Objective: To describe the frequency of mild cognitive impairment (MCI) in Parkinson disease (PD) in a cohort of newly diagnosed incident PD cases and the associations with a panel of biomarkers.Methods: Between June 2009 and December 2011, 219 subjects with PD and 99 age-matched controls participated in clinical and neuropsychological assessments as part of a longitudinal observational study. Consenting individuals underwent structural MRI, lumbar puncture, and genotyping for common variants of COMT, MAPT, SNCA, BuChE, EGF, and APOE. PD-MCI was defined with reference to the new Movement Disorder Society criteria.Results: The frequency of PD-MCI was 42.5% using level 2 criteria at 1.5 SDs below normative values. Memory impairment was the most common domain affected, with 15.1% impaired at 1.5 SDs. Depression scores were significantly higher in those with PD-MCI than the cognitively normal PD group. A significant correlation was found between visual Pattern Recognition Memory and cerebrospinal b-amyloid 1-42 levels (b standardized coefficient 5 0.350; p 5 0.008) after controlling for age and education in a linear regression model, with lower b-amyloid 1-42 and 1-40 levels observed in those with PD-MCI. Voxel-based morphometry did not reveal any areas of significant gray matter loss in participants with PD-MCI compared with controls, and no specific genotype was associated with PD-MCI at the 1.5-SD threshold. Conclusions:In a large cohort of newly diagnosed PD participants, PD-MCI is common and significantly correlates with lower cerebrospinal b-amyloid 1-42 and 1-40 levels. Future longitudinal studies should enable us to determine those measures predictive of cognitive decline.
IMPORTANCE Sleep disturbances are recognized as a common nonmotor complaint in Parkinson disease but their etiology is poorly understood. OBJECTIVE To define the sleep and circadian phenotype of patients with early-stage Parkinson disease. DESIGN, SETTING, AND PARTICIPANTS Initial assessment of sleep characteristics in a large population-representative incident Parkinson disease cohort (N=239) at the University of Cambridge, England, followed by further comprehensive case-control sleep assessments in a subgroup of these patients (n=30) and matched controls (n=15). MAIN OUTCOMES AND MEASURES Sleep diagnoses and sleep architecture based on polysomnography studies, actigraphy assessment, and 24-hour analyses of serum cortisol, melatonin, and peripheral clock gene expression (Bmal1, Per2, and Rev-Erbα). RESULTS Subjective sleep complaints were present in almost half of newly diagnosed patients and correlated significantly with poorer quality of life. Patients with Parkinson disease exhibited increased sleep latency (P = .04), reduced sleep efficiency (P = .008), and reduced rapid eye movement sleep (P = .02). In addition, there was a sustained elevation of serum cortisol levels, reduced circulating melatonin levels, and altered Bmal1 expression in patients with Parkinson disease compared with controls. CONCLUSIONS AND RELEVANCE Sleep dysfunction seen in early Parkinson disease may reflect a more fundamental pathology in the molecular clock underlying circadian rhythms.
ObjectiveWe hypothesized that specific mutations in the β‐glucocerebrosidase gene (GBA) causing neuropathic Gaucher's disease (GD) in homozygotes lead to aggressive cognitive decline in heterozygous Parkinson's disease (PD) patients, whereas non‐neuropathic GD mutations confer intermediate progression rates.MethodsA total of 2,304 patients with PD and 20,868 longitudinal visits for up to 12.8 years (median, 4.1) from seven cohorts were analyzed. Differential effects of four types of genetic variation in GBA on longitudinal cognitive decline were evaluated using mixed random and fixed effects and Cox proportional hazards models.ResultsOverall, 10.3% of patients with PD and GBA sequencing carried a mutation. Carriers of neuropathic GD mutations (1.4% of patients) had hazard ratios (HRs) for global cognitive impairment of 3.17 (95% confidence interval [CI], 1.60–6.25) and a hastened decline in Mini–Mental State Exam scores compared to noncarriers (p = 0.0009). Carriers of complex GBA alleles (0.7%) had an HR of 3.22 (95% CI, 1.18–8.73; p = 0.022). By contrast, the common, non‐neuropathic N370S mutation (1.5% of patients; HR, 1.96; 95% CI, 0.92–4.18) or nonpathogenic risk variants (6.6% of patients; HR, 1.36; 95% CI, 0.89–2.05) did not reach significance.InterpretationMutations in the GBA gene pathogenic for neuropathic GD and complex alleles shift longitudinal cognitive decline in PD into “high gear.” These findings suggest a relationship between specific types of GBA mutations and aggressive cognitive decline and have direct implications for improving the design of clinical trials. Ann Neurol 2016;80:674–685
Genomic technologies such as next-generation sequencing (NGS) are revolutionizing molecular diagnostics and clinical medicine. However, these approaches have proven inefficient at identifying pathogenic repeat expansions. Here, we apply a collection of bioinformatics tools that can be utilized to identify either known or novel expanded repeat sequences in NGS data. We performed genetic studies of a cohort of 35 individuals from 22 families with a clinical diagnosis of cerebellar ataxia with neuropathy and bilateral vestibular areflexia syndrome (CANVAS). Analysis of whole-genome sequence (WGS) data with five independent algorithms identified a recessively inherited intronic repeat expansion [(AAGGG) exp ] in the gene encoding Replication Factor C1 (RFC1). This motif, not reported in the reference sequence, localized to an Alu element and replaced the reference (AAAAG) 11 short tandem repeat. Genetic analyses confirmed the pathogenic expansion in 18 of 22 CANVAS-affected families and identified a core ancestral haplotype, estimated to have arisen in Europe more than twenty-five thousand years ago. WGS of the four RFC1-negative CANVAS-affected families identified plausible variants in three, with genomic re-diagnosis of SCA3, spastic ataxia of the Charlevoix-Saguenay type, and SCA45. This study identified the genetic basis of CANVAS and demonstrated that these improved bioinformatics tools increase the diagnostic utility of WGS to determine the genetic basis of a heterogeneous group of clinically overlapping neurogenetic disorders.
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