Synaptic density patterns in early Alzheimer's disease assessed by independent component analysis.

Synaptic loss is a primary pathology in Alzheimer's disease and correlates best with cognitive impairment as found in post-mortem studies. Previously, we observed in vivo reductions of synaptic density with [11C]UCB-J PET (radiotracer for synaptic vesicle protein 2A) throughout the neocortex and medial temporal brain regions in early Alzheimer's disease. In this study, we applied independent component analysis to synaptic vesicle protein 2A-PET data to identify brain networks associated with cognitive deficits in Alzheimer's disease in a blinded data-driven manner. [11C]UCB-J binding to synaptic vesicle protein 2A was measured in 38 Alzheimer's disease (24 mild Alzheimer's disease dementia and 14 mild cognitive impairment) and 19 cognitively normal participants. [11C]UCB-J distribution volume ratio values were calculated with a whole cerebellum reference region. Principal components analysis was first used to extract 18 independent components to which independent component analysis was then applied. Subject loading weights per pattern were compared between groups using Kruskal-Wallis tests. Spearman's rank correlations were used to assess relationships between loading weights and measures of cognitive and functional performance: Logical Memory II, Rey Auditory Verbal Learning Test-long delay, Clinical Dementia Rating sum of boxes and Mini-Mental State Examination. We observed significant differences in loading weights among cognitively normal, mild cognitive impairment and mild Alzheimer's disease dementia groups in 5 of the 18 independent components, as determined by Kruskal-Wallis tests. Only Patterns 1 and 2 demonstrated significant differences in group loading weights after correction for multiple comparisons. Excluding the cognitively normal group, we observed significant correlations between the loading weights for Pattern 1 (left temporal cortex and the cingulate gyrus) and Clinical Dementia Rating sum of boxes (r = -0.54, P = 0.0019), Mini-Mental State Examination (r = 0.48, P = 0.0055) and Logical Memory II score (r = 0.44, P = 0.013). For Pattern 2 (temporal cortices), significant associations were demonstrated between its loading weights and Logical Memory II score (r = 0.34, P = 0.0384). Following false discovery rate correction, only the relationship between the Pattern 1 loading weights with Clinical Dementia Rating sum of boxes (r = -0.54, P = 0.0019) and Mini-Mental State Examination (r = 0.48, P = 0.0055) remained statistically significant. We demonstrated that independent component analysis could define coherent spatial patterns of synaptic density. Furthermore, commonly used measures of cognitive performance correlated significantly with loading weights for two patterns within only the mild cognitive impairment/mild Alzheimer's disease dementia group. This study leverages data-centric approaches to augment the conventional region-of-interest-based methods, revealing distinct patterns that differentiate between mild cognitive impairment and mild Alzheimer's disease dementia, marking a significant advancement in the field.

Relationship between neuroimaging and cognition in frontotemporal dementia: An FDG-PET and structural MRI study.

BACKGROUND AND PURPOSE: Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative condition with a prevalence comparable to Alzheimer's disease for patients under 65 years of age. Limited studies have examined the association between cognition and neuroimaging in FTD using different imaging modalities. METHODS: We examined the association of cognition using Montreal Cognitive Assessment (MoCA) with both gray matter (GM) volume and glucose metabolism using magnetic resonance imaging and fluorodeoxyglucose (FDG)-PET in 21 patients diagnosed with FTD. Standardized uptake value ratio (SUVR) using the brainstem as a reference region was the primary outcome measure for FDG-PET. Partial volume correction was applied to PET data to account for disease-related atrophy. RESULTS: Significant positive associations were found between whole-cortex GM volume and MoCA scores (r = 0.46, p = .04). The association between whole-cortex FDG SUVR and MoCA scores was not significant (r = 0.37, p = .09). GM volumes of the frontal cortex (r = 0.54, p = .01), caudate (r = 0.62, p<.01), and insula (r = 0.57, p<.01) were also significantly correlated with MoCA, as were SUVR values of the insula (r = 0.51, p = .02), thalamus (r = 0.48, p = .03), and posterior cingulate cortex (PCC) (r = 0.47, p = .03). CONCLUSIONS: Whole-cortex atrophy is associated with cognitive dysfunction, and this association is larger than for whole-cortex hypometabolism as measured with FDG-PET. At the regional level, focal atrophy and/or hypometabolism in the frontal cortex, insula, PCC, thalamus, and caudate seem to be important for the decline of cognitive function in FTD. Furthermore, these results highlight how functional and structural changes may not overlap and might contribute to cognitive dysfunction in FTD in different ways.

Sex differences in the pleiotropy of hearing difficulty with imaging-derived phenotypes: a brain-wide investigation.

Hearing difficulty (HD) is one of the major health burdens in older adults. While aging-related changes in the peripheral auditory system play an important role, genetic variation associated with brain structure and function could also be involved in HD predisposition. We analyzed a large-scale HD genome-wide association study (GWAS; Ntotal = 501,825, 56% females) and GWAS data related to 3,935 brain imaging-derived phenotypes (IDPs) assessed in up to 33,224 individuals (52% females) using multiple magnetic resonance imaging modalities. To investigate HD pleiotropy with brain structure and function, we conducted genetic correlation, latent causal variable, Mendelian randomization, and multivariable generalized linear regression analyses. Additionally, we performed local genetic correlation and multi-trait colocalization analyses to identify genomic regions and loci implicated in the pleiotropic mechanisms shared between HD and brain IDPs. We observed a widespread genetic correlation of HD with 120 IDPs in females, 89 IDPs in males, and 171 IDPs in the sex-combined analysis. The latent causal variable analysis showed that some of these genetic correlations could be due to cause-effect relationships. For seven correlations, the causal effects were also confirmed by the Mendelian randomization approach: vessel volume→HD in the sex-combined analysis; hippocampus volume→HD, cerebellum grey matter volume→HD, primary visual cortex volume→HD, and HD→fluctuation amplitudes of node 46 in resting-state functional MRI dimensionality 100 in females; global mean thickness→HD and HD→mean orientation dispersion index in superior corona radiata in males. The local genetic correlation analysis identified 13 pleiotropic regions between HD and these seven IDPs. We also observed a colocalization signal for the rs13026575 variant between HD, primary visual cortex volume, and SPTBN1 transcriptomic regulation in females. Brain structure and function may have a role in the sex differences in HD predisposition via possible cause-effect relationships and shared regulatory mechanisms.

Relationship between Neuroimaging and Cognition in Frontotemporal Dementia: A [18 F]FDG PET and Structural MRI Study.

Background: Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous condition with a prevalence comparable to Alzheimer's Disease for patients under sixty-five years of age. Gray matter (GM) atrophy and glucose hypometabolism are important biomarkers for the diagnosis and evaluation of disease progression in FTD. However, limited studies have systematically examined the association between cognition and neuroimaging in FTD using different imaging modalities in the same patient group. Methods: We examined the association of cognition using Montreal Cognitive Assessment (MoCA) with both GM volume and glucose metabolism using structural magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography scanning ([18F]FDG PET) in 21 patients diagnosed with FTD. Standardized uptake value ratio (SUVR) using the brainstem as a reference region was the primary outcome measure for [18F]FDG PET. Partial volume correction was applied to PET data to account for disease-related atrophy. Results: Significant positive associations were found between whole-cortex GM volume and MoCA scores (r = 0.461, p = 0.035). The association between whole-cortex [18F]FDG SUVR and MoCA scores was not Significant (r = 0.374, p = 0.094). GM volumes of the frontal cortex (r = 0.540, p = 0.011), caudate (r = 0.616, p = 0.002), and insula (r = 0.568, p = 0.007) were also Significantly correlated with MoCA, as were SUVR values of the insula (r = 0.508, p = 0.018), thalamus (r = 0.478, p = 0.028), and posterior cingulate cortex (PCC) (r = 0.472, p = 0.030). Discussion: Whole-cortex atrophy is associated with cognitive dysfunction, and this effect is larger than for cortical hypometabolism as measured with [18F]FDG PET. At the regional level, focal atrophy and/or hypometabolism in the frontal lobe, insula, PCC, thalamus, and caudate seem to imply the importance of these regions for the decline of cognitive function in FTD. Furthermore, these results highlight how functional and structural changes may not overlap and might contribute to cognitive dysfunction in FTD in different ways. Our findings provide insight into the relationships between structural, metabolic, and cognitive changes due to FTD.

Assessment of disparities in timely diagnosis and comprehensive workup of cognitive impairment between English and Spanish speakers.

BACKGROUND: Previous studies have examined disparities in dementia care that affect the U.S. Hispanic/Latino population, including clinician bias, lack of cultural responsiveness, and less access to health care. However, there is limited research that specifically investigates the impact of language barriers to health disparities in dementia diagnosis. METHODS: In this retrospective cross-sectional study, 12,080 English- or Spanish- speaking patients who received an initial diagnosis of mild cognitive impairment (MCI) or dementia between July 2017 and June 2019 were identified in the Yale New Haven Health (YNHH) electronic medical record. To evaluate the timeliness of diagnosis, an initial diagnosis of MCI was classified as "timely", while an initial diagnosis of dementia was considered "delayed." Comprehensiveness of diagnosis was assessed by measuring the presence of laboratory studies, neuroimaging, specialist evaluation, and advanced diagnostics six months before or after diagnosis. Binomial logistic regressions were calculated with and without adjustment for age, legal sex, ethnicity, neighborhood disadvantage, and medical comorbidities. RESULTS: Spanish speakers were less likely to receive a timely diagnosis when compared with English speakers both before (unadjusted OR, 0.65; 95% CI, 0.53-0.80, p <0.0001) and after adjusting for covariates (adjusted OR, 0.55; 95% CI, 0.40-0.75, p = 0.0001). Diagnostic services were provided equally between groups, except for referrals to geriatrics, which were more frequent among Spanish-speaking patients. A subgroup analysis revealed that Spanish-speaking Hispanic/Latino patients were less likely to receive a timely diagnosis compared to English-speaking Hispanic/Latino patients (adjusted OR, 0.53; 95% CI, 0.38-0.73, p = 0.0001). CONCLUSIONS: Non-English language preference is likely to be a contributing factor to timely diagnosis of cognitive impairment. In this study, Spanish language preference rather than Hispanic/Latino ethnicity was a significant predictor of a less timely diagnosis of cognitive impairment. Policy changes are needed to reduce barriers in cognitive disorders care for Spanish-speaking patients.

A pilot study to evaluate the effect of CT1812 treatment on synaptic density and other biomarkers in Alzheimer's disease.

BACKGROUND: Effective, disease-modifying therapeutics for the treatment of Alzheimer's disease (AD) remain a large unmet need. Extensive evidence suggests that amyloid beta (Aß) is central to AD pathophysiology, and Aß oligomers are among the most toxic forms of Aß. CT1812 is a novel brain penetrant sigma-2 receptor ligand that interferes with the binding of Aß oligomers to neurons. Preclinical studies of CT1812 have demonstrated its ability to displace Aß oligomers from neurons, restore synapses in cell cultures, and improve cognitive measures in mouse models of AD. CT1812 was found to be generally safe and well tolerated in a placebo-controlled phase 1 clinical trial in healthy volunteers and phase 1a/2 clinical trials in patients with mild to moderate dementia due to AD. The unique objective of this study was to incorporate synaptic positron emission tomography (PET) imaging as an outcome measure for CT1812 in AD patients. METHODS: The present phase 1/2 study was a randomized, double-blind, placebo-controlled, parallel-group trial conducted in 23 participants with mild to moderate dementia due to AD to primarily evaluate the safety of CT1812 and secondarily its pharmacodynamic effects. Participants received either placebo or 100 mg or 300 mg per day of oral CT1812 for 24 weeks. Pharmacodynamic effects were assessed using the exploratory efficacy endpoints synaptic vesicle glycoprotein 2A (SV2A) PET, fluorodeoxyglucose (FDG) PET, volumetric MRI, cognitive clinical measures, as well as cerebrospinal fluid (CSF) biomarkers of AD pathology and synaptic degeneration. RESULTS: No treatment differences relative to placebo were observed in the change from baseline at 24 weeks in either SV2A or FDG PET signal, the cognitive clinical rating scales, or in CSF biomarkers. Composite region volumetric MRI revealed a trend towards tissue preservation in participants treated with either dose of CT1812, and nominally significant differences with both doses of CT1812 compared to placebo were found in the pericentral, prefrontal, and hippocampal cortices. CT1812 was safe and well tolerated. CONCLUSIONS: The safety findings of this 24-week study and the observed changes on volumetric MRI with CT1812 support its further clinical development. TRIAL REGISTRATION: The clinical trial described in this manuscript is registered at clinicaltrials.gov (NCT03493282).

The regional pattern of age-related synaptic loss in the human brain differs from gray matter volume loss: in vivo PET measurement with [11C]UCB-J.

PURPOSE: Aging is a major societal concern due to age-related functional losses. Synapses are crucial components of neural circuits, and synaptic density could be a sensitive biomarker to evaluate brain function. [11C]UCB-J is a positron emission tomography (PET) ligand targeting synaptic vesicle glycoprotein 2A (SV2A), which can be used to evaluate brain synaptic density in vivo. METHODS: We evaluated age-related changes in gray matter synaptic density, volume, and blood flow using [11C]UCB-J PET and magnetic resonance imaging (MRI) in a wide age range of 80 cognitive normal subjects (21-83 years old). Partial volume correction was applied to the PET data. RESULTS: Significant age-related decreases were found in 13, two, and nine brain regions for volume, synaptic density, and blood flow, respectively. The prefrontal cortex showed the largest volume decline (4.9% reduction per decade: RPD), while the synaptic density loss was largest in the caudate (3.6% RPD) and medial occipital cortex (3.4% RPD). The reductions in caudate are consistent with previous SV2A PET studies and likely reflect that caudate is the site of nerve terminals for multiple major tracts that undergo substantial age-related neurodegeneration. There was a non-significant negative relationship between volume and synaptic density reductions in 16 gray matter regions. CONCLUSION: MRI and [11]C-UCB-J PET showed age-related decreases of gray matter volume, synaptic density, and blood flow; however, the regional patterns of the reductions in volume and SV2A binding were different. Those patterns suggest that MR-based measures of GM volume may not be directly representative of synaptic density.

Assessment of Gray Matter Microstructure and Synaptic Density in Alzheimer's Disease: A Multimodal Imaging Study With DTI and SV2A PET.

OBJECTIVE: Multimodal imaging techniques have furthered our understanding of how different aspects of Alzheimer's disease (AD) pathology relate to one another. Diffusion tensor imaging (DTI) measures such as mean diffusivity (MD) may be a surrogate measure of the changes in gray matter structure associated with AD. Positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) has been used to quantify synaptic loss, which is the major pathological correlate of cognitive impairment in AD. In this study, we investigated the relationship between gray matter microstructure and synaptic density. METHODS: DTI was used to measure MD and [11C]UCB-J PET to measure synaptic density in 33 amyloid-positive participants with AD and 17 amyloid-negative cognitively normal (CN) participants aged 50-83. Univariate regression analyses were used to assess the association between synaptic density and MD in both the AD and CN groups. RESULTS: Hippocampal MD was inversely associated with hippocampal synaptic density in participants with AD (r = -0.55, p <0.001, df = 31) but not CN (r = 0.13, p = 0.62, df = 15). Exploratory analyses across other regions known to be affected in AD suggested widespread inverse associations between synaptic density and MD in the AD group. CONCLUSION: In the setting of AD, an increase in gray matter MD is inversely associated with synaptic density. These co-occurring changes may suggest a link between synaptic loss and gray matter microstructural changes in AD. Imaging studies of gray matter microstructure and synaptic density may allow important insights into AD-related neuropathology.

Aging gene signature of memory CD8+ T cells is associated with neurocognitive functioning in Alzheimer's disease.

BACKGROUND: Memory CD8+ T cells expand with age. We previously demonstrated an age-associated expansion of effector memory (EM) CD8+ T cells expressing low levels of IL-7 receptor alpha (IL-7Rαlow) and the presence of its gene signature (i.e., IL-7Rαlow aging genes) in peripheral blood of older adults without Alzheimer's disease (AD). Considering age as the strongest risk factor for AD and the recent finding of EM CD8+ T cell expansion, mostly IL-7Rαlow cells, in AD, we investigated whether subjects with AD have alterations in IL-7Rαlow aging gene signature, especially in relation to genes possibly associated with AD and disease severity. RESULTS: We identified a set of 29 candidate genes (i.e., putative AD genes) which could be differentially expressed in peripheral blood of patients with AD through the systematic search of publicly available datasets. Of the 29 putative AD genes, 9 genes (31%) were IL-7Rαlow aging genes (P < 0.001), suggesting the possible implication of IL-7Rαlow aging genes in AD. These findings were validated by RT-qPCR analysis of 40 genes, including 29 putative AD genes, additional 9 top IL-7R⍺low aging but not the putative AD genes, and 2 inflammatory control genes in peripheral blood of cognitively normal persons (CN, 38 subjects) and patients with AD (40 mild cognitive impairment and 43 dementia subjects). The RT-qPCR results showed 8 differentially expressed genes between AD and CN groups; five (62.5%) of which were top IL-7Rαlow aging genes (FGFBP2, GZMH, NUAK1, PRSS23, TGFBR3) not previously reported to be altered in AD. Unbiased clustering analysis revealed 3 clusters of dementia patients with distinct expression levels of the 40 analyzed genes, including IL-7Rαlow aging genes, which were associated with neurocognitive function as determined by MoCA, CDRsob and neuropsychological testing. CONCLUSIONS: We report differential expression of "normal" aging genes associated with IL-7Rαlow EM CD8+ T cells in peripheral blood of patients with AD, and the significance of such gene expression in clustering subjects with dementia due to AD into groups with different levels of cognitive functioning. These results provide a platform for studies investigating the possible implications of age-related immune changes, including those associated with CD8+ T cells, in AD.

Dementia risk analysis using temporal event modeling on a large real-world dataset.

The objective of the study is to identify healthcare events leading to a diagnosis of dementia from a large real-world dataset. This study uses a data-driven approach to identify temporally ordered pairs and trajectories of healthcare codes in the electronic health record (EHR). This allows for discovery of novel temporal risk factors leading to an outcome of interest that may otherwise be unobvious. We identified several known (Down syndrome RR = 116.1, thiamine deficiency RR = 76.1, and Parkinson's disease RR = 41.1) and unknown (Brief psychotic disorder RR = 68.6, Toxic effect of metals RR = 40.4, and Schizoaffective disorders RR = 40.0) factors for a specific dementia diagnosis. The associations with the greatest risk for any dementia diagnosis were found to be primarily related to mental health (Brief psychotic disorder RR = 266.5, Dissociative and conversion disorders RR = 169.8), or neurologic conditions or procedures (Dystonia RR = 121.9, Lumbar Puncture RR = 119.0). Trajectory and clustering analysis identified factors related to cerebrovascular disorders, as well as diagnoses which increase the risk of toxic imbalances. The results of this study have the ability to provide valuable insights into potential patient progression towards dementia and improve recognition of patients at risk for developing dementia.

Sex differences in the pleiotropy of hearing difficulty with imaging-derived phenotypes: a brain-wide investigation.

Background: Hearing difficulty (HD) is one of the major health burdens in older adults. While aging-related changes in the peripheral auditory system play an important role, genetic variation associated with brain structure and function could also be involved in HD predisposition. Methods: We analyzed a large-scale HD genome-wide association study (GWAS; N total = 501,825, 56% females) and GWAS data related to 3,935 brain imaging-derived phenotypes (IDPs) assessed in up to 33,224 individuals (52% females) using multiple magnetic resonance imaging (MRI) modalities. To investigate HD pleiotropy with brain structure and function, we conducted genetic correlation, latent causal variable (LCV), Mendelian randomization (MR), and multivariable generalized linear regression analyses. Additionally, we performed local genetic correlation and multi-trait colocalization analyses to identify genomic regions and loci implicated in the pleiotropic mechanisms shared between HD and brain IDPs. Results: We observed a widespread genetic correlation of HD with 120 IDPs in females, 89 IDPs in males, and 171 IDPs in the sex-combined analysis. The LCV analyses showed that some of these genetic correlations could be due to cause-effect relationships. For seven correlations, the causal effects were also confirmed by the MR approach: vessel volume→HD in the sex-combined analysis; hippocampus volume→HD, cerebellum grey matter volume→HD, primary visual cortex volume→HD, and HD→rfMRI-ICA100 node 46 in females; global mean thickness→HD and HD→mean orientation dispersion index in superior corona radiata in males. The local genetic correlation analyses identified 13 pleiotropic regions between HD and these seven IDPs. We also observed a colocalization signal for the rs13026575 variant between HD, primary visual cortex volume, and SPTBN1 transcriptomic regulation in females. Conclusion: Brain structure and function may have a role in the sex differences in HD predisposition via possible cause-effect relationships and shared regulatory mechanisms.

Principal component analysis of synaptic density measured with [11C]UCB-J PET in early Alzheimer's disease.

BACKGROUND: Synaptic loss is considered an early pathological event and major structural correlate of cognitive impairment in Alzheimer's disease (AD). We used principal component analysis (PCA) to identify regional patterns of covariance in synaptic density using [11C]UCB-J PET and assessed the association between principal components (PC) subject scores with cognitive performance. METHODS: [11C]UCB-J binding was measured in 45 amyloid + participants with AD and 19 amyloid- cognitively normal participants aged 55-85. A validated neuropsychological battery assessed performance across five cognitive domains. PCA was applied to the pooled sample using distribution volume ratios (DVR) standardized (z-scored) by region from 42 bilateral regions of interest (ROI). RESULTS: Parallel analysis determined three significant PCs explaining 70.2% of the total variance. PC1 was characterized by positive loadings with similar contributions across the majority of ROIs. PC2 was characterized by positive and negative loadings with strongest contributions from subcortical and parietooccipital cortical regions, respectively, while PC3 was characterized by positive and negative loadings with strongest contributions from rostral and caudal cortical regions, respectively. Within the AD group, PC1 subject scores were positively correlated with performance across all cognitive domains (Pearson r = 0.24-0.40, P = 0.06-0.006), PC2 subject scores were inversely correlated with age (Pearson r = -0.45, P = 0.002) and PC3 subject scores were significantly correlated with CDR-sb (Pearson r = 0.46, P = 0.04). No significant correlations were observed between cognitive performance and PC subject scores in CN participants. CONCLUSIONS: This data-driven approach defined specific spatial patterns of synaptic density correlated with unique participant characteristics within the AD group. Our findings reinforce synaptic density as a robust biomarker of disease presence and severity in the early stages of AD.

Synaptic density and cognitive performance in Alzheimer's disease: A PET imaging study with [11 C]UCB-J.

INTRODUCTION: For 30 years synapse loss has been referred to as the major pathological correlate of cognitive impairment in Alzheimer's disease (AD). However, this statement is based on remarkably few patients studied by autopsy or biopsy. With the recent advent of synaptic vesicle glycoprotein 2A (SV2A) positron emission tomography (PET) imaging, we have begun to evaluate the consequences of synaptic alterations in vivo. METHODS: We examined the relationship between synaptic density measured by [11 C]UCB-J PET and neuropsychological test performance in 45 participants with early AD. RESULTS: Global synaptic density showed a significant positive association with global cognition and performance on five individual cognitive domains in participants with early AD. Synaptic density was a stronger predictor of cognitive performance than gray matter volume. CONCLUSION: These results confirm neuropathologic studies demonstrating a significant association between synaptic density and cognitive performance, and suggest that this correlation extends to the early stages of AD.

Association of entorhinal cortical tau deposition and hippocampal synaptic density in older individuals with normal cognition and early Alzheimer's disease.

Sites of early neuropathologic change provide important clues regarding the initial clinical features of Alzheimer's disease (AD). We have shown significant reductions in hippocampal synaptic density in participants with AD, consistent with the early degeneration of entorhinal cortical (ERC) cells that project to hippocampus via the perforant path. In this study, [11C]UCB-J binding to synaptic vesicle glycoprotein 2A (SV2A) and [18F]flortaucipir binding to tau were measured via PET in 10 participants with AD (5 mild cognitive impairment, 5 mild dementia) and 10 cognitively normal participants. In the overall sample, ERC tau was inversely associated with hippocampal synaptic density (r = -0.59, p = 0.009). After correction for partial volume effects, the association of ERC tau with hippocampal synaptic density was stronger in the overall sample (r = -0.61, p = 0.007) and in the AD group where the effect size was large, but not statistically significant (r = -0.58, p = 0.06). This inverse association of ERC tau and hippocampal synaptic density may reflect synaptic failure due to tau pathology in ERC neurons projecting to the hippocampus.

Glutamate Carboxypeptidase II in Aging Rat Prefrontal Cortex Impairs Working Memory Performance.

Glutamate carboxypeptidase II (GCPII) expression in brain is increased by inflammation, and reduces NAAG (N-acetyl aspartyl glutamate) stimulation of mGluR3 signaling. Genetic insults in this signaling cascade are increasingly linked to cognitive disorders in humans, where increased GCPII and or decreased NAAG-mGluR3 are associated with impaired prefrontal cortical (PFC) activation and cognitive impairment. As aging is associated with increased inflammation and PFC cognitive deficits, the current study examined GCPII and mGluR3 expression in the aging rat medial PFC, and tested whether GCPII inhibition with 2-(3-mercaptopropyl) pentanedioic acid (2-MPPA) would improve working memory performance. We found that GCPII protein was expressed on astrocytes and some microglia as expected from previous studies, but was also prominently expressed on neurons, and showed increased levels with advancing age. Systemic administration of the GCPII inhibitor, 2-MPPA, improved working memory performance in young and aged rats, and also improved performance after local infusion into the medial PFC. As GCPII inhibitors are well-tolerated, they may provide an important new direction for treatment of cognitive disorders associated with aging and/or inflammation.

Generation of synthetic PET images of synaptic density and amyloid from 18 F-FDG images using deep learning.

PURPOSE: Positron emission tomography (PET) imaging with various tracers is increasingly used in Alzheimer's disease (AD) studies. However, access to PET scans using new or less-available tracers with sophisticated synthesis and short half-life isotopes may be very limited. Therefore, it is of great significance and interest in AD research to assess the feasibility of generating synthetic PET images of less-available tracers from the PET image of another common tracer, in particular 18 F-FDG. METHODS: We implemented advanced deep learning methods using the U-Net model to predict 11 C-UCB-J PET images of synaptic vesicle protein 2A (SV2A), a surrogate of synaptic density, from 18 F-FDG PET data. Dynamic 18 F-FDG and 11 C-UCB-J scans were performed in 21 participants with normal cognition (CN) and 33 participants with Alzheimer's disease (AD). Cerebellum was used as the reference region for both tracers. For 11 C-UCB-J image prediction, four network models were trained and tested, which included 1) 18 F-FDG SUV ratio (SUVR) to 11 C-UCB-J SUVR, 2) 18 F-FDG Ki ratio to 11 C-UCB-J SUVR, 3) 18 F-FDG SUVR to 11 C-UCB-J distribution volume ratio (DVR), and 4) 18 F-FDG Ki ratio to 11 C-UCB-J DVR. The normalized root mean square error (NRMSE), structure similarity index (SSIM), and Pearson's correlation coefficient were calculated for evaluating the overall image prediction accuracy. Mean bias of various ROIs in the brain and correlation plots between predicted images and true images were calculated for ROI-based prediction accuracy. Following a similar training and evaluation strategy, 18 F-FDG SUVR to 11 C-PiB SUVR network was also trained and tested for 11 C-PiB static image prediction. RESULTS: The results showed that all four network models obtained satisfactory 11 C-UCB-J static and parametric images. For 11 C-UCB-J SUVR prediction, the mean ROI bias was -0.3% ± 7.4% for the AD group and -0.5% ± 7.3% for the CN group with 18 F-FDG SUVR as the input, -0.7% ± 8.1% for the AD group, and -1.3% ± 7.0% for the CN group with 18 F-FDG Ki ratio as the input. For 11 C-UCB-J DVR prediction, the mean ROI bias was -1.3% ± 7.5% for the AD group and -2.0% ± 6.9% for the CN group with 18 F-FDG SUVR as the input, -0.7% ± 9.0% for the AD group, and -1.7% ± 7.8% for the CN group with 18 F-FDG Ki ratio as the input. For 11 C-PiB SUVR image prediction, which appears to be a more challenging task, the incorporation of additional diagnostic information into the network is needed to control the bias below 5% for most ROIs. CONCLUSIONS: It is feasible to use 3D U-Net-based methods to generate synthetic 11 C-UCB-J PET images from 18 F-FDG images with reasonable prediction accuracy. It is also possible to predict 11 C-PiB SUVR images from 18 F-FDG images, though the incorporation of additional non-imaging information is needed.

Partial volume correction analysis for 11C-UCB-J PET studies of Alzheimer's disease.

PURPOSE: 11C-UCB-J PET imaging, targeting synaptic vesicle glycoprotein 2A (SV2A), has been shown to be a useful indicator of synaptic density in Alzheimer's disease (AD). For SV2A imaging, a decrease in apparent tracer uptake is often due to the combination of gray-matter (GM) atrophy and SV2A decrease in the remaining tissue. Our aim is to reveal the true SV2A change by performing partial volume correction (PVC). METHODS: We performed two PVC algorithms, Müller-Gärtner (MG) and 'iterative Yang' (IY), on 17 AD participants and 11 cognitive normal (CN) participants using the brain-dedicated HRRT scanner. Distribution volume VT, the rate constant K1, binding potential BPND (centrum semiovale as reference region), and tissue volume were compared. RESULTS: In most regions, both PVC algorithms reduced the between-group differences. Alternatively, in hippocampus, IY increased the significance of between-group differences while MG reduced it (VT, BPND and K1 group differences: uncorrected: 20%, 27%, 17%; MG: 18%, 22%, 14%; IY: 22%, 28%, 17%). The group difference in hippocampal volume (10%) was substantially smaller than any PET measures. MG increased GM binding values to a greater extent than IY due to differences in algorithm assumptions. CONCLUSION: 11C-UCB-J binding is significantly reduced in AD hippocampus, but PVC is important to adjust for significant volume reduction. After correction, PET measures are substantially more sensitive to group differences than volumetric MRI measures. Assumptions of each PVC algorithm are important and should be carefully examined and validated. For 11C-UCB-J, the less stringent assumptions of IY support its use as a PVC algorithm over MG.