From genetic associations to genes: methods, applications, and challenges.

Area of Science:

• Genetics and Genomics
• Bioinformatics
• Translational Medicine

Background:

• Genome-wide association studies (GWASs) identify genetic loci linked to human traits and diseases.
• A significant challenge is pinpointing causal genes within these loci, hindering biological interpretation and medical applications.

Purpose of the Study:

• To provide a comprehensive review of methods and technologies for prioritizing genes from GWAS loci.
• To discuss strategies for generating and applying context-dependent molecular quantitative trait loci (xQTL) data.
• To highlight the role of gene prioritization in drug repurposing and future research directions.

Main Methods:

• Gene-based association tests.
• Integrative analysis of GWAS and molecular quantitative trait loci (xQTL) data.
• Enhancer-gene connection mapping and network-based prioritization.

Main Results:

• Overview of established and emerging gene prioritization techniques.
• Strategies for leveraging context-specific xQTL data.
• Potential applications of gene prioritization in identifying novel drug targets and repurposing existing medications.

Conclusions:

• Effective gene prioritization is essential for translating GWAS findings into actionable biological insights and clinical applications.
• Advancements in integrative omics and network analysis offer powerful tools for causal gene identification.
• Gene prioritization holds significant promise for accelerating drug discovery and development.