MyVisionTest News Archive
Feb 25, 2012
The role of genetic markers and environmental factors in the development of AMD
A new study finds that the gene for complement factor H (CFH) confers more risk to the bilaterality of geographic atrophy, whereas the gene for HTRA1/LOC387715 contributes more to the bilaterality of choroidal neovascularization (CNV).
Because AMD is one of the most studied common eye diseases of the past 5 years, knowledge of its genetic basis has increased exponentially.
Genetic variants at 2 gene regions:
A number of other genetic variants, such as complement component 2 (C2 [OMIM 217000]), complement factor B (CFB [OMIM 138470]), and complement component 3 (C3 [OMIM 120700]), have also been identified to be strongly and consistently associated with AMD.
Of the environmental risk factors, age and smoking have most consistently been identified as major risks.
IT REMAINS UNCLEAR TO WHAT EXTENT THESE RISK FACTORS AS A GROUP COULD EXPLAIN THE OCCURRENCE OF AMD.
Early detection and risk prediction could potentially improve disease prognosis and outcomes by allowing for gene-based treatment or spurring patients to modify lifestyle habits. Joint effects of genetic variants and environmental factors are implicated to have better prediction of susceptibility to advanced AMD.
In this study, we used a combined data set consisting of cohorts from Utah and the Age-Related Eye Disease Study (AREDS) to refine the association of known genetic and environmental factors with advanced AMD. Effects of potential gene-gene (GxG) and gene-environment (GxE) interactions were also estimated. We aimed to develop an AMD risk model to distinguish individuals who would be infected with advanced AMD from those who would not.
Methods & Results
Demographic information, including age at onset, smoking status, and body mass index, was collected for 1844 participants. Genotypes were evaluated for 8 variants in 5 genes related to AMD. Unconditional logistic regression analyses were performed to generate a risk predictive model.
All genetic variants showed a strong association with AMD. Multivariate odds ratios (95% confidence interval) were:
Smoking was independently associated with advanced AMD after controlling for age, sex, body mass index, and all genetic variants.
Discussion & Conclusions
We demonstrate a significant association between AMD and known genetic polymorphisms of CFH, HTRA1/LOC387715, C2, CFB, and C3. The results of allele frequencies and the ORs for each marker confirmed the findings of previously published reports.
The risk allele of C3 rs2230199 was significantly higher in GA (32.4%) than in CNV (26.4%) (P < 001) when adjusted for age and sex. This result, for the first time to our knowledge, shows that C3 rs2230199 predisposes individuals to GA more than CNV. A similar trend was also observed in an earlier study. The ways in which C3 contributes differently to the pathogenesis of GA vs CNV require further investigation.
Vision-related quality of life is strongly associated with visual acuity and the presence of bilateral AMD. Bilateral AMD corresponds to a more severe stage of the disease and is a sign of progression. It is not surprising to find that all the risk alleles are more common in the bilaterally affected group than in the unilaterally affected group but only significantly for CFH rs2274700, CFH rs1410996, HTRA1/LOC387715 rs10490924, and HTRA1/LOC387715 rs11200638.
Although not statistically significant, SNPs in CFH showed a tendency to have a higher risk allele frequency in GA, whereas SNPs in HTRA1/LOC387715 have higher allele frequencies in CNV. Overall, neither CFH nor HTRA1/LOC387715 has been shown to be responsible for directing AMD toward a specific late phenotype (GA or CNV). However, both genes may play a role in increasing its severity once a late phenotype develops. Our results show that CFH increases the severity of GA, whereas HTRA1/LOC387715 heightens CNV. This is in agreement with the findings from other authors that the HTRA1/LOC387715 gene is more strongly related to the progression of CNV than to GA.
Our results showed that of the environmental risk factors, smoking and age were identified as major risk factors, which was consistent with the combined analysis of population-based eye studies from 3 continents. Smoking was confirmed as an independent risk factor for AMD in this study. Patients have a 1.8-fold higher chance of developing AMD if they ever smoked compared with those who never smoked. The risk was elevated to 3.7-fold for current smokers. As another risk factor, BMI showed a weak contribution to the occurrence of AMD. Neither smoking nor BMI was found to have a significant interaction with genotypes. Although a single study found an interaction between smoking and HTRA1/LOC387715 rs10490924, interaction between smoking and genotypes was eliminated when stepwise logistic regression was performed, which was consistent with data from multiple reports. However, an interaction is still a possibility because logistic regression has only modest power for distinguishing interactions.
In terms of interactions among genotypes, we found weak interactions of CFH rs1061170CTHTRA1/LOC387715 rs10490924TT and CFH rs2274700CT HTRA1/LOC387715 rs10490924TG. Because our model was not improved by inclusion of these interactions, for the sake of simplicity, no interaction term was included in our risk model. This result is similar to that of a study in Finland in which a tentative interaction between CFH and LOC387715 with a marginal P value (.06) was observed. However, most studies have not found an interaction between these 2 genes. Our final model supported the notion that CFH and HTRA1/LOC387715 act independently, and the log-linear additive model fits well for the joint effects of these 2 genes.
We developed a risk model that predicts the individual’s risk for AMD. Targeting high-risk individuals could lead to more frequent surveillance and clinical interventions. Patients would benefit from more targeted education regarding a healthy lifestyle. However, the risk predictions resulting from this model are directly applicable only to the population from which it was developed; we still need to be careful when extending the results to other populations. Sensitivities and specificities for a variety of risk factors were evaluated to assess the optimal use of the model for individual risk prediction. The sensitivity, specificity, and area under the ROC curve established in this study were analogous to those reported by previous studies. To improve the AMD prediction model, more genetic- or environmental-influencing factors need to be clarified.
In summary, CFH confers more risk to the bilaterality of geographic atrophy, whereas HTRA1/LOC387715 contributes more to the bilaterality of choroidal neovascularization. Early detection and risk prediction of AMD could help to improve the prognosis of AMD and to reduce the outcome of blindness. Targeting high-risk individuals for surveillance and clinical interventions may help reduce disease burden.
Read more...
Arch Ophthalmol. 2011 Mar;129(3):344-51
Tags: AMD, genetics, tobacco
A new study finds that the gene for complement factor H (CFH) confers more risk to the bilaterality of geographic atrophy, whereas the gene for HTRA1/LOC387715 contributes more to the bilaterality of choroidal neovascularization (CNV).Because AMD is one of the most studied common eye diseases of the past 5 years, knowledge of its genetic basis has increased exponentially.
- complement factor H (CFH [OMIM 134370])
- high-temperature requirement factor A-1 (HTRA1 [OMIM 602194])/LOC387715
A number of other genetic variants, such as complement component 2 (C2 [OMIM 217000]), complement factor B (CFB [OMIM 138470]), and complement component 3 (C3 [OMIM 120700]), have also been identified to be strongly and consistently associated with AMD.
Of the environmental risk factors, age and smoking have most consistently been identified as major risks.
IT REMAINS UNCLEAR TO WHAT EXTENT THESE RISK FACTORS AS A GROUP COULD EXPLAIN THE OCCURRENCE OF AMD.
Early detection and risk prediction could potentially improve disease prognosis and outcomes by allowing for gene-based treatment or spurring patients to modify lifestyle habits. Joint effects of genetic variants and environmental factors are implicated to have better prediction of susceptibility to advanced AMD.
In this study, we used a combined data set consisting of cohorts from Utah and the Age-Related Eye Disease Study (AREDS) to refine the association of known genetic and environmental factors with advanced AMD. Effects of potential gene-gene (GxG) and gene-environment (GxE) interactions were also estimated. We aimed to develop an AMD risk model to distinguish individuals who would be infected with advanced AMD from those who would not.
Methods & Results
Demographic information, including age at onset, smoking status, and body mass index, was collected for 1844 participants. Genotypes were evaluated for 8 variants in 5 genes related to AMD. Unconditional logistic regression analyses were performed to generate a risk predictive model.
All genetic variants showed a strong association with AMD. Multivariate odds ratios (95% confidence interval) were:
- 3.52 (2.08-5.94) for CFH rs1061170 CC
- 4.21 (2.30-7.70) for CFH rs2274700 CC
- 0.46 (0.27-0.80) for C2 rs9332739 CC/CG
- 0.44 (0.30-0.66) for CFB rs641153 TT/CT
- 10.99 (6.04-19.97) for HTRA1/LOC387715 rs10490924 TT
- 2.66 (1.43-4.96) for C3 rs2230199 GG
Smoking was independently associated with advanced AMD after controlling for age, sex, body mass index, and all genetic variants.
Discussion & Conclusions
We demonstrate a significant association between AMD and known genetic polymorphisms of CFH, HTRA1/LOC387715, C2, CFB, and C3. The results of allele frequencies and the ORs for each marker confirmed the findings of previously published reports.The risk allele of C3 rs2230199 was significantly higher in GA (32.4%) than in CNV (26.4%) (P < 001) when adjusted for age and sex. This result, for the first time to our knowledge, shows that C3 rs2230199 predisposes individuals to GA more than CNV. A similar trend was also observed in an earlier study. The ways in which C3 contributes differently to the pathogenesis of GA vs CNV require further investigation.
Vision-related quality of life is strongly associated with visual acuity and the presence of bilateral AMD. Bilateral AMD corresponds to a more severe stage of the disease and is a sign of progression. It is not surprising to find that all the risk alleles are more common in the bilaterally affected group than in the unilaterally affected group but only significantly for CFH rs2274700, CFH rs1410996, HTRA1/LOC387715 rs10490924, and HTRA1/LOC387715 rs11200638.
Although not statistically significant, SNPs in CFH showed a tendency to have a higher risk allele frequency in GA, whereas SNPs in HTRA1/LOC387715 have higher allele frequencies in CNV. Overall, neither CFH nor HTRA1/LOC387715 has been shown to be responsible for directing AMD toward a specific late phenotype (GA or CNV). However, both genes may play a role in increasing its severity once a late phenotype develops. Our results show that CFH increases the severity of GA, whereas HTRA1/LOC387715 heightens CNV. This is in agreement with the findings from other authors that the HTRA1/LOC387715 gene is more strongly related to the progression of CNV than to GA.
Our results showed that of the environmental risk factors, smoking and age were identified as major risk factors, which was consistent with the combined analysis of population-based eye studies from 3 continents. Smoking was confirmed as an independent risk factor for AMD in this study. Patients have a 1.8-fold higher chance of developing AMD if they ever smoked compared with those who never smoked. The risk was elevated to 3.7-fold for current smokers. As another risk factor, BMI showed a weak contribution to the occurrence of AMD. Neither smoking nor BMI was found to have a significant interaction with genotypes. Although a single study found an interaction between smoking and HTRA1/LOC387715 rs10490924, interaction between smoking and genotypes was eliminated when stepwise logistic regression was performed, which was consistent with data from multiple reports. However, an interaction is still a possibility because logistic regression has only modest power for distinguishing interactions.
In terms of interactions among genotypes, we found weak interactions of CFH rs1061170CTHTRA1/LOC387715 rs10490924TT and CFH rs2274700CT HTRA1/LOC387715 rs10490924TG. Because our model was not improved by inclusion of these interactions, for the sake of simplicity, no interaction term was included in our risk model. This result is similar to that of a study in Finland in which a tentative interaction between CFH and LOC387715 with a marginal P value (.06) was observed. However, most studies have not found an interaction between these 2 genes. Our final model supported the notion that CFH and HTRA1/LOC387715 act independently, and the log-linear additive model fits well for the joint effects of these 2 genes.
We developed a risk model that predicts the individual’s risk for AMD. Targeting high-risk individuals could lead to more frequent surveillance and clinical interventions. Patients would benefit from more targeted education regarding a healthy lifestyle. However, the risk predictions resulting from this model are directly applicable only to the population from which it was developed; we still need to be careful when extending the results to other populations. Sensitivities and specificities for a variety of risk factors were evaluated to assess the optimal use of the model for individual risk prediction. The sensitivity, specificity, and area under the ROC curve established in this study were analogous to those reported by previous studies. To improve the AMD prediction model, more genetic- or environmental-influencing factors need to be clarified.
In summary, CFH confers more risk to the bilaterality of geographic atrophy, whereas HTRA1/LOC387715 contributes more to the bilaterality of choroidal neovascularization. Early detection and risk prediction of AMD could help to improve the prognosis of AMD and to reduce the outcome of blindness. Targeting high-risk individuals for surveillance and clinical interventions may help reduce disease burden.
Read more...
Arch Ophthalmol. 2011 Mar;129(3):344-51
