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: 10327319
• 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/10327319
• 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; 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; Lead; 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; base; biobank; 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