Journal of nephrology · 2025
Identification of conserved gene expression changes across common glomerular diseases by spatial transcriptomics.
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Cho Jeong Min, Kang Minji, Park Sehoon, Oh Jaeik, Ku Hyunah, Shin Ha Yeon, Koh Jung Hun, Cho Semin, Kim Yaerim, Lee Soojin, Kim Yong Chul, Han Seung Seok, Joo Kwon-Wook, Kim Yon Su, Yang Seung Hee, Moon Kyung Chul, Lee Hajeong, Kim Hyun Je, Kim Dong Ki, KORNERSTONE investigators
Аннотация
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.
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.
Предметные рубрики MeSH
GlomerulonephritisKidney GlomerulusGene Expression ProfilingGene Expression RegulationBiopsyCase-Control StudiesTissue DonorsProto-Oncogene Proteins c-junTristetraprolinKruppel-Like Transcription FactorsHumansMaleFemaleAdultMiddle AgedNephrosis, LipoidGlomerulonephritis, IGAGlomerulonephritis, MembranousGlomerulosclerosis, Focal SegmentalDiabetic Nephropathies