Genetic Risk Scoring for Early Type 1 Diabetes Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for predicting the risk of developing type 1 diabetes are insufficient in accurately stratifying genetic scores to predict the risk, particularly for pre-symptomatic cases.
Innovation Solution
A method involving the calculation of a genetic risk score (GRS) by multiplying the score weights of 41 SNPs with the number of risk alleles, considering specific genotypes like HLA DR4-DQ8/DR4-DQ8 and DR3/DR4-DQ8, and summing the products to determine the risk of developing type 1 diabetes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If risk assessment relies on family history and HLA loci genotypes, then the identification of at-risk infants is simplified, but the prediction precision is insufficient (only identifying up to 10% of children who develop the disease)
Solution Approach 1:
The patent segments the genetic risk assessment into multiple independent components: HLA class II genotypes (DR and DQ loci) and non-HLA susceptibility loci (including insulin gene, HLA class I, and other regions). Each component is evaluated separately and then combined to generate an overall risk score, allowing for more precise prediction while maintaining manageable complexity through modular analysis
Solution Approach 2:
The patent merges the evaluation of HLA class II genotypes with non-HLA susceptibility loci into a unified risk assessment framework. By combining results from multiple genetic regions (HLA DR, HLA DQ, insulin gene, HLA class I, and other susceptibility regions) into a composite risk score, the system achieves superior prediction precision compared to using HLA loci alone
2Reliability
If multi-loci genetic scores are used to identify type 1 diabetes cases, then the risk stratification is improved, but the establishment of precise genetic scores for predicting individual risk remains insufficient
Solution Approach 1:
The patent introduces a quantitative risk score parameter that transforms qualitative genetic findings into a continuous numerical assessment. The risk score is calculated by assigning weights to different genetic variants and summing their contributions, enabling precise individual risk prediction. This parameter change allows for continuous stratification of risk rather than categorical classification, improving both reliability and precision
Data Source
AI summary
The present invention relates to a method of determining whether a subject is at risk of developing type 1 diabetes by determining the genetic risk score (GRS) of a subject. The present invention also comprises a pharmaceutical composition comprising insulin and a pharmaceutical acceptable carrier for use in a method for preventing type 1 diabetes in a subject having a genetic risk score as determined by the method mentioned above. Further, it encompasses a kit for use in a method of determining whether a subject is at risk of developing type 1 diabetes by determining the genetic risk score of a subject and a type 1 diabetes antigen for use in a method of immunizing a subject against type 1 diabetes having a genetic risk score as determined by the method mentioned above.