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CD4+ T cells contribute to neurodegeneration in Lewy body dementia [CSF_and_PBMCs_Healthy and LBD]

GSE141578 Homo sapiens (human) Single-cell RNA-seq 35 samples Submitted 2021/09/14 Platform GPL28038Platform GPL24676
At a glance

Single-cell RNA-seq · human · 35 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. 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
35 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.
Summary (written by the submitters)
Recent studies indicate that the adaptive immune system plays a role in Lewy body dementia (LBD). However, the mechanism regulating T cell brain homing in LBD is unknown. Here, we observed T cells adjacent to Lewy bodies and dopaminergic neurons in post-mortem LBD brains. Single-cell RNA sequencing of cerebrospinal fluid (CSF) identified upregulated expression of C-X-C Motif Chemokine Receptor 4 (CXCR4) in CD4+ T cells in LBD.
Read the full summary ↓
CSF protein levels of the CXCR4 ligand, C-X-C Motif Chemokine Ligand 12 (CXCL12) were associated with neuroaxonal damage in LBD. Furthermore, we observed clonal expansion and upregulated Interleukin 17A expression by CD4+ T cells stimulated with a phosphorylated α-synuclein epitope. Thus, CXCR4-CXCL12 signaling may represent a mechanistic target for inhibiting pathological interleukin-17-producing T cell trafficking in LBD.
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 GSE141578_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: 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 PRJNA593998 and SRA study SRP234979. Searching any of these in the dataset finder brings you back here.

Samples in this study

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