Late-onset AD
Late-onset Alzheimer’s disease (LoAD) accounts for >90% of AD cases, and the preclinical phase of LoAD is crucial for diagnosis and intervention.
The pathological changes (like amyloid deposition and tau accumulation) that accompany LoAD show a characteristic pattern of emergence and spread across the brain. Some brain regions are affected to a much greater degree than are others.
The underlying neurochemistry of these spatial patterns, and their biological basis is not understood and may hold the keys to diagnosis, and in the case of brain areas that are relatively protected even at late stages of the disease, to protective intervention.
Current questions and approaches
In this work, we measure the levels of thousands of proteins (the proteome) and metabolites (the metabolome) at hundreds of sites across the cortex and cerebellum, sampling the whole surface at about 5mm resolution.
The resulting data live in a very high dimensional space (thousands of dimensions). To get traction on the underlying patterns, we collaborate with Duke Biostatistician Dr. Pixu Shi to develop sophisticated statistical tools based on spatial principal component analysis and partial least squares discriminant analysis.
We also use bioinformatics methods to integrate the metabolome and proteome for pathway and network analysis. Our collaborator Dr. Michael Lutz provides powerful tools adapted from gene set enrichment analysis to work with our data, and to compare our data with data from human patients with AD
Some of the specific questions we are interested in are:
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- What are the biochemical differences between brain regions like the entorhinal cortex that are highly vulnerable to AD pathology and regions like the cerebellum that seem to be relatively protected?
- How do a high sugar diet and low levels of exercise impact this chemistry?
- Why do macaques develop biomarkers of AD and show mild cognitive impairment but then do not progress to the most devastating stages of AD pathology? Is there something different about their whole brain biochemistry, when compared with humans, that is protective?
Because it is not fully genetically determined, late-onset (also known as spontaneous) AD is not well-modeled by the transgenic animal models commonly used in aging research.
Macaque monkeys, on the other hand, model the preclinical phase of LoAD without genetic modification.
Specifically, Macaques:
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- recapitulate the spontaneous accumulation of amyloid and tau pathology seen with aging in humans,
- show accompanying memory impairment equivalent to mild cognitive impairment in humans,
- carry only one apolipoprotein isoform, equivalent to the high-risk human ε4 allele.
Furthermore, female macaques undergo menopause, which is a risk factor and likely time of onset for preclinical changes in human females. This means that all female macaques are at high risk for LoAD-like pathology.
The macaque monkey - more specifically the per-menopausal female macaque - thus offers a unique opportunity to study preclinical brain changes in aging and LoAD, in a species with a brain that is structurally and functionally very similar to that of humans.
Image: Timothy Gonsalves, CC BY-SA 4.0, via Wikimedia Commons.