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INTRODUCTION: Tau-positron emission tomography (PET) outcome data of patients with Alzheimer's disease (AD) cannot currently be meaningfully compared or combined when different tracers are used due to differences in tracer properties, instrumentation, and methods of analysis. METHODS: Using head-to-head data from five cohorts with tau PET radiotracers designed to target tau deposition in AD, we tested a joint propagation model (JPM) to harmonize quantification (units termed "CenTauR" [CTR]). JPM is a statistical model that simultaneously models the relationships between head-to-head and anchor point data. JPM was compared to a linear regression approach analogous to the one used in the amyloid PET Centiloid scale. RESULTS: A strong linear relationship was observed between CTR values across brain regions. Using the JPM approach, CTR estimates were similar to, but more accurate than, those derived using the linear regression approach. DISCUSSION: Preliminary findings using the JPM support the development and adoption of a universal scale for tau-PET quantification. HIGHLIGHTS: Tested a novel joint propagation model (JPM) to harmonize quantification of tau PET. Units of common scale are termed "CenTauRs". Tested a Centiloid-like linear regression approach. Using five cohorts with head-to-head tau PET, JPM outperformed linearregressionbased approach. Strong linear relationship was observed between CenTauRs values across brain regions.

In 2018, the Australian Dementia Network (ADNeT) was established to bring together Australia's leading dementia researchers, people with living experience and clinicians to transform research and clinical care in the field. To address dementia diagnosis, treatment, and care, ADNeT has established three core initiatives: the Clinical Quality Registry (CQR), Memory Clinics, and Screening for Trials. Collectively, the initiatives have developed an integrated clinical and research community, driving practice excellence in this field, leading to novel innovations in diagnostics, clinical care, professional development, quality and harmonization of healthcare, clinical trials, and translation of research into practice. Australia now has a national Registry for Mild Cognitive Impairment and dementia with 55 participating clinical sites, an extensive map of memory clinic services, national Memory and Cognition Clinic Guidelines and specialized screening for trials sites in five states. This paper provides an overview of ADNeT's achievements to date and future directions. With the increase in dementia cases expected over coming decades, and with recent advances in plasma biomarkers and amyloid lowering therapies, the nationally coordinated initiatives and partnerships ADNeT has established are critical for increased national prevention efforts, co-ordinated implementation of emerging treatments for Alzheimer's disease, innovation of early and accurate diagnosis, driving continuous improvements in clinical care and patient outcome and access to post-diagnostic support and clinical trials. For a heterogenous disorder such as dementia, which is now the second leading cause of death in Australia following cardiovascular disease, the case for adequate investment into research and development has grown even more compelling.

In this article the affiliation details for Ulman Lindenberger were incorrectly given as ‘Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany’ but should have been ‘Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany’, ‘Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany’. The original article has been corrected.

Traumatic brain injury (TBI) is associated with greater 'brain age' that may be caused by atrophy in grey and white matter. Here, we investigated 'brain age' in a chronic TBI (≥10 years) sample. We examined whether 'brain age' increases with years post injury, and whether it is associated with injury severity, cognition and functional outcome. We recruited 102 participants with moderate to severe TBI aged between 40 and 85 years. TBI participants were assessed on average 22 years post-injury. Seventy-seven healthy controls were also recruited. Participants' 'brain age' was determined using T1-weighted MRI images. TBI participants were estimated to have greater 'brain age' compared to healthy controls. 'Brain age' gap was unrelated to time since injury or long-term functional outcome on the Glasgow Outcome Scale-Extended. Greater brain age was associated with greater injury severity measured by post traumatic amnesia duration and Glasgow Coma Scale. 'Brain age' was significantly and inversely associated with verbal memory, but unrelated to visual memory/ability and cognitive flexibility and processing speed. A longitudinal study is required to determine whether TBI leads to a 'one-off' change in 'brain age' or progressive ageing of the brain over time.

We integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 individuals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 individuals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association (P < 1 × 10-3), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.

PURPOSE: Cancer-related cognitive impairment (CRCI) is a recognised adverse consequence of cancer and its treatment. This study assessed the feasibility of collecting longitudinal data on cognition in patients with newly diagnosed, aggressive lymphoma undergoing standard therapy with curative intent via self-report, neuropsychological assessment, peripheral markers of inflammation, and neuroimaging. An exploration and description of patterns of cancer-related cognitive impairment over the course of treatment and recovery was also undertaken and will be reported separately. METHODS: Eligible participants completed repeated measures of cognition including self-report and neuropsychological assessment, and correlates of cognition including blood cell-based inflammatory markers, and neuroimaging at three pre-specified timepoints, time 1 (T1) - pre-treatment (treatment naïve), time 2 (T2) - mid-treatment, and time 3 (T3) - 6 to 8 weeks post-completion of treatment. RESULTS: 30/33 eligible patients (91%, 95% CI: 76%, 97%) were recruited over 10 months. The recruitment rate was 3 patients/month (95% CI: 2.0, 4.3 patients/month). Reasons for declining included feeling overwhelmed and rapid treatment commencement. Mean age was 57 years (SD = 17 years) and 16/30 (53%) were male. Most patients (20/30, 67%) had diffuse large B cell lymphoma or Hodgkin lymphoma (4/30, 13%). The neuroimaging sub-study was optional, 11/30 participants (37%) were eligible to take part, and all agreed. The remaining 19 participants were ineligible as their diagnostic PET/CT scan was completed prior. Retention and compliance with all assessments were 89 to 100% at all timepoints. Only one participant was withdrawn due to disease progression. CONCLUSIONS: Findings from this study including excellent recruitment, retention, and compliance rates demonstrate it is feasible to longitudinally assess cognition in people with newly diagnosed aggressive lymphoma during their initial treatment and recovery to

Prior to the usual clinical symptoms of dementia, there can be subtle changes in cognitive function that differ from the normal age-related cognitive decline, which has been termed mild cognitive impairment (MCI). The increase in the numbers of individuals with possible MCI presenting to health care professionals, notably, General Practitioners (GPs), is going to rise dramatically in the coming years. With ever increasing demands on GPs, it is therefore timely to provide information that can be accessed by health care professionals to assist them in making appropriate diagnoses and to provide the most relevant, evidence-based treatment options. We have provided a comprehensive list of recommendations that aim to address key aspects of MCI in primary care. Specifically, these relate to detection and diagnosis; sharing the diagnosis, monitoring, and follow up; practical interventions to potentially delay progression; and personalizing care-planning, engagement, and patient motivation for the long term.

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

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

Background Previous studies have shown that Aß‐amyloid (Aß) likely promotes tau to spread beyond the medial temporal lobe. However, the Aß levels necessary for tau to spread in the neocortex is still unclear. Method 466 participants underwent tau imaging with [18F]MK6420 and Aß imaging with [18F]NAV4694 (Fig. 1). Aß scans were quantified on the Centiloid (CL) scale with a cut‐off of 25CL for abnormal levels of Aß (A+). Tau scans were quantified in three regions of interest (ROI) (mesial temporal (Me); temporoparietal neocortex (Te); and rest of neocortex (R)) and four mesial temporal region (entorhinal cortex, amygdala, hippocampus and parahippocampus) using the cerebellar cortex as reference region. Regional tau thresholds were established as the 95%ile of the cognitively unimpaired A‐ subjects. The prevalence of abnormal tau levels (T+) along the Centiloid continuum was determined. Result The plots of prevalence of T+ (Fig. 2) show earlier and greater increase along the Centiloid continuum in the medial temporal area compared to neocortex. Prevalence of T+ was low but associated with Aß level between 10‐40 CL reaching 23% in Me, 15% in Te and 11% in R. Between 40‐70 CL, the prevalence of T+ subjects per CL increased four‐fold faster and at 70 CL was 64% in Me, 51% in Te and 37% in R. In cognitively unimpaired (Fig. 3), there were no T+ in R below 50 CL. The highest prevalence of T+ was found in the entorhinal cortex, reaching 40% at 40 CL and 80% at 60 CL. Conclusion Outside the entorhinal cortex, abnormal levels of cortical tau on PET are rarely found with Aß levels below 40 CL. Above 40 CL prevalence of T+ accelerates in all areas. Moderate Aß levels are required before neocortical tau becomes detectable.

Background The introduction of the AT(N) framework raised several issues in regards to the definition of T+. What brain regions should be sampled? Based on one or on multiple tracers? In this work, we developed a “universal” cortical tau mask for the AD continuum derived from all the major tau ligands. This “universal” cortical mask will serve as the common tau area for all tracers over which several different regional sampling VOI or composites can be then applied. Guaranteeing sampling of the same common regions is the first step to develop a common scale for all tau tracers: the CenTauR. Method 464 participants underwent tau scans with either 18F‐AV1451 (CN=54/AD=24), 18F‐MK6240 (CN=157/AD=22), 18F‐PI2620 (CN=10/AD=21), 18F‐PM‐PBB3 (CN=30/AD=28), 18F‐GTP1 (CN=15/AD=38) or 18F‐RO948 (CN=35/AD=30). All CN were Aß‐ and all AD were Aß+. The tau scans were spatially normalized using CapAIBL and the cerebellar cortex was used as reference region. For each tracer, a difference image between the means of the Aß‐ CN and Aß+ AD patients was generated. Difference images were subsequently thresholded at 1/3 of the difference between Aß‐ CN and Aß+ AD in the inferior temporal lobe. A single tau specific mask was then constructed from the intersection of all the specific tau tracer masks. A MRI‐derived grey matter mask at PET resolution was applied to the composite mask only sampling grey matter regions. Finally, the mask was mirrored and fused to remove the hemispherical asymmetry of tau pathology. Agreement between masks was assessed by dice‐scores. Result Visually, all the tracer‐specific masks appeared very similar. None of the known off‐target binding regions were discernible in the resulting masks (Figure 1). There was good agreement between all masks, with dice‐scores of 0.60 and 0.66 for cortical regions. Conclusion We constructed an “universal” tau mask for the AD continuum based on all the commonly used tau tracers aiming at standardizing tau sampling and quantificat

The Worldwide Alzheimer's Disease Neuroimaging Initiative (WW-ADNI) is a collaborative effort to investigate imaging and biofluid markers that can inform Alzheimer's disease treatment trials. It is a public-private partnership that spans North America, Argentina, Australia, Canada, China, Japan, Korea, Mexico, and Taiwan. In 2004, ADNI researchers began a naturalistic, longitudinal study that continues today around the globe. Through several successive phases (ADNI-1, ADNI-GO, ADNI-2, and ADNI-3), the study has fueled amyloid and tau phenotyping and refined neuroimaging methodologies. WW-ADNI researchers have successfully standardized analyses and openly share data without embargo, providing a rich data set for other investigators. On August 26, 2020, the Alzheimer's Association convened WW-ADNI researchers who shared updates from ADNI-3 and their vision for ADNI-4.

Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer’s disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P-threshold (Poptimal) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD.

Background: Dementia was identified as a priority area for the development of a Clinical Quality Registry (CQR) in Australia in 2016. The Australian Dementia Network (ADNeT) Registry is being established as part of the ADNeT initiative, with the primary objective of collecting data to monitor and enhance the quality of care and patient outcomes for people diagnosed with either dementia or Mild Cognitive Impairment (MCI). A secondary aim is to facilitate the recruitment of participants into dementia research and trials. This paper describes the Registry protocol. Methods: The ADNeT Registry is a prospective CQR of patients newly diagnosed with either dementia or MCI. Eligible patients will be identified initially from memory clinics and individual medical specialists (e.g., geriatricians, psychiatrists and neurologists) involved in the diagnosis of dementia. Participants will be recruited using either an opt-out approach or waiver of consent based on three key determinants (capacity, person responsible, and communication of diagnosis). Data will be collected from four sources: participating sites, registry participants, carers, and linkage with administrative datasets. It is anticipated that the Registry will recruit approximately 10,000 participants by the end of 2023. The ADNeT registry will be developed and implemented to comply with the national operating principles for CQRs and governed by the ADNeT Registry Steering Committee. Discussion: The ADNeT Registry will provide important data on current clinical practice in the diagnosis, treatment and care of people with dementia and MCI in Australia as well as long-term outcomes among these people. These data will help to identify variations in clinical practice and patient outcomes and reasons underlying these variations, which in turn, will inform the development of interventions to improve care and outcomes for people with dementia and MCI.

Changes to lipid metabolism are tightly associated with the onset and pathology of Alzheimer's disease (AD). Lipids are complex molecules comprising many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 species across 32 classes) allows for detailed lipid separation and characterisation. In this study we examined peripheral samples of two cohorts (AIBL, n = 1112 and ADNI, n = 800). We are able to identify concordant peripheral signatures associated with prevalent AD arising from lipid pathways including; ether lipids, sphingolipids (notably GM3 gangliosides) and lipid classes previously associated with cardiometabolic disease (phosphatidylethanolamine and triglycerides). We subsequently identified similar lipid signatures in both cohorts with future disease. Lastly, we developed multivariate lipid models that improved classification and prediction. Our results provide a holistic view between the lipidome and AD using a comprehensive approach, providing targets for further mechanistic investigation.

White matter hyperintensities (WMH) are regions of high signal intensity typically identified on fluid attenuated inversion recovery (FLAIR). Although commonly observed in elderly individuals, they are more prevalent in Alzheimer's disease (AD) patients. Given that WMH appear relatively homogeneous on FLAIR, they are commonly partitioned into location- or distance-based classes when investigating their relevance to disease. Since pathology indicates that such lesions are often heterogeneous, probing their microstructure in vivo may provide greater insight than relying on such arbitrary classification schemes. In this study, we investigated WMH in vivo using an advanced diffusion MRI method known as single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), which models white matter microstructure while accounting for grey matter and CSF compartments. Diffusion MRI data and FLAIR images were obtained from AD (n = 48) and healthy elderly control (n = 94) subjects. WMH were automatically segmented, and classified: (1) as either periventricular or deep; or (2) into three distance-based contours from the ventricles. The 3-tissue profile of WMH enabled their characterisation in terms of white matter-, grey matter-, and fluid-like characteristics of the diffusion signal. Our SS3T-CSD findings revealed substantial heterogeneity in the 3-tissue profile of WMH, both within lesions and across the various classes. Moreover, this heterogeneity information indicated that the use of different commonly used WMH classification schemes can result in different disease-based conclusions. We conclude that future studies of WMH in AD would benefit from inclusion of microstructural information when characterising lesions, which we demonstrate can be performed in vivo using SS3T-CSD.

INTRODUCTION: Cancer-related cognitive impairment (CRCI) is a distressing and disabling side-effect of cancer treatments affecting up to 75% of patients. For some patients, their cognitive impairment may be transient, but for a subgroup, these symptoms can be long-standing and have a major impact on the quality of life. This paper describes the protocol for a study: (1) to assess the feasibility of collecting longitudinal data on cognition via self-report, neuropsychological testing, peripheral markers of inflammation and neuroimaging and (2) to explore and describe patterns of cancer-related cognitive impairment over the course of treatment and recovery in patients with newly diagnosed, aggressive lymphoma undergoing standard therapy with curative intent. METHODS AND ANALYSIS: This is a prospective, longitudinal, feasibility study in which 30 newly diagnosed, treatment-naive patients with aggressive lymphoma will be recruited over a 12-month period. Patients will complete comprehensive assessments at three time points: baseline (time 1, pre-treatment) and two post-baseline follow-up assessments (time 2, mid-treatment and time 3, 6-8 weeks post-treatment completion). All patients will be assessed for self-reported cognitive difficulties and objective cognitive function using Stroop Colour and Word, Trail Making Test Part A and B, Hopkins Verbal Learning Test-Revised, Controlled Oral Word Association and Digit Span. Blood cell-based inflammatory markers and neuroimaging including a positron emission tomography (PET) with 18F-labelled fluoro-2-deoxyglucose (18F-FDG) and CT (18F-FDG-PET/CT) and a MRI will explore potential inflammatory and neuroanatomical or functional mechanisms and biomarkers related to CRCI. The primary intent of analysis will be to assess the feasibility of collecting longitudinal data on cognition using subjective reports and objective tasks from patients during treatment and recovery for lymphoma. These data will inform the design of a larger-sca

White matter (WM) microstructure is a sensitive marker to distinguish individuals at risk of Alzheimer's disease. The association of objective physical fitness (PF) measures and WM microstructure has not been explored and mixed results reported with physical activity (PA). Longitudinal studies of WM with PA and PF measures have had limited investigation. This study explored the relationship between objective PF measures over 24-months with "normal-appearing" WM microstructure. Data acquired on magnetic resonance imaging was used to measure "normal-appearing" WM microstructure at baseline and 24-months. Clinical variables such as cognitive and blood-based measures were collected longitudinally. Also, as part of the randomized controlled trial of a PA, extensive measures of PA and fitness were obtained over the 24 months. Bilateral corticospinal tracts (CST) and the corpus callosum showed a significant association between PF performance over 24-months and baseline WM microstructural measures. There was no significant longitudinal effect of the intervention or PF performance over 24-months. Baseline WM microstructural measures were significantly associated with PF performance over 24-months in this cohort of participants with vascular risk factors and at risk of Alzheimer's disease with distinctive patterns for each PF test.

BACKGROUND: Lipid metabolism is altered in Alzheimer's disease (AD); however, the relationship between AD risk factors (age, APOEɛ4, and gender) and lipid metabolism is not well defined. OBJECTIVE: We investigated whether altered lipid metabolism associated with increased age, gender, and APOE status may contribute to the development of AD by examining these risk factors in healthy controls and also clinically diagnosed AD individuals. METHODS: We performed plasma lipidomic profiling (582 lipid species) of the Australian Imaging, Biomarkers and Lifestyle flagship study of aging cohort (AIBL) using liquid chromatography-mass spectrometry. Linear regression and interaction analysis were used to explore the relationship between risk factors and plasma lipid species. RESULTS: We observed strong associations between plasma lipid species with gender and increasing age in cognitively normal individuals. However, APOEɛ4 was relatively weakly associated with plasma lipid species. Interaction analysis identified differential associations of sphingolipids and polyunsaturated fatty acid esterified lipid species with AD based on age and gender, respectively. These data indicate that the risk associated with age, gender, and APOEɛ4 may, in part, be mediated by changes in lipid metabolism. CONCLUSION: This study extends our existing knowledge of the relationship between the lipidome and AD and highlights the complexity of the relationships between lipid metabolism and AD at different ages and between men and women. This has important implications for how we assess AD risk and also for potential therapeutic strategies involving modulation of lipid metabolic pathways.

Motor deficits in parkinsonism are caused by degeneration of dopaminergic nigral neurons. The success of disease-modifying therapies relies on early detection of the underlying pathological process, leading to early interventions in the disease phenotype. Healthy (n = 16), REM sleep behavior disorder (RBD) (n = 14), dementia with Lewy bodies (n = 10), and Parkinson's disease (PD) (n = 20) participants underwent 18F-AV133 vesicular monoamine transporter type-2 (VMAT2) PET to determine the integrity of the nigrostriatal pathway. Clinical, neurophysiological and neuropsychological testing was conducted to assess parkinsonian symptoms. There was reduced VMAT2 levels in RBD participants in the caudate and putamen, indicating nigrostriatal degeneration. RBD patients also presented with hyposmia and anxiety, non-motor symptoms associated with parkinsonism. 18F-AV133 VMAT2 PET allows identification of underlying nigrostriatal degeneration in RBD patients. These findings align with observations of concurrent non-motor symptoms in PD and RBD participants of the Parkinson's Progression Markers Initiative. Together, these findings suggest that RBD subjects have prodromal parkinsonism supporting the concept of conducting neuroprotective therapeutic trials in RBD-enriched cohorts. Ongoing longitudinal follow-up of these subjects will allow us to determine the time-window of clinical progression.

BACKGROUND: Previous studies have demonstrated that physical activity (PA) interventions can improve physical and cognitive outcomes in older adults, but most have been relatively short in duration (<1 year) with a few having specifically targeting individuals at risk of developing Alzheimer's disease. OBJECTIVE: To examine adherence and physical health outcomes in a 24-month home-based PA intervention in older adults at risk of Alzheimer's disease. METHODS: Participants 60 years and older with mild cognitive impairment (MCI) or subjective memory complaints (SMC) with at least 1 cerebrovascular risk factor recruited from The Australian Imaging Biomarkers and Lifestyle Flagship Study of Aging (AIBL) were randomized to a PA or control group (n = 106). The control group continued with their usual lifestyle. The PA group received a 24-month home-based program with a target of 150 minutes/week of moderate PA and a behavioral intervention. Retention (participants remaining) and PA adherence (PA group only, percent PA completed to the PA prescribed) were determined at 6, 12, 18, and 24 months. Assessments at baseline, 6, 12, and 24 months included, PA; fitness; body composition and fat distribution. Key outcome measures were PA adherence and PA. RESULTS: The 24-month retention rate (97.2%) and the median PA adherence 91.67% (Q1-Q3, 81.96, 100.00) were excellent. In the long-term the intervention group achieved significantly better improvements in PA levels, leg strength, fat mass and fat distribution compared to the control. CONCLUSION: This study demonstrates that in this target group, long-term PA adherence is achievable and has physical health benefits.

OBJECTIVE: We investigated the relationship between the interictal metabolic patterns, the extent of resection of 18 F-fluorodeoxyglucose positron emission tomography (18 FDG-PET) hypometabolism, and seizure outcomes in patients with unilateral drug-resistant mesial temporal lobe epilepsy (MTLE) following anterior temporal lobe (TL) resection. METHODS: Eighty-two patients with hippocampal sclerosis or normal magnetic resonance imaging (MRI) findings, concordant 18 FDG-PET hypometabolism, and at least 2 years of postoperative follow-up were included in this 2-center study. The hypometabolic regions in each patient were identified with reference to 20 healthy controls (p < 0.005). The resected TL volume and the volume of resected TL PET hypometabolism (TLH) were calculated from the pre- and postoperative MRI scans coregistered with interictal 18 FDG-PET. RESULTS: Striking differences in metabolic patterns were observed depending on the lateralization of the epileptogenic TL. The extent of the ipsilateral TLH was significantly greater in left MTLE patients (p < 0.001), whereas right MTLE patients had significantly higher rates of contralateral (CTL) TLH (p = 0.016). In right MTLE patients, CTL hypometabolism was the strongest predictor of an unfavorable seizure outcome, associated with a 5-fold increase in the likelihood of seizure recurrence (odds ratio [OR] = 4.90, 95% confidence interval [CI] = 1.07-22.39, p = 0.04). In left MTLE patients, greater extent of resection of ipsilateral TLH was associated with lower rates of seizure recurrence (p = 0.004) in univariate analysis; however, its predictive value did not reach statistical significance (OR = 0.96, 95% CI = 0.90-1.02, p = 0.19). INTERPRETATION: The difference in metabolic patterns depending on the lateralization of MTLE may represent distinct epileptic networks in patients with right versus left MTLE, and can guide preoperative counseling and surgical planning. Ann Neurol 2019; 1-10 ANN NEUROL 2019;85:241-250.

Introduction Identifying at what point atrophy rates first change in Alzheimer's disease is important for informing design of presymptomatic trials. Methods Serial T1-weighted magnetic resonance imaging scans of 94 participants (28 noncarriers, 66 carriers) from the Dominantly Inherited Alzheimer Network were used to measure brain, ventricular, and hippocampal atrophy rates. For each structure, nonlinear mixed-effects models estimated the change-points when atrophy rates deviate from normal and the rates of change before and after this point. Results Atrophy increased after the change-point, which occurred 1–1.5 years (assuming a single step change in atrophy rate) or 3–8 years (assuming gradual acceleration of atrophy) before expected symptom onset. At expected symptom onset, estimated atrophy rates were at least 3.6 times than those before the change-point. Discussion Atrophy rates are pathologically increased up to seven years before “expected onset”. During this period, atrophy rates may be useful for inclusion and tracking of disease progression.

OBJECTIVES: To further validate the diagnostic utility of 18F-AV-133 vesicular monoamine transporter type 2 (VMAT2) positron emission tomography (PET) in patients with clinically uncertain parkinsonian syndromes (CUPS) by comparison to clinical diagnosis at 3 years follow-up. DESIGN, SETTING AND PARTICIPANTS: In a previous study, we reported that 18F-AV-133 PET in community patients with CUPS changed diagnosis and management and increased diagnostic confidence. The current diagnosis of this cohort was obtained from the patient and treating specialist and compared with the diagnosis suggested 3 years earlier by the 18F-AV-133 PET. A second 18F-AV-133 PET was available in those with a discordant or inconclusive final diagnosis. STUDY OUTCOME MEASURES: The primary end point was the proportion of patients who had a follow-up clinical diagnosis, which was concordant with their initial 18F-AV-133 PET scan. Secondary end points were the proportion of patients who had the same diagnosis at follow-up as that reached after the initial scan and the stability of diagnostic changes made after the first scan. RESULTS: 81 of the 85 patients previously recruited to the CUPS study had follow-up of which 79 had a clinical diagnosis and 2 remained CUPS. The diagnosis was in agreement with the initial 18F-AV-133 PET scan result in 74 cases. Five patients had a discordant diagnosis; one patient with rubral tremor had a severely abnormal scan that had worsened when rescanned; four cases with normal initial and repeat scans had a clinical diagnosis of Parkinson's disease. Two patients with suspected genetic disorders remained classified as CUPS and both had normal scans. In the 24 CUPS cohort patients where 18F-AV-133 PET initially changed diagnosis, this change was supported by follow-up diagnosis in all but the one rubral tremor case. CONCLUSION: 18F-AV-133 PET is a useful tool in improving diagnostic accuracy in CUPS providing results and diagnostic changes that remain robust after 3 y

Cortical cholinergic deficiency is prominent in Alzheimer's disease (AD), and published findings of diminished pupil flash response in AD suggest that this deficiency may extend to the visual cortical areas and anterior eye. Pupillometry is a low-cost, noninvasive technique that may be useful for monitoring cholinergic deficits which generally lead to memory and cognitive disorders. The aim of the study was to evaluate pupillometry for early detection of AD by comparing the pupil flash response (PFR) in AD (N = 14) and cognitively normal healthy control (HC, N = 115) participants, with the HC group stratified according to high (N = 38) and low (N = 77) neocortical amyloid burden (NAB). Constriction phase PFR parameters were significantly reduced in AD compared to HC (maximum acceleration p < 0.05, maximum velocity p < 0.0005, average velocity p < 0.005, and constriction amplitude p < 0.00005). The high-NAB HC subgroup had reduced PFR response cross-sectionally, and also a greater decline longitudinally, compared to the low-NAB subgroup, suggesting changes to pupil response in preclinical AD. The results suggest that PFR changes may occur in the preclinical phase of AD. Hence, pupillometry has a potential as an adjunct for noninvasive, cost-effective screening for preclinical AD.

INTRODUCTION: A blood-based biomarker panel to identify individuals with preclinical Alzheimer's disease (AD) would be an inexpensive and accessible first step for routine testing. METHODS: We analyzed 14 biomarkers that have previously been linked to AD in the Australian Imaging Biomarkers lifestyle longitudinal study of aging cohort. RESULTS: Levels of apolipoprotein J (apoJ) were higher in AD individuals compared with healthy controls at baseline and 18 months (P = .0003) and chemokine-309 (I-309) were increased in AD patients compared to mild cognitive impaired individuals over 36 months (P = .0008). DISCUSSION: These data suggest that apoJ may have potential in the context of use (COU) of AD diagnostics, I-309 may be specifically useful in the COU of identifying individuals at greatest risk for progressing toward AD. This work takes an initial step toward identifying blood biomarkers with potential use in the diagnosis and prognosis of AD and should be validated across other prospective cohorts.

Background: We report results of the novel Washout Allometric Reference Method (WARM) that uses estimates of cerebral blood flow and amyloid load from the same [11C]Pittsburgh Compound B ([11C]PiB) retention maps in brain to distinguish between patients with different forms dementia, including Alzheimer's disease, and healthy volunteers. The method introduces two approaches to the identification of brain pathology related to amyloid accumulation, (1) a novel analysis of amyloid binding based on the late washout of the tracer from brain tissue, and (2) the simultaneous estimation of absolute cerebral blood flow indices (sCBF) from the early accumulation of the tracer in brain tissue. Objective: We tested the hypothesis that a change of cerebral blood flow is correlated with the degree of tracer [11C]PiB retention, reflecting dendritic spine pathology and consequent inhibition of brain energy metabolism and reduction of blood flow by neurovascular coupling in neurodegenerative disorders, including Alzheimer's disease. Methods: Previously reported images of [11C]PiB retention in brain of 29 subjects with cognitive impairment or dementia [16 Alzheimer's Disease (AD), eight subjects with dementia with Lewy bodies (DLB), five patients with frontotemporal lobar degeneration (FTLD), five patients with mild cognitive impairment, and 29 age-matched healthy control subjects (HC)], underwent analysis of PiB delivery and retention by means of WARM for quantitation of [11C]PiB's binding potentials (BPND) and correlated surrogate cerebral blood flow (sCBF) estimates, based on the [11C]PiB images, compared to estimates by conventional Standard Uptake Value Ratio (SUVR) of [11C]PiB retention with cerebellum gray matter as reference. Receiver Operating Characteristics (ROC) revealed the power of discrimination among estimates. Results: For AD, the discriminatory power of [11C]PiB binding potential (BPND) by WARM exceeded the power of SUVR that in turn exceeded the power of sCBF estim

In vivo imaging of tau deposits is providing a better understanding of the temporal and spatial tau deposition in the brain, allowing a more comprehensive insight into the causes, diagnoses, and potentially treatment of tauopathies such as Alzheimer's disease, progressive supranuclear palsy, corticobasal syndrome, chronic traumatic encephalopathy, and some variants of frontotemporal lobar degeneration. The assessment of tau deposition in the brain over time will allow a deeper understanding of the relationship between tau and other variables such as cognition, genotype, and neurodegeneration, as well as assessing the role tau plays in ageing. Preliminary human studies suggest that tau imaging could also be used as a diagnostic, prognostic, and theranostic biomarker, as well as a surrogate marker for target engagement, patient recruitment, and efficacy monitoring for disease-specific therapeutic trials.

BACKGROUND: The cerebrospinal fluid (CSF) amyloid-β (Aβ)(1-42), total-tau (T-tau), and phosphorylated-tau (P-tau181P) profile has been established as a valuable biomarker for Alzheimer's disease (AD). OBJECTIVE: The current study aimed to determine CSF biomarker cut-points using positron emission tomography (PET) Aβ imaging screened subjects from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, as well as correlate CSF analyte cut-points across a range of PET Aβ amyloid ligands. METHODS: Aβ pathology was determined by PET imaging, utilizing ¹¹C-Pittsburgh Compound B, ¹⁸F-flutemetamol, or ¹⁸F-florbetapir, in 157 AIBL participants who also underwent CSF collection. Using an INNOTEST assay, cut-points were established (Aβ(1-42) >544 ng/L, T-tau <407 ng/L, and P-tau181P <78 ng/L) employing a rank based method to define a "positive" CSF in the sub-cohort of amyloid-PET negative healthy participants (n = 97), and compared with the presence of PET demonstrated AD pathology. RESULTS: CSF Aβ(1-42) was the strongest individual biomarker, detecting cognitively impaired PET positive mild cognitive impairment (MCI)/AD with 85% sensitivity and 91% specificity. The ratio of P-tau181P or T-tau to Aβ(1-42) provided greater accuracy, predicting MCI/AD with Aβ pathology with ≥92% sensitivity and specificity. Cross-validated accuracy, using all three biomarkers or the ratio of P-tau or T-tau to Aβ(1-42) to predict MCI/AD, reached ≥92% sensitivity and specificity. CONCLUSIONS: CSF Aβ(1-42) levels and analyte combination ratios demonstrated very high correlation with PET Aβ imaging. Our study offers additional support for CSF biomarkers in the early and accurate detection of AD pathology, including enrichment of patient cohorts for treatment trials even at the pre-symptomatic stage.

Alzheimer disease is the cause of up to one-third of cases of primary progressive aphasia or corticobasal syndrome. The primary objective of this study was to determine the accuracy of 18F-FDG PET metabolic imaging for the detection of Alzheimer disease in patients with primary progressive aphasia or corticobasal syndrome. Methods: A cohort of patients (n = 94), including those with an expert clinical diagnosis of logopenic (n = 19), nonfluent (n = 16), or semantic (n = 13) variants of primary progressive aphasia, corticobasal syndrome (n = 14), or Alzheimer disease (n = 24), underwent 18F-FDG metabolic and 11C-labeled Pittsburgh compound B (11C-PiB) amyloid PET brain imaging. 18F-FDG PET scans interpreted with Neurostat and 3D-SSP displays were classified as revealing Alzheimer disease or "other" by interpreters who were unaware of the clinical assessments and 11C-PiB PET results. 11C-PiB PET imaging was considered to be the diagnostic reference standard, with a threshold standardized uptake value ratio of 1.5 being indicative of Alzheimer disease pathology. To address possible bias from subgroup selection for the Alzheimer disease binary classifier, we calculated both conventional and balanced accuracies. Results: Diagnoses of Alzheimer disease based on 18F-FDG PET resulted in 84% accuracy (both conventional and balanced). In comparison, diagnoses based on clinical assessments resulted in 65% conventional accuracy and 67% balanced accuracy. Conclusion: Brain 18F-FDG PET scans interpreted with Neurostat and 3D-SSP displays accurately detected Alzheimer disease in patients with primary progressive aphasia or corticobasal syndrome as focal-onset dementias. In such diagnostically challenging cohorts, 18F-FDG PET imaging can provide more accurate diagnoses, enabling more appropriate therapy.

FFQ are commonly used to examine the association between diet and disease. They are the most practical method for usual dietary data collection as they are relatively inexpensive and easy to administer. In Australia, the Cancer Council of Victoria FFQ (CCVFFQ) version 2 and the online Commonwealth Scientific and Industrial Research Organisation FFQ (CSIROFFQ) are used. The aim of our study was to establish the level of agreement between nutrient intakes captured using the online CSIROFFQ and the paper-based CCVFFQ. The CCVFFQ and the online CSIROFFQ were completed by 136 healthy participants. FFQ responses were analysed to give g per d intake of a range of nutrients. Agreement between twenty-six nutrient intakes common to both FFQ was measured by a variety of methods. Nutrient intake levels that were significantly correlated between the two FFQ were carbohydrates, total fat, Na and MUFA. When assessing ranking of nutrients into quintiles, on average, 56 % of the participants (for all nutrients) were classified into the same or adjacent quintiles in both FFQ, with the highest percentage agreement for sugar. On average, 21 % of participants were grossly misclassified by three or four quintiles, with the highest percentage misclassification for fibre and Fe. Quintile agreement was similar to that reported by other studies, and we concluded that both FFQ are suitable tools for dividing participants' nutrient intake levels into high- and low-consumption groups. Use of either FFQ was not appropriate for obtaining accurate estimates of absolute nutrient intakes.

BACKGROUND: Assessment of risk and early diagnosis of Alzheimer's disease (AD) is a key to its prevention or slowing the progression of the disease. Previous research on risk factors for AD typically utilizes statistical comparison tests or stepwise selection with regression models. Outcomes of these methods tend to emphasize single risk factors rather than a combination of risk factors. However, a combination of factors, rather than any one alone, is likely to affect disease development. Genetic algorithms (GA) can be useful and efficient for searching a combination of variables for the best achievement (eg. accuracy of diagnosis), especially when the search space is large, complex or poorly understood, as in the case in prediction of AD development. RESULTS: Multiple sets of neuropsychological tests were identified by GA to best predict conversions between clinical categories, with a cross validated AUC (area under the ROC curve) of 0.90 for prediction of HC conversion to MCI/AD and 0.86 for MCI conversion to AD within 36 months. CONCLUSIONS: This study showed the potential of GA application in the neural science area. It demonstrated that the combination of a small set of variables is superior in performance than the use of all the single significant variables in the model for prediction of progression of disease. Variables more frequently selected by GA might be more important as part of the algorithm for prediction of disease development.

Non-invasive imaging of tau pathology in the living brain would be useful for accurately diagnosing Alzheimer's disease, tracking disease progression, and evaluating the treatment efficacy of disease-specific therapeutics. In this study, we evaluated the clinical usefulness of a novel tau-imaging positron emission tomography tracer 18F-THK5105 in 16 human subjects including eight patients with Alzheimer's disease (three male and five females, 66-82 years) and eight healthy elderly controls (three male and five females, 63-76 years). All participants underwent neuropsychological examination and 3D magnetic resonance imaging, as well as both 18F-THK5105 and 11C-Pittsburgh compound B positron emission tomography scans. Standard uptake value ratios at 90-100 min and 40-70 min post-injection were calculated for 18F-THK5105 and 11C-Pittsburgh compound B, respectively, using the cerebellar cortex as the reference region. As a result, significantly higher 18F-THK5105 retention was observed in the temporal, parietal, posterior cingulate, frontal and mesial temporal cortices of patients with Alzheimer's disease compared with healthy control subjects. In patients with Alzheimer's disease, the inferior temporal cortex, which is an area known to contain high densities of neurofibrillary tangles in the Alzheimer's disease brain, showed prominent 18F-THK5105 retention. Compared with high frequency (100%) of 18F-THK5105 retention in the temporal cortex of patients with Alzheimer's disease, frontal 18F-THK5105 retention was less frequent (37.5%) and was only observed in cases with moderate-to-severe Alzheimer's disease. In contrast, 11C-Pittsburgh compound B retention was highest in the posterior cingulate cortex, followed by the ventrolateral prefrontal, anterior cingulate, and superior temporal cortices, and did not correlate with 18F-THK5105 retention in the neocortex. In healthy control subjects, 18F-THK5105 retention was ∼10% higher in the mesial temporal cortex than in the neo

Since the launch in 2003 of the Alzheimer's Disease Neuroimaging Initiative (ADNI) in the USA, ever growing, similarly oriented consortia have been organized and assembled around the world. The various accomplishments of ADNI have contributed substantially to a better understanding of the underlying physiopathology of aging and Alzheimer's disease (AD). These accomplishments are basically predicated in the trinity of multimodality, standardization and sharing. This multimodality approach can now better identify those subjects with AD-specific traits that are more likely to present cognitive decline in the near future and that might represent the best candidates for smaller but more efficient therapeutic trials - trials that, through gained and shared knowledge, can be more focused on a specific target or a specific stage of the disease process. In summary, data generated from ADNI have helped elucidate some of the pathophysiological mechanisms underpinning aging and AD pathology, while contributing to the international effort in setting the groundwork for biomarker discovery and establishing standards for early diagnosis of AD.

High amyloid has been associated with substantial episodic memory decline over 18 and 36 months in healthy older adults and individuals with mild cognitive impairment. However, the nature and magnitude of amyloid-related memory and non-memory change from the preclinical to the clinical stages of Alzheimer's disease has not been evaluated over the same time interval. Healthy older adults (n = 320), individuals with mild cognitive impairment (n = 57) and individuals with Alzheimer's disease (n = 36) enrolled in the Australian Imaging, Biomarkers and Lifestyle study underwent at least one positron emission tomography neuroimaging scan for amyloid. Cognitive assessments were conducted at baseline, and 18- and 36-month follow-up assessments. Compared with amyloid-negative healthy older adults, amyloid-positive healthy older adults, and amyloid-positive individuals with mild cognitive impairment and Alzheimer's disease showed moderate and equivalent decline in verbal and visual episodic memory over 36 months (d's = 0.47-0.51). Relative to amyloid-negative healthy older adults, amyloid-positive healthy older adults showed no decline in non-memory functions, but amyloid-positive individuals with mild cognitive impairment showed additional moderate decline in language, attention and visuospatial function (d's = 0.47-1.12), and amyloid-positive individuals with Alzheimer's disease showed large decline in all aspects of memory and non-memory function (d's = 0.73-2.28). Amyloid negative individuals with mild cognitive impairment did not show any cognitive decline over 36 months. When non-demented individuals (i.e. healthy older adults and adults with mild cognitive impairment) were further dichotomized, high amyloid-positive non-demented individuals showed a greater rate of decline in episodic memory and language when compared with low amyloid positive non-demented individuals. Memory decline does not plateau with increasing disease severity, and decline in non-memory functions