Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease, 2023, Wagner et al.

Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease
Siegfried Karl Wagner; David Romero-Bascones; Mario Cortina-Borja; Dominic J Williamson; Robbert R Struyven; Yukun Zhou; Salil Patel; Rimona S Weil; Chrystalina A Antoniades; Eric J Topol; Edward Korot; Paul J Foster; Konstantinos Balaskas; Unai Ayala; Maitane Barrenechea; Iñigo Gabilondo; Anthony HV Schapira; Anthony P Khawaja; Praveen J Patel; Jugnoo S Rahi; Alastair K Denniston; Axel Petzold; Pearse Andrew Keane; for UK Biobank Eye & Vision Consortium

Background and objectives:
Cadaveric studies have shown disease-related neurodegeneration and other morphological abnormalities in the retina of individuals with Parkinson disease (PD), however it remains unclear whether this can be reliably detected with in vivo imaging. We investigated inner retinal anatomy, measured using optical coherence tomography (OCT), in prevalent PD and subsequently assessed the association of these markers with the development of PD using a prospective research cohort.

Methods:
This cross-sectional analysis used data from two studies. For the detection of retinal markers in prevalent PD, we used data from AlzEye, a retrospective cohort of 154,830 patients aged 40 years and over attending secondary care ophthalmic hospitals in London, UK between 2008 and 2018. For the evaluation of retinal markers in incident PD, we used data from UK Biobank, a prospective population-based cohort where 67,311 volunteers aged 40-69 years were recruited between 2006 and 2010 and underwent retinal imaging. Macular retinal nerve fibre layer (mRNFL), ganglion cell-inner plexiform layer (GCIPL), and inner nuclear layer (INL) thicknesses were extracted from fovea--centred OCT. Linear mixed effects models were fitted to examine the association between prevalent PD and retinal thicknesses. Hazard ratios for the association between time to PD diagnosis and retinal thicknesses were estimated using frailty models.

Results:
Within the AlzEye cohort, there were 700 individuals with prevalent PD and 105,770 controls (mean age 65.5 ± 13.5 years, 51.7% female). Individuals with prevalent PD had thinner GCIPL (-2.12 μm, 95% confidence interval: -3.17, -1.07, p = 8.2 × 10-5) and INL (-0.99 μm, 95% confidence interval: -1.52, -0.47, p = 2.1 × 10-4). The UK Biobank included 50,405 participants (mean age 56.1 ± 8.2 years, 54.7% female), of whom 53 developed PD at a mean of 2653 ± 851 days. Thinner GCIPL (hazard ratio: 0.62 per standard deviation increase, 95% confidence interval: 0.46, 0.84, p =0.002) and thinner INL (hazard ratio: 0.70, 95% confidence interval: 0.51, 0.96, p =0.026) were also associated with incident PD.

Discussion:
Individuals with PD have reduced thickness of the INL and GCIPL of the retina. Involvement of these layers several years before clinical presentation highlight a potential role for retinal imaging for at-risk stratification of PD.

Link | PDF (Neurology)

 

See Eye scans detect signs of Parkinson’s disease up to seven years before diagnosis (NHS Moorfields)

 

Sounds like good news for Long-Covid and ME/CFS to me, since OCT-A and some other techniques are also showing some results there. With Parkinson in the back one can hope for further refinements of this technology and more studies, whilst at the same time the PD and LC/ME/CFS markers in the eye do seem somewhat different.

 

I tweeted at the author and asked him to consider looking at ME/CFS as an indication for this tech. He liked my tweet.

 

Eric Topol is in the author list.

 

Awesome! Thank you Maybe you could also tell him about this study https://link.springer.com/article/10.1007/s10456-023-09885-6 and trial https://classic.clinicaltrials.gov/ct2/show/NCT05635552 which uses these techniques, as well as the work by Carmen Scheibenbogen who wants to use OCT-A in her biomarker platform https://cfc.charite.de/klinische_studien/nksg/ as well as Hohbergers work who centrally uses OCT-A https://pubmed.ncbi.nlm.nih.gov/34307408/,https://pubmed.ncbi.nlm.nih.gov/36430175/,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9266742/.

Eric Topol is also a co-author so one would hope that he'd at least recognize the potential, but I wouldn't be sure of it.

 

Thanks so much @EndME, I just shared a few of those links with them on Twitter.

 

Thank you!!!