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Background <p>Glomerular diseases encompass a group of kidney diseases that may share common gene expression pathways. Here, we analyzed glomerular-specific gene expression profiles across various glomerular diseases.</p> Methods <p>We performed spatial transcriptomic profiling using formalin-fixed paraffin-embedded kidney biopsy specimens of controls and patients with five types of glomerular diseases using the GeoMx Digital Spatial Profiler. Disease-representative glomerular regions of interest (ROIs) were configured, probed with oligonucleotide barcodes linked with target complimentary sequence. The UV-cleaved barcodes were amplified to generate libraries and subsequently sequenced. Common differentially expressed genes across glomerular diseases were identified and Gene Ontology annotation was performed using the ToppGene suite.</p> Results <p>The mean age of patients with glomerular diseases and kidney donors was 49.5 ± 12.2 and 49.5 ± 9.8&#xa0;years, respectively. A total of 35 differentially expressed genes were consistently downregulated in glomeruli across the disease compared to the control, while none of the differentially expressed genes were consistently upregulated. Twelve of 35 downregulated differentially expressed genes, including the two hub genes JUN and FOS, were annotated with molecular function Gene Ontology terms related to DNA-binding transcription factor activity. The annotated biological process Gene Ontology terms included response to lipid-related (17/35 differentially expressed genes), response to steroid hormone (12/35 differentially expressed genes), or cell cycle regulation (10/35 differentially expressed genes). Xenium and immunofluorescence staining confirmed the reduced expression of JUN, ZFP36, and KLF9 in intraglomerular cells of glomerular diseases.</p> Conclusions <p>Identifying common differentially expressed genes by spatial transcriptomic analysis provides insights into the underlying molecular mechanisms of glomerular diseases and may lead to novel assessment or therapeutic strategies.</p> Graphical abstract <p></p>

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Identification of conserved gene expression changes across common glomerular diseases by spatial transcriptomics

  • 期刊论文

  • 发表日期：

    2025年3月11日

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  • Jeong Min Cho,
  • Minji Kang,
  • Sehoon Park,
  • Jaeik Oh,
  • Hyunah Ku,
  • Ha Yeon Shin,
  • Jung Hun Koh,
  • Semin Cho,
  • Yaerim Kim,
  • Soojin Lee,
  • Yong Chul Kim,
  • Seung Seok Han,
  • Kwon-Wook Joo,
  • Yon Su Kim,
  • Seung Hee Yang,
  • Kyung Chul Moon,
  • Hajeong Lee,
  • Hyun Je Kim,
  • Dong Ki Kim

摘要

Background

Glomerular diseases encompass a group of kidney diseases that may share common gene expression pathways. Here, we analyzed glomerular-specific gene expression profiles across various glomerular diseases.

Methods

We performed spatial transcriptomic profiling using formalin-fixed paraffin-embedded kidney biopsy specimens of controls and patients with five types of glomerular diseases using the GeoMx Digital Spatial Profiler. Disease-representative glomerular regions of interest (ROIs) were configured, probed with oligonucleotide barcodes linked with target complimentary sequence. The UV-cleaved barcodes were amplified to generate libraries and subsequently sequenced. Common differentially expressed genes across glomerular diseases were identified and Gene Ontology annotation was performed using the ToppGene suite.

Results

The mean age of patients with glomerular diseases and kidney donors was 49.5 ± 12.2 and 49.5 ± 9.8 years, respectively. A total of 35 differentially expressed genes were consistently downregulated in glomeruli across the disease compared to the control, while none of the differentially expressed genes were consistently upregulated. Twelve of 35 downregulated differentially expressed genes, including the two hub genes JUN and FOS, were annotated with molecular function Gene Ontology terms related to DNA-binding transcription factor activity. The annotated biological process Gene Ontology terms included response to lipid-related (17/35 differentially expressed genes), response to steroid hormone (12/35 differentially expressed genes), or cell cycle regulation (10/35 differentially expressed genes). Xenium and immunofluorescence staining confirmed the reduced expression of JUN, ZFP36, and KLF9 in intraglomerular cells of glomerular diseases.

Conclusions

Identifying common differentially expressed genes by spatial transcriptomic analysis provides insights into the underlying molecular mechanisms of glomerular diseases and may lead to novel assessment or therapeutic strategies.

Graphical abstract