Alzheimer disease in the computational era: from a deterministic disease to a multifaceted disorder

The definition of Alzheimer disease (AD) keeps changing over the years, which is critical for studying it, understanding it, and developing treatments. Here we first review the different definitions proposed for AD from its original characterization by Kraepelin in 1908, to the recent Alzheimer's Association revised criteria in 2024. We describe these definitions in parallel to the new knowledge gained, demonstrating how they vacillate between restricted and circumscribed clinicopathological characterizations and wider clinical and pathological ones. Then, we describe AD multifaceted clinical presentations, including very early subtle cognitive and behavioural changes, alongside its pathological multifactorial variability of core-pathologies, co-pathologies and risk factors, encompassing changes in various cortical and subcortical brain regions, and its genetic complex landscape. We suggest that all potential factors among the different levels should be considered to provide a patient-tailored clinical profile. To address the richness and complexity of the data, we outline a metamodeling-based computational framework that allows diverse sources of evidence to be integrated without forcing them into a single monolithic model. Specifically, different data subsets are first used to construct partial models, each addressing selected domains and factors; these models are then converted into probabilistic surrogate models with shared variables and parameters; finally, the latent variables inferred from the surrogate models are related via a probabilistic coupling layer to create predictions of individual patients' trajectories and intervention effects, staging, clinical stratification and attribution maps. Taken together, the computational and data revolutions may enable us to expose the complexity of AD through large-scale patients' data, computational metamodeling, and hypothesis-free analyses, leading to reconceptualization of AD from a monolithic diagnostic category into a stratified, mechanistically interpretable nosology, with practical implications at the individual patient level.