Prevalence and Relationship of Rest Tremor and Action Tremor in Parkinson's Disease.

Background: Despite the significance of tremor in Parkinson's disease (PD) diagnosis, classification, and patient's quality of life, there is a relative lack of data on prevalence and relationship of different tremor types in PD. Methods: The presence of rest tremor (RT) and action tremor (AT; defined as combination of both postural and kinetic tremor) was determined and RT severity was defined using the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) at baseline in the Progression Marker Initiative (PPMI, n = 423), the Fox Investigation for New Discovery of Biomarkers (BioFIND, n = 118) and the Parkinson's Disease Biomarkers Program (PDBP, n = 873) cohorts. Results: Across baseline data of all three cohorts, RT prevalence (58.2%) was higher than AT prevalence (39.0%). Patients with RT had significantly higher (Chi-square test, p < 0.05) prevalence of AT compared to patients without RT in the PPMI (40.0% versus 30.1%), BioFIND (48.0% versus 40.0%) and PDBP (49.9% versus 21.0%) cohorts. Furthermore, patients with AT had significantly (Student t-test, p < 0.05) higher RT severity that those without AT in PPMI (5.7 ± 5.4 versus 3.9 ± 3.3), BioFIND, 6.4 ± 6.3 versus 3.8 ± 4.4) and PDBP (6.4 ± 6.6 versus 3.7 ± 4.4) cohorts. In the BioFIND cohort, the prevalence of all types of tremor and their combinations significantly decreased from the off-state to on-state. Discussion: The RT is the most frequent tremor type and present in more than half of the PD patients. However, AT is also present in nearly one-third of the PD patients. Our results also indicate that RT and AT may have cross-interactions in PD, and that dopaminergic treatment influences both RT and AT.

Integration of "omics" Data and Phenotypic Data Within a Unified Extensible Multimodal Framework.

Analysis of "omics" data is often a long and segmented process, encompassing multiple stages from initial data collection to processing, quality control and visualization. The cross-modal nature of recent genomic analyses renders this process challenging to both automate and standardize; consequently, users often resort to manual interventions that compromise data reliability and reproducibility. This in turn can produce multiple versions of datasets across storage systems. As a result, scientists can lose significant time and resources trying to execute and monitor their analytical workflows and encounter difficulties sharing versioned data. In 2015, the Ludmer Centre for Neuroinformatics and Mental Health at McGill University brought together expertise from the Douglas Mental Health University Institute, the Lady Davis Institute and the Montreal Neurological Institute (MNI) to form a genetics/epigenetics working group. The objectives of this working group are to: (i) design an automated and seamless process for (epi)genetic data that consolidates heterogeneous datasets into the LORIS open-source data platform; (ii) streamline data analysis; (iii) integrate results with provenance information; and (iv) facilitate structured and versioned sharing of pipelines for optimized reproducibility using high-performance computing (HPC) environments via the CBRAIN processing portal. This article outlines the resulting generalizable "omics" framework and its benefits, specifically, the ability to: (i) integrate multiple types of biological and multi-modal datasets (imaging, clinical, demographics and behavioral); (ii) automate the process of launching analysis pipelines on HPC platforms; (iii) remove the bioinformatic barriers that are inherent to this process; (iv) ensure standardization and transparent sharing of processing pipelines to improve computational consistency; (v) store results in a queryable web interface; (vi) offer visualization tools to better view the data; and (vii) provide the mechanisms to ensure usability and reproducibility. This framework for workflows facilitates brain research discovery by reducing human error through automation of analysis pipelines and seamless linking of multimodal data, allowing investigators to focus on research instead of data handling.

Neuroimaging Biomarkers of a History of Concussion Observed in Asymptomatic Young Athletes.

Participation in contact sports places athletes at elevated risk for repeated head injuries and is associated with negative mental health outcomes later in life. The current study identified changes observable on neuroimaging that persisted beyond the apparent resolution of acute symptoms of concussion. Sixteen young adult ice hockey players with a remote history of concussion but no subjective complaints were compared against 13 of their teammates with no history of concussion. Participants completed a detailed phenotypic assessment and a neuroimaging battery including diffusion kurtosis imaging and resting-state functional magnetic resonance imaging. Athletes with a history of concussion performed no differently from those without on phenotypic assessment, but showed significantly elevated fractional anisotropy (FA) in the left genu and anterior corona radiata relative to those without. Post hoc analyses revealed that elevated FA was associated with increased microstructural complexity perpendicular to the primary axon (radial kurtosis). Athletes with concussion history also showed significant differences in the organization of the default mode network (DMN) characterized by stronger temporal coherence in posterior DMN, decreased temporal coherence in anterior DMN, and increased functional connectivity outside the DMN. In the absence of deficits on detailed phenotypic assessment, athletes with a history of concussion displayed changes to the microstructural architecture of the cerebral white matter and to the functional connectivity of the brain at rest. Some of these changes are consistent with those previously associated with persisting deficits and complaints, but we also report novel, complementary changes that possibly represent compensatory mechanisms.

Postconcussion symptoms are associated with cerebral cortical thickness in healthy collegiate and preparatory school ice hockey players.

OBJECTIVE: To investigate the degree to which concussion history and postconcussive symptoms are associated with cortical morphology among male hockey players. STUDY DESIGN: Male subjects (n = 29), ranging in age from 14 to 23 years (mean 17.8 years), were recruited from preparatory school and collegiate ice hockey teams and underwent neuroimaging and baseline Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) testing. Cerebral cortical thickness was regressed against ImPACT Total Symptom Score (TSS), concussion history, as well as baseline measures of psychopathology. Reconstruction of surfaces and cortical thickness analysis were conducted with FreeSurfer (version 5.3.0). RESULTS: ImPACT TSS was inversely associated with local cortical thickness in widespread brain areas. Associations were revealed in a host of frontal as well as bilateral temporoparietal cortices. Conversely, concussion history was not associated with cortical thickness. An "Age by Concussion History" interaction was associated with thickness in the right ventrolateral and right parietal cortices. Post-hoc analysis revealed that concussed participants did not exhibit age-related cortical thinning in these regions. CONCLUSION: We have identified an association between brain structure and postconcussive symptoms among young, otherwise-healthy male athletes. Postconcussive symptoms and related reductions in cortical thickness may be tied to participation in a full-contact sport that involves frequent blows to the head.