Psychiatry - Research Publications
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ItemNo Preview AvailableDevelopment of harmonized and co‐calibrated scores for memory, executive functioning, language, and visuospatial in the AIBL Study, ADNI, and NACC datasets(Wiley, 2022-12)Background The Australian Imaging, Biomarkers and Lifestyle (AIBL) Study is a prospective study collecting extensive cognitive, clinical, fluid, and imaging biomarkers data from older adults living in Australia. Integration of outcomes between large prospective studies of AD will provide greater precision in models of AD brain‐behavior relationships, so it is important to align composite scores for cognitive domains between such studies. Methods Detailed methods for AIBL, the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the National Alzheimer’s Coordinating Center (NACC) have been published. Briefly, AIBL participants had cognition assessed with an extensive neuropsychological test battery alongside health and biomarker assessments at entry and each 18‐months thereafter. Granular‐level cognitive data were obtained and an expert panel of two neuropsychologists and a behavioral neurologist categorized each element as assessing memory, executive functioning, language, visuospatial, or none of these, exactly as we have done previously. We also identified elements we had previously calibrated from other studies; after careful quality control and confirmation these served as anchors enabling co‐calibration. We used confirmatory factor analysis bi‐factor models to calibrate the AIBL battery with other studies. We used those calibrations to obtain co‐calibrated scores for all AIBL participants at every study visit. Here we show descriptive statistics for baseline visits, separately by diagnosis (normal cognition, mild cognitive impairment (MCI), dementia) for two enrollment waves for AIBL as well as for each phase of ADNI and across the Uniform Data Set (UDS) 1 & 2 (UDS1/2) and UDS3 time periods for NACC. Results Box plots for memory, executive functioning, language, and visuospatial for people with normal cognition are in Figure 1, MCI in Figure 2, and dementia in Figure 3. These figures show there is substantial cognitive variation across waves within these disease stage groups and across studies. Conclusion Co‐calibrated neuropsychological domain scores provide a common metric for integrating cognitive data across studies. Co‐calibrated scores aggregated across large prospective AD studies such as AIBL, ADNI, and NACC provide a foundation for large‐scale models of the development of AD and can serve as phenotypes for genetics studies. Co‐calibrated scores are available from AIBL, ADNI, and from NACC.
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ItemNo Preview AvailableObjectively measured physical activity and cognition in cognitively normal older adults: A longitudinal analysis of the Australian Imaging Biomarkers and Lifestyle (AIBL) study(Wiley Open Access, 2022-12)Background Physical inactivity is one of the greatest modifiable risk factors for dementia and research shows physical activity can delay cognitive decline in older adults. However, much of this research has used subjective physical activity data and a single follow‐up cognitive assessment. Further studies using objectively measured physical activity and comprehensive cognitive data measured at multiple timepoints are required. Methods Participants were 199 community‐dwelling cognitively normal older adults (68.7 5.9 years) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study. Actigraphy was used to measure physical activity at baseline, yielding measures of intensity (peak counts), total activity (total counts) and energy expenditure (kilocalories; k/cal). Cognitive function was assessed using a cognitive battery administered every 18‐months from baseline (3‐11 years follow‐up), yielding composite scores for episodic memory, executive function, attention and processing speed, and global cognition. Results Higher baseline energy expenditure predicted improvements in episodic memory and maintained global cognition over time (β = 0.011, SE = 0.005, p = 0.031; β = 0.009, SE = 0.004, p = 0.047, respectively). Both physical activity intensity and total activity predicted global cognition, such that those with higher peak and total counts had better cognition over time (β = 0.012, SE = 0.004, p = 0.005; β = 0.012, SE = 0.004, p = 0.005, respectively). Finally, higher total activity predicted improved episodic memory over time (β = 0.011, SE = 0.005, p = .022). Conclusion These results suggest that physical activity is associated with preserved cognitive function over time, and that activity intensity may play an important role. This research further highlights the importance of early intervention to prevent cognitive decline and may aid in informing lifestyle interventions for dementia prevention.
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ItemNo Preview AvailableHigher coffee consumption is associated with slower cognitive decline and Aβ‐amyloid accumulation over 126 months: Data from the AIBL study(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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ItemNo Preview AvailableHow lifestyle shapes the brain: Associations between physical activity, sleep, beta‐amyloid and cognitive function in older adults(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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ItemCerebrovascular disease, Alzheimer's disease biomarkers and longitudinal cognitive decline(WILEY-BLACKWELL, 2016-06)
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ItemRecommendations for the nomenclature of cognitive change associated with anaesthesia and surgery-2018(WILEY, 2018-11)Cognitive change affecting patients after anaesthesia and surgery has been recognised for more than 100 yr. Research into cognitive change after anaesthesia and surgery accelerated in the 1980s when multiple studies utilised detailed neuropsychological testing for assessment of cognitive change after cardiac surgery. This body of work consistently documented decline in cognitive function in elderly patients after anaesthesia and surgery, and cognitive changes have been identified up to 7.5 yr afterwards. Importantly, other studies have identified that the incidence of cognitive change is similar after non-cardiac surgery. Other than the inclusion of non-surgical control groups to calculate postoperative cognitive dysfunction, research into these cognitive changes in the perioperative period has been undertaken in isolation from cognitive studies in the general population. The aim of this work is to develop similar terminology to that used in cognitive classifications of the general population for use in investigations of cognitive changes after anaesthesia and surgery. A multispecialty working group followed a modified Delphi procedure with no prespecified number of rounds comprised of three face-to-face meetings followed by online editing of draft versions. Two major classification guidelines [Diagnostic and Statistical Manual for Mental Disorders, fifth edition (DSM-5) and National Institute for Aging and the Alzheimer Association (NIA-AA)] are used outside of anaesthesia and surgery, and may be useful for inclusion of biomarkers in research. For clinical purposes, it is recommended to use the DSM-5 nomenclature. The working group recommends that 'perioperative neurocognitive disorders' be used as an overarching term for cognitive impairment identified in the preoperative or postoperative period. This includes cognitive decline diagnosed before operation (described as neurocognitive disorder); any form of acute event (postoperative delirium) and cognitive decline diagnosed up to 30 days after the procedure (delayed neurocognitive recovery) and up to 12 months (postoperative neurocognitive disorder).
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ItemFifteen Years of the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study: Progress and Observations from 2,359 Older Adults Spanning the Spectrum from Cognitive Normality to Alzheimer's Disease(IOS PRESS, 2021)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.
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ItemAssociation of β-Amyloid Level, Clinical Progression, and Longitudinal Cognitive Change in Normal Older Individuals(LIPPINCOTT WILLIAMS & WILKINS, 2021-02-02)OBJECTIVE: To determine the effect of β-amyloid (Aβ) level on progression risk to mild cognitive impairment (MCI) or dementia and longitudinal cognitive change in cognitively normal (CN) older individuals. METHODS: All CN from the Australian Imaging Biomarkers and Lifestyle study with Aβ PET and ≥3 years follow-up were included (n = 534; age 72 ± 6 years; 27% Aβ positive; follow-up 5.3 ± 1.7 years). Aβ level was divided using the standardized 0-100 Centiloid scale: <15 CL negative, 15-25 CL uncertain, 26-50 CL moderate, 51-100 CL high, >100 CL very high, noting >25 CL approximates a positive scan. Cox proportional hazards analysis and linear mixed effect models were used to assess risk of progression and cognitive decline. RESULTS: Aβ levels in 63% were negative, 10% uncertain, 10% moderate, 14% high, and 3% very high. Fifty-seven (11%) progressed to MCI or dementia. Compared to negative Aβ, the hazard ratio for progression for moderate Aβ was 3.2 (95% confidence interval [CI] 1.3-7.6; p < 0.05), for high was 7.0 (95% CI 3.7-13.3; p < 0.001), and for very high was 11.4 (95% CI 5.1-25.8; p < 0.001). Decline in cognitive composite score was minimal in the moderate group (-0.02 SD/year, p = 0.05), while the high and very high declined substantially (high -0.08 SD/year, p < 0.001; very high -0.35 SD/year, p < 0.001). CONCLUSION: The risk of MCI or dementia over 5 years in older CN is related to Aβ level on PET, 5% if negative vs 25% if positive but ranging from 12% if 26-50 CL to 28% if 51-100 CL and 50% if >100 CL. This information may be useful for dementia risk counseling and aid design of preclinical AD trials.