As noted in Part I of this Parkinson’s disease (PD) blog series, the translation process from physician-based diagnosis into scientific diagnostic criteria used in multicentre Parkinson’s clinical trials of the disease is difficult, often impossible1.
Moreover, the diagnostic accuracy at first visit is only slightly above 80%, as shown by a meta-analysis of eleven Parkinson’s clinical trials assessing a UK Parkinson’s disease Society Brain Bank-based clinical diagnosis against post-mortem pathological examination as the gold standard2.
Such findings highlight the need for diagnostic tests and biomarkers to enhance diagnostic confidence in early disease, or to eventually diagnose Parkinson’s disease in its prodromal stages3. The suitable biomarker would allow treatment with putative neuroprotective agents to begin long before the significant and irreversible loss of neurons, and would enable the assessment of disease modification in individuals receiving treatment4. This blog examines the strengths and weaknesses of current Parkinson’s disease biomarkers and suggests the best available tools for studying Parkinson’s disease progression in disease modifying clinical trials.
Genetic biomarkers offer specific but limited utility
Mutations on SNCA, LRRK2, or VPS35 are responsible for development of autosomal dominant forms of Parkinson’s disease. Autosomal recessive PD with early onset and complex phenotypes that include parkinsonism have been assigned mutation on another PARK loci. There is increasing knowledge of other genes (including GBA, GCH1, ADH1C, and TBP) that contribute to an increased risk for the sporadic form of the PD. In fact, glucocerebrosidase (GBA) heterozygous mutation is the most prevalent genetic Parkinson’s disease biomarker, affecting 5–10% PD population. As genetic PD is still rare, accounting for only 2–3% of all Parkinson’s disease populations, genetic tests are not part of the standard diagnostic process.
Proteomics and other ‘omics’ techniques expected to improve biochemical biomarkers
There have been numerous attempts to identify specific and sensitive Parkinson’s disease biomarkers in the body fluids and biopsy tissues. Blood, cerebrospinal fluid (CSF) and saliva have all been extensively investigated in Parkinson’s disease research. Studies of alpha-synuclein (a-syn) in CSF showed conflicting results, although data has shown that PD patients have significantly lower a-syn levels. However, because a-syn and other proteins are present in the blood, erythrocytes and thrombocytes, even minor blood contamination may profoundly affect the results of CSF analysis. According to one research group, CSF samples should not contain more than 10 erythrocytes per microlitre CSF5, or 500 erythrocytes per microlitre CSF according to a European recommendation6. In saliva, a-syn was lower in PD patients compared to controls and this was inversely correlated with the change in the unified Parkinson’s disease rating scale (UPDRS) score7. Alpha-synuclein has also been found in the colonic mucosa before the emergence of PD clinical symptoms8, and additionally, published data showing gut microbiota in subjects with PD might be another potential biomarker for diagnosis of premotor PD9. Development of new, powerful tools – so-called ‘omics’ techniques — such as proteomics, metabolomics and transcriptomics in Parkinson’s disease biomarker research will certainly make significant progress shortly.
Disease and pharmacologic interventions affect interpretation of neuroimaging Parkinson’s disease biomarkers
Neuroimaging biomarkers have been widely used in visualisation of striatal dopaminergic depletion of neurons. Dopaminergic positron emission tomography (PET) scan is sensitive in identifying dopamine deficiency, even during the preclinical disease, and it is potentially useful in quantifying disease progression. However, there are a number of challenges associated with neuroimaging biomarkers, such as: interpretation of results may be affected by compensatory changes resulting from disease and pharmacological intervention, and dopaminergic PET is expensive, and needs specialised infrastructure and expert analysis.
123I-ioflupane single-photon emission CT (SPECT) (also known as DaTscan) is a more widely available and less expensive tool, which is already approved for routine clinical use. It can be used to differentiate between Parkinson’s disease and other diseases that manifest as PD, but are not associated with presynaptic nigrostriatal terminal dysfunction. Both dopaminergic PET and SPECT are useful adjuncts, but have shown limited correlation with clinical measures in therapeutic Parkinson’s clinical trials.
FDG-PET in Parkinson’s disease is helpful in differential diagnosis of parkinsonism and may be helpful in the assessment of disease progression. However, it is less specific than dopaminergic PET and it may be affected by compensatory changes or drug treatment.
New MRI techniques reveal specific changes
Structural magnetic resonance imaging (MRI) is more widely available than PET or SPECT and it is useful in differential diagnosis to identify symptomatic parkinsonism. Newly developed MRI techniques can reveal specific changes in the basal ganglia (i.e. iron accumulation at SN during PD progression), whereas diffusion-weighted imaging, volumetric imaging, automated subcortical volume segmentation and multimodal imaging have been explored to enhance diagnostic accuracy for Parkinson’s disease versus other types of degenerative parkinsonism.
Transcranial ultrasound (TCUS) has been used to demonstrate increased echogenicity in the midbrain of patients with PD, as a result of the increased nigral iron content in this region. Although TCUS can be useful in the detection of premotor PD and differentiations against other akinetic-rigid syndrome, the hyperechogenicity does not seem to increase with disease progression. TCUS is cost-effective and has shown promise as a possible imaging biomarker in Parkinson’s disease, but it is very dependent on operator skill, it is not specific and requires an adequate temporal acoustic bone window for good imaging.
Non-dopaminergic biomarkers useful in diagnosing Parkinson’s disease
Apart from dopaminergic biomarkers, there are a few non-dopaminergic biomarkers useful in diagnosis of Parkinson’s disease. Loss of cardiac sympathetic innervation can be documented in PD by decreased uptake of the sympathetic marker, 123I-metaiodobenzylguanidine (MIBG), in cardiac SPECT. Moreover, this marker contributes to the differential diagnosis between Parkinson’s disease and other forms of parkinsonism such as multiple system atrophy or dimension with Lewey bodies. MIBG is the only biomarker specifically addressed in the recently published Movement Disorders Society criteria for diagnosis of PD10. Uptake of 123I-MIBG in myocardial scintigraphy is often reported as a heart-to-mediastinum (H/M) ratio of count densities, whereas washout rate index may also be assessed using early and delayed images. MIBG should be considered in the light of the entire clinical presentation because various cardiovascular morbidities, latent cardiac disorder and medications may damage the postganglionic sympathetic neurons, leading to false positive findings. Additionally, 123I-MIBG H/M ratios may also decrease with age and show gender-specific variations, making it essential to use well-matched subgroups in Parkinson’s clinical trials.
Neuroinflammation biomarkers tested with varying success
Neuroinflammation markers of activated microglia, such as 11C-PBR028-PET have been tested with varying success. Small sample sizes and lack of autopsy-verified diagnosis have limited the value of results. A viable application of this technique is in monitoring therapeutic responses in Parkinson’s clinical trials.
Functional imaging represents best available tool for Parkinson’s disease research
Regardless of critical need, there is neither a fully validated diagnostic nor prognostic Parkinson’s disease biomarker available for Parkinson’s clinical trials and drug development. It seems that functional imaging, regardless of several limitations still represents the best available tools to study PD progression in disease-modifying clinical studies. We believe that new methods like a-syn accumulation assessment or combination of markers will provide greater reliability in the forthcoming years.
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- Babic T. The Role of Biomarkers in Parkinson’s Disease. Journal for Clinical Studies, May:2017:36-40.
- Rizzo G et al. Accuracy of clinical diagnosis of Parkinson disease: a syst. ematic review and meta-analysis. Neurology 2006:86, 566–576.
- Poewe W et al. Parkinson’s disease. Nature Reviews 2017:3:17013.
- Miller DB, O’Callaghan P. Biomarkers of Parkinson’s disease: Present and future. Metabolism 2015:64:40-46.
- Caudle WM et al. Using ‘omics’ to define pathogenesis and biomarkers of Parkinson’s disease. Expert Rev.Neurother. 2010:10, 925–942.
- Teunissen CE et al. A consensus protocol for the standardization of cerebro-spinal-fluid collection and biobanking. Neurology 73, 1914–1922.
- Devic I et al. Salivary alpha-synuclein and DJ-1: potential biomarkers for Parkinson’s disease. Brain 2011: 134, e178.
- Shannon KM. Is alpha-synuclein in the colon a biomarker for premotor Parkinson’s disease? Evidence from 3 cases. Mov. Disord. 27, 716–719.
- Scheperjans F. Can microbiota research change our understanding of neurodegenerative diseases? Neurodegener. Dis. Manag. 6, 81–85 (2016).
- Postuma RB et al. MDS Clinical Diagnostic Criteria for Parkinson’s Disease. Mov Dis 2015:30:1591-1599.