Identifying causal genes for depression via integration of the proteome and transcriptome from brain and blood.
Mol Psychiatry
; 27(6): 2849-2857, 2022 06.
Article
en En
| MEDLINE
| ID: mdl-35296807
ABSTRACT
Genome-wide association studies (GWASs) have identified numerous risk genes for depression. Nevertheless, genes crucial for understanding the molecular mechanisms of depression and effective antidepressant drug targets are largely unknown. Addressing this, we aimed to highlight potentially causal genes by systematically integrating the brain and blood protein and expression quantitative trait loci (QTL) data with a depression GWAS dataset via a statistical framework including Mendelian randomization (MR), Bayesian colocalization, and Steiger filtering analysis. In summary, we identified three candidate genes (TMEM106B, RAB27B, and GMPPB) based on brain data and two genes (TMEM106B and NEGR1) based on blood data with consistent robust evidence at both the protein and transcriptional levels. Furthermore, the protein-protein interaction (PPI) network provided new insights into the interaction between brain and blood in depression. Collectively, four genes (TMEM106B, RAB27B, GMPPB, and NEGR1) affect depression by influencing protein and gene expression level, which could guide future researches on candidate genes investigations in animal studies as well as prioritize antidepressant drug targets.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Proteoma
/
Estudio de Asociación del Genoma Completo
Tipo de estudio:
Clinical_trials
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Mol Psychiatry
Asunto de la revista:
BIOLOGIA MOLECULAR
/
PSIQUIATRIA
Año:
2022
Tipo del documento:
Article
País de afiliación:
China