Clinical Risk Prediction Modeling in Rheumatoid Arthritis

描述（由申请人提供）：该提案是作为NIH R01 AR49880-03“女性RA的激素，细胞因子和遗传风险”的竞争延续提交的，其中我们确定了生殖因素包括母乳喂养，月经初潮和不规则月经，炎症标志物包括抗ccp抗体，TNFR2水平和催乳素基因中的新型RA风险等位基因是RA的重要危险因素。扩展我们开发临床风险预测模型的工作，该提案建立在我们在护士健康研究中研究RA流行病学的良好记录上，这是世界上最大的前瞻性风湿病队列。我们的合作研究者最近在RA的全基因组关联研究中发现了新的风险位点。然而，尽管在了解RA的遗传基础方面进展迅速，但尚不清楚如何在临床上利用这些信息来预测RA。识别自身抗体和细胞因子存在多年前RA发病提供了一个令人兴奋的机会，在临床前阶段进行干预。然而，了解类风湿关节炎危险因素的作用对于高危人群的潜在毒性治疗是至关重要的。预测建模在类风湿关节炎预防临床试验的进展中至关重要。我们建议建立一个RA临床风险预测模型，将RA遗传易感性等位基因和环境风险因素及其相互作用纳入其中，并在美国和瑞典的大型队列中进行验证。在一个独特的高风险RA队列中进一步验证，代表了预防试验的目标群体，将有助于了解模型是否预测临床前RA的发展，这是未来RA预防试验的重要信息。我们提出以下目标：1)在护士健康研究（NHS）的700例RA病例和700例匹配对照，以及RA流行病学调查（EIRA）队列的2000例病例和1150例匹配对照中，使用经过验证的RA易感等位基因，得出遗传风险评分（GRS），并检查GRS与RA风险之间的关系，特别是与RA血清阳性风险之间的关系；2)建立两种RA临床预测模型，以预测所有RA以及由性别、免疫表型和家族史定义的亚型的5年RA风险：(a)使用行为因素、环境暴露和临床因素的“环境”模型，以及(b)使用环境因素、GRS和基因-环境相互作用术语的“环境+遗传”模型；3)检验在Aim 2中开发和验证的预测模型的拟合优度，用于预测一个中间终点，临床前RA定义的自身抗体，或RA症状，在一个独特的高风险RA队列中，类风湿关节炎病因学研究（SERA）由2100个RA病例的一级亲属和800个富集HLA-DR4等位基因的个体组成（总N=2900）。基于简单的遗传风险评分、行为、环境和临床风险因素准确预测个体5年发展为临床类风湿性关节炎的风险的能力将是一个巨大的进步，使风险因素修改和更早地引入有效的治疗来消除这种疾病的破坏和残疾。

DESCRIPTION (provided by applicant): This proposal is submitted as a competing continuation of NIH R01 AR49880-03, Hormone, Cytokine and Genetic Risks for RA in Women, in which we identified reproductive factors including breastfeeding, early menarche, and irregular menses, inflammatory markers including anti-CCP antibodies, and TNFR2 levels and a novel RA risk allele in the prolactin gene as significant risk factors for RA. Extending our work to develop clinical risk prediction models, this proposal builds on our strong track record of studying RA epidemiology in the Nurses' Health Studies, the largest prospective rheumatic disease cohorts in the world. Recent whole genome association studies in RA from our co-investigators have identified novel risk loci. However, despite rapid advances in understanding the genetic basis of RA, it is unclear how to utilize this information clinically for RA prediction. Identification of autoantibodies and cytokines present many years prior to RA onset provides an exciting opportunity to intervene during the pre-clinical phase. However, it is critical to understand the role of RA risk factors for the targeting of potentially toxic therapies at highest risk individuals. Predictive modeling is critical in the progress towards an RA prevention clinical trial. We propose to build a RA clinical risk prediction models incorporating RA genetic susceptibility alleles and environmental risk factors and their interactions, with validation in large U.S. and Swedish cohorts. Further validation in a unique high risk RA cohort, representing a target group for prevention trials, will lead to understanding of whether the models predict development of pre-clinical RA, essential information for future RA prevention trials. We propose the following aims: 1) Using validated RA susceptibility alleles, derive a Genetic Risk Score (GRS) and examine associations between GRS and RA risk in general, and with seropositive RA risk specifically, in 700 RA cases and 700 matched controls from the Nurses' Health Study (NHS) and in 2000 cases and 1150 matched controls from the Epidemiologic Investigation of RA (EIRA) cohort; 2) Develop two RA clinical prediction models to predict 5-year RA risk for all RA and for subsets defined by sex, immune phenotype, and family history: (a) an "environmental" model using behavioral factors, environmental exposures, and clinical factors , and (b) an "environmental + genetic" model with environmental factors, GRS, and gene-environment interaction terms; and 3) Examine the goodness of fit of the prediction models developed and validated in Aim 2 for predicting an intermediate endpoint, pre-clinical RA defined autoantibodies, or RA symptoms, in a unique high risk RA cohort, the Studies of the Etiologies of Rheumatoid Arthritis (SERA) comprised of 2100 first-degree relatives of RA cases and of 800 individuals enriched with HLA-DR4 alleles (total N=2900). The ability to accurately predict an individual's 5-year risk of developing clinical RA based on a simple genetic risk score, behavioral, environmental and clinical risk factors would be an enormous advance, enabling risk factor modification and earlier introduction of effective therapies to abrogate the destruction and disability of this disease.