Urine biomarkers of lupus nephritis pathology and response to therapy

狼疮性肾炎病理学的尿液生物标志物和治疗反应

• 批准号: 8392947
• 负责人: JAMES C OATES
• 金额: --
• 依托单位: RALPH H JOHNSON VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-04-01 至 2014-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8392947
• 关键词: Acute Renal Failure with Renal Papillary Necrosis; Address; Adrenal Cortex Hormones; Affect; African American; American; Antigen-Antibody Complex; Automobile Driving; Baltimore; Biological Assay; Biological Markers; Biological Neural Networks; Biopsy; Blood Pressure; Caucasians; Caucasoid Race; Characteristics; Classification; Clinic; Clinical; Clinical Trials; Color; Complement; Complex; Consensus; Coupled; Cyclophosphamide; Data; Decision Making; Detection; Development; Diabetes Mellitus; Diagnosis; Diagnostic; Disease; Disease Marker; Drug toxicity; Electron Microscopy; Elements; Enzyme-Linked Immunosorbent Assay; Excretory function; Exposure to; Female; Fibrosis; Funding; Future; Glomerulonephritis; Goals; Gold; Growth Factor; Health; Heterogeneity; High Pressure Liquid Chromatography; Histopathology; Hypertension; Immune response; Immunoassay; Individual; International; Intravenous; Kidney; Kidney Diseases; Kidney Failure; Lesion; Link; Literature; Logistic Regressions; Lupus Nephritis; Machine Learning; Measures; Mediating; Methods; Minority; Modeling; Monitor; Nature; Neoadjuvant Therapy; Nephritis; Nephrology; Online Systems; Oral; Outcome; Outcome Measure; Oxidative Stress; Pathogenesis; Pathology; Pathway Analysis; Pathway interactions; Patient Care; Patients; Performance; Phase; Physiologic pulse; Population; Population Study; Post-Translational Protein Processing; Preparation; Principal Investigator; Process; Production; Proliferative Glomerulonephritis; Proteins; Qualifying; Regression Analysis; Renal function; Research; Research Personnel; Rheumatology; Severity of illness; Societies; Staging; Study models; System; Systemic Lupus Erythematosus; Techniques; Technology; Testing; Therapeutic; Time; Training; Treatment Failure; Treatment Protocols; Tyrosine; Urine; Validation; Veterans; Woman; Work; base; candidate marker; chemokine; clinical decision-making; cohort; college; cytokine; design; drug development; health disparity; mathematical model; meetings; novel; novel strategies; patient population; population health; predictive modeling; prevent; programs; prospective; public health relevance; response; rheumatologist; standard care; therapeutic target; tool; treatment response; urinary

DESCRIPTION (provided by applicant): Lupus nephritis (LN) results in renal failure in up to 42% of patients after five years. However, traditional biomarkers and clinical indicators of treatment response often cannot detect treatment failure until irreversible damage to the kidneys has occurred. Therefore, a more reliable means of determining diagnosis and response to induction therapy in LN is needed. The goals of this project are to provide clinicians and investigators with 1) a non-invasive, reliable tool for diagnosis of International Society of Nephrology/Renal Pathology Society (ISN/RPS) class (Class) in LN, 2) a short-term marker of long-term response to therapy, 3) validated assays of biomarkers for clinical use, and 4) hypotheses about mechanisms of response to therapy that can be used as future therapeutic targets. During the first three years of funding, biomarker discovery efforts provided preliminary data that has focused efforts on a limited number of candidate markers. Markers of reactive intermediate production also showed promise as biomarkers. Links between candidate biomarkers and oxidative stress in LN were suggested by our preliminary data and pathways analysis. In preliminary studies, models using this narrowed set of markers had increased predictive power in diagnosing Class and predicting response to therapy over traditional biomarker or single biomarkers models. We hypothesize that changes in expression of and reactive intermediate-induced post-translational modifications of urinary proteins will serve as biomarkers of Class and response to therapy in LN. To address these hypotheses, the following Specific Aims are proposed: 1) Create and validate models of urine biomarkers diagnostic of International Society of Nephrology/Renal Pathology Society (ISN/RPS) biopsy class (Class) in lupus nephritis (LN), 2) Create and validate models of urine biomarkers predictive of renal response to induction therapy in LN, and 3) Develop and validate biomarker assays for clinical use. Subjects will derive from the Charleston and Baltimore inception cohorts and the Genentech LUNAR study population. ISN/RPS class of nephritis will be determined at entry, and outcomes at one year after start of induction therapy will be characterized by the American College of Rheumatology and Systemic Lupus Erythematosus International Cooperating Clinics renal response criteria. Urine will be collected at zero and three months after entry. Candidate low abundance proteins (chemokines, growth factors, cytokines, and renal damage markers selected from discovery analysis in the first funding period) will be quantitated by the Luminex bead assay and ELISA. Post-translational modifications of urine protein tyrosines (Tyr) indicative of exposure to reactive intermediates will be detected by high performance liquid chromatography-electrochemical detection (HPLC-EC). Levels of individual markers at baseline (for Aim 1) and baseline and three months (for Aim 2) will be used to create a mathematical models (by artificial neural network (ANN) that use the levels of surrogate urine protein markers to: 1) diagnose Class of LN at baseline and 2) predict response therapy at one year. Due to the technical nature of machine learning, a reviewer familiar with ANN analysis is requested. In the third Aim, an immunoassay for reactive-intermediate-modified Tyr will be developed, and all biomarker immunoassays will undergo method validation suitable for formal biomarker qualification. This latter step is essential to rapid acceptance and application of the findings of this study to the clinic. Pathways analysis will be used to explore mechanistic interactions between biomarkers deemed predictive in the first two aims. Hypotheses regarding mechanisms of disease activity, damage, and response to therapy will be identified that could be exploited with targeted therapies. This study is unique in 1) the size, diversity, and rigorous characterization of the population used to train and validate the predictive models and 2) its use of novel and well described biomarkers representing diverse pathogenic mechanisms to be tested in a single model. The long-term goal is to provide clinicians with a qualified biomarker panel coupled with a web-based predictive tool for more accurate diagnosis and therapeutic monitoring of LN.

描述（由申请人提供）： 狼疮肾炎（LN）导致五年后多达42％的患者肾衰竭。但是，在发生不可逆的肾脏损害之前，传统的生物标志物和治疗反应的临床指标通常无法检测到治疗失败。因此，需要一种更可靠的方法来确定LN诊断和对诱导治疗的反应。 The goals of this project are to provide clinicians and investigators with 1) a non-invasive, reliable tool for diagnosis of International Society of Nephrology/Renal Pathology Society (ISN/RPS) class (Class) in LN, 2) a short-term marker of long-term response to therapy, 3) validated assays of biomarkers for clinical use, and 4) hypotheses about mechanisms of response to therapy that can be used as future therapeutic目标。在资金的前三年中，生物标志物发现工作提供了初步数据，这些数据将精力集中在有限数量的候选标记上。反应性中间生产的标志也显示出作为生物标志物的希望。通过我们的初步数据和途径分析提出了候选生物标志物与LN中氧化应激之间的联系。在初步研究中，使用这种狭窄标记的模型在诊断类别的诊断和预测对传统生物标志物或单个生物标志物模型的治疗反应方面具有提高的预测能力。我们假设尿蛋白的翻译后和反应性中间诱导的翻译后修饰的表达变化将作为类别的生物标志物和对LN治疗的反应。为了解决这些假设，提出了以下具体目的：1）创建和验证尿液生物标志物的模型和国际肾脏病学会/肾脏病理学会（ISN/RPS）活检类（ISN/RPS）的诊断，狼疮肾炎（LN）2），2），2）创建和验证了对尿液生物标记的模型，并验证了尿液源于尿素的范围，并在尿液中及3次尿素及其定性范围及其定性范围。临床用途。受试者将衍生出查尔斯顿和巴尔的摩成立人群以及Genentech Lunar研究人群。 ISN/RPS类肾炎将在入境时确定，在归纳治疗开始后的一年后，美国风湿病学和系统性红斑狼疮学院将以国际合作诊所肾脏反应标准为特征。尿液将在进入后三个月以零收集。候选低丰度蛋白（趋化因子，生长因子，细胞因子和肾脏损伤标志物在第一个资金期间选择分析）将由Luminex珠测定和ELISA定量。尿液蛋白酪氨酸（TYR）的翻译后修饰，指示暴露于反应性中间体的情况下，将通过高性能液相色谱 - 电气化学检测（HPLC-EC）检测。基线时（AIM 1）和基线和三个月（针对目标2）的单个标记水平将用于创建数学模型（通过人工神经网络（ANN），使用替代尿液蛋白标记水平为：1）诊断为：1）在基线时诊断为LN和2）在一年中预测反应治疗。由于机器学习的技术性质，请求熟悉ANN分析的审稿人。在第三个目标中，将开发用于反应性中间体修饰的Tyr的免疫测定法，所有生物标志物免疫测定将接受适合正式生物标志物资格的方法验证。后一个步骤对于将本研究的发现快速接受和应用到诊所至关重要。途径分析将用于探索在前两个目标中被认为预测性的生物标志物之间的机械相互作用。将发现有关疾病活动，损害和对治疗反应机制的假设，可以通过有针对性的疗法来利用。这项研究是独一无二的1）种群的大小，多样性和严格的表征，用于训练和验证预测模型； 2）其使用新颖和描述的生物标志物，代表了多种致病机制，可以在单个模型中测试。长期的目标是为临床医生提供合格的生物标志物面板，并为基于Web的预测工具提供更准确的LN诊断和治疗监测。