Integrative Analysis of Genomic Risk Factors in Juvenile Idiopathic Arthritis

描述(由申请人提供)：青少年特发性关节炎(JIA)，每10,000名北美儿童中有1人患有，包括一组高度不同的慢性、免疫调节的关节疾病。慢性疾病活动除了导致剧烈疼痛、组织损伤和身体不能动弹外，还会导致永久性矮小和肢体毁容。与其他一些复杂的多基因自身免疫性疾病类似，JIA有明显的可遗传成分，但所有已知的遗传风险因素对疾病遗传性的解释不到20%。其中大部分可归因于主要组织亲和性的变异 (MHC)基因座，但对JIA中MHC关联的明确高分辨率鉴定尚未得出定论。贾跃亭目前被分为七个临床亚型，基于一个几乎没有研究或临床实用的分类方案，因为10%-50%的病例被归类为“未分化”。基于血清自身抗体和其他免疫缺陷分子生物标志物的生物学和分子证据表明，现有的7种JIA亚型可分为两大类-代表以血清阳性为主的自身免疫(AID)疾病或血清阴性的自身炎症(AIF)疾病。AID和AIF样JIA亚型的遗传风险因素是否不同尚不清楚，特别是在存在显著的表型异质性的情况下，传统的遗传关联研究方法很难识别具有亚型特异性效应的基因座。为了验证这样的假设，即不同的遗传风险因素是临床观察到的AID和AIF样JIA亚型差异的基础，并确定共同的和亚型不同的遗传易感基因座，我建议使用亚型敏感的GWA来识别JIA疾病亚型特定的遗传学关联，评估在JIA亚型中不同或共享的功能性HLA关联的证据，并测试已识别的遗传关联是否可以用于预测疾病易感性，区分属于AID和AIF样JIA类别的患者，以及重新分类目前定义为未区分疾病的患者。本文提出的分析方法集成了基因组筛选、疾病建模和预测，以及使用表达和功能数据资源来更好地了解JIA的病原学。这项工作的成功完成可能会产生新的生物分子或基于途径的靶点，用于开发治疗JIA儿童和其他相关风湿病或免疫学疾病的药物。

DESCRIPTION (provided by applicant): Juvenile Idiopathic Arthritis (JIA), afflicting ~1 in 10,000 North American Children, encompasses a highly heterogeneous group of chronic, immune-mediated joint disorders. Aside from causing severe pain, tissue damage, and physical immobility, chronic disease activity leads to permanent short stature and limb disfigurement. Similar to a number of other complex polygenic autoimmune diseases, there is a clear heritable component to JIA, but all known genetic risk factors explain less than 20% of disease heritability. The majority of this is attributable to variation across the Major Histocompatibility (MHC) locus, yet definitive high-resolution identification of MHC associations in JIA have not been conclusive. JIA is currently classified into seven clinical subtypes, based on a classification schema that has little research or clinical utility, since 10-50% of cases are classified as "undifferentiated". Biological and molecular evidence based on the presence of serum autoantibodies and other molecular biomarkers of immunological defects suggest that the existing seven JIA subtypes could be grouped into two major classes-subtypes that represent either predominantly seropositive autoimmune (AID) diseases or seronegative autoinflammatory (AIF) diseases. Whether genetic risk factors differ for AID versus AIF-like JIA subtypes is unknown, especially since the traditional approach to genetic association studies is poorly powered to identify loci with subtype- specific effects in the presence of significant phenotypic heterogeneity. To test the hypothesis that distinct genetic risk factors underlie the clinically observed differences in AID versus AIF-like JIA subtypes and identify both shared and subtype-distinct genetic susceptibility loci, I propose to use a subtype-sensitive GWAS to identify JIA disease subtype-specific genetics associations, evaluate evidence for functional HLA associations that are distinct or shared across JIA subtypes, and test if the identified genetic associations can be used to predict disease susceptibility, distinguish patients who belong to AID versus AIF-like JIA classes, and reclassify patients currently defined as having undifferentiated disease. The analysis approach proposed here integrates genomic screening, disease modeling and prediction, and the use of expression and functional data resources to better understand the etiology of JIA. The successful completion of this work will likely yield novel biomolecular or pathway-based targets for the development of therapeutic agents for children with JIA and patients with other related rheumatological or immunological diseases.