Project Summary:
Alzheimer’s disease (AD) is the most common neurodegenerative dementia and a major public health problem that is a growing epidemic across the globe. Early identification of AD dementia is essential for preventing or delaying disease onset. However, the mechanisms that lead to synapse destabilization and neuron death remain elusive. There is currently no effective treatment for AD, which may be attributed in part to the lack of a clear underlying mechanism.
Mild Cognitive Impairment (MCI), a prodromal stage of dementia, is prevalent in older adults, affecting around 22% of people aged 65 years or older in the United States. MCI with memory impairment (amnestic type or aMCI) is the prototypical prodromal symptomatic stage of AD, with progression rates from MCI to dementia due to AD ranging from 10 to 15% per year in clinical samples. Gold standard clinical practices for diagnosing MCI include self-reported symptoms, neuropsychological testing, and MRI and other lab workup to rule out known possible causes such as systemic or brain diseases. Early pathological changes associated with AD—beta-amyloid (Aβ) deposition and tau accumulation—cannot reliably predict who will develop clinical symptoms of AD in their lifetimes. In fact, only about one-third of people diagnosed with MCI who test positive for AD biomarkers develop dementia within five years.
Dementia significantly afflicts the quality of life and productivity of those affected, resulting in loss of employment and independence, impacting not only the affected individuals, but also immediate family members and others tasked with providing care. In Wisconsin, it is estimated that 205,000 caregivers will provide 297 million hours of unpaid care, a value of over $5.5 billion, in 2024 alone. In addition to the loss of economic productivity, dementia also imposes a heavy burden on the state’s healthcare system, with $777 million in Medicaid costs in 2020. Around 11% of Wisconsinites aged 45 years or older report living with cognitive decline, the second highest incidence in the Midwest.
The share of the state’s total population above age 60 is 25% (the 16th largest among U.S. states and the second among contiguous states), and this proportion is projected to grow over the coming decades, reaching 29% by 2040. Therefore, understanding the neural mechanisms underlying memory decline and developing more effective diagnostictools for early detection of dementia are high priorities for biomedical research in Wisconsin.
Novel neuroimaging techniques focusing on fine-scale patterns of brain activity hold untapped potential to detect AD dementia, potentially even earlier than biomarkers of Aβ and tau. While several studies have used functional MRI (fMRI) to investigate changes in brain activity associated with aMCI and AD, virtually all of them rely on cognitive subtraction paradigms that measure the overall difference in neural activation between two cognitive tasks. Representation similarity analysis (RSA) of multivoxel activation patterns, on the other hand, measures the information content encoded in those patterns, which is largely undetectable to conventional univariate activation techniques.
This project will generate preliminary data on how cognitive decline in aMCI is related to changes in neural representations of individual concepts detected with fMRI during semantic word processing. Data from persons clinically diagnosed with aMCI will be compared with data from age-matched cognitively unimpaired participants, and the results will reveal whether differences in the neural representation of word meanings—assessed with state-of-the-art fMRI techniques developed by the research team—can predict 1) MCI status and 2) individual differences in semantic memory performance. This will be the first step toward developing a neuroimaging protocol that might allow early detection of the cognitive decline associated with AD, as well as an important advance in the understanding of how semantic memory is implemented in the brain. These results will serve as preliminary data for a grant application to the National Institute on Aging to fund a large-scale study examining these questions in greater depth.