Demographic-Based Polygenic Model Selection for Trait Prediction
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Solution Overview
Problem
The complexity of associating specific phenotypic traits with genetic variants is challenging due to the vast amount of genomic data and the presence of non-coding regions, leading to inaccurate predictions and the need for enhanced systems to identify relevant genetic correlations.
Innovation Solution
A polygenic prediction system that dynamically selects a polygenic model based on an individual's demographics, using a set of models each performing different analyses of genetic variants to improve prediction accuracy for characteristics like height, weight, and eye color.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If generic polygenic models are used to predict traits, then the system is simple and easy to operate, but the prediction accuracy decreases
Solution Approach 1:
The patent segments the polygenic model selection process into distinct components: demographic data collection, model candidate identification, accuracy metric calculation, and model selection. This segmentation allows the system to manage complexity through structured workflows while maintaining high prediction accuracy through demographic-specific modeling
Solution Approach 2:
The patent performs preliminary actions by pre-calculating accuracy metrics for multiple polygenic models across different demographic groups before actual trait prediction. This pre-computation enables rapid model selection during inference without compromising prediction accuracy, resolving the contradiction between accuracy and operational complexity
2Measurement precision
If multiple polygenic models are maintained for different demographics, then prediction accuracy for specific traits improves, but the quantity of data and model storage increases
Solution Approach 1:
The patent applies local quality by maintaining different polygenic models tailored to specific demographic characteristics (e.g., ancestry, age, sex) rather than using a single universal model. Each demographic group receives a model optimized for its specific genetic and phenotypic characteristics, improving prediction accuracy while storing only the necessary subset of models for the population being served
Solution Approach 2:
The patent changes the parameter of model selection based on demographic inputs. By dynamically selecting which polygenic model to apply based on the individual's demographic profile, the system maintains high prediction accuracy across diverse populations without needing to store and process all possible models simultaneously, thus managing data volume efficiently
3Reliability
If demographic-specific polygenic models are selected, then the reliability of predictions for specific populations improves, but the complexity of model selection increases
Solution Approach 1:
The patent implements a dynamic model selection process that automatically adapts to the demographic characteristics of each individual. The system dynamically determines which polygenic model to apply based on real-time demographic input, ensuring reliable predictions for specific populations while managing selection complexity through automated demographic-based routing logic
Data Source
AI summary
Systems and methods are provided for selecting from among polygenic models that predict characteristics of individuals. One embodiment is a genetic prediction server that includes a memory that stores polygenic models which predict characteristics of individuals based on genetic variants of the individuals, including a set of polygenic models for a characteristic that each perform a different analysis of genetic variants when making a prediction. The server also includes a controller that receives an indication of genetic variants of an individual, determines that the individual belongs to a demographic, and selects, based on the demographic, a polygenic model from the set to predict the characteristic for the individual.