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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.

Background: The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study commenced in 2006 as a prospective study of 1,112 individuals (768 cognitively normal (CN), 133 with mild cognitive impairment (MCI), and 211 with Alzheimer’s disease dementia (AD)) as an ‘Inception cohort’ who underwent detailed ssessments every 18 months. Over the past decade, an additional 1247 subjects have been added as an ‘Enrichment cohort’ (as of 10 April 2019). Objective: Here we provide an overview of these Inception and Enrichment cohorts of more than 8,500 person-years of investigation. Methods: Participants underwent reassessment every 18 months including comprehensive cognitive testing, neuroimaging (magnetic resonance imaging, MRI; positron emission tomography, PET), biofluid biomarkers and lifestyle evaluations. Results: AIBL has made major contributions to the understanding of the natural history of AD, with cognitive and biological definitions of its three major stages: preclinical, prodromal and clinical. Early deployment of Aβ-amyloid and tau molecular PET imaging and the development of more sensitive and specific blood tests have facilitated the assessment of genetic and environmental factors which affect age at onset and rates of progression. Conclusion: This fifteen-year study provides a large database of highly characterized individuals with longitudinal cognitive, imaging and lifestyle data and biofluid collections, to aid in the development of interventions to delay onset, prevent or treat AD. Harmonization with similar large longitudinal cohort studies is underway to further these aims.

Background Physical inactivity has been consistently linked to increased risk of cognitive decline; however, studies examining the impact of exercise interventions on cognition have produced inconsistent findings. Some observational studies suggest exercise intensity may be important for inducing cognitive improvements; however, this has yet to be thoroughly examined in older adult cohorts. The objective of the current study was to evaluate the effect of systematically manipulated high-intensity and moderate-intensity exercise interventions on cognition. Methods This multi-arm pilot randomised clinical trial investigated the effects of 6 months of high-intensity exercise and moderate-intensity exercise, compared with an inactive control, on cognition. Outcome measures were assessed at pre- (baseline), post- (6 months), and 12 months post-intervention. Ninety-nine cognitively normal men and women (aged 60–80 years) were enrolled from October 2016 to November 2017. Participants that were allocated to an exercise group (i.e. high-intensity or moderate-intensity) engaged in cycle-based exercise two times per week for 6 months. Cognition was assessed using a comprehensive neuropsychological test battery. Cardiorespiratory fitness was evaluated by a graded exercise test. Results There was a dose-dependent effect of exercise intensity on cardiorespiratory fitness, whereby the high-intensity group experienced greater increases in fitness than the moderate-intensity and control groups. However, there was no direct effect of exercise on cognition. Conclusions We did not observe a direct effect of exercise on cognition. Future work in this field should be appropriately designed and powered to examine factors that may contribute to individual variability in response to intervention.

Background: Clinical trials in Alzheimer’s disease (AD) depend on clinical endpoints that may lack sensitivity to the cognitive changes that characterize the disease prior to dementia diagnosis. Consequently, trials designed to determine whether new drugs can forestall dementia or prevent cognitive decline prior to onset of AD dementia will require outcomes measures that are sensitive to cognitive changes earlier in the disease. Objectives: The objective of this work was to identify individuals whose cognitive scores progress more rapidly (“accelerators”) from those whose cognition does not reach this same level over the same time period (“non-accelerators”). The specific aim was to assess the MMSE, CDR-SB and seven different cognitive composite scores to examine 1) their ability to cluster accelerators and non- accelerators, 2) which cognitive scores can be used as strong predictors of cognitive change, and 3) the proportion agreement of progression classification within specific subgroups of AD pathology. This process was entirely data driven in that it was performed without using the formal AIBL clinical classification to inform disease stage. Methods: Using longitudinal data from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing, seven cognitive composite scores (the AIBL PACC score (CVLT-II, LMII, DSC & MMSE), attention and processing speed (DSC & total digit span), episodic memory (delayed recall, LMII & RCFT30), executive function (verbal fluency & category switching), language (BNT & verbal fluency [D-KEFS]), recognition (recognition CVLT-II & RCFT), visuospatial function (RCFT copy & clock along) along with MMSE and CDR-SB from 144 months of AIBL were selected from all participants with at least three time points (at baseline: total N=1269; 973 Cognitively Normal (CN), 143 with Mild Cognitive Impairment (MCI), 153 with AD). Using the mathematical properties of a proposed sigmoidal function, “cognitive turning points” are defined to all

Background:Cerebrovascular disease often coexists with Alzheimer’s disease (AD). While both diseases share common risk factors, their interrelationship remains unclear. Increasing the understanding of how cerebrovascular changes interact with AD is essential to develop therapeutic strategies and refine biomarkers for early diagnosis. Objective:We investigate the prevalence and risk factors for the comorbidity of amyloid-β (Aβ) and cerebrovascular disease in the Australian Imaging, Biomarkers and Lifestyle Study of Ageing, and further examine their cross-sectional association. Methods:A total of 598 participants (422 cognitively normal, 89 with mild cognitive impairment, 87 with AD) underwent positron emission tomography and structural magnetic resonance imaging for assessment of Aβ deposition and cerebrovascular disease. Individuals were categorized based on the comorbidity status of Aβ and cerebrovascular disease (V) as Aβ–V–, Aβ–V+, Aβ+V–, or Aβ+V+. Results:Advancing age was associated with greater likelihood of cerebrovascular disease, high Aβ load and their comorbidity. Apolipoprotein E ɛ4 carriage was only associated with Aβ positivity. Greater total and regional WMH burden were observed in participants with AD. However, no association were observed between Aβ and WMH measures after stratification by clinical classification, suggesting that the observed association between AD and cerebrovascular disease was driven by the common risk factor of age. Conclusion:Our observations demonstrate common comorbid condition of Aβ and cerebrovascular disease in later life. While our study did not demonstrate a convincing cross-sectional association between Aβ and WMH burden, future longitudinal studies are required to further confirm this.

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.

Higher cardiorespiratory fitness has been associated with better cognitive function in older adults; yet, this relationship demonstrates a degree of variability across the older adult population. Thus, it is hypothesised that variation in genetic factors may influence the relationship between fitness and cognitive health. One such genetic factor is the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism, which has previously been shown to moderate the relationship between self-reported physical activity and memory performance. In this study we aim to investigate the interaction between BDNF Val66Met polymorphism and objectively-measured cardiorespiratory fitness on performance on tasks assessing verbal and visuospatial memory. Data from ninety-nine cognitively normal men and women aged 60–80 years were used. Fitness was assessed by peak oxygen consumption, and verbal and visuospatial memory were evaluated using well-validated measures. Participants were categorised into: lower-fit Met carriers, higher-fit Met carriers, lower-fit Val/Val, or higher-fit Val/Val. Higher-fit individuals performed better on a task assessing visuospatial memory, compared with lower-fit individuals. Furthermore, an interaction between BDNF Val66Met and fitness was observed in terms of visuospatial memory performance on a continuous paired associate learning task; whereby lower-fit Met carriers performed 1 standard deviation worse than higher-fit Met carriers. No differences were observed between the higher-fit and lower-fit Val/Val homozygotes. Future intervention studies should evaluate the effect of structured exercise on cognitive health between BDNF Val66Met carriers and Val/Val homozygotes.

Over the last two decades, EDTA-plasma has been used as the preferred sample matrix for human blood proteomic profiling. Serum has also been employed widely. Only a few studies have assessed the difference and relevance of the proteome profiles obtained from plasma samples, such as EDTA-plasma or lithium-heparin-plasma, and serum. A more complete evaluation of the use of EDTA-plasma, heparin-plasma, and serum would greatly expand the comprehensiveness of shotgun proteomics of blood samples. In this study, we evaluated the use of heparin-plasma with respect to EDTA-plasma and serum to profile blood proteomes using a scalable automated proteomic pipeline (ASAP2). The use of plasma and serum for mass-spectrometry-based shotgun proteomics was first tested with commercial pooled samples. The proteome coverage consistency and the quantitative performance were compared. Furthermore, protein measurements in EDTA-plasma and heparin-plasma samples were comparatively studied using matched sample pairs from 20 individuals from the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study. We identified 442 proteins in common between EDTA-plasma and heparin-plasma samples. Overall agreement of the relative protein quantification between the sample pairs demonstrated that shotgun proteomics using workflows such as the ASAP2 is suitable in analyzing heparin-plasma and that such sample type may be considered in large-scale clinical research studies. Moreover, the partial proteome coverage overlaps (e.g., ∼70%) showed that measures from heparin-plasma could be complementary to those obtained from EDTA-plasma.

© 2018-IOS Press and the authors. All rights reserved. Worldwide there are over 46 million people living with dementia, and this number is expected to double every 20 years reaching about 131 million by 2050. The cost to the community and government health systems, as well as the stress on families and carers is incalculable. Over three decades of research into this disease have been undertaken by several research groups in Australia, including work by our original research group in Western Australia which was involved in the discovery and sequencing of the amyloid-β peptide (also known as Aβ or A4 peptide) extracted from cerebral amyloid plaques. This review discusses the journey from the discovery of the Aβ peptide in Alzheimer's disease (AD) brain to the establishment of pre-clinical AD using PET amyloid tracers, a method now serving as the gold standard for developing peripheral diagnostic approaches in the blood and the eye. The latter developments for early diagnosis have been largely achieved through the establishment of the Australian Imaging Biomarker and Lifestyle research group that has followed 1,100 Australians for 11 years. AIBL has also been instrumental in providing insight into the role of the major genetic risk factor apolipoprotein E ϵ4, as well as better understanding the role of lifestyle factors particularly diet, physical activity and sleep to cognitive decline and the accumulation of cerebral Aβ.

Alzheimer’s Disease (AD) is the most common form of dementia, characterised by extracellular amyloid deposition as plaques and intracellular neurofibrillary tangles of tau protein. As no current clinical test can diagnose individuals at risk of developing AD, the aim of this project is to evaluate a blood-based biomarker panel to identify individuals who carry this risk. We analysed the levels of 22 biomarkers in clinically classified healthy controls (HC), mild cognitive impairment (MCI) and Alzheimer’s participants from the well characterised Australian Imaging, Biomarker and Lifestyle (AIBL) study of aging. High levels of IL-10 and IL-12/23p40 were significantly associated with amyloid deposition in HC, suggesting that these two biomarkers might be used to detect at risk individuals. Additionally, other biomarkers (Eotaxin-3, Leptin, PYY) exhibited altered levels in AD participants possessing the APOE ε4 allele. This suggests that the physiology of some potential biomarkers may be altered in AD due to the APOE ε4 allele, a major risk factor for AD. Taken together, these data highlight several potential biomarkers that can be used in a blood-based panel to allow earlier identification of individuals at risk of developing AD and/or early stage AD for which current therapies may be more beneficial.

Background Hypothalamic-pituitary-adrenal axis dysregulation, which is typically assessed by measuring cortisol levels, is associated with cognitive dysfunction, hippocampal atrophy, and increased risk for mild cognitive impairment and Alzheimer’s disease (AD). However, little is known about the role of hypothalamic-pituitary-adrenal axis dysregulation in moderating the effect of high levels of amyloid-β (Aβ+) on cognitive decline in the preclinical phase of AD, which is often protracted, and thus offers opportunities for prevention and early intervention. Methods Using data from a 6-year multicenter prospective cohort study, we evaluated the relation between Aβ level, plasma cortisol level, and cognitive decline in 416 cognitively normal older adults. Results Results revealed that Aβ+ older adults experienced faster decline than Aβ− older adults in all cognitive domains (Cohen’s d at 6-year assessment = 0.37–0.65). They further indicated a significant interaction between Aβ and cortisol levels for global cognition (d = 0.32), episodic memory (d = 0.50), and executive function (d = 0.59) scores, with Aβ+ older adults with high cortisol levels having significantly faster decline in these domains compared with Aβ+ older adults with low cortisol levels. These effects were independent of age, sex, APOE genotype, anxiety symptoms, and radiotracer type. Conclusions In cognitively healthy older adults, Aβ+ is associated with greater cognitive decline and high plasma cortisol levels may accelerate the effect of Aβ+ on decline in global cognition, episodic memory, and executive function. These results suggest that therapies targeted toward lowering plasma cortisol and Aβ levels may be helpful in mitigating cognitive decline in the preclinical phase of AD.

Introduction Inconsistent results from previous studies of exercise and cognitive function suggest that rigorously designed randomized controlled trials are urgently needed. Here, we describe the design of the Intense Physical Activity and Cognition (IPAC) study, which will assess the impact of a 6-month high-intensity exercise intervention on cognitive function and biomarkers of dementia risk, compared with a 6-month moderate-intensity exercise intervention and control group (no study-related exercise). Methods One-hundred and five cognitively healthy men and women aged between 60 and 80 years are randomized into a high-intensity exercise, moderate-intensity exercise, or control group. Individuals randomized to an exercise intervention undertake 6 months of cycle-based exercise twice a week, at 50 minutes per session. All participants undergo comprehensive neuropsychological testing, blood sampling, brain magnetic resonance imaging, fitness testing, and a body composition scan at baseline, 6 months (immediately after intervention), and 18 months (12 months after intervention). Discussion The IPAC study takes a multidisciplinary approach to investigating the role of exercise in maintaining a healthy brain throughout aging. Rigorous monitoring of exertion and adherence throughout the intervention, combined with repeated measures of fitness, is vital in ensuring an optimum exercise dose is reached. Results Results from the IPAC study will be used to inform a large-scale multicentre randomized controlled trial, with the ultimate aim of pinpointing the frequency, duration, and intensity of exercise that provides the most benefit to the brain, in terms of enhancing cognitive function and reducing dementia risk in older adults.

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.

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.

Previous studies have proposed that the early elucidation of brain injury from structural Magnetic Resonance Images (sMRI) is critical for the clinical assessment of children with cerebral palsy (CP). Although distinct aetiologies, including cortical maldevelopments, white and grey matter lesions and ventricular enlargement, have been categorised, these injuries are commonly only assessed in a qualitative fashion. As a result, sMRI remains relatively underexploited for clinical assessments, despite its widespread use. In this study, several automated and validated techniques to automatically quantify these three classes of injury were generated in a large cohort of children (n = 139) aged 5–17, including 95 children diagnosed with unilateral CP. Using a feature selection approach on a training data set (n = 97) to find severity of injury biomarkers predictive of clinical function (motor, cognitive, communicative and visual function), cortical shape and regional lesion burden were most often chosen associated with clinical function. Validating the best models on the unseen test data (n = 42), correlation values ranged between 0.545 and 0.795 (p < 0.008), indicating significant associations with clinical function. The measured prevalence of injury, including ventricular enlargement (70%), white and grey matter lesions (55%) and cortical malformations (30%), were similar to the prevalence observed in other cohorts of children with unilateral CP. These findings support the early characterisation of injury from sMRI into previously defined aetiologies as part of standard clinical assessment. Furthermore, the strong and significant association between quantifications of injury observed on structural MRI and multiple clinical scores accord with empirically established structure-function relationships.

Alzheimer’s disease (AD) is a degenerative brain disorder and is the most common form of dementia. Minimally invasive approaches are required that combine biomarkers to identify individuals who are at risk of developing mild cognitive impairment (MCI) and AD, to appropriately target clinical trials for therapeutic discovery as well as lifestyle strategies aimed at prevention. Buccal mucosa cells from the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing cohort (n=60) were investigated for cytological markers that could be used to identify both MCI and AD individuals. Visual scoring of the buccal cytome demonstrated a significantly lower frequency of basal and karyorrhectic cells in the MCI group compared with controls. A high content, automated assay was developed using laser scanning cytometry to simultaneously measure cell types, nuclear DNA content and aneuploidy, neutral lipid content, putative Tau and amyloid-β (Aβ) in buccal cells. DNA content, aneuploidy, neutral lipids and Tau were similar in all groups. However, there was significantly lower Tau protein in both basal and karyolytic buccal cell types compared with differentiated buccal cells. Aβ, as measured by frequency of cells containing Aβ signal, as well as area and integral of Aβ signal, was significantly higher in the AD group compared with the control group. Buccal cell Aβ was correlated with mini-mental state examination (MMSE) scores (r = -0.436, P=0.001) and several blood-based biomarkers. Combining newly identified biomarkers from buccal cells with those already established may offer a potential route for more specific biomarker panels which may substantially increase the likelihood of better predictive markers for earlier diagnosis of AD.

Background: Several scoring systems for measuring brain injury severity have been developed to standardize the classification of MRI results, which allows for the prediction of functional outcomes to help plan effective interventions for children with cerebral palsy. Objective: The aim of this study is to use statistical techniques to optimize the clinical utility of a recently proposed template-based scoring method by weighting individual anatomical scores of injury, while maintaining its simplicity by retaining only a subset of scored anatomical regions. Materials and methods: Seventy-six children with unilateral cerebral palsy were evaluated in terms of upper limb motor function using the Assisting Hand Assessment measure and injuries visible on MRI using a semiquantitative approach. This cohort included 52 children with periventricular white matter injury and 24 with cortical and deep gray matter injuries. A subset of the template-derived cerebral regions was selected using a data-driven region selection algorithm. Linear regression was performed using this subset, with interaction effects excluded. Results: Linear regression improved multiple correlations between MRI-based and Assisting Hand Assessment scores for both periventricular white matter (R squared increased to 0.45 from 0, P < 0.0001) and cortical and deep gray matter (0.84 from 0.44, P < 0.0001) cohorts. In both cohorts, the data-driven approach retained fewer than 8 of the 40 template-derived anatomical regions. Conclusion: The equal or better prediction of the clinically meaningful Assisting Hand Assessment measure using fewer anatomical regions highlights the potential of these developments to enable enhanced quantification of injury and prediction of patient motor outcome, while maintaining the clinical expediency of the scoring approach.

Understanding the relationships between the structure and function of the brain largely relies on the qualitative assessment of Magnetic Resonance Images (MRIs) by expert clinicians. Automated analysis systems can support these assessments by providing quantitative measures of brain injury. However, the assessment of deep gray matter structures, which are critical to motor and executive function, remains difficult as a result of large anatomical injuries commonly observed in children with Cerebral Palsy (CP). Hence, this article proposes a robust surrogate marker of the extent of deep gray matter injury based on impingement due to local ventricular enlargement on surrounding anatomy. Local enlargement was computed using a statistical shape model of the lateral ventricles constructed from 44 healthy subjects. Measures of injury on 95 age-matched CP patients were used to train a regression model to predict six clinical measures of function. The robustness of identifying ventricular enlargement was demonstrated by an area under the curve of 0.91 when tested against a dichotomised expert clinical assessment. The measures also showed strong and significant relationships for multiple clinical scores, including: motor function (r2 = 0.62, P < 0.005), executive function (r2 = 0.55, P < 0.005), and communication (r2 = 0.50, P < 0.005), especially compared to using volumes obtained from standard anatomical segmentation approaches. The lack of reliance on accurate anatomical segmentations and its resulting robustness to large anatomical variations is a key feature of the proposed automated approach. This coupled with its strong correlation with clinically meaningful scores, signifies the potential utility to repeatedly assess MRIs for clinicians diagnosing children with CP.

White and grey matter lesions are the most prevalent type of injury observable in the Magnetic Resonance Images (MRIs) of children with cerebral palsy (CP). Previous studies investigating the impact of lesions in children with CP have been qualitative, limited by the lack of automated segmentation approaches in this setting. As a result, the quantitative relationship between lesion burden has yet to be established. In this study, we perform automatic lesion segmentation on a large cohort of data (107 children with unilateral CP and 18 healthy children) with a new, validated method for segmenting both white matter (WM) and grey matter (GM) lesions. The method has better accuracy (94%) than the best current methods (73%), and only requires standard structural MRI sequences. Anatomical lesion burdens most predictive of clinical scores of motor, cognitive, visual and communicative function were identified using the Least Absolute Shrinkage and Selection operator (LASSO). The improved segmentations enabled identification of significant correlations between regional lesion burden and clinical performance, which conform to known structure-function relationships. Model performance was validated in an independent test set, with significant correlations observed for both WM and GM regional lesion burden with motor function (p < 0.008), and between WM and GM lesions alone with cognitive and visual function respectively (p < 0.008). The significant correlation of GM lesions with functional outcome highlights the serious implications GM lesions, in addition to WM lesions, have for prognosis, and the utility of structural MRI alone for quantifying lesion burden and planning therapy interventions.