Harnessing Big Data to Understand Alzheimer’s Disease Risk

2019, 2022

We propose to take a unique, big data approach to understanding risks factors for Alzheimer’s disease using medical claims obtained from Medicare. Medicare provides insurance coverage for more than 95% of adults ages 65 and older in the United States, corresponding to the age at which AD is most common. These Medicare data contain nearly 100,000 diagnoses codes, procedures and medications that can be investigated to determine which are associated with either a lower or a higher risk of AD. In our preliminary studies, we found that those with a prior history of meningitis had a higher risk of developing AD. In addition, we identified 41 medications, most notably medications used to treat gout, which were associated with a lower risk of developing AD. In the current application, we will build on our preliminary studies by creating the largest Medicare study of AD risk ever performed. In this study, we will evaluate the relationship between meningitis and the risk of AD in order to provide evidence from clinical data to confirm results from nonhuman AD model systems. We will use the entire Medicare medication formulary to identify medications associated with a lower risk of developing AD. If successful, we will provide unique insight into causes of AD and identify novel, potential disease-modifying therapies for AD from drugs that easily could be repurposed to treat those with AD.

Funding to Date



Biomarkers/Diagnostics/Studies of Risk & Resilience, Foundational


Brad A. Racette, M.D.

Alejandra Camacho-Soto, M.D., M.P.H.S. 

Susan Searles Nielsen, Ph.D.

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