Background Genome-wide association studies (GWASs) in Parkinson's disease (PD) have increased the scope of biological knowledge about the disease over the past decade. We sought to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into disease etiology. Methods We performed the largest meta-GWAS of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases (having a first degree relative with PD), and 1.4M controls. We carried out a meta-analysis of this GWAS data to nominate novel loci. We then evaluated heritable risk estimates and predictive models using this data. We also utilized large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type and biological pathway enrichments for the identified risk factors. Additionally we examined shared genetic risk between PD and other phenotypes of interest via genetic correlations followed by Mendelian randomization. Findings We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16-36% of the heritable risk of PD depending on prevalence. Integrating methylation and expression data within a Mendelian randomization framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested PD loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. Mendelian randomization between cognitive performance and PD risk showed a robust association. Interpretation These data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified. Funding See supplemental materials (Text S2). lead to earlier detection and refined diagnostics, which may help improve clinical trials (4). The generation of copious amounts of public summary statistics created by this effort relating to both the GWAS and subsequent analyses of gene expression and methylation patterns may be of use to investigators planning follow-up functional studies in stem cells or other cellular screens, allowing them to prioritize targets more efficiently using our data as additional evidence. We hope our findings may have some downstream clinical impact in the future such as improved patient stratification for clinical trials and genetically informed drug targets.

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To determine the estimates of minimal, moderate, and large clinically important differences (CIDs) for the Unified Parkinson's Disease Rating Scale (UPDRS). Design: Cross-sectional analysis of the CIDs for UPDRS total and motor scores was performed on patients with Parkinson disease (PD) using distribution-and anchorbased approaches based on the following 3 external standards: disability (10% on the Schwab and England Activities of Daily Living Scale), disease stage (1 stage on the Hoehn and Yahr Scale), and quality of life (1 SD on the 12-Item Short Form Health Survey).

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Background Increasing evidence supports an extensive and complex genetic contribution to PD. Previous genome‐wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age at onset are largely unknown. Objectives To identify the genetic determinants of PD age at onset. Methods Using genetic data of 28,568 PD cases, we performed a genome‐wide association study based on PD age at onset. Results We estimated that the heritability of PD age at onset attributed to common genetic variation was ∼0.11, lower than the overall heritability of risk for PD (∼0.27), likely, in part, because of the subjective nature of this measure. We found two genome‐wide significant association signals, one at SNCA and the other a protein‐coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni‐corrected significant effect at other known PD risk loci, GBA, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. Notably, SNCA, TMEM175, SCARB2, BAG3, and GBA have all been shown to be implicated in α‐synuclein aggregation pathways. Remarkably, other well‐established PD risk loci, such as GCH1 and MAPT, did not show a significant effect on age at onset of PD. Conclusions Overall, we have performed the largest age at onset of PD genome‐wide association studies to date, and our results show that not all PD risk loci influence age at onset with significant differences between risk alleles for age at onset. This provides a compelling picture, both within the context of functional characterization of disease‐linked genetic variability and in defining differences between risk alleles for age at onset, or frank risk for disease. © 2019 International Parkinson and Movement Disorder Society

We performed the largest genome-wide association study of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases, and 1.4M controls. We identified 90 independent genome-wide significant signals across 78 loci, including 38 independent risk signals in 37 novel loci. These variants explained 26-36% of the heritable risk of PD. Tests of causality within a Mendelian randomization framework identified putatively causal genes for 70 risk signals. Tissue expression enrichment analysis suggested that signatures of PD loci were heavily brain-enriched, consistent with specific neuronal cell types being implicated from single cell expression data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. In sum, these data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified.

Many patients with Parkinson's disease (PD) have clinically significant anxiety, depression, fatigue, sleep disturbance, or sensory symptoms. The comorbidity of these nonmotor symptoms and their relationship to PD severity has not been extensively evaluated. Ninety- nine nondemented PD patients were evaluated with the following battery of tests: Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI), Fatigue Severity Scale (FSS), Pittsburgh Sleep Quality Index (PSQI), a sensory symptom questionnaire, Unified Parkinson's Disease Rating Scale (UPDRS), Hoehn & Yahr (H/Y) Stage, and the Schwab & England ADL scale (S/E). The comorbidity of the nonmotor symptoms and their relationship to PD severity was analyzed. Thirty-six percent of the study population had depression (BDI > or =10), 33% had anxiety (BAI > or =10), 40% had fatigue (FSS > 4), 47% had sleep disturbance (PSQI > 5), and 63% reported sensory symptoms. Only 12% of the sample had no nonmotor symptoms. Fifty-nine percent of the patients had two or more nonmotor symptoms, and nearly 25% had four or more. Increased comorbidity was associated with greater PD severity (P < 001). This study reveals that the nonmotor symptoms of PD frequently occur together in the same patients. Increased comorbidity of the five nonmotor symptoms was associated with greater PD severity. These results suggest that recognition of these diverse nonmotor symptoms may be enhanced by looking for others when one nonmotor symptom has been identified.

Fatigue is a common problem in Parkinson's disease (PD), often the most troubling of all symptoms. It is poorly understood, generally under-recognized, and has no known treatment. This article reviews what is known about the symptom, putting it into the context of fatigue in other disorders, and outlines a program for developing better understanding and therapy.