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Phenotypic variability in SCN1A-associated febrile seizures: transcriptomic and electrophysiological insights from iPSC-derived neurons

GSE289689 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/06/30 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 24 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
24 samples: 8 conditions, mostly in triplicateGroups 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
Transcriptomic and electrophysiological alterations underlying phenotypic variability in SCN1A-associated febrile seizuresScientific reports · 2025
Summary (written by the submitters)
Febrile seizures (FS) are a common childhood neurological condition triggered by fever in children without prior neurological disorders. While generally benign, some individuals, particularly those with complex FS or genetic predispositions, may develop epilepsy or other neurological comorbidities. The mechanisms underlying this transition remain unclear.
Read the full summary ↓
Mutations in SCN1A, encoding the NaV1.1 sodium channel α-subunit, have been linked to several epilepsy syndromes associated with FS. This study examines phenotypic variability in individuals carrying the same SCN1A c.434T>C mutation, using induced pluripotent stem cell (iPSC)-derived neurons from two siblings with FS. Despite sharing the mutation, only the older sibling developed temporal lobe epilepsy (TLE). Transcriptomic analysis revealed downregulation of GABAergic pathway genes in both siblings’ neurons, aligning with SCN1A-associated epilepsy. However, neurons from the sibling with TLE exhibited additional abnormalities, including altered AMPA receptor subunit composition, changes in GABAA receptor subunit and chloride cotransporter expression, and reduced brain-derived neurotrophic factor (BDNF) levels, indicative of developmental immaturity. Voltage-clamp recordings confirmed impaired GABAergic and AMPA receptor-mediated synaptic activity. These findings suggest that combined GABAergic dysfunction, aberrant AMPA receptor composition, and reduced BDNF signaling contribute to the more severe phenotype and increased epilepsy susceptibility. These findings suggest that combined GABAergic dysfunction, aberrant AMPA receptor composition, and reduced BDNF signaling may underlie the more severe phenotype and increase epilepsy susceptibility in this individual.
Published in
Transcriptomic and electrophysiological alterations underlying phenotypic variability in SCN1A-associated febrile seizures
Scalise S, Gaeta A, Aprigliano E et al. · Scientific reports 2025 · PMID 40634438 · doi:10.1038/s41598-025-09208-3
This dataset
Open GSE289689 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 GSE289689_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1223951 and SRA study SRP564056. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40634438) ↗
Study design
8 conditions, mostly in triplicate
GCd15 ×3 GCd45 ×3 GSd15 ×3 GSd45 ×3 SEVd15 ×3 SEVd45 ×3 MILDd15 ×3 MILDd45 ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 of them. 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
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