Longitudinal changes in the functional connectivity of individuals at risk of Alzheimer's disease.

First-degree relatives of Alzheimer's disease patients constitute a key population in the search for early markers. Our group identified functional connectivity differences between cognitively unimpaired individuals with and without a family history. In this unprecedented follow-up study, we examine whether family history is associated with a longitudinal increase in the functional connectivity of those regions. Moreover, this is the first work to correlate electrophysiological measures with plasma p-tau231 levels, a known pathology marker, to interpret the nature of the change. We evaluated 69 cognitively unimpaired individuals with a family history of Alzheimer's disease and 28 without, at two different time points, approximately 3 years apart, including resting state magnetoencephalography recordings and plasma p-tau231 determinations. Functional connectivity changes in both precunei and left anterior cingulate cortex in the high-alpha band were studied using non-parametric cluster-based permutation tests. Connectivity values were correlated with p-tau231 levels. Three clusters emerged in individuals with family history, exhibiting a longitudinal increase of connectivity. Notably, the clusters for both precunei bore a striking resemblance to those found in previous cross-sectional studies. The connectivity values at follow-up and the change in connectivity in the left precuneus cluster showed significant positive correlations with p-tau231. This study consolidates the use of electrophysiology, in combination with plasma biomarkers, to monitor healthy individuals at risk of Alzheimer's disease and emphasizes the value of combining noninvasive markers to understand the underlying mechanisms and track disease progression. This could facilitate the design of more effective intervention strategies and accurate progression assessment tools.

Alzheimer's disease: a continuum with visual involvements.

Introduction: Alzheimer's disease (AD) is the most common form of dementia affecting the central nervous system, and alteration of several visual structures has been reported. Structural retinal changes are usually accompanied by changes in visual function in this disease. The aim of this study was to analyse the differences in visual function at different stages of the pathology (family history group (FH+), mild cognitive impairment (MCI), mild AD and moderate AD) in comparison with a control group of subjects with no cognitive decline and no family history of AD. Methods: We included 53 controls, 13 subjects with FH+, 23 patients with MCI, 25 patients with mild AD and, 21 patients with moderate AD. All were ophthalmologically healthy. Visual acuity (VA), contrast sensitivity (CS), colour perception, visual integration, and fundus examination were performed. Results: The analysis showed a statistically significant decrease in VA, CS and visual integration score between the MCI, mild AD and moderate AD groups compared to the control group. In the CS higher frequencies and in the colour perception test (total errors number), statistically significant differences were also observed in the MCI, mild AD and moderate AD groups with respect to the FH+ group and also between the control and AD groups. The FH+ group showed no statistically significant difference in visual functions compared to the control group. All the test correlated with the Mini Mental State Examination score and showed good predictive value when memory decline was present, with better values when AD was at a more advanced stage. Conclusion: Alterations in visual function appear in subjects with MCI and evolve when AD is established, being stable in the initial stages of the disease (mild AD and moderate AD). Therefore, visual psychophysical tests are a useful, simple and complementary tool to neuropsychological tests to facilitate diagnosis in the preclinical and early stages of AD.

Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol.

More than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage between normal brain aging and dementia stage memory disorder. The path MCI takes can be divergent; while some maintain stability or even revert to cognitive norms, alarmingly, up to half of the cases progress to dementia within 5 years. Current diagnostic practice lacks the necessary screening tools to identify those at risk of progression. The European patient experience often involves a long journey from the initial signs of MCI to the eventual diagnosis of dementia. The trajectory is far from ideal. Here, we introduce the AI-Mind project, a pioneering initiative with an innovative approach to early risk assessment through the implementation of advanced artificial intelligence (AI) on multimodal data. The cutting-edge AI-based tools developed in the project aim not only to accelerate the diagnostic process but also to deliver highly accurate predictions regarding an individual's risk of developing dementia when prevention and intervention may still be possible. AI-Mind is a European Research and Innovation Action (RIA H2020-SC1-BHC-06-2020, No. 964220) financed between 2021 and 2026. First, the AI-Mind Connector identifies dysfunctional brain networks based on high-density magneto- and electroencephalography (M/EEG) recordings. Second, the AI-Mind Predictor predicts dementia risk using data from the Connector, enriched with computerized cognitive tests, genetic and protein biomarkers, as well as sociodemographic and clinical variables. AI-Mind is integrated within a network of major European initiatives, including The Virtual Brain, The Virtual Epileptic Patient, and EBRAINS AISBL service for sensitive data, HealthDataCloud, where big patient data are generated for advancing digital and virtual twin technology development. AI-Mind's innovation lies not only in its early prediction of dementia risk, but it also enables a virtual laboratory scenario for hypothesis-driven personalized intervention research. This article introduces the background of the AI-Mind project and its clinical study protocol, setting the stage for future scientific contributions.