Nicholas Howell

Diabetic retinopathy (DR) is a complication of diabetes and the leading cause of vision-loss and blindness among adults worldwide. It is prevalent across type I and type II diabetics (T1D and T2D), appearing in most T1D and about 60% of T2D within the two decades following diagnosis. The putative disease progression results in four phenotypes, varying in their threat of vision-loss. While the duration since diabetes onset and metabolic factors are known to play a role in the development of these phenotypes, recent studies have also provided significant evidence for genetic predisposition. This project examines the contribution of single nucleotide polymorphisms (SNP) in the development of DR. Specifically, we test a common variant hypothesis based on genome-wide risk assessment scores. Genome-wide association studies (GWAS) have identified thousands of statistically significant SNPs associated with diabetes, diabetic complications, and numerous other conditions. Using the results of these GWAS, this project generated polygenic risk scores (PRS)—whole genome indicators of risk—for diabetic retinopathy, T1D and T2D, and other disease phenotypes, and analyzed whether they could predict which diabetics are at increased risk of developing DR. These polygenic risk scores were validated in the UK BioBank cohort and demonstrated that 1) the PRS for DR, T1D, and T2D are valid indicators of risk in healthy controls, and our pipeline is working as intended; 2) the DR PRS is highly associated with DR diagnoses in diabetics, T1D PRS is statistically significant and moderately clinically useful, and T2D PRS is statistically significant but is not likely to be clinically useful; and 3) additional disease PRS, like kidney failure and HbA1c measurement, have a statistically significant association with DR in diabetics that trends towards clinical utility. These results suggest that to predict DR in diabetics the risk prediction tool should incorporate DR, T1D, kidney failure, and HbA1c polygenic risk scores.