Integrative Post-Genome-Wide Association Study Analyses Relevant to Psychiatric Disorders: Imputing Transcriptome and...

Area of Science:

• Genetics
• Bioinformatics
• Psychiatric Research

Background:

• Genome-wide association studies (GWAS) identify genetic variants linked to complex traits, including psychiatric disorders (PDs).
• Post-GWAS analyses are crucial for connecting statistical findings to biological entities like genes, proteins, and pathways.
• Methods incorporating molecular phenotypes (gene expression, protein abundance) mediate variant-trait associations.

Purpose of the Study:

• To review recent advancements in Transcriptome-wide association studies (TWAS) and Proteome-wide association studies (PWAS).
• To highlight the utility of TWAS and PWAS in identifying causal genes for psychiatric disorders.
• To recommend specific tools for researchers conducting these post-GWAS analyses.

Main Methods:

• TWAS and PWAS integrate omic data with GWAS summary statistics.
• These methods impute transcript/protein data and test associations with phenotypes using GWAS data and reference omic datasets.
• Summary Mendelian Randomization (SMR) is recommended for its versatility in performing both TWAS and PWAS.

Main Results:

• TWAS and PWAS are effective for primary association scans and fine-mapping of potentially causal genes in PDs.
• Prioritized genes from TWAS/PWAS can serve as targets for novel drug development.
• SMR is recommended due to its ability to use the same tool for TWAS/PWAS, its independence from pre-computed weights, and compatibility with public transcriptome data.

Conclusions:

• TWAS and PWAS are powerful post-GWAS analytical tools for psychiatric disorder research.
• These methods facilitate the identification of biologically relevant genes underlying complex traits.
• Mendelian randomization tools like SMR offer a practical and efficient approach for TWAS and PWAS analyses.