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Roberta McKean-Cowdin, Rohit Varma, Darryl Nousome, Mina Torres, Bruce Burkemper, Xiuqing Guo, Barbara Klein, Kaili Ding, Xiaohui Li, Eli Ipp, Wayne Huey-Herng Sheu, Kent Taylor, Jerome I Rotter; Genetic Susceptibility to Diabetic Retinopathy Using a Genetic Risk Score in Multiethnic Cohorts. Invest. Ophthalmol. Vis. Sci. 2020;61(7):3849.
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© ARVO (1962-2015); The Authors (2016-present)
Diabetic retinopathy (DR) is a common microvascular complication of diabetes and is a leading cause of visual impairment and blindness among adults in the US. Candidate gene and genome-wide association studies (GWAS), largely based on data from European and African-American populations, provide evidence that genetic variation contributes to the development of DR, a complex trait. In this analysis, genetic risk scores (GRS) were used to model the associations between type 2 diabetes (T2D) and Hemoglobin A1c (HbA1c) associated SNPs and DR in Latino and multiethnic populations.
Genome wide association data was assembled from the Los Angeles Latino Eye Study (LALES) [n=1,052], Taiwan–US Diabetic Retinopathy (TUDR) [n=962], Multi-Ethnic Study of Atherosclerosis (MESA) [9=957], and Genetics of Latino Diabetic Retinopathy (GOLDR) [n=598]. We developed GRS based on SNPs associated with type 2 diabetes (Scott 2017) and HbA1c (Wheeler 2017) using weights (betas) from the modeled associations between each SNP and the phenotype. Weights for the GRS calculated for T2D SNPs included: betas from models of DR or T2D from within sample and from Scott et al, 2017. Weights for the GRS calculated for HBA1c included: betas from models of DR or HbA1c from within sample and from Wheeler et al, 2017. The individual GRS were calculated as the sum of each individual SNP risk allele count x weight. We identified 58 HbA1c SNPs for inclusion in logistic regression models and 128 T2D SNPs. The association between the individual GRS scores and DR was conducted after controlling for sex and principal components.
Consistent associations between GRS constructed from T2D SNPs were identified with the strongest association for weights generated from DR (β = 0.92; p<3x10-19) and T2D (Scott)( β = 0.40; p<0.002) weighted models. This also was observed when results were combined in a meta-analysis for DR using T2D weighting (β=0.416, p=7.94x10-10). Associations for GRS constructed from HbA1c models were statistically significant using weights from DR only (β=1.05; p<1.4 x10-10 for LALES and β=0.349, p=4.4x10-05 for the mulitethnic meta-analysis).
Associations between GRS and DR suggest that multiple SNPs contributing to risk of T2D are associated with DR. Predictors of HbA1c were not consistently associated with DR and therefore pathways other than glucose control may be important determinants of DR.
This is a 2020 ARVO Annual Meeting abstract.
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