# Spatial Mapping of Proteomic and Transcriptional Signatures in Kidney Disease > **NIH NIH U01** · UNIVERSITY OF COLORADO DENVER · 2022 · $555,864 ## Abstract AKI and CKD are highly prevalent diseases that are associated with significant morbidity and mortality. Unfortunately, there are not currently any specific treatments for either of these conditions. Both diseases are caused by a range of underlying diseases and processes. AKI, for example, can result from hemodynamic, toxic, infectious, and immune insults to the kidney. In both AKI and CKD, the diagnosis is based on changes in the serum creatinine and albuminuria, but these tests do not discriminate among the various etiologies of injury. Thus, beyond detecting a reduction in kidney function, clinicians typically have little information regarding the underlying pathologic process. Better understanding of the cellular and molecular patterns in the kidneys of patients with AKI and CKD will provide key insights into these diseases and will lead to new diagnostic and therapeutic approaches. In recent years, multi-omics analyses have had a major impact on our understanding of several fields, such as cancer biology, and have supported the identification and development of new treatments. These same technologies could transform our understanding of AKI and CKD, particularly when spatial resolution is complemented with proteomic and transcriptomic cellular analyses. Although kidney biopsies are not usually performed in patients with AKI and CKD, biopsy samples obtained through the Kidney Precision Medicine Project (KPMP) offer a valuable opportunity to analyze kidney tissue using state-of-the-art high-dimensional multi-omic platforms. We propose to utilize complementary spatial protein and RNA technologies to generate comprehensive tissue atlases for AKI and CKD. We will pursue the following specific aims: Aim 1. Generate a kidney cellular map via phenotypic and functional protein expression profiling. We will analyze biopsies using Multiplexed Ion Beam Imaging (MIBI), which detects 40+ protein targets at single-cell resolution (250 nm) with tissue-specific spatial information. Aim 2. Generate a kidney morphological map via phenotypic and functional gene expression profiling. We will analyze biopsies using Visium Spatial Transcriptomics (ST), which provides the whole transcriptome with morphological context. Aim 3. Generate an integrated cellular and molecular protein and gene expression kidney atlas. We will apply statistical and bioinformatic approaches to integrate the results from Aims 1 and 2 to create a composite map of the cellular protein and transcriptional expression profiles in the kidney. To accomplish these goals, we have assembled a multidisciplinary research team that includes nephrologists, renal pathologists, immunologists, and experts on multi-omics systems biology analyses. The proposed experiments are expected to reveal subsets of AKI and CKD patients based on the patterns of cells and molecular pathways present in the kidney, and to support identification of novel candidate biomarkers and therapeutic targets. ## Key facts - **NIH application ID:** 10498653 - **Project number:** 1U01DK133113-01 - **Recipient organization:** UNIVERSITY OF COLORADO DENVER - **Principal Investigator:** WEN-YUAN E HSIEH - **Activity code:** U01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $555,864 - **Award type:** 1 - **Project period:** 2022-09-15 → 2027-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10498653 ## Citation > US National Institutes of Health, RePORTER application 10498653, Spatial Mapping of Proteomic and Transcriptional Signatures in Kidney Disease (1U01DK133113-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10498653. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*