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Inducement and Evaluation of a Murine Model of Experimental Myopia
Published on: January 22, 2019
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Genetic associations of high myopia
Bin Mao1, Xing-Xuan Dong1, Shi-Yi Gong1
1School of Public Health, Suzhou Medical College of Soochow University, Suzhou, China.
The British Journal of Ophthalmology
|October 28, 2025
Summary
This meta-analysis identified 22 single nucleotide polymorphisms (SNPs) in 13 genes associated with high myopia (HM). These findings highlight potential genetic biomarkers for HM susceptibility.
Area of Science:
- Ophthalmology
- Genetics
- Molecular Biology
Background:
- High myopia (HM) is a complex ocular condition with a significant genetic component.
- The precise genetic factors contributing to HM susceptibility remain incompletely understood.
- Identifying genetic variants associated with HM is crucial for understanding its pathogenesis and developing targeted interventions.
Purpose of the Study:
- To systematically evaluate the association between genetic polymorphisms and high myopia (HM) susceptibility.
- To identify specific single nucleotide polymorphisms (SNPs) and genes implicated in HM.
- To provide a comprehensive overview of current evidence on the genetic basis of HM.
Main Methods:
- A systematic literature search was conducted across five major databases up to January 2025.
- Included were case-control studies investigating the association of SNPs with HM.
- Meta-analysis using fixed or random effects models was performed to assess pooled odds ratios (ORs) and confidence intervals (CIs) for each SNP.
Main Results:
- The meta-analysis included 76 studies (89 cohorts) examining 77 SNPs in 34 genes.
- Twenty-two SNPs within 13 genes demonstrated statistically significant associations with HM.
- Key genes identified include ACAN, COL1A1, CRYBA4, LUM, MMP2, PAX6, RASGRF1, SNTB1, and TGFB1, among others.
Conclusions:
- This study identified 22 SNPs in 13 genes as potential genetic biomarkers for high myopia.
- These genetic variants may play a role in the susceptibility to HM.
- Further large-scale genome-wide association studies in diverse populations are recommended to validate these findings and uncover additional genetic factors.
Keywords:
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