Abstract: TH-PO542
Identification of Conserved Gene Expression Changes Across Common Glomerular Diseases by Spatial Transcriptomics
Session Information
- Glomerular Diseases: From Inflammation to Fibrosis - I
November 02, 2023 | Location: Exhibit Hall, Pennsylvania Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Glomerular Diseases
- 1401 Glomerular Diseases: From Inflammation to Fibrosis
Authors
- Cho, Jeongmin, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
- Park, Sehoon, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
- Koh, Jung Hun, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
- Kim, Yaerim, Keimyung University Daegu Dongsan Hospital, Daegu, Korea (the Republic of)
- Lee, Hajeong, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
- Han, Seung Seok, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
- Kim, Dong Ki, Seoul National University Hospital, Jongno-gu, Seoul, Korea (the Republic of)
Background
Glomerular diseases encompass a group of kidney diseases that may share common gene expression pathways. We aimed to analyze 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. We identified common differentially expressed genes (DEGs) across glomerular diseases and performed Gene Ontology (GO) annotation using the ToppGene suite.
Results
A total of 35 DEGs were consistently downregulated in glomeruli across the disease compared to the control, while none of the DEGs were consistently upregulated. Twelve of 35 downregulated DEGs, including the two hub genes FOS and JUN, were annotated with molecular function GO terms related to DNA-binding transcription factor activity. The annotated biological process GO terms included response to lipid-related (17/35 DEGs), response to steroid hormone (12/35 DEGs), or cell cycle regulation (10/35 DEGs).
Conclusion
Identifying common DEGs by spatial transcriptomic analysis provides insights into underlying molecular mechanisms of glomerular diseases and may lead to novel assessment or therapeutic strategies.
Figure 1. Glomerular region-of-interest (ROI) scan for digital spatial profiling
Figure 2. Gene association network analysis