Two researchers, one cause

 

From left, Elan Barenholtz, an associate professor in the department of psychology, Charles E. Schmidt College of Science, and Qi Zhang, Ph.D., a research assistant professor of biomedical science in the Charles E. Schmidt College of Medicine. Graphics by Craig Korn.

Two Researchers: One Cause

Grants Fund Research on Alzheimer's Disease

Even though Alzheimer’s disease was discovered more than 100 years ago, scientists still know shockingly little about what causes it, how to treat it, and how to diagnose it. But, hopefully, that will change soon.

Two research groups at the FAU Brain Institute have received grants to study these problems with the expectation that their work will result in new, more effective approaches to understanding and diagnosing the disease.

In 1906 Alois Alzheimer dissected the brain of a patient who died of a mysterious pathology. He discovered a buildup of plaque between brain cells and long tangles inside the cells. Ever since then, the scientific community has regarded that plaque, called amyloid-beta, and those tangles, called tau, as the culprits in Alzheimer’s disease (AD).

Qi Zhang, Ph.D., a research assistant professor of biomedical science in the Charles E. Schmidt College of Medicine, isn’t so sure. Zhang hypothesizes that the amyloid-beta plaque and tau tangles don’t cause the disease; he believes they’re merely pathological outcomes. The real culprit, according to Zhang, is misregulation of cholesterol in the brain cells, especially neurons.

Cholesterol is critical to neurons’ ability to send and receive the chemical signals that drive our thoughts and actions. When there’s too much or too little cholesterol on the surface of brain cells, they stop functioning and eventually die – leading to shrinking brain. When there’s a lot of cholesterol on the surface, there’s very little amyloid precursor protein (APP), which is the stuff that gives rise to the amyloid-beta plaque. Conversely, when there’s little cholesterol on the surface, there’s a lot of APP. Zhang suggests that APP regulates cell surface cholesterol, thereby affecting the neurons’ ability to function.

With a grant from the Ed and Ethel Moore Alzeheimer’s Foundation, Zhang will investigate the mechanisms, genetic and otherwise, by which APP regulates cholesterol. “We believe that the death of neurons may be rooted in the malfunction of cholesterol regulation,” he said. “Using genetic tools to surgically sever the tie between the cholesterol and amyloid precursor protein, we hope to find whether the regulatory role of APP and cholesterol is neurologically meaningful and plays a role in the development of neurodegeneration of the disease.”

Understanding the mechanisms behind cell death will help researchers – including Zhang – find ways to prevent it.

As scientists struggle to find the causes of Alzheimer’s disease, they also wrestle with the difficulties of diagnosing it, especially in early stages, before the patient displays significant loss of speech, memory or capacity to reason.

Elan Barenholtz, an associate professor in the department of psychology, has received a grant from the Florida Department of Health to develop a test that can diagnose AD in its early stages based on a patient’s eye movements and speech patterns. Barenholtz will be supervising postdoc Michael J. Kleiman, who contributed significantly to the design of the study and will be working on the test.

Eye movements reflect very small changes in cognition. The test takes 15 to 20 minutes and doesn’t require a doctor to administer. The patient is asked to read sentences or describe a picture while a machine records his or her eye movements and ability to respond linguistically. The grant funding will help fund an eye tracker that records 300 frames per second – that will produce a lot of data.

Barenholtz and Kleiman will apply machine learning analytics to sift through the data to determine which patients are at risk of developing Alzheimer’s and which are not. “If there's some pattern in there, a good machine learning algorithm will find it and say, yes, I can predict this patient will develop AD a year from now,” Barenholtz said. “Machine learning is an excellent tool to find patterns that are predictive of something. In this case, it would be a preliminary pathology that we can’t detect.”

Barenholtz’s test is based on accepted neuroscience. Zhang’s research challenges accepted neuroscience. Together, both research approaches could lead to major steps forward in the fight against this terrifying disease.

If you would like more information, please contact us at dorcommunications@fau.edu.