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

NCT01564992.

Summary Background Cognitive decline is a debilitating manifestation of disease progression in Parkinson’s disease. We aimed to develop a clinical-genetic score to predict global cognitive impairment in patients with the disease. Methods A prediction algorithm for global cognitive impairment (defined as Mini Mental State Exam (MMSE) ≤25) was built using data from 1,350 patients with 5,165 longitudinal visits over 12.8 (median, 2.8) years. Age at onset, MMSE, education, motor exam score, gender, depression and GBA mutations, machine selected through stepwise Cox’ hazards analysis and Akaike’s information criterion, were used to compute the multivariable predictor. Independent validation was achieved in another 1,132 patients with 19,127 visits over 8.6 (median, 6.5) years. Findings The cognitive risk score accurately predicted cognitive impairment within ten years of disease onset with an area under the curve (AUC) of >0.85 in both the discovery (95% CI, 0.821–0.902) and validation populations (95% CI, 0.779 – 0.913). 72.6% of patients scoring in the highest quartile were cognitively impaired by ten years vs. 3.7% in the lowest quartile (hazard ratio, 18.4, 95% CI, 9.4 – 36.1). Dementia or disabling cognitive impairment was predicted with an AUC of 0.877 (95% CI 0.788–0.943) and high negative predictive value (0.920, 95% 0.877–0.954) at the predefined cutoff (0.196). Performance was stable in 10,000 randomly resampled subsets. Interpretation Our predictive algorithm provides a potential test for future cognitive health or impairment in patients with Parkinson’s. It could improve trials of cognitive interventions and inform on prognosis.

Although speech disorder is frequently an early and prominent clinical feature of Parkinson's disease (PD) as well as atypical parkinsonian syndromes (APS) such as progressive supranuclear palsy (PSP) and multiple system atrophy (MSA), there is a lack of objective and quantitative evidence to verify whether any specific speech characteristics allow differentiation between PD, PSP and MSA. Speech samples were acquired from 77 subjects including 15 PD, 12 PSP, 13 MSA and 37 healthy controls. The accurate differential diagnosis of dysarthria subtypes was based on the quantitative acoustic analysis of 16 speech dimensions. Dysarthria was uniformly present in all parkinsonian patients but was more severe in PSP and MSA than in PD. Whilst PD speakers manifested pure hypokinetic dysarthria, ataxic components were more affected in MSA whilst PSP subjects demonstrated severe deficits in hypokinetic and spastic elements of dysarthria. Dysarthria in PSP was dominated by increased dysfluency, decreased slow rate, inappropriate silences, deficits in vowel articulation and harsh voice quality whereas MSA by pitch fluctuations, excess intensity variations, prolonged phonemes, vocal tremor and strained-strangled voice quality. Objective speech measurements were able to discriminate between APS and PD with 95% accuracy and between PSP and MSA with 75% accuracy. Dysarthria severity in APS was related to overall disease severity (r = 0.54, p = 0.006). Dysarthria with various combinations of hypokinetic, spastic and ataxic components reflects differing pathophysiology in PD, PSP and MSA. Thus, motor speech examination may provide useful information in the evaluation of these diseases with similar manifestations.