Identification of Mood Disorders Causal Genes by Integrating the Brain Proteome and Transcriptome.

Genome-wide association analysis studies (GWAS) have revealed loci associated with mood disorders (MD). However, the mechanism of action of these loci on drug targets for MD remains uncertain. Therefore, in this study, our aim was to identify causal genes for MD by integrating brain transcriptomic and proteomic expression data. We employed a combination of PWAS (proteome-wide association study), TWAS (transcriptome-wide association study), Mendelian randomization (MR), Bayesian colocalization analysis, as well as conditional and joint analysis to identify causal genes for MD in the brain. To validate our findings, we also utilized the GEO dataset. Our comprehensive analyses indicated that GPX1 and GMPPB were the most promising target genes, as they exhibited the highest causal association with MD. GPX1 exhibited the highest causal association index with MD, followed by GMPPB. Increased abundance of these two genes was associated with an elevated risk of developing MD, and both were predominantly expressed in the cerebral cortex.