Date of Award
5-2019
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Program
Biomedical Sciences
Track
Neuroscience
Research Advisor
Robert W. Williams, PhD.
Committee
William E. Armstrong, David Bridges, Catherine C. Kaczorowski, Kyhobeni Mozhui, Kristen M.S. O'Connell
Keywords
aging, Alzheimer's disease, cognitive decline, genetics, mouse models
Abstract
An individual's genetic makeup plays an important role in determining susceptibility to cognitive aging and transition to dementia such as Alzheimer's disease (AD). Identifying the specific genetic variants that contribute to cognitive aging and AD may aid in early diagnosis of at-risk patients, as well as identify novel therapeutics targets to treat or prevent development of symptoms. Challenges to identifying these specific genes in human studies include complex genetics, difficulty in controlling environmental factors, and limited access to human brain tissue. Here, we turned to genetically diverse mice from the BXD genetic reference panel (GRP) to overcome some of the barriers traditionally associated with human studies. Using a forward genetics screen, we first identified and validated the gene heterochromatin protein l binding protein 3 (Hp1bp3) as a novel modulator of normal cognitive aging. We then demonstrated that targeted knockdown of Hp1bp3 in the hippocampus by 50-75% was sufficient to induce cognitive deficits and transcriptional changes reminiscent of those observed in aging and AD, namely an increase in inflammatory pathways and decrease in neuronal and synaptically-localized transcripts. We also show Hp1bp3 is a translationally relevant target, as transcriptional changes induced by our targeted knockdown significantly overlapped those observed in the aging human brain. In addition, HPlBP3 itself was decreased in the hippocampus of cognitively impaired aging humans. In summary, our results suggest therapeutics designed to target either Hp1bp3 or its downstream effectors may be useful promoting cognitive longevity. We next expanded on our findings that the BXDs were variably susceptible to cognitive aging and combined the BXD GRP with a well-established transgenic mouse model of AD harboring 5 familial AD mutations, the 5XFAD model. The resulting panel, which we termed the AD-BXDs, consists of genetically diverse yet isogenic Fl mice that all harbor the same high-risk human AD mutations but who differ across the remainder of their genome. We first showed that genetic variation profoundly modified the impact of human AD mutations on both cognitive and pathological phenotypes. We then validated this complex AD model by demonstrating high degrees of genetic, transcriptomic, and phenotypic overlap with human AD. Genetic mapping was used to identify novel genomic loci that modified susceptibility or resilience to cognitive and pathological symptoms of AD. Finally, we used transcriptome profiling to identify gene networks present in the pre-symptomatic mouse brain that predict cognitive performance at an advanced age. Together, the candidates identified through these analyses highlight new potential drivers of susceptibility or resilience to AD and contribute significantly to our understanding of early, potentially causal disease mechanisms. In summary, work here highlights the utility of genetically diverse mice to elucidate mechanisms underlying complex human disease, namely cognitive aging and AD. In addition, we developed a novel AD mouse population as an innovative and reproducible resource for the study of mechanisms underlying AD. Data presented here provides convincing evidence that preclinical models incorporating genetic diversity may better translate to human disease. Due to the reproducible nature of the BXDs and resulting AD-BXDs, this approach creates substantial opportunities to develop improved models of human aging and AD as well as develop a better understanding of precise mechanisms underlying disease. Together, these resources may ultimately enable precision medicine approaches across a diverse population. Finally, our experimental design is likely to be broadly applicable to mouse models of human disease that incorporate a dominantly inherited high-risk genotype in the form of a transgene or other genetic perturbation, enhancing the general utility of results reported here.
ORCID
0000-0001-5091-401X
DOI
10.21007/etd.cghs.2019.0477
Recommended Citation
Neuner, Sarah M. (0000-0001-5091-401X), "Using Genetic Diversity to Understand Susceptibility to Cognitive Decline in Aging and Alzheimer’s Disease" (2019). Theses and Dissertations (ETD). Paper 485. http://dx.doi.org/10.21007/etd.cghs.2019.0477.
https://dc.uthsc.edu/dissertations/485
Declaration of Authorship
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