Hypercholesterolemia Classification via Polygenic Risk and LDL Distributions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for identifying and classifying severe hypercholesterolemia are inadequate, as they fail to distinguish between monogenic and polygenic forms, leading to misclassification and inappropriate treatment.
Innovation Solution
A computer-implemented method for determining a hypercholesterolemic profile by obtaining statistical distributions of polygenic risk scores and LDL cholesterol concentrations for both mutated and non-mutated individuals, allowing for classification into specific hereditary categories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If clinico-biological criteria (DLCN) are used for identifying FH patients, then screening can be performed with simple criteria, but misclassification occurs between monogenic and polygenic forms
Solution Approach 1:
The patent segments the homogeneous group of severe hypercholesterolemia patients into distinct subgroups based on genetic mutation status (monogenic vs. polygenic forms). By creating separate statistical distributions for mutated and non-mutated individuals, the method enables precise classification while maintaining operational simplicity through standardized screening protocols.
Solution Approach 2:
The patent introduces new parameters (polygenic risk score thresholds, decile-based LDLc classifications) to differentiate between monogenic and polygenic forms. By changing the classification parameters from simple clinical criteria to genetically-informed statistical distributions, the method achieves both operational simplicity and classification precision.
2Ease of operation
If a single threshold (LDLc > 1.9 gL-1) is used for severe hypercholesterolemia, then screening is straightforward, but the majority of cases are misclassified as non-monogenic
Solution Approach 1:
The patent adds a new dimension to the classification system by introducing polygenic risk score analysis alongside LDLc thresholds. Instead of relying solely on the single dimension of LDLc concentration, the method incorporates genetic risk assessment to recover lost etiological information while maintaining the simplicity of threshold-based screening.
Solution Approach 2:
The patent uses statistical distributions and polygenic risk scores as intermediary tools to bridge the gap between simple threshold screening and accurate etiological classification. These intermediaries enable the system to maintain operational simplicity while preventing information loss about the underlying genetic causes.
3Productivity
If genetic screening is performed without differentiated classification, then all severe cases are treated uniformly, but personalized treatment approaches cannot be implemented
Solution Approach 1:
The patent segments patients into distinct categories (monogenic FH, polygenic hypercholesterolemia, intermediate forms) based on their genetic profiles and statistical distributions. This segmentation enables personalized treatment approaches for each subgroup while maintaining efficient screening processes through standardized entry criteria.
Solution Approach 2:
The patent applies different treatment and management strategies tailored to each classified subgroup. By recognizing that monogenic and polygenic forms have different etiologies and risk profiles, the method enables local quality improvements in treatment personalization while maintaining overall screening efficiency.
Data Source
Figure 1A
Figure 1B~3
Figure 2
AI summary
A hypercholesterolemic profile of a patient is determined on the basis of (i) a first statistical distribution based on a scale of polygenic risk score levels and a scale of cholesterol concentration levels in low-density lipoproteins, the first statistical distribution giving, based on these scales, a distribution of individuals in a first sub-sample of severely hypercholesterolemic individuals having at least one genetic mutation causing hypercholesterolemia for at least one gene from a set of genes and (ii) a second statistical distribution based on the same scale of polygenic risk score levels and the same scale of cholesterol concentration levels in low-density lipoproteins,the second statistical distribution giving, as a function of these scales, a distribution of individuals from a second sub-sample of severely hypercholesterolemic individuals not presenting a genetic mutation in the set of genes;