A powerful association test for qualitative traits incorporating imprinting effects using general pedigree data

Area of Science:

• Genetics
• Statistical Genetics
• Bioinformatics

Background:

• Pedigree Disequilibrium Test (PDT) and its extension (MCPDT) are powerful for genetic association studies but do not account for imprinting effects.
• Existing imprinting-aware methods like TDTI* are limited to small, two-generation families, unsuitable for extended pedigrees.

Purpose of the Study:

• To extend PDT to incorporate imprinting effects for association analysis in complete pedigrees (PDTI).
• To develop a method (MCPDTI) for handling missing genotypes in extended pedigrees with imprinting effects using Monte Carlo sampling.

Main Methods:

• Developed PDTI statistic for complete pedigrees, extending PDT to include imprinting information.
• Developed MCPDTI statistic using Monte Carlo sampling and estimation to handle missing genotypes in extended pedigrees.
• Both methods utilize a two-stage framework for statistical analysis.

Main Results:

• Simulations confirmed that PDTI and MCPDTI effectively control type I error rates under the null hypothesis.
• PDTI and MCPDTI demonstrated superior power compared to PDT and TDTI* when imprinting effects are present.
• The proposed methods are suitable for analyzing extended pedigrees, including those with missing genotype data.

Conclusions:

• PDTI and MCPDTI are powerful and robust statistical methods for genetic association studies incorporating imprinting effects.
• These methods enhance the analysis of complex pedigrees, offering improved power and flexibility over existing approaches.
• The developed statistics provide valuable tools for identifying disease-associated variants influenced by imprinting in large family studies.