Article Text
Abstract
Purpose To evaluate the potential of retinal optical coherence tomography (OCT) measurements and polygenic risk scores (PRS) to identify people at risk of cognitive impairment.
Methods Using OCT images from 50 342 UK Biobank participants, we examined associations between retinal layer thickness and genetic risk for neurodegenerative disease and combined these metrics with PRS to predict baseline cognitive function and future cognitive deterioration. Multivariate Cox proportional hazard models were used to predict cognitive performance. P values for retinal thickness analyses are false-discovery-rate-adjusted.
Results Higher Alzheimer’s disease PRS was associated with a thicker inner nuclear layer (INL), chorio-scleral interface (CSI) and inner plexiform layer (IPL) (all p<0.05). Higher Parkinson’s disease PRS was associated with thinner outer plexiform layer (p<0.001). Worse baseline cognitive performance was associated with thinner retinal nerve fibre layer (RNFL) (aOR=1.038, 95% CI (1.029 to 1.047), p<0.001) and photoreceptor (PR) segment (aOR=1.035, 95% CI (1.019 to 1.051), p<0.001), ganglion cell complex (aOR=1.007, 95% CI (1.002 to 1.013), p=0.004) and thicker ganglion cell layer (aOR=0.981, 95% CI (0.967 to 0.995), p=0.009), IPL (aOR=0.976, 95% CI (0.961 to 0.992), p=0.003), INL (aOR=0.923, 95% CI (0.905 to 0.941), p<0.001) and CSI (aOR=0.998, 95% CI (0.997 to 0.999), p<0.001). Worse future cognitive performance was associated with thicker IPL (aOR=0.945, 95% CI (0.915 to 0.999), p=0.045) and CSI (aOR=0.996, 95% CI (0.993 to 0.999) 95% CI, p=0.014). Prediction of cognitive decline was significantly improved with the addition of PRS and retinal measurements.
Conclusions and relevance Retinal OCT measurements are significantly associated with genetic risk of neurodegenerative disease and may serve as biomarkers predictive of future cognitive impairment.
- Imaging
- Genetics
Data availability statement
Data are available upon reasonable request. Data is available from the UK Biobank.
Statistics from Altmetric.com
Footnotes
SS, YS and SS contributed equally.
Contributors SSekimitsu, SShareef and YZ worked on data analysis. SSekimitsu and YS drafted the initial manuscript. TE, AS and JW worked on data acquisition and provided feedback. NZ led the project, assisted with study design and provided feedback on the final manuscript. NZ is the guarantor of this project.
Funding This work was supported in part by the NIH K23 Career Development Award (EY032634) (NZ), NIH R21 Exploratory/Developmental Research Grant Award (EY032953) (NZ), Research to Prevent Blindness Career Development Award (NZ), Fulbright Scholarship (YS), NIH R21 Exploratory/Developmental Research Grant Award (EY030631) (TE), NIH R01 Research Project Grant (EY030575) (TE), NIH P30 Center Core Grant (EY003790) (TE), NIH R01 Research Project Grant (EY032559) (JW, AS), NIH P30 Center Core Grant (EY014104) (JW) and NIH R01 Research Project Grant (EY031424-01) (AS). The funding organisation had no role in the design or conduct of this research.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.