GEO series

Whole transcriptome analysis of unmutated sporadic ALS patients’ peripheral blood reveals phenotype-specific gene expression signature

GSE288704 Homo sapiens (human) RNA-seq (gene expression) 66 samples Submitted 2026/02/04 Platform GPL21697

At a glance

RNA-seq (gene expression) · human · 66 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: 66 samples: 66 samples, each with a distinct title — no replicated groupsGroups 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)

Amyotrophic lateral sclerosis (ALS) is an adult neurodegenerative disorder. According to clinical criteria, ALS patients can be classified into eight subgroups: classic, bulbar, pyramidal, pure lower motor neuron, flail arm, pure upper motor neuron, flail leg, and respiratory. There are no well-established molecular biomarkers for early diagnosis, prognosis, and progression monitoring of this fatal disease.

Read the full summary ↓

Classification based on clinical phenotypes could be associated with peculiar gene expression patterns shaped during lifespan, allowing the identification of specific sporadic ALS (sALS) subtypes with less heterogeneous clinical and biological features. Our objective was to define a phenotype-specific transcriptomic signature of distinct ALS phenotypes, and lay the foundation for biomarkers development. We characterized 48 sALS patients by clinical and paraclinical parameters, and subdivided them in “Classic” (n=12), “Bulbar” (n=10), “Flail Arm” (n=7), “Flail Leg” (n=10) and “Pyramidal” (n=9) phenotypes. RNAs extracted from patients’ PBMCs and 19 controls were sequenced. Our analysis allowed the visualization of gene expression differential clusters between patients and controls. Interestingly, only one gene (Y3_RNA, a misc_RNA component of the Ro60 ribonucleoprotein involved in cellular response to interferon-alpha) was upregulated at different levels across all phenotypes, whereas other genes appeared phenotype-specific. The work proposed stress the innovative view of ALS as a multi-systemic disorder rather than a pure motor neuron-associated and ‘neurocentric’ pathology. The possibility to cluster ALS patients based on their molecular signature pave the way for future personalized clinical trials and early diagnosis.

This dataset

Open GSE288704 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 GSE288704_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 PRJNA1219103 and SRA study SRP561464. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

66 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 66 sample titles: 66 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

GSM8773301 PBMCs,ALS,B1,T0
GSM8773302 PBMCs,ALS,B2,T0
GSM8773303 PBMCs,ALS,B3,T0
GSM8773304 PBMCs,ALS,B4,T0
GSM8773305 PBMCs,ALS,B5,T0
GSM8773306 PBMCs,ALS,B6,T0
GSM8773307 PBMCs,ALS,B7,T0
GSM8773308 PBMCs,ALS,B8,T0
GSM8773309 PBMCs,ALS,B9,T0
GSM8773310 PBMCs,ALS,B10,T0
GSM8773311 PBMCs,ALS,C1,T0
GSM8773312 PBMCs,ALS,C2,T0
GSM8773313 PBMCs,ALS,C3,T0
GSM8773314 PBMCs,ALS,C4,T0
GSM8773315 PBMCs,ALS,C5,T0
GSM8773316 PBMCs,ALS,C6,T0
GSM8773317 PBMCs,ALS,C7,T0
GSM8773318 PBMCs,ALS,C8,T0
GSM8773319 PBMCs,ALS,C9,T0
GSM8773320 PBMCs,ALS,C10,T0
GSM8773321 PBMCs,ALS,C12,T0
GSM8773322 PBMCs,ALS,FA1,T0
GSM8773323 PBMCs,ALS,FA2,T0
GSM8773324 PBMCs,ALS,FA3,T0
GSM8773325 PBMCs,ALS,FA4,T0
GSM8773326 PBMCs,ALS,FA5,T0
GSM8773327 PBMCs,ALS,FA6,T0
GSM8773328 PBMCs,ALS,FA7,T0
GSM8773329 PBMCs,ALS,FL1,T0
GSM8773330 PBMCs,ALS,FL2,T0
GSM8773331 PBMCs,ALS,FL3,T0
GSM8773332 PBMCs,ALS,FL4,T0
GSM8773333 PBMCs,ALS,FL5,T0
GSM8773334 PBMCs,ALS,FL6,T0
GSM8773335 PBMCs,ALS,FL7,T0
GSM8773336 PBMCs,ALS,FL8,T0
GSM8773337 PBMCs,ALS,FL9,T0
GSM8773338 PBMCs,ALS,FL10,T0
GSM8773339 PBMCs,ALS,P1,T0
GSM8773340 PBMCs,ALS,P2,T0

+ 26 more — browse all 66 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.