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Diabetic retinopathy environment-wide association study (EWAS) in NHANES 2005-8.

K. Blighe,S. Gurudas,Ying Lee,S. Sivaprasad

Published 2020 in medRxiv

ABSTRACT

Background: Several circulating biomarkers are reported to be associated with diabetic retinopathy (DR). However, their relative contributions to DR compared to known risk factors, such as hyperglycemia, hypertension, and hyperlipidemia, remain unclear. In this data driven study, we used novel models to evaluate the associations of over 400 laboratory parameters with DR. Methods: We performed an environment-wide association study (EWAS) of laboratory parameters available in National Health and Nutrition Examination Survey (NHANES) 2007-8 in individuals with diabetes with DR as the outcome (test set). We employed independent variable ('feature') selection approaches, including parallelized univariate regression modeling, Principal Component Analysis (PCA), penalized regression, and RandomForest. These models were replicated in NHANES 2005-6 (replication set). Findings: The test and replication set consisted of 1025 and 637 individuals with available DR status and laboratory data respectively. Glycohemoglobin (HbA1c) was the strongest risk factor for DR. Our PCA-based approach produced a model that incorporated 18 principal components (PCs) that had AUC 0.796 (95% CI 0.761-0.832), while penalized regression identified a 9-feature model with 78.51% accuracy and AUC 0.74 (95% CI 0.72-0.77). RandomForest identified a 31-feature model with 78.4% accuracy and AUC 0.71 (95% CI 0.65-0.77). On grouping the selected variables in our RandomForest, hyperglycemia alone achieved AUC 0.72 (95% CI 0.68-0.76). The AUC increased to 0.84 (95% CI 0.78-0.9) when the model also included hypertension, hypercholesterolemia, hematocrit, renal and liver function tests. Interpretation: All models showed that the contributions of established risk factors of DR especially hyperglycemia outweigh other laboratory parameters available in NHANES.

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