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Drive for Diagnostic Measures for Alzheimer’s DiseaseAdd a Blog Post Title

By Aleksandra Recupero

Reciting your phone number, conveying directions to your house, and calling your family members by name tend to be relatively menial tasks for the average healthy person. However, these small but important tasks can quickly be forgotten. Such is the daily struggle for the more than five million Americans diagnosed with Alzheimer’s disease (AD).1

Alzheimer’s disease is a progressive brain disorder that causes slow deterioration of memory and thinking abilities. It begins in the hippocampus, the part of the brain essential for memory, amyloid plaques and tau tangles develop. These growing protein deposits lead to neuronal death as neurons lose both proper function and connections with other neurons. During the final stages of the disease, amyloid and tau proliferate throughout the brain, ultimately causing atrophy of brain tissue. Ironically despite these extreme changes in brain morphology over time, Alzheimer’s disease can only be definitively diagnosed after death through the examination of brain tissue.

The trouble with diagnosing Alzheimer’s disease is that much of the previously described brain damage does not manifest in cognition problems until nearly a decade after onset. Therefore, many people do not seek medical attention until after much of the initial brain damage has already taken place. The diagnosis process proceeds with many qualitative tests of one’s brain function. These tests include but are not limited to verbal tests of memory, problem solving, attention, and language in addition to consultations with family members and friends of the patient. A wide-range of brain scans, ranging from computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), have begun to provide means of better diagnosing individuals.2

The ability to diagnose Alzheimer’s disease early on is becoming more and more critical. This necessity is due to the fact that the baby boomer generation is advancing in years and thus many individuals are approaching the ages at which a greater proportion of the population is diagnosed with AD. Predictions forecast that by 2050 13.8 million Americans will have some form of Alzheimer’s disease. This projection is quite significant considering that Alzheimer’s disease is one of the most financially costly chronic diseases to society. In 2016, health care expenses for Alzheimer’s disease were estimated to be $236 billion. Currently one in every five Medicare dollars goes to treating individuals with AD and this cost is projected to rise to one in every three Medicare dollars by 2050.1 Short of a cure to this detrimental illness, the best way to combat Alzheimer’s is with early diagnostic measures, which can postpone and may even reduce symptoms. Early diagnostic approaches would also cut long-term costs accumulated throughout the progression of the disease.

Brain imaging has been at the forefront of early detection of Alzheimer’s disease. Using imaging, physicians can mark changes in the brain structure that have not necessarily developed into memory or thinking problems. Both positron emission tomography and magnetic resonance imaging have been used to observe changes in brain glucose metabolism, morphology, and functional connectivity, all of which have appeared to be connected with preclinical risk for Alzheimer’s disease.3 Furthermore, magnetic resonance imaging has provided a means to detect early brain atrophy in the medial temporal lobe grey matter, which consists of cell bodies, dendrites, and axon terminals. In this way, the grey matter in the medial temporal lobe serves as an important assay since it is affected early by the onset of AD. In addition, changes in the white matter of the brain, or the myelinated axons connecting the grey matter, have been detected among Alzheimer’s patients, thus providing a marker for doctors to look for in their diagnoses.4

One novel approach to assessing early onset of the disease is through the use of nanotechnology. For example, biocompatible nanoparticles have been produced with enhanced optical and magnetic properties. Such nanoparticles could function as important contrasting agents in brain imaging for early diagnosis.5 The development of biocompatible nanoparticles is still underway and further utility of such an approach will become more clear with time.

Despite such proposals, the greatest roadblock to early diagnosis is the lack of multivariate biomarkers needed to identify Alzheimer’s disease. Compounded with the struggle of developing imaging biomarkers is the difficulty in taking into consideration the effects of brain aging on the disease pathology. Structural MRI has functioned as an essential biomarker for neurodegeneration but it is highly based on volumetric MRI studies. To combat this dependence on volume, the use of multiple, diverse MRI biomarkers have been noted to increase the sensitivity of the structural MRI to symptoms of Alzheimer’s disease.6 Even with such developments, it is still difficult to directly attribute changes in brain structure to AD. This trouble will only be amended through a greater understanding of the mechanism of this complex disease.

Beyond just producing early detection methods, the main goal is to eventually cure Alzheimer’s disease. For this goal to be achieved, a greater understanding of the molecular and cellular basis for this disease is imperative. It is easy to lose sight of the imminent threat of such a disease that looms in the future for many people. The need for a cure is more urgent than ever and with any illness the first step in the right direction is diagnosis.

References

  1. Alzheimer’s Association. 2017. “2016 Alzheimer’s Disease Facts and Figures.” Accessed February 9. http://www.alz.org/facts/
  2. National Institute on Aging. 2016. “Alzheimer’s Disease Fact Sheet.” Las modified August 18. https://www.nia.nih.gov/alzheimers/publication/alzheimers-disease-fact-sheet
  3. Alexander, Gene E. 2017. “An Emerging Role for Imaging White Matter in the Preclinical Risk for Alzheimer Disease.” Jama Neurology 74, 1: 17-19.
  4. Badea, Alexandra et al. 2016. “The fornix provides multiple biomarkers to characterize circuit disruption in a mouse model of Alzheimer’s disease.” NeuroImage 142: 498-511.
  5. Leszek, J et al. 2017. “Nanotechnology for Alzheimer Disease.” Current Alzheimer Research.
  6. Sorensen, Lauge et al. 2017. “Differential diagnosis of mild cognitive impairment and Alzheimer’s disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry.” NeuroImage: Clinical 13: 470-482.

Image Credit (Creative Commons): “PET scan-normal brain-alzheimers disease brain.” Accessed March 2, 2017. https://commons.wikimedia.org/wiki/File:PET_scan-normal_brain-alzheimers_disease_brain.PNG

Aleksandra Recupero is a first-year student at the University of Chicago majoring in Biological Sciences. Her interests include medicine and neuroscience research.

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