Polygenic Score for Heart Failure Beta-Blocker Response
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Solution Overview
Problem
Current methods for identifying patients who will benefit from beta-blocker treatment in heart failure are inconsistent and lack clinically actionable genetic markers, leading to a 'one size fits all' approach that does not account for individual genetic variations, resulting in variable treatment responses.
Innovation Solution
A polygenic response predictor (PRP) score is developed using a genome-wide analysis of beta-blocker genotype interactions to predict time to all-cause mortality, incorporating a MAGGIC score, beta-blocker exposure, and propensity score, identifying relevant SNPs to determine a patient's likelihood of responding to beta-blocker treatment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a one size fits all approach is used for beta-blocker treatment in heart failure patients, then treatment coverage is maximized, but individual treatment efficacy varies significantly
Solution Approach 1:
The patent segments the heart failure patient population into distinct genetic subgroups based on polygenic risk scores. By dividing patients into those with high vs. low PRP scores, the treatment approach moves from a uniform strategy to a segmented one where beta-blockers are targeted to specific genetic subgroups, thereby improving both adaptability and response consistency.
Solution Approach 2:
The patent applies local quality by tailoring treatment recommendations to specific genetic characteristics of individual patients. Rather than applying the same treatment uniformly, the approach adjusts treatment intensity and recommendations based on each patient's local genetic profile as captured by their PRP score, improving treatment personalization and efficacy.
2Measurement precision
If individual SNP analysis is used to predict beta-blocker response, then genetic precision is improved, but clinical utility is limited due to inconsistency
Solution Approach 1:
The patent merges multiple individual SNP analyses into a unified polygenic risk score. By combining the effects of numerous SNPs into a single PRP metric, the approach maintains the precision of genetic measurement while producing a clinically actionable score that can be directly used to guide treatment decisions, thereby resolving the contradiction between precision and utility.
Solution Approach 2:
The polygenic risk score functions as a composite genetic marker, integrating information from multiple SNPs into a single predictive metric. This composite approach maintains the precision of individual SNP analysis while improving clinical actionability by providing a unified, interpretable score that reflects overall genetic predisposition to beta-blocker response.
3Quantity of substance
If genome-wide analysis is conducted to identify polygenic markers, then comprehensive genetic coverage is achieved, but analysis complexity increases
Solution Approach 1:
The patent extracts the essential predictive information from comprehensive genome-wide data by focusing on a specific set of SNPs that contribute to the polygenic risk score. Rather than analyzing all genetic variants equally, the method extracts and weights only those SNPs that are most relevant to beta-blocker response, maintaining comprehensive genetic coverage while simplifying the analysis methodology.
Data Source
AI summary
The present disclosure provides methods for creation, validation and application of a polygenic response predictor (PRP) score which can identify and/or predict beta-blocker survival benefit in heart failure. In one aspect, provided herein are systems and methods for identifying, diagnosing, and treating heart failure patients of European descent who are likely to respond to beta-blocker treatment.