The invention provides a myopia progress prediction method based on a dynamic weight multi-
gene risk
score (PRS). The myopia progress prediction method comprises the following steps of: selecting a myopia progress prediction model according to the dynamic weight multi-
gene risk
score (PRS); the method comprises the following steps of: inputting a whole
genome association study (GWAS) effect value of a basic
population and individual
genotype data of a
target population, carrying out dynamic correction on a
single nucleotide polymorphism (SNP) effect value in combination with a
population differentiation index (Fst) and a
linkage disequilibrium (LD) parameter of the
target population, and constructing a PRS model with a
population generalization ability. The method further collects individual
environmental behavior data, including close-range eye load and outdoor
exposure, calculates environmental interaction factors, and introduces the environmental interaction factors into a risk scoring model to comprehensively generate an individual dynamic risk
score (PRSdynamic). The method has the characteristics of cross-racial adaptability, genetic-environment interaction modeling ability and optimization along with time change, can be used for individualized accurate prediction of myopia progress risks, and provides a scientific basis for myopia prevention and control research and intervention strategy formulation.