GEO series

Age-related transcriptomic differences in peripheral blood of adolescents with major depressive disorder

GSE255685 Homo sapiens (human) RNA-seq (gene expression) 279 samples Submitted 2026/04/13 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 279 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: 279 samples: 180 × YZ vs 99 × ZGroups 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: Integrated bulk and single-cell RNA sequencing reveals peripheral immune dysregulation in adolescent major depressive disorderBrain, behavior, and immunity · 2026

Summary (written by the submitters)

In this study, we collected peripheral blood samples of a typical large population, including MDD cases and healthy controls from children and adolescents, and aimed to apply RNA-seq sequencing to comprehensively analyze the transcriptomic characteristics in adolescent depression patients. In comparison to healthy patients, we discovered that several immune response-associated genes were dysregulated in MDD patients, with the majority of these differential genes strongly correlated with the HAMD-17 and HAMA scores.

Read the full summary ↓

Furthermore, we investigated the effects of drug therapy on transcription variations in teenagers with MDD and discovered that changes in these differentially expressed genes and immune cell types were unaffected by drug use, implying that the current medication has a lower effect on the MDD population. Notably, these transcriptional differences may disrupt the immune system's coordinated function during adolescent and adult depression, resulting in distinct changes in immune cells that contribute to the pathophysiology of depression in adolescents. Our findings may shed new light on the pathogenesis of depression in children and adolescents, potentially leading to more precise and effective treatment strategies.

Published in

Integrated bulk and single-cell RNA sequencing reveals peripheral immune dysregulation in adolescent major depressive disorder

Liu X, Huang F, He Y et al. · Brain, behavior, and immunity 2026 · PMID 41740874 · doi:10.1016/j.bbi.2026.106512

This dataset

Open GSE255685 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 GSE255685_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 PRJNA1076163 and SRA study SRP489627. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41740874) ↗

Study design

180 × YZ vs 99 × Z

Supports a between-group comparison across 279 samples.

How we read this: 2 replicated groups read from 279 sample titles; they account for 279 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

GSM8077449 YZ1002 YZ
GSM8077450 YZ1005 YZ
GSM8077451 YZ1045 YZ
GSM8077452 YZ1077 YZ
GSM8077453 YZ1083 YZ
GSM8077454 YZ1092 YZ
GSM8077455 YZ161 YZ
GSM8077456 YZ164 YZ
GSM8077457 YZ166 YZ
GSM8077458 YZ178 YZ
GSM8077459 YZ188 YZ
GSM8077460 YZ268 YZ
GSM8077461 YZ312 YZ
GSM8077462 YZ353 YZ
GSM8077463 YZ359 YZ
GSM8077464 YZ362 YZ
GSM8077465 YZ369 YZ
GSM8077466 YZ376 YZ
GSM8077467 YZ391 YZ
GSM8077468 YZ403 YZ
GSM8077469 YZ406 YZ
GSM8077470 YZ407 YZ
GSM8077471 YZ408 YZ
GSM8077472 YZ419 YZ
GSM8077473 YZ420 YZ
GSM8077474 YZ425 YZ
GSM8077475 YZ427 YZ
GSM8077476 YZ431 YZ
GSM8077477 YZ432 YZ
GSM8077478 YZ435 YZ
GSM8077479 YZ449 YZ
GSM8077480 YZ450 YZ
GSM8077481 YZ452 YZ
GSM8077482 YZ454 YZ
GSM8077483 YZ456 YZ
GSM8077484 YZ461 YZ
GSM8077485 YZ471 YZ
GSM8077486 YZ473 YZ
GSM8077487 YZ475 YZ
GSM8077488 YZ478 YZ

+ 239 more — browse all 279 samples with per-sample file links →

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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.