A robust score test for linkage disequilibrium in general pedigrees

Area of Science:

• Genetics
• Statistical genetics
• Bioinformatics

Background:

• Traditional family-based linkage disequilibrium tests have limitations with complex pedigrees and multiple case families.
• The Pedigree Disequilibrium Test (PDT) was developed to address these limitations.
• There is a need for methods that can incorporate covariates into family-based association analyses.

Purpose of the Study:

• To extend the Pedigree Disequilibrium Test (PDT) to incorporate measured covariates.
• To evaluate the performance of the extended PDT (ePDT) in detecting associations between genetic variants and disease.
• To assess the impact of environmental factors on association analyses using the ePDT.

Main Methods:

• An extension of the PDT was developed using conditional logistic regression.
• The ePDT was applied to simulated population-isolate data, testing associations with functional and inert single nucleotide polymorphisms (SNPs).
• The method was used to test for linkage disequilibrium after correcting for an environmental factor (E1).

Main Results:

• The ePDT demonstrated high power (100%) for detecting association with a functional SNP on gene 1.
• The ePDT showed moderate power (approximately 50%) for a functional SNP on gene 6.
• Both PDT and ePDT maintained appropriate type I error rates for an inert SNP.
• Correcting for environmental factor E1 slightly improved the power to detect the association with gene 6.

Conclusions:

• The conditional logistic regression extension of the PDT is a valid and powerful method for family-based association studies with covariates.
• The ePDT effectively identifies disease-associated SNPs in complex family structures.
• Accounting for environmental factors can enhance the power of genetic association analyses.