Finding the Sources of Missing Heritability within Rare Variants Through Simulation.

Area of Science:

• Genetics
• Genomics
• Statistical Genetics

Background:

• Genome-wide association studies (GWAS) identify genetic variants for complex disorders but explain limited phenotypic variance.
• A significant portion of heritability for many disorders remains unexplained, termed "missing heritability".

Purpose of the Study:

• To investigate the impact of rare variants on the "missing heritability" problem.
• To simulate how the distribution of causal rare variants affects the detection of genetic associations with quantitative traits.

Main Methods:

• Simulated a causality scenario where rare variants influence gestational ages.
• Embedded 1000 simulated causal rare variants into promoter regions of 1000 Genomes Project data.
• Analyzed correlations between rare variant aggregations and gestational ages under varying proportions of causal variants.

Main Results:

• Genetic association signals weakened as the proportion of causal rare variants decreased.
• No individual promoter regions showed significant genetic association when the causal rare variant proportion was below 0.4.
• Dispersed and sparse distribution of causal rare variants dilutes association signals.

Conclusions:

• Rare variants, particularly when sparsely distributed, are a significant contributor to "missing heritability".
• Current GWAS methods may fail to detect associations due to the diluted signals from dispersed rare variants.
• Understanding rare variant distribution is crucial for advancing complex trait genetics.