Linkage analysis versus association analysis: distinguishing between two models that explain disease-marker...

Area of Science:

• Human Genetics
• Genetic Epidemiology
• Statistical Genetics

Background:

• Weak-to-moderate associations between genetic markers and diseases are common but poorly understood.
• Distinguishing the causes of these associations is critical for advancing human disease genetics research.
• Current association studies often complement or replace traditional linkage studies for complex diseases.

Purpose of the Study:

• To formulate and differentiate between linkage disequilibrium and susceptibility models for weak-to-moderate disease-marker associations.
• To evaluate existing family-based association tests and their ability to distinguish between these models.
• To propose novel linkage-based approaches for differentiating between the two association models.

Main Methods:

• Development of two distinct models: linkage disequilibrium and susceptibility.
• Analysis of two family-based association tests (Parsian et al. and Spielman et al.) under both models.
• Proposal and derivation of formulas for two linkage analysis-based methods to distinguish between models.

Main Results:

• Existing family-based association tests cannot differentiate between linkage disequilibrium and susceptibility models.
• Formulas characterizing the behavior of these tests under weak-to-moderate associations were derived.
• Two novel approaches, including a partitioned association-linkage (PAL) test, were proposed to distinguish the models.

Conclusions:

• A clear distinction between linkage disequilibrium and susceptibility models is essential for interpreting disease genetics.
• Family-based association tests confirm association but not its underlying cause.
• Linkage analysis offers robust methods to differentiate true linkage from pure association in genetic studies.