ArticleBiological psychiatry2021
Delineating the Genetic Component of Gene Expression in Major Depression.
Article in Biological psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 6 of them syntheses that pooled it.
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Who cites it
72 citing papers in PubMed, 6 syntheses or guidelines pooled it, 106 citations in OpenAlex.
- Multiancestry and Multitrait GWAS Meta-Analysis on Schizophrenia With a Sample of 322,321 Unveils Genetic Links to Chronic Lung Diseases.Genes, brain, and behavior · 2026Pooled it
- Multi-Trait Genetic Insights Into Schizophrenia Across Ancestries: Genome-Wide Association Meta-Analyses, Machine Learning, and Drug Repurposing Study.Brain and behavior · 2026Pooled it
- A systematic narrative review of the form, process, and function of sensory hyposensitivity in depression.Translational psychiatry · 2026Pooled it
- Cross-ancestry genome-wide association study and systems-level integrative analyses implicate new risk genes and therapeutic targets for depression.Nature human behaviour · 2025Pooled it
- Pooled it
- Genome-wide meta-analysis, functional genomics and integrative analyses implicate new risk genes and therapeutic targets for anxiety disorders.Nature human behaviour · 2024Pooled it
- Precision medicine for atherosclerotic cardiovascular disease: Integrative genomics maps risk loci and AI-predicted functional consequences.Clinical and translational medicine · 2026Article
- Integrative Genomic Analyses IdentifybioRxiv : the preprint server for biology · 2026Article
- Optimization of potential targets for antidepressant Chinese medicines: AI and multi-omics methods.Chinese medicine · 2026Review
- Unraveling the genetic interplay and therapeutic potentials between major depressive disorder and metabolic syndrome: multi-ancestry and multi-trait genome-wide association analyses.BMC psychiatry · 2026Article
- Article
- Elevated NEGR1 in brain induces anxiety or depression-like phenotypes and synaptic dysfunction.Molecular psychiatry · 2025Article
- GRPa-PRS: A risk stratification method to identify genetically-regulated pathways in polygenic diseases.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Analysis of Genomic and Transcriptomic Data Revealed Key Genes and Processes in the Development of Major Depressive Disorder.International journal of molecular sciences · 2025Article
- Multiomic analyses direct hypotheses for Creutzfeldt-Jakob disease risk genes.Brain : a journal of neurology · 2025Article
- Single-nucleus chromatin accessibility profiling identifies cell types and functional variants contributing to major depression.Nature genetics · 2025Article
- The C/C Genotype of the C-1019G (rs6295) Polymorphism of the 5-HT1A Receptor Gene Is Associated with Lower Susceptibility to Depressive Symptoms in a Rural Population in Mexico.Neurology international · 2025Article
- The regulatory variant rs1950834 confers the risk of depressive disorder by reducing LRFN5 expression.BMC medicine · 2025Article
- Increased TMEM106B levels lead to lysosomal dysfunction which affects synaptic signaling and neuronal health.Molecular neurodegeneration · 2025Article
- PSMB4: a potential biomarker and therapeutic target for depression, perspective from integration analysis of depression GWAS data and human plasma proteome.Translational psychiatry · 2025Article
12 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundMajor depression (MD) is determined by a multitude of factors including genetic risk variants that regulate gene expression. We examined the genetic component of gene expression in MD by performing a transcriptome-wide association study (TWAS), inferring gene expression-trait relationships from genetic, transcriptomic, and phenotypic information.
methodsGenes differentially expressed in depression were identified with the TWAS FUSION method, based on summary statistics from the largest genome-wide association analysis of MD (n = 135,458 cases, n = 344,901 controls) and gene expression levels from 21 tissue datasets (brain; blood; thyroid, adrenal, and pituitary glands). Follow-up analyses were performed to extensively characterize the identified associations: colocalization, conditional, and fine-mapping analyses together with TWAS-based pathway investigations.
resultsTranscriptome-wide significant differences between cases and controls were found at 94 genes, approximately half of which were novel. Of the 94 significant genes, 6 represented strong, colocalized, and potentially causal associations with depression. Such high-confidence associations include NEGR1, CTC-467M3.3, TMEM106B, LRFN5, ESR2, and PROX2. Lastly, TWAS-based enrichment analysis highlighted dysregulation of gene sets for, among others, neuronal and synaptic processes.
conclusionsThis study sheds further light on the genetic component of gene expression in depression by characterizing the identified associations, unraveling novel risk genes, and determining which associations are congruent with a causal model. These findings can be used as a resource for prioritizing and designing subsequent functional studies of MD.
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