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前一时期的生物标志物发现的基础上。在四个目标中，我们将重点关注“炎症”候选生物标志物识别有突发症状性膝关节OA （SKOA）风险的患者，或那些已确定的SKOA患者，他们的疾病进展风险增加的总体假设。与我们的合作者一起，我们建议使用四个OA队列验证和复制我们的初始发现：1)NIH骨关节炎倡议（OAI， M. Hochberg）；2)第二周期OAI+扩展(e)NYU （OAI+eNYU）发现队列，使用高质量的x线片；3) Johnston County Osteoarthritis Project (JoCo， J. Jordan)；4)广泛性骨关节炎遗传学纵向研究（GOGO Long， V. Kraus）。在Aim 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的表达）或血浆蛋白/脂质（GPL）生物标志物是否预测有症状的膝关节OA患者疾病严重程度或进展的风险增加。我们将：a)在OAI中验证从NYU发现的GPL生物标记面板；b)构建来自OAI+eNYU的GPL生物标记物面板；c)在GOGO Long和JoCo中复制这个面板。在Aim 2中，我们将确定候选遗传生物标志物（GWAS检测中指向炎症基因的单核苷酸多态性和全外显子组测序检测中的外显子变异）是否预测放射学膝关节OA患者疾病进展的风险增加。我们将：a)构建来自OAI+eNYU的SNP生物标志物面板；b)在GOGO+JoCo中验证该面板；c)构建eNYU+OAI的外显子变异生物标志物面板；d)通过在eNYU+OAI中坚持验证该面板。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确定遗传变异、基因表达和血浆蛋白/脂质表达之间潜在的致病相互作用。我们将：a)在OAI+eNYU中使用GPL+SNP生物标志物进行综合建模；b)在GOGO和JoCo中验证该模型；c)在OAI+eNYU中使用GPL+SNP+外显子变异生物标志物进行综合建模。在Aim 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能预测出现症状性膝关节炎的风险增加。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。基于我们的初步数据，我们期望该提案将确定预后生物标志物测试，可以预测个体的疾病发作风险或快速进展到关节破坏。这些预后生物标志物的验证将促进新的疾病改善药物的开发，并且在未来，可以加强疾病的临床管理，如在药物管理方面的决策。

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.