Combining genetic information with population imaging to improve diagnostic markers for Alzheimer's Disease
Approved Research ID: 65299
Approval date: January 11th 2021
As we age several properties of our bodies change over time as well. For instance, muscles loose strength and brains shrink. Brain disorders, such as Alzheimer's Disease, lead to brain shrinkage that is much faster than what we would expect in people without the disorder. A disease often does not affect the whole brain the same way. For instance, in Alzheimer's Disease a small brain region, the hippocampus, shows shrinkage early in the disease. The hippocampus is part of the brain that is particularly important for memory, thus leading to the well-known memory problems in Alzheimer's disease.
Neuroimaging enables us to take pictures of the brain and measure its size and also the size of the hippocampus. Now, in order to understand whether a person's measurement is in the healthy range, we can compare their measurement to the ones obtained from age-matched healthy individuals. If we collect such measurements for different age groups we can generate a diagram that tells us how this measure changes in the population over time: a nomogram.
Nomograms are a widely used tool in medicine. Most prominently they are employed to assess and track the growth of newborns. Likewise, a nomogram for hippocampal volume can be used to assess and track the decline of this important part of the brain. People whose measurements are 'below the curve' may require further check-ups and closer monitoring. Traditionally, nomograms are generated for men and women separately. However, this is only one possible difference. One other component is genetics. Our genes can influence whether we have naturally a larger or smaller hippocampus. But so far, the contribution of genetics has not been leveraged in the development of nomograms. As a consequence, people with a smaller hippocampus may incorrectly be diagnosed with possible Alzheimer's disease, whereas people with a naturally larger hippocampus may not be recognized as abnormal until very late in the disease.
In this project we aim to improve nomograms by incorporating genetic information. We will test whether these improved nomograms can better detect abnormal aging and may lead to the earlier diagnosis of Alzheimer's disease.