GEO series

Integrated bulk and spatial transcriptomic analysis identifies progression-associated molecular signatures in biopsy-proven hypertensive nephropathy [Spatial Transcriptomics]

GSE339455 Homo sapiens (human) Spatial transcriptomics 4 samples Submitted 2026/07/22 Platform GPL24676

At a glance

Spatial transcriptomics · human · 4 samples

What it is: Spatial transcriptomicsGene activity measured with its position in a tissue section.
Organism: Homo sapiens (human)
Samples: 4 samples
Data you can get: A processed table (series matrix) and supplementary files from NCBI.

Summary (written by the submitters)

Hypertensive nephropathy (HN) is a leading cause of chronic kidney disease (CKD), but molecular mechanisms underlying disease progression remain poorly understood. We aimed to identify transcriptomic signatures associated with disease progression and to localize these signatures within renal architectures. Patients with biopsy-proven HN were selected from the Norwegian Kidney Biopsy Registry and stratified after ≥5 years of follow-up into early stable (ES), early progressor (EP), late stable (LS) and late progressor (LP) based on baseline kidney function and annual eGFR decline.

Read the full summary ↓

Bulk transcriptomic profiling was performed in a discovery cohort and validated in an independent cohort using nCounter profiling. Spatial transcriptomics was applied to map progression-associated signatures to nephron compartments. Bulk RNA sequencing identified 415 differentially expressed genes (DEGs) between ES and EP, and 692 between LS and LP samples. ES was enriched in circadian rhythm pathways, with reduced NR1D1 and NR1D2 expression in EP. LP was associated with metabolic reprogramming including glutathione, retinol and amino acid metabolism. Random forest modelling identified NR1D1 gene expression as a key classifier, validated in an independent cohort. Spatial transcriptomics revealed nephron segment-specific expression patterns, including a proximal tubule cluster enriched in ferroptosis in LP. Comparative nephron-segment analyses across groups revealed progression-associated biomarkers, including CHGA, CCN2 and SFRP2 in glomeruli, and APOE in proximal tubules. HN progression appears to involve stage-specific and compartmentalized molecular programs. Integration of bulk and spatial transcriptomics identifies candidate biomarkers and pathways, potentially supporting innovative prognostic stratification and therapeutic strategies.

This dataset

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Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE339455_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: Spatial studies usually ship Space Ranger style folders (count matrix plus tissue images). Look for them among the supplementary files.

Also filed as BioProject PRJNA1498893. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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