A Novel Test for Detecting SNP-SNP Interactions in Case-Only Trio Studies

Area of Science:

• Genetics
• Statistical genetics
• Bioinformatics

Background:

• Epistasis, or gene-gene interaction, is crucial for complex traits but difficult to detect in human studies due to statistical challenges.
• Existing genome-wide epistasis tests face a multiple-hypothesis burden, limiting their power and replication in human populations.

Purpose of the Study:

• To develop a novel, powerful statistical test for detecting single nucleotide polymorphism-single nucleotide polymorphism (SNP-SNP) interactions in case-only trio studies.
• To address the limitations of current methods in identifying epistatic effects in complex human diseases.

Main Methods:

• Introduced the trio correlation (TC) test, which calculates the joint distribution of marker pairs in offspring conditional on parental genotypes.
• Integrated this distribution into a standard 1 degree-of-freedom correlation test for interaction analysis.
• Utilized extensive simulations across various disease models to evaluate test performance.

Main Results:

• The TC test demonstrated substantially superior performance compared to existing interaction tests in case-only trio studies.
• Identified and explained a bias present in a previously used case-only trio interaction test.
• Confirmed that a proposed permutation scheme effectively mitigates population stratification biases in trio studies.

Conclusions:

• The TC test offers improved power for detecting epistasis in both current and future trio association studies.
• This method provides a valuable tool for unraveling the genetic architecture of complex human phenotypes.
• The TC test is publicly available, facilitating its adoption in genetic research.