GEO series

Biomarkers of Immune Dysregulation and Post-Treatment Inflammation in Spinal Muscular Atrophy

GSE290216 Homo sapiens (human) Single-cell RNA-seq 11 samples Submitted 2025/09/09 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 11 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 11 samples: 9 distinct titles, 2 of them repeatedGroups are read from the sample names, not from the paper. Check the list below.
Data you can get: A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper: Biomarkers of immune dysregulation and posttreatment inflammation in spinal muscular atrophyProceedings of the National Academy of Sciences of the United States of America · 2025

Summary (written by the submitters)

Spinal Muscular Atrophy (SMA) is a neurodegenerative disorder primarily affecting motor neurons, but immune dysfunction may contribute to disease progression and treatment response. While AAV9-delivered SMN1 gene therapy (e.g., Zolgensma) improves survival, long-term motor outcomes remain variable. This study integrates bulk and single-cell RNA sequencing (scRNA-seq) to define immune dysregulation in SMA.

Read the full summary ↓

We analyzed peripheral blood from infants with SMA (n = 7 for bulk RNA-seq; n = 4 for scRNA-seq, <25 mo of age) along with age-matched healthy controls (n = 4 for bulk RNA-seq; n = 6 for scRNA-seq). We profiled differentially expressed genes, immune pathways, cell–cell interactions, and gene regulatory networks. SMA samples showed distinct transcriptomic signatures and elevated immune activation compared to controls. NECTIN1 was identified as a transcriptomic biomarker of disease progression, while HSPA7 was validated from prior reports. A 6- to 7-mo inflection point marked a transition from metabolic regulation to immune activation in SMA infants. NF-κB–related inflammatory gene expression was significantly elevated post–gene therapy relative to both pretreatment and healthy controls, with IL1B and RNF19B emerging as key transcriptomic mediators. scRNA-seq revealed early dysfunction and G1-phase arrest in CD4+ T-cells, along with a switch to RELB-mediated noncanonical NF-κB signaling. In symptomatic infants, CD8+ T-cells showed higher proliferation and exhaustion, with co-upregulation of TBX21 and EOMES, genes consistent with chronic stimulation and a trajectory toward terminal differentiation. Immune dysregulation is a central feature of SMA and may influence treatment response. These findings support future development of adjunct immunomodulatory strategies to enhance gene therapy efficacy and suggest that immune signatures may correlate with motor function outcomes.

Published in

Biomarkers of immune dysregulation and posttreatment inflammation in spinal muscular atrophy

Jordan SC, Bakhtiari M, Bhasin SS et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 40986347 · doi:10.1073/pnas.2506976122

This dataset

Open GSE290216 in finder → Find more human RNA-seq datasets →

Download · which file do I need?

Direct links to NCBI and ENA, 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, or the whole study as GSE290216_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1226588 and SRA study SRP565594. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40986347) ↗

Study design

9 distinct titles, 2 of them repeated

Asymptomatic SMA Infant # ×2 Symptomatic SMA Infant # ×2

How we read this: Read from 11 sample titles: 9 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

GSM8808559 Bulk RNA-seq: SMA Infant #1, Post-Treatment
GSM8808560 Bulk RNA-seq: SMA Infant #2, Pre-Treatment
GSM8808561 Bulk RNA-seq: SMA Infant #2, Post-Treatment
GSM8808562 Bulk RNA-seq: SMA Infant #3, Pre-Treatment
GSM8808563 Bulk RNA-seq: SMA Infant #3, Post-Treatment
GSM8808564 Bulk RNA-seq: SMA Infant #4, Pre-Treatment
GSM8808565 Bulk RNA-seq: SMA Infant #4, Post-Treatment
GSM8808566 Single-Cell RNA-seq: Asymptomatic SMA Infant #1
GSM8808567 Single-Cell RNA-seq: Asymptomatic SMA Infant #2
GSM8808568 Single-Cell RNA-seq: Symptomatic SMA Infant #1
GSM8808569 Single-Cell RNA-seq: Symptomatic SMA Infant #2

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