The Synapse Project

Study Overview
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Brief Summary
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The overarching goal of this project is to use [C-11]UCB-J to obtain spatial information on neuronal synapse abundance and inform Alzheimer's disease (AD) progression. The investigators propose to collect longitudinal amyloid, tau, and Synaptic vesicle glycoprotein 2A (SV2A) positron emission tomography (PET) in participants in the Wisconsin Alzheimer's Disease Research Center (ADRC) and Wisconsin Registry for Alzheimer's Prevention (WRAP) across the clinical stages of AD, including cognitively unimpaired biomarker negative, unimpaired biomarker positive, mild cognitive impairment (MCI), and dementia due to AD.

Detailed Description
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Synaptic loss is a major feature of symptomatic AD. Conversely, abundance of synapses may confer resilience to cognitive decline in the presence of AD pathology. The pathology-defining features of AD are amyloid plaques and neurofibrillary tangles and their presence and distribution can be spatially estimated in-vivo with amyloid and tau PET. Although these biomarkers can inform on the degree and location of pathology, they do not provide an indicator of their effect on collocated or extended in-network neural damage including synaptic density. SV2A is expressed ubiquitously in synapses and the capability of assessing SV2A in vivo may provide a direct indicator of synaptic health. Such information would be of high importance for staging the level of synaptic loss or conversely synaptic abundance in the AD continuum and may potentially improve prognostic precision. The PET radioligand [C-11]UCB-J is a marker of SV2A. The overarching goal of this project is to use [C-11]UCB-J to obtain spatial information on neuronal synapse abundance and inform upon disease progression. The investigators propose to collect longitudinal amyloid, tau, and SV2A PET in participants in the Wisconsin ADRC and WRAP across the clinical stages of AD, including cognitively unimpaired biomarker negative, unimpaired biomarker positive, MCI, and dementia due to AD. Specific Aim 1). Determine the extent to which [C-11]UCB-J provides unique information from MRI regarding neurodegeneration. Approach: The investigators will recruit N=60 cognitively unimpaired participants, N=30 MCI participants, and N=30 participants with AD dementia to undergo PET imaging with [C-11]UCB-J. MRI will include anatomic and diffusion connectivity MRI. When available, ancillary cerebrospinal fluid (CSF) indicators of neurodegeneration and synapse function will be examined for relationships with UCB-J. Specific Aim 2). Determine the rate of synapse loss as reflected by [C-11]UCB-J signal across all participants. Rationale: Trajectories of synaptic loss are unknown in vivo. Approach: The investigators will determine the longitudinal trajectories of regional synapse loss that are observed over time among participants who undergo repeat [C-11]UCB-J (separated by two years, same participants scanned for Aim 1). The investigators will also examine trajectories by amyloid and tau load. Quantifying longitudinal synaptic loss is expected to eventually facilitate the identification of individuals who are progressing to dementia, as well as inform upon changes that are normal for age. Specific Aim 3). Determine the extent to which [C-11]UCB-J associates with cognitive decline. Rationale: The investigators expect that lower baseline SV2A density and longitudinal decline in SV2A density in the medial temporal lobe will be associated with faster progression of cognitive decline. The investigators will also test the extent to which harboring multiple pathologies (↑amyloid, ↑tau, and ↓SV2A density) contributes to cognitive decline. Approach: The investigators will examine core indices of cognitive status and continuous measures of cognitive function from the source cohorts and utilize mixed effects models to ascertain the effect of UCB-J amyloid and tau on cognition. Specific Aim 4). Determine factors which impact synapse loss. Rationale: Several risk factors for cognitive decline and dementia have been identified including potentially modifiable factors such as insulin resistance and vascular risk factors. Approach: The investigators will determine cross-sectional and longitudinal trajectories of regional synapse loss in relation to risk factors for cognitive decline and dementia. In order to determine insulin resistance, the investigators will perform blood draw and assess fasting glucose and insulin values to determine the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). The impact of potentially modifiable risk factors on synapse loss in vivo is currently unknown. This aim will address this gap in knowledge, results which may translate to strategies for reducing dementia risk.

Official Title
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SV2A PET Imaging in Alzheimer's Disease

Conditions
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Alzheimer Disease

Intervention / Treatment
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* Drug: UCB-J


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Cognitively unimpaired adults- Aged 55 - 89 Normal cognition (results of most recent testing with the source cohort indicate the participant is cognitively unimpaired as judged by consensus or expert review) In good general health with no conditions/medications affecting cognition or imaging Willing to undergo [C-11]UCB-J, [C-11]PiB, and [F-18]MK6240 PET scans An adequate MRI exam within 12 months prior to baseline. An MRI will be performed if not already available. Mild dementia and amnestic Mild Cognitive Impairment- Aged 50 years or older Abnormal cognitive status of MCI or dementia as judged by consensus or expert review using NIA-AA 2018 criteria MCI's must be affected in the memory domain but may also have other affected domains Willing to undergo [C-11]UCB-J, [C-11]PiB, and [F-18]MK6240 PET scans An adequate MRI exam within 12 months prior to baseline. This MRI exam will come from ADRC/WRAP studies. Clinical MRI's (ones obtained outside of the research program) will not be adequate. An MRI will be performed if not already available from within the research program. Exclusion Criteria: For women, pregnant, lactating or breastfeeding, or intention to become pregnant Evidence of unstable or untreated clinically significant gastrointestinal, cardiovascular, hepatic, renal, hematological, neoplastic, endocrine, alternative neurological, immunodeficiency, pulmonary, or other disorder or disease. Stable, treated chronic medical conditions like hypertension, hypercholesterolemia, diabetes mellitus, non-metastatic dermatologic or prostatic cancer, etc. are acceptable as long as they do not, in the study investigator's opinion, contribute to cognitive dysfunction or limit participation in study procedures. Any illness or other consideration that makes it unlikely that the subject will be able to complete the 24-month study. Current or prior history (within past 5 years) of significant alcohol or substance abuse as determined by the investigator. Psychiatric disorders that may interfere with the study including current major Axis I DSM-V disorders including but not limited to severe Major depression, current or history of bipolar I disorder, or schizophrenia. Current use of the anti-seizure medication Levetiracetam, also known as Keppra, Spritam or Roweepra MRI exclusion criteria include findings from previous MRI's within the ADRC/WRAP research program that may be responsible for neurologic status of the subject such as evidence of cerebrovascular disease with multiple infarcts, infectious disease, space-occupying lesion, normal pressure hydrocephalus, CNS trauma, or any other structural abnormality that may impact cognition or image analysis, as judged by the investigator. MRI-incompatible implants or devices such as certain cardiac pacemakers or defibrillators, insulin pumps, cochlear implants, metallic ocular foreign body, implanted neural stimulators, CNS aneurysm clips and other medical implants that have not been certified for MRI, or history of claustrophobia in MRI that prevents completion of MRI protocol. Lack of decisional capacity at the time of informed consent Lumbar puncture exclusion criteria include: previous lumbar spine surgery, currently taking blood-thinning anti-platelet medications, taking immunosuppressive medications, currently being treated or were recently treated for an infection or virus within the last 2 to 3 months.

Ages Eligible for Study
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Minimum Age: 55 Years
Maximum Age: 89 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Allocation: Non-Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Active Comparator: Cognitively unimpaired<br>Results of most recent testing with the source cohort indicate the participant is cognitively unimpaired as judged by consensus or expert review. | Drug: UCB-J<br>* PET imaging with UCB-J<br>|
| Active Comparator: Mild Cognitive Impairment<br>Abnormal cognitive status of MCI as judged by consensus or expert review using NIA-AA 2018 criteria. | Drug: UCB-J<br>* PET imaging with UCB-J<br>|
| Active Comparator: Mild dementia<br>Abnormal cognitive status of dementia as judged by consensus or expert review using NIA-AA 2018 criteria. | Drug: UCB-J<br>* PET imaging with UCB-J<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Difference between ROC AUCs (MCI/AD vs cognitively unimpaired (CU)) for medial temporal lobe (MTL) UCB-J distribution volume ratio (DVR) and hippocampal volume | DeLong's method will test whether the MTL UCB-J receiver-operator characteristic (ROC) area under the curve (AUC) has better mild cognitive impairment/probable AD dementia (MCI/AD) prediction accuracy than the hippocampal volume ROC AUC. | Baseline | 
| Difference between ROC AUCs (MCI/AD vs CU) for MTL UCB-J and hippocampal cingulum neurite density index | DeLong's method will test whether the MTL UCB-J ROC AUC has better MCI/AD prediction accuracy than the hippocampal cingulum neurite density index ROC AUC. | Baseline | 
| Annual rate of change in UCB-J DVR | Linear mixed effects regression will model UCB-J DVR as a function of time since baseline. | Baseline and 2 years | 
| Baseline diagnosis group differences in annual rate of change in UCB-J DVR | Baseline diagnosis (CU vs MCI/probable AD dementia) group differences in rate of UCB-J DVR change will be estimated via group x time interaction term in a linear mixed effects model. | baseline and 2 years | 
| Amyloid positivity status differences in annual rate of change in UCB-J DVR | Amyloid positivity status differences in rate of UCB-J DVR change will be estimated via group x time interaction term in a linear mixed effects model. Amyloid positivity status will be determined from amyloid PET. | baseline and 2 years | 
| Tau positivity status differences in annual rate of change in UCB-J DVR | Tau positivity status differences in rate of UCB-J DVR change will be estimated via group x time interaction term in a linear mixed effects model. Tau positivity status will be determined from tau PET. | baseline and 2 years | 
| MTL UCB-J DVR baseline differences in a cognitive performance age slope in non-demented participants | Linear mixed effects will be used to model non-demented participants' MTL UCB-J DVR baseline differences in a cognitive performance age slope via an MTL UCB-J DVR baseline x age interaction term with education and sex controlled. Cognitive performance will be assessed using a cognitive composite index comprised of episodic memory, learning, and executive functioning tests. | baseline and 2 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Difference between ROC AUCs (MCI/AD vs CU) for medial temporal lobe (MTL) UCB-J distribution volume ratio (DVR) and cerebrospinal fluid (CSF) neurofilament light chain protein (NfL) | DeLong's method will test whether the MTL UCB-J ROC AUC has better mild cognitive impairment/probable AD dementia (MCI/AD) prediction accuracy than the CSF NfL ROC AUC. | baseline | 
| Difference between ROC AUCs (MCI/AD vs CU) for MTL UCB-J DVR and cerebrospinal fluid (CSF) T-tau | DeLong's method will test whether the MTL UCB-J ROC AUC has better MCI/AD prediction accuracy than the CSF T-tau ROC AUC. | baseline | 
| Difference between ROC AUCs (MCI/AD vs CU) for MTL UCB-J and CSF neurogranin | DeLong's method will test whether the MTL UCB-J ROC AUC has better MCI/AD prediction accuracy than the CSF neurogranin ROC AUC. | baseline | 
| Sex differences in annual rate of change in UCB-J DVR | Sex differences in rate of UCB-J DVR change will be estimated via group x time interaction term in a linear mixed effects model. | baseline and 2 years | 
| Age differences in annual rate of change in UCB-J DVR | Age differences in rate of UCB-J DVR change will be estimated in a linear mixed effects model. | baseline and 2 years | 
| APOE4 allele status differences in annual rate of change in UCB-J DVR | APOE4 allele status differences in rate of UCB-J DVR change will be estimated via group x time interaction term in a linear mixed effects model. | baseline and 2 years |