Chapter 108
Neurodegeneration — 14
The hunt for a biomarker for Parkinson’s has lagged the progress for Alzheimer’s disease, but recent work is very encouraging for α-synuclein seed amplification assays (SAA) from cerebrospinal fluid for identifying individuals with high sensitivity and specificity. This was validated in a large study of more than 1,100 participants, which included 545 with Parkinson’s, 51 people with the precursor signs of loss of smell or rapid eye movement sleep behavior disorder (RBD), and 310 carriers without manifesting Parkinson’s. Being able to differentiate carriers of gene mutations who do not manifest the disease with this biomarker presents a real potential advantage. Alternative to the need for a spinal tap, the SAA assay from skin or skin biopsy for phosphorylated α-synuclein has high accuracy. Multiple types of PET imaging (dopaminergic, metabolic, or cardiac denervation) have been shown to have high sensitivity, but these are not widely available, they are expensive, and they expose the individual to high doses of radiation.
We’re still in need of a reliable blood test, and many candidates have been raised, such as glycoprotein nonmetastatic melanoma protein B (GPNMB), a mitochondrial damage assay, DOPA decarboxylase for dopaminergic cell loss, and many others. A simple, noninvasive biomarker that can be used to accurately predict Parkinson’s years before it is clinically declared is a major unmet need. That’s why the report of a blood panel of over 120 proteins that could predict Parkinson’s disease up to seven years before symptom onset is seen as a very encouraging advance. Several more are in the works.
We’ve had better forecasting success with the retina image. In two studies in which I collaborated with Pearse Keane and his colleagues at Moorfields Eye Hospital and the University College of London in the United Kingdom, AI analysis of retinal images could accurately predict Parkinson’s’ disease up to nine years before symptoms occurred. As emphasized with Alzheimer’s disease, the retina gateway to the brain, with the help of the digital eyes of AI, is providing an important means for differentiating high risk for neurodegenerative disorders.
Detection and tracking the progression of the disease are having success with wristband accelerometers that can pick up change in gait and motor activity years before symptoms, nocturnal breathing signals from radio waves, and multimodal AI of imaging, electronic health records, and genetic and metabolomics to predict an individual’s trajectory and treatment response.
The current treatments for Parkinson’s are diverse and are all symptom directed, including a long list of medications for treating the motor abnormalities and the neuropsychiatric sequelae of depression, anxiety, sleep disturbances, hallucinations, orthostatic hypotension, urinary dysfunction, and dementia. Brain surgery to enable deep brain stimulation or an ablative procedure without implantation of hardware are other options.
For the first time, we may be on the brink of therapy to slow or stop the progression of Parkinson’s disease. Prasinezumab is a monoclonal antibody that binds aggregated α-synuclein and was assessed in a randomized trial of Parkinson’s disease. In the subgroup who were taking monoamine oxide inhibitors or had other prespecified signs of faster progression, there was evidence for slowing of the motor symptom (tremor, stiffness, slowness of movement) progression over four years of follow-up.