Parkinson's disease is the second most common neurodegenerative condition after Alzheimer's disease. The disease begins 20 years before the typical symptoms appear clinically. There is therefore great interest in early diagnosis before the onset of symptoms in affected individuals.
More than a year ago, Annika Kluge's research group published their study results, giving hope for a long-awaited blood test for Parkinson's disease. Until now, Parkinson's disease could only be confirmed by post-mortem detection of misfolded α-synuclein. The detection of misfolded α-synuclein as a structural component of Lewy bodies in the dopaminergic neurons of the substantia nigra is currently still the gold standard.
Diagnosis is based on the typical symptoms in combination with the results of imaging procedures. This results in a considerable delay in recognising Parkinson's disease: the motor symptoms only appear when more than half of the dopaminergic neurons in the substantia nigra have already died.2
If early detection of Parkinson's disease were possible, the knowledge obtained could pave the way for the development and application of disease-modifying therapies. Recognising Parkinson's before the onset of motor symptoms in the prodromal phase is therefore the aim of various research groups. Kluge's research group is one of these.
The researchers utilised extracellular vesicles originating from neurons in blood plasma samples from Parkinson's patients and non-Parkinson's patients. They isolated these extracellular vesicles and then analysed them in immunoblot analyses. Using this method, they were able to detect the α-synuclein originating from extracellular vesicles. Compared to the healthy control group, patients with Parkinson's disease were found to have a significantly higher proportion of pathological α-synuclein forms. The results of the study group give hope for making a blood test for Parkinson's disease a reality.2
The role of OCT diagnostics in the early detection of neurodegenerative diseases is already the subject of intensive research. We know that changes in the thickness of the retinal nerve fibre layer can indicate an early onset of Alzheimer's disease.
The research team from London carried out the largest cross-sectional analysis of retinal imaging in patients with Parkinson's disease to date. They analysed the inner retinal anatomy using optical coherence tomography (OCT) in prevalent Parkinson's disease. They were able to identify markers that could make the presence of Parkinson's disease possible as early as seven years (on average) before clinical presentation.
The research group enlisted the help of artificial intelligence to do this. They analysed the datasets from the UK Biobank and the AlzEye dataset. With the help of digital support, eye scans of the two data sets were analysed. The data obtained from the inner retinal layers provided the desired markers. These were then evaluated with regard to the development of Parkinson's disease using a prospective research cohort.1
The AlzEye dataset represents a retrospective cohort of a total of 154,830 patients aged ≥ 40 years. Prevalent Parkinson's disease was present in 700 people. The control group comprised 105,770 people. The average age was 65.5 ± 13.5 years. The female gender predominated with 51.7 %. The UK Biobank is a prospective population-based cohort. 53 of the 50,405 participants (mean age 56.1 ± 8.2 years, 54.7 % female) developed Parkinson's disease after an average of 2653 ± 851 days.
The data sets from these two studies were used for the cross-sectional analysis. The thicknesses of the macular retinal nerve fibre layer (mRNFL), the ganglion cell inner plexiform layer (GCIPL) and the inner nuclear layer (INL) were investigated. Particular attention was paid to a correlation between prevalent Parkinson's disease and retinal thickness.2
Analysing the AlzEye dataset using artificial intelligence showed that people with prevalent PD had a thinner GCIPL and INL (compared to the control group). A thinner GCIPL and INL was also associated with the occurrence of Parkinson's disease after analysing the UK Biobank data set.2