high-risk groups.ConclusionsThe results show activation of the TNF pathway in CAD patients. Evaluating these markers in serum can be a potential tool for identifying high-risk T1D patients for intensive anti-inflammatory therapeutic interventions. Serum levels of 22 proteins were measured in type-1 diabetes (T1D) patients with and without coronary artery disease (CAD) in a high-throughput manner using multiplex immunoassays. Machine learning-based scores can stratify CAD patients into low, medium, and high-risk groups. Our findings have translational potential to identify T1D patients at higher risk of CAD.image