Global transmission/disequilibrium tests based on haplotype sharing in multiple candidate genes

Area of Science:

• Genetics
• Biostatistics
• Genomic Medicine

Background:

• Complex diseases often involve multiple genes, making single-gene studies insufficient for identifying low-effect susceptibility genes.
• High-density genomic markers necessitate advanced statistical approaches for collective gene analysis.

Purpose of the Study:

• To develop novel statistical methods for jointly analyzing multiple candidate genes (linked or unlinked) in complex disease susceptibility.
• To enhance the power of detecting disease-associated genes, particularly those with small effect sizes.

Main Methods:

• Proposed a class of Transmission Disequilibrium Test (TDT)-type methods for joint haplotype analysis across multiple genes.
• Utilized a linear signed rank statistic to compare transmitted and non-transmitted haplotypes at the individual gene level.
• Combined gene-level statistics into global statistics for simultaneous association testing of gene sets.

Main Results:

• Simulation studies confirmed correct type I error rates in stratified populations.
• The proposed global tests demonstrated increased power compared to gene-by-gene tests when all candidate genes contribute to the disease.
• The methods effectively assess the collective effect of multiple genes on disease susceptibility.

Conclusions:

• The developed statistical framework offers a powerful approach for identifying complex disease susceptibility genes.
• Jointly analyzing multiple genes collectively improves the detection of genes with small effect sizes.
• These methods are valuable for genomic association studies aiming to unravel the genetic architecture of complex diseases.