The ?4 allele of the APOE gene (APOE4) is a major genetic risk factor for late onset Alzheimer's disease (AD). Nevertheless, the question of how APOE4 so profoundly increases AD risk remains unanswered. From its association with not only increased risk for AD, but also with increased risk for Dementia with Lewy Bodies and poor recovery following traumatic brain injury, we can infer that the expression of APOE4 disrupts multiple cellular functions to increase susceptibility to neurodegenerative insult. No approved therapy exists for AD that targets the underlying molecular factors. Thus, a mechanistic understanding of how APOE4 increases disease susceptibility and progression will enable us to define novel therapeutic targets. I propose to use induced- pluripotent stem cell (iPSC) technology to elucidate, in a cell type-specific manner, how APOE4 disrupts specific pathways and proteins. I will also construct predictive computational networks of genes perturbed by APOE4 to complement my mechanistic studies in neural cells and to illuminate the relationships between various APOE4-associated processes. To identify which cellular pathways APOE4 impacts, I constructed a set of yeast models that exhibit a dose-dependent growth defect specifically when expressing APOE4. Previous studies have clearly demonstrated that high-throughput screens in yeast can be used to discover underlying cellular dysfunctions associated with neurodegenerative diseases. These pathways identified in yeast have been validated in patient-derived neurons. Using the genetic tractability of yeast and the conservation of fundamental cellular biology between yeast and humans, I performed a genome-wide overexpression screen to identify modifier genes that robustly rescue the toxicity of APOE4 and indicate pathways disrupted by APOE4. I now propose to examine how these aspects of APOE4 biology manifest in the highly specialized cell types of the human brain. I will utilize isogenic sets of human induced pluripotent stem cell (iPSC) lines that vary only at the APOE locus to investigate disruptions in specific pathways and processes implicated by my high-throughput screens. I will study these disruptions in iPSC-derived astrocytes, neurons, and in astrocyte-neuron co- cultures. Additionally, to be able to predict how the genes and pathways disrupted by APOE4 relate to each other, I will build computational networks with data from yeast screens, iPSCs, and patient datasets and use them to generate testable hypotheses on the cell type-specific and AD-specific effects of APOE4. I will work with my mentor, Dr. Li-Huei Tsai, co-mentorship committee, Dr. Angelika Amon, Dr. Judith Frydman, and Dr. Jeff Kelly, and my advisory committee, Dr. Bonnie Berger, Dr. Phillip De Jager, and Dr. David Holtzman to carry out my proposed training plan. The proposed mechanistic studies in iPSC-derived cells and predictive computational tools will complement my past training in yeast genetics, cell biology, and biophysics to provide a strong foundation for an independent research program dedicated to the long-term goal of understanding the molecular dysfunctions that lead to AD.

Public Health Relevance

With the number of affected individuals in the US projected to triple by 2050, Alzheimer's disease poses one of the most imminent threats to public health. No approved therapy exists for Alzheimer's disease that targets the underlying molecular factors. I propose to investigate how the major genetic risk factor for Alzheimer's disease, APOE4, increases disease susceptibility in order to decipher the mechanisms underlying disease risk and devise new therapeutic strategies for this devastating disorder.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Career Transition Award (K99)
Project #
5K99AG055697-03
Application #
9526986
Study Section
Neuroscience of Aging Review Committee (NIA)
Program Officer
Wise, Bradley C
Project Start
2017-07-15
Project End
2019-06-30
Budget Start
2018-07-15
Budget End
2019-06-30
Support Year
3
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Type
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code