Identify genetic variants (GWAS/WES) associated with:

• Myopia onset risk (high-risk SNPs ).
• Myopia progression rate (e.g., axial elongation/year).

Evaluate gene-intervention interactions for:

• Low-dose atropine (0.01%, 0.05%).
• Orthokeratology.
• Defocus-incorporated spectacles.
• Outdoor/sunlight exposure (≥2 hours/day).

Beyond detecting links between gene variants and myopia development, the testing analyzes how these variants influence treatment effectiveness. The aim is to enable early risk prediction and personalized treatment guidance for children through oral DNA testing.

1. Measure the Myopia Progression Rate (Change in Diopters/year)

   • Measurement Tool: Autorefractor (Topcon KR-8900)
   • Method: Spherical equivalent refraction (SER) will be measured at baseline and every 6 months, with the annual rate of change (ΔD/year) calculated.
   • Unit: Diopters (D)

2. Measure the Axial Length Growth Rate (mm/year)

   • Measurement Tool: Optical Biometer (Zeiss IOLMaster 700)
   • Method: Axial length (AL) will be measured at baseline and every 6 months, with the annual rate of change (Δmm/year) calcu

3. Genetic Risk Assessment Model

   • Measurement Tool: Candidate genetic loci will be screened using whole-exome sequencing (WES)or genome-wide association study (GWAS).
   • A PRS model for myopia progression will be constructed by integrating refractive error (SER) and axial length changes using LASSO, DBSLMM or LDpred2 regression.
   • The correlation between PRS and myopia progression rate will be evaluated (R² or AUC curve).

1. Data Collection

   • error (spherical equivalent, ΔD/year) - Measured via autorefractor (per Primary Outcome Measure)
   • Axial length (Δmm/year) - Measured via optical biometer (per Secondary Outcome Measure)
   • Genetic Data: Myopia-associated SNPs (derived from WES/GWAS)
   • Clinical Intervention Data: Type of myopia control intervention (e.g., 0.01% atropine, orthokeratology, defocus-incorporated spectacles, myopia-control soft contact lenses)

2. Analytical Pipeline

   • Compute individual PRS by aggregating weighted risk alleles (SNP effect sizes from GWAS or WES)
   • Optimal Intervention Stratification
   • Apply logistic regression/decision tree analysis to:Identify PRS threshold(s) predictive of treatment response. Test hypotheses ( "Subjects with PRS >X exhibit superior efficacy with atropine vs. orthokeratology")

3. Clinical Translation

   • Generate decision trees or nomograms to visualize:
   • PRS-guided intervention selection
   • Predicted treatment efficacy probabilities