# Spatial Elucidation of Human Acute Kidney Injury and Chronic Kidney Disease using Imaging Mass Cytometry

> **NIH NIH U01** · YALE UNIVERSITY · 2023 · $360,000

## Abstract

Abstract
Acute kidney injury (AKI) is a syndromic term encompassing a wide range of insults and pathogenic
responses that lead to a rapid reduction in glomerular filtration. Although we have made significant
progress in our understanding of kidney injury in animal models, far less attention has been focused on
the pathogenesis and treatment of the diverse types of human AKI. The largest barrier in achieving this
knowledge is the limited number of kidney biopsies performed for AKI and the small amount of tissue
obtained from renal biopsy. The Kidney Precision Medicine Project is tackling this complex issue by
recruiting altruistic patients with AKI who are willing to have kidney biopsies in order to advance our
knowledge of human kidney disease. These biopsies are being interrogated using multiple complementary
technologies. We propose to use Imaging Mass Cytometry to help provide a highly detailed, quantitative
cellular map of nearly all cells present in sections from those kidney biopsies, including their differentiation
state and activation of injury and repair pathways. Combined with the cell sequencing, metabolomic, and
proteomic data generated under KPMP guidance, this will provide a substantial increase in our
understanding of human AKI and CKD.
Imaging mass cytometry (IMC) uses a high-resolution laser combined with a mass cytometer to detect the
presence, location and amount of up to 42 different heavy metal conjugated antibodies hybridized to a
tissue section. We have successfully used IMC with a panel of 22 heavy metal conjugated validated
antibodies to identify resident kidney cell populations, infiltrating cell populations, and cell activation and
injury states using archival FFPE human kidney tissue, and developed a machine learning technique
termed Kidney MAPPS to rapidly and accurately identify, quantify and localize ~92% of all cells in those
biopsies. We now propose to increase that validated antibody panel to >30 antibodies that will allow
identification of >95% of cells and improve cell injury and activation state assessment, and to optimize the
IMC and Kidney-MAPPS analysis pipeline to perform 2D and 3D quantitative assessment of cell location,
cell-cell interactions and cellular responses in human AKI and CKD biopsy tissues (SA1). We will
standardize a defined work-flow protocol coupled with rigorous quality control assessment steps at key
points (SA2), and then apply this IMC work-flow to kidney samples provided by KPMP and integrate with
the KPMP Central Hub and consortium members to develop accurate protocols for mapping the
scRNAseq/snRNAseq data, proteomics data and metabolomics data onto the appropriate cells and
locations using Kidney-MAPPS (SA3).

## Key facts

- **NIH application ID:** 10701865
- **Project number:** 5U01DK133768-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** LLOYD G CANTLEY
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $360,000
- **Award type:** 5
- **Project period:** 2022-09-15 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10701865

## Citation

> US National Institutes of Health, RePORTER application 10701865, Spatial Elucidation of Human Acute Kidney Injury and Chronic Kidney Disease using Imaging Mass Cytometry (5U01DK133768-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10701865. Licensed CC0.

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