InTACT: An adaptive and powerful framework for joint-tissue transcriptome-wide association studies

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Transcriptome-wide association studies (TWAS) integrate gene expression and genome-wide association studies (GWAS) for complex trait gene discovery.
• Current TWAS methods can lose power by not accounting for correlated gene expression across tissues.

Purpose of the Study:

• To develop a computationally efficient method, Integrative Test for Associations via Cauchy Transformation (InTACT), to enhance gene discovery by leveraging multi-tissue expression data.
• To improve the power of identifying genes associated with complex traits.

Main Methods:

• InTACT combines gene association information across multiple tissues using a Cauchy transformation.
• The method was evaluated using simulations to assess power and Type 1 error rates.
• InTACT was applied to a large Alzheimer's disease GWAS dataset.

Main Results:

• Simulations confirmed InTACT's high power and accurate control of Type 1 error rates.
• Application to Alzheimer's disease GWAS identified 227 genome-wide significant genes.
• 130 genes identified by InTACT were missed by benchmark methods (TWAS, MultiXcan).
• Five novel Alzheimer's disease loci were discovered using InTACT.

Conclusions:

• InTACT is a powerful and efficient method for gene discovery in complex traits by integrating multi-tissue expression data.
• The developed software "InTACT" is publicly available for research use.
• InTACT significantly advances the identification of candidate genes and novel loci for diseases like Alzheimer's.