Medicine (Austin & Northern Health) - Research Publications

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    Alzheimer’s disease specific MRI brain regions are differentially associated with accelerated decline as defined using sigmoidal cognitive turning point methodology in amyloid‐positive AIBL participants
    Gillis, C ; Cespedes, MI ; Maserejian, NN ; Dore, V ; Maruff, P ; Fowler, C ; Rainey‐Smith, S ; Villemagne, VL ; Rowe, C ; Martins, RN ; Vacher, M ; Masters, CL ; Doecke, JD (Wiley, 2022-12)
    Background Variability in cognitive decline among adults with Alzheimer’s disease (AD) is seen across studies. While such variability is often modelled using linear models, in the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, application of a sigmoidal methodology has shown excellent precision in modelling cognitive and biomarker changes. Here we expand these findings by examining associations of brain volumes in AD specific Regions of Interest (ROIs) with accelerated cognitive decline among amyloid‐beta positive (Ab+) AIBL participants. Method Longitudinal cognitive scores for the AIBL PACC, Language, Visuospatial functioning and CDR‐SB were mapped to sigmoidal trajectories, with a threshold defining the inflection point of accelerated cognitive decline. Participants to the left of the threshold were classified as having non‐accelerated decline (non‐accelerators), and participants beyond the threshold were classed as accelerators (Figure 1B). Using these classifications, we investigated differences in 16 ICV corrected ROI (left and right hemispheres pooled) for reductions in brain volume via generalised linear models adjusted for age, gender, and APOE‐e4 status. Three participant subgroups were tested: 1) Ab+/Tau unknown, 2) Ab+/Tau‐ and 3) Ab+/Tau+. Significant t‐values for the summed ROI volumes were mapped on a standard brain mesh for visualisation. Result Of regions tested, two stood out consistently amongst top markers in each of the participant subgroups and cognitive outcomes: 1) supramarginal volume and 2) middle temporal volume (Figure 1C). Largest volume differences between accelerators and non‐accelerators were seen in the Ab+/Tau+ group; whilst smallest p‐values were in the Ab+/Tau unknown group due to a larger sample size (Table 1). Brain mesh visualization showed most of the AD signature ROIs altered in accelerator groups as compared with non‐accelerator groups. Figure 1D shows the AD signature for each cognitive outcome amongst the Ab+/Tau participant group. Top ranked ROI for the left being middle temporal volume (T=7.10, PACC) and supramarginal volume (T=7.10, CDR‐SB). Conclusion Sigmoid analyses of MRI using binary cognitive scores show decreased ROI volumes in AIBL Ab+ participants with accelerated cognitive decline. This effect was mediated by known information on Tauopathy. Whilst effect sizes were high, smaller sample sizes in some groups affected p‐values and should therefore be replicated in larger samples.
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    Higher coffee consumption is associated with slower cognitive decline and Aβ‐amyloid accumulation over 126 months: Data from the AIBL study
    Gardener, SL ; Rainey‐Smith, SR ; Villemagne, VLL ; Fripp, J ; Dore, V ; Bourgeat, P ; Taddei, K ; Masters, CL ; Maruff, PT ; Rowe, CC ; Ames, D ; Martins, RN (Wiley, 2021-12)
    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 available in cohorts of older adults reporting associations of coffee intake with cognitive decline, in distinct domains, and investigating the neuropathological mechanisms underpinning these associations. Method The aim of the current study was to investigate the relationship between self‐reported baseline coffee intake (mean = 280 ± 323 g/day) and cognitive decline assessed using a comprehensive neuropsychological battery, over 126 months, in 227 cognitively normal individuals from the Australian Imaging, Biomarkers, and Lifestyle (AIBL) study. We also sought to investigate the relationship between coffee intake and cerebral Aβ‐amyloid accumulation and brain volumes in a subset of individuals (n=60; and n=51, respectively) over 126 months. Result Higher baseline coffee consumption was associated with slower cognitive decline in executive function, attention, and the AIBL Preclinical AD Cognitive Composite (PACC; shown to reliably measure the first signs of cognitive decline in at‐risk cognitively normal populations) over 126 months. Higher baseline coffee consumption was also associated with slower Aβ‐amyloid accumulation over 126 months, and lower risk of transitioning from ‘negative’ Aβ‐amyloid status to ‘moderate’, and ‘very high’ Aβ‐amyloid burden over the same time period. There were no associations between coffee intake and atrophy in total grey matter, white matter, or hippocampal volume. Conclusion Our results further support the hypothesis that coffee intake may be a protective factor against AD, with increased coffee consumption reducing cognitive decline potentially 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 how coffee intake could be incorporated as one modifiable lifestyle factor aimed at delaying AD onset.
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    How lifestyle shapes the brain: Associations between physical activity, sleep, beta‐amyloid and cognitive function in older adults
    Sewell, KR ; Rainey‐Smith, SR ; Villemagne, VLL ; Peiffer, JJ ; Sohrabi, HR ; Taddei, K ; Ames, D ; Maruff, PT ; Laws, SM ; Masters, CL ; Rowe, CC ; Martins, RN ; Erickson, KI ; Brown, BM (Wiley, 2021-12)
    Abstract Background Lifestyle factors such as sleep and physical activity influence risk of cognitive decline and dementia. Higher habitual physical activity and optimal sleep are associated with better cognitive function and lower levels of Alzheimer’s disease biomarkers, including beta‐amyloid (Aß). There is currently a poor understanding of how physical activity may influence the relationship between sleep and cognition, and whether exercise and sleep interact to influence cognition and Aß. Developing this understanding is crucial for creating effective lifestyle interventions for dementia prevention. Method Data from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were utilised to determine whether self‐reported physical activity moderates the cross‐sectional relationship between self‐reported sleep parameters (duration, efficiency, latency, disturbance, quality), cognitive function (episodic memory, attention and processing speed, executive function), and brain Aß (quantified by amyloid positron emission tomography, using the Centiloid scale). Analyses were adjusted for age, sex, APOE ε4 carriage, mood, premorbid intelligence, and collection point. Participants were 404 community‐dwelling cognitively normal older adults aged 60 and above (75.3 5.7 years). Data from a subset of participants (n = 220, aged 75.2 5.6 years) were used for analyses with AB as the outcome. Result Physical activity moderated the relationship between sleep duration and episodic memory (ß = ‐.09, SE = .03, p = .005), and sleep efficiency and episodic memory (ß = ‐.08, SE = .03, p = .016). Physical activity moderated the relationship between sleep duration and A® (ß = ‐.12, SE = .06, p = .036), and sleep quality and Aß (ß = .12, SE = .06, p = .029). Conclusion Physical activity may play an important role in the relationship between sleep and cognitive function, and sleep and brain Aß. Future longitudinal and intervention studies in this area are crucial for informing interventions for dementia prevention.
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    Empirically derived composite cognitive test scores to predict preclinical and clinical stages of Alzheimer’s disease
    Shishegar, R ; Chai, TY ; Cox, T ; Lamb, F ; Robertson, JS ; Laws, SM ; Porter, T ; Fripp, J ; Doecke, JD ; Tosun‐Turgut, D ; Maruff, PT ; Savage, G ; Rowe, CC ; Masters, CL ; Weiner, MW ; Villemagne, VLL ; Burnham, SC (Wiley, 2021-12)
    Abstract Background Alzheimer’s disease (AD) clinical trials require cognitive test scores that assess change in cognitive function accurately. Here, we propose new composite cognitive test scores to detect earlier stages of AD accurately by using the full neuropsychological testing battery (in ADNI) and a manifold learning dimension reduction technique namely UMAP. Method Data for this study included N=1585 ADNI participants ([492 cognitively normal (CN), 804 mild cognitively impaired (MCI), 289 AD; aged 73.8±7.1; 708 females]; Table 1). Subjects with 3 or more follow‐up sessions were included. Cognitive test scores with more than 60% missing data were excluded. Missing data within included test scores were imputed using the MissForest algorithm. A linear mixed model using all follow‐up data was applied to calculate the random slope (rate of change) and random intercept for each cognitive score and for each subject. The scores and demographic measurements: age, gender, years of education and APOE‐ɛ4 status were used to inform the UMAP. Levels for the output variable were defined as: 1) stable CN, 2) CN who progressed to MCI or probable dementia due to AD, 3) stable MCI, 4) MCI who progressed to dementia AD and 5) dementia due to AD. The model calculated two composite scores. These cognitive stages were predicted using Support Vector Machine (SVM) analysis of both the new composite scores and the traditional clinical rating measures of Clinical Dementia Rating (CDR) and Mini‐Mental State Examination (MMSE). Result Predicting cognitive stages using the proposed composite scores show a highly significant improvement with a 0.981 accuracy and 0.976 reliability (evaluated by Cohen's kappa coefficient), compared to using the combination of CDR and MMSE scores covaried for demographics, which had 0.660 accuracy and 0.567 reliability. Individuals’ clinical and preclinical stages with regards to UMAP two‐dimensional embedding and the clinical rating measures, CDR and MMSE, are presented in Figure 1. Table 2 reports the importance of the test measures on the UMAP components used in AD staging predictions. Conclusion The results here suggest that the proposed empirically derived composite cognitive test scores provides a practical solution to differentiate cognitive stages with a high accuracy and reliability.
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    Unpacking cognitive composites: A longitudinal analysis
    Cox, T ; Shishegar, R ; Lim, YY ; Robertson, J ; Lamb, F ; Laws, SM ; Porter, T ; Fripp, J ; Doecke, JD ; Maruff, PT ; Savage, G ; Rowe, CC ; Masters, CL ; Villemagne, VL ; Burnham, SC (Wiley, 2021-12)
    Abstract Background The development of cognitive endpoints that can accurately assess changes in cognition over short time frames is crucial for clinical trials and research of Alzheimer’s disease (AD). Understanding the changing influence of contributing test scores on composites throughout the disease course provides the opportunity to optimise cognitive composite scores for different stages of AD. Method AIBL participants with declining cognitive performance were included in this study N=1275 [688 cognitively unimpaired (CU), 277 mild cognitively impaired (MCI), 310 AD; aged 73±9; 718 females]). Two cognitive composite scores (Episodic Memory (EM) and PACC) and their component test scores (California Verbal Learning Test‐II Delayed Recall (CVLT‐II DR), Logical Memory Delayed Recall (LMII), Rey Complex Figure Test 30 minute delayed recall (RCFT‐DR) and CVLT‐II DR, LMII, Digit Symbol Substitution Test (DS), MMSE, respectively) were evaluated. We first examined the relationship between each of component tests score for each composite. We then compared the extent to which longitudinal trajectories of each component test score and each cognitive composite score differed at each disease stage. Result CVLT‐II DR contributed the most to the EM composite followed by RCFT‐DR and LMII with the influence remaining unchanged across each disease stage. For PACC, CVLT‐II DR contributed the most to the initial decline, with MMSE and LMII contributing similar amounts and DS contributing the least. CVLT‐II DR contributed substantially to changes in PACC earlier in the disease course but MMSE drove the PACC change in later stages of disease. Initially, both composites follow similar longitudinal trajectories. However, the EM composite reaches a floor not observed for the PACC. Conclusion Understanding the temporal contribution of component tests scores on cognitive composites could provide improved cognitive endpoints tailored to use. For instance, MMSE is sensitive to change later in the disease trajectory and therefore should be included in a composite endpoint for trials in prodromal or clinical AD, however is unlikely to have value for preclinical AD trials.
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    Leukocyte surface biomarkers implicate deficits of innate immunity in sporadic Alzheimer's disease
    Huang, X ; Li, Y ; Fowler, C ; Doecke, JD ; Lim, YY ; Drysdale, C ; Zhang, V ; Park, K ; Trounson, B ; Pertile, K ; Rumble, R ; Pickering, JW ; Rissman, RA ; Sarsoza, F ; Abdel-Latif, S ; Lin, Y ; Dore, V ; Villemagne, V ; Rowe, CC ; Fripp, J ; Martins, R ; Wiley, JS ; Maruff, P ; Mintzer, JE ; Masters, CL ; Gu, BJ (WILEY, 2023-05)
    INTRODUCTION: Blood-based diagnostics and prognostics in sporadic Alzheimer's disease (AD) are important for identifying at-risk individuals for therapeutic interventions. METHODS: In 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. RESULTS: We 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. CONCLUSION: Our 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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    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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    Trajectories of depressive and anxiety symptoms in older adults: a 6-year prospective cohort study
    Holmes, SE ; Esterlis, I ; Mazure, CM ; Lim, YY ; Ames, D ; Rainey-Smith, S ; Fowler, C ; Ellis, K ; Martins, RN ; Salvado, O ; Dore, V ; Villemagne, VL ; Rowe, CC ; Laws, SM ; Masters, CL ; Pietrzak, RH ; Maruff, P (WILEY, 2018-02)
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    Amyloid burden and incident depressive symptoms in cognitively normal older adults
    Harrington, KD ; Gould, E ; Lim, YY ; Ames, D ; Pietrzak, RH ; Rembach, A ; Rainey-Smith, S ; Martins, RN ; Salvado, O ; Villemagne, VL ; Rowe, CC ; Masters, CL ; Maruff, P (WILEY, 2017-04)