Visual dysfunction is a better predictor than retinal thickness for dementia in Parkinson's disease

Abstract

Background: Dementia is a common and devastating symptom of Parkinson's disease (PD). Visual function and retinal structure are both emerging as potentially predictive for dementia in Parkinson's but lack longitudinal evidence.

Methods: We prospectively examined higher order vision (skew tolerance and biological motion) and retinal thickness (spectral domain optical coherence tomography) in 100 people with PD and 29 controls, with longitudinal cognitive assessments at baseline, 18 months and 36 months. We examined whether visual and retinal baseline measures predicted longitudinal cognitive scores using linear mixed effects models and whether they predicted onset of dementia, death and frailty using time-to-outcome methods.

Results: Patients with PD with poorer baseline visual performance scored lower on a composite cognitive score (β=0.178, SE=0.05, p=0.0005) and showed greater decreases in cognition over time (β=0.024, SE=0.001, p=0.013). Poorer visual performance also predicted greater probability of dementia (χ² (1)=5.2, p=0.022) and poor outcomes (χ² (1) =10.0, p=0.002). Baseline retinal thickness of the ganglion cell-inner plexiform layer did not predict cognitive scores or change in cognition with time in PD (β=-0.013, SE=0.080, p=0.87; β=0.024, SE=0.001, p=0.12).

Conclusions: In our deeply phenotyped longitudinal cohort, visual dysfunction predicted dementia and poor outcomes in PD. Conversely, retinal thickness had less power to predict dementia. This supports mechanistic models for Parkinson's dementia progression with onset in cortical structures and shows potential for visual tests to enable stratification for clinical trials.

Keywords: Parkinson's disease; cognition; dementia; vision.

Conflict of interest statement

Competing interests: RSW has received honoraria from GE Healthcare and Britannia, as well as speaking honoraria from the Shirley Ryan Ability Lab. PAK has received honoraria from Alimera, AbbVie, Apellis, Boehringer-Ingleheim, Thea, Bayer and Gyroscope, as well as consulting fees from DeepMind. PAK participates on data safety monitoring /advisory boards for RetinAI, Novartis, Roche, AbbVie, Boehringer-Ingleheim and Apellis. PAK also holds stock with Big Medical Picture, stock options with Bitfount, and holds a patent: Google US10198832B2.

© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.

Figures

Figure 1

Patient flow in the study patients and controls recruited and tested in this study at baseline and during 18-month and 36-month follow-up visits. Due to the COVID-19 pandemic, the 18-month follow-up visits were missed for five controls. Note that patients who declined follow-up are not included in follow-up data but are logged as censored events for the time to survival analysis. CBD, cortical basal degeneration; MCI, mild cognitive impairment; MSA multiple system atrophy; PSP, Progressive supranuclear palsy.

Figure 2

Relationship between visual function and cognitive measures at (A) baseline and (B) after 36-month follow-up; and between GCIPL retinal thickness and cognitive measures at (C) baseline and (D) after 36-month follow-up. Scatter plots display original data, without adjustment for age. GCIPL, ganglion cell—inner plexiform layer; MoCA, Montreal Cognitive Test. Shaded area represents 95% CIs.

Figure 3

Risk of cognitive decline predicted by higher order visual measures and retinal thickness. Modelled data for predicted composite cognitive score over time in the Parkinson’s disease group, based on (A) baseline higher-order visual function z-scores of +1.5 (high visual performer) and −1.5 (low visual performer); (B) baseline parafoveal GCIPL thickness z-scores of +1.5 (high retinal thickness) and −1.5 (low retinal thickness). Estimated marginal means from linear mixed effect models were calculated, and the lines plotted holding age and gender constant. Shaded area represents 95% CIs. GCIPL, ganglion cell layer and internal plexiform layer.

Figure 4

Survival curves for prediction of dementia, death and frailty in Parkinson’s disease Kaplan-Meier plots illustrating the probability of remaining free from (A) dementia and (B) cumulative death, dementia, or frailty in low versus high visual performers. Low visual performers scored below the median on two tests of higher-order visual perception, as in our previous work. Kaplan-Meier plots illustrating the probability of remaining free from (C) dementia and (D) cumulative death, dementia, or frailty in medium/high versus low retinal tertiles. Retinal tertiles were based on the parafoveal GCIPL thickness of a reference retinal thickness distribution (as in previous work. Dementia was defined using clinical diagnosis or MMSE score