A haplotype-based framework for group-wise transmission/disequilibrium tests for rare variant association analysis

Area of Science:

• Human genetics
• Statistical genetics
• Complex disease association studies

Background:

• Identifying rare variants linked to complex diseases is a key goal in human genetics.
• Rare variants pose challenges in association studies due to reduced detection power and difficulties in controlling for population stratification.
• Family-based Transmission/Disequilibrium Tests (TDT) are robust to population stratification, making them suitable for rare variant association studies.

Purpose of the Study:

• To develop a flexible framework for group-wise TDT (gTDT) to enhance rare variant association analysis.
• To incorporate various genetic models, including additive, dominant, and compound heterozygous (recessive) models, into TDT.
• To improve the power of rare variant association studies compared to single-marker TDT.

Main Methods:

• Developed a haplotype-based framework for group-wise TDT (gTDT).
• gTDT constructs haplotypes by transmission, accounting for linkage disequilibrium.
• Implemented gTDT in C++ with source code available online.

Main Results:

• Simulations demonstrated that gTDT correctly controls Type I error rates for rare variants, even with population stratification.
• gTDT showed increased statistical power across various genetic models compared to single-marker TDT.
• Application to autism exome sequencing data identified candidate genes with compound heterozygous rare variants.

Conclusions:

• gTDT provides a powerful and flexible approach for rare variant association studies in families.
• The method effectively controls for population stratification and enhances the detection of disease-associated rare variants.
• gTDT is a valuable tool for analyzing complex genetic data, particularly for identifying compound heterozygous rare variants.