ArticleTranslational psychiatry2018
Identification and replication of RNA-Seq gene network modules associated with depression severity.
Article in Translational psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed, 52 citations in OpenAlex.
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- Higher immune-related gene expression in major depression is independent of CRP levels: results from the BIODEP study.Translational psychiatry · 2023Article
- Identification of key potassium channel genes of temporal lobe epilepsy by bioinformatics analyses and experimental verification.Frontiers in neurology · 2023Article
- The long noncoding RNA FEDORA is a cell type- and sex-specific regulator of depression.Science advances · 2022Article
- Differential expression of MDGA1 in major depressive disorder.Brain, behavior, & immunity - health · 2022Article
- Cellular and immunometabolic mechanisms of inflammation in depression: Preliminary findings from single cell RNA sequencing and a tribute to Bruce McEwen.Neurobiology of stress · 2022Article
- Identification of Key Modules and Genes Associated with Major Depressive Disorder in Adolescents.Genes · 2022Article
- Identifying Antidepressant Effects of Brain-Derived Neurotrophic Factor and IDO1 in the Mouse Model Based on RNA-Seq Data.Frontiers in genetics · 2022Article
- Advancements in Genomic and Behavioral Neuroscience Analysis for the Study of Normal and Pathological Brain Function.Frontiers in molecular neuroscience · 2022Review
- Preventive strategies for adolescent depression: What are we missing? A focus on biomarkers.Brain, behavior, & immunity - health · 2021Article
- No evidence for differential gene expression in major depressive disorder PBMCs, but robust evidence of elevated biological ageing.Translational psychiatry · 2021Article
- Aiding and Abetting Anhedonia: Impact of Inflammation on the Brain and Pharmacological Implications.Pharmacological reviews · 2021Review
- Weighted gene co-expression network analysis identifies specific modules and hub genes related to coronary artery disease.Scientific reports · 2021Article
- Changes in transcriptome profiling during the acute/subacute phases of contusional spinal cord injury in rats.Annals of translational medicine · 2020Article
- Novel immune subtypes of lung adenocarcinoma identified through bioinformatic analysis.FEBS open bio · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
12 authors at 8 institutions in 1 country.
Funding
Abstract
Genomic variation underlying major depressive disorder (MDD) likely involves the interaction and regulation of multiple genes in a network. Data-driven co-expression network module inference has the potential to account for variation within regulatory networks, reduce the dimensionality of RNA-Seq data, and detect significant gene-expression modules associated with depression severity. We performed an RNA-Seq gene co-expression network analysis of mRNA data obtained from the peripheral blood mononuclear cells of unmedicated MDD (n = 78) and healthy control (n = 79) subjects. Across the combined MDD and HC groups, we assigned genes into modules using hierarchical clustering with a dynamic tree cut method and projected the expression data onto a lower-dimensional module space by computing the single-sample gene set enrichment score of each module. We tested the single-sample scores of each module for association with levels of depression severity measured by the Montgomery-Åsberg Depression Scale (MADRS). Independent of MDD status, we identified 23 gene modules from the co-expression network. Two modules were significantly associated with the MADRS score after multiple comparison adjustment (adjusted p = 0.009, 0.028 at 0.05 FDR threshold), and one of these modules replicated in a previous RNA-Seq study of MDD (p = 0.03). The two MADRS-associated modules contain genes previously implicated in mood disorders and show enrichment of apoptosis and B cell receptor signaling. The genes in these modules show a correlation between network centrality and univariate association with depression, suggesting that intramodular hub genes are more likely to be related to MDD compared to other genes in a module.
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