Tau pathology in AD spreads in a hierarchical pattern, whereby it first appears in the entorhinal cortex, then spreads to the hippocampus and later to the surrounding areas. Based on this sequential appearance, AD can be classified into six stages (“Braak stages”). The mechanisms and agents underlying the progression of Tau pathology are a matter of debate. Emerging evidence indicates that the propagation of Tau pathology may be due to the transmission of Tau protein, but the underlying pathways and Tau species are not well understood. In this study we investigated the question of Tau spreading via small extracellular vesicles called exosomes. Exosomes from different sources were analyzed by biochemical methods and electron microscopy (EM) and cryo-EM. Microfluidic devices that allow the culture of cell populations in different compartments were used to investigate the spreading of Tau. We show that Tau protein is released by cultured primary neurons or by N2a cells overexpressing different Tau constructs via exosomes. Neuron-derived exosomal Tau is hypo-phosphorylated, compared with cytosolic Tau. Depolarization of neurons promotes release of Tau-containing exosomes, highlighting the importance of neuronal activity. Using microfluidic devices we show that exosomes mediate trans-neuronal transfer of Tau depending on synaptic connectivity. Tau spreading is achieved by direct transmission of exosomes between neurons. In organotypic hippocampal slices, Tau-containing exosomes in conditioned medium are taken up by neurons and microglia, not astrocytes. In N2a cells, Tau assemblies are released via exosomes. They can induce inclusions of other Tau molecules in N2a cells expressing mutant human Tau. We also studied exosomes from cerebrospinal fluid in AD and control subjects containing monomeric and oligomeric Tau. Split-luciferase complementation reveals that exosomes from CSF can promote Tau aggregation in cultured cells. Our study demonstrates that exosomes contribute to trans-synaptic Tau transmission, and thus offer new approches to control the spreading of pathology in AD and other tauopathies.

Objective: Quantification of gait with wearable technology is promising; recent cross‐sectional studies showed that gait characteristics are potential prodromal markers for Parkinson disease (PD). The aim of this longitudinal prospective observational study was to establish gait impairments and trajectories in the prodromal phase of PD, identifying which gait characteristics are potentially early diagnostic markers of PD.Methods: The 696 healthy controls (mean age = 63 ± 7 years) recruited in the Tubingen Evaluation of Risk Factors for Early Detection of Neurodegeneration study were included. Assessments were performed longitudinally 4 times at 2‐year intervals, and people who converted to PD were identified. Participants were asked to walk at different speeds under single and dual tasking, with a wearable device placed on the lower back; 14 validated clinically relevant gait characteristics were quantified. Cox regression was used to examine whether gait at first visit could predict time to PD conversion after controlling for age and sex. Random effects linear mixed models (RELMs) were used to establish longitudinal trajectories of gait and model the latency between impaired gait and PD diagnosis.Results: Sixteen participants were diagnosed with PD on average 4.5 years after first visit (converters; PDC). Higher step time variability and asymmetry of all gait characteristics were associated with a shorter time to PD diagnosis. RELMs indicated that gait (lower pace) deviates from that of non‐PDC approximately 4 years prior to diagnosis.Interpretation: Together with other prodromal markers, quantitative gait characteristics can play an important role in identifying prodromal PD and progression within this phase. ANN NEUROL 2019;86:357–367

Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice.