Article

Genetic Associations with Temporal Modeling of Alzheimer’s Disease Progression Supports a Novel Paradigm for Disease Risk

2026-07-10

Abstract excerpt

<h4>Summary</h4> A major challenge in Alzheimer’s disease (AD) research is predicting who will develop AD, how it progresses, and how to slow, prevent, or reverse progression. Here, we apply a data-driven timeline inference framework to sparse longitudinal blood metabolomics data to reconstruct AD timelines and derive individual-specific timeline progression rates. Inferred temporal locations for each metabolomic...

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Literature Corpus work: a82a3466-c89b-58e6-821c-5fadf59cac60
DOI: 10.64898/2026.07.07.26356710

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