Background: We performed exploratory analyses of retinal thickness data from a clinical trial of the AβPP cleaving enzyme (BACE) inhibitor verubecestat in patients with Alzheimer’s disease (AD). Objective: To evaluate: 1) possible retinal thickness changes following BACE inhibition; and 2) possible association between retinal thickness and brain atrophy. Methods: Retinal thickness was measured using spectral-domain optical coherence tomography in a 78-week randomized placebo-controlled trial of verubecestat in 1,785 patients with mild-to-moderate AD. Changes from baseline in retinal pigment epithelium, macular grid retinal nerve fiber layer, central subfield retinal thickness, and macular grid volume were evaluated for verubecestat versus placebo. Correlation analyses were performed to investigate the potential association between macular grid retinal nerve fiber layer and central subfield retinal thickness with brain volumetric magnetic resonance imaging (vMRI) data at baseline, as well as correlations for changes from baseline at Week 78 in patients receiving placebo. Results: Verubecestat did not significantly alter retinal thickness during the trial compared with placebo. At baseline, mean macular grid retinal nerve fiber layer and central subfield retinal thickness were weakly but significantly correlated (Pearson’s r values≤0.23, p-values < 0.01) with vMRI of several brain regions including whole brain, hippocampus, and thalamus. At Week 78, correlations between retinal thickness and brain vMRI changes from baseline in the placebo group were small and mostly not statistically significant. Conclusion: BACE inhibition by verubecestat was not associated with adverse effects on retinal thickness in patients with mild-to-moderate AD. Correlations between retinal thickness and brain volume were observed at baseline. Trial registration: Clinicaltrials.gov NCT01739348 (registered December 3, 2012; https://clinicaltrials.gov/ct2/show/NCT01739348).
Retinal nerve fiber layer and optical coherence tomography angiography analysis in fibromyalgia using logistic regression
