Improving Alzheimer’s Disease Tracking

by | Jul 27, 2020 | Alzheimer's Disease, I. Issues | 0 comments

Written by: Brielle Ruscitti and Emily Xu

Alzheimer’s disease (AD) is a progressive neurodegenerative disease, most trademarked by cognitive impairment (1). In the United States, it is the 6th leading cause of death, and worldwide nearly 50 million people suffer from AD or related dementia. (2) It is estimated that 5.8 million Americans age 65 and older are living with Alzheimer’s dementia in 2020 and eighty percent are 75 years or older (5). People with AD only can manage their symptoms or slow their rate of decline (1), as there is no cure for AD or way to reverse the damage done to the neurons. Therefore, the current best strategy for managing AD is early detection and monitoring of symptom progression.

The standard diagnostic and screening tools that exist for AD fall into two categories: cognitive screening tests and neuroimaging and lab tests. These tests depend on the identification of biomarkers which can be objectively and reliably evaluated as an indication of biological processes in the brain. (3) Such biomarkers include β-amyloid, total tau and phospho-tau-181. (3)

Neuropsychiatric tests like the Mini-mental State Examination (MMSE) can screen patients for cognitive and functional defects that would then qualify them for neuroimaging screening. The problem with such cognitive tests is that they are not definitively objective and do not distinguish well between AD and non-AD dementia. (2) More objective neuroimaging and lab tests such as fluorodeoxyglucose (FDG) PET scans and CSF tests can be invasive and expensive. With the high prevalence and burden of AD in the population, there is a need for a more objective, affordable, non-invasive screening test that can support cognitive screening and better inform later decisions to use more invasive tests.

The search for such a biomarker for early AD detection and monitoring has led to the discovery of associations between eye abnormalities and AD. In particular, saccadic eye movement changes have been observed in AD patients and can occur even before the appearance of cognitive changes. (2) AD patients have demonstrated changes in saccade latency, peak velocity, and errors in the anti-saccadic process. (2) Of note, the pattern of increased anti-saccadic errors is specific to AD and has not been seen in other neuropsychiatric disorders such as schizophrenia and Parkinson’s disease. (4) Since these changes can occur during the preclinical stages of AD, they can be used as an early screening measure for patients who will go on to develop Mild Cognitive Impairment (MCI) and progression to clinical AD.

Esurgi is using this biomarker of eye saccade changes to develop EyeAD, an adjunct tool used for early detection and ongoing monitoring of AD. A patient may progress from mild cognitive impairment to AD more quickly than expected or before visits to their Physician. Using this tool, patients can monitor and test themselves in an affordable, non-invasive manner. Regular qualitative and triggered eye pattern summary data is communicated to the patient’s provider so that healthcare professionals have consistent and recent updates on a patient’s disease progression. These updates aid in making timely decisions about further testing and intervention. Although EyeAD does not have the ability to completely replace the use of CSF analysis or FDG PET scans, it is an effective supplement that can fill in the gaps left by current screening and monitoring tools.

Would you find an adjunct tool that monitors eye patterns on an ongoing basis useful? What do you hope to see in this type of solution?

Citations:

  1. Alzheimer’s disease. (2018, December 08). Retrieved July 23, 2020, from https://www.mayoclinic.org/diseases-conditions/alzheimers-disease/symptoms-causes/syc-20350447.
  2. Panchal, H., De, A., Agbakwuruonyike, C., Jiang, Y., & Kamjoo, P. (2020). Literature Review on the Correlation between Abnormalities in Eye Movement and the Presence of Alzheimer Disease. The IRES International Conference, 44-50. Retrieved July 26, 2020, from https://www.worldresearchlibrary.org/up_proc/pdf/3792-159340740744-50.pdf
  3. Humpel, C. (2011). Identifying and validating biomarkers for Alzheimer’s disease. Trends in Biotechnology, 29(1), 26-32. doi:10.1016/j.tibtech.2010.09.007.
  4. Wilcockson, T. D., Mardanbegi, D., Xia, B., Taylor, S., Sawyer, P., Gellersen, H. W., . . . Crawford, T. J. (2019). Abnormalities of saccadic eye movements in dementia due to Alzheimer’s disease and mild cognitive impairment. Aging, 11(15), 5389-5398. doi:10.18632/aging.102118.
  5. Association, A. (2020). Facts and Figures. Retrieved July 25, 2020, from https://www.alz.org/alzheimers-dementia/facts-figures

What do you think?