Leukocyte Gene Expression and Genetic Biomarkers of OA Incidence and Progression

描述（由申请人提供）：本次竞争性更新将建立在上一阶段的生物标志物发现基础上。在四个目标中，我们将重点关注以下总体假设：“炎症”候选生物标志物可识别有偶发症状性膝关节OA（SKOA）风险的患者，或已确诊的SKOA患者，这些患者疾病进展风险增加。与我们的合作者一起，我们建议使用四个OA队列来验证和复制我们的初步发现：1）NIH骨关节炎倡议（OAI，M。Hochberg）; 2）第二周期OAI+扩展（e）使用高质量X光片的纽约大学（OAI+eNYU）发现队列; 3）约翰斯顿县骨关节炎项目（JoCo，J. Jordan）;和4）全身性骨关节炎遗传学纵向研究（GOGO Long，V. Kraus）。在目标1中，我们将确定候选基因组生物标志物（外周血白细胞炎症基因表达）或血浆蛋白/脂质（GPL）生物标志物是否可预测有症状的放射学膝关节OA受试者的疾病严重程度或进展风险增加。我们将：a）在OAI中验证来自NYU的发现的GPL生物标志物组; B）构建来自OAI+eNYU的GPL生物标志物组; c）在GOGO Long和JoCo中复制该组。在目标2中，我们将确定候选遗传生物标志物（来自GWAS测定的SNP，其映射到来自全外显子组测序测定的炎症基因和外显子变体）是否预测放射学膝关节OA受试者的疾病进展风险增加。我们将：a）构建来自OAI+eNYU的SNP生物标志物组; B）在GOGO+JoCo中验证该组; c）构建来自eNYU+OAI的外显子变体生物标志物组; d）通过在eNYU+OAI中保持验证该组。在目标3中，我们将进行综合分析，应用预测性多测定分析方法来识别遗传变异、基因表达和血浆蛋白/脂质表达之间的潜在致病相互作用。我们将：a）在OAI+eNYU中使用GPL+SNP生物标志物进行整合建模; B）在GOGO和JoCo中验证该模型; c）在OAI+eNYU中使用GPL+SNP+外显子变体生物标志物进行整合建模。在目标4中，我们将确定基因组、遗传和蛋白质/脂质生物标志物是否可预测偶发症状性膝关节OA的风险增加。相关性：骨关节炎是一种影响多个关节的常见疾病，可导致关节破坏、功能丧失和残疾。根据我们的初步数据，我们预计该提案将确定预后生物标志物测试，可以预测疾病发作或快速进展到关节破坏的风险个体。这种预后生物标志物的验证将促进新的疾病修饰OA药物的开发，并且在未来，可以增强疾病的临床管理，如关于药物给药的决定。

DESCRIPTION (provided by applicant): This Competitive Renewal will build upon biomarker discoveries from the previous period. In four Aims we will focus upon the overall hypothesis that "inflammatory" candidate biomarkers identify patients at risk for incident symptomatic knee OA (SKOA), or those patients with established SKOA, who are at increased risk for disease progression. Together with our collaborators on this grant, we propose to validate and replicate our initial discoveries using four OA cohorts: 1) the NIH Osteoarthritis Initiative (OAI, M. Hochberg); 2) a second cycle OAI+expanded (e)NYU (OAI+eNYU) discovery cohort using high quality radiographs; 3) the Johnston County Osteoarthritis Project (JoCo, J. Jordan); and 4) the Genetics of Generalized Osteoarthritis longitudinal study (GOGO Long, V. Kraus). In Aim 1, we will determine whether candidate Genomic biomarkers (peripheral blood leukocyte expression of inflammatory genes) or plasma Protein/Lipid (GPL) biomarkers predict increased risk of disease severity or progression in subjects with symptomatic radiographic knee OA. We will: a) validate discovered GPL biomarker panel from NYU in the OAI; b) construct a panel of GPL biomarkers from OAI+eNYU; c) replicate this panel in GOGO Long and JoCo. In Aim 2 we will determine whether candidate genetic biomarkers (SNPs from GWAS assays that map to inflammatory genes and exonic variants from whole-exome sequencing assay) predict increased risk of disease progression in subjects with radiographic knee OA. We will: a) construct a panel of SNP biomarkers from OAI+eNYU; b) validate this panel in GOGO+JoCo; c) construct a panel of exonic variant biomarkers from eNYU+OAI; d) validate this panel by holdout in eNYU+OAI. In Aim 3 we will perform an integrative analysis, applying a predictive multi-assay analyses approach to identify potential pathogenic interactions among genetic variations, gene expression and plasma protein/lipid expression. We will: a) perform integrative modeling using GPL+SNP biomarkers in OAI+eNYU; b) validate this model in GOGO and JoCo; c) perform integrative modeling using GPL+SNP+exonic variant biomarkers in OAI+eNYU. In Aim 4 we will determine whether genomic, genetic and protein/lipid biomarkers predict increased risk of incident symptomatic knee OA. Relevance: Osteoarthritis is a common disease that affects multiple joints, resulting in joint destruction, loss of function and disability. Base on our preliminary data we expect that this proposal will identify prognostic biomarker test(s) that can predict individuals at risk for disease onset or of progressing rapidly to joint destruction. Validation of such prognostic biomarkers will facilitate the development new disease-modifying OA drugs, and, in the future, could enhance clinical management of the disease, as in decisions regarding administration of drugs.