The future of association studies: gene-based analysis and replication

Area of Science:

• Genetics and Genomics
• Statistical Genetics
• Disease Etiology Research

Background:

• Traditional genetic association studies focused on single variants (alleles) or haplotypes.
• Increasing marker density and linkage disequilibrium analysis have shifted focus to haplotypic levels.
• Replication of findings at the single-nucleotide-polymorphism (SNP) or haplotype level presents challenges.

Purpose of the Study:

• To propose a shift from SNP or haplotype-based association testing to a comprehensive gene-based approach.
• To address inconsistencies in association findings arising from population differences.
• To enhance the reliability and interpretability of genetic association studies.

Main Methods:

• Consideration of all common genetic variations within a candidate gene jointly.
• Utilizing a gene-based approach to resolve population-specific inconsistencies.
• Application of genewide significance levels to account for multiple testing.
• Formalization of meta-analysis procedures through the combination of P-values for gene-based methods.

Main Results:

• The gene-based approach offers a more robust method for resolving population differences compared to SNP or haplotype approaches.
• This method captures all potential risk-conferring variations within a gene, simplifying interpretation of negative findings.
• Genewide significance levels provide a straightforward way to manage chance findings from multiple testing.

Conclusions:

• A gene-based approach is proposed as the future standard for genetic association analysis.
• This comprehensive method will facilitate the identification of functional variants contributing to disease etiology.
• As whole-gene variation mapping becomes complete, the gene-based approach will be the natural endpoint for association studies.