The gene expression landscape of disease genes

Area of Science:

• Genomics
• Systems Biology
• Translational Medicine

Background:

• Genome-wide association studies (GWAS) identify numerous disease-associated genes.
• Previous methods relied on expression enrichment, limiting direct causal inference.
• This study utilizes high-confidence causal gene lists for a more direct approach.

Purpose of the Study:

• To determine the specific tissues and cell types where disease-associated genes operate.
• To identify novel tissue-disease associations.
• To provide insights for drug development.

Main Methods:

• Integrated GWAS summary statistics, gene prioritization results, and RNA-sequencing data from 46 tissues and 204 cell types.
• Analyzed gene expression of putative disease genes across various tissues and cell types.
• Correlated gene expression patterns with 11 major diseases and cancers.

Main Results:

• Disease genes exhibited higher and more specific expression in relevant tissues/cell types compared to controls.
• Identified elevated gene expression in tissues/cell types not previously linked to specific diseases.
• Highlighted tissue-disease pairs associated with increased drug development potential.

Conclusions:

• Developed an open-source framework for systematic disease gene and tissue analysis.
• Framework offers novel insights into disease mechanisms and potential therapeutic targets.
• Findings can inform drug development and delivery strategies.