The omnigenic model and polygenic prediction of complex traits

Area of Science:

• Genetics
• Evolutionary Biology
• Bioinformatics

Background:

• Genome-wide association studies (GWASs) reveal complex traits have a highly polygenic architecture.
• The omnigenic model provides a framework to understand this polygenic nature.
• Recent observations show low transferability of polygenic scores and limited evidence for polygenic selection across populations.

Purpose of the Study:

• To argue that the omnigenic model explains cross-population genetic effects.
• To explore the implications of the omnigenic model for the interpretation and use of GWAS summary statistics and polygenic scores.
• To discuss the challenges in detecting polygenic selection and interpreting polygenic scores without explicit genetic architecture models.

Main Methods:

• Conceptual analysis and theoretical argumentation based on existing literature and data.
• Application of the omnigenic model to explain observed phenomena in population genetics.
• Discussion of the consequences for evolutionary and clinical genetics.

Main Results:

• The omnigenic model explains the low transferability of polygenic scores across populations.
• It clarifies why most GWAS variants exhibit varying effects between populations.
• It suggests that most GWAS associations may not be robust clinical targets due to population-specific effects.

Conclusions:

• The omnigenic model offers a unifying explanation for cross-population genetic effects observed in GWASs.
• Polygenic scores may have limited applicability outside their discovery populations.
• Interpreting the clinical and evolutionary significance of polygenic scores requires explicit consideration of genetic architecture and population context.