NPJ Parkinson's Disease最新文献

People with Parkinson’s disease (PWP) face critical challenges, including lack of access to neurological care, inadequate measurement and communication of motor symptoms, and suboptimal medication management and compliance. We have developed QDG-Care: a comprehensive connected care platform for Parkinson’s disease (PD) that delivers validated, quantitative metrics of all motor signs in PD in real time, monitors the effects of adjusting therapy and medication adherence and is accessible in the electronic health record. In this article, we describe the design and engineering of all components of QDG-Care, including the development and utility of the QDG Mobility and Tremor Severity Scores. We present the preliminary results and insights from an at-home trial using QDG-Care. QDG technology has enormous potential to improve access to, equity of, and quality of care for PWP, and improve compliance with complex time-critical medication regimens. It will enable rapid “Go-NoGo” decisions for new therapeutics by providing high-resolution data that require fewer participants at lower cost and allow more diverse recruitment.

Parkinson's disease (PD) is a common neurodegenerative disorder with a significant risk proportion driven by genetics. While much progress has been made, most of the heritability remains unknown. This is in-part because previous genetic studies have focused on the contribution of single nucleotide variants. More complex forms of variation, such as structural variants and tandem repeats, are already associated with several synucleinopathies. However, because more sophisticated sequencing methods are usually required to detect these regions, little is understood regarding their contribution to PD. One example is a polymorphic CT-rich region in intron 4 of the SNCA gene. This haplotype has been suggested to be associated with risk of Lewy Body (LB) pathology in Alzheimer's Disease and SNCA gene expression, but is yet to be investigated in PD. Here, we attempt to resolve this CT-rich haplotype and investigate its role in PD. We performed targeted PacBio HiFi sequencing of the region in 1375 PD cases and 959 controls. We replicate the previously reported associations and a novel association between two PD risk SNVs (rs356182 and rs5019538) and haplotype 4, the largest haplotype. Through quantitative trait locus analyzes we identify a significant haplotype 4 association with alternative CAGE transcriptional start site usage, not leading to significant differential SNCA gene expression in post-mortem frontal cortex brain tissue. Therefore, disease association in this locus might not be biologically driven by this CT-rich repeat region. Our data demonstrates the complexity of this SNCA region and highlights that further follow up functional studies are warranted.

While numerous single nucleotide variants and small indels have been identified in Parkinson's disease (PD), the contribution of structural variants (SVs), copy number variants (CNVs), and short tandem repeats (STRs) remains poorly understood. Here we investigated the association using the high-depth whole-genome sequencing data from 466 Chinese PD patients and 513 controls. Totally, we identified 29,561 SVs, 32,153 CNVs, and 174,905 STRs, and found that CNV deletions were significantly enriched in the end-proportion of autosomal chromosomes in PD. After genome-wide association analysis and replication in an external cohort of 352 cases and 547 controls, we validated that the 1.6 kb-deletion neighboring MUC19, 12.4kb-deletion near RXFP1 and GGGAAA repeats in SLC2A13 were significantly associated with PD. Moreover, the MUC19 deletion and the SLC2A13 5-copy repeat reduced the penetrance of the LRRK2 G2385R variant. Moreover, genes with these variants were dosage-sensitive. These data provided novel insights into the genetic architecture of PD.

Although most cases of Parkinson's disease (PD) are sporadic, mutations in over 20 genes are known to cause heritable forms of the disease. Recessive loss-of-function mutations in ATP13A2, a lysosomal transmembrane P5_B-type ATPase and polyamine exporter, can cause early-onset familial PD. Familial ATP13A2 mutations are also linked to related neurodegenerative diseases, including Kufor-Rakeb syndrome, hereditary spastic paraplegias, neuronal ceroid lipofuscinosis, and amyotrophic lateral sclerosis. Despite the severe effects of ATP13A2 mutations in humans, ATP13A2 knockout (KO) mice fail to exhibit neurodegeneration even at advanced ages, making it challenging to study the neuropathological effects of ATP13A2 loss in vivo. Germline deletion of ATP13A2 in rodents may trigger the upregulation of compensatory pathways during embryonic development that mask the full neurotoxic effects of ATP13A2 loss in the brain. To explore this idea, we selectively deleted ATP13A2 in the adult mouse brain by the unilateral delivery of an AAV-Cre vector into the substantia nigra of young adult mice carrying conditional loxP-flanked ATP13A2 KO alleles. We observe a progressive loss of striatal dopaminergic nerve terminals at 3 and 10 months after AAV-Cre delivery. Cre-injected mice also exhibit robust dopaminergic neuronal degeneration in the substantia nigra at 10 months. Adult-onset ATP13A2 KO also recreates many of the phenotypes observed in aged germline ATP13A2 KO mice, including lysosomal abnormalities, p62-positive inclusions, and neuroinflammation. Our study demonstrates that the adult-onset homozygous deletion of ATP13A2 in the nigrostriatal pathway produces robust and progressive dopaminergic neurodegeneration that serves as a useful in vivo model of ATP13A2-related neurodegenerative diseases.

Different neurostimulators for deep brain stimulation (DBS) come already with the ability to chronically sense local field potentials during stimulation. This invaluable new data has the potential to increase our understanding of disease-related brain activity patterns, their temporal evolution, and their modulation in response to therapies. It also gives the opportunity to unveil new electrophysiological biomarkers and ultimately bring adaptive stimulation therapies closer to clinical practice. Unfortunately, there are still very limited options on how to visualize, analyze, and exploit the full potential of the sensing data from these new DBS neurostimulators. To answer this need, we developed a free open-source toolbox, named DBScope, that imports data from neurostimulation devices and can be operated in two ways: via user interface and programmatically, as a library of functions. In this way, it can be used by both clinicians during clinical sessions (for instance, to visually inspect data from the current or previous in-clinic visits), and by researchers in their research pipelines (e.g., for pre-processing, feature extraction and biomarker search). All in all, the DBScope toolbox is set to facilitate the clinical decision-making process and the identification of clinically relevant biomarkers. The toolbox is already being used in clinical and research environments, and it is freely available to download at GitHub (where it is also fully documented).

The metabolic profile predating the onset of Parkinson’s disease (PD) remains unclear. We aim to investigate the metabolites associated with incident and prevalent PD and their predictive values in the UK Biobank participants with metabolomics and genetic data at the baseline. A panel of 249 metabolites was quantified using a nuclear magnetic resonance analytical platform. PD was ascertained by self-reported history, hospital admission records and death registers. Cox proportional hazard models and logistic regression models were used to investigate the associations between metabolites and incident and prevalent PD, respectively. Area under receiver operating characteristics curves (AUC) were used to estimate the predictive values of models for future PD. Among 109,790 participants without PD at the baseline, 639 (0.58%) individuals developed PD after one year from the baseline during a median follow-up period of 12.2 years. Sixty-eight metabolites were associated with incident PD at nominal significance (P < 0.05), spanning lipids, lipid constituent of lipoprotein subclasses and ratios of lipid constituents. After multiple testing corrections (P < 9(times)10⁻⁴), polyunsaturated fatty acids (PUFA) and omega-6 fatty acids remained significantly associated with incident PD, and PUFA was shared by incident and prevalent PD. Additionally, 14 metabolites were exclusively associated with prevalent PD, including amino acids, fatty acids, several lipoprotein subclasses and ratios of lipids. Adding these metabolites to the conventional risk factors yielded a comparable predictive performance to the risk-factor-based model (AUC = 0.766 vs AUC = 0.768, P = 0.145). Our findings suggested metabolic profiles provided additional knowledge to understand different pathways related to PD before and after its onset.

The seeding amplification assay (SAA) has recently emerged as a valuable tool for detecting α-synuclein (αSyn) aggregates in various clinically accessible biospecimens. Despite its efficiency and specificity, optimal tissue-specific conditions for distinguishing Parkinson's disease (PD) from non-PD outside the brain remain underexplored. This study systematically evaluated 150 reaction conditions to identify the one with the highest discriminatory potential between PD and non-synucleinopathy controls using skin samples, resulting in a modified SAA. The streamlined SAA achieved an overall sensitivity of 92.46% and specificity of 93.33% on biopsy skin samples from 332 PD patients and 285 controls within 24 h. Inter-laboratory reproducibility demonstrated a Cohen's kappa value of 0.87 (95% CI 0.69-1.00), indicating nearly perfect agreement. Additionally, αSyn seeds in the skin were stable at -80 °C but were vulnerable to short-term exposure to non-ultra-low temperatures and grinding. This study thoroughly investigated procedures for sample preprocessing, seed amplification, and storage, introducing a well-structured experimental framework for PD diagnosis using skin samples.

Many studies have reported metabolomic analysis of different bio-specimens from Parkinson's disease (PD) patients. However, inconsistencies in reported metabolite concentration changes make it difficult to draw conclusions as to the role of metabolism in the occurrence or development of Parkinson's disease. We reviewed the literature on metabolomic analysis of PD patients. From 74 studies that passed quality control metrics, 928 metabolites were identified with significant changes in PD patients, but only 190 were replicated with the same changes in more than one study. Of these metabolites, 60 exclusively increased, such as 3-methoxytyrosine and glycine, 54 exclusively decreased, such as pantothenic acid and caffeine, and 76 inconsistently changed in concentration in PD versus control subjects, such as ornithine and tyrosine. A genome-scale metabolic model of PD and corresponding metabolic map linking most of the replicated metabolites enabled a better understanding of the dysfunctional pathways of PD and the prediction of additional potential metabolic markers from pathways with consistent metabolite changes to target in future studies.

In Parkinson's disease (PD), GBA1- and LRRK2-mutations are associated with different clinical phenotypes which might be related to differential involvement of the cholinergic system. We investigated cholinergic integrity in 149 asymptomatic GBA1 and 169 asymptomatic LRRK2 mutation carriers, 112 LRRK2 and 60 GBA1 carriers with PD, 492 idiopathic PD, and 180 controls from the PPMI cohort. Basal forebrain volumes were extracted and white matter pathways from nucleus basalis of Meynert (NBM) to cortex and from pedunculopontine nucleus (PPN) to thalamus were assessed with a free water-corrected DTI model. Bayesian ANCOVAs were conducted for group comparisons and Bayesian linear mixed models to assess associations with cognitive decline. Basal forebrain volumes were increased in asymptomatic GBA1 (Bayes Factor against the null hypothesis (BF₁₀) = 75.2) and asymptomatic LRRK2 (BF₁₀ = 57.0) compared to controls. Basal forebrain volumes were increased in LRRK2- compared to GBA1-PD (BF₁₀ = 14.5) and idiopathic PD (BF₁₀ = 3.6*10⁷), with no difference between idiopathic PD and PD-GBA1 (BF₁₀ = 0.25). Mean diffusivity along the medial NBM pathway was decreased in asymptomatic GBA1 compared to controls (BF₁₀ = 30.3). Over 5 years, idiopathic PD and PD-GBA1 declined across all cognitive domains whereas PD-LRRK2 patients only declined in processing speed. We found an interaction between basal forebrain volume and time in predicting multiple cognitive domains in idiopathic PD and PD-GBA1, but not in PD-LRRK2. While LRRK2 and GBA1 mutations are both associated with increased basal forebrain volume at asymptomatic stages, this increase persists at the symptomatic PD stage only in LRRK2 and might be related to slower cognitive decline in these patients.