ArticleTranslational psychiatry2024
Single-cell multiomics analysis reveals cell/tissue-specific associations in bipolar disorder.
Article in Translational psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Deep learning-based differential diagnosis of major depression and bipolar disorder using microglia-cellular sensors and patient-derived small extracellular vesicles.Scientific reports · 2026Article
- Immune involvement in neuropsychiatric disorders: Insights from single-cell transcriptomic studies.Psychiatry and clinical neurosciences · 2026Review
- Cortical Transcriptomic Profiling Reveals Cellular and Mitochondrial Adaptive Stress Signatures That Differ Between Schizophrenia and Bipolar Disorder.Schizophrenia bulletin · 2026Article
- Multi-omics approaches to major psychiatric disorders.Neuropsychiatrie : Klinik, Diagnostik, Therapie und Rehabilitation : Organ der Gesellschaft Osterreichischer Nervenarzte und Psychiater · 2026Review
- Molecular and Neuroimaging Correlates of Bipolar Disorder: Linking Inflammation, Mitochondria, and Brain Circuitry.International journal of molecular sciences · 2026Review
- Review
- Artificial Intelligence-Based Methods and Omics for Mental Illness Diagnosis: A Review.Bioengineering (Basel, Switzerland) · 2025Review
- New Genomics Discoveries Across the Bipolar Disorder Spectrum Implicate Neurobiological and Developmental Pathways.Biological psychiatry · 2025Review
- Canonical and non-canonical roles of oligodendrocyte precursor cells in mental disorders.Npj mental health research · 2025Review
- Binding of zebrafish lipovitellin and L1‑ORF2 increases the accessibility of L1‑ORF2 via interference with histone wrapping.International journal of molecular medicine · 2025Article
- Neuronal Synaptic Communication and Mitochondrial Energetics in Human Health and Disease.Advances in experimental medicine and biology · 2025Review
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
This study investigates the cellular origin and tissue heterogeneity in bipolar disorder (BD) by integrating multiomics data. Four distinct datasets were employed, including single-cell RNA sequencing (scRNA-seq) data (embryonic and fetal brain, n = 8, 1,266 cells), BD Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data (adult brain, n = 210), BD bulk RNA-seq data (adult brain, n = 314), and BD genome-wide association study (GWAS) summary data (n = 413,466). The integration of scRNA-seq data with multiomics data relevant to BD was accomplished using the single-cell disease relevance score (scDRS) algorithm. We have identified a novel brain cell cluster named ADCY1, which exhibits distinct genetic characteristics. From a high-resolution genetic perspective, glial cells emerge as the primary cytopathology associated with BD. Specifically, astrocytes were significantly related to BD at the RNA-seq level, while microglia showed a strong association with BD across multiple panels, including the transcriptome-wide association study (TWAS), ATAC-seq, and RNA-seq. Additionally, oligodendrocyte precursor cells displayed a significant association with BD in both ATAC-seq and RNA-seq panel. Notably, our investigation of brain regions affected by BD revealed significant associations between BD and all three types of glial cells in the dorsolateral prefrontal cortex (DLPFC). Through comprehensive analyses, we identified several BD-associated genes, including CRMP1, SYT4, UCHL1, and ZBTB18. In conclusion, our findings suggest that glial cells, particularly in specific brain regions such as the DLPFC, may play a significant role in the pathogenesis of BD. The integration of multiomics data has provided valuable insights into the etiology of BD, shedding light on potential mechanisms underlying this complex psychiatric disorder.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.