2,522 results on '"Villemagne, Victor L."'
Search Results
2. Neuropsychiatric Symptoms and Microglial Activation in Patients with Alzheimer Disease
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Aguzzoli, Cristiano Schaffer, Ferreira, Pâmela CL, Povala, Guilherme, Ferrari-Souza, João Pedro, Bellaver, Bruna, Katz, Carolina Soares, Zalzale, Hussein, Lussier, Firoza Z, Rohden, Francieli, Abbas, Sarah, Leffa, Douglas T, Medeiros, Marina Scop, Therriault, Joseph, Benedet, Andréa L, Tissot, Cécile, Servaes, Stijn, Rahmouni, Nesrine, Macedo, Arthur Cassa, Bezgin, Gleb, Kang, Min Su, Stevenson, Jenna, Pallen, Vanessa, Cohen, Ann, Lopez, Oscar L, Tudorascu, Dana L, Klunk, William E, Villemagne, Victor L, Soucy, Jean Paul, Zimmer, Eduardo R, Schilling, Lucas P, Karikari, Thomas K, Ashton, Nicholas J, Zetterberg, Henrik, Blennow, Kaj, Gauthier, Serge, Valcour, Victor, Miller, Bruce L, Rosa-Neto, Pedro, and Pascoal, Tharick A
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Health Services and Systems ,Health Sciences ,Aging ,Alzheimer's Disease ,Brain Disorders ,Acquired Cognitive Impairment ,Dementia ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Neurosciences ,Biomedical Imaging ,Neurodegenerative ,Clinical Research ,4.2 Evaluation of markers and technologies ,Detection ,screening and diagnosis ,4.1 Discovery and preclinical testing of markers and technologies ,Neurological ,Male ,Humans ,Female ,Aged ,Alzheimer Disease ,Microglia ,tau Proteins ,Cross-Sectional Studies ,Amyloid beta-Peptides ,Biomarkers ,Biomedical and clinical sciences ,Health sciences - Abstract
ImportanceNeuropsychiatric symptoms are commonly encountered and are highly debilitating in patients with Alzheimer disease. Understanding their underpinnings has implications for identifying biomarkers and treatment for these symptoms.ObjectiveTo evaluate whether glial markers are associated with neuropsychiatric symptoms in individuals across the Alzheimer disease continuum.Design, setting, and participantsThis cross-sectional study was conducted from January to June 2023, leveraging data from the Translational Biomarkers in Aging and Dementia cohort at McGill University, Canada. Recruitment was based on referrals of individuals from the community or from outpatient clinics. Exclusion criteria included active substance abuse, major surgery, recent head trauma, safety contraindications for positron emission tomography (PET) or magnetic resonance imaging, being currently enrolled in other studies, and having inadequately treated systemic conditions.Main outcomes and measuresAll individuals underwent assessment for neuropsychiatric symptoms (Neuropsychiatry Inventory Questionnaire [NPI-Q]), and imaging for microglial activation ([11C]PBR28 PET), amyloid-β ([18F]AZD4694 PET), and tau tangles ([18F]MK6240 PET).ResultsOf the 109 participants, 72 (66%) were women and 37 (34%) were men; the median age was 71.8 years (range, 38.0-86.5 years). Overall, 70 had no cognitive impairment and 39 had cognitive impairment (25 mild; 14 Alzheimer disease dementia). Amyloid-β PET positivity was present in 21 cognitively unimpaired individuals (30%) and in 31 cognitively impaired individuals (79%). The NPI-Q severity score was associated with microglial activation in the frontal, temporal, and parietal cortices (β = 7.37; 95% CI, 1.34-13.41; P = .01). A leave-one-out approach revealed that irritability was the NPI-Q domain most closely associated with the presence of brain microglial activation (β = 6.86; 95% CI, 1.77-11.95; P = .008). Furthermore, we found that microglia-associated irritability was associated with study partner burden measured by NPI-Q distress score (β = 5.72; 95% CI, 0.33-11.10; P = .03).Conclusions and relevanceIn this cross-sectional study of 109 individuals across the AD continuum, microglial activation was associated with and a potential biomarker of neuropsychiatric symptoms in Alzheimer disease. Moreover, our findings suggest that the combination of amyloid-β- and microglia-targeted therapies could have an impact on relieving these symptoms.
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- 2023
3. CYP1B1-RMDN2 Alzheimer’s disease endophenotype locus identified for cerebral tau PET
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Nho, Kwangsik, Risacher, Shannon L., Apostolova, Liana G., Bice, Paula J., Brosch, Jared R., Deardorff, Rachael, Faber, Kelley, Farlow, Martin R., Foroud, Tatiana, Gao, Sujuan, Rosewood, Thea, Kim, Jun Pyo, Nudelman, Kelly, Yu, Meichen, Aisen, Paul, Sperling, Reisa, Hooli, Basavaraj, Shcherbinin, Sergey, Svaldi, Diana, Jack, Jr., Clifford R., Jagust, William J., Landau, Susan, Vasanthakumar, Aparna, Waring, Jeffrey F., Doré, Vincent, Laws, Simon M., Masters, Colin L., Porter, Tenielle, Rowe, Christopher C., Villemagne, Victor L., Dumitrescu, Logan, Hohman, Timothy J., Libby, Julia B., Mormino, Elizabeth, Buckley, Rachel F., Johnson, Keith, Yang, Hyun-Sik, Petersen, Ronald C., Ramanan, Vijay K., Ertekin-Taner, Nilüfer, Vemuri, Prashanthi, Cohen, Ann D., Fan, Kang-Hsien, Kamboh, M. Ilyas, Lopez, Oscar L., Bennett, David A., Ali, Muhammad, Benzinger, Tammie, Cruchaga, Carlos, Hobbs, Diana, De Jager, Philip L., Fujita, Masashi, Jadhav, Vaishnavi, Lamb, Bruce T., Tsai, Andy P., Castanho, Isabel, Mill, Jonathan, Weiner, Michael W., and Saykin, Andrew J.
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- 2024
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4. Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting
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Zeng, Xuemei, Chen, Yijun, Sehrawat, Anuradha, Lee, Jihui, Lafferty, Tara K., Kofler, Julia, Berman, Sarah B., Sweet, Robert A., Tudorascu, Dana L., Klunk, William E., Ikonomovic, Milos D., Pfister, Anna, Zetterberg, Henrik, Snitz, Beth E., Cohen, Anne D., Villemagne, Victor L., Pascoal, Tharick A., Kamboh, M. llyas, Lopez, Oscar I., Blennow, Kaj, and Karikari, Thomas K.
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- 2024
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5. A universal neocortical mask for Centiloid quantification
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Bourgeat, Pierrick, Doré, Vincent, Rowe, Christopher C, Benzinger, Tammie, Tosun, Duygu, Goyal, Manu S, LaMontagne, Pamela, Jin, Liang, Weiner, Michael W, Masters, Colin L, Fripp, Jurgen, Villemagne, Victor L, Initiative, for the Alzheimer's Disease Neuroimaging, and OASIS3, and the AIBL research group
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Biomedical and Clinical Sciences ,Clinical Sciences ,Acquired Cognitive Impairment ,Neurosciences ,Dementia ,Brain Disorders ,Alzheimer's Disease ,Biomedical Imaging ,Neurodegenerative ,Aging ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Detection ,screening and diagnosis ,4.1 Discovery and preclinical testing of markers and technologies ,amyloid positron emission tomography ,Centiloid ,Florbetaben ,Florbetapir ,Flutemetamol ,NAV4694 ,PiB ,Alzheimer's Disease Neuroimaging Initiative ,OASIS3 ,and the AIBL research group ,Genetics ,Biological psychology - Abstract
IntroductionThe Centiloid (CL) project was developed to harmonize the quantification of amyloid beta (Aβ) positron emission tomography (PET) scans to a unified scale. The CL neocortical mask was defined using 11C Pittsburgh compound B (PiB), overlooking potential differences in regional distribution among Aβ tracers. We created a universal mask using an independent dataset of five Aβ tracers, and investigated its impact on inter-tracer agreement, tracer variability, and group separation.MethodsUsing data from the Alzheimer's Dementia Onset and Progression in International Cohorts (ADOPIC) study (Australian Imaging Biomarkers and Lifestyle + Alzheimer's Disease Neuroimaging Initiative + Open Access Series of Imaging Studies), age-matched pairs of mild Alzheimer's disease (AD) and healthy controls (HC) were selected: 18F-florbetapir (N = 147 pairs), 18F-florbetaben (N = 22), 18F-flutemetamol (N = 10), 18F-NAV (N = 42), 11C-PiB (N = 63). The images were spatially and standardized uptake value ratio normalized. For each tracer, the mean AD-HC difference image was thresholded to maximize the overlap with the standard neocortical mask. The universal mask was defined as the intersection of all five masks. It was evaluated on the Global Alzheimer's Association Interactive Network (GAAIN) head-to-head datasets in terms of inter-tracer agreement and variance in the young controls (YC) and on the ADOPIC dataset comparing separation between HC/AD and HC/mild cognitive impairment (MCI).ResultsIn the GAAIN dataset, the universal mask led to a small reduction in the variance of the YC, and a small increase in the inter-tracer agreement. In the ADOPIC dataset, it led to a better separation between HC/AD and HC/MCI at baseline.DiscussionThe universal CL mask led to an increase in inter-tracer agreement and group separation. Those increases were, however, very small, and do not provide sufficient benefits to support departing from the existing standard CL mask, which is suitable for the quantification of all Aβ tracers.HighlightsThis study built an amyloid universal mask using a matched cohort for the five most commonly used amyloid positron emission tomography tracers.There was a high overlap between each tracer-specific mask.Differences in quantification and group separation between the standard and universal mask were small.The existing standard Centiloid mask is suitable for the quantification of all amyloid beta tracers.
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- 2023
6. Tau, β-Amyloid, and Glucose Metabolism Following Service-Related Traumatic Brain Injury in Vietnam War Veterans: The Australian Imaging Biomarkers and Lifestyle Study of Aging-Veterans Study (AIBL-VETS)
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Cummins, Tia L, Doré, Vincent, Feizpour, Azadeh, Krishnadas, Natasha, Bourgeat, Pierrick, Elias, Alby, Lamb, Fiona, Williams, Robert, Hopwood, Malcolm, Landau, Susan, Villemagne, Victor L, Weiner, Michael, and Rowe, Christopher C
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Biomedical and Clinical Sciences ,Biological Psychology ,Clinical Sciences ,Neurosciences ,Psychology ,Physical Injury - Accidents and Adverse Effects ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Clinical Research ,Prevention ,Neurodegenerative ,Traumatic Head and Spine Injury ,Dementia ,Brain Disorders ,Biomedical Imaging ,Traumatic Brain Injury (TBI) ,Aging ,Alzheimer's Disease ,Acquired Cognitive Impairment ,Neurological ,Good Health and Well Being ,Aged ,Humans ,Male ,Middle Aged ,Alzheimer Disease ,Amyloid beta-Peptides ,Australia ,Biomarkers ,Brain Injuries ,Traumatic ,Case-Control Studies ,Cognitive Dysfunction ,Fluorodeoxyglucose F18 ,Glucose ,Life Style ,Positron-Emission Tomography ,tau Proteins ,Veterans ,Vietnam ,beta-amyloid ,F-18-FDG ,brain imaging ,positron emission tomography ,tau ,traumatic brain injury ,Vietnam veterans ,18F-FDG ,β-amyloid ,Neurology & Neurosurgery ,Clinical sciences ,Biological psychology - Abstract
Traumatic brain injury (TBI) is common among military veterans and has been associated with an increased risk of dementia. It is unclear if this is due to increased risk for Alzheimer's disease (AD) or other mechanisms. This case control study sought evidence for AD, as defined by the 2018 National Institute on Aging - Alzheimer's Association (NIA-AA) research framework, by measuring tau, β-amyloid, and glucose metabolism using positron emission tomography (PET) in veterans with service-related TBI. Seventy male Vietnam war veterans-40 with TBI (age 68.0 ± 2.5 years) and 30 controls (age 70.1 ± 5.3 years)-with no prior diagnosis of dementia or mild cognitive impairment underwent β-amyloid (18F-Florbetaben), tau (18F-Flortaucipir), and fluorodeoxyglucose (18F-FDG) PET. The TBI cohort included 15 participants with mild, 16 with moderate, and nine with severe injury. β-Amyloid level was calculated using the Centiloid (CL) method and tau was measured by standardized uptake value ratios (SUVRs) using the cerebellar cortex as reference region. Analyses were adjusted for age and APOE-e4. The findings were validated in an independent cohort from the Department of Defense-Alzheimer's Disease Neuroimaging Initiative (DOD ADNI) study. There were no significant nor trending differences in β-amyloid or tau levels or 18F-FDG uptake between the TBI and control groups before and after controlling for covariates. The β-amyloid and tau findings were replicated in the DOD ADNI validation cohort and persisted when the Australian Imaging Biomarkers and Lifestyle study of aging-Veterans study (AIBL-VETS) and DOD ADNI cohorts were combined (114 TBI vs. 87 controls in total). In conclusion, no increase in the later life accumulation of the neuropathological markers of AD in veterans with a remote history of TBI was identified.
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- 2023
7. Influence of Comorbidity of Cerebrovascular Disease and Amyloid-β on Alzheimer’s Disease
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Yassi, Nawaf, primary, Hilal, Saima, additional, Xia, Ying, additional, Lim, Yen Ying, additional, Watson, Rosie, additional, Kuijf, Hugo, additional, Fowler, Christopher, additional, Yates, Paul, additional, Maruff, Paul, additional, Martins, Ralph, additional, Ames, David, additional, Chen, Christopher, additional, Rowe, Christopher C., additional, Villemagne, Victor L., additional, Salvado, Olivier, additional, Desmond, Patricia M., additional, and Masters, Colin L., additional
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- 2024
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8. Higher Brain Amyloid Burdens in Patients with Severe Obstructive Sleep Apnea: A Pilot PET Imaging Study
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Jackson, Melinda L., primary, Cavuoto, Marina, additional, Schembri, Rachel, additional, Doré, Vincent, additional, Villemagne, Victor L., additional, Barnes, Maree, additional, O’Donoghue, Fergal J., additional, Rowe, Christopher C., additional, and Robinson, Stephen R., additional
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- 2024
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9. β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3
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Bourgeat, Pierrick, Doré, Vincent, Burnham, Samantha C, Benzinger, Tammie, Tosun, Duygu, Li, Shenpeng, Goyal, Manu, LaMontagne, Pamela, Jin, Liang, Rowe, Christopher C, Weiner, Michael W, Morris, John C, Masters, Colin L, Fripp, Jurgen, Villemagne, Victor L, and Alzheimer's Disease Neuroimaging Initiative, OASIS3
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Biomedical and Clinical Sciences ,Clinical Sciences ,Biomedical Imaging ,Neurosciences ,Alzheimer Disease ,Amyloid beta-Peptides ,Aniline Compounds ,Cross-Sectional Studies ,Humans ,Longitudinal Studies ,Positron-Emission Tomography ,Amyloid PET ,Centiloid ,Harmonisation ,Alzheimer's Disease Neuroimaging Initiative ,OASIS3 ,and the AIBL research group ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Neurology & Neurosurgery ,Biomedical and clinical sciences ,Health sciences - Abstract
IntroductionThe Centiloid scale was developed to harmonise the quantification of β-amyloid (Aβ) PET images across tracers, scanners, and processing pipelines. However, several groups have reported differences across tracers and scanners even after centiloid conversion. In this study, we aim to evaluate the impact of different pre and post-processing harmonisation steps on the robustness of longitudinal Centiloid data across three large international cohort studies.MethodsAll Aβ PET data in AIBL (N = 3315), ADNI (N = 3442) and OASIS3 (N = 1398) were quantified using the MRI-based Centiloid standard SPM pipeline and the PET-only pipeline CapAIBL. SUVR were converted into Centiloids using each tracer's respective transform. Global Aβ burden from pre-defined target cortical regions in Centiloid units were quantified for both raw PET scans and PET scans smoothed to a uniform 8 mm full width half maximum (FWHM) effective smoothness. For Florbetapir, we assessed the performance of using both the standard Whole Cerebellum (WCb) and a composite white matter (WM)+WCb reference region. Additionally, our recently proposed quantification based on Non-negative Matrix Factorisation (NMF) was applied to all spatially and SUVR normalised images. Correlation with clinical severity measured by the Mini-Mental State Examination (MMSE) and effect size, as well as tracer agreement in 11C-PiB-18F-Florbetapir pairs and longitudinal consistency were evaluated.ResultsThe smoothing to a uniform resolution partially reduced longitudinal variability, but did not improve inter-tracer agreement, effect size or correlation with MMSE. Using a Composite reference region for 18F-Florbetapir improved inter-tracer agreement, effect size, correlation with MMSE, and longitudinal consistency. The best results were however obtained when using the NMF method which outperformed all other quantification approaches in all metrics used.ConclusionsFWHM smoothing has limited impact on longitudinal consistency or outliers. A Composite reference region including subcortical WM should be used for computing both cross-sectional and longitudinal Florbetapir Centiloid. NMF improves Centiloid quantification on all metrics examined.
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- 2022
10. APOEε4 potentiates amyloid β effects on longitudinal tau pathology
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Ferrari-Souza, João Pedro, Bellaver, Bruna, Ferreira, Pâmela C. L., Benedet, Andréa L., Povala, Guilherme, Lussier, Firoza Z., Leffa, Douglas T., Therriault, Joseph, Tissot, Cécile, Soares, Carolina, Wang, Yi-Ting, Chamoun, Mira, Servaes, Stijn, Macedo, Arthur C., Vermeiren, Marie, Bezgin, Gleb, Kang, Min Su, Stevenson, Jenna, Rahmouni, Nesrine, Pallen, Vanessa, Poltronetti, Nina Margherita, Cohen, Ann, Lopez, Oscar L., Klunk, William E., Soucy, Jean-Paul, Gauthier, Serge, Souza, Diogo O., Triana-Baltzer, Gallen, Saad, Ziad S., Kolb, Hartmuth C., Karikari, Thomas K., Villemagne, Victor L., Tudorascu, Dana L., Ashton, Nicholas J., Zetterberg, Henrik, Blennow, Kaj, Zimmer, Eduardo R., Rosa-Neto, Pedro, and Pascoal, Tharick A.
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- 2023
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11. Apolipoprotein E and Alzheimer’s disease pathology in African American older adults
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Royse, Sarah K., Snitz, Beth E., Hill, Ashley V., Reese, Alexandria C., Roush, Rebecca E., Kamboh, M. Ilyas, Bertolet, Marnie, Saeed, Anum, Lopresti, Brian J., Villemagne, Victor L., Lopez, Oscar L., Reis, Steven E., Becker, James T., and Cohen, Ann D.
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- 2024
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12. Astrocyte reactivity influences amyloid-β effects on tau pathology in preclinical Alzheimer’s disease
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Bellaver, Bruna, Povala, Guilherme, Ferreira, Pamela C. L., Ferrari-Souza, João Pedro, Leffa, Douglas T., Lussier, Firoza Z., Benedet, Andréa L., Ashton, Nicholas J., Triana-Baltzer, Gallen, Kolb, Hartmuth C., Tissot, Cécile, Therriault, Joseph, Servaes, Stijn, Stevenson, Jenna, Rahmouni, Nesrine, Lopez, Oscar L., Tudorascu, Dana L., Villemagne, Victor L., Ikonomovic, Milos D., Gauthier, Serge, Zimmer, Eduardo R., Zetterberg, Henrik, Blennow, Kaj, Aizenstein, Howard J., Klunk, William E., Snitz, Beth E., Maki, Pauline, Thurston, Rebecca C., Cohen, Ann D., Ganguli, Mary, Karikari, Thomas K., Rosa-Neto, Pedro, and Pascoal, Tharick A.
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- 2023
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13. Traits and Trammels of Tau Tracer Imaging
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Villemagne, Victor L., Lopresti, Brian J., Doré, Vincent, Minhas, Davneet, Gogola, Alexandra, Nadkarni, Neelesh, Mason, N. Scott, Bourgeat, Pierrick, Lopez, Oscar, Ikonomovic, Milos D., Cohen, Ann D., Cross, Donna J., editor, Mosci, Karina, editor, and Minoshima, Satoshi, editor
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- 2023
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14. Genetic risk for attention-deficit/hyperactivity disorder predicts cognitive decline and development of Alzheimer’s disease pathophysiology in cognitively unimpaired older adults
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Leffa, Douglas T., Ferrari-Souza, João Pedro, Bellaver, Bruna, Tissot, Cécile, Ferreira, Pamela C. L., Brum, Wagner S., Caye, Arthur, Lord, Jodie, Proitsi, Petroula, Martins-Silva, Thais, Tovo-Rodrigues, Luciana, Tudorascu, Dana L., Villemagne, Victor L., Cohen, Ann D., Lopez, Oscar L., Klunk, William E., Karikari, Thomas K., Rosa-Neto, Pedro, Zimmer, Eduardo R., Molina, Brooke S. G., Rohde, Luis Augusto, and Pascoal, Tharick A.
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- 2023
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15. The strategic biomarker roadmap for the validation of Alzheimer’s diagnostic biomarkers: methodological update
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Boccardi, Marina, Dodich, Alessandra, Albanese, Emiliano, Gayet-Ageron, Angèle, Festari, Cristina, Ashton, Nicholas J, Bischof, Gérard N, Chiotis, Konstantinos, Leuzy, Antoine, Wolters, Emma E, Walter, Martin A, Rabinovici, Gil D, Carrillo, Maria, Drzezga, Alexander, Hansson, Oskar, Nordberg, Agneta, Ossenkoppele, Rik, Villemagne, Victor L, Winblad, Bengt, Frisoni, Giovanni B, and Garibotto, Valentina
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Biomedical and Clinical Sciences ,Clinical Sciences ,Acquired Cognitive Impairment ,Neurosciences ,Aging ,Neurodegenerative ,Alzheimer's Disease ,Brain Disorders ,Dementia ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Detection ,screening and diagnosis ,4.1 Discovery and preclinical testing of markers and technologies ,4.2 Evaluation of markers and technologies ,Alzheimer Disease ,Amyloid beta-Peptides ,Biomarkers ,Cognitive Dysfunction ,Cross-Sectional Studies ,Disease Progression ,Humans ,Reference Standards ,tau Proteins ,Biomarker ,Alzheimer’ ,s disease ,MCI ,Mild cognitive impairment ,Validation methodology ,Alzheimer’s disease ,Other Physical Sciences ,Nuclear Medicine & Medical Imaging ,Clinical sciences - Abstract
BackgroundThe 2017 Alzheimer's disease (AD) Strategic Biomarker Roadmap (SBR) structured the validation of AD diagnostic biomarkers into 5 phases, systematically assessing analytical validity (Phases 1-2), clinical validity (Phases 3-4), and clinical utility (Phase 5) through primary and secondary Aims. This framework allows to map knowledge gaps and research priorities, accelerating the route towards clinical implementation. Within an initiative aimed to assess the development of biomarkers of tau pathology, we revised this methodology consistently with progress in AD research.MethodsWe critically appraised the adequacy of the 2017 Biomarker Roadmap within current diagnostic frameworks, discussed updates at a workshop convening the Alzheimer's Association and 8 leading AD biomarker research groups, and detailed the methods to allow consistent assessment of aims achievement for tau and other AD diagnostic biomarkers.ResultsThe 2020 update applies to all AD diagnostic biomarkers. In Phases 2-3, we admitted a greater variety of study designs (e.g., cross-sectional in addition to longitudinal) and reference standards (e.g., biomarker confirmation in addition to clinical progression) based on construct (in addition to criterion) validity. We structured a systematic data extraction to enable transparent and formal evidence assessment procedures. Finally, we have clarified issues that need to be addressed to generate data eligible to evidence-to-decision procedures.DiscussionThis revision allows for more versatile and precise assessment of existing evidence, keeps up with theoretical developments, and helps clinical researchers in producing evidence suitable for evidence-to-decision procedures. Compliance with this methodology is essential to implement AD biomarkers efficiently in clinical research and diagnostics.
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- 2021
16. Longitudinal trajectories of basal forebrain volume in normal aging and Alzheimer’s disease
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Xia, Ying, Maruff, Paul, Doré, Vincent, Bourgeat, Pierrick, Laws, Simon M., Fowler, Christopher, Rainey-Smith, Stephanie R., Martins, Ralph N., Villemagne, Victor L., Rowe, Christopher C., Masters, Colin L., Coulson, Elizabeth J., and Fripp, Jurgen
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- 2023
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17. Using imputation to provide harmonized longitudinal measures of cognition across AIBL and ADNI
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Shishegar, Rosita, Cox, Timothy, Rolls, David, Bourgeat, Pierrick, Doré, Vincent, Lamb, Fiona, Robertson, Joanne, Laws, Simon M, Porter, Tenielle, Fripp, Jurgen, Tosun, Duygu, Maruff, Paul, Savage, Greg, Rowe, Christopher C, Masters, Colin L, Weiner, Michael W, Villemagne, Victor L, and Burnham, Samantha C
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Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Aging ,Neurosciences ,Acquired Cognitive Impairment ,Brain Disorders ,Neurodegenerative ,Dementia ,Biomedical Imaging ,Alzheimer's Disease ,Aged ,Aged ,80 and over ,Algorithms ,Alzheimer Disease ,Amyloid beta-Peptides ,Australia ,Biomarkers ,Cognition ,Cognitive Dysfunction ,Computational Biology ,Data Analysis ,Female ,Humans ,Longitudinal Studies ,Male ,Neuroimaging ,Positron-Emission Tomography ,Reproducibility of Results - Abstract
To improve understanding of Alzheimer's disease, large observational studies are needed to increase power for more nuanced analyses. Combining data across existing observational studies represents one solution. However, the disparity of such datasets makes this a non-trivial task. Here, a machine learning approach was applied to impute longitudinal neuropsychological test scores across two observational studies, namely the Australian Imaging, Biomarkers and Lifestyle Study (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) providing an overall harmonised dataset. MissForest, a machine learning algorithm, capitalises on the underlying structure and relationships of data to impute test scores not measured in one study aligning it to the other study. Results demonstrated that simulated missing values from one dataset could be accurately imputed, and that imputation of actual missing data in one dataset showed comparable discrimination (p
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- 2021
18. Postmortem Neocortical 3H-PiB Binding and Levels of Unmodified and Pyroglutamate Aβ in Down Syndrome and Sporadic Alzheimer’s Disease
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Pivtoraiko, Violetta N, Racic, Tamara, Abrahamson, Eric E, Villemagne, Victor L, Handen, Benjamin L, Lott, Ira T, Head, Elizabeth, and Ikonomovic, Milos D
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Biological Psychology ,Biomedical and Clinical Sciences ,Neurosciences ,Psychology ,Aging ,Acquired Cognitive Impairment ,Dementia ,Down Syndrome ,Alzheimer's Disease ,Brain Disorders ,Intellectual and Developmental Disabilities (IDD) ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Neurodegenerative ,2.1 Biological and endogenous factors ,Aetiology ,Neurological ,Alzheimer’s disease ,Down syndrome ,Pittsburgh Compound-B ,amyloid ,cerebral amyloid angiopathy ,default mode network ,pyroglutamate ,Biochemistry and Cell Biology ,Cognitive Sciences ,Biological psychology - Abstract
Individuals with Down syndrome (DS) have a genetic predisposition for amyloid-β (Aβ) overproduction and earlier onset of Aβ deposits compared to patients with sporadic late-onset Alzheimer's disease (AD). Positron emission tomography (PET) with Pittsburgh Compound-B (PiB) detects fibrillar Aβ pathology in living people with DS and AD, but its relationship with heterogeneous Aβ forms aggregated within amyloid deposits is not well understood. We performed quantitative in vitro 3H-PiB binding assays and enzyme-linked immunosorbent assays of fibrillar (insoluble) unmodified Aβ40 and Aβ42 forms and N-terminus truncated and pyroglutamate-modified AβNpE3-40 and AβNpE3-42 forms in postmortem frontal cortex and precuneus samples from 18 DS cases aged 43-63 years and 17 late-onset AD cases aged 62-99 years. Both diagnostic groups had frequent neocortical neuritic plaques, while the DS group had more severe vascular amyloid pathology (cerebral amyloid angiopathy, CAA). Compared to the AD group, the DS group had higher levels of Aβ40 and AβNpE3-40, while the two groups did not differ by Aβ42 and AβNpE3-42 levels. This resulted in lower ratios of Aβ42/Aβ40 and AβNpE3-42/AβNpE3-40 in the DS group compared to the AD group. Correlations of Aβ42/Aβ40 and AβNpE3-42/AβNpE3-40 ratios with CAA severity were strong in DS cases and weak in AD cases. Pyroglutamate-modified Aβ levels were lower than unmodified Aβ levels in both diagnostic groups, but within group proportions of both pyroglutamate-modified Aβ forms relative to both unmodified Aβ forms were lower in the DS group but not in the AD group. The two diagnostic groups did not differ by 3H-PiB binding levels. These results demonstrate that compared to late-onset AD cases, adult DS individuals with similar severity of neocortical neuritic plaques and greater CAA pathology have a preponderance of both pyroglutamate-modified AβNpE3-40 and unmodified Aβ40 forms. Despite the distinct molecular profile of Aβ forms and greater vascular amyloidosis in DS cases, cortical 3H-PiB binding does not distinguish between diagnostic groups that are at an advanced level of amyloid plaque pathology. This underscores the need for the development of CAA-selective PET radiopharmaceuticals to detect and track the progression of cerebral vascular amyloid deposits in relation to Aβ plaques in individuals with DS.
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- 2021
19. Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease
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Keret, Ophir, Staffaroni, Adam M, Ringman, John M, Cobigo, Yann, Goh, Sheng‐Yang M, Wolf, Amy, Allen, Isabel Elaine, Salloway, Stephen, Chhatwal, Jasmeer, Brickman, Adam M, Reyes‐Dumeyer, Dolly, Bateman, Randal J, Benzinger, Tammie LS, Morris, John C, Ances, Beau M, Joseph‐Mathurin, Nelly, Perrin, Richard J, Gordon, Brian A, Levin, Johannes, Vöglein, Jonathan, Jucker, Mathias, la Fougère, Christian, Martins, Ralph N, Sohrabi, Hamid R, Taddei, Kevin, Villemagne, Victor L, Schofield, Peter R, Brooks, William S, Fulham, Michael, Masters, Colin L, Ghetti, Bernardino, Saykin, Andrew J, Jack, Clifford R, Graff‐Radford, Neill R, Weiner, Michael, Cash, David M, Allegri, Ricardo F, Chrem, Patricio, Yi, Su, Miller, Bruce L, Rabinovici, Gil D, Rosen, Howard J, and Network, Dominantly Inherited Alzheimer
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Biological Psychology ,Biomedical and Clinical Sciences ,Neurosciences ,Psychology ,Aging ,Prevention ,Neurodegenerative ,Alzheimer's Disease ,Dementia ,Brain Disorders ,Acquired Cognitive Impairment ,Genetics ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Patient Safety ,Neurological ,Good Health and Well Being ,autosomal dominant Alzheimer's disease ,brain atrophy ,Dominantly Inherited Alzheimer Network ,preclinical Alzheimer's disease ,Biological psychology - Abstract
IntroductionAsymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment.MethodsWe created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally.ResultsOur risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset.DiscussionIndividualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials.
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- 2021
20. Astrocyte biomarker signatures of amyloid-β and tau pathologies in Alzheimer’s disease
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Ferrari-Souza, João Pedro, Ferreira, Pâmela C. L., Bellaver, Bruna, Tissot, Cécile, Wang, Yi-Ting, Leffa, Douglas T., Brum, Wagner S., Benedet, Andréa L., Ashton, Nicholas J., De Bastiani, Marco Antônio, Rocha, Andréia, Therriault, Joseph, Lussier, Firoza Z., Chamoun, Mira, Servaes, Stijn, Bezgin, Gleb, Kang, Min Su, Stevenson, Jenna, Rahmouni, Nesrine, Pallen, Vanessa, Poltronetti, Nina Margherita, Klunk, William E., Tudorascu, Dana L., Cohen, Ann D., Villemagne, Victor L., Gauthier, Serge, Blennow, Kaj, Zetterberg, Henrik, Souza, Diogo O., Karikari, Thomas K., Zimmer, Eduardo R., Rosa-Neto, Pedro, and Pascoal, Tharick A.
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- 2022
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21. Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease
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Dincer, Aylin, Gordon, Brian A, Hari-Raj, Amrita, Keefe, Sarah J, Flores, Shaney, McKay, Nicole S, Paulick, Angela M, Lewis, Kristine E Shady, Feldman, Rebecca L, Hornbeck, Russ C, Allegri, Ricardo, Ances, Beau M, Berman, Sarah B, Brickman, Adam M, Brooks, William S, Cash, David M, Chhatwal, Jasmeer P, Farlow, Martin R, la Fougère, Christian, Fox, Nick C, Fulham, Michael J, Jack, Clifford R, Joseph-Mathurin, Nelly, Karch, Celeste M, Lee, Athene, Levin, Johannes, Masters, Colin L, McDade, Eric M, Oh, Hwamee, Perrin, Richard J, Raji, Cyrus, Salloway, Stephen P, Schofield, Peter R, Su, Yi, Villemagne, Victor L, Wang, Qing, Weiner, Michael W, Xiong, Chengjie, Yakushev, Igor, Morris, John C, Bateman, Randall J, Benzinger, Tammie LS, and DIAN, for the Dominantly Inherited Alzheimer Network
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Neurodegenerative ,Dementia ,Clinical Research ,Brain Disorders ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Neurosciences ,Aging ,Acquired Cognitive Impairment ,Alzheimer's Disease ,2.1 Biological and endogenous factors ,Aetiology ,Neurological ,Alzheimer Disease ,Amyloid beta-Peptides ,Atrophy ,Hippocampus ,Humans ,Magnetic Resonance Imaging ,Positron-Emission Tomography ,Alzheimer disease ,Autosomal dominant Alzheimer disease ,Preclinical ,Cortical signature ,Amyloid ,Cortical thickness ,Dominantly Inherited Alzheimer Network DIAN - Abstract
Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.
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- 2020
22. Kinetic modeling of the monoamine oxidase-B radioligand [18F]SMBT-1 in human brain with positron emission tomography
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Lopresti, Brian J, primary, Stehouwer, Jeffrey, additional, Reese, Alexandria C, additional, Mason, Neale S, additional, Royse, Sarah K, additional, Narendran, Rajesh, additional, Laymon, Charles M, additional, Lopez, Oscar L, additional, Cohen, Ann D, additional, Mathis, Chester A, additional, and Villemagne, Victor L, additional
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- 2024
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23. Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume
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Milicic, Lidija, Vacher, Michael, Porter, Tenielle, Doré, Vincent, Burnham, Samantha C., Bourgeat, Pierrick, Shishegar, Rosita, Doecke, James, Armstrong, Nicola J., Tankard, Rick, Maruff, Paul, Masters, Colin L., Rowe, Christopher C., Villemagne, Victor L., and Laws, Simon M.
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- 2022
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24. Multisite study of the relationships between antemortem [11C]PIB‐PET Centiloid values and postmortem measures of Alzheimer's disease neuropathology
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La Joie, Renaud, Ayakta, Nagehan, Seeley, William W, Borys, Ewa, Boxer, Adam L, DeCarli, Charles, Doré, Vincent, Grinberg, Lea T, Huang, Eric, Hwang, Ji‐Hye, Ikonomovic, Milos D, Jack, Clifford, Jagust, William J, Jin, Lee‐Way, Klunk, William E, Kofler, Julia, Lesman‐Segev, Orit H, Lockhart, Samuel N, Lowe, Val J, Masters, Colin L, Mathis, Chester A, McLean, Catriona L, Miller, Bruce L, Mungas, Daniel, O'Neil, James P, Olichney, John M, Parisi, Joseph E, Petersen, Ronald C, Rosen, Howard J, Rowe, Christopher C, Spina, Salvatore, Vemuri, Prashanthi, Villemagne, Victor L, Murray, Melissa E, and Rabinovici, Gil D
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Biomedical and Clinical Sciences ,Clinical Sciences ,Neurosciences ,Dementia ,Bioengineering ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Neurodegenerative ,Brain Disorders ,Biomedical Imaging ,Acquired Cognitive Impairment ,Aging ,Alzheimer's Disease ,Aged ,Alzheimer Disease ,Aniline Compounds ,Autopsy ,Female ,Humans ,Male ,Neuropathology ,Plaque ,Amyloid ,Positron-Emission Tomography ,Retrospective Studies ,Thiazoles ,beta-amyloid ,Positron emission tomography ,Centiloid ,CERAD ,Thal ,Alzheimer's disease neuropathologic changes ,Harmonization ,Threshold ,Pittsburgh compound-B ,β-amyloid ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
IntroductionWe sought to establish the relationships between standard postmortem measures of AD neuropathology and antemortem [11C]PIB-positron emission tomography ([11C]PIB-PET) analyzed with the Centiloid (CL) method, a standardized scale for Aβ-PET quantification.MethodsFour centers contributed 179 participants encompassing a broad range of clinical diagnoses, PET data, and autopsy findings.ResultsCL values increased with each CERAD neuritic plaque score increment (median -3 CL for no plaques and 92 CL for frequent plaques) and nonlinearly with Thal Aβ phases (increases were detected starting at phase 2) with overlap between scores/phases. PET-pathology associations were comparable across sites and unchanged when restricting the analyses to the 56 patients who died within 2 years of PET. A threshold of 12.2 CL detected CERAD moderate-to-frequent neuritic plaques (area under the curve = 0.910, sensitivity = 89.2%, specificity = 86.4%), whereas 24.4 CL identified intermediate-to-high AD neuropathological changes (area under the curve = 0.894, sensitivity = 84.1%, specificity = 87.9%).DiscussionOur study demonstrated the robustness of a multisite Centiloid [11C]PIB-PET study and established a range of pathology-based CL thresholds.
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- 2019
25. Prevalence of amyloid‐β pathology in distinct variants of primary progressive aphasia
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Bergeron, David, Gorno‐Tempini, Maria L, Rabinovici, Gil D, Santos‐Santos, Miguel A, Seeley, William, Miller, Bruce L, Pijnenburg, Yolande, Keulen, M Antoinette, Groot, Colin, van Berckel, Bart NM, van der Flier, Wiesje M, Scheltens, Philip, Rohrer, Jonathan D, Warren, Jason D, Schott, Jonathan M, Fox, Nick C, Sanchez‐Valle, Raquel, Grau‐Rivera, Oriol, Gelpi, Ellen, Seelaar, Harro, Papma, Janne M, van Swieten, John C, Hodges, John R, Leyton, Cristian E, Piguet, Olivier, Rogalski, Emily J, Mesulam, Marsel M, Koric, Lejla, Kristensen, Nora, Pariente, Jeéreémie, Dickerson, Bradford, Mackenzie, Ian R, Hsiung, Ging‐Yuek R, Belliard, Serge, Irwin, David J, Wolk, David A, Grossman, Murray, Jones, Matthew, Harris, Jennifer, Mann, David, Snowden, Julie S, Chrem‐Mendez, Patricio, Calandri, Ismael L, Amengual, Alejandra A, Miguet‐Alfonsi, Carole, Magnin, Eloi, Magnani, Giuseppe, Santangelo, Roberto, Deramecourt, Vincent, Pasquier, Florence, Mattsson, Niklas, Nilsson, Christer, Hansson, Oskar, Keith, Julia, Masellis, Mario, Black, Sandra E, Matías‐Guiu, Jordi A, Cabrera‐Martin, María‐Nieves, Paquet, Claire, Dumurgier, Julien, Teichmann, Marc, Sarazin, Marie, Bottlaender, Michel, Dubois, Bruno, Rowe, Christopher C, Villemagne, Victor L, Vandenberghe, Rik, Granadillo, Elias, Teng, Edmond, Mendez, Mario, Meyer, Philipp T, Frings, Lars, Lleó, Alberto, Blesa, Rafael, Fortea, Juan, Seo, Sang Won, Diehl‐Schmid, Janine, Grimmer, Timo, Frederiksen, Kristian Steen, Sánchez‐Juan, Pascual, Chételat, Gaël, Jansen, Willemijn, Bouchard, Rémi W, Laforce, Robert Jr, Visser, Pieter Jelle, and Ossenkoppele, Rik
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Biomedical and Clinical Sciences ,Neurosciences ,Clinical Sciences ,Dementia ,Rare Diseases ,Aging ,Neurodegenerative ,Brain Disorders ,Frontotemporal Dementia (FTD) ,Clinical Research ,Aphasia ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Acquired Cognitive Impairment ,Alzheimer's Disease Related Dementias (ADRD) ,Genetics ,Alzheimer's Disease ,4.2 Evaluation of markers and technologies ,Aetiology ,Detection ,screening and diagnosis ,2.1 Biological and endogenous factors ,Neurological ,Age Factors ,Aged ,Aged ,80 and over ,Amyloid beta-Peptides ,Aphasia ,Primary Progressive ,Apolipoproteins E ,Brain ,Female ,Genotype ,Humans ,Male ,Middle Aged ,Prevalence ,Neurology & Neurosurgery ,Clinical sciences - Abstract
ObjectiveTo estimate the prevalence of amyloid positivity, defined by positron emission tomography (PET)/cerebrospinal fluid (CSF) biomarkers and/or neuropathological examination, in primary progressive aphasia (PPA) variants.MethodsWe conducted a meta-analysis with individual participant data from 1,251 patients diagnosed with PPA (including logopenic [lvPPA, n = 443], nonfluent [nfvPPA, n = 333], semantic [svPPA, n = 401], and mixed/unclassifiable [n = 74] variants of PPA) from 36 centers, with a measure of amyloid-β pathology (CSF [n = 600], PET [n = 366], and/or autopsy [n = 378]) available. The estimated prevalence of amyloid positivity according to PPA variant, age, and apolipoprotein E (ApoE) ε4 status was determined using generalized estimating equation models.ResultsAmyloid-β positivity was more prevalent in lvPPA (86%) than in nfvPPA (20%) or svPPA (16%; p
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- 2018
26. Insulin resistance, cognition and Alzheimer's disease biomarkers: Evidence that CSF Aβ42 moderates the association between insulin resistance and increased CSF tau levels
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Woodfield, Amy, Porter, Tenielle, Gilani, Israa, Noordin, Siti, Li, Qiao-Xin, Collins, Steven, Martins, Ralph N., Maruff, Paul, Masters, Colin L., Rowe, Christopher C., Villemagne, Victor L., Dore, Vincent, Newsholme, Philip, Laws, Simon M., and Verdile, Giuseppe
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- 2022
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27. Assessment of a polygenic hazard score for the onset of pre-clinical Alzheimer’s disease
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Vacher, Michael, Doré, Vincent, Porter, Tenielle, Milicic, Lidija, Villemagne, Victor L., Bourgeat, Pierrick, Burnham, Sam C., Cox, Timothy, Masters, Colin L., Rowe, Christopher C., Fripp, Jurgen, Doecke, James D., and Laws, Simon M.
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- 2022
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28. Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease
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Cadby, Gemma, Giles, Corey, Melton, Phillip E., Huynh, Kevin, Mellett, Natalie A., Duong, Thy, Nguyen, Anh, Cinel, Michelle, Smith, Alex, Olshansky, Gavriel, Wang, Tingting, Brozynska, Marta, Inouye, Mike, McCarthy, Nina S., Ariff, Amir, Hung, Joseph, Hui, Jennie, Beilby, John, Dubé, Marie-Pierre, Watts, Gerald F., Shah, Sonia, Wray, Naomi R., Lim, Wei Ling Florence, Chatterjee, Pratishtha, Martins, Ian, Laws, Simon M., Porter, Tenielle, Vacher, Michael, Bush, Ashley I., Rowe, Christopher C., Villemagne, Victor L., Ames, David, Masters, Colin L., Taddei, Kevin, Arnold, Matthias, Kastenmüller, Gabi, Nho, Kwangsik, Saykin, Andrew J., Han, Xianlin, Kaddurah-Daouk, Rima, Martins, Ralph N., Blangero, John, Meikle, Peter J., and Moses, Eric K.
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- 2022
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29. Mesial temporal tau in amyloid-β-negative cognitively normal older persons
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Krishnadas, Natasha, Doré, Vincent, Groot, Colin, Lamb, Fiona, Bourgeat, Pierrick, Burnham, Samantha C., Huang, Kun, Goh, Anita M. Y., Masters, Colin L., Villemagne, Victor L., and Rowe, Christopher C.
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- 2022
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30. Implementation and Assessment of Tau Thresholds in Non-Demented Individuals as Predictors of Cognitive Decline in Tau Imaging Studies.
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Gogola, Alexandra, Cohen, Ann D., Snitz, Beth, Minhas, Davneet, Tudorascu, Dana, Ikonomovic, Milos D., Shaaban, C. Elizabeth, Doré, Vincent, Matan, Cristy, Bourgeat, Pierrick, Mason, N. Scott, Leuzy, Antoine, Aizenstein, Howard, Mathis, Chester A., Lopez, Oscar L., Lopresti, Brian J., and Villemagne, Victor L.
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ALZHEIMER'S disease ,TEMPORAL lobe ,COGNITION disorders ,DISEASE progression ,TAU proteins - Abstract
Background: Tau accumulation in Alzheimer's disease is associated with short term clinical progression and faster rates of cognitive decline in individuals with high amyloid-β deposition. Defining an optimal threshold of tau accumulation predictive of cognitive decline remains a challenge. Objective: We tested the ability of regional tau PET sensitivity and specificity thresholds to predict longitudinal cognitive decline. We also tested the predictive performance of thresholds in the proposed new NIA-AA biological staging for Alzheimer's disease where multiple levels of tau positivity are used to stage participants. Methods:
18 F-flortaucipir scans from 301 non-demented participants were processed and sampled. Four cognitive measures were assessed longitudinally. Regional standardized uptake value ratios were split into infra- and suprathreshold groups at baseline using previously derived thresholds. Survival analysis, log rank testing, and Generalized Estimation Equations assessed the relationship between the application of regional sensitivity/specificity thresholds and change in cognitive measures as well as tau threshold performance in predicting cognitive decline within the new NIA-AA biological staging. Results: The meta temporal region was best for predicting risk of short-term cognitive decline in suprathreshold, as compared to infrathreshold participants. When applying multiple levels of tau positivity, each subsequent level of tau identified cognitive decline at earlier timepoints. Conclusions: When using18 F-flortaucipir, meta temporal suprathreshold classification was associated with increased risk of cognitive decline, suggesting that abnormal tau deposition in the cortex predicts decline. Likewise, the application of multiple levels of tau clearly predicts the distinctive cognitive trajectories in the new NIA-AA biological staging framework. [ABSTRACT FROM AUTHOR]- Published
- 2024
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31. Aβ Imaging in Aging, Alzheimer’s Disease, and Other Neurodegenerative Conditions
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Villemagne, Victor L., Doré, Vincent, Burnham, Samantha, Rowe, Christopher C., Dierckx, Rudi A. J. O., editor, Otte, Andreas, editor, de Vries, Erik F. J., editor, van Waarde, Aren, editor, and Leenders, Klaus L., editor
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- 2021
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32. Correction to: The Strategic Biomarker Roadmap for the validation of Alzheimer’s diagnostic biomarkers: methodological update
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Boccardi, Marina, Dodich, Alessandra, Albanese, Emiliano, Gayet-Ageron, Angèle, Festari, Cristina, Ashton, Nicholas J., Bischof, Gérard N., Chiotis, Konstantinos, Leuzy, Antoine, Wolters, Emma E., Walter, Martin, Rabinovici, Gil D., Carrillo, Maria, Drzezga, Alexander, Hansson, Oskar, Nordberg, Agneta, Ossenkoppele, Rik, Villemagne, Victor L., Winblad, Bengt, Frisoni, Giovanni, and Garibotto, Valentina
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- 2021
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33. Association of Cerebral Amyloid-β Aggregation With Cognitive Functioning in Persons Without Dementia
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Jansen, Willemijn J, Ossenkoppele, Rik, Tijms, Betty M, Fagan, Anne M, Hansson, Oskar, Klunk, William E, van der Flier, Wiesje M, Villemagne, Victor L, Frisoni, Giovanni B, Fleisher, Adam S, Lleó, Alberto, Mintun, Mark A, Wallin, Anders, Engelborghs, Sebastiaan, Na, Duk L, Chételat, Gäel, Molinuevo, José Luis, Landau, Susan M, Mattsson, Niklas, Kornhuber, Johannes, Sabri, Osama, Rowe, Christopher C, Parnetti, Lucilla, Popp, Julius, Fladby, Tormod, Jagust, William J, Aalten, Pauline, Lee, Dong Young, Vandenberghe, Rik, de Oliveira, Catarina Resende, Kapaki, Elisabeth, Froelich, Lutz, Ivanoiu, Adrian, Gabryelewicz, Tomasz, Verbeek, Marcel M, Sanchez-Juan, Páscual, Hildebrandt, Helmut, Camus, Vincent, Zboch, Marzena, Brooks, David J, Drzezga, Alexander, Rinne, Juha O, Newberg, Andrew, de Mendonça, Alexandre, Sarazin, Marie, Rabinovici, Gil D, Madsen, Karine, Kramberger, Milica G, Nordberg, Agneta, Mok, Vincent, Mroczko, Barbara, Wolk, David A, Meyer, Philipp T, Tsolaki, Magda, Scheltens, Philip, Verhey, Frans RJ, Visser, Pieter Jelle, Aarsland, Dag, Alcolea, Daniel, Alexander, Myriam, Almdahl, Ina S, Arnold, Steven E, Baldeiras, Inês, Barthel, Henryk, van Berckel, Bart NM, Blennow, Kaj, van Buchem, Mark A, Cavedo, Enrica, Chen, Kewei, Chipi, Elena, Cohen, Ann D, Förster, Stefan, Fortea, Juan, Frederiksen, Kristian S, Freund-Levi, Yvonne, Gkatzima, Olymbia, Gordon, Mark Forrest, Grimmer, Timo, Hampel, Harald, Hausner, Lucrezia, Hellwig, Sabine, Herukka, Sanna-Kaisa, Johannsen, Peter, Klimkowicz-Mrowiec, Aleksandra, Köhler, Sebastian, Koglin, Norman, van Laere, Koen, de Leon, Mony, Lisetti, Viviana, Maier, Wolfgang, Marcusson, Jan, Meulenbroek, Olga, Møllergård, Hanne M, Morris, John C, Nordlund, Arto, Novak, Gerald P, Paraskevas, George P, Perera, Gayan, Peters, Oliver, and Ramakers, Inez HGB
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Health Services and Systems ,Health Sciences ,Acquired Cognitive Impairment ,Alzheimer's Disease Related Dementias (ADRD) ,Neurosciences ,Aging ,Dementia ,Brain Disorders ,Behavioral and Social Science ,Neurodegenerative ,Alzheimer's Disease ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Clinical Research ,Aetiology ,2.1 Biological and endogenous factors ,Neurological ,Mental health ,Aged ,Alzheimer Disease ,Amyloid beta-Peptides ,Brain ,Cognition Disorders ,Cognitive Dysfunction ,Cross-Sectional Studies ,Female ,Humans ,Male ,Memory ,Episodic ,Mental Status and Dementia Tests ,Middle Aged ,Positron-Emission Tomography ,Reference Values ,Amyloid Biomarker Study Group ,Other Medical and Health Sciences ,Psychology ,Cognitive Sciences ,Clinical sciences ,Clinical and health psychology - Abstract
ImportanceCerebral amyloid-β aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials.ObjectiveTo investigate whether amyloid-β aggregation is associated with cognitive functioning in persons without dementia.Design, setting, and participantsThis cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017.Main outcomes and measuresGlobal cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score ≤27 or memory z score≤-1.28) and to assess whether this association was moderated by age, sex, educational level, or apolipoprotein E genotype.ResultsAmong 2908 persons with normal cognition (mean [SD] age, 67.4 [12.8] years), amyloid positivity was associated with low memory scores after age 70 years (mean difference in amyloid positive vs negative, 4% [95% CI, 0%-7%] at 72 years and 21% [95% CI, 10%-33%] at 90 years) but was not associated with low MMSE scores (mean difference, 3% [95% CI, -1% to 6%], P = .16). Among 4133 patients with MCI (mean [SD] age, 70.2 [8.5] years), amyloid positivity was associated with low memory (mean difference, 16% [95% CI, 12%-20%], P
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- 2018
34. The AUstralian multidomain Approach to Reduce dementia Risk by prOtecting brain health With lifestyle intervention study (AU‐ARROW): A study protocol for a single‐blind, multi‐site, randomized controlled trial
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Gardener, Samantha L., primary, Fuller, Stephanie J., additional, Naismith, Sharon L., additional, Baker, Laura, additional, Kivipelto, Miia, additional, Villemagne, Victor L., additional, Grieve, Stuart M., additional, Yates, Paul, additional, Rainey‐Smith, Stephanie R., additional, Chen, Juliana, additional, Thompson, Belinda, additional, Armstrong, Nicola J., additional, Fernando, Malika G., additional, Blagojevic Castro, Carolina, additional, Meghwar, Silochna, additional, Raman, Rema, additional, Gleason, Andrew, additional, Ireland, Catriona, additional, Clarnette, Roger, additional, Anstey, Kaarin J., additional, Taddei, Kevin, additional, Garg, Manohar, additional, Sohrabi, Hamid R., additional, and Martins, Ralph N., additional
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- 2024
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35. Effect of blood collection tube containing protease inhibitors on the pre-analytical stability of Alzheimer’s disease plasma biomarkers
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Chen, Yijun, primary, Zeng, Xuemei, additional, Lee, Jihui, additional, Sehrawat, Anuradha, additional, Lafferty, Tara K., additional, Boslett, James J., additional, Klunk, William E., additional, Pascoal, Tharick A., additional, Villemagne, Victor L., additional, Cohen, Annie D., additional, Lopez, Oscar, additional, Yates, Nathan A., additional, and Karikari, Thomas K., additional
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- 2024
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36. PET Imaging of brain muscarinic receptors with 18F-Fluorobenzyl-Dexetimide: A first in human study
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Rowe, Christopher C., Krishnadas, Natasha, Ackermann, Uwe, Doré, Vincent, Goh, Rachel Y.W., Guzman, Rodney, Chong, Lee, Bozinovski, Svetlana, Mulligan, Rachel, Kanaan, Richard, Dean, Brian, and Villemagne, Victor L.
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- 2021
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37. The Amyloid-β Pathway in Alzheimer’s Disease
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Hampel, Harald, Hardy, John, Blennow, Kaj, Chen, Christopher, Perry, George, Kim, Seung Hyun, Villemagne, Victor L., Aisen, Paul, Vendruscolo, Michele, Iwatsubo, Takeshi, Masters, Colin L., Cho, Min, Lannfelt, Lars, Cummings, Jeffrey L., and Vergallo, Andrea
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- 2021
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38. Androgen receptor CAG repeat length as a moderator of the relationship between free testosterone levels and cognition
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Tan, Sherilyn, Porter, Tenielle, Bucks, Romola S., Weinborn, Michael, Milicic, Lidija, Brown, Ailsa, Rainey-Smith, Stephanie R., Taddei, Kevin, Ames, David, Masters, Colin L., Maruff, Paul, Savage, Greg, Rowe, Christopher C., Villemagne, Victor L., Brown, Belinda, Sohrabi, Hamid R., Laws, Simon M., and Martins, Ralph N.
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- 2021
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39. Advances in Brain Amyloid Imaging
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Krishnadas, Natasha, Villemagne, Victor L., Doré, Vincent, and Rowe, Christopher C.
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- 2021
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40. Non-negative matrix factorisation improves Centiloid robustness in longitudinal studies
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Bourgeat, Pierrick, Doré, Vincent, Doecke, James, Ames, David, Masters, Colin L., Rowe, Christopher C., Fripp, Jurgen, and Villemagne, Victor L.
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- 2021
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41. Relationship between amyloid and tau levels and its impact on tau spreading
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Doré, Vincent, Krishnadas, Natasha, Bourgeat, Pierrick, Huang, Kun, Li, Shenpeng, Burnham, Samantha, Masters, Colin L., Fripp, Jurgen, Villemagne, Victor L., and Rowe, Christopher C.
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- 2021
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42. Mesial temporal tau is related to worse cognitive performance and greater neocortical tau load in amyloid-β–negative cognitively normal individuals
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Groot, Colin, Doré, Vincent, Robertson, Joanne, Burnham, Samantha C., Savage, Greg, Ossenkoppele, Rik, Rowe, Christopher C., and Villemagne, Victor L.
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- 2021
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43. The Australian multidomain approach to reduce dementia risk by protecting brain health with lifestyle intervention study (AU-ARROW): A study protocol for a single-blind, multi-site, randomized controlled trial
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Gardener, Samantha L., Fuller, Stephanie J., Naismith, Sharon L., Baker, Laura, Kivipelto, Miia, Villemagne, Victor L., Grieve, Stuart M., Yates, Paul, Rainey-Smith, Stephanie R., Chen, Juliana, Thompson, Belinda, Armstrong, Nicola J., Fernando, Malika G., Castro, Carolina B., Meghwar, Silochna, Raman, Rema, Gleason, Andrew, Ireland, Catriona, Clarnette, Roger, Anstey, Kaarin J., Taddei, Kevin, Garg, Manohar, Sohrabi, Hamid R., Martins, Ralph N., Gardener, Samantha L., Fuller, Stephanie J., Naismith, Sharon L., Baker, Laura, Kivipelto, Miia, Villemagne, Victor L., Grieve, Stuart M., Yates, Paul, Rainey-Smith, Stephanie R., Chen, Juliana, Thompson, Belinda, Armstrong, Nicola J., Fernando, Malika G., Castro, Carolina B., Meghwar, Silochna, Raman, Rema, Gleason, Andrew, Ireland, Catriona, Clarnette, Roger, Anstey, Kaarin J., Taddei, Kevin, Garg, Manohar, Sohrabi, Hamid R., and Martins, Ralph N.
- Abstract
INTRODUCTION: The Finnish Geriatric Intervention Study (FINGER) led to the global dementia risk reduction initiative: World-Wide FINGERS (WW-FINGERS). As part of WW-FINGERS, the Australian AU-ARROW study mirrors aspects of FINGER, as well as US-POINTER. METHOD: AU-ARROW is a randomized, single-blind, multisite, 2-year clinical trial (n = 600; aged 55–79). The multimodal lifestyle intervention group will engage in aerobic exercise, resistance training and stretching, dietary advice to encourage MIND diet adherence, BrainHQ cognitive training, and medical monitoring and health education. The Health Education and Coaching group will receive occasional health education sessions. The primary outcome measure is the change in a global composite cognitive score. Extra value will emanate from blood biomarker analysis, positron emission tomography (PET) imaging, brain magnetic resonance imaging (MRI), and retinal biomarker tests. DISCUSSION: The finalized AU-ARROW protocol is expected to allow development of an evidence-based innovative treatment plan to reduce cognitive decline and dementia risk, and effective transfer of research outcomes into Australian health policy. Highlights: Study protocol for a single-blind, randomized controlled trial, the AU-ARROW Study. The AU-ARROW Study is a member of the World-Wide FINGERS (WW-FINGERS) initiative. AU-ARROW's primary outcome measure is change in a global composite cognitive score. Extra significance from amyloid PET imaging, brain MRI, and retinal biomarker tests. Leading to development of an innovative treatment plan to reduce cognitive decline.
- Published
- 2024
44. Impact of APOE-ε4 carriage on the onset and rates of neocortical Aβ-amyloid deposition
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Burnham, Samantha C., Laws, Simon M., Budgeon, Charley A., Doré, Vincent, Porter, Tenielle, Bourgeat, Pierrick, Buckley, Rachel F., Murray, Kevin, Ellis, Kathryn A., Turlach, Berwin A., Salvado, Olivier, Ames, David, Martins, Ralph N., Rentz, Dorene, Masters, Colin L., Rowe, Christopher C., and Villemagne, Victor L.
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- 2020
- Full Text
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45. Amyloid-PET and 18F-FDG-PET in the diagnostic investigation of Alzheimer's disease and other dementias
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Chételat, Gaël, Arbizu, Javier, Barthel, Henryk, Garibotto, Valentina, Law, Ian, Morbelli, Silvia, van de Giessen, Elsmarieke, Agosta, Federica, Barkhof, Frederik, Brooks, David J, Carrillo, Maria C, Dubois, Bruno, Fjell, Anders M, Frisoni, Giovanni B, Hansson, Oskar, Herholz, Karl, Hutton, Brian F, Jack, Clifford R, Jr, Lammertsma, Adriaan A, Landau, Susan M, Minoshima, Satoshi, Nobili, Flavio, Nordberg, Agneta, Ossenkoppele, Rik, Oyen, Wim J G, Perani, Daniela, Rabinovici, Gil D, Scheltens, Philip, Villemagne, Victor L, Zetterberg, Henrik, and Drzezga, Alexander
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- 2020
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46. Association of plasma biomarkers of Alzheimer's disease and related disorders with cognition and cognitive decline: The MYHAT population‐based study.
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Zhang, Yingjin, Ferreira, Pamela C. L., Jacobsen, Erin, Bellaver, Bruna, Pascoal, Tharick A., Snitz, Beth E., Chang, Chung‐Chou H., Villemagne, Victor L., Ganguli, Mary, and Karikari, Thomas K.
- Abstract
INTRODUCTION: Plasma biomarkers of Alzheimer's disease and related dementias predict global cognitive performance and decline over time; it remains unclear how they associate with changes in different dementia syndromes affecting distinct cognitive domains. METHODS: In a prospective study with repeated assessments of a randomly selected population‐based cohort (n = 787, median age 73), we evaluated performance and decline in different cognitive domains over up to 8 years in relation to plasma concentrations of amyloid beta 42/40 (Aβ42/40) ratio, phosphorylated tau181 (p‐tau181), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP). RESULTS: Cross‐sectionally, memory showed the strongest associations with p‐tau181, and attention, executive, and visuospatial functions with NfL. Longitudinally, memory decline was distinguishable with all biomarker profiles dichotomized according to data‐driven cutoffs, most efficiently with Aβ42/40. GFAP and Aβ42/40 were the best discriminators of decline patterns in language and visuospatial functions, respectively. DISCUSSION: These relatively non‐invasive tests may be beneficial for clinical screening after replication in other populations and validation through neuroimaging or cerebrospinal fluid analysis. Highlights: We performed a prospective study with up to 8 years of repeated domain‐specific cognitive assessments and baseline plasma Alzheimer's disease and related dementias biomarker measurements in a randomly selected population‐based cohort.We considered distinct growth curves of trajectories of different cognitive domains and survival bias induced by missing data by adding quadratic time and applying joint modeling technique.Cross‐sectionally, memory showed the strongest associations with plasma phosphorylated tau181, while attention, executive, and visuospatial functions were most strongly associated with neurofilament light chain.Longitudinally, memory and visuospatial declines were most efficiently distinguished by dichotomized amyloid beta 42/40 profile among all plasma biomarkers, while language was by dichotomized glial fibrillary acidic protein.These relatively non‐invasive tests may be beneficial for clinical screening; however, they will need replication in other populations and validation through neuroimaging and/or cerebrospinal fluid assessments. [ABSTRACT FROM AUTHOR]
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- 2024
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47. Association Between β-Amyloid Accumulation and Incident Dementia in Individuals 80 Years or Older Without Dementia
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Lopez, Oscar L., primary, Villemagne, Victor L., additional, Chang, Yue-Fang, additional, Cohen, Ann D., additional, Klunk, William E., additional, Mathis, Chester A., additional, Pascoal, Tharick, additional, Ikonomovic, Milos D., additional, Rowe, Christopher, additional, Dore, Vincent, additional, Snitz, Beth E., additional, Lopresti, Brian J., additional, Kamboh, M. Ilyas, additional, Aizenstein, Howard J., additional, and Kuller, Lewis H., additional
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- 2024
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48. Brain 11β-Hydroxysteroid Dehydrogenase Type 1 Occupancy by Xanamem™ Assessed by PET in Alzheimer’s Disease and Cognitively Normal Individuals
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Villemagne, Victor L., primary, Doré, Vincent, additional, Chong, Lee, additional, Kassiou, Michael, additional, Mulligan, Rachel, additional, Feizpour, Azadeh, additional, Taylor, Jack, additional, Roesner, Miriam, additional, Miller, Tamara, additional, and Rowe, Christopher C., additional
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- 2024
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49. Alzheimer's Disease biological PET staging using plasma p217+tau
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Feizpour, Azadeh, primary, Dore, Vincent, additional, Krishnadas, Natasha, additional, Bourgeat, Pierrick, additional, Doecke, James D., additional, Saad, Ziad, additional, Triana-Baltzer, Gallen, additional, Laws, Simon M., additional, Shishegar, Rosita, additional, Huang, Kun, additional, Fowler, Christopher, additional, Ward, Larry, additional, Masters, Colin L., additional, Mejan-Fripp, Jurgen, additional, Kolb, Hartmuth C., additional, Villemagne, Victor L., additional, and Rowe, Christopher C., additional
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- 2024
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50. Accurate Detection and Staging of Alzheimer's Disease by Plasma Ptau217 on a High Throughput Immunoassay Platform
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Feizpour, Azadeh, primary, Doecke, James D., additional, Doré, Vincent, additional, Krishnadas, Natasha, additional, Huang, Kun, additional, Bourgeat, Pierrick, additional, Laws, Simon M., additional, Fowler, Christopher, additional, Robertson, Joanne, additional, Mackintosh, Lucy, additional, Ayton, Scott, additional, Martins, Ralph N., additional, Rainey-Smith, Stephanie R., additional, Taddei, Kevin, additional, Ward, Larry, additional, Stage, Eddie, additional, Bannon, Anthony W., additional, Masters, colin, additional, Fripp, Jurgen, additional, Villemagne, Victor L., additional, and Rowe, Christopher C., additional
- Published
- 2024
- Full Text
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