A pathway-centric approach to rare variant association analysis

Area of Science:

• Genomics
• Statistical Genetics
• Systems Biology

Background:

• Rare variant analysis often lacks statistical power for individual genes.
• Conventional methods are limited to coding regions, excluding intronic variants.
• Biological pathway information can contextualize gene function.

Purpose of the Study:

• To develop an enhanced rare variant analysis method incorporating pathway information and broader functional annotations.
• To investigate the association of rare variants within the arginine and proline metabolism pathway with systolic blood pressure.
• To demonstrate the advantage of pathway-based analysis over single-gene approaches.

Main Methods:

• Utilized whole-genome sequencing data from the UK10K project.
• Incorporated functional annotations from the Combined Annotation Dependent Depletion (CADD) tool for intronic variants.
• Applied the optimal sequence kernel association test (SKAT) to analyze variants within the KEGG arginine and proline metabolism pathway.
• Replicated findings using imputed data from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort.

Main Results:

• A significant association was found between rare variants in the arginine and proline metabolism pathway and systolic blood pressure (P=3.32x10^-5).
• This association was successfully replicated in an independent cohort (P=0.02).
• Individual gene analyses within the pathway showed diminished statistical significance, highlighting the power of the pathway-based approach.

Conclusions:

• Pathway-based rare variant analysis, integrating functional annotations like CADD, enhances the detection of complex disease associations.
• The arginine and proline metabolism pathway is implicated in systolic blood pressure regulation.
• Future studies should leverage pathway-centric approaches to unravel the genetic architecture of complex traits.