期刊
BIOLOGICAL PSYCHIATRY
卷 89, 期 6, 页码 627-636出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.biopsych.2020.09.010
关键词
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资金
- Medical Research Council [MR/N015746/1]
- National Institute for Health Research Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust and King's College London
- Maudsley Charity [980]
- Guy's and St. Thomas' Charity [TR130505]
A transcriptome-wide association study identified 94 genes differentially expressed in depression, with approximately half being novel. Six of these genes showed strong, colocalized, and potentially causal associations with depression. Enrichment analysis highlighted dysregulation of gene sets related to neuronal and synaptic processes.
BACKGROUND: Major 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. METHODS: Genes 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. RESULTS: Transcriptome-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. CONCLUSIONS: This 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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