Exploring the genetics of depression: multi-phenotype analysis of genome-wide association and functional genomics studies reveals novel markers and effector genes for major depressive disorder.
Major Depressive Disorder, colocalization, Mendelian Randomization, genome-wide association studies
This work explored the genetics of Major Depressive Disorder (MDD) through an integrated approach that combined multi-trait Genome-Wide Association Studies (GWAS) with functional genomics. Given the polygenic nature of depression and the challenge of "missing heritability", multi-trait analysis was employed to increase statistical power by leveraging the shared genetic architecture with other psychiatric disorders. The Multi-trait Analysis of GWAS (MTAG) software was utilized for this purpose, selecting phenotypes based on rigorous criteria of genetic correlation, ancestry, and sample size. After the multi-trait analysis, significant loci were annotated, and the majority of variants were found in non-coding regions of deoxyribonucleic acid (DNA), which motivated the performance of a colocalization study. For genome-wide Mendelian Randomization (MR) and colocalization, a bioinformatics pipeline called Causeway was developed, aiming to overcome the computational difficulties of existing software and ensure scalability and reproducibility with Nextflow. Colocalization analysis was performed between the multi-phenotype GWAS results and expression quantitative trait loci (eQTLs)/protein quantitative trait loci (pQTLs) data from blood and brain, identifying 227 significant colocalization regions, involving 120 variants and 145 distinct genes. Functional evaluation of these genes through ontology enrichment revealed pathways linked to neuroinflammation, immune dysfunction, and cellular homeostasis mechanisms, reinforcing their relevance in MDD etiopathogenesis. Notably, a significant proportion of colocalization findings in blood eQTLs concentrated in the Major Histocompatibility Complex (MHC) region. Furthermore, genes with previously documented associations with MDD and other neuropsychiatric disorders, as well as new candidates, were found. The analysis also highlighted the effectiveness of colocalization in identifying potential drug targets, with 37 genes found to interact with approved or in-progress drugs, including some used for mood disorders. In summary, this work demonstrates the efficacy of multi-trait analysis and the Causeway pipeline in discovering and characterizing new genetic markers and effector genes for MDD. The findings provide valuable insights into the biology of depression, emphasizing the role of inflammation and cellular homeostasis, and open new avenues for investigating therapeutic targets and the development of more precise and personalized interventions.