The drug bumetanide, an established treatment for fluid retention, could help prevent development of Alzheimer’s Disease according to research that includes a combination of basic lab work and electronic health record (EHR) analysis.
“This is a drug with a well-established safety record, so it could reach patients much faster than typical drug development takes,” says Yadong Huang, MD, PhD, a Gladstone Institute researcher and a senior author of the new study published in the journal Nature Aging.
Researchers at Gladstone Institutes teamed up with scientists from UC San Francisco (UCSF) and Icahn School of Medicine at Mount Sinai and discovered that bumetanide—used for more than 30 years to treat fluid retention associated with conditions like hypertension and heart failure—reverses signs of Alzheimer’s disease in mice, as well as in human brain cells.
Moreover, when they analyzed electronic health records from two independent institutions, the team discovered that people over 65 who took bumetanide were less likely to develop Alzheimer’s disease than those who didn’t.
“Though further tests and clinical trials are needed, this research underscores the value of big data-driven tactics combined with more traditional scientific approaches to identify existing FDA-approved drugs as candidates for drug repurposing to treat Alzheimer’s disease,” said Richard J. Hodes, M.D., director of the NIH’s National Institute on Aging in a statement.
Alzheimer’s disease currently affects an estimated 6 million Americans. Developing new, targeted drugs for complex conditions like AD is a long and expensive process. In 2017, with the goal of bringing safe treatments to patients more quickly, Huang launched the Gladstone Center for Translational Advancement to repurpose FDA-approved drugs for new uses.
Huang’s approach centers around the idea that patients with Alzheimer’s disease may have different underlying causes of neurodegeneration, and therefore, the efficacy of specific treatments may differ among patients—a strategy called precision medicine. However, in the large clinical trials required for new drugs, it can be hard to pinpoint whether a drug is effective in only a subpopulation of the patients.
The research team used a computational approach to identify unique gene expression profiles associated with Alzheimer’s disease in brain tissues from specific subgroups of patients. They then screened a database of existing drugs to find the ones most likely to reverse the altered gene expression profiles in each subgroup.
In the new study, the researchers first analyzed a publicly available database of 213 brain samples from people with and without Alzheimer’s disease, including people with different versions of a gene called APOE, the major genetic risk factor for the disease.
The team identified nearly 2,000 altered gene expressions in the brains of people with Alzheimer’s disease. While roughly 6 percent of the altered genes were similar between people with different APOE versions, the vast majority of them were unique to people with specific combinations of the APOE3 or APOE4 versions, the latter conferring the highest genetic risk of Alzheimer’s disease.
The researchers next queried a database of more than 1,300 existing drugs to look for those able to change the altered gene expressions they had identified for subgroups of Alzheimer’s patients.
“In traditional drug development, in addition to animal and cell studies, we would typically need to do in-depth safety testing before launching clinical trials in humans,” said Marina Sirota, PhD, an associate professor at the Bakar Computational Health Sciences Institute at UCSF and a co-senior author of the study. “But with an existing FDA-approved drug, we can leverage the real-world human data to test, in silico, what the drug might be able to achieve.”