GEO series
Genotype-Epigenome-Phenotype Integration Reveals the Contributions of Peripheral Immune Cells to Bipolar Disorder Pathogenesis, Phenotypic Heterogeneity, and Therapy
GSE316497
Homo sapiens (human)
ChIP-seq / ATAC-seq (genome binding and open chromatin)
1012 samples
Submitted 2026/03/31
Platform GPL20301Platform GPL20795
At a glance
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 1012 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Homo sapiens (human)
- Samples
- 1012 samples: 137 conditions, mostly in duplicateGroups 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)
Immune dysfunction is increasingly implicated in bipolar disorder (BD), yet its mechanistic basis remains unclear. To address this, we profile and integrate 833 genome-wide ChIP-seq datasets of five histone modifications from peripheral blood immune cells of 180 individuals (88 type I BD patients, 92 controls), with whole-genome sequencing data and clinical records.
Read the full summary ↓
We annotate 450k candidate cis-regulatory elements (CREs) based on ChIP-seq peaks and identify BD-associated differential CREs (dCREs), revealing down-regulated adaptive and up-regulated innate immune response signatures. We next map histone quantitative trait loci (QTLs) and identify genetically driven CREs (gCREs) associated with BD genetic variants, which linked to genes involved in calcium signaling and endoplasmic reticulum transport, pathways essential in both immune and neuronal function. Integrating dCREs, gCREs, and CRE-gene links, we prioritize 39 candidate driver genes in circulating immune cells, including ORMDL3, a pivotal gene associated with inflammation in asthma and ulcerative colitis. Most of these genes are associated with BD variants via blood-specific eQTLs absent in brain cells, suggesting peripheral immune-specific regulatory mechanisms. We further stratify BD patients into five epigenomic subtypes with distinct clinical features, including inflammation, glucose intolerance, and hypertension. Immune-partitioned polygenic risk scores predict these subtypes, supporting a genetic basis for immuno-epigenomic heterogeneity. Finally, we identify hundreds of drugs/compounds whose perturbation signatures counter BD-associated immune dysfunction, including drugs with known effects on the nervous system, cancers, and the cardiovascular system, offering repurposing opportunities tailored to BD patients based on inflammatory signatures. Our findings reveal a potential causal role for circulating immune cells in BD and highlight how our integrative approaches can uncover immune mechanisms and empower precision medicine in complex, non-canonical immune diseases, such as BD.
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 GSE316497_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1400219 and SRA study SRP660884. Searching any of these in the dataset finder brings you back here.
Study design
137 conditions, mostly in duplicate
histone ChIP-seq data for id_10_K4me ×2
histone ChIP-seq data for id_100_K4me ×2
histone ChIP-seq data for id_102_K4me ×2
histone ChIP-seq data for id_103_K4me ×2
histone ChIP-seq data for id_105_K4me ×2
histone ChIP-seq data for id_106_K4me ×2
histone ChIP-seq data for id_107_K4me ×2
histone ChIP-seq data for id_109_K4me ×2
+255 more
Supports a between-group comparison across 274 samples.
How we read this: 137 replicated groups read from the first 400 of 1012 sample titles; they account for 274 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
- GSM9454043 histone ChIP-seq data for id_10_K4me1 histone ChIP-seq data f…
- GSM9454044 histone ChIP-seq data for id_100_K4me1 histone ChIP-seq data f…
- GSM9454045 histone ChIP-seq data for id_102_K4me1 histone ChIP-seq data f…
- GSM9454046 histone ChIP-seq data for id_103_K4me1 histone ChIP-seq data f…
- GSM9454047 histone ChIP-seq data for id_105_K4me1 histone ChIP-seq data f…
- GSM9454048 histone ChIP-seq data for id_106_K4me1 histone ChIP-seq data f…
- GSM9454049 histone ChIP-seq data for id_107_K4me1 histone ChIP-seq data f…
- GSM9454050 histone ChIP-seq data for id_108_K4me1
- GSM9454051 histone ChIP-seq data for id_109_K4me1 histone ChIP-seq data f…
- GSM9454052 histone ChIP-seq data for id_11_K4me1 histone ChIP-seq data f…
- GSM9454053 histone ChIP-seq data for id_110_K4me1 histone ChIP-seq data f…
- GSM9454054 histone ChIP-seq data for id_111_K4me1 histone ChIP-seq data f…
- GSM9454055 histone ChIP-seq data for id_113_K4me1 histone ChIP-seq data f…
- GSM9454056 histone ChIP-seq data for id_115_K4me1 histone ChIP-seq data f…
- GSM9454057 histone ChIP-seq data for id_116_K4me1 histone ChIP-seq data f…
- GSM9454058 histone ChIP-seq data for id_117_K4me1 histone ChIP-seq data f…
- GSM9454059 histone ChIP-seq data for id_119_K4me1 histone ChIP-seq data f…
- GSM9454060 histone ChIP-seq data for id_12_K4me1 histone ChIP-seq data f…
- GSM9454061 histone ChIP-seq data for id_120_K4me1 histone ChIP-seq data f…
- GSM9454062 histone ChIP-seq data for id_121_K4me1 histone ChIP-seq data f…
- GSM9454063 histone ChIP-seq data for id_122_K4me1 histone ChIP-seq data f…
- GSM9454064 histone ChIP-seq data for id_123_K4me1 histone ChIP-seq data f…
- GSM9454065 histone ChIP-seq data for id_124_K4me1 histone ChIP-seq data f…
- GSM9454066 histone ChIP-seq data for id_125_K4me1 histone ChIP-seq data f…
- GSM9454067 histone ChIP-seq data for id_126_K4me1 histone ChIP-seq data f…
- GSM9454068 histone ChIP-seq data for id_127_K4me1 histone ChIP-seq data f…
- GSM9454069 histone ChIP-seq data for id_128_K4me1 histone ChIP-seq data f…
- GSM9454070 histone ChIP-seq data for id_129_K4me1 histone ChIP-seq data f…
- GSM9454071 histone ChIP-seq data for id_13_K4me1 histone ChIP-seq data f…
- GSM9454072 histone ChIP-seq data for id_130_K4me1
- GSM9454073 histone ChIP-seq data for id_131_K4me1 histone ChIP-seq data f…
- GSM9454074 histone ChIP-seq data for id_132_K4me1 histone ChIP-seq data f…
- GSM9454075 histone ChIP-seq data for id_133_K4me1 histone ChIP-seq data f…
- GSM9454076 histone ChIP-seq data for id_134_K4me1 histone ChIP-seq data f…
- GSM9454077 histone ChIP-seq data for id_135_K4me1 histone ChIP-seq data f…
- GSM9454078 histone ChIP-seq data for id_136_K4me1 histone ChIP-seq data f…
- GSM9454079 histone ChIP-seq data for id_138_K4me1 histone ChIP-seq data f…
- GSM9454080 histone ChIP-seq data for id_139_K4me1 histone ChIP-seq data f…
- GSM9454081 histone ChIP-seq data for id_140_K4me1 histone ChIP-seq data f…
- GSM9454082 histone ChIP-seq data for id_142_K4me1 histone ChIP-seq data f…
+ 972 more — browse all 1012 samples with per-sample file links →
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Share this dataset
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.