Rare variant association analysis in case-parents studies by allowing for missing parental genotypes

Area of Science:

• Genetics
• Bioinformatics
• Statistical Genetics

Background:

• Next-generation sequencing enables rare variant identification.
• Family-based designs, like case-parent studies, control for population structure in rare variant analysis.
• Existing methods for case-parent studies require complete parental genotype data, risking power loss.

Purpose of the Study:

• To develop and evaluate methods for rare variant-disease association analysis in case-parent studies that accommodate missing parental genotypes.
• To improve statistical power in rare variant association studies by utilizing incomplete family data.

Main Methods:

• Extended the collapsing method to include case-parent trios with missing parental genotypes.
• Investigated two methods using genotype differences between affected offspring and their complements within a Transmission Disequilibrium Test (TDT) framework.
• Employed simulations to assess method performance.

Main Results:

• The proposed strategy, allowing for missing parental genotypes, significantly improves statistical power compared to methods using only complete data.
• Incorporating incomplete family data or even unrelated affected individuals enhances power without introducing bias from population stratification.
• The developed methods demonstrate increased power for rare variant-disease association analysis.

Conclusions:

• Including case-parent data with missing parental genotypes substantially boosts the power of rare variant-disease association strategies.
• The developed methods offer a robust approach to rare variant association analysis, particularly when dealing with incomplete family data.