Background There is mounting evidence for a connection between the gut and Parkinson’s disease (PD). Dysbiosis of gut microbiota could explain several features of PD. Objective To determine if PD involves dysbiosis of gut microbiome, disentangle effects of confounders, and identify candidate taxa and functional pathways to guide research. Methods 197 PD cases and 130 controls were studied. Microbial composition was determined by 16S rRNA gene sequencing of DNA extracted from stool. Metadata were collected on 39 potential confounders including medications, diet, gastrointestinal symptoms, and demographics. Statistical analyses were conducted while controlling for potential confounders and correcting for multiple testing. We tested differences in the overall microbial composition, taxa abundance, and functional pathways. Results Independent microbial signatures were detected for PD (P=4E-5), subjects’ region of residence within the United States (P=3E-3), age (P=0.03), sex (P=1E-3) and dietary fruits/vegetables (P=0.01). Among patients, independent signals were detected for catechol-O-methyltransferase-inhibitors (P=4E-4), anticholinergics (P=5E-3), and possibly carbidopa/levodopa (P=0.05). We found significantly altered abundance of Bifidobacteriaceae, Christensenellaceae, [Tissierellaceae], Lachnospiraceae, Lactobacillaceae, Pasteurellaceae and Verrucomicrobiaceae families. Functional predictions revealed changes in numerous pathways including metabolism of plant-derived compounds and xenobiotics degradation. Conclusion PD is accompanied by dysbiosis of gut microbiome. Results coalesce divergent findings of prior studies, reveal altered abundance of several taxa, nominate functional pathways, and demonstrate independent effects of PD medications on the microbiome. The findings provide new leads and testable hypotheses on the pathophysiology and treatment of PD.

Of 842 consecutive patients with movement disorders seen over a 71 month period, 28 (3.3%) were diagnosed as having a documented or clinically established psychogenic movement disorder. Tremor was most common (50%) followed by dystonia, myoclonus, and parkinsonism. Clinical descriptions of various types are reviewed. Clinical characteristics common in these patients included distractability (86%), abrupt onset (54%), and selective disabilities (39%). Distractability seems to be most important in tremor and least important in dystonia. Other diagnostic clues included entrainment of tremor to the frequency of repetitive movements of another limb, fatigue of tremor, stimulus sensitivity, and previous history of psychogenic illness. On examination, 71% had other psychogenic features. Over 60% had a clear history of a precipitating event and secondary gain and 50% had a psychiatric diagnosis (usually depression). Twenty five per cent of patients presented with combined psychogenic movement disorder and organic movement disorder; 35% resolved and this subgroup had a shorter duration of disease than those who are unresolved. Psychogenic movement disorder represents an uncommon diagnosis among patients with movement disorders. The ability to make a diagnosis rests on the presence of a multitude of clinical clues and therapeutic action should be taken as early as possible.

Objective: To assess the cognitive phenotype of glucocerebrosidase (GBA) mutation carriers with early-onset Parkinson disease (PD). Methods:We administered a neuropsychological battery and the University of Pennsylvania Smell Identification Test (UPSIT) to participants in the CORE-PD study who were tested for mutations in PARKIN, LRRK2, and GBA. Participants included 33 GBA mutation carriers and 60 noncarriers of any genetic mutation. Primary analyses were performed on 26 GBA heterozygous mutation carriers without additional mutations and 39 age-and PD duration-matched noncarriers. Five cognitive domains, psychomotor speed, attention, memory, visuospatial function, and executive function, were created from transformed z scores of individual neuropsychological tests. Clinical diagnoses (normal, mild cognitive impairment [MCI], dementia) were assigned blind to genotype based on neuropsychological performance and functional impairment as assessed by the Clinical Dementia Rating (CDR) score. The association between GBA mutation status and neuropsychological performance, CDR, and clinical diagnoses was assessed.

In clinical trials for patients with Parkinson's disease (PD) with motor fluctuations, efficacy is generally ascribed to an intervention if motor function is significantly improved or if "off" time is significantly reduced. However, we have argued that patients might not be improved if off time is reduced only to the extent that unwanted dyskinesia is increased. Therefore, a home diary should include an assessment of dyskinesia to provide an accurate reflection of clinical status over a period of time. We undertook two studies to develop a home diary to assess functional status in patients with PD with motor fluctuations and dyskinesia. In both studies, patients concurrently completed a test and a reference diary. In Study I, we evaluated the impact of different severities of dyskinesia on patient-defined functional status. There were 1,149 evaluable half-hour time periods from 24 patients; 94.3% of off time was considered "bad" time and 90.2% of "on" time without dyskinesia, 72.6% of on time with mild dyskinesia, 43.0% of on time with moderate dyskinesia, and 15.2% of on time with severe dyskinesia was considered "good" time. In Study II, we evaluated a new home diary designed to separate dyskinesia that had a negative impact on patient-defined functional status from dyskinesia that did not. There were 816 evaluable time periods from 17 patients; 84.9% of off time and 89.9% of on time with troublesome dyskinesia was considered bad time while 85.5% of on time without dyskinesia and 93.8% of on time with nontroublesome dyskinesia was considered good time. With this diary (Diary II), the effect of an intervention can be expressed as the change in off time and the change in on time with troublesome dyskinesia (bad time). The sum can be used as an outcome variable and compared to baseline or across groups. In evaluating the efficacy of an intervention, assessment of change in off time and change in on time with troublesome dyskinesia provides a more accurate reflection of clinical response than change in off time alone.

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