Clinical utility of extracellular RNA as marker of kidney disease progression

描述(由申请人提供)： 慢性肾脏疾病(CKD)是心血管疾病、感染和癌症导致的过早死亡的罪魁祸首，给人类带来了巨大的痛苦和社会代价。很大比例的CKD患者发展为终末期肾脏疾病，需要透析或肾移植。确定有CKD进展风险的患者可能有助于精准医学和预防伴随的并发症。开发预测慢性肾脏病进展的机械性生物标记物可能有助于开发新的治疗方法(S)。非编码RNA(NcRNA)，特别是microRNA(MiRNA)是一种通过调节基因表达影响多种细胞过程的生物分子。众所周知，组织RNA的表达传达了疾病状态的信息。最近，人们已经认识到，细胞外RNA(ExRNA)被其包裹的微泡保护而不受核酸酶的影响，因此可以在包括尿液在内的生物液中检测到，并传达病理生理知识。我们的实验室在高通量RNA表达分析方面拥有丰富的经验。我们开发了一种cDNA深度测序方法来分析多个样本中的miRNA，以一种经济、转录范围广和减少偏见的方式。通过研究数千个不同的人类样本，我们发现并整理了miRNA和其他小RNA。目前，我们正在开发一种并行方法来筛选所有ncRNA。我们还采用了定量逆转录聚合酶链式反应(qRT-PCR)技术，以允许在更大的原发和移植肾病患者研究队列中进行非侵入性验证和验证。我们建议应用我们的方法来全面分析CKD患者尿样中的miRNA和其他ncRNA。我们的目标是确定尿中的exRNA可以预测CKD的进展并开发预后生物标记物。我们提出了一个两阶段的方案；一个发现阶段，应用深度测序来进行转录组范围的分析和候选标记的识别，以及一个验证阶段，应用RT-qPCR来表征额外的样本并对发现的发现进行鉴定。为了快速实施我们的研究计划，我们与进行CKD纵向队列研究的研究人员建立了合作关系。尿样与丰富的人口学、临床和肾脏结果数据相关联，可从成人和儿童队列研究中获得；从肾小球疾病和非肾小球疾病研究中获得；从天然肾脏和肾移植受者中获得。这使得发现能够预测肾脏疾病进展的生物标志物成为可能，因为CKD的进展机制在很大程度上独立于CKD的病因。尽管如此，我们的研究是为了发现亚群特定的生物标记物。我们的初步发现证实了在生物体液中分析exRNA的可行性，并检测与临床相关结果的相关性。我们预测，我们的发现将使基础科学家了解肾脏疾病进展中的RNA异常，并为临床试验提供候选的临床科学家生物标记物。

DESCRIPTION (provided by applicant): Chronic kidney disease (CKD) is responsible for premature death from cardiovascular disease, infections and cancer, considerable human suffering and social costs. A large proportion of CKD patients develop end stage renal disease and require dialysis or kidney transplantation. Identifying patients at risk for CKD progression may facilitate precision medicine and prevent attendant complications. Development of mechanistic biomarkers predictive of CKD progression may help develop new treatment(s). Non-coding RNA (ncRNA), specifically microRNA (miRNA) is increasingly recognized as biomolecules that affect multiple cellular processes via regulation of gene expression. It is known that tissue RNA expression conveys information on disease status. Recently, it has been recognized that extracellular RNA (exRNA) is protected from nucleases by their encompassing microvesicles, and therefore can be measured in biological fluids including urine, and convey pathophysiological knowledge. Our labs have extensive experience in high throughput analysis of RNA expression. We have developed a cDNA deep sequencing method to profile miRNA in multiple samples, in a cost-effective, transcriptome-wide and bias-reduced manner. By studying thousands of diverse human samples we have discovered and curated miRNA and other small RNA. Currently, we are developing a parallel method to screen for all ncRNA. We have also adapted quantitative reverse-transcription polymerase chain reaction (qRT-PCR) technology to allow non- invasive verification and validation in larger study cohorts of patients with native and transplant kidney disease. We propose to apply our methods to comprehensively profile miRNA and other ncRNA in urine specimens collected from CKD patients. We aim to identify exRNA in the urine that can predict progression of CKD and develop prognostic biomarkers. We propose a 2-stage protocol; a discovery stage applying deep sequencing for transcriptome-wide profiling and identification of candidate markers, and a validation phase applying RT- qPCR to characterize additional samples and qualify the discovered findings. To allow rapid implementation of our research plan we established collaborations with investigators conducting longitudinal cohort studies of CKD. Urine specimens, linked with rich demographic, clinical and kidney outcome data are available from studies of both adult and pediatric cohorts; both glomerular and non-glomerular diseases; in both native kidneys and kidney transplant recipients. This permits discovery of biomarkers capable of predicting progression across the spectrum of kidney diseases as mechanisms of CKD progression are to a largely independent of CKD etiology. Nonetheless, our studies are powered for subgroup-specific biomarker discovery. Our preliminary findings confirm feasibility to profile exRNA in biofluids, and to detect associations with clinical relevant outcomes. We predict that our findings will inform basic scientist on RNA dysregulation in kidney disease progression and provide clinical scientist biomarker candidates for clinical trials.