← BioTransfer GEO Dataset Finder
GEO series

Peripheral blood transcriptomics identifies cohesin–chromatin and immune dysregulation in tics and Tourette syndrome

GSE310998 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2026/05/14 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 28 × Ticpatient vs 20 × ControlGroups 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
Peripheral blood transcriptomics identifies cohesin-chromatin and immune dysregulation in tics and Tourette syndromeFrontiers in neurology · 2026
Summary (written by the submitters)
Tic disorders and Tourette syndrome are neurodevelopmental disorders arising from interplay between genetic and environmental factors. Gene regulation, via chromatin and other epigenetic mechanisms, may provide a key link between gene-environment interactions, yet remains under-investigated in tic disorders. We performed bulk RNA sequencing of peripheral blood from 28 children with tic disorders (19 with Tourette syndrome, aged 6-16, median age 10 years, 18 (64%) males) compared to 20 matched healthy controls (aged 1-25, median age 11 years, 13 (65%) males).
Read the full summary ↓
Differentially expressed genes (DEGs) were identified following false discovery rate (FDR) correction, and pathway enrichment was analysed using Gene Set Enrichment Analysis (GSEA) based on Gene Ontology (GO) and Reactome databases. To assess convergence between peripheral and brain molecular changes, DEGs were compared with published post-mortem brain transcriptomic data from individuals with Tourette syndrome. A total of 4,169 DEGs (FDR < 0.05) were identified in blood transcriptomic analysis, with 2,192 upregulated and 1,977 downregulated genes. The blood transcriptomic findings included upregulation of chromatin- and cohesin-related pathways, immune activation, and cell signalling, and downregulation of translational machinery, mitochondrial function, and DNA methylation. Comparison with post-mortem brain transcriptomic data revealed 30 overlapping genes, including 20 that were concordantly upregulated in both blood and brain, predominantly associated with immune, signalling, and cellular stress responses. Our data points to gene regulation and chromatin biology as a nexus where genetic risk and environmental exposures converge in tic disorders and related neurodevelopmental disorders, and highlight epigenetic and immune-targeting therapies as promising avenues for disease modification.
Published in
Peripheral blood transcriptomics identifies cohesin-chromatin and immune dysregulation in tics and Tourette syndrome
Patel S, Han VX, Keating BA et al. · Frontiers in neurology 2026 · PMID 42079835 · doi:10.3389/fneur.2026.1730761
This dataset
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.

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 GSE310998_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1367926 and SRA study SRP648318. Searching any of these in the dataset finder brings you back here.

Study design
28 × Ticpatient vs 20 × Control

Supports a case/control comparison: 28 samples read as cases, 20 as controls.

How we read this: 2 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.