Publication Date
11-7-2024
DOI
10.1136/bmjophth-2024-001791
PMID
39510601
PMCID
PMC11552016
PubMedCentral® Posted Date
11-7-2024
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Keywords
Humans, Tomography, Optical Coherence, Male, Cross-Sectional Studies, Female, Middle Aged, Retinal Ganglion Cells, Diabetic Retinopathy, Nerve Fibers, Aged, Retinal Degeneration, Retina, Adult, Retina, Degeneration, Diagnostic tests/Investigation
Abstract
OBJECTIVE: Macular retinal nerve fibre layer (mRNFL) and ganglion cell-inner plexiform layer thickness (GC-IPL) measurements are important markers of diabetic retinal neurodegeneration (DRN). In this cross-sectional study, we aimed to quantify the contribution of total retinal thickness (TRT) and other factors in the variation of mRNFL and GC-IPL thickness among participants with diabetes.
METHODS AND ANALYSIS: We used macular-centred spectral domain-optical coherence tomography scans from participants with diabetes in the UK Biobank. Two multiple linear regression models (prior to and after adjusting for TRT) were used to determine factors associated with mRNFL and GC-IPL thicknesses. A p value of less than 0.05 was considered statistically significant.
RESULTS: A total of 3832 eyes from 3832 participants with diabetes were analysed. Factors that explained the greatest variation in thickness were TRT (20.9% for mRNFL and 57.2% for GC-IPL), followed by spherical equivalent (8.0% for mRNFL only), gender (2.2% for mRNFL only) and age (1.4% for GC-IPL only). Other factors significantly associated with mRNFL and/or GC-IPL thickness explained less than 1% of the variation in their thicknesses. Self-reported ancestral background was not significantly associated with mRNFL thickness after accounting for TRT.
CONCLUSIONS: Although many factors were significantly associated with mRNFL and GC-IPL thickness in participants with diabetes, they accounted for a fraction of the variation in the thickness of both layers. TRT explained most of the variation in these measurements, hence accounting for TRT is needed when using these metrics to evaluate DRN.