Evaluation of retinal nerve fibre layer thickness as a possible measure of diabetic retinal neurodegeneration in the EPIC-Norfolk Eye Study

Background/aims Markers to clinically evaluate structural changes from diabetic retinal neurodegeneration (DRN) have not yet been established. To study the potential role of peripapillary retinal nerve fibre layer (pRNFL) thickness as a marker for DRN, we evaluated the relationship between diabetes, as well as glycaemic control irrespective of diabetes status and pRNFL thickness. Methods Leveraging data from a population-based cohort, we used general linear mixed models (GLMMs) with a random intercept for patient and eye to assess the association between pRNFL thickness (measured using GDx) and demographic, systemic and ocular parameters after adjusting for typical scan score. GLMMs were also used to determine: (1) the relationship between: (A) glycated haemoglobin (HbA1c) irrespective of diabetes diagnosis and pRNFL thickness, (B) diabetes and pRNFL thickness and (2) which quadrants of pRNFL may be affected in participants with diabetes and in relation to HbA1c. Results 7076 participants were included. After controlling for covariates, inferior pRNFL thickness was 0.94 mu m lower (95% CI -1.28 mu m to -0.60 mu m), superior pRNFL thickness was 0.83 mu m lower (95% CI -1.17 mu m to -0.49 mu m) and temporal pRNFL thickness was 1.33 mu m higher (95% CI 0.99 mu m to 1.67 mu m) per unit increase in HbA1c. Nasal pRNFL thickness was not significantly associated with HbA1c (p=0.23). Similar trends were noted when diabetes was used as the predictor. Conclusion Superior and inferior pRNFL was significantly thinner among those with higher HbA1c levels and/or diabetes, representing areas of the pRNFL that may be most affected by diabetes.

Automated summary

This study examined the relationship between diabetes, glycemic control, and retinal nerve fiber layer thickness. The results showed that higher HbA1c levels and diabetes were associated with thinner superior and inferior pRNFL, indicating the areas most affected by diabetes.