A Systems Biology and Patient Stratification Approach to Improve Outcomes of Patients with Hypoxic Injury in Renal Tubular Cells in Chronic Kidney Diseases

系统生物学和患者分层方法可改善慢性肾脏病肾小管细胞缺氧损伤患者的预后

• 批准号: 10541190
• 负责人: Jennifer Ann Schaub
• 金额: $ 16.96万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10541190
• 关键词: Address; Anemia; Animals; Atherosclerosis; Atrophic; Award; Beds; Bioinformatics; Biological Markers; Biology; Biopsy; Cardiovascular Diseases; Cells; Chronic; Chronic Kidney Failure; Clinical; Clinical Data; Clinical Treatment; Clinical Trials; Complex; Data; Data Set; Descriptor; Disease Progression; End stage renal failure; Epidemic; Erythropoietin; Fibrosis; Future; Gene Expression; Gene Expression Profiling; Glomerular Filtration Rate; Goals; Hypoxia; Hypoxia Inducible Factor; Injury; Investigation; Kidney; Machine Learning; Measures; Mentors; Molecular; Molecular Profiling; Monitor; Morphology; Native Americans; Nephrology; Nephrotic Syndrome; Non-Insulin-Dependent Diabetes Mellitus; Outcome; Pathologic; Pathology; Pathway interactions; Patient-Focused Outcomes; Patients; Pharmaceutical Preparations; Pima Indian; Process; Procollagen-Proline Dioxygenase; Production; Renal function; Reproducibility; Resources; Sampling; Serum; Severities; Severity of illness; Specificity; Statistical Models; Systems Biology; Techniques; Testing; Therapeutic; Therapeutic Agents; Therapeutic Intervention; Tissues; Training; Tubular formation; Urine; biobank; biomarker identification; cell type; clinical phenotype; cohort; experience; global health; glomerulosclerosis; hypoxia inducible factor 1; improved; improved outcome; individualized medicine; inhibitor; interstitial; kidney biopsy; mortality; mortality risk; novel; novel marker; novel therapeutics; patient stratification; patient subsets; phase III trial; predictive marker; research clinical testing; response; single-cell RNA sequencing; statistical and machine learning; transcription factor

ABSTRACT Chronic Kidney Disease (CKD) is a global health epidemic and patients with CKD suffer from increased mortality and cardiovascular disease. Despite the severity of the disease, there are limited treatment options to hinder its progression. Tubular injury (TI) is a common finding on many kidney biopsies from patients with CKD, and there is mechanistic data supporting that TI can lead to interstitial fibrosis and tubular atrophy. While interstitial fibrosis and tubular atrophy are the strongest known pathologic predictor of progression of CKD, we have limited understand of how TI contributes to this progression. Hypoxia Inducible Factor-1α (HIF-1α) has been shown in animal studies to impact the severity of TI and is also known to trigger a fibrotic cascade, but there is limited data regarding its overall activity in kidney tissue, its cell type specific activity, its association with pathologic features or patient outcomes. It is of utmost importance to better understand this pathway as several Prolyl Hydroxylase inhibitors, which are novel therapeutic agents that increase the expression of HIF- 1α, are currently in clinical trial testing to treat anemia of CKD. The first aim of this proposal is to develop a measure of HIF-1α pathway activity that enables evaluation of clinical and morphologic features and cell-type specificity. Specifically, the candidate will a) Identify clinical and pathologic descriptors associated with increased HIF-1α pathway activity score and b) Determine the cell-type specific expression level of HIF-1α and its downstream components in tubular cells using single-cell RNA-sequencing. The second aim of this proposal is to determine the association of increased HIF-1α activity with outcomes and identify patients with increased HIF-1α activity non-invasively using biomarkers. Specifically, the candidate will a) Determine the association of increased HIF-1α activity score with patient outcomes and b) Identify serum or urine biomarkers that detect increased HIF-1α pathway activity in patients. The candidate will analyze data from 3 cohorts to accomplish these aims: Nephrotic Syndrome Study Network (NEPTUNE), Clinical Phenotyping Resource and Biobank Core (C-PROBE) and the Native Americans with Type 2 Diabetes cohort (formerly known as the Pima Indian cohort). These investigations will allow us to monitor HIF-1α activity non-invasively in trials where patients receive novel drug agents, such as Prolyl Hydroxylase Inhibitors. The candidate will obtain formal training in analysis of gene expression data, single cell RNA- sequencing and machine learning techniques during the course of the award period to successfully integrate gene expression data, pathology data and clinical data. She will be mentored by an expert team with complementary experience in nephrology, tubular injury biology, systems biology and bioinformatics. The long-term goal of these investigations is to ultimately be able to better sub-type patients with tubular injury based on mechanistic terms.

摘要 慢性肾脏病(CKD)是一种全球性的健康流行病，CKD患者的发病率增加 死亡率和心血管疾病。尽管这种疾病很严重，但治疗选择有限 来阻碍它的发展。肾小管损伤(TI)是许多肾活检患者的常见发现。 CKD，并且有机制数据支持TI可导致间质纤维化和肾小管萎缩。而当 间质纤维化和肾小管萎缩是CKD进展的最强病理预测因子。 对TI如何促进这一进程的了解有限。缺氧诱导因子-1α(HIF-1α) 在动物研究中被证明会影响TI的严重性，也被认为会引发纤维化级联反应，但 关于它在肾脏组织中的整体活性、其细胞类型特异性活性、其相关性的数据有限。 具有病理特征或患者结局的。最重要的是要更好地理解这条途径 几种脯氨酸羟化酶抑制剂，是一种新型的治疗药物，可以增加HIF-1的表达。 1α，目前正在进行治疗慢性肾脏病贫血的临床试验。这项提议的第一个目标是开发一种 能够评估临床和形态特征以及细胞类型的HIF-1α途径活性的测量 专一性。具体地说，候选人将a)确定与以下方面相关的临床和病理描述 增加的HIF-1α通路活性评分和b)决定HIF-1α的细胞类型特异性表达水平和 利用单细胞RNA测序技术对其下游成分在肾小管上皮细胞中的表达进行分析。这样做的第二个目的是 建议确定缺氧诱导因子-1α活性增加与预后的关系，并确定患者 使用生物标志物非侵入性增加缺氧诱导因子-1α活性。具体地说，候选人将a)确定 缺氧诱导因子-1α活性评分升高与患者预后的关系以及b)确定血清或尿液生物标记物 检测到患者体内HIF-1α途径活性增加。候选人将分析来自3个队列的数据，以 实现这些目标：肾病综合征研究网络(NEPOTUNE)、临床表型资源和 生物库核心(C-Probe)和患有2型糖尿病的美洲原住民队列(以前称为PIMA 印第安人队列)。这些调查将使我们能够在以下试验中非侵入性地监测HIF-1α的活性 患者接受新的药物制剂，如Pro羟基酶抑制剂。 应聘者将接受基因表达数据分析、单细胞RNA- 在获奖过程中使用排序和机器学习技术，以成功整合 基因表达数据、病理数据和临床数据。她将得到一个专家团队的指导， 在肾脏病、肾小管损伤生物学、系统生物学和生物信息学方面有互补经验。这个 这些研究的长期目标是最终能够改善肾小管损伤的亚型患者 基于机械术语。