GEO series

Shared patterns of glial transcriptional dysregulation link Huntington's disease and schizophrenia

GSE188558 Homo sapiens (human) RNA-seq (gene expression) 137 samples Submitted 2024/05/08 Platform GPL16791

At a glance

RNA-seq (gene expression) · human · 137 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: 137 samples
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: Shared patterns of glial transcriptional dysregulation link Huntington's disease and schizophreniaBrain : a journal of neurology · 2024

Summary (written by the submitters)

Huntington’s disease (HD) and juvenile-onset schizophrenia (SCZ) have long been regarded as distinct disorders. However, both manifest cell-intrinsic abnormalities in glial differentiation, with resultant astrocytic dysfunction and hypomyelination. To assess whether a common mechanism might underlie the similar glial pathology of these otherwise disparate conditions, we utilized comparative correlation network approaches to analyze RNA-seq data from human glial progenitor cells (hGPCs) produced from disease-derived pluripotent stem cells.

Read the full summary ↓

We identified gene sets preserved between HD and SCZ hGPCs yet distinct from normal controls, that included 174 highly-connected genes in the shared disease-associated network, focused on genes involved in synaptic signaling. These synaptic genes were largely suppressed in both SCZ and HD hGPCs, and gene regulatory network analysis identified a core set of upstream regulators of this network, of which OLIG2 and TCF7L2 were prominent. Among their downstream targets, ADGRL3, a modulator of glutamatergic synapses, was notably suppressed in both SCZ and HD hGPCs. ChIP-seq confirmed that OLIG2 and TCF7L2 each bound to the regulatory region of ADGRL3, whose expression was then rescued by lentiviral overexpression of these transcription factors. These data suggest that the disease-associated suppression of OLIG2 and TCF7L2-dependent transcription of glutamate signaling regulators may impair glial receptivity to neuronal glutamate. The consequent loss of activity-dependent mobilization of hGPCs may yield deficient oligodendrocyte production, and hence the hypomyelination noted in these disorders, as well as the disrupted astrocytic differentiation and attendant synaptic dysfunction associated with each. Together, these data highlight the importance of convergent glial molecular pathology in both the pathogenesis and phenotypic similarities of two otherwise unrelated disorders, HD and SCZ.

Published in

Shared patterns of glial transcriptional dysregulation link Huntington's disease and schizophrenia

Huynh NPT, Osipovitch M, Foti R et al. · Brain : a journal of neurology 2024 · PMID 39028640 · doi:10.1093/brain/awae166

This dataset

Open GSE188558 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 GSE188558_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 PRJNA779421 and SRA study SRP345441. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39028640) ↗

Samples in this study

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+ 137 more — browse all 137 samples with per-sample file links →

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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.