Epigenetics Landscape of Chronic Kidney Disease

描述（由申请人提供）：慢性肾脏疾病在美国影响2000万人，并与心血管死亡率增加约3-5倍相关。ESRD是美国第九大死因；它与大约20%的年死亡率相关，这比大多数实体癌症（结肠癌、乳腺癌、肺癌）更糟糕。糖尿病和高血压肾病（DNP， HN）和FSGS——所谓的非免疫介导的退行性肾小球疾病——在美国导致了75%的ESRD病例。目前，我们为肾病患者提供的治疗选择非常少。此外，我们有非常有限的工具来确定哪些患者患肾脏疾病的风险增加。为了回答这些问题，我们在人类对照和病变肾脏样本上使用表达微阵列进行了大规模的基因表达研究。我们发现了与肾脏疾病进展相关的新的基因表达模式（潜在的生物标志物模式）。然而，我们发现基因表达水平的变化在人类样本中比我们之前在小鼠中观察到的要高得多。因此，目前需要大量基因的表达水平来识别进行性肾脏疾病患者。我们建议，基因表达研究与表观基因组学分析一起进行，将有助于识别进行性肾脏疾病的新诊断和预后标志物。1.在对照健康和病变肾脏样本中生成基因组尺度的胞嘧啶甲基化图谱。我们建议使用HELP分析来确定微解剖肾小球和小管间质样本的DNA甲基化模式。2. 比较对照组（“健康”）和患病肾脏组织样本肾小球和小管中的DNA甲基化谱，并确定肾脏疾病中候选的甲基化变化3。整合mRNA表达和DNA甲基化研究的结果，以确定a)新的途径，b)进展性肾脏疾病的新的生物标志物。我们已经使用Affymetrix表达阵列生成的基因表达数据结果将与DNA甲基化分析结果进行交叉参考和整合，以确定新的途径和新的生物标志物。总之，这些研究将首次描述肾脏的表观遗传修饰，并帮助我们了解导致肾功能进行性丧失的复杂调控网络。大量具有良好特征的人体组织样本以及相应的基因表达数据的可用性使我们处于实现这些目标的独特位置。公共卫生相关性：慢性肾脏疾病在美国影响着2000万人，其死亡率增加了约3-5倍。终末期肾病（ESRD）是美国第九大死因；它与每年约20%的死亡率有关，这比大多数实体癌症（前列腺癌、结肠癌和乳腺癌）更糟糕。目前，美国大约有50万患者需要肾脏替代治疗（透析或移植），每年的费用约为300亿美元。慢性肾脏疾病的表观基因组景观尚未被研究。这将是第一个对人类肾脏组织进行基因组尺度DNA甲基化研究的研究。基于我们的初步结果，我们提出DNA甲基化模式存在显著差异，我们还提出这些甲基化差异可以驱动控制慢性肾脏疾病进展的基因表达差异。

DESCRIPTION (provided by applicant): Chronic Kidney Disease affects 20 million people in the US and is associated with an approximately 3-5-fold increase in cardiovascular mortality. ESRD is the 9th leading cause of death in the US; it is associated with an approximately 20% yearly mortality rate, which is worse than most solid (colon, breast lung) cancers. Diabetic and hypertensive renal disease (DNP, HN) and FSGS -so called non- immune mediated degenerative glomerular diseases- are responsible for >75% of ESRD cases in the US. Currently, we have very few therapeutic options to offer to people with renal disease. In addition we have very limited tools to identify patients who are increased risk for the development of renal disease. In order to answer these questions we performed large scale gene expression studies using expression microarrays on human control and diseased kidney samples. We identified new gene expression patterns (potential biomarker patterns) that are associated with progression of renal disease. However, we found that the variation of gene expression levels is much higher in human samples than we previously observed in mouse. Thereby currently the expression levels of large number of genes are needed to identify patients with progressive renal disease. We propose that gene expression studies performed together with epigenomics analysis would facilitate the identification of new diagnostic and prognostic markers for progressive renal disease. 1.Generate genome scale cytosine methylation maps in control healthy and diseased kidney samples. We propose to use the HELP assay to determine DNA methylation patterns of microdissected glomerular and tubulointerstitial samples. 2. Compare DNA methylation profiles in the glomeruli and tubuli in control ("healthy") and diseased kidney tissue samples and identify candidate methylation changes in kidney disease 3. Integrate results of mRNA expression and DNA methylation studies in order to identify a) new pathways, b) new biomarkers of progressive renal disease. The results of gene expression data that we already generated using Affymetrix expression arrays will be cross referenced and integrated with results of DNA methylation assays in order to identify new pathways and new biomarkers. In summary these studies would describe for the first time epigenetic modification in the kidney and help us to understand the complex regulatory network that leads to progressive loss of renal function. The availability of large number of well characterized human tissue samples with the corresponding gene expression data puts us into a unique position to achieve these goals. PUBLIC HEALTH RELEVANCE: Chronic kidney disease affects 20 million people in the US and is associated with an approximately 3-5-fold increase in mortality. ESRD (end stage renal disease) is the 9th leading cause of death in the US; it is associated with an approximately 20% yearly mortality rate, which is worse than most solid (prostate, colon and breast) cancers. Currently there are approximately 500,000 patients that require renal replacement therapy (dialysis or transplant) in the US, which is associated with an annual cost of about 30 billion dollars. The epigenomic landscape of chronic kidney disease has not been studied. This would be the first study to perform genome scale DNA methylation studies on human kidney tissue. Based on our preliminary results we propose that there are significant differences in DNA methylation patterns, we also propose that these methylation differences can drive gene expression differences that govern the progression of chronic kidney disease.