Pathway-Level Polygenic Risk Scoring for Precision Treatment
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Solution Overview
Problem
Current genome-wide polygenic risk scoring methods lack biological salience and fail to provide specific information for designing precision treatment strategies for complex disorders, despite revealing insights into their genetic architecture.
Innovation Solution
A method that quantifies common variant enrichment in biological pathways with known drug targets to identify pharmacologically relevant pathways, using gene set association analysis and predictive polygenic scores to select therapeutic agents for treatment or prevention of complex disorders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If genome-wide polygenic risk scoring is used to identify genetic variants associated with complex disorders, then the quantity of genetic information available for therapeutic intervention increases, but the biological salience and clinical utility of this information decreases due to the small effect size and heterogeneity of individual variants
Solution Approach 1:
The patent combines multiple individual genetic variants into pathway-level polygenic risk scores by aggregating effect sizes of variants within biologically relevant pathways. This merging approach transforms numerous small-effect variants into consolidated pathway scores that capture cumulative genetic risk while maintaining biological interpretability, thereby resolving the contradiction between quantity of genetic information and biological salience
Solution Approach 2:
The patent introduces biological pathways as intermediary structures between individual genetic variants and clinical phenotypes. By mapping variants to pathways and calculating pathway-level risk scores, the methodology creates an intermediate representation that preserves biological context and enhances clinical utility, bridging the gap between raw genetic data and actionable therapeutic insights
2Reliability
If strict genome-wide significance thresholds are applied to identify genetic variants, then the reliability of individual variant associations increases, but the polygenicity captured decreases, limiting the utility for precision treatment strategies
Solution Approach 1:
The patent applies partial action by implementing multiple filtering stages with progressively relaxed thresholds. Initial strict genome-wide significance thresholds (P<5×10^-8) ensure high reliability for core variants, while subsequent relaxed thresholds (P<10^-5, P<10^-3) capture additional polygenic signal. This staged approach balances reliability and polygenicity capture by retaining only those variants that meet appropriate significance criteria at each filtering level
Solution Approach 2:
The patent changes the parameter of significance thresholds dynamically across different analysis stages and pathway contexts. By adjusting P-value thresholds based on pathway-specific characteristics and cumulative evidence, the methodology optimizes the balance between maintaining association reliability and capturing sufficient polygenicity for precision treatment applications
Data Source
AI summary
Disclosed herein are methods for treating complex disorders in human subjects and for preventing complex disorders in human subjects at risk of developing the disorder, including identifying one or more pharmacologically relevant biological pathways associated with a complex disorder and selecting an agent suitable for the treatment or prevention of the complex disorder. As described herein, the quantification of common variant enrichment in biological pathways with known drug targets provides a means of functionally annotating genome-wide polygenic risk scoring, which provides an indication of an individual's exposure to risk variants that are potentially treatable using existing pharmaceutical agents, dietary supplements or lifestyle interventions.