Updating Our Definitions of Parkinson's Disease for a Molecular Age

Measurement of α-synuclein as protein cargo in plasma extracellular vesicles

Extracellular vesicles (EVs) are released by all cells and hold great promise as a class of biomarkers. This promise has led to increased interest in measuring EV proteins from both total EVs as well as brain-derived EVs in plasma. However, measuring cargo proteins in EVs has been challenging because EVs are present at low levels, and EV isolation methods are imperfect at separating EVs from free proteins. Thus, knowing whether a protein measured after EV isolation is truly inside EVs is difficult. In this study, we developed methods to measure whether a protein is inside EVs and quantify the ratio of a protein in EVs relative to total plasma. To achieve this, we combined a high-yield size-exclusion chromatography protocol with an optimized protease protection assay and Single Molecule Array (Simoa) digital enzyme-linked immunoassays (ELISAs) for ultrasensitive measurement of proteins inside EVs. We applied these methods to analyze α-synuclein and confirmed that a small fraction of the total plasma α-synuclein is inside EVs. Additionally, we developed a highly sensitive Simoa assay for phosphorylated α-synuclein (phosphorylated at the Ser129 residue). We found enrichment in the phosphorylated α-synuclein to total α-synuclein ratio inside EVs relative to outside EVs. Finally, we applied the methods we developed to measure total and phosphorylated α-synuclein inside EVs from Parkinson's disease and Lewy body dementia patient samples. This work provides a framework for determining the levels of proteins in EVs and represents an important step in the development of EV diagnostics for diseases of the brain, as well as other organs.

Parkinson's Disease Subtyping Using Clinical Features and Biomarkers: Literature Review and Preliminary Study of Subtype Clustering

The second most common progressive neurodegenerative disorder, Parkinson’s disease (PD), is characterized by a broad spectrum of symptoms that are associated with its progression. Several studies have attempted to classify PD according to its clinical manifestations and establish objective biomarkers for early diagnosis and for predicting the prognosis of the disease. Recent comprehensive research on the classification of PD using clinical phenotypes has included factors such as dominance, severity, and prognosis of motor and non-motor symptoms and biomarkers. Additionally, neuroimaging studies have attempted to reveal the pathological substrate for motor symptoms. Genetic and transcriptomic studies have contributed to our understanding of the underlying molecular pathogenic mechanisms and provided a basis for classifying PD. Moreover, an understanding of the heterogeneity of clinical manifestations in PD is required for a personalized medicine approach. Herein, we discuss the possible subtypes of PD based on clinical features, neuroimaging, and biomarkers for developing personalized medicine for PD. In addition, we conduct a preliminary clustering using gait features for subtyping PD. We believe that subtyping may facilitate the development of therapeutic strategies for PD.

Status and future directions of clinical trials in Parkinson's disease

Novel therapies are needed to treat Parkinson's disease (PD) in which the clinical unmet need is pressing. Currently, no clinically available therapeutic strategy can either retard or reverse PD or repair its pathological consequences. l-DOPA (levodopa) is still the gold standard therapy for motor symptoms yet symptomatic therapies for both motor and non-motor symptoms are improving. Many on-going, intervention trials cover a broad range of targets, including cell replacement and gene therapy approaches, quality of life improving technologies, and disease-modifying strategies (e.g., controlling aberrant α-synuclein accumulation and regulating cellular/neuronal bioenergetics). Notably, the repurposing of glucagon-like peptide-1 analogues with potential disease-modifying effects based on metabolic pathology associated with PD has been promising. Nevertheless, there is a clear need for improved therapeutic and diagnostic options, disease progression tracking and patient stratification capabilities to deliver personalized treatment and optimize trial design. This review discusses some of the risk factors and consequent pathology associated with PD and particularly the metabolic aspects of PD, novel therapies targeting these pathologies (e.g., mitochondrial and lysosomal dysfunction, oxidative stress, and inflammation/neuroinflammation), including the repurposing of metabolic therapies, and unmet needs as potential drivers for future clinical trials and research in PD.

Biomarkers of Parkinson's disease: 20 years later

Despite intensive effort, biomarker research for the detection of prodromal stage, diagnosis and progression of Parkinson's disease (PD) falls short of expectations. This article reviews the attempts in the last 20 years to find a biomarker, addresses challenges along the biomarker search and suggests the steps that should be taken to overcome these challenges. Although several biomarkers are currently available, none of them is specific enough for diagnosis, prediction of future PD or disease progression. The main reason for the failure finding a strong biomarker seems to be drastic heterogeneity of PD, which exhibits itself in all domains; from the clinic to pathophysiology or genetics. The diversity in patient selection, assessment methods or outcomes in biomarker studies also limit the interpretation and generalizability of the data. In search of a reliable biomarker, consideration of novel approaches encompassing individual demographic, clinical, genetic, epigenetic and environmental differences, employment of strategies enabling marker combinations, designing multicenter studies with compatible assessment methods, integration of data from preclinical domains and utilization of novel technology-based assessments are necessary.