GEO series

Blood-brain barrier disruption in sports-related traumatic encephalopathy syndrome

GSE319802 Homo sapiens (human) Single-nucleus RNA-seq 65 samples Submitted 2026/03/01 Platform GPL24676

At a glance

Single-nucleus RNA-seq · human · 65 samples

What it is: Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). 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: 65 samples: 57 × Retired vs 8 × 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.

Summary (written by the submitters)

Cerebrovascular disruption has been implicated in the pathophysiology of head trauma and chronic traumatic encephalopathy (CTE). However, the long-term consequences of repetitive head trauma on blood–brain barrier (BBB) integrity and its link to cognitive function remains unknown. Here, using dynamic contrast enhanced MRI (DCE-MRI), we show that BBB disruption can be detected years after combat and collision sports athletes (n = 47) have retired from their respective sports.

Read the full summary ↓

A subgroup of individuals (n = 17) with extensive BBB disruption displayed worse cognitive decline compared to those with less extensive disruption. While commonly used systemic biomarkers of central nervous system injury and neurodegeneration were of limited utility, we did observe a greater systemic inflammatory burden with a higher proportion of circulating monocytes that was significantly associated with cognitive decline in retired athletes. Transcriptomic analysis of these peripheral immune cells revealed dysregulation of the complement system and vascular developmental pathways. Altered expression of complement receptors including C5AR1, ITGAM, ITGB2 and CD59, a potent inhibitor of the membrane attack complex (MAC), was associated with BBB disruption and cognitive decline. Post-mortem tissue from confirmed cases of CTE showed MAC deposition around cerebral blood vessels. Finally, bioinformatic analysis of single nucleus RNA sequencing data from post-mortem CTE cases revealed microglia-endothelial crosstalk which may mediate complement dysregulation. Together, our data suggest that sustained systemic inflammation and persistent BBB disruption is associated with the long-term outcome of repetitive head trauma.

This dataset

Open GSE319802 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 GSE319802_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 PRJNA1425117 and SRA study SRP677882. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

57 × Retired vs 8 × Control

Supports a between-group comparison across 65 samples.

How we read this: 2 replicated groups read from 65 sample titles; they account for 65 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

GSM9526593 Retired 1 Retired
GSM9526594 Retired 2 Retired
GSM9526595 Retired 3 Retired
GSM9526596 Retired 4 Retired
GSM9526597 Retired 5 Retired
GSM9526598 Retired 6 Retired
GSM9526599 Retired 7 Retired
GSM9526600 Retired 8 Retired
GSM9526601 Retired 9 Retired
GSM9526602 Retired 10 Retired
GSM9526603 Retired 11 Retired
GSM9526604 Retired 12 Retired
GSM9526605 Retired 13 Retired
GSM9526606 Retired 14 Retired
GSM9526607 Retired 15 Retired
GSM9526608 Retired 16 Retired
GSM9526609 Retired 17 Retired
GSM9526610 Retired 18 Retired
GSM9526611 Retired 19 Retired
GSM9526612 Retired 20 Retired
GSM9526613 Retired 21 Retired
GSM9526614 Retired 22 Retired
GSM9526615 Retired 23 Retired
GSM9526616 Control 1 Control
GSM9526617 Retired 24 Retired
GSM9526618 Retired 25 Retired
GSM9526619 Retired 26 Retired
GSM9526620 Retired 27 Retired
GSM9526621 Retired 28 Retired
GSM9526622 Retired 29 Retired
GSM9526623 Retired 30 Retired
GSM9526624 Retired 31 Retired
GSM9526625 Retired 32 Retired
GSM9526626 Retired 33 Retired
GSM9526627 Retired 34 Retired
GSM9526628 Retired 35 Retired
GSM9526629 Retired 36 Retired
GSM9526630 Control 2 Control
GSM9526631 Retired 37 Retired
GSM9526632 Retired 38 Retired

+ 25 more — browse all 65 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.