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Whole-blood transcriptomic response to whole-body hyperthermia in participants with major depressive disorder

GSE301868 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2026/04/22 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 20 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
20 samples: 8 × Treatment, Female, Sample vs 5 × Sham, Male, Sample vs 4 × Sham, Female, Sample vs 3 × Treatment, Male, SampleGroups 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
Whole-blood transcriptomic response to whole-body hyperthermia in participants with major depressive disorderBrain, behavior, & immunity - health · 2026
Summary (written by the submitters)
Depression is the leading cause of global disability according to the World Health Organization, and Major Depressive Disorder (MDD) makes up a majority of these cases. Current pharmacological interventions suffer from significant limitations and side effects, highlighting a need for novel therapeutic approaches. Whole-body hyperthermia (WBH) has been identified as a promising avenue of treatment; however, a comprehensive understanding of the mechanisms responsible for the antidepressant effects of WBH remains elusive.
Read the full summary ↓
In this study we utilized high-throughput RNA sequencing (RNA-seq) to compare the whole-blood transcriptomic response, 30 minutes post intervention, of participants with MDD exposed to WBH or sham WBH. Briefly, 34 individuals with moderate to severe MDD (HDRS score > 16) were randomized to a WBH (n = 17) or sham WBH (n = 17) condition. Of 34 participants who were randomized, 22 participants provided blood samples (13 WBH and 9 sham WBH) that were available for sequencing, and 18 participants provided blood samples (9 WBH [33% female] and 9 sham WBH [44% female]) that were included in final RNA-seq analysis. Through differentially expressed gene (DEG) analysis with a false discovery rate (FDR) adjusted p-value (q-value) < 0.01 we identified 17 upregulated DEGs including multiple genes encoding heat-shock proteins (e.g., HSP70 [HSPA1A, HSPA1B, HSPA4], HSP90 [HSP90AB1, HSP90AA1], and HSP110 families [HSPH1]). Resulting log-fold changes and unadjusted p-values for all genes were used in Gene Set Enrichment Analysis (GSEA), which identified enriched (family-wise error rate-adjusted p-value < 0.05) biological processes (BPs) including “chaperone mediated protein folding”, “chaperone cofactor dependent protein refolding”, “cellular response to heat”, “positive regulation of response to cytokine stimulus”, “B cell receptor signaling pathway”, “peptide antigen assembly with MHC protein complex”, “positive regulation of type I interferon production”, and “positive regulation of interferon beta production”. These data identify novel genes and BPs that warrant further investigation as potential mediators of the antidepressant effects of WBH.
Published in
Whole-blood transcriptomic response to whole-body hyperthermia in participants with major depressive disorder
Akonom TN, Allen MA, Begay TK et al. · Brain, behavior, & immunity - health 2026 · PMID 42004495 · doi:10.1016/j.bbih.2026.101225
This dataset
Open GSE301868 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 GSE301868_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 PRJNA1287674 and SRA study SRP598906. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42004495) ↗
Study design
8 × Treatment, Female, Sample vs 5 × Sham, Male, Sample vs 4 × Sham, Female, Sample vs 3 × Treatment, Male, Sample

Supports a between-group comparison across 20 samples.

How we read this: 4 replicated groups read from 20 sample titles; they account for 20 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
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