Anatomy and Neuroscience - Research Publications

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    BDNF VAL66MET polymorphism and memory decline across the spectrum of Alzheimer's disease
    Lim, YY ; Laws, SM ; Perin, S ; Pietrzak, RH ; Fowler, C ; Masters, CL ; Maruff, P (WILEY, 2021-06)
    The brain-derived neurotrophic factor (BDNF) Val66Met (rs6265) polymorphism has been shown to moderate the extent to which memory decline manifests in preclinical Alzheimer's disease (AD). To date, no study has examined the relationship between BDNF and memory in individuals across biologically confirmed AD clinical stages (i.e., Aβ+). We aimed to understand the effect of BDNF on episodic memory decline and clinical disease progression over 126 months in individuals with preclinical, prodromal and clinical AD. Participants enrolled in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study who were Aβ + (according to positron emission tomography), and cognitively normal (CN; n = 238), classified as having mild cognitive impairment (MCI; n = 80), or AD (n = 66) were included in this study. Cognition was evaluated at 18 month intervals using an established episodic memory composite score over 126 months. We observed that in Aβ + CNs, Met66 was associated with greater memory decline with increasing age and were 1.5 times more likely to progress to MCI/AD over 126 months. In Aβ + MCIs, there was no effect of Met66 on memory decline or on disease progression to AD over 126 months. In Aβ + AD, Val66 homozygotes showed greater memory decline, while Met66 carriers performed at a constant and very impaired level. Our current results illustrate the importance of time and disease severity to clinicopathological models of the role of BDNF Val66Met in memory decline and AD clinical progression. Specifically, the effect of BDNF on memory decline is greatest in preclinical AD and reduces as AD clinical disease severity increases.
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    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
    Habes, M ; Pomponio, R ; Shou, H ; Doshi, J ; Mamourian, E ; Erus, G ; Nasrallah, I ; Launer, LJ ; Rashid, T ; Bilgel, M ; Fan, Y ; Toledo, JB ; Yaffe, K ; Sotiras, A ; Srinivasan, D ; Espeland, M ; Masters, C ; Maruff, P ; Fripp, J ; Volzk, H ; Johnson, SC ; Morris, JC ; Albert, MS ; Miller, M ; Bryan, RN ; Grabe, HJ ; Resnick, SM ; Wolk, DA ; Davatzikos, C (WILEY, 2021-01)
    INTRODUCTION: Relationships 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). METHODS: Three 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. RESULTS: WMHs 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. DISCUSSION: A 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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    Plasma p-tau181/Aβ1-42 ratio predicts Aβ-PET status and correlates with CSF-p-tau181/Aβ1-42 and future cognitive decline
    Fowler, CJ ; Stoops, E ; Rainey-Smith, SR ; Vanmechelen, E ; Vanbrabant, J ; Dewit, N ; Mauroo, K ; Maruff, P ; Rowe, CC ; Fripp, J ; Li, Q-X ; Bourgeat, P ; Collins, SJ ; Martins, RN ; Masters, CL ; Doecke, JD (WILEY, 2022)
    BACKGROUND: In Alzheimer's disease (AD), plasma amyloid beta (Aβ)1-42 and phosphorylated tau (p-tau) predict high amyloid status from Aβ positron emission tomography (PET); however, the extent to which combination of these plasma assays can predict remains unknown. METHODS: Prototype Simoa assays were used to measure plasma samples from participants who were either cognitively normal (CN) or had mild cognitive impairment (MCI)/AD in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. RESULTS: The p-tau181/Aβ1-42 ratio showed the best prediction of Aβ-PET across all participants (area under the curve [AUC] = 0.905, 95% confidence interval [CI]: 0.86-0.95) and in CN (AUC = 0.873; 0.80-0.94), and symptomatic (AUC = 0.908; 0.82-1.00) adults. Plasma p-tau181/Aβ1-42 ratio correlated with cerebrospinal fluid (CSF) p-tau181 (Elecsys, Spearman's ρ = 0.74, P < 0.0001) and predicted abnormal CSF Aβ (AUC = 0.816; 0.74-0.89). The p-tau181/Aβ1-42 ratio also predicted future rates of cognitive decline assessed by AIBL Preclinical Alzheimer Cognitive Composite or Clinical Dementia Rating Sum of Boxes (P < 0.0001). DISCUSSION: Plasma p-tau181/Aβ1-42 ratio predicted both Aβ-PET status and cognitive decline, demonstrating potential as both a diagnostic aid and as a screening and prognostic assay for preclinical AD trials.
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    Association of Elevated Amyloid and Tau Positron Emission Tomography Signal With Near-Term Development of Alzheimer Disease Symptoms in Older Adults Without Cognitive Impairment
    Strikwerda-Brown, C ; Hobbs, DA ; Gonneaud, J ; St-Onge, F ; Binette, AP ; Ozlen, H ; Provost, K ; Soucy, J-P ; Buckley, RF ; Benzinger, TLS ; Morris, JC ; Villemagne, VL ; Dore, V ; Sperling, RA ; Johnson, KA ; Rowe, CC ; Gordon, BA ; Poirier, J ; Breitner, JCS ; Villeneuve, S (AMER MEDICAL ASSOC, 2022-10)
    IMPORTANCE: National Institute on Aging-Alzheimer's Association (NIA-AA) workgroups have proposed biological research criteria intended to identify individuals with preclinical Alzheimer disease (AD). OBJECTIVE: To assess the clinical value of these biological criteria to identify older individuals without cognitive impairment who are at near-term risk of developing symptomatic AD. DESIGN, SETTING, AND PARTICIPANTS: This longitudinal cohort study used data from 4 independent population-based cohorts (PREVENT-AD, HABS, AIBL, and Knight ADRC) collected between 2003 and 2021. Participants were older adults without cognitive impairment with 1 year or more of clinical observation after amyloid β and tau positron emission tomography (PET). Median clinical follow-up after PET ranged from 1.94 to 3.66 years. EXPOSURES: Based on binary assessment of global amyloid burden (A) and a composite temporal region of tau PET uptake (T), participants were stratified into 4 groups (A+T+, A+T-, A-T+, A-T-). Presence (+) or absence (-) of neurodegeneration (N) was assessed using temporal cortical thickness. MAIN OUTCOMES AND MEASURES: Each cohort was analyzed separately. Primary outcome was clinical progression to mild cognitive impairment (MCI), identified by a Clinical Dementia Rating score of 0.5 or greater in Knight ADRC and by consensus committee review in the other cohorts. Clinical raters were blind to imaging, genetic, and fluid biomarker data. A secondary outcome was cognitive decline, based on a slope greater than 1.5 SD below the mean of an independent subsample of individuals without cognitive impairment. Outcomes were compared across the biomarker groups. RESULTS: Among 580 participants (PREVENT-AD, 128; HABS, 153; AIBL, 48; Knight ADRC, 251), mean (SD) age ranged from 67 (5) to 76 (6) years across cohorts, with between 55% (137/251) and 74% (95/128) female participants. Across cohorts, 33% to 83% of A+T+ participants progressed to MCI during follow-up (mean progression time, 2-2.72 years), compared with less than 20% of participants in other biomarker groups. Progression further increased to 43% to 100% when restricted to A+T+(N+) individuals. Cox proportional hazard ratios for progression to MCI in the A+T+ group vs other biomarker groups were all 5 or greater. Many A+T+ nonprogressors also showed longitudinal cognitive decline, while cognitive trajectories in other groups remained predominantly stable. CONCLUSIONS AND RELEVANCE: The clinical prognostic value of NIA-AA research criteria was confirmed in 4 independent cohorts, with most A+T+(N+) older individuals without cognitive impairment developing AD symptoms within 2 to 3 years.
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    Visually Identified Tau 18F-MK6240 PET Patterns in Symptomatic Alzheimer's Disease
    Krishnadas, N ; Huang, K ; Schultz, SA ; Dore, V ; Bourgeat, P ; Goh, AMY ; Lamb, F ; Bozinovski, S ; Burnham, SC ; Robertson, JS ; Laws, SM ; Maruff, P ; Masters, CL ; Villemagne, VL ; Rowe, CC ; Jacobs, H (IOS PRESS, 2022)
    BACKGROUND: In Alzheimer's disease, heterogeneity has been observed in the postmortem distribution of tau neurofibrillary tangles. Visualizing the topography of tau in vivo may facilitate clinical trials and clinical practice. OBJECTIVE: This study aimed to investigate whether tau distribution patterns that are limited to mesial temporal lobe (MTL)/limbic regions, and those that spare MTL regions, can be visually identified using 18F-MK6240, and whether these patterns are associated with different demographic and cognitive profiles. METHODS: Tau 18F-MK6240 PET images of 151 amyloid-β positive participants with mild cognitive impairment (MCI) and dementia were visually rated as: tau negative, limbic predominant (LP), MTL-sparing, and Typical by two readers. Groups were evaluated for differences in age, APOE ɛ4 carriage, hippocampal volumes, and cognition (MMSE, composite memory and non-memory scores). Voxel-wise contrasts were also performed. RESULTS: Visual rating resulted in 59.6% classified as Typical, 17.9% as MTL-sparing, 9.9% LP, and 12.6% as tau negative. Intra-rater and inter-rater reliability was strong (Cohen's kappa values of 0.89 and 0.86 respectively). Tracer retention in a "hook"-like distribution on sagittal sequences was observed in the LP and Typical groups. The visually classified MTL-sparing group had lower APOE ɛ4 carriage and relatively preserved hippocampal volumes. Higher MTL tau was associated with greater amnestic cognitive impairment. High cortical tau was associated with greater impairments on non-memory domains of cognition, and individuals with high cortical tau were more likely to have dementia than MCI. CONCLUSION: Tau distribution patterns can be visually identified using 18F-MK6240 PET and are associated with differences in APOE ɛ4 carriage, hippocampal volumes, and cognition.
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    Identification of Leukocyte Surface P2X7 as a Biomarker Associated with Alzheimer's Disease
    Li, Y ; Huang, X ; Fowler, C ; Lim, YY ; Laws, SM ; Faux, N ; Doecke, JD ; Trounson, B ; Pertile, K ; Rumble, R ; Dore, V ; Villemagne, VL ; Rowe, CC ; Wiley, JS ; Maruff, P ; Masters, CL ; Gu, BJ (MDPI, 2022-07)
    Alzheimer's disease (AD) has shown altered immune responses in the periphery. We studied P2X7 (a proinflammatory receptor and a scavenger receptor) and two integrins, CD11b and CD11c, on the surface of circulating leukocytes and analysed their associations with Aβ-PET, brain atrophy, neuropsychological assessments, and cerebrospinal fluid (CSF) biomarkers. Total 287 age-matched, sex-balanced participants were recruited in a discovery cohort and two validation cohorts through the AIBL study and studied using tri-colour flow cytometry. Our results demonstrated reduced expressions of P2X7, CD11b, and CD11c on leukocytes, particularly monocytes, in Aβ +ve cases compared with Aβ -ve controls. P2X7 and integrin downregulation was observed at pre-clinical stage of AD and stayed low throughout disease course. We further constructed a polygenic risk score (PRS) model based on 12 P2RX7 risk alleles to assess the genetic impact on P2X7 function in AIBL and ADNI cohorts. No significant association was identified between the P2RX7 gene and AD, indicating that P2X7 downregulation in AD is likely caused by environmental changes rather than genetic factors. In conclusion, the downregulation of P2X7 and integrins at pre-clinical stage of AD indicates altered pro-inflammatory responses, phagocytic functions, and migrating capabilities of circulating monocytes in early AD pathogenesis. Our study not only improves our understanding of peripheral immune involvement in early stage of AD but also provides more insights into novel biomarker development, diagnosis, and prognosis of AD.
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    No Influence of Age-Related Hearing Loss on Brain Amyloid-β
    Sarant, JZ ; Harris, DC ; Busby, PA ; Fowler, C ; Fripp, J ; Masters, CL ; Maruff, P ; Bendlin, B (IOS PRESS, 2022)
    BACKGROUND: Hearing loss is independently associated with a faster rate of cognitive decline in older adults and has been identified as a modifiable risk factor for dementia. The mechanism for this association is unknown, and there has been limited exploration of potential casual pathology. OBJECTIVE: Our objective was to investigate whether there was an association between degree of audiometrically measured hearing loss (HL) and brain amyloid-β (Aβ) in a pre-clinical sample. METHODS: Participants of the Australian Imaging and Biomarker Longitudinal Study (AIBL; n = 143) underwent positron emission tomography (PET) imaging and objective measurement of hearing thresholds within 5 years of imaging, as well as cognitive assessment within 2 years of imaging in this observational cohort study. RESULTS: With one exception, study participants who had cognitive assessments within 2 years of their PET imaging (n = 113) were classified as having normal cognition. There was no association between cognitive scores and degree of hearing loss, or between cognitive scores and Aβ load. No association between HL and Aβ load was found once age was controlled for. As previously reported, positive Apolipoprotein E4 (APOE4) carrier status increased the risk of being Aβ positive (p = 0.002). CONCLUSION: Degree of HL was not associated with positive Aβ status.
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    A deep learning framework identifies dimensional representations of Alzheimer's Disease from brain structure
    Yang, Z ; Nasrallah, IM ; Shou, H ; Wen, J ; Doshi, J ; Habes, M ; Erus, G ; Abdulkadir, A ; Resnick, SM ; Albert, MS ; Maruff, P ; Fripp, J ; Morris, JC ; Wolk, DA ; Davatzikos, C (NATURE PORTFOLIO, 2021-12-03)
    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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    Higher Coffee Consumption Is Associated With Slower Cognitive Decline and Less Cerebral Aβ-Amyloid Accumulation Over 126 Months: Data From the Australian Imaging, Biomarkers, and Lifestyle Study
    Gardener, SL ; Rainey-Smith, SR ; Villemagne, VL ; Fripp, J ; Dore, V ; Bourgeat, P ; Taddei, K ; Fowler, C ; Masters, CL ; Maruff, P ; Rowe, CC ; Ames, D ; Martins, RN ; AIBL, I (FRONTIERS MEDIA SA, 2021-11-19)
    Background: Worldwide, coffee is one of the most popular beverages consumed. Several studies have suggested a protective role of coffee, including reduced risk of Alzheimer's disease (AD). However, there is limited longitudinal data from cohorts of older adults reporting associations of coffee intake with cognitive decline, in distinct domains, and investigating the neuropathological mechanisms underpinning any such associations. Methods: The aim of the current study was to investigate the relationship between self-reported habitual coffee intake, and cognitive decline assessed using a comprehensive neuropsychological battery in 227 cognitively normal older adults from the Australian Imaging, Biomarkers, and Lifestyle (AIBL) study, over 126 months. In a subset of individuals, we also investigated the relationship between habitual coffee intake and cerebral Aβ-amyloid accumulation (n = 60) and brain volumes (n = 51) over 126 months. Results: Higher baseline coffee consumption was associated with slower cognitive decline in executive function, attention, and the AIBL Preclinical AD Cognitive Composite (PACC; shown reliably to measure the first signs of cognitive decline in at-risk cognitively normal populations), and lower likelihood of transitioning to mild cognitive impairment or AD status, over 126 months. Higher baseline coffee consumption was also associated with slower Aβ-amyloid accumulation over 126 months, and lower risk of progressing to "moderate," "high," or "very high" Aβ-amyloid burden status over the same time-period. There were no associations between coffee intake and atrophy in total gray matter, white matter, or hippocampal volume. Discussion: Our results further support the hypothesis that coffee intake may be a protective factor against AD, with increased coffee consumption potentially reducing cognitive decline by slowing cerebral Aβ-amyloid accumulation, and thus attenuating the associated neurotoxicity from Aβ-amyloid-mediated oxidative stress and inflammatory processes. Further investigation is required to evaluate whether coffee intake could be incorporated as a modifiable lifestyle factor aimed at delaying AD onset.
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    Using imputation to provide harmonized longitudinal measures of cognition across AIBL and ADNI
    Shishegar, R ; Cox, T ; Rolls, D ; Bourgeat, P ; Dore, V ; Lamb, F ; Robertson, J ; Laws, SM ; Porter, T ; Fripp, J ; Tosun, D ; Maruff, P ; Savage, G ; Rowe, CC ; Masters, CL ; Weiner, MW ; Villemagne, VL ; Burnham, SC (NATURE PORTFOLIO, 2021-12-10)
    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 < 0.001) for clinical classification to measured data in the other dataset. Further, the increased power of the overall harmonised dataset was demonstrated by observing a significant association between CVLT-II test scores (imputed for ADNI) with PET Amyloid-β in MCI APOE-ε4 homozygotes in the imputed data (N = 65) but not for the original AIBL dataset (N = 11). These results suggest that MissForest can provide a practical solution for data harmonization using imputation across studies to improve power for more nuanced analyses.