To view an abstract, select an author from the vertical list on the left.
2016 Grants - Szigeti
Narrowing the Gap in the Genetic Architecture of Alzheimer’s Disease
Kinga Szigeti, M.D., Ph.D.
State University of New York (SUNY) at Buffalo
Buffalo, New York
2016 Alzheimer’s Association Research Grant (AARG)
Could certain genetic variations that alter gene activity levels contribute to the risk for Alzheimer’s disease?
Certain genetic factors can play a role in contributing to a person’s risk of developing Alzheimer’s disease. Scientists have identified specific variations in the sequence (“spelling”) of a certain genes that may indicate an increased risk for Alzheimer’s. Large-scale genetic studies of people with Alzheimer’s have traditionally focused on these sequence variations (misspellings), but another type of genetic factor called copy number variations (CNVs) could also play a role in the risk for disease. CNVs refer to areas in a person’s genome (genetic blueprint) where there is an extra or missing copy of a gene, or part of a gene, which can increase or decrease the level of that gene’s activity. Additional research is needed to better understand the potential contribution of CNVs to Alzheimer’s disease.
Kinga Szigeti, M.D., Ph.D. and colleagues will use novel analytical methods to systematically detect CNVs in large datasets of genetic information from people with Alzheimer’s disease. The researchers will then use “induced pluripotent stem cells” (iPSCs) to study how these CNVs may impact cellular function. iPSCs can be made from adult skin or blood cells that have been collected from individuals with Alzheimer’s disease and then “reprogrammed” to behave like nerve cells. Dr. Szigeti hopes to identify CNVs are linked to Alzheimer’s-like changes in nerve cells and also determine if CNVs may alter the way nerve cells respond to experimental drug treatments.
This study may help researchers identify novel genetic factors that could impact the risk for Alzheimer’s disease. These findings could also inform the development new tools for detecting genetic variations that may be associated with Alzheimer’s disease.