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

> **NIH NIH K08** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $169,560

## Abstract

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 ...

## Key facts

- **NIH application ID:** 10327319
- **Project number:** 5K08DK124449-03
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Jennifer Ann Schaub
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $169,560
- **Award type:** 5
- **Project period:** 2020-04-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10327319

## Citation

> US National Institutes of Health, RePORTER application 10327319, A Systems Biology and Patient Stratification Approach to Improve Outcomes of Patients with Hypoxic Injury in Renal Tubular Cells in Chronic Kidney Diseases (5K08DK124449-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10327319. Licensed CC0.

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