[Linkage analysis for complex diseases: a new life for an old method].

Area of Science:

• Genetics
• Human Disease Gene Mapping
• Statistical Genetics

Background:

• Complex human diseases involve multiple genes and environmental factors, making gene mapping challenging.
• Traditional linkage analysis methods require a predefined genetic model, which is often unknown for complex diseases.

Purpose of the Study:

• To present and compare the main approaches for gene mapping of complex human diseases using linkage analysis.
• To evaluate the utility and performance of traditional LOD-score analysis versus non-parametric linkage methods.

Main Methods:

• Review of traditional LOD-score analysis with refinements for complicating factors (incomplete penetrance, heterogeneity, unknown inheritance).
• Description and comparison of three main non-parametric linkage analysis approaches (model-free methods).
• Comparative analysis of LOD-score and non-parametric methods based on recent publications.

Main Results:

• Non-parametric methods are often considered more appropriate for complex diseases due to their model-free nature.
• LOD-score analysis, despite perceived limitations, remains a useful tool.
• In specific circumstances, LOD-score analysis can offer greater power and precision than model-free methods.

Conclusions:

• Both LOD-score and non-parametric methods have distinct advantages and drawbacks for complex disease gene mapping.
• The choice of method depends on the specific genetic factors and available data.
• LOD-score analysis should not be disregarded for complex disease studies and can be advantageous in certain scenarios.