Recent Advances in Biomarkers for Parkinson’s Disease

Central and peripheral insulin-like peptides (ILPs), which include insulin, insulin-like growth factor 1 (IGF1) and IGF2, exert many effects in the brain. Through their actions on brain growth and differentiation, ILPs contribute to building circuitries that subserve metabolic and behavioural adaptation to internal and external cues of energy availability. In the adult brain each ILP has distinct effects, but together their actions ultimately regulate energy homeostasis - they affect nutrient sensing and regulate neuronal plasticity to modulate adaptive behaviours involved in food seeking, including high-level cognitive operations such as spatial memory. In essence, the multifaceted activity of ILPs in the brain may be viewed as a system organization involved in the control of energy allocation. Show more

To date there is no accepted clinical diagnostic test for Parkinson's disease (PD) based on biochemical analysis of blood or cerebrospinal fluid (CSF). alpha-Synuclein (alpha-syn) protein has been linked to the pathogenesis of PD with the discovery of mutations in the gene encoding alpha-syn in familial cases with early-onset PD. Lewy bodies and Lewy neurites, which constitute the main pathological features in the brains of patients with sporadic PD and dementia with Lewy bodies, are formed by the conversion of soluble monomers of alpha-syn into insoluble aggregates. We recently reported the presence of alpha-syn in normal human blood plasma and in postmortem CSF. Here, we investigated whether alpha-syn can be used as a biomarker for PD. We have developed a novel ELISA method that detects only oligomeric "soluble aggregates" of alpha-syn. Using this ELISA, we report the presence of significantly elevated (P=0.002) levels of oligomeric forms of alpha-syn in plasma samples obtained from 34 PD patients compared with 27 controls; 52% (95% confidence intervals 0.353-0.687) of the PD patients displayed signals >0.5 OD with our ELISA assay in comparison to only 14.8% (95% confidence intervals 0.014-0.281) for the control cases. An analysis of the test's diagnostic value revealed a specificity of 0.852 (95% confidence intervals 0.662-0.958), sensitivity of 0.529 (95% confidence intervals 0.351-0.702) and a positive predictive value of 0.818 (95% confidence intervals 0.597-0.948). These observations offer new opportunities for developing diagnostic tests for PD and related diseases and for testing therapeutic agents aimed at preventing or reversing the aggregation of alpha-syn. Show more

Parkinson's disease varies widely in clinical manifestations, course of progression and biomarker profiles from person to person. Identification of distinct Parkinson's disease subtypes is of great priority to illuminate underlying pathophysiology, predict progression and develop more efficient personalized care approaches. There is currently no clear way to define and divide subtypes in Parkinson's disease. Using data from the Parkinson's Progression Markers Initiative, we aimed to identify distinct subgroups via cluster analysis of a comprehensive dataset at baseline (i.e. cross-sectionally) consisting of clinical characteristics, neuroimaging, biospecimen and genetic information, then to develop criteria to assign patients to a Parkinson's disease subtype. Four hundred and twenty-one individuals with de novo early Parkinson's disease were included from this prospective longitudinal multicentre cohort. Hierarchical cluster analysis was performed using data on demographic and genetic information, motor symptoms and signs, neuropsychological testing and other non-motor manifestations. The key classifiers in cluster analysis were a motor summary score and three non-motor features (cognitive impairment, rapid eye movement sleep behaviour disorder and dysautonomia). We then defined three distinct subtypes of Parkinson's disease patients: 223 patients were classified as 'mild motor-predominant' (defined as composite motor and all three non-motor scores below the 75th percentile), 52 as 'diffuse malignant' (composite motor score plus either ≥1/3 non-motor score >75th percentile, or all three non-motor scores >75th percentile) and 146 as 'intermediate'. On biomarkers, people with diffuse malignant Parkinson's disease had the lowest level of cerebrospinal fluid amyloid-β (329.0 ± 96.7 pg/ml, P = 0.006) and amyloid-β/total-tau ratio (8.2 ± 3.0, P = 0.032). Data from deformation-based magnetic resonance imaging morphometry demonstrated a Parkinson's disease-specific brain network had more atrophy in the diffuse malignant subtype, with the mild motor-predominant subtype having the least atrophy. Although disease duration at initial visit and follow-up time were similar between subtypes, patients with diffuse malignant Parkinson's disease progressed faster in overall prognosis (global composite outcome), with greater decline in cognition and in dopamine functional neuroimaging after an average of 2.7 years. In conclusion, we introduce new clinical criteria for subtyping Parkinson's disease based on a comprehensive list of clinical manifestations and biomarkers. This clinical subtyping can now be applied to individual patients for use in clinical practice using baseline clinical information. Even though all participants had a recent diagnosis of Parkinson's disease, patients with the diffuse malignant subtype already demonstrated a more profound dopaminergic deficit, increased atrophy in Parkinson's disease brain networks, a more Alzheimer's disease-like cerebrospinal fluid profile and faster progression of motor and cognitive deficits. Show more