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Item 11C-PiB PET can underestimate brain amyloid-β burden when cotton wool plaques are numerous(Oxford University Press, 2022) Abrahamson, Eric E.; Kofler, Julia K.; Becker, Carl R.; Price, Julie C.; Newell, Kathy L.; Ghetti, Bernardino; Murrell, Jill R.; McLean, Catriona A.; Lopez, Oscar L.; Mathis, Chester A.; Klunk, William E.; Villemagne, Victor L.; Ikonomovic, Milos D.; Pathology and Laboratory Medicine, School of MedicineIndividuals with familial Alzheimer's disease due to PSEN1 mutations develop high cortical fibrillar amyloid-β load but often have lower cortical 11C-Pittsburgh compound B (PiB) retention than Individuals with sporadic Alzheimer's disease. We hypothesized this is influenced by limited interactions of Pittsburgh compound B with cotton wool plaques, an amyloid-β plaque type common in familial Alzheimer's disease but rare in sporadic Alzheimer's disease. Histological sections of frontal and temporal cortex, caudate nucleus and cerebellum were obtained from 14 cases with sporadic Alzheimer's disease, 12 cases with familial Alzheimer's disease due to PSEN1 mutations, two relatives of a PSEN1 mutation carrier but without genotype information and three non-Alzheimer's disease cases. Sections were processed immunohistochemically using amyloid-β-targeting antibodies and the fluorescent amyloid stains cyano-PiB and X-34. Plaque load was quantified by percentage area analysis. Frozen homogenates from the same brain regions from five sporadic Alzheimer's disease and three familial Alzheimer's disease cases were analysed for 3H-PiB in vitro binding and concentrations of amyloid-β1-40 and amyloid-β1-42. Nine sporadic Alzheimer's disease, three familial Alzheimer's disease and three non-Alzheimer's disease participants had 11C-PiB PET with standardized uptake value ratios calculated using the cerebellum as the reference region. Cotton wool plaques were present in the neocortex of all familial Alzheimer's disease cases and one sporadic Alzheimer's disease case, in the caudate nucleus from four familial Alzheimer's disease cases, but not in the cerebellum. Cotton wool plaques immunolabelled robustly with 4G8 and amyloid-β42 antibodies but weakly with amyloid-β40 and amyloid-βN3pE antibodies and had only background cyano-PiB fluorescence despite labelling with X-34. Relative to amyloid-β plaque load, cyano-Pittsburgh compound B plaque load was similar in sporadic Alzheimer's disease while in familial Alzheimer's disease it was lower in the neocortex and the caudate nucleus. In both regions, insoluble amyloid-β1-42 and amyloid-β1-40 concentrations were similar in familial Alzheimer's disease and sporadic Alzheimer's disease groups, while 3H-PiB binding was lower in the familial Alzheimer's disease than the sporadic Alzheimer's disease group. Higher amyloid-β1-42 concentration associated with higher 3H-PiB binding in sporadic Alzheimer's disease but not familial Alzheimer's disease. 11C-PiB retention correlated with region-matched post-mortem amyloid-β plaque load; however, familial Alzheimer's disease cases with abundant cotton wool plaques had lower 11C-PiB retention than sporadic Alzheimer's disease cases with similar amyloid-β plaque loads. PiB has limited ability to detect amyloid-β aggregates in cotton wool plaques and may underestimate total amyloid-β plaque burden in brain regions with abundant cotton wool plaques.Item Assessment of myocardial metabolic flexibility and work efficiency in human type 2 diabetes using 16-[18F]fluoro-4-thiapalmitate, a novel PET fatty acid tracer(American Physiological Society, 2016-03-15) Mather, K.J.; Hutchins, G.D.; Perry, K.; Territo, W.; Chisholm, R.; Acton, A.; Glick-Wilson, B.; Considine, R.V.; Moberly, S.; DeGrado, T.R.; Department of Medicine, IU School of MedicineAltered myocardial fuel selection likely underlies cardiac disease risk in diabetes, affecting oxygen demand and myocardial metabolic flexibility. We investigated myocardial fuel selection and metabolic flexibility in human type 2 diabetes mellitus (T2DM), using positron emission tomography to measure rates of myocardial fatty acid oxidation {16-[18F]fluoro-4-thia-palmitate (FTP)} and myocardial perfusion and total oxidation ([11C]acetate). Participants underwent paired studies under fasting conditions, comparing 3-h insulin + glucose euglycemic clamp conditions (120 mU·m−2·min−1) to 3-h saline infusion. Lean controls (n = 10) were compared with glycemically controlled volunteers with T2DM (n = 8). Insulin augmented heart rate, blood pressure, and stroke index in both groups (all P < 0.01) and significantly increased myocardial oxygen consumption (P = 0.04) and perfusion (P = 0.01) in both groups. Insulin suppressed available nonesterified fatty acids (P < 0.0001), but fatty acid concentrations were higher in T2DM under both conditions (P < 0.001). Insulin-induced suppression of fatty acid oxidation was seen in both groups (P < 0.0001). However, fatty acid oxidation rates were higher under both conditions in T2DM (P = 0.003). Myocardial work efficiency was lower in T2DM (P = 0.006) and decreased in both groups with the insulin-induced increase in work and shift in fuel utilization (P = 0.01). Augmented fatty acid oxidation is present under baseline and insulin-treated conditions in T2DM, with impaired insulin-induced shifts away from fatty acid oxidation. This is accompanied by reduced work efficiency, possibly due to greater oxygen consumption with fatty acid metabolism. These observations suggest that improved fatty acid suppression, or reductions in myocardial fatty acid uptake and retention, could be therapeutic targets to improve myocardial ischemia tolerance in T2DM.Item Comparing amyloid-β plaque burden with antemortem PiB PET in autosomal dominant and late-onset Alzheimer disease(Springer, 2021) Chen, Charles D.; Joseph-Mathurin, Nelly; Sinha, Namita; Zhou, Aihong; Li, Yan; Friedrichsen, Karl; McCullough, Austin; Franklin, Erin E.; Hornbeck, Russ; Gordon, Brian; Sharma, Vijay; Cruchaga, Carlos; Goate, Alison; Karch, Celeste; McDade, Eric; Xiong, Chengjie; Bateman, Randall J.; Ghetti, Bernardino; Ringman, John M.; Chhatwal, Jasmeer; Masters, Colin L.; McLean, Catriona; Lashley, Tammaryn; Su, Yi; Koeppe, Robert; Jack, Clifford; Klunk, William E.; Morris, John C.; Perrin, Richard J.; Cairns, Nigel J.; Benzinger, Tammie L.S.; Pathology and Laboratory Medicine, School of MedicinePittsburgh compound B (PiB) radiotracer for positron emission tomography (PET) imaging can bind to different types of amyloid-β plaques and blood vessels (cerebral amyloid angiopathy). However, the relative contributions of different plaque subtypes (diffuse versus cored/compact) to in vivo PiB PET signal on a region-by-region basis is incompletely understood. Of particular interest is whether the same staging schemes for summarizing amyloid-β burden are appropriate for both late-onset and autosomal dominant forms of Alzheimer disease (LOAD and ADAD). Here we compared antemortem PiB PET with follow-up postmortem estimation of amyloid-β burden using stereologic methods to estimate the relative area fraction of diffuse and cored/compact amyloid-β plaques across 16 brain regions in 15 individuals with ADAD and 14 individuals with LOAD. In ADAD, we found that PiB PET correlated with diffuse plaques in the frontal, parietal, temporal, and striatal regions commonly used to summarize amyloid-β burden in PiB PET, and correlated with both diffuse and cored/compact plaques in the occipital lobe and parahippocampal gyrus. In LOAD, we found that PiB PET correlated with both diffuse and cored/compact plaques in the anterior cingulate, frontal lobe (middle frontal gyrus), and parietal lobe, and showed additional correlations with diffuse plaque in the amygdala and occipital lobe, and with cored/compact plaque in the temporal lobe. Thus, commonly used PiB PET summary regions predominantly reflect diffuse plaque burden in ADAD and a mixture of diffuse and cored/compact plaque burden in LOAD. In direct comparisons of ADAD and LOAD, postmortem stereology identified much greater mean amyloid-β plaque burdens in ADAD versus LOAD across almost all brain regions studied. However, standard PiB PET did not recapitulate these stereologic findings, likely due to non-trivial amyloid-β plaque burdens in ADAD within the cerebellum and brainstem – commonly used reference regions in PiB PET. Our findings suggest that PiB PET summary regions correlate with amyloid-β plaque burden in both ADAD and LOAD; however, they might not be reliable in direct comparisons of regional amyloid-β plaque burden between the two forms of AD.Item Comparison of left ventriculography and coronary arteriography with positron emission tomography in assessment of myocardial viability(Wiley, 2003-02) Bourdillon, Patrick D. V.; Von Der Lohe, Elisabeth; Lewis, Stephen J.; Sharifi, Mohsen; Burt, Robert W.; Sawada, Stephen G.; Medicine, School of MedicineBackground: Assessment of viability of myocardium after an ischemic insult is an important clinical question that affects decisions pertaining to potential revascularization. The results of contrast left ventriculograms and coronary angiography were compared to positron emission tomography (PET) in 64 patients with coronary artery disease and reduced left ventricular function. Hypothesis: The study was undertaken to determine the relative utility of the invasive studies in the assessment of viability. Methods: Right anterior oblique ventriculograms were assessed for hypokinesis, akinesis, or dyskinesis in six segments. The PET scans were assessed for viability by visual estimation of flourodeoxyglucose (FDG) uptake in six segments that corresponded to the segments analyzed on the ventriculograms. Results: Of a total of 373 segments successfully analyzed by PET, 272 were judged to be viable (normal or hypokinetic) by contrast ventriculography. Of these, 253 (93%) were considered viable by PET. Of 177 segments deemed either normal or mild‐to‐moderately hypokinetic by ventriculography, 170 (94%) were viable by PET. Of 95 severely hypokinetic segments, 83 (84%) were viable by PET. Of 79 akinetic segments, 44 (56%) were considered viable by PET. For segments that were dyskinetic and thought to be nonviable by ventriculography, 19 of 22 (86%) were also considered nonviable by PET. For 294 segments for which a determination on viability was made based on the presence of wall motion on the ventriculogram (normal, hypokinetic, or dyskinetic; not akinetic), there was excellent agreement with PET (93%; p < 0.001). In 49 patients there was akinesis in no more than one segment in either the anterior or inferior territories, indicating the potential for assessment of viability by ventriculography in at least two of three segments in each territory. Coronary anatomy was analyzed to assess whether coronary patency could help in assessing viability. Segments supplied by patent arteries were more likely to be viable by PET than segments supplied by occluded arteries (p < 0.001). Akinetic segments were more likely to be supplied by occluded arteries (56 vs. 23, 72%). Dyskinetic segments were predominantly nonviable by PET (86%) and were usually supplied by occluded arteries (77%). Conclusion: In patients in whom the assessment of viability is clinically relevant, the presence of systolic inward motion on the contrast left ventriculogram correlates well with segment viability by PET, while outward or dyskinetic movement correlates well with nonviability. Thus, the use of PET to assess viability in many patients may be unnecessary.Item Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies(Elsevier, 2019-02-22) Su, Yi; Flores, Shaney; Wang, Guoqiao; Hornbeck, Russ C.; Speidel, Benjamin; Joseph-Mathurin, Nelly; Vlassenko, Andrei G.; Gordon, Brian A.; Koeppe, Robert A.; Klunk, William E.; Clifford, R. Jack, Jr.; Farlow, Martin R.; Salloway, Stephen; Snider, Barbara J.; Berman, Sarah B.; Roberson, Erik D.; Broschi, Jared; Jimenez-Velazques, Ivonne; van Dyck, Christopher H.; Galasko, Douglas; Yuan, Shauna H.; Jayadev, Suman; Honig, Lawrence S.; Gauthier, Serge; Hsiung, Ging-Yuek R.; Masellis, Mario; Brooks, William S.; Fulham, Michael; Clarnette, Roger; Masters, Colin L.; Wallon, David; Hannequin, Didier; Dubois, Bruno; Pariente, Jeremie; Sanchez-Valle, Raquel; Mummery, Catherine; Ringman, John M.; Bottlaender, Michel; Klein, Gregory; Milosavljevic-Ristic, Smiljana; McDade, Eric; Xiong, Chengjie; Morris, John C.; Bateman, Randall J.; Benzinger, Tammie L.S.; Neurology, School of MedicineIntroduction: Quantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B-based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design. Methods: Pittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally. Results: Global amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers. Discussion: Although the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers.Item Contribution of Alzheimer's biomarkers and risk factors to cognitive impairment and decline across the Alzheimer's disease continuum(Wiley, 2022) Tosun, Duygu; Demir, Zeynep; Veitch, Dallas P.; Weintraub, Daniel; Aisen, Paul; Jack, Clifford R., Jr.; Jagust, William J.; Petersen, Ronald C.; Saykin, Andrew J.; Shaw, Leslie M.; Trojanowski, John Q.; Weiner, Michael W.; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: Amyloid beta (Aβ), tau, and neurodegeneration jointly with the Alzheimer's disease (AD) risk factors affect the severity of clinical symptoms and disease progression. Methods: Within 248 Aβ-positive elderly with and without cognitive impairment and dementia, partial least squares structural equation pathway modeling was used to assess the direct and indirect effects of imaging biomarkers (global Aβ-positron emission tomography [PET] uptake, regional tau-PET uptake, and regional magnetic resonance imaging-based atrophy) and risk-factors (age, sex, education, apolipoprotein E [APOE], and white-matter lesions) on cross-sectional cognitive impairment and longitudinal cognitive decline. Results: Sixteen percent of variance in cross-sectional cognitive impairment was accounted for by Aβ, 46% to 47% by tau, and 25% to 29% by atrophy, although 53% to 58% of total variance in cognitive impairment was explained by incorporating mediated and direct effects of AD risk factors. The Aβ-tau-atrophy pathway accounted for 50% to 56% of variance in longitudinal cognitive decline while Aβ, tau, and atrophy independently explained 16%, 46% to 47%, and 25% to 29% of the variance, respectively. Discussion: These findings emphasize that treatments that remove Aβ and completely stop downstream effects on tau and neurodegeneration would only be partially effective in slowing of cognitive decline or reversing cognitive impairment.Item Contribution of clinical information to the predictive performance of plasma β-amyloid levels for amyloid positron emission tomography positivity(Frontiers Media, 2023-03-14) Chun, Min Young; Jang, Hyemin; Kim, Hee Jin; Kim, Jun Pyo; Gallacher, John; Allué, José Antonio; Sarasa, Leticia; Castillo, Sergio; Pascual-Lucas, María; Na, Duk L.; Seo, Sang Won; DPUK; Radiology and Imaging Sciences, School of MedicineBackground: Early detection of β-amyloid (Aβ) accumulation, a major biomarker for Alzheimer's disease (AD), has become important. As fluid biomarkers, the accuracy of cerebrospinal fluid (CSF) Aβ for predicting Aβ deposition on positron emission tomography (PET) has been extensively studied, and the development of plasma Aβ is beginning to receive increased attention recently. In the present study, we aimed to determine whether APOE genotypes, age, and cognitive status increase the predictive performance of plasma Aβ and CSF Aβ levels for Aβ PET positivity. Methods: We recruited 488 participants who underwent both plasma Aβ and Aβ PET studies (Cohort 1) and 217 participants who underwent both cerebrospinal fluid (CSF) Aβ and Aβ PET studies (Cohort 2). Plasma and CSF samples were analyzed using ABtest-MS, an antibody-free liquid chromatography-differential mobility spectrometry-triple quadrupole mass spectrometry method and INNOTEST enzyme-linked immunosorbent assay kits, respectively. To evaluate the predictive performance of plasma Aβ and CSF Aβ, respectively, logistic regression and receiver operating characteristic analyses were performed. Results: When predicting Aβ PET status, both plasma Aβ42/40 ratio and CSF Aβ42 showed high accuracy (plasma Aβ area under the curve (AUC) 0.814; CSF Aβ AUC 0.848). In the plasma Aβ models, the AUC values were higher than plasma Aβ alone model, when the models were combined with either cognitive stage (p < 0.001) or APOE genotype (p = 0.011). On the other hand, there was no difference between the CSF Aβ models, when these variables were added. Conclusion: Plasma Aβ might be a useful predictor of Aβ deposition on PET status as much as CSF Aβ, particularly when considered with clinical information such as APOE genotype and cognitive stage.Item Correction to: Cryo-EM structures of tau filaments from Alzheimer’s disease with PET ligand APN-1607(SpringerLink, 2021-06) Shi, Yang; Murzin, Alexey G.; Falcon, Benjamin; Epstein, Alexander; Machin, Jonathan; Tempest, Paul; Newell, Kathy L.; Vidal, Ruben; Garringer, Holly J.; Sahara, Naruhiko; Higuchi, Makoto; Ghetti, Bernardino; Jang, Ming‑Kuei; Scheres, Sjors H.W; Goedert, Michel; Pathology and Laboratory Medicine, School of MedicineCorrection to: Acta Neuropathologica 10.1007/s00401-021-02294-3Item Cryo-EM structures of tau filaments from Alzheimer’s disease with PET ligand APN-1607(Springer, 2021-05) Shi, Yang; Murzin, Alexey G.; Falcon, Benjamin; Epstein, Alexander; Machin, Jonathan; Tempest, Paul; Newell, Kathy L.; Vidal, Ruben; Garringer, Holly J.; Sahara, Naruhiko; Higuchi, Makoto; Ghetti, Bernardino; Jang, Ming‑Kuei; Scheres, Sjors H. W.; Goedert, Michel; Pathology and Laboratory Medicine, School of MedicineTau and Aβ assemblies of Alzheimer's disease (AD) can be visualized in living subjects using positron emission tomography (PET). Tau assemblies comprise paired helical and straight filaments (PHFs and SFs). APN-1607 (PM-PBB3) is a recently described PET ligand for AD and other tau proteinopathies. Since it is not known where in the tau folds PET ligands bind, we used electron cryo-microscopy (cryo-EM) to determine the binding sites of APN-1607 in the Alzheimer fold. We identified two major sites in the β-helix of PHFs and SFs and a third major site in the C-shaped cavity of SFs. In addition, we report that tau filaments from posterior cortical atrophy (PCA) and primary age-related tauopathy (PART) are identical to those from AD. In support, fluorescence labelling showed binding of APN-1607 to intraneuronal inclusions in AD, PART and PCA. Knowledge of the binding modes of APN-1607 to tau filaments may lead to the development of new ligands with increased specificity and binding activity. We show that cryo-EM can be used to identify the binding sites of small molecules in amyloid filaments.Item Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data(Frontiers, 2019-08-20) Jo, Taeho; Nho, Kwangslk; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineDeep learning, a state-of-the-art machine learning approach, has shown outstanding performance over traditional machine learning in identifying intricate structures in complex high-dimensional data, especially in the domain of computer vision. The application of deep learning to early detection and automated classification of Alzheimer's disease (AD) has recently gained considerable attention, as rapid progress in neuroimaging techniques has generated large-scale multimodal neuroimaging data. A systematic review of publications using deep learning approaches and neuroimaging data for diagnostic classification of AD was performed. A PubMed and Google Scholar search was used to identify deep learning papers on AD published between January 2013 and July 2018. These papers were reviewed, evaluated, and classified by algorithm and neuroimaging type, and the findings were summarized. Of 16 studies meeting full inclusion criteria, 4 used a combination of deep learning and traditional machine learning approaches, and 12 used only deep learning approaches. The combination of traditional machine learning for classification and stacked auto-encoder (SAE) for feature selection produced accuracies of up to 98.8% for AD classification and 83.7% for prediction of conversion from mild cognitive impairment (MCI), a prodromal stage of AD, to AD. Deep learning approaches, such as convolutional neural network (CNN) or recurrent neural network (RNN), that use neuroimaging data without pre-processing for feature selection have yielded accuracies of up to 96.0% for AD classification and 84.2% for MCI conversion prediction. The best classification performance was obtained when multimodal neuroimaging and fluid biomarkers were combined. Deep learning approaches continue to improve in performance and appear to hold promise for diagnostic classification of AD using multimodal neuroimaging data. AD research that uses deep learning is still evolving, improving performance by incorporating additional hybrid data types, such as-omics data, increasing transparency with explainable approaches that add knowledge of specific disease-related features and mechanisms.