661 results on '"Maruff, Paul"'
Search Results
2. Gene-SGAN: discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering
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Yang, Zhijian, Wen, Junhao, Abdulkadir, Ahmed, Cui, Yuhan, Erus, Guray, Mamourian, Elizabeth, Melhem, Randa, Srinivasan, Dhivya, Govindarajan, Sindhuja T., Chen, Jiong, Habes, Mohamad, Masters, Colin L., Maruff, Paul, Fripp, Jurgen, Ferrucci, Luigi, Albert, Marilyn S., Johnson, Sterling C., Morris, John C., LaMontagne, Pamela, Marcus, Daniel S., Benzinger, Tammie L. S., Wolk, David A., Shen, Li, Bao, Jingxuan, Resnick, Susan M., Shou, Haochang, Nasrallah, Ilya M., and Davatzikos, Christos
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- 2024
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3. Leukocyte surface biomarkers implicate deficits of innate immunity in sporadic Alzheimer's disease
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Huang, Xin, Li, Yihan, Fowler, Christopher, Doecke, James D, Lim, Yen Ying, Drysdale, Candace, Zhang, Vicky, Park, Keunha, Trounson, Brett, Pertile, Kelly, Rumble, Rebecca, Pickering, John W, Rissman, Robert A, Sarsoza, Floyd, Abdel‐Latif, Sara, Lin, Yong, Doré, Vincent, Villemagne, Victor, Rowe, Christopher C, Fripp, Jurgen, Martins, Ralph, Wiley, James S, Maruff, Paul, Mintzer, Jacobo E, Masters, Colin L, and Gu, Ben J
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Biomedical and Clinical Sciences ,Biological Psychology ,Clinical Sciences ,Neurosciences ,Psychology ,Neurodegenerative ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Alzheimer's Disease ,Brain Disorders ,Acquired Cognitive Impairment ,Dementia ,Aging ,2.1 Biological and endogenous factors ,Aetiology ,Detection ,screening and diagnosis ,4.1 Discovery and preclinical testing of markers and technologies ,Humans ,Alzheimer Disease ,Amyloid beta-Peptides ,Biomarkers ,Leukocytes ,Immunity ,Innate ,Alzheimer's disease ,CD11c ,CD163 ,CD59 ,CD91 ,complement system ,innate phagocytosis ,leukocyte biomarker ,peripheral immune response ,receptor for advanced glycation end products ,ROC curve ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
IntroductionBlood-based diagnostics and prognostics in sporadic Alzheimer's disease (AD) are important for identifying at-risk individuals for therapeutic interventions.MethodsIn three stages, a total of 34 leukocyte antigens were examined by flow cytometry immunophenotyping. Data were analyzed by logistic regression and receiver operating characteristic (ROC) analyses.ResultsWe identified leukocyte markers differentially expressed in the patients with AD. Pathway analysis revealed a complex network involving upregulation of complement inhibition and downregulation of cargo receptor activity and Aβ clearance. A proposed panel including four leukocyte markers - CD11c, CD59, CD91, and CD163 - predicts patients' PET Aβ status with an area under the curve (AUC) of 0.93 (0.88 to 0.97). CD163 was the top performer in preclinical models. These findings have been validated in two independent cohorts.ConclusionOur finding of changes on peripheral leukocyte surface antigens in AD implicates the deficit in innate immunity. Leukocyte-based biomarkers prove to be both sensitive and practical for AD screening and diagnosis.
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- 2023
4. Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering
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Yang, Zhijian, Wen, Junhao, Abdulkadir, Ahmed, Cui, Yuhan, Erus, Guray, Mamourian, Elizabeth, Melhem, Randa, Srinivasan, Dhivya, Govindarajan, Sindhuja T., Chen, Jiong, Habes, Mohamad, Masters, Colin L., Maruff, Paul, Fripp, Jurgen, Ferrucci, Luigi, Albert, Marilyn S., Johnson, Sterling C., Morris, John C., LaMontagne, Pamela, Marcus, Daniel S., Benzinger, Tammie L. S., Wolk, David A., Shen, Li, Bao, Jingxuan, Resnick, Susan M., Shou, Haochang, Nasrallah, Ilya M., and Davatzikos, Christos
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Quantitative Biology - Quantitative Methods ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first validate the generalizability, interpretability, and robustness of Gene-SGAN in semi-synthetic experiments. We then demonstrate its application to real multi-site datasets from 28,858 individuals, deriving subtypes of Alzheimer's disease and brain endophenotypes associated with hypertension, from MRI and SNP data. Derived brain phenotypes displayed significant differences in neuroanatomical patterns, genetic determinants, biological and clinical biomarkers, indicating potentially distinct underlying neuropathologic processes, genetic drivers, and susceptibility factors. Overall, Gene-SGAN is broadly applicable to disease subtyping and endophenotype discovery, and is herein tested on disease-related, genetically-driven neuroimaging phenotypes.
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- 2023
5. Increasing the Cognitive Screening Efficiency of Global Phase III Trials in Early Alzheimer Disease
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Doherty, Thomas, Gee, Michelle, Maruff, Paul, Smith, Robert, Murphy, Jennifer, Marsh, Julie, Koschalka, Luke, Martinez, Mairelys, Irizarry, Michael, and Albala, Bruce
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Biomedical and Clinical Sciences ,Biological Psychology ,Clinical Sciences ,Neurosciences ,Psychology ,Dementia ,Neurodegenerative ,Prevention ,Clinical Research ,Aging ,Clinical Trials and Supportive Activities ,Brain Disorders ,Acquired Cognitive Impairment ,Health Services ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Alzheimer's Disease ,Behavioral and Social Science ,Alzheimer Disease ,Clinical Trials ,Phase III as Topic ,Cognition ,Humans ,Mass Screening ,Alzheimer disease ,clinical trials ,screening ,cognitive testing ,elenbecestat ,Cognitive Sciences ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
PurposeA Cognitive Task Force (CTF) was established for the MissionAD program with the aim of reducing the screen failure (SF) rate to ∼30% and thereby reduce unnecessary subject burden, site burden, and excess trial costs.Methods/subjectsThe MissionAD program consisted of 2 global phase 3 studies evaluating the BACE inhibitor elenbecestat in subjects with early Alzheimer disease. The CTF monitored and engaged with MissionAD clinical sites to provide support through collegial discussions to maximize the efficiency of the preconsent recruitment phase.ResultsThe CTF significantly improved cognitive screening efficiency in the MissionAD program, with a 24% decline in cognitive SF rate for the sites that the CTF contacted. The study-wide 11.5% reduction in cognitive SF rates were likely further driven by wider country-level initiatives in which CTF members held CTF-specific Investigator meetings with the recruitment staff, speaking to all sites on a country level regardless of their recruitment performance.ConclusionsThe establishment of a CTF to support efficient cognitive screening is highly recommended for future Alzheimer disease studies. Additional benefits included improved site relationships, increased engagement in MissionAD and access to a group of cognitive experts for consulting, with a focus on achieving more efficient trial recruitment.
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- 2022
6. Cross-sectional associations between neighborhood characteristics, cognition and dementia risk factor burden in middle-aged and older Australians
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Cavuoto, Marina G., Davies, Liam, Rowsthorn, Ella, Cribb, Lachlan G., Yiallourou, Stephanie R., Yassi, Nawaf, Maruff, Paul, Lim, Yen Ying, and Pase, Matthew P.
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- 2024
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7. Alzheimer’s disease genetic risk and cognitive reserve in relationship to long-term cognitive trajectories among cognitively normal individuals
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Pettigrew, Corinne, Nazarovs, Jurijs, Soldan, Anja, Singh, Vikas, Wang, Jiangxia, Hohman, Timothy, Dumitrescu, Logan, Libby, Julia, Kunkle, Brian, Gross, Alden L., Johnson, Sterling, Lu, Qiongshi, Engelman, Corinne, Masters, Colin L., Maruff, Paul, Laws, Simon M., Morris, John C., Hassenstab, Jason, Cruchaga, Carlos, Resnick, Susan M., Kitner-Triolo, Melissa H., An, Yang, and Albert, Marilyn
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- 2023
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8. Monthly At-Home Computerized Cognitive Testing to Detect Diminished Practice Effects in Preclinical Alzheimer's Disease
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Jutten, Roos J, Rentz, Dorene M, Fu, Jessie F, Mayblyum, Danielle V, Amariglio, Rebecca E, Buckley, Rachel F, Properzi, Michael J, Maruff, Paul, Stark, Craig E, Yassa, Michael A, Johnson, Keith A, Sperling, Reisa A, and Papp, Kathryn V
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Biological Psychology ,Biomedical and Clinical Sciences ,Neurosciences ,Psychology ,Neurodegenerative ,Alzheimer's Disease ,Clinical Research ,Aging ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Acquired Cognitive Impairment ,Brain Disorders ,Dementia ,Neurological ,computerized testing ,remote assessment ,practice effects ,digital biomarkers ,preclinical AD ,Biochemistry and Cell Biology ,Cognitive Sciences ,Biological psychology - Abstract
Introduction: We investigated whether monthly assessments of a computerized cognitive composite (C3) could aid in the detection of differences in practice effects (PE) in clinically unimpaired (CU) older adults, and whether diminished PE were associated with Alzheimer's disease (AD) biomarkers and annual cognitive decline. Materials and Methods: N = 114 CU participants (age 77.6 ± 5.0, 61% female, MMSE 29 ± 1.2) from the Harvard Aging Brain Study completed the self-administered C3 monthly, at-home, on an iPad for one year. At baseline, participants underwent in-clinic Preclinical Alzheimer's Cognitive Composite-5 (PACC5) testing, and a subsample (n = 72, age = 77.8 ± 4.9, 59% female, MMSE 29 ± 1.3) had 1-year follow-up in-clinic PACC5 testing available. Participants had undergone PIB-PET imaging (0.99 ± 1.6 years before at-home baseline) and Flortaucipir PET imaging (n = 105, 0.62 ± 1.1 years before at-home baseline). Linear mixed models were used to investigate change over months on the C3 adjusting for age, sex, and years of education, and to extract individual covariate-adjusted slopes over the first 3 months. We investigated the association of 3-month C3 slopes with global amyloid burden and tau deposition in eight predefined regions of interest, and conducted Receiver Operating Characteristic analyses to examine how accurately 3-month C3 slopes could identify individuals that showed >0.10 SD annual decline on the PACC-5. Results: Overall, individuals improved on all C3 measures over 12 months (β = 0.23, 95% CI [0.21-0.25], p < 0.001), but improvement over the first 3 months was greatest (β = 0.68, 95% CI [0.59-0.77], p < 0.001), suggesting stronger PE over initial repeated exposures. However, lower PE over 3 months were associated with more global amyloid burden (r = -0.20, 95% CI [-0.38 - -0.01], p = 0.049) and tau deposition in the entorhinal cortex (r = -0.38, 95% CI [-0.54 - -0.19], p < 0.001) and inferior-temporal lobe (r = -0.23, 95% CI [-0.41 - -0.02], p = 0.03). 3-month C3 slopes exhibited good discriminative ability to identify PACC-5 decliners (AUC 0.91, 95% CI [0.84-0.98]), which was better than baseline C3 (p < 0.001) and baseline PACC-5 scores (p = 0.02). Conclusion: While PE are commonly observed among CU adults, diminished PE over monthly cognitive testing are associated with greater AD biomarker burden and cognitive decline. Our findings imply that unsupervised computerized testing using monthly retest paradigms can provide rapid detection of diminished PE indicative of future cognitive decline in preclinical AD.
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- 2022
9. A deep learning framework identifies dimensional representations of Alzheimer's Disease from brain structure.
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Yang, Zhijian, Nasrallah, Ilya M, Shou, Haochang, Wen, Junhao, Doshi, Jimit, Habes, Mohamad, Erus, Guray, Abdulkadir, Ahmed, Resnick, Susan M, Albert, Marilyn S, Maruff, Paul, Fripp, Jurgen, Morris, John C, Wolk, David A, Davatzikos, Christos, iSTAGING Consortium, Baltimore Longitudinal Study of Aging (BLSA), and Alzheimer’s Disease Neuroimaging Initiative (ADNI)
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iSTAGING Consortium ,Baltimore Longitudinal Study of Aging ,Alzheimer’s Disease Neuroimaging Initiative ,Brain ,Humans ,Alzheimer Disease ,Magnetic Resonance Imaging ,Cluster Analysis ,Case-Control Studies ,Longitudinal Studies ,Image Processing ,Computer-Assisted ,Aged ,Aged ,80 and over ,Middle Aged ,Female ,Male ,Neuroimaging ,Healthy Volunteers ,Cognitive Dysfunction ,Deep Learning ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Acquired Cognitive Impairment ,Biomedical Imaging ,Brain Disorders ,Alzheimer's Disease ,Dementia ,Clinical Research ,Aging ,Neurosciences ,Neurodegenerative ,Detection ,screening and diagnosis ,4.1 Discovery and preclinical testing of markers and technologies ,Neurological ,Good Health and Well Being - Abstract
Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a semi-supervised deep-clustering method, which examines neuroanatomical heterogeneity contrasted against normal brain structure, to identify disease subtypes through neuroimaging signatures. When applied to regional volumes derived from T1-weighted MRI (two studies; 2,832 participants; 8,146 scans) including cognitively normal individuals and those with cognitive impairment and dementia, Smile-GAN identified four patterns or axes of neurodegeneration. Applying this framework to longitudinal data revealed two distinct progression pathways. Measures of expression of these patterns predicted the pathway and rate of future neurodegeneration. Pattern expression offered complementary performance to amyloid/tau in predicting clinical progression. These deep-learning derived biomarkers offer potential for precision diagnostics and targeted clinical trial recruitment.
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- 2021
10. Medical Image Harmonization Using Deep Learning Based Canonical Mapping: Toward Robust and Generalizable Learning in Imaging
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Bashyam, Vishnu M., Doshi, Jimit, Erus, Guray, Srinivasan, Dhivya, Abdulkadir, Ahmed, Habes, Mohamad, Fan, Yong, Masters, Colin L., Maruff, Paul, Zhuo, Chuanjun, Völzke, Henry, Johnson, Sterling C., Fripp, Jurgen, Koutsouleris, Nikolaos, Satterthwaite, Theodore D., Wolf, Daniel H., Gur, Raquel E., Gur, Ruben C., Morris, John C., Albert, Marilyn S., Grabe, Hans J., Resnick, Susan M., Bryan, R. Nick, Wolk, David A., Shou, Haochang, Nasrallah, Ilya M., and Davatzikos, Christos
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Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Conventional and deep learning-based methods have shown great potential in the medical imaging domain, as means for deriving diagnostic, prognostic, and predictive biomarkers, and by contributing to precision medicine. However, these methods have yet to see widespread clinical adoption, in part due to limited generalization performance across various imaging devices, acquisition protocols, and patient populations. In this work, we propose a new paradigm in which data from a diverse range of acquisition conditions are "harmonized" to a common reference domain, where accurate model learning and prediction can take place. By learning an unsupervised image to image canonical mapping from diverse datasets to a reference domain using generative deep learning models, we aim to reduce confounding data variation while preserving semantic information, thereby rendering the learning task easier in the reference domain. We test this approach on two example problems, namely MRI-based brain age prediction and classification of schizophrenia, leveraging pooled cohorts of neuroimaging MRI data spanning 9 sites and 9701 subjects. Our results indicate a substantial improvement in these tasks in out-of-sample data, even when training is restricted to a single site.
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- 2020
11. Phase 1 randomized study on the safety, tolerability, and pharmacodynamic cognitive and electrophysiological effects of a dopamine D1 receptor positive allosteric modulator in patients with schizophrenia
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Desai, Amit, Benner, Lauren, Wu, Ruishan, Gertsik, Lev, Maruff, Paul, Light, Gregory A, Uz, Tolga, Marek, Gerard J, and Zhu, Tong
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Biological Psychology ,Pharmacology and Pharmaceutical Sciences ,Biomedical and Clinical Sciences ,Psychology ,Mind and Body ,Brain Disorders ,Schizophrenia ,Patient Safety ,Clinical Research ,Serious Mental Illness ,Mental Health ,Behavioral and Social Science ,Clinical Trials and Supportive Activities ,Neurosciences ,Evaluation of treatments and therapeutic interventions ,6.1 Pharmaceuticals ,Mental health ,Cognition ,Dopamine ,Humans ,Psychotic Disorders ,Receptors ,Dopamine ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Psychiatry ,Biological psychology - Abstract
ASP4345, a novel dopamine D1 receptor positive allosteric modulator, is being evaluated for the treatment of cognitive impairment associated with schizophrenia (CIAS). This phase 1 multiple ascending-dose study (NCT02720263) assessed the safety, tolerability, and pharmacodynamics of ASP4345 in patients with schizophrenia/schizoaffective disorder. Pharmacodynamic assessments were Cogstate cognitive tests and electrophysiological biomarkers, including gamma-band power and phase synchronization in response to 40-Hz auditory steady-state stimulation, as well as mismatch negativity (MMN) and P3a event-related potentials. The sample size determination was based on standard practice in assessing safety and tolerability of a new chemical entity. Data were summarized by conversion of this data into effect sizes using descriptive and inferential statistics. A total of 36 randomized patients received ASP4345 (3, 15, 50, and 150 mg; n = 9 each dose) and 12 patients received placebo. Patients in the ASP4345 group experienced 73 treatment-emergent adverse events (TEAEs) and 34 TEAEs were reported for the placebo group. The most common TEAEs were headache and somnolence and nearly all TEAEs were mild in severity. No changes in mood or self-reports of suicidal ideation/behavior were observed. Improvements in performance on cognitive tests were noted, which suggests a potential improvement in psychomotor function and visual attention. Furthermore, positive changes in neurophysiological biomarkers (auditory steady-state response [ASSR] and MMN) suggest improvement in information processing. The findings need to be confirmed in studies with a larger patient population. Nonetheless, the trends in safety and pharmacodynamic data support further clinical development of ASP4345 for the treatment of CIAS.
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- 2021
12. Pilot Evaluation of the Unsupervised, At-Home Cogstate Brief Battery in ADNI-2
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Edgar, Chris J, Siemers, Eric, Maruff, Paul, Petersen, Ronald C, Aisen, Paul S, Weiner, Michael W, Albala, Bruce, and Initiative, for the Alzheimer’s Disease Neuroimaging
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Biomedical and Clinical Sciences ,Biological Psychology ,Clinical Sciences ,Neurosciences ,Psychology ,Behavioral and Social Science ,Brain Disorders ,Aging ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Acquired Cognitive Impairment ,Dementia ,Neurodegenerative ,Alzheimer's Disease ,Neurological ,Aged ,Cognitive Dysfunction ,Female ,Humans ,Male ,Neuroimaging ,Neuropsychological Tests ,Pilot Projects ,Telemedicine ,Alzheimer's disease ,clinical trials as a topic ,cognition ,digital technology ,healthcare research ,Alzheimer’s Disease Neuroimaging Initiative ,Alzheimer’s disease ,Cognitive Sciences ,Neurology & Neurosurgery ,Clinical sciences ,Biological psychology - Abstract
BackgroundThere is a need for feasible, scalable assessments to detect cognitive impairment and decline. The Cogstate Brief Battery (CBB) is validated for Alzheimer's disease (AD) and in unsupervised and bring your own device contexts. The CBB has shown usability for self-completion in the home but has not been employed in this way in a multisite clinical trial in AD.ObjectiveThe objective of the pilot was to evaluate feasibility of at-home, self-completion of the CBB in the Alzheimer's Disease Neuroimaging Initiative (ADNI) over 24 months.MethodsThe CBB was included as a pilot for cognitively normal (CN) and mild cognitive impairment (MCI) participants in ADNI-2, invited to take the assessment in-clinic, then at at-home over a period of 24 months follow-up. Data were analyzed to explore acceptability/usability, concordance of in-clinic and at-home assessment, and validity.ResultsData were collected for 104 participants (46 CN, 51 MCI, and 7 AD) who consented to provide CBB data. Subsequent analyses were performed for the CN and MCI groups only. Test completion rates were 100%for both the first in-clinic supervised and first at-home unsupervised assessments, with few repeat performances required. However, available follow-up data declined sharply over time. Good concordance was seen between in-clinic and at-home assessments, with non-significant and small effect size differences (Cohen's d between -0.04 and 0.28) and generally moderate correlations (r = 0.42 to 0.73). Known groups validity was also supported (11/16 comparisons with Cohen's d≥0.3).ConclusionThese data demonstrate the feasibility of use for the CBB for unsupervised at-home, testing, including MCI groups. Optimal approaches to the application of assessments to support compliance over time remain to be determined.
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- 2021
13. 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
14. The Brain Chart of Aging: Machine‐learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans
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Habes, Mohamad, Pomponio, Raymond, Shou, Haochang, Doshi, Jimit, Mamourian, Elizabeth, Erus, Guray, Nasrallah, Ilya, Launer, Lenore J, Rashid, Tanweer, Bilgel, Murat, Fan, Yong, Toledo, Jon B, Yaffe, Kristine, Sotiras, Aristeidis, Srinivasan, Dhivya, Espeland, Mark, Masters, Colin, Maruff, Paul, Fripp, Jurgen, Völzk, Henry, Johnson, Sterling C, Morris, John C, Albert, Marilyn S, Miller, Michael I, Bryan, R Nick, Grabe, Hans J, Resnick, Susan M, Wolk, David A, Davatzikos, Christos, and for the iSTAGING consortium, the Preclinical AD consortium
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Biological Psychology ,Psychology ,Biomedical Imaging ,Aging ,Neurosciences ,Alzheimer's Disease ,Dementia ,Clinical Research ,Acquired Cognitive Impairment ,Brain Disorders ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Neurodegenerative ,Aetiology ,2.1 Biological and endogenous factors ,Mental health ,Neurological ,Adult ,Aged ,Aged ,80 and over ,Amyloid beta-Peptides ,Atrophy ,Biomarkers ,Brain ,Cerebral Small Vessel Diseases ,Cognitive Dysfunction ,Disease Progression ,Female ,Humans ,Image Processing ,Computer-Assisted ,Machine Learning ,Magnetic Resonance Imaging ,Male ,Middle Aged ,Neuropsychological Tests ,White Matter ,Young Adult ,Alzheimer's disease pathology ,beta-amyloid ,brain aging ,brain signatures ,cognitive testing ,harmonized neuroimaging cohorts ,MRI ,Neuroimaging ,PET ,preclinical Alzheimer's disease ,small vessel ischemic disease ,tau ,iSTAGING consortium ,the Preclinical AD consortium ,the ADNI ,and the CARDIA studies ,Clinical Sciences ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
IntroductionRelationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging database (11 studies; 10,216 subjects).MethodsThree brain signatures were calculated: Brain-age, AD-like neurodegeneration, and white matter hyperintensities (WMHs). Brain Charts measured and displayed the relationships of these signatures to cognition and molecular biomarkers of AD.ResultsWMHs were associated with advanced brain aging, AD-like atrophy, poorer cognition, and AD neuropathology in mild cognitive impairment (MCI)/AD and cognitively normal (CN) subjects. High WMH volume was associated with brain aging and cognitive decline occurring in an ≈10-year period in CN subjects. WMHs were associated with doubling the likelihood of amyloid beta (Aβ) positivity after age 65. Brain aging, AD-like atrophy, and WMHs were better predictors of cognition than chronological age in MCI/AD.DiscussionA Brain Chart quantifying brain-aging trajectories was established, enabling the systematic evaluation of individuals' brain-aging patterns relative to this large consortium.
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- 2021
15. Machine learning approaches to predicting amyloid status using data from an online research and recruitment registry: The Brain Health Registry
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Albright, Jack, Ashford, Miriam T, Jin, Chengshi, Neuhaus, John, Rabinovici, Gil D, Truran, Diana, Maruff, Paul, Mackin, R Scott, Nosheny, Rachel L, and Weiner, Michael W
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Biological Psychology ,Psychology ,Neurosciences ,Brain Disorders ,Clinical Research ,Genetics ,Biological psychology - Abstract
IntroductionThis study investigated the extent to which subjective and objective data from an online registry can be analyzed using machine learning methodologies to predict the current brain amyloid beta (Aβ) status of registry participants.MethodsWe developed and optimized machine learning models using data from up to 664 registry participants. Models were assessed on their ability to predict Aβ positivity using the results of positron emission tomography as ground truth.ResultsStudy partner-assessed Everyday Cognition score was preferentially selected for inclusion in the models by a feature selection algorithm during optimization.DiscussionOur results suggest that inclusion of study partner assessments would increase the ability of machine learning models to predict Aβ positivity.
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- 2021
16. Validation of online functional measures in cognitively impaired older adults
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Nosheny, Rachel L, Camacho, Monica R, Jin, Chengshi, Neuhaus, John, Truran, Diana, Flenniken, Derek, Ashford, Miriam, Carrillo, Maria C, Fargo, Keith N, Hendrix, James, Hanna, Lucy, Rabinovici, Gil, Maruff, Paul, Mackin, R Scott, and Weiner, Michael W
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Biological Psychology ,Psychology ,Neurosciences ,Aging ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Clinical Research ,Dementia ,Acquired Cognitive Impairment ,Brain Disorders ,Behavioral and Social Science ,Alzheimer's Disease ,Neurodegenerative ,Prevention ,Detection ,screening and diagnosis ,4.2 Evaluation of markers and technologies ,Neurological ,Aged ,Aged ,80 and over ,Cognitive Dysfunction ,Female ,Humans ,Male ,Neuropsychological Tests ,Online Systems ,activities of daily living ,amyloid beta ,dementia ,functional decline ,internet-based registry ,mild cognitive impairment ,study partner ,subjective cognitive decline ,Clinical Sciences ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
IntroductionAssessment of functional status is associated with risk of cognitive decline and diagnosis of dementia, and can be assessed by participants and study partners (SPs).MethodsIn 770 older adults enrolled in the Imaging Dementia-Evidence for Amyloid Scanning (IDEAS) study and the online Brain Health Registry (BHR), we estimated associations between online assessments and clinical variables related to Alzheimer's disease (AD) risk.ResultsWorse online learning scores and SP-reported functional decline were associated with higher probability of AD dementia diagnosis and poor in-clinic cognitive assessment, and with higher odds of amyloid beta (Aβ) positivity when combined with participants' report of less decline. SP report of functional decline conferred predictive value independent of online cognitive assessments. Participants underreported decline compared to SPs.DiscussionThe results support the validity of online assessments and their greater utilization in healthcare and research settings. Online SP-reported functional decline is an indicator of dementia and AD risk.
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- 2020
17. 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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18. Determining clinically meaningful decline in preclinical Alzheimer disease
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Insel, Philip S, Weiner, Michael, Mackin, R Scott, Mormino, Elizabeth, Lim, Yen Ying, Stomrud, Erik, Palmqvist, Sebastian, Masters, Colin L, Maruff, Paul T, Hansson, Oskar, and Mattsson, Niklas
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Biomedical and Clinical Sciences ,Neurosciences ,Clinical Sciences ,Clinical Trials and Supportive Activities ,Brain Disorders ,Dementia ,Aging ,Neurodegenerative ,Acquired Cognitive Impairment ,Alzheimer's Disease ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Clinical Research ,Neurological ,Aged ,Aged ,80 and over ,Alzheimer Disease ,Amyloid beta-Peptides ,Aniline Compounds ,Asymptomatic Diseases ,Benzothiazoles ,Brain ,Cognitive Dysfunction ,Contrast Media ,Disease Progression ,Ethylene Glycols ,Female ,Humans ,Male ,Mental Recall ,Mental Status and Dementia Tests ,Middle Aged ,Neuropsychological Tests ,Positron-Emission Tomography ,Thiazoles ,Time Factors ,Trail Making Test ,Cognitive Sciences ,Neurology & Neurosurgery ,Clinical sciences - Abstract
ObjectiveTo determine the time required for a preclinical Alzheimer disease population to decline in a meaningful way, use estimates of decline to update previous clinical trial design assumptions, and identify factors that modify β-amyloid (Aβ)-related decline.MethodsIn 1,120 cognitively unimpaired individuals from 3 international cohorts, we estimated the relationship between Aβ status and longitudinal changes across multiple cognitive domains and assessed interactions between Aβ and baseline factors. Power analyses were performed to explore sample size as a function of treatment effect.ResultsCognitively unimpaired Aβ+ participants approach mild cognitive impairment (MCI) levels of performance 6 years after baseline, on average. Achieving 80% power in a simulated 4-year treatment trial, assuming a 25% treatment effect, required 2,000 participants/group. Multiple factors interacted with Aβ to predict cognitive decline; however, these findings were all cohort-specific. Despite design differences across the cohorts, with large sample sizes and sufficient follow-up time, the Aβ+ groups declined consistently on cognitive composite measures.ConclusionsA preclinical AD population declines to the cognitive performance of an early MCI population in 6 years. Slowing this rate of decline by 40%-50% delays clinically relevant impairment by 3 years-a potentially meaningful treatment effect. However, assuming a 40%-50% drug effect highlights the difficulties in preclinical AD trial design, as a more commonly assumed treatment effect of 25% results in a required sample size of 2,000/group. Designers of preclinical AD treatment trials need to prepare for larger and longer trials than are currently being considered. Interactions with Aβ status were inconsistent and not readily generalizable.
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- 2019
19. Recommendations for the nomenclature of cognitive change associated with anaesthesia and surgery—2018
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Evered, L, Silbert, B, Knopman, DS, Scott, DA, DeKosky, ST, Rasmussen, LS, Oh, ES, Crosby, G, Berger, M, Eckenhoff, RG, Group, The Nomenclature Consensus Working, Evered, Lisbeth, Eckenhoff, Roderic G, Ames, David, Bekker, Alex, Berger, Miles, Blacker, Deborah, Browndyke, Jeffrey, Crosby, Greg, Deiner, Stacie G, van Dijk, Diederik, DeKosky, Steven T, Eckenhoff, Maryellen F, Eriksson, Lars, Galasko, Dougas, Hogan, Kirk, Inouye, Sharon, Knopman, David, Lyketsos, Constantine, Marcantonio, Edward, Maruff, Paul, Maze, Mervyn, Oh, Esther, Orser, Beverley A, Ottens, Thomas, Price, Catherine, Rasmussen, Lars S, Sachdev, Perminder, Schenning, Katie, Scott, David A, Seiber, Frederick E, Silbert, Brendan, Silverstein, Jeff, Steinmetz, Jacob, Terrando, Niccolo, Trzapacz, Paula, Whittington, Rob, and Xie, Zhongcong
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Biomedical and Clinical Sciences ,Clinical Sciences ,Acquired Cognitive Impairment ,Dementia ,Mental Health ,Behavioral and Social Science ,Clinical Research ,Brain Disorders ,Aging ,Neurosciences ,Mental health ,Anesthesia ,Cognition Disorders ,Diagnostic and Statistical Manual of Mental Disorders ,Emergence Delirium ,Humans ,Incidence ,Neuropsychological Tests ,Postoperative Complications ,Preexisting Condition Coverage ,Research Design ,Terminology as Topic ,Nomenclature Consensus Working Group ,cognition disorders ,delirium ,neurocognitive disorders ,postoperative complications ,Anesthesiology ,Clinical sciences - Abstract
Cognitive change affecting patients after anaesthesia and surgery has been recognised for more than 100 yr. Research into cognitive change after anaesthesia and surgery accelerated in the 1980s when multiple studies utilised detailed neuropsychological testing for assessment of cognitive change after cardiac surgery. This body of work consistently documented decline in cognitive function in elderly patients after anaesthesia and surgery, and cognitive changes have been identified up to 7.5 yr afterwards. Importantly, other studies have identified that the incidence of cognitive change is similar after non-cardiac surgery. Other than the inclusion of non-surgical control groups to calculate postoperative cognitive dysfunction, research into these cognitive changes in the perioperative period has been undertaken in isolation from cognitive studies in the general population. The aim of this work is to develop similar terminology to that used in cognitive classifications of the general population for use in investigations of cognitive changes after anaesthesia and surgery. A multispecialty working group followed a modified Delphi procedure with no prespecified number of rounds comprised of three face-to-face meetings followed by online editing of draft versions. Two major classification guidelines [Diagnostic and Statistical Manual for Mental Disorders, fifth edition (DSM-5) and National Institute for Aging and the Alzheimer Association (NIA-AA)] are used outside of anaesthesia and surgery, and may be useful for inclusion of biomarkers in research. For clinical purposes, it is recommended to use the DSM-5 nomenclature. The working group recommends that 'perioperative neurocognitive disorders' be used as an overarching term for cognitive impairment identified in the preoperative or postoperative period. This includes cognitive decline diagnosed before operation (described as neurocognitive disorder); any form of acute event (postoperative delirium) and cognitive decline diagnosed up to 30 days after the procedure (delayed neurocognitive recovery) and up to 12 months (postoperative neurocognitive disorder).
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- 2018
20. Within subject rise in serum TNFα to IL-10 ratio is associated with poorer attention, decision-making and working memory in jockeys
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Piantella, Stefan, O'Brien, William T., Hale, Matthew W., Maruff, Paul, McDonald, Stuart J., and Wright, Bradley J.
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- 2022
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21. Preclinical and randomized clinical evaluation of the p38α kinase inhibitor neflamapimod for basal forebrain cholinergic degeneration
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Jiang, Ying, Alam, John J., Gomperts, Stephen N., Maruff, Paul, Lemstra, Afina W., Germann, Ursula A., Stavrides, Philip H., Darji, Sandipkumar, Malampati, Sandeep, Peddy, James, Bleiwas, Cynthia, Pawlik, Monika, Pensalfini, Anna, Yang, Dun-Sheng, Subbanna, Shivakumar, Basavarajappa, Balapal S., Smiley, John F., Gardner, Amanda, Blackburn, Kelly, Chu, Hui-May, Prins, Niels D., Teunissen, Charlotte E., Harrison, John E., Scheltens, Philip, and Nixon, Ralph A.
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- 2022
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22. Clearance and transport of amyloid β by peripheral monocytes correlate with Alzheimer's disease progression.
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Huang, Xin, Fowler, Chris, Li, Yihan, Li, Qiao-Xin, Sun, Jiaqi, Pan, Yijun, Jin, Liang, Perez, Keyla A., Dubois, Céline, Lim, Yen Y., Drysdale, Candace, Rumble, Rebecca L., Chinnery, Holly R., Rowe, Christopher C., Martins, Ralph N., Maruff, Paul, Doecke, James D., Lin, Yong, Belaidi, Abdel A., and Barnham, Kevin J.
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PERIPHERAL circulation ,ALZHEIMER'S disease ,CEREBROSPINAL fluid ,MILD cognitive impairment ,CENTRAL nervous system ,CEREBROSPINAL fluid examination - Abstract
Impaired clearance of amyloid β (Aβ) in late-onset Alzheimer's disease (AD) affects disease progression. The role of peripheral monocytes in Aβ clearance from the central nervous system (CNS) is unclear. We use a flow cytometry assay to identify Aβ-binding monocytes in blood, validated by confocal microscopy, Western blotting, and mass spectrometry. Flow cytometry immunophenotyping and correlation with AD biomarkers are studied in 150 participants from the AIBL study. We also examine monocytes in human cerebrospinal fluid (CSF) and their migration in an APP/PS1 mouse model. The assay reveals macrophage-like Aβ-binding monocytes with high phagocytic potential in both the periphery and CNS. We find lower surface Aβ levels in mild cognitive impairment (MCI) and AD-dementia patients compared to cognitively unimpaired individuals. Monocyte infiltration from blood to CSF and migration from CNS to peripheral lymph nodes and blood are observed. Here we show that Aβ-binding monocytes may play a role in CNS Aβ clearance, suggesting their potential as a biomarker for AD diagnosis and monitoring. Impaired Aβ clearance in late-onset Alzheimer's disease (AD) affects progression. Here, the authors show that CD14 + CD16+ monocytes carry Aβ in peripheral circulation and CSF in AD, suggesting a role in Aβ clearance. [ABSTRACT FROM AUTHOR]
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- 2024
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23. Total Sleep Time Interacts With Age to Predict Cognitive Performance Among Adults.
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Mohlenhoff, Brian S, Insel, Philip S, Mackin, R Scott, Neylan, Thomas C, Flenniken, Derek, Nosheny, Rachel, Richards, Anne, Maruff, Paul, and Weiner, Michael W
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Neurodegenerative ,Clinical Research ,Basic Behavioral and Social Science ,Neurosciences ,Aging ,Sleep Research ,Dementia ,Alzheimer's Disease ,Acquired Cognitive Impairment ,Brain Disorders ,Behavioral and Social Science ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Aetiology ,2.3 Psychological ,social and economic factors ,2.1 Biological and endogenous factors ,Neurological ,Mental health ,Adult ,Age Factors ,Aged ,Cohort Studies ,Female ,Humans ,Male ,Memory Disorders ,Middle Aged ,Neuropsychological Tests ,Registries ,Risk Factors ,Self Report ,Sleep ,Sleep Wake Disorders ,Time Factors ,aging ,cognition ,internet ,sleep ,Clinical Sciences ,Other Medical and Health Sciences ,Psychology ,Neurology & Neurosurgery - Abstract
Study objectivesTo investigate interactions between high and low amounts of sleep and other predictors of cognitive performance.MethodsWe used four cognitive tests to determine whether sleep time interacted with age, personal history of a memory problem, parental history of a memory problem, or personal concerns about memory and were associated with cognitive performance. Data were collected from an internet-based cohort study. We used an ordinary least squares regression with restricted cubic splines, controlling for demographic variables and comorbidities.ResultsWe found significant nonlinear interactions between (1) total sleep time and age and (2) total sleep time and personal history of a memory problem and cognitive performance. Short and long sleep durations and self-reported memory complaints were associated with poorer performance on a test of attention and this was true to a greater degree in younger and older adults. A repeat analysis excluding subjects reporting dementia was significant only for the test of attention.ConclusionsThese results extend existing data on sleep duration and cognition across the lifespan by combining in a single study the results from four specific cognitive tests, both younger and older adults, and four self-reported risk factors for cognitive impairment. Longitudinal studies with biomarkers should be undertaken to determine whether causal mechanisms, such as inflammation or amyloid buildup, account for these associations.
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- 2018
24. Unsupervised online neuropsychological test performance for individuals with mild cognitive impairment and dementia: Results from the Brain Health Registry
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Mackin, R Scott, Insel, Philip S, Truran, Diana, Finley, Shannon, Flenniken, Derek, Nosheny, Rachel, Ulbright, Aaron, Comacho, Monica, Bickford, David, Harel, Brian, Maruff, Paul, and Weiner, Michael W
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Clinical and Health Psychology ,Psychology ,Dementia ,Acquired Cognitive Impairment ,Aging ,Alzheimer's Disease ,Brain Disorders ,Clinical Trials and Supportive Activities ,Neurosciences ,Clinical Research ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Neurodegenerative ,Behavioral and Social Science ,Neurological ,Mental health ,Attention ,Brain health registry ,Information-processing speed ,Internet ,Memory ,Mild cognitive impairment ,Online cognitive tests ,Research registry ,Genetics ,Biological psychology - Abstract
IntroductionThe purpose of this study is to compare online neuropsychological test performance of older adults across self-reported diagnoses of being cognitively normal, mild cognitive impairment, and dementia due to Alzheimer's disease and to determine the association of memory concerns and family history of dementia on cognitive performance.MethodsParticipants completed the Cogstate Brief Battery unsupervised at home.ResultsData from 6463 participants over the age of 55 years were analyzed. Adults with the diagnosis of mild cognitive impairment and Alzheimer's disease were associated with poorer performance on all cognitive tests than cognitively normal adults (P
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- 2018
25. Online study partner‐reported cognitive decline in the Brain Health Registry
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Nosheny, Rachel L, Camacho, Monica R, Insel, Philip S, Flenniken, Derek, Fockler, Juliet, Truran, Diana, Finley, Shannon, Ulbricht, Aaron, Maruff, Paul, Yaffe, Kristine, Mackin, R Scott, Weiner, Michael W, and Initiative, Alzheimer's Disease Neuroimaging
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Biological Psychology ,Psychology ,Neurosciences ,Acquired Cognitive Impairment ,Dementia ,Brain Disorders ,Aging ,Basic Behavioral and Social Science ,Behavioral and Social Science ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Clinical Research ,Neurodegenerative ,Alzheimer's Disease ,Mental health ,Neurological ,Activities of daily living ,Alzheimer's disease ,Brain Health Registry ,Cognitive decline ,Cognitive neuropsychology in dementia ,Informant-reported outcomes ,Mild cognitive impairment ,Neuropsychological tests ,Online registry ,Study partner-reported outcomes ,Clinical sciences ,Biological psychology - Abstract
IntroductionMethods for efficiently identifying cognitive decline and Alzheimer's disease (AD) are a critical unmet need. The goal of this work was to validate novel online study partner (SP)-reported outcomes to identify cognitive decline in older adults.MethodsIn older adults enrolled in the Brain Health Registry, we analyzed associations between SP-reported cognitive decline, measured by the Everyday Cognition Scale, and either (1) participant cognition, assessed by Cogstate Brief Battery or (2) participant-reported diagnosis of mild cognitive impairment or AD.ResultsWe found strong associations between SP-reported Everyday Cognition Scale and both Cogstate scores and participant diagnosis. The associations were cognitive domain specific, dependant on participant diagnosis, and were stronger in spouse dyads and those who knew each other longer.DiscussionCollecting SP-reported data online from a large cohort is feasible. Results support the construct validity of our approach, which has the potential to facilitate clinical AD and aging research.
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- 2018
26. Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan
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Pomponio, Raymond, Erus, Guray, Habes, Mohamad, Doshi, Jimit, Srinivasan, Dhivya, Mamourian, Elizabeth, Bashyam, Vishnu, Nasrallah, Ilya M., Satterthwaite, Theodore D., Fan, Yong, Launer, Lenore J., Masters, Colin L., Maruff, Paul, Zhuo, Chuanjun, Völzke, Henry, Johnson, Sterling C., Fripp, Jurgen, Koutsouleris, Nikolaos, Wolf, Daniel H., Gur, Raquel, Gur, Ruben, Morris, John, Albert, Marilyn S., Grabe, Hans J., Resnick, Susan M., Bryan, R. Nick, Wolk, David A., Shinohara, Russell T., Shou, Haochang, and Davatzikos, Christos
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- 2020
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27. Genomic loci influence patterns of structural covariance in the human brain
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Wen, Junhao, primary, Nasrallah, Ilya M., additional, Abdulkadir, Ahmed, additional, Satterthwaite, Theodore D., additional, Yang, Zhijian, additional, Erus, Guray, additional, Robert-Fitzgerald, Timothy, additional, Singh, Ashish, additional, Sotiras, Aristeidis, additional, Boquet-Pujadas, Aleix, additional, Mamourian, Elizabeth, additional, Doshi, Jimit, additional, Cui, Yuhan, additional, Srinivasan, Dhivya, additional, Skampardoni, Ioanna, additional, Chen, Jiong, additional, Hwang, Gyujoon, additional, Bergman, Mark, additional, Bao, Jingxuan, additional, Veturi, Yogasudha, additional, Zhou, Zhen, additional, Yang, Shu, additional, Dazzan, Paola, additional, Kahn, Rene S., additional, Schnack, Hugo G., additional, Zanetti, Marcus V., additional, Meisenzahl, Eva, additional, Busatto, Geraldo F., additional, Crespo-Facorro, Benedicto, additional, Pantelis, Christos, additional, Wood, Stephen J., additional, Zhuo, Chuanjun, additional, Shinohara, Russell T., additional, Gur, Ruben C., additional, Gur, Raquel E., additional, Koutsouleris, Nikolaos, additional, Wolf, Daniel H., additional, Saykin, Andrew J., additional, Ritchie, Marylyn D., additional, Shen, Li, additional, Thompson, Paul M., additional, Colliot, Olivier, additional, Wittfeld, Katharina, additional, Grabe, Hans J., additional, Tosun, Duygu, additional, Bilgel, Murat, additional, An, Yang, additional, Marcus, Daniel S., additional, LaMontagne, Pamela, additional, Heckbert, Susan R., additional, Austin, Thomas R., additional, Launer, Lenore J., additional, Espeland, Mark, additional, Masters, Colin L., additional, Maruff, Paul, additional, Fripp, Jurgen, additional, Johnson, Sterling C., additional, Morris, John C., additional, Albert, Marilyn S., additional, Bryan, R. Nick, additional, Resnick, Susan M., additional, Fan, Yong, additional, Habes, Mohamad, additional, Wolk, David, additional, Shou, Haochang, additional, and Davatzikos, Christos, additional
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- 2023
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28. Rates of age- and amyloid β-associated cortical atrophy in older adults with superior memory performance
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Chambers, Brian, Chiu, Edmond, Clarnette, Roger, Darby, David, Davison, Mary, Drago, John, Drysdale, Peter, Gilbert, Jacqueline, Lim, Kwang, Lautenschlager, Nicola, LoGiudice, Dina, McCardle, Peter, McFarlane, Steve, Mander, Alastair, Merory, John, O'Connor, Daniel, Scholes, Ron, Samuel, Mathew, Trivedi, Darshan, Woodward, Michael, Dang, Christa, Yassi, Nawaf, Harrington, Karra D., Xia, Ying, Lim, Yen Ying, Ames, David, Laws, Simon M., Hickey, Martha, Rainey-Smith, Stephanie, Sohrabi, Hamid R., Doecke, James D., Fripp, Jurgen, Salvado, Olivier, Snyder, Peter J., Weinborn, Michael, Villemagne, Victor L., Rowe, Christopher C., Masters, Colin L., and Maruff, Paul
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- 2019
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29. Acute cognitive effects of single-dose intravenous ketamine in major depressive and posttraumatic stress disorder
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Davis, Margaret T., DellaGiogia, Nicole, Maruff, Paul, Pietrzak, Robert H., and Esterlis, Irina
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- 2021
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30. 2014 Report on the Milestones for the US National Plan to Address Alzheimer's Disease
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Workgroup, Alzheimer's Association National Plan Milestone, Fargo, Keith N, Aisen, Paul, Albert, Marilyn, Au, Rhoda, Corrada, Maria M, DeKosky, Steven, Drachman, David, Fillit, Howard, Gitlin, Laura, Haas, Magali, Herrup, Karl, Kawas, Claudia, Khachaturian, Ara S, Khachaturian, Zaven S, Klunk, William, Knopman, David, Kukull, Walter A, Lamb, Bruce, Logsdon, Rebecca G, Maruff, Paul, Mesulam, Marsel, Mobley, William, Mohs, Richard, Morgan, David, Nixon, Ralph A, Paul, Steven, Petersen, Ronald, Plassman, Brenda, Potter, William, Reiman, Eric, Reisberg, Barry, Sano, Mary, Schindler, Rachel, Schneider, Lon S, Snyder, Peter J, Sperling, Reisa A, Yaffe, Kristine, Bain, Lisa J, Thies, William H, and Carrillo, Maria C
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Biomedical and Clinical Sciences ,Biological Psychology ,Clinical Sciences ,Neurosciences ,Psychology ,Acquired Cognitive Impairment ,Prevention ,Neurodegenerative ,Alzheimer's Disease ,Brain Disorders ,Aging ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Dementia ,Neurological ,Alzheimer Disease ,Animals ,Biological Ontologies ,Biomarkers ,Drug Discovery ,Health Policy ,Humans ,Patient Selection ,Public-Private Sector Partnerships ,Translational Research ,Biomedical ,United States ,United States Dept. of Health and Human Services ,Voluntary Health Agencies ,Policy ,National Plan to Address Alzheimer's Disease ,Milestones ,Alzheimer's Association National Plan Milestone Workgroup ,Geriatrics ,Clinical sciences ,Biological psychology - Abstract
With increasing numbers of people with Alzheimer's and other dementias across the globe, many countries have developed national plans to deal with the resulting challenges. In the United States, the National Alzheimer's Project Act, signed into law in 2011, required the creation of such a plan with annual updates thereafter. Pursuant to this, the US Department of Health and Human Services (HHS) released the National Plan to Address Alzheimer's Disease in 2012, including an ambitious research goal of preventing and effectively treating Alzheimer's disease by 2025. To guide investments, activities, and the measurement of progress toward achieving this 2025 goal, in its first annual plan update (2013) HHS also incorporated into the plan a set of short, medium and long-term milestones. HHS further committed to updating these milestones on an ongoing basis to account for progress and setbacks, and emerging opportunities and obstacles. To assist HHS as it updates these milestones, the Alzheimer's Association convened a National Plan Milestone Workgroup consisting of scientific experts representing all areas of Alzheimer's and dementia research. The workgroup evaluated each milestone and made recommendations to ensure that they collectively constitute an adequate work plan for reaching the goal of preventing and effectively treating Alzheimer's by 2025. This report presents these Workgroup recommendations.
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- 2014
31. 2014 Report on the Milestones for the US National Plan to Address Alzheimer's Disease.
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Alzheimer's Association National Plan Milestone Workgroup, Fargo, Keith N, Aisen, Paul, Albert, Marilyn, Au, Rhoda, Corrada, Maria M, DeKosky, Steven, Drachman, David, Fillit, Howard, Gitlin, Laura, Haas, Magali, Herrup, Karl, Kawas, Claudia, Khachaturian, Ara S, Khachaturian, Zaven S, Klunk, William, Knopman, David, Kukull, Walter A, Lamb, Bruce, Logsdon, Rebecca G, Maruff, Paul, Mesulam, Marsel, Mobley, William, Mohs, Richard, Morgan, David, Nixon, Ralph A, Paul, Steven, Petersen, Ronald, Plassman, Brenda, Potter, William, Reiman, Eric, Reisberg, Barry, Sano, Mary, Schindler, Rachel, Schneider, Lon S, Snyder, Peter J, Sperling, Reisa A, Yaffe, Kristine, Bain, Lisa J, Thies, William H, and Carrillo, Maria C
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Alzheimer's Association National Plan Milestone Workgroup ,Animals ,Humans ,Alzheimer Disease ,Patient Selection ,United States Dept. of Health and Human Services ,Health Policy ,Voluntary Health Agencies ,United States ,Drug Discovery ,Public-Private Sector Partnerships ,Translational Medical Research ,Biological Ontologies ,Biomarkers ,Milestones ,National Plan to Address Alzheimer's Disease ,Policy ,Neurodegenerative ,Acquired Cognitive Impairment ,Neurosciences ,Alzheimer's Disease ,Prevention ,Aging ,Dementia ,Brain Disorders ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,Neurological ,Geriatrics ,Clinical Sciences - Abstract
With increasing numbers of people with Alzheimer's and other dementias across the globe, many countries have developed national plans to deal with the resulting challenges. In the United States, the National Alzheimer's Project Act, signed into law in 2011, required the creation of such a plan with annual updates thereafter. Pursuant to this, the US Department of Health and Human Services (HHS) released the National Plan to Address Alzheimer's Disease in 2012, including an ambitious research goal of preventing and effectively treating Alzheimer's disease by 2025. To guide investments, activities, and the measurement of progress toward achieving this 2025 goal, in its first annual plan update (2013) HHS also incorporated into the plan a set of short, medium and long-term milestones. HHS further committed to updating these milestones on an ongoing basis to account for progress and setbacks, and emerging opportunities and obstacles. To assist HHS as it updates these milestones, the Alzheimer's Association convened a National Plan Milestone Workgroup consisting of scientific experts representing all areas of Alzheimer's and dementia research. The workgroup evaluated each milestone and made recommendations to ensure that they collectively constitute an adequate work plan for reaching the goal of preventing and effectively treating Alzheimer's by 2025. This report presents these Workgroup recommendations.
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- 2014
32. Suboptimal self‐reported sleep efficiency and duration are associated with faster accumulation of brain amyloid beta in cognitively unimpaired older adults.
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Pivac, Louise N., Brown, Belinda M., Sewell, Kelsey R., Doecke, James D., Villemagne, Victor L., Doré, Vincent, Weinborn, Michael, Sohrabi, Hamid R., Gardener, Samantha L., Bucks, Romola S., Laws, Simon M., Taddei, Kevin, Maruff, Paul, Masters, Colin L., Rowe, Christopher, Martins, Ralph N., and Rainey‐Smith, Stephanie R.
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SLEEP duration ,OLDER people ,AMYLOID ,SLEEP quality ,APOLIPOPROTEIN E ,MIND-wandering ,SLEEP - Abstract
INTRODUCTION: This study investigated whether self‐reported sleep quality is associated with brain amyloid beta (Aβ) accumulation. METHODS: Linear mixed effect model analyses were conducted for 189 cognitively unimpaired (CU) older adults (mean ± standard deviation 74.0 ± 6.2; 53.2% female), with baseline self‐reported sleep data, and positron emission tomography‐determined brain Aβ measured over a minimum of three time points (range 33.3–72.7 months). Analyses included random slopes and intercepts, interaction for apolipoprotein E (APOE) ε4 allele status, and time, adjusting for sex and baseline age. RESULTS: Sleep duration <6 hours, in APOE ε4 carriers, and sleep efficiency <65%, in the whole sample and APOE ε4 non‐carriers, is associated with faster accumulation of brain Aβ. DISCUSSION: These findings suggest a role for self‐reported suboptimal sleep efficiency and duration in the accumulation of Alzheimer's disease (AD) neuropathology in CU individuals. Additionally, poor sleep efficiency represents a potential route via which individuals at lower genetic risk may progress to preclinical AD. Highlights: In cognitively unimpaired older adults self‐report sleep is associated with brain amyloid beta (Aβ) accumulation.Across sleep characteristics, this relationship differs by apolipoprotein E (APOE) genotype.Sleep duration <6 hours is associated with faster brain Aβ accumulation in APOE ε4 carriers.Sleep efficiency < 65% is associated with faster brain Aβ accumulation in APOE ε4 non‐carriers.Personalized sleep interventions should be studied for potential to slow Aβ accumulation. [ABSTRACT FROM AUTHOR]
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- 2024
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33. Physical activity and brain amyloid beta: A longitudinal analysis of cognitively unimpaired older adults.
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Slee, Michael G., Rainey‐Smith, Stephanie R., Villemagne, Victor L., Doecke, James D., Sohrabi, Hamid R., Taddei, Kevin, Ames, David, Dore, Vincent, Maruff, Paul, Laws, Simon M., Masters, Colin L., Rowe, Christopher C., Martins, Ralph N., Erickson, Kirk I., and Brown, Belinda M.
- Abstract
INTRODUCTION: The current study evaluated the relationship between habitual physical activity (PA) levels and brain amyloid beta (Aβ) over 15 years in a cohort of cognitively unimpaired older adults. METHODS: PA and Aβ measures were collected over multiple timepoints from 731 cognitively unimpaired older adults participating in the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study of Aging. Regression modeling examined cross‐sectional and longitudinal relationships between PA and brain Aβ. Moderation analyses examined apolipoprotein E (APOE) ε4 carriage impact on the PA‐Aβ relationship. RESULTS: PA was not associated with brain Aβ at baseline (β = –0.001, p = 0.72) or over time (β = –0.26, p = 0.24). APOE ε4 status did not moderate the PA‐Aβ relationship over time (β = 0.12, p = 0.73). Brain Aβ levels did not predict PA trajectory (β = –54.26, p = 0.59). DISCUSSION: Our study did not identify a relationship between habitual PA and brain Aβ levels. Highlights: Physical activity levels did not predict brain amyloid beta (Aβ) levels over time in cognitively unimpaired older adults (≥60 years of age).Apolipoprotein E (APOE) ε4 carrier status did not moderate the physical activity–brain Aβ relationship over time.Physical activity trajectories were not impacted by brain Aβ levels. [ABSTRACT FROM AUTHOR]
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- 2024
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34. Similar neurocognitive outcomes after 48 weeks in HIV-1-infected participants randomized to continue tenofovir/emtricitabine + atazanavir/ritonavir or simplify to abacavir/lamivudine + atazanavir
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Robertson, Kevin, Maruff, Paul, Ross, Lisa L., Wohl, David, Small, Catherine B, Edelstein, Howard, and Shaefer, Mark S.
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- 2019
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35. A randomized, exploratory molecular imaging study targeting amyloid β with a novel 8-OH quinoline in Alzheimer's disease: The PBT2-204 IMAGINE study
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Villemagne, Victor L., Rowe, Christopher C., Barnham, Kevin J., Cherny, Robert, Woodward, Michael, Bozinosvski, Svetlana, Salvado, Olivier, Bourgeat, Pierrick, Perez, Keyla, Fowler, Christopher, Rembach, Alan, Maruff, Paul, Ritchie, Craig, Tanzi, Rudy, and Masters, Colin L.
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- 2017
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36. Amyloid β–associated cognitive decline in the absence of clinical disease progression and systemic illness
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Harrington, Karra D., Lim, Yen Ying, Ames, David, Hassenstab, Jason, Laws, Simon M., Martins, Ralph N., Rainey-Smith, Stephanie, Robertson, Joanne, Rowe, Christopher C., Salvado, Olivier, Doré, Vincent, Villemagne, Victor L., Snyder, Peter J., Masters, Colin L., and Maruff, Paul
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- 2017
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37. A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium
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Gross, Alden L., Hassenstab, Jason J., Johnson, Sterling C., Clark, Lindsay R., Resnick, Susan M., Kitner-Triolo, Melissa, Masters, Colin L., Maruff, Paul, Morris, John C., Soldan, Anja, Pettigrew, Corinne, and Albert, Marilyn S.
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- 2017
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38. Cognitive impairment and decline in cognitively normal older adults with high amyloid-β: A meta-analysis
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Baker, Jenalle E., Lim, Yen Ying, Pietrzak, Robert H., Hassenstab, Jason, Snyder, Peter J., Masters, Colin L., and Maruff, Paul
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- 2017
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39. Evaluation of the effect of Cooled HaEmodialysis on Cognitive function in patients suffering with end-stage KidnEy Disease (E-CHECKED): feasibility randomised control trial protocol
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Dasgupta, Indranil, Odudu, Aghogho, Baharani, Jyoti, Fergusson, Niall, Griffiths, Helen, Harrison, John, Maruff, Paul, Thomas, G Neil, Woodhall, Gavin, Youseff, Samir, and Tadros, George
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- 2020
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40. Development of a new virtual reality test of cognition: assessing the test-retest reliability, convergent and ecological validity of CONVIRT
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Horan, Ben, Heckenberg, Rachael, Maruff, Paul, and Wright, Bradley
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- 2020
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41. Disruption of cholinergic neurotransmission, within a cognitive challenge paradigm, is indicative of Aβ-related cognitive impairment in preclinical Alzheimer’s disease after a 27-month delay interval
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Alber, Jessica, Maruff, Paul, Santos, Cláudia Y., Ott, Brian R., Salloway, Stephen P., Yoo, Don C., Noto, Richard B., Thompson, Louisa I., Goldfarb, Danielle, Arthur, Edmund, Song, Alex, and Snyder, Peter J.
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- 2020
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42. Effects of Hearing Aid Use on Cognition in Older Adults
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Sarant, Julia, Harris, David, Busby, Peter, Maruff, Paul, Schembri, Adrian, Lemke, Ulrike, and Launer, Stefan
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- 2020
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43. Physical activity and brain amyloid beta: A longitudinal analysis of cognitively unimpaired older adults
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Slee, Michael G., Rainey-Smith, Stephanie R., Villemagne, Victor L., Doecke, James D., Sohrabi, Hamid R., Taddei, Kevin, Ames, David, Dore, Vincent, Maruff, Paul, Laws, Simon M., Masters, Colin L., Rowe, Christopher C., Martins, Ralph N., Erickson, Kirk I., Brown, Belinda M., Slee, Michael G., Rainey-Smith, Stephanie R., Villemagne, Victor L., Doecke, James D., Sohrabi, Hamid R., Taddei, Kevin, Ames, David, Dore, Vincent, Maruff, Paul, Laws, Simon M., Masters, Colin L., Rowe, Christopher C., Martins, Ralph N., Erickson, Kirk I., and Brown, Belinda M.
- Abstract
Introduction: The current study evaluated the relationship between habitual physical activity (PA) levels and brain amyloid beta (A ) over 15 years in a cohort of cognitively unimpaired older adults. Methods: PA and A measures were collected over multiple timepoints from 731 cognitively unimpaired older adults participating in the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study of Aging. Regression modeling examined cross-sectional and longitudinal relationships between PA and brain A . Moderation analyses examined apolipoprotein E (APOE) 4 carriage impact on the PA-A relationship. Results: PA was not associated with brain A at baseline ( = –0.001, p = 0.72) or over time ( = –0.26, p = 0.24). APOE 4 status did not moderate the PA-A relationship over time ( = 0.12, p = 0.73). Brain A levels did not predict PA trajectory ( = –54.26, p = 0.59). Discussion: Our study did not identify a relationship between habitual PA and brain A levels. Highlights: Physical activity levels did not predict brain amyloid beta (A ) levels over time in cognitively unimpaired older adults ( ≥ 60 years of age). Apolipoprotein E (APOE) 4 carrier status did not moderate the physical activity–brain A relationship over time. Physical activity trajectories were not impacted by brain A levels.
- Published
- 2023
44. Development of complex executive function over childhood : Longitudinal growth curve modeling of performance on the Groton Maze Learning Task
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McGuckian, Thomas B., Wilson, Peter H., Johnston, Rich D., Rahimi-Golkhandan, Shahin, Piek, Jan, Green, Dido, Rogers, Jeffrey M., Maruff, Paul, Steenbergen, Bert, Ruddock, Scott, McGuckian, Thomas B., Wilson, Peter H., Johnston, Rich D., Rahimi-Golkhandan, Shahin, Piek, Jan, Green, Dido, Rogers, Jeffrey M., Maruff, Paul, Steenbergen, Bert, and Ruddock, Scott
- Abstract
This longitudinal study modeled children's complex executive function (EF) development using the Groton Maze Learning Task (GMLT). Using a cohort-sequential design, 147 children (61 males, 5.5–11 years) were recruited from six multicultural primary schools in Melbourne and Perth, Australia. Race/ethnicity data were not available. Children were assessed on the GMLT at 6-month intervals over 2-years between 2010 and 2012. Growth curve models describe age-related change from 5.5 to 12.5 years old. Results showed a quadratic growth trajectory on each measure of error—that is, those that reflect visuospatial memory, executive control (or the ability to apply rules for action), and complex EF. The ability to apply rules for action, while a rate-limiting factor in complex EF, develops rapidly over early-to-mid childhood.
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- 2023
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45. Nonvascular retinal imaging markers of preclinical Alzheimer's disease
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Snyder, Peter J., Johnson, Lenworth N., Lim, Yen Ying, Santos, Cláudia Y., Alber, Jessica, Maruff, Paul, and Fernández, Brian
- Published
- 2016
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46. Sensitivity of composite scores to amyloid burden in preclinical Alzheimer's disease: Introducing the Z-scores of Attention, Verbal fluency, and Episodic memory for Nondemented older adults composite score
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Lim, Yen Ying, Snyder, Peter J., Pietrzak, Robert H., Ukiqi, Albulene, Villemagne, Victor L., Ames, David, Salvado, Olivier, Bourgeat, Pierrick, Martins, Ralph N., Masters, Colin L., Rowe, Christopher C., and Maruff, Paul
- Published
- 2016
- Full Text
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47. Brain aging patterns in a large and diverse cohort of 49,482 individuals
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Yang, Zhijian, Wen, Junhao, Erus, Guray, Govindarajan, Sindhuja T., Melhem, Randa, Mamourian, Elizabeth, Cui, Yuhan, Srinivasan, Dhivya, Abdulkadir, Ahmed, Parmpi, Paraskevi, Wittfeld, Katharina, Grabe, Hans J., Bülow, Robin, Frenzel, Stefan, Tosun, Duygu, Bilgel, Murat, An, Yang, Yi, Dahyun, Marcus, Daniel S., LaMontagne, Pamela, Benzinger, Tammie L. S., Heckbert, Susan R., Austin, Thomas R., Waldstein, Shari R., Evans, Michele K., Zonderman, Alan B., Launer, Lenore J., Sotiras, Aristeidis, Espeland, Mark A., Masters, Colin L., Maruff, Paul, Fripp, Jurgen, Toga, Arthur W., O’Bryant, Sid, Chakravarty, Mallar M., Villeneuve, Sylvia, Johnson, Sterling C., Morris, John C., Albert, Marilyn S., Yaffe, Kristine, Völzke, Henry, Ferrucci, Luigi, Nick Bryan, R., Shinohara, Russell T., Fan, Yong, Habes, Mohamad, Lalousis, Paris Alexandros, Koutsouleris, Nikolaos, Wolk, David A., Resnick, Susan M., Shou, Haochang, Nasrallah, Ilya M., and Davatzikos, Christos
- Abstract
Brain aging process is influenced by various lifestyle, environmental and genetic factors, as well as by age-related and often coexisting pathologies. Magnetic resonance imaging and artificial intelligence methods have been instrumental in understanding neuroanatomical changes that occur during aging. Large, diverse population studies enable identifying comprehensive and representative brain change patterns resulting from distinct but overlapping pathological and biological factors, revealing intersections and heterogeneity in affected brain regions and clinical phenotypes. Herein, we leverage a state-of-the-art deep-representation learning method, Surreal-GAN, and present methodological advances and extensive experimental results elucidating brain aging heterogeneity in a cohort of 49,482 individuals from 11 studies. Five dominant patterns of brain atrophy were identified and quantified for each individual by respective measures, R-indices. Their associations with biomedical, lifestyle and genetic factors provide insights into the etiology of observed variances, suggesting their potential as brain endophenotypes for genetic and lifestyle risks. Furthermore, baseline R-indices predict disease progression and mortality, capturing early changes as supplementary prognostic markers. These R-indices establish a dimensional approach to measuring aging trajectories and related brain changes. They hold promise for precise diagnostics, especially at preclinical stages, facilitating personalized patient management and targeted clinical trial recruitment based on specific brain endophenotypic expression and prognosis.
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- 2024
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48. Indigenous traumatic brain injury research: responding to recruitment challenges in the hospital environment
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Fitts, Michelle S., Condon, Taeha, Gilroy, John, Bird, Katrina, Bleakley, Erica, Matheson, Lauren, Fleming, Jennifer, Clough, Alan R., Esterman, Adrian, Maruff, Paul, and Bohanna, India
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- 2019
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49. Clinical and Blood Biomarker Trajectories after Concussion: New Insights from a Longitudinal Pilot Study of Professional Flat-Track Jockeys
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McDonald, Stuart J., primary, Piantella, Stefan, additional, O'Brien, William T., additional, Hale, Matthew W., additional, O'Halloran, Paul, additional, Kinsella, Glynda, additional, Horan, Ben, additional, O'Brien, Terence J, additional, Maruff, Paul, additional, Shultz, Sandy R., additional, and Wright, Bradley J., additional
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- 2023
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50. Incidence of emergency department presentations for traumatic brain injury in Indigenous and non-Indigenous residents aged 15–64 over the 9-year period 2007–2015 in North Queensland, Australia
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Esterman, Adrian, Thompson, Fintan, Fitts, Michelle, Gilroy, John, Fleming, Jennifer, Maruff, Paul, Clough, Alan, and Bohanna, India
- Published
- 2018
- Full Text
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