Abnormal α-synuclein aggregation is a key pathological feature of a group of neurodegenerative diseases known as synucleinopathies, which include Parkinson’s disease (PD), dementia with Lewy bodies and multiple system atrophy (MSA). The pathogenic β-sheet seed conformation of α-synuclein is found in various tissues, suggesting potential as a biomarker, but few studies have been able to reliably detect these seeds in serum samples. In this study, we developed a modified assay system, called immunoprecipitation-based real-time quaking-induced conversion (IP/RT-QuIC), which enables the detection of pathogenic α-synuclein seeds in the serum of individuals with synucleinopathies. In our internal first and second cohorts, IP/RT-QuIC showed high diagnostic performance for differentiating PD versus controls (area under the curve (AUC): 0.96 (95% confidence interval (CI) 0.95–0.99)/AUC: 0.93 (95% CI 0.84–1.00)) and MSA versus controls (AUC: 0.64 (95% CI 0.49–0.79)/AUC: 0.73 (95% CI 0.49–0.98)). IP/RT-QuIC also showed high diagnostic performance in differentiating individuals with PD (AUC: 0.86 (95% CI 0.74–0.99)) and MSA (AUC: 0.80 (95% CI 0.65–0.97)) from controls in a blinded external cohort. Notably, amplified seeds maintained disease-specific properties, allowing the differentiation of samples from individuals with PD versus MSA. In summary, here we present a novel platform that may allow the detection of individuals with synucleinopathies using serum samples.

Objective The pathogenesis of Parkinson's disease (PD) involves complex interactions between environmental and genetic factors. Metabolomics can shed light on alterations in metabolic pathways in many diseases, including neurodegenerative diseases. In the present study, we attempted to elucidate the candidate metabolic pathway(s) associated with PD. Methods Serum samples were collected from 35 individuals with idiopathic PD without dementia and 15 healthy age-matched control participants without PD. This analysis used a combination of three independent platforms: ultrahigh-performance liquid chromatography/tandem mass spectrometry (UPLC/MS/MS) optimised for basic species, UPLC/MS/MS optimised for acidic species and gas chromatography/MS (GC/MS). Results The metabolomic profiles of PD were clearly different from normal controls. PD profiles had significantly lower levels of tryptophan, caffeine and its metabolites, bilirubin and ergothioneine, and significantly higher levels of levodopa metabolites and biliverdin than those of normal controls. Alterations in the bilirubin/biliverdin ratio and ergothioneine can indicate oxidative stress intensity and may suggest elevated oxidative stress and/or insufficient ability for scavenging free radicals, which could contribute to PD pathogenesis. Decreased serum tryptophan level is associated with psychiatric problems in PD. A decrease in serum caffeine levels is consistent with an inverse association of caffeine consumption with development of PD based on past epidemiological studies. Conclusions Metabolomic analysis detected biomarkers associated with PD pathogenesis and disease progression. Since critical metabolic biomarkers need to be identified in PD, future studies should include assay validation and replication in independent cohorts.

The incidence of neurodegenerative diseases has shown an increasing trend. These conditions typically cause progressive functional disability. Identification of robust biomarkers of neurodegenerative diseases is a key imperative to facilitate early identification of the pathological features and to foster a better understanding of the pathogenetic mechanisms of individual diseases. Diffusion tensor imaging (DTI) is the most widely used diffusion MRI technique for assessment of neurodegenerative diseases. The DTI parameters are promising biomarkers for evaluation of microstructural changes; however, some limitations of DTI restrict its wider clinical use. New diffusion MRI techniques, such as diffusion kurtosis imaging (DKI), bi‐tensor DTI, and neurite orientation density and dispersion imaging (NODDI) have been demonstrated to provide value addition to DTI for evaluation of neurodegenerative diseases. In this review article, we summarize the key technical aspects and provide an overview of the current state of knowledge regarding the role of DKI, bi‐tensor DTI, and NODDI as biomarkers of microstructural changes in representative neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease.Level of Evidence: 5Technical Efficacy Stage: 2 J. MAGN. RESON. IMAGING 2020;52:1620–1636.

Leucine-Rich Repeat Kinase 2 (LRRK2) is a causative gene for the autosomal dominant form of Parkinson's disease (PD). The gene encodes the ∼280 kDa LRRK2 protein composed of domains such as leucine-rich repeats, Ras in complex proteins (Roc) followed by C-terminal of Roc (COR), mitogen-activated protein kinase kinase kinase (MAPKKK) and WD40. However, the normal function of the protein as well as its contribution to the pathogenesis of PD remains largely unknown. Here we describe the localization of LRRK2 in Golgi apparatus, plasma membrane and synaptic vesicles in cultured cells including mouse primary neurons. The membrane association of LRRK2 resists solubilization by ice-cold 1% Triton X-100, indicating its association through lipid rafts. To investigate whether mutations found in PD patients affect the localization of LRRK2, we transfected various LRRK2 mutants into cultured cells and performed fractionation experiments. Unexpectedly, the mutants are collected in both membrane and soluble fractions in a manner similar to wild type (WT). I2020T mutant LRRK2 associates with lipid rafts, similar to the WT. The lipid raft association of LRRK2 mutants as well as WT LRRK2 suggests that alteration of LRRK2 function on lipid rafts contributes to the pathogenesis of PD.