ArticleMolecular psychiatry2020
Identification and prioritization of gene sets associated with schizophrenia risk by co-expression network analysis in human brain.
Article in Molecular psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 1 of them a synthesis that pooled it.
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Who cites it
72 citing papers in PubMed, 1 synthesis or guideline pooled it.
- MiR-574-5P, miR-1827, and miR-4429 as Potential Biomarkers for Schizophrenia.Journal of molecular neuroscience : MN · 2022Pooled it
- Analysis of gene co-expression connectivity dynamics implicates aberrant neuron-oligodendroglia interactions in schizophrenia.Nature communications · 2026Article
- Co-expression-based models improve eQTL predictions for transcriptome-wide association studies and highlight new schizophrenia-associated genes.Nature genetics · 2026Article
- Genetic Risk and Resilience for Schizophrenia Stratified by Perinatal Gene Expression Predict Adult Cognitive Performance.bioRxiv : the preprint server for biology · 2026Article
- Transcriptomics and proteomics of projection neurons in a circuit linking hippocampus with dorsolateral prefrontal cortex in the human brain.bioRxiv : the preprint server for biology · 2026Article
- Astrocyte fatty acid metabolism as a driver of risk for major depressive disorder.Nature communications · 2026Article
- Functional implications of polygenic risk for schizophrenia in human neurons.Nature communications · 2026Article
- Altered immune and inflammatory gene expression in prefrontal cortex of antipsychotic-free schizophrenia subjects.Brain, behavior, & immunity - health · 2025Article
- Pathway Analysis Interpretation in the Multi-Omic Era.Biotech (Basel (Switzerland)) · 2025Review
- Schizophrenia-Like Deficits and Impaired Glutamate/Gamma-aminobutyric acid Homeostasis in Zfp804a Conditional Knockout Mice.Schizophrenia bulletin · 2024Article
- Article
- Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo.Nature communications · 2024Article
- The Genomic Intersection of Oligodendrocyte Dynamics in Schizophrenia and Aging Unravels Novel Pathological Mechanisms and Therapeutic Potentials.International journal of molecular sciences · 2024Review
- Exploring the multifaceted role of RASGRP1 in disease: immune, neural, metabolic, and oncogenic perspectives.Cell cycle (Georgetown, Tex.) · 2024Review
- Convergent and divergent genes expression profiles associated with brain-wide functional connectome dysfunction in deficit and non-deficit schizophrenia.Translational psychiatry · 2024Article
- Integration of machine learning to identify diagnostic genes in leukocytes for acute myocardial infarction patients.Journal of translational medicine · 2023Article
- Investigating trait variability of gene co-expression network architecture in brain by controlling for genomic risk of schizophrenia.PLoS genetics · 2023Article
- Identification of schizophrenia symptom-related gene modules by postmortem brain transcriptome analysis.Translational psychiatry · 2023Article
- Consensus molecular environment of schizophrenia risk genes in coexpression networks shifting across age and brain regions.Science advances · 2023Article
- Polygenic scores for psychiatric disorders in a diverse postmortem brain tissue cohort.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023Article
12 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Schizophrenia polygenic risk is plausibly manifested by complex transcriptional dysregulation in the brain, involving networks of co-expressed and functionally related genes. The main purpose of this study was to identify and prioritize co-expressed gene sets in a hierarchical manner, based on the strength of the relationships with clinical diagnosis and with polygenic risk for schizophrenia. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to RNA-quality-adjusted DLPFC RNA-Seq data from the LIBD Postmortem Human Brain Repository (90 controls, 74 schizophrenia cases; all Caucasians) to construct co-expression networks and detect "modules" of co-expressed genes. After multiple internal and external validation procedures, modules of selected interest were tested for enrichment in biological ontologies, for association with schizophrenia polygenic risk scores (PRSs) and with diagnosis, and also for enrichment in genes within the significant GWAS loci reported by the Psychiatric Genomic Consortium (PGC2). The association between schizophrenia genetic signals and modules of co-expression converged on one module showing not only a significant association with both diagnosis and PRS but also significant overlap with 36 PGC2 loci genes, deemed the strongest candidates for drug targets. This module contained many genes involved in synaptic signaling and neuroplasticity. Fifty-three PGC2 genes were in modules associated only with diagnosis and 59 in modules unrelated to diagnosis or PRS. Our study highlights complex relationships between gene co-expression networks in the brain and clinical state and polygenic risk for SCZ and provides a strategy for using this information in selecting and prioritizing potentially targetable gene sets for therapeutic drug development.
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