Heart Disease in Rheumatoid Arthritis

描述(申请人提供)：类风湿性关节炎(RA)是一种慢性炎症性和自身免疫性疾病，以高发病率和死亡率为特征，并严重残疾。在该奖项的前几个周期中，我们发现，与普通人群相比，RA患者患心血管(CV)疾病(即心肌梗死和心力衰竭)的可能性明显更大，且心血管疾病后的预后明显更差。此外，RA患者的心血管疾病表现出明显不同的风险特征，传统的心血管风险因素发挥的作用相对较小(有时是自相矛盾的)，而炎症/免疫功能障碍的标记物发挥的作用要大得多。事实上，我们证明了为普通人群(例如Framingham)开发的CV风险预测工具在RA中几乎没有价值，这是因为校准(即预测绝对风险的能力)和辨别能力(即区分低风险和高风险的能力)较差。因此，在当前的赠款周期中，我们引入了一种新的表型生物标志物-免疫反应信号，它(在横断面研究中)显著改善了对患有无症状心肌功能障碍的RA受试者的识别。这项续签申请的目的是改善RA患者的心血管风险预测。我们建议：1)建立(在纵向研究中)免疫反应信号与我们丰富的流行病学数据相结合的实用性，用于预测RA的心肌功能，检查疾病活动和生物治疗的影响；2)创建并验证一种新的、针对RA的心血管风险评估工具。在目标1中，我们将重复对心肌功能的评估，并测试假设，即11个细胞因子免疫反应特征(在当前的捐赠周期中开发)在调整人口统计学、疾病特征和心血管特征后，是未来心肌功能障碍的重要预测因子。我们将比较在两个时间点测量的免疫反应特征，并测试特征改善与心肌功能障碍风险降低相关的假设，以及调查生物疗法的影响。在目标2中，我们将通过重新校准Framingham和其他可用的CV风险评分来设计一个新的、针对RA的CV风险评分，以更准确地预测RA的CV风险；并通过系统地评估RA疾病特征、实验室测量和免疫反应特征以纳入新的CV风险评分，以实现最大限度的区分。为了确保新评分的概括性，将使用大型(n=25,977)和成熟的国家风湿病数据库进行外部验证。创建有效的心血管风险预测工具和生物标志物将使筛查和预防战略能够针对那些可能受益最大的人，从而降低RA患者的心血管发病率、死亡率和医疗成本。

DESCRIPTION (provided by applicant): Rheumatoid Arthritis (RA) is a chronic inflammatory and autoimmune disorder characterized by high morbidity and mortality, and profound disability. During the prior cycles of this award, we discovered that RA patients are significantly more likely to develop cardiovascular (CV) disease (i.e., myocardial infarction and heart failure) and have significantly worse outcomes after CV disease, compared to the general population. Moreover, CV disease in persons with RA showed a markedly different risk profile, with traditional CV risk factors playing a relatively less important (and sometimes paradoxical) role, and markers of inflammation/immune dysfunction playing a much greater role. Indeed, we demonstrated that CV risk prediction tools developed for the general population (e.g., Framingham) were of little value in RA, due to poor calibration (i.e., ability to predict absolute risk), and poor discrimination (i.e., ability to distinguish low from high risk). Thus, we introduced, in the current grant cycle, a novel phenotypic biomarker, immune response signatures, which (in cross sectional studies) significantly improved identification of RA subjects with silent myocardial dysfunction. The objective of this renewal application is to improve CV risk prediction for persons with RA. We propose to: 1) establish (in longitudinal studies) the utility of immune response signatures, when combined with our rich epidemiological data, for predicting myocardial function in RA, examining the impact of disease activity and biological treatment; and 2) create and validate a new, RA-specific, CV risk assessment tool. In Aim 1 we will repeat assessment of myocardial function and test the hypothesis that the 11 cytokine immune response signature (developed in the current grant cycle) is a significant predictor of future myocardial dysfunction after adjusting for demographic, disease features and CV characteristics. We will compare immune response signatures measured at 2 time points and test the hypotheses that improvement in signature is associated with lower risk for myocardial dysfunction, as well as investigating the impact of biological therapies. In Aim 2 we will devise a new, RA-specific, CV risk score by re-calibrating the Framingham, and other available CV risk scores to more accurately predict CV risk for RA; and by systematically evaluating RA disease characteristics, laboratory measures and immune response signatures for inclusion into the new CV risk score, in order to maximize discrimination. To ensure generalizability of the new score, external validation will be conducted using the large (n=25,977) and well established National Databank for Rheumatic Diseases. The creation of effective CV risk prediction tools and biomarkers will enable targeting of screening and prevention strategies towards those who could benefit the most, thereby reducing CV morbidity, mortality, and healthcare costs in persons with RA.