Cross-variant polygenic risk modeling for genetic sequence analysis

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing polygenic predictive data analysis systems face challenges in accuracy and reliability due to their inability to effectively map relationships between genetic sequences and medical conditions, particularly when individual genetic variant interactions are not statistically significant, and they require resource-intensive statistical operations.

Innovation Solution

The use of cross-variant polygenic risk modeling that generates per-variant genetic risk scores and risk profiles, allowing for more precise predictive analysis by independently describing correlations between genetic variants and medical conditions, reducing the need for resource-intensive operations through log of odds ratios and efficient data processing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional polygenic predictive data analysis systems are used, then comprehensive genetic analysis can be performed, but accuracy and reliability deteriorate due to inability to effectively map relationships between genetic sequences and medical conditions

Engineering Contradiction:

Improveaccuracy of predictive analysisVSAvoidcomplexity of mapping genetic sequences to medical conditions

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the complex genetic analysis by creating separate per-variant genetic risk scores for individual genetic variants, then combining them into composite genetic risk profiles. This segmentation allows independent modeling of each variant's contribution while maintaining overall predictive accuracy, resolving the contradiction between reliability and complexity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces per-variant genetic risk scores as intermediary elements between raw genetic sequence data and final medical condition predictions. These intermediate scores serve as mediators that simplify the mapping process while improving reliability by capturing individual variant contributions before aggregation into final predictions.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If traditional statistical operations are used for polygenic analysis, then comprehensive genetic variant interactions can be analyzed, but resource consumption increases due to requirement of resource-intensive statistical operations

Engineering Contradiction:

Improveprecision of genetic variant interaction analysisVSAvoidcomputational resource consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent divides the computational workload into separate per-variant risk score calculations that can be independently computed and then aggregated. This segmentation reduces resource consumption by avoiding the need for comprehensive statistical operations on all variant interactions simultaneously, while maintaining measurement precision through systematic combination of individual variant scores.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent focuses computational resources on calculating per-variant genetic risk scores for individually significant variants rather than performing exhaustive statistical operations on all possible variant interactions. This partial action approach maintains sufficient measurement precision while dramatically reducing computational resource consumption.

Inventive Principle:

Principle #16Partial or excessive action

3Measurement precision

If individual genetic variant correlations are modeled independently, then predictive accuracy improves through precise mapping, but the number of required genetic variants increases

Engineering Contradiction:

Improveprecision of genetic variant correlation mappingVSAvoidnumber of genetic variants to be modeled

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

The patent merges individual per-variant genetic risk scores into composite genetic risk profiles that aggregate multiple variant contributions. This combining approach maintains measurement precision by preserving individual variant correlations while reducing the effective number of variants that need to be modeled independently, as variants with similar patterns can be grouped together in the same risk profile.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS11574738B2Cross-variant polygenic predictive data analysis

Publication Date: 2023.02.07 OPTUM SERVICES IRELAND LTD

AI summary

There is a need for more effective and efficient predictive data analysis solutions for processing genetic sequencing data. This need can be addressed by, for example, techniques for performing predictive data analysis based on genetic sequences that utilize at least one of cross-variant polygenic risk modeling using genetic risk profiles, cross-variant polygenic risk modeling using functional genetic risk profiles, per-condition polygenic clustering operations, cross-condition polygenic predictive inferences, and cross-condition polygenic diagnoses.