Background We classified non‐demented European Prevention of Alzheimer's Dementia (EPAD) participants through the amyloid/tau/neurodegeneration (ATN) scheme and assessed their neuropsychological and imaging profiles. Materials and methods From 1500 EPAD participants, 312 were excluded. Cerebrospinal fluid cut‐offs of 1000 pg/mL for amyloid beta (Aß)1‐42 and 27 pg/mL for p‐tau181 were validated using Gaussian mixture models. Given strong correlation of p‐tau and t‐tau (R2 = 0.98, P < 0.001), neurodegeneration was defined by age‐adjusted hippocampal volume. Multinomial regressions were used to test whether neuropsychological tests and regional brain volumes could distinguish ATN stages. Results Age was 65 ± 7 years, with 58% females and 38% apolipoprotein E (APOE) ε4 carriers; 57.1% were A–T–N–, 32.5% were in the Alzheimer's disease (AD) continuum, and 10.4% suspected non‐Alzheimer's pathology. Age and cerebrovascular burden progressed with biomarker positivity (P < 0.001). Cognitive dysfunction appeared with T+. Paradoxically higher regional gray matter volumes were observed in A+T–N– compared to A–T–N– (P < 0.001). Discussion In non‐demented individuals along the AD continuum, p‐tau drives cognitive dysfunction. Memory and language domains are affected in the earliest stages.

Background: Gait analysis with accelerometers is a relatively inexpensive and easy to use method to potentially support clinical diagnoses of Alzheimer's disease and other dementias. It is not clear, however, which gait features are most informative and how these measures relate to Alzheimer's disease pathology. Objective: In this study, we tested if calculated features of gait 1) differ between cognitively normal subjects (CN), mild cognitive impairment (MCI) patients, and dementia patients, 2) are correlated with cerebrospinal fluid (CSF) biomarkers related to Alzheimer's disease, and 3) predict cognitive decline.

The early stages of neurodegenerative disorders such as Alzheimer's disease (AD) and Parkinson's disease (PD) involve deterioration of specific (visuo)motor functions. The aim of the current study was to investigate differences in visuomotor behavior between age-matched groups of 17 patients with AD, 17 patients with PD, and 20 healthy control subjects across three eye-hand-coordination tasks of different cognitive complexity. In two of three tasks, timing and execution parameters of eyes and hand significantly differed between groups. Timing and execution parameters of the eyes and hands could potentially give a quantitative description of disease specific deficits in the spatial and temporal domains and may serve as a tool to monitor disease progression in AD and PD populations.

The presented data suggest that memory function and visuomotor function are equally impaired in the present study population. This could indicate that visuomotor dysfunction might be a more important clinical feature of AD than is currently assumed. This knowledge can be used to develop new tests and markers for AD reflecting deficits in visuomotor functions, such as quantification of eye and hand movements.

Cerebellar plasticity is a critical mechanism for optimal feedback control. While Purkinje cell activity of the oculomotor vermis predicts eye movement speed and direction, more lateral areas of the cerebellum may play a role in more complex tasks, including decision-making. It is still under question how this motor-cognitive functional dichotomy between medial and lateral areas of the cerebellum plays a role in optimal feedback control. Here we show that elite athletes subjected to a trajectory prediction, go/no-go task manifest superior subsecond trajectory prediction accompanied by optimal eye movements and changes in cognitive load dynamics. Moreover, while interacting with the cerebral cortex, both the medial and lateral cerebellar networks are prominently activated during the fast feedback stage of the task, regardless of whether or not a motor response was required for the correct response. Our results show that cortico-cerebellar interactions are widespread during dynamic feedback and that experience can result in superior task-specific decision skills.

Background: Noninvasive interventions to aid healthy cognitive aging are considered an important healthcare priority. Traditional approaches typically focus on cognitive training or aerobic exercise training. In the current study, we investigate the effect of exercises that directly combine cognitive and motor functions on visuomotor skills and general cognition in elderly with various degrees of cognitive deficits. Subjects and Methods: A total of 37 elderly, divided into four groups based on their level of cognition, completed a 16-week cognitive-motor training program. The weekly training sessions consisted of playing a videogame requiring goal-directed hand movements on a computer tablet for 30 minutes. Before and after the training program, all participants completed a test battery to establish their level of cognition and visuomotor skills. Results: We observed an overall change in visuomotor behavior in all groups, as participants completed the tasks faster but less accurately. More importantly, we observed a significant improvement in measures of overall cognition in the subaverage cognition group and the mild-to-moderate cognitive deficits group. Conclusion: Our findings indicate that (1) cognitive-motor exercises induce improved test scores, which is most prominent in elderly with only mild cognitive deficits, and (2) cognitive-motor exercises induce altered visuomotor behavior and slight improvements in measures of general cognition.

Background Functional decline in Alzheimer’s disease (AD) is typically measured using single-time point subjective rating scales, which rely on direct observation or (caregiver) recall. Remote monitoring technologies (RMTs), such as smartphone applications, wearables, and home-based sensors, can change these periodic subjective assessments to more frequent, or even continuous, objective monitoring. The aim of the RADAR-AD study is to assess the accuracy and validity of RMTs in measuring functional decline in a real-world environment across preclinical-to-moderate stages of AD compared to standard clinical rating scales. Methods This study includes three tiers. For the main study, we will include participants (n = 220) with preclinical AD, prodromal AD, mild-to-moderate AD, and healthy controls, classified by MMSE and CDR score, from clinical sites equally distributed over 13 European countries. Participants will undergo extensive neuropsychological testing and physical examination. The RMT assessments, performed over an 8-week period, include walk tests, financial management tasks, an augmented reality game, two activity trackers, and two smartphone applications installed on the participants’ phone. In the first sub-study, fixed sensors will be installed in the homes of a representative sub-sample of 40 participants. In the second sub-study, 10 participants will stay in a smart home for 1 week. The primary outcome of this study is the difference in functional domain profiles assessed using RMTs between the four study groups. The four participant groups will be compared for each RMT outcome measure separately. Each RMT outcome will be compared to a standard clinical test which measures the same functional or cognitive domain. Finally, multivariate prediction models will be developed. Data collection and privacy are important aspects of the project, which will be managed using the RADAR-base data platform running on specifically designed biomedical research computing infrastructure. Results First results are expected to be disseminated in 2022. Conclusion Our study is well placed to evaluate the clinical utility of RMT assessments. Leveraging modern-day technology may deliver new and improved methods for accurately monitoring functional decline in all stages of AD. It is greatly anticipated that these methods could lead to objective and real-life functional endpoints with increased sensitivity to pharmacological agent signal detection.

Background The Amyloid/Tau/Neurodegeneration (ATN) framework has been proposed as a means of evidencing the biological state of Alzheimer’s disease (AD). Predicting ATN status in pre-dementia individuals therefore provides an important opportunity for targeted recruitment into AD interventional studies. We investigated the extent to which ATN-defined biomarker status can be predicted by known AD risk factors as well as vascular-related composite risk scores. Methods One thousand ten cognitively healthy older adults were allocated to one of five ATN-defined biomarker categories. Multinomial logistic regression tested risk factors including age, sex, education, APOE4, family history of dementia, cognitive function, vascular risk indices (high systolic blood pressure, body mass index (BMI), high cholesterol, physical inactivity, ever smoked, blood pressure medication, diabetes, prior cardiovascular disease, atrial fibrillation and white matter lesion (WML) volume), and three vascular-related composite scores, to predict five ATN subgroups; ROC curve models estimated their added value in predicting pathology. Results Age, APOE4, family history, BMI, MMSE and white matter lesions (WML) volume differed between ATN biomarker groups. Prediction of Alzheimer’s disease pathology (versus normal AD biomarkers) improved by 7% after adding family history, BMI, MMSE and WML to a ROC curve that included age, sex and APOE4. Risk composite scores did not add value. Conclusions ATN-defined Alzheimer’s disease biomarker status prediction among cognitively healthy individuals is possible through a combination of constitutional and cardiovascular risk factors but established dementia composite risk scores do not appear to add value in this context.