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Improved Alzheimer disease onset risk prediction method

A technology for Alzheimer's disease and risk prediction, applied in the field of medical testing, can solve problems such as ignoring SNP interactions, and achieve the effect of improving accuracy and correctness

Active Publication Date: 2017-05-10
HARBIN INST OF TECH
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0007] Current studies have shown that the interaction between SNPs has an important impact on the pathogenesis of Alzheimer's disease, while wGRS ignores the interaction between SNPs when predicting risk

Method used

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  • Improved Alzheimer disease onset risk prediction method
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  • Improved Alzheimer disease onset risk prediction method

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Embodiment Construction

[0036] A specific embodiment of the present invention will be described in detail below with reference to the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments.

[0037] Such as figure 1 As shown, the embodiment of the present invention provides an improved method for predicting the risk of Alzheimer’s disease. When the present invention uses genotype data to predict the risk of Alzheimer’s disease, the interaction relationship between SNPs is used to perform Alzheimer’s disease risk. Prediction of the risk of Alzheimer’s disease; the purpose of the present invention is to train an Alzheimer’s disease risk model using the genotype data of Alzheimer’s disease individuals and normal control individuals, and then use the model and the genotype of the individual to be tested The data predicts the risk of Alzheimer's disease. The method of the present invention includes the following steps: ...

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Abstract

The invention belongs to the field of medical detection, and particularly discloses an improved Alzheimer disease onset risk prediction method. The method puts forward an improved wGRS (Genetic Risk Score) method based on traditional wGRS, the function of single SNP (Single nucleotide polymorphisms) is considered during wGRS calculation, and meanwhile, the mutual function of SNPs is also considered. According to the improved wGRS method, the accuracy of Alzheimer disease onset risk prediction is further improved. Therefore, the method takes the important influence of the mutual function of the SNPs on the Alzheimer disease into consideration, and the mutual function of the SNPs is applied to the Alzheimer disease onset risk prediction to further improve the accuracy of the Alzheimer disease onset risk prediction.

Description

Technical field [0001] The present invention relates to the field of medical detection, in particular to an improved method for predicting the risk of Alzheimer's disease. Background technique [0002] Alzheimer's disease is a degenerative disease of the nervous system, which is clinically characterized by dementia such as memory loss and cognitive decline. Modern science believes that Alzheimer's disease is the result of a combination of genes and environmental factors, among which genes play a major role. [0003] At present, the proportion of patients with Alzheimer's disease is increasing year by year, which seriously affects people's daily life. In recent years, genome-wide association studies and candidate gene studies have discovered a large number of Alzheimer's disease susceptibility polymorphic loci. Therefore, it is very important to establish a corresponding model based on the genotype data of Alzheimer's disease individuals and normal control individuals to predict t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C12Q1/68G06F19/22
CPCC12Q1/6883C12Q2600/156G16B30/00
Inventor 蒋庆华刘桂友胡杨王亚东
Owner HARBIN INST OF TECH
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