Detecting retinal neurodegeneration in people with diabetes: Findings from the UK Biobank

• Published in: PloS one 2021-09, Vol.16 (9), p.e0257836-e0257836
• Main Authors: Channa, Roomasa, Lee, Kyungmoo, Staggers, Kristen A, Mehta, Nitish, Zafar, Sidra, Gao, Jie, Frankfort, Benjamin J, Chua, Sharon Y L, Khawaja, Anthony P, Foster, Paul J, Patel, Praveen J, Minard, Charles G, Amos, Chris, Abramoff, Michael D
• Format: Article
• Language: English
• Subjects: Acuity; Adult; Aged; Biobanks; Biological Specimen Banks; Biology and Life Sciences; Body mass; Body mass index; Body size; Cognitive ability; Complications; Complications and side effects; Cross-Sectional Studies; Diabetes; Diabetes mellitus; Diabetes Mellitus - metabolism; Diabetic retinopathy; Diabetic Retinopathy - diagnostic imaging; Diabetic Retinopathy - metabolism; Diagnosis; Edema; Female; Glaucoma; Glycated Hemoglobin A - metabolism; Hemoglobin; Humans; Male; Medicine and Health Sciences; Middle Aged; Minority & ethnic groups; Nerve Fibers; Neurodegeneration; Patients; Population; Retina; Retina - diagnostic imaging; Retinopathy; Risk factors; Self Report; Severity of Illness Index; Social Sciences; Standard deviation; Surgery; Thickness measurement; Tomography, Optical Coherence - methods; United Kingdom; Values; Visual acuity
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0257836

Efforts are underway to incorporate retinal neurodegeneration in the diabetic retinopathy severity scale. However, there is no established measure to quantify diabetic retinal neurodegeneration (DRN). We compared total retinal, macular retinal nerve fiber layer (mRNFL) and ganglion cell-inner plexiform layer (GC-IPL) thickness among participants with and without diabetes (DM) in a population-based cohort. Cross-sectional analysis, using the UK Biobank data resource. Separate general linear mixed models (GLMM) were created using DM and glycated hemoglobin as predictor variables for retinal thickness. Sub-analyses included comparing thickness measurements for patients with no/mild diabetic retinopathy (DR) and evaluating factors associated with retinal thickness in participants with and without diabetes. Factors found to be significantly associated with DM or thickness were included in a multiple GLMM. Diagnosis of DM was determined via self-report of diagnosis, medication use, DM-related complications or glycated hemoglobin level of ≥ 6.5%. Total retinal, mRNFL and GC-IPL thickness. 74,422 participants (69,985 with no DM; 4,437 with DM) were included. Median age was 59 years, 46% were men and 92% were white. Participants with DM had lower total retinal thickness (-4.57 μm, 95% CI: -5.00, -4.14; p