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Urine protein markers of disease in lupus nephritis

狼疮性肾炎疾病的尿蛋白标志物

基本信息

批准号：
6951552
负责人：
JAMES C OATES
金额：
$ 6.3万
依托单位：
MEDICAL UNIVERSITY OF SOUTH CAROLINA
依托单位国家：
美国
项目类别：
财政年份：
2004
资助国家：
美国
起止时间：
2004-09-20 至 2007-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/6951552
关键词：
artificial intelligence biomarker clinical research diagnosis design /evaluation human subject kidney disorder diagnosis lupus nephritis mass spectrometry matrix assisted laser desorption ionization noninvasive diagnosis patient oriented research prognosis protein purification proteomics two dimensional gel electrophoresis urinalysis

项目摘要

DESCRIPTION (provided by applicant): Lupus nephritis (LN) affects up to 65% of systemic lupus erythematosus (SLE) patients and results in renal failure in up to 42% of patients after five years. Renal failure rates can vary up to eight fold over five years in aggressive LN despite use of the same treatment protocol. A more reliable means of determining prognosis is therefore required. The long-term objective of this proposal is to identify noninvasive urine protein markers of disease that are predictive of renal compromise. Previous studies in this area have resulted in the identification of a limited number of candidate proteins that correlate with disease type and glomerular inflammatory activity. To develop models of prognostic indicators in a heterogeneous disorder such as LN, the candidate protein approach has limited power. The Specific Aims of this proposal are to determine: 1) differentially expressed proteins in the urine of LN subjects (revealed by proteomic techniques and artificial neural network (ANN) technology) as surrogate markers of the WHO class, activity, and chronicity of glomerular lesions on renal biopsy and 2) the feasibility of a larger study designed to examine these urine protein markers as predictors of renal outcome in LN. To address these aims, urine from 1) LN subjects undergoing renal biopsy and 2) subjects with either LN or SLE without LN will be analyzed using proteomic techniques. All subjects will be followed prospectively for renal outcomes. Urine proteins will be concentrated and resolved by 2D-gel electrophoresis. Spots will be identified by location and removed for identification by matrix assisted laser desorption/ionization mass spectrometry and peptide mass fingerprinting. Data from these procedures will be analyzed using ANN modeling to determine surrogate urine protein markers of WHO class, activity, and chronicity of LN renal biopsies. ANN will be used to determine surrogate markers that predict compromise in renal function due to LN. These markers will be compared to renal biopsy and traditional laboratory and clinical indices of disease as predictors of renal outcome. Within the two years of this study, surrogate urine protein markers of biopsy findings should be identified, and the feasibility of a long-term outcome study should be determined. The ultimate results of this study could revolutionize the manner in which treatment for LN is determined. Due to the power of proteomic and ANN techniques, novel mediators of disease activity and damage should be identified and thus contribute to the development of more targeted therapies for LN.

描述（由申请人提供）：狼疮性肾炎（LN）影响高达65%的系统性红斑狼疮（SLE）患者，并导致高达42%的患者在五年后出现肾衰竭。尽管使用相同的治疗方案，侵袭性LN的肾衰竭率在五年内可能变化高达八倍。因此，需要一种更可靠的方法来确定预后。这项提案的长期目标是确定非侵入性的尿蛋白标志物的疾病是预测肾损害。这一领域的先前研究已经鉴定出有限数量的与疾病类型和肾小球炎症活性相关的候选蛋白。为了开发LN等异质性疾病的预后指标模型，候选蛋白质方法的能力有限。本提案的具体目的是确定：1）LN受试者尿液中差异表达的蛋白质（通过蛋白质组学技术和人工神经网络（ANN）技术揭示）作为肾活检肾小球病变WHO分类、活动性和慢性化的替代标志物，以及2）旨在检查这些尿蛋白标志物作为LN肾脏结局预测因子的更大规模研究的可行性。为了解决这些目标，将使用蛋白质组学技术分析来自1）接受肾活检的LN受试者和2）患有LN或不具有LN的SLE的受试者的尿液。将前瞻性随访所有受试者的肾脏结局。将通过2D凝胶电泳浓缩和分离尿蛋白。将通过位置识别斑点，并通过基质辅助激光解吸/电离质谱法和肽质量指纹图谱进行识别。将使用ANN建模分析这些程序的数据，以确定LN肾活检的WHO分类、活动性和慢性化的替代尿蛋白标志物。人工神经网络将被用来确定替代标志物，预测损害肾功能，由于LN。这些标志物将与肾活检和传统的实验室和临床疾病指数进行比较，作为肾脏结局的预测因子。在本研究的两年内，应确定活检结果的替代尿蛋白标志物，并确定长期结局研究的可行性。这项研究的最终结果可能会彻底改变LN治疗的方式。由于蛋白质组学和人工神经网络技术的力量，新的介质的疾病活动和损害应被确定，从而有助于更有针对性的治疗LN的发展。