ArticleMedical science monitor : international medical journal of experimental and clinical research2018
Polymorphisms in Selected Genes and Their Association with Age-Related Macular Degeneration in a Chinese Population.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.
- Genetic Variability in Molecular Pathways Implicated in Alzheimer's Disease: A Comprehensive Review.Frontiers in aging neuroscience · 2021Pooled it
- Haplotypes ofDisease markers · 2019Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Increasing evidence shows that polymorphisms in a number of genes can influence age-related macular degeneration (AMD) risk. This study aimed to investigate the association of CX3CR1 839C/T, CX3CR1 745G/A, PLEKHA1 958A/G, VEGFA +674C/T, and VEGFA +936C/T polymorphisms with AMD risk among Chinese. MATERIAL AND METHODS The polymorphisms were genotyped on 827 AMD patients and 827 controls, and the odds ratios (ORs) were calculated under allele, additive, recessive, and dominant genetic models. Logistic regression analysis was performed to control for potential confounders (age, sex, and smoking status). RESULTS We showed that all the 5 polymorphisms showed a significant association with AMD risk under the additive model (for homozygous mutant genotype) and at least 1 other genetic model, both before and after adjustment for the potential confounders. PLEKHA1 958A/G polymorphism was associated with a decreased AMD risk (additive model: aOR=0.722, 95% CI=0.450-0.979, P=0.019; allele model: aOR=0.883, 95% CI=0.736-0.992, P=0.014), while all other polymorphisms were associated with an increased AMD risk (CX3CR1 839C/T, additive model: aOR=2.682, 95% CI=1.119-5.709, P=0.022, recessive model: aOR=2.729, 95% CI=1.141-6.048, P=0.010; CX3CR1 745G/A, additive model: aOR=2.614, 95% CI=1.231-6.012, P=0.020, recessive model: aOR=2.340, 95% CI=1.227-5.993, P=0.011; VEGFA +674C/T, additive model: aOR=1.601, 95% CI=1.253-2.179, P<0.001, dominant model: aOR=1.287, 95% CI=1.058-1.570, P<0.001, allele model: OR=1.220, 95% CI=1.118-1.427, P<0.001; VEGFA +936C/T, additive model: aOR=1.509, 95% CI=1.105-2.311, P<0.001, recessive model: aOR=1.432, 95% CI=1.027-2.192, P=0.009, dominant model: aOR=1.207, 95% CI=1.031-1.514, P0.001, allele model: aOR=1.216, 95% CI=1.062-1.408, P<0.001). CONCLUSIONS We conclude that the 5 polymorphisms could serve as biomarkers for AMD susceptibility.
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