New data platform transforms prediction and understanding of Alzheimer’s disease

A powerful new real-world data platform could transform how scientists predict and understand Alzheimer's disease and Alzheimer's disease related dementias (AD/ADRD), reports a new study at Columbia University Mailman School of Public Health and collaborators at the Vagelos College of Physicians and Surgeons, the School of Nursing as well as the University of Miami and University of Chicago. The project, known as the M3AD Study and Real-World Data Metaplatform, represents one of the most comprehensive efforts to date to use large-scale clinical data to advance precision aging research and accelerate discoveries in Alzheimer's prevention and care. The study is published in the journal Alzheimer's & Dementia.

Drawing on electronic health records from three U.S. cities including approximately 60,000 individuals with AD/ADRD, the platform allows researchers to track how multiple chronic diseases, behaviors, and social conditions interact over time to shape dementia risk, creating one of the largest and most comprehensive datasets ever assembled to study dementia.

Unlike traditional studies that examine a limited set of individual diseases, the platform analyzes interacting health conditions, behaviors, and social factors simultaneously and over time, so that the full complexity of aging and multimorbidity is captured and predictions of dementia risk and progression are improved.

As people live longer, chronic diseases increasingly occur together, creating complex health trajectories that traditional disease-by-disease research does not easily capture. The new platform addresses this challenge by integrating and harmonizing electronic health records (EHRs) from nearly 10 million patients across three major health systems in New York City, Chicago, and Miami, including the roughly 60,000 patients with Alzheimer's disease and related dementias."