Methods to evaluate rare variants gene-age interaction for triglycerides.

Area of Science:

• Genetics
• Biostatistics
• Cardiovascular Health

Background:

• Triglycerides are key heart health indicators, but genetics explain limited lipid level variance.
• Gene-environment interactions, like with age, may influence lipid levels.
• Existing rare variant interaction tests struggle with main genetic effects.

Purpose of the Study:

• To develop novel statistical methods for testing gene-environment interactions of rare variants.
• To improve power and interpretability by grouping single-nucleotide polymorphisms (SNPs) into SNP-sets.
• To address limitations of existing methods when main genetic effects are present.

Main Methods:

• Introduced two methods: testing of optimally weighted combination of SNP environment interaction (TOW-SE) and variable weight TOW-SE (VW-TOW-SE).
• Grouped SNPs into biologically meaningful sets (genes or pathways).
• Validated methods using simulations for various environmental and outcome types.

Main Results:

• Proposed methods demonstrated controlled Type I error rates in simulations.
• VW-TOW-SE showed the highest power, followed by TOW-SE, outperforming iSKAT for gene-environment interactions.
• Application to GAW20 simulated data yielded no positive results in regions without simulated gene-age interaction.

Conclusions:

• TOW-SE and VW-TOW-SE are effective and powerful tools for analyzing rare variant gene-environment interactions.
• These methods offer advantages in power and interpretability over existing approaches.
• The developed methods contribute to a better understanding of genetic and environmental influences on lipid levels.