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Computational modeling and preclinical evaluation support targeting somatic instability for Huntington’s disease treatment.

GSE338964 Homo sapiens (human) RNA-seq (gene expression) 104 samples Submitted 2026/07/21 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 104 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
104 samples: 96 distinct titles, 4 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.
Summary (written by the submitters)
Huntington’s disease (HD) is caused by an expanded CAG trinucleotide repeat within the huntingtin (HTT) gene. Genetic modifiers of disease onset and progression in HD implicate somatic instability (SI) of the expanded CAG repeat as a key pathogenic driver, with MSH3 emerging as a leading therapeutic target. To inform development of an SI-targeting therapy, we generated a computational model that uses HD patient data to infer therapeutic effects of reducing SI.
Read the full summary ↓
To target SI experimentally, we designed an artificial microRNA to lower MSH3 mRNA (miMSH3) after delivery with AAV-DB-3, a previously described medium spiny neuron (MSN)-targeting AAV capsid variant. AAV-DB-3.miMSH3 achieved 48–94% MSH3 mRNA reduction in MSNs of nonhuman primates (NHPs). Predictive modeling indicates this level of knockdown would delay motor symptom onset by more than 5 years in most HD gene-positive individuals, with many predicted to experience delays exceeding 50 years. Applied to a representative patient, the model predicts 50–120 % slowing of HD progression as measured by change from baseline in the composite Unified Huntington Disease Rating Scale (cUHDRS). Finally, AAV-DB-3.miMSH3 reduced Msh3 mRNA and protein by up to 27% and 40%, respectively, and SI by up to 46% in HdhQ111 mice. Cumulatively, the preclinical experimental data and the computational model support the translational potential of AAV-DB-3.miMSH3 as a disease-modifying therapy for HD.
This dataset
Open GSE338964 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 GSE338964_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 PRJNA1496612 and SRA study SRP718811. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
96 distinct titles, 4 of them repeated
CMV ×3 HDS1 ×3 MSH3-6 ×3 MSH3-11 ×3

How we read this: Read from 104 sample titles: 96 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

+ 64 more — browse all 104 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.