NEW YORK – New research by investigators at the University of Pennsylvania and other centers in the US and Germany has spelled out cellular features found across spatially defined kidney sites, characterizing kidney microenvironment features and microenvironment shifts coinciding with chronic kidney disease (CKD).
"We provide a comprehensive spatially resolved molecular roadmap of the human kidney and the fibrotic process, demonstrating the clinical utility of spatial transcriptomics," senior and corresponding author Katalin Susztak, director of the University of Pennsylvania's Penn-CHOP Kidney Innovation Center, and colleagues wrote in Nature Genetics on Wednesday.
Using a combination of 10x Genomics Chromium single-nucleus and single-cell RNA sequencing, NanoString CosMx-based spatial RNA-seq (spRNA-seq), and single-nucleus ATAC-seq-based open chromosome analyses, the researchers profiled nearly 338,600 individual cells or nuclei from 81 kidney samples, mapping molecular and cellular features in different regions of the kidney microenvironment in individuals with or without CKD.
All told, the team considered 36 samples from healthy control individuals, 20 samples from individuals with diabetic kidney disease, and 25 samples from individuals diagnosed with hypertensive-attributed CKD. The samples came from 58 participants with an average age of 64.1 years old and were accompanied by corresponding clinical and histological data, when applicable.
"Traditionally, kidney biopsies are examined using pink and blue stains, allowing pathologists to diagnose from a limited set of approximately 25 conditions based on cell patterns. However, the kidney is highly complex, comprising over 30 different cell types that change and interact dynamically, especially in disease states," Susztak said in an email.
To dig into that complexity, the team analyzed expression and chromatin patterns in the cells alongside published single-cell data from efforts such as the Kidney Precision Medicine Project, bringing the number of individual kidney cells considered to almost 700,000.
With the spatially informed dataset and unbiased deconvolution analyses, the researchers defined four kidney microenvironments — dubbed immune, fibrotic, glomerular, and tubule — and explored how expression shifts coincided with kidney disease.
"Our work fills a critical knowledge gap by characterizing the gene expression program of cells previously only defined by their spatial location, showing the anatomical location of cells observed in dissociated single-cell expression data, and defining cell type-specific gene expression changes in diseased states," the authors reported.
When the investigators considered features found in these microenvironment regions in relation to healthy and diseased human kidney conditions, for example, they identified expression changes in the fibrotic microenvironment that tracked with kidney diseases such as diabetic kidney disease, while providing potentially prognostic clues that coincide with progression from chronic kidney disease to end-stage renal disease.
"Our findings revealed that gene expression patterns within the fibrotic microenvironment significantly enhance disease prediction, outperforming traditional pathologist methods, particularly in the early stages of disease progression," Susztak explained, noting that this finding in particular "holds promise for more accurate clinical disease prediction and the identification of high-value molecular targets for future therapeutic development."
More broadly, members of the team suggested that the multimodal single-cell expression profiling approach used "serves as a model for applying cutting-edge technologies in research, with potential implications for treating various medical conditions beyond kidney disease."