Megan Heffernan

Mild cognitive impairment in a community sample: The Sydney Memory and Ageing Study

Mild cognitive impairment (MCI) is associated with an increased dementia risk. This study reports incidence of MCI subtypes, rates of progression to dementia, and stability of MCI classification.

Neuropsychiatric Symptoms in Older People with and without Cognitive Impairment

Neuropsychiatric symptoms (NPS) are non-cognitive disturbances such as depression. Rates of NPS have been shown to increase as cognitive ability declines and may be useful in predicting transition from mild cognitive impairment (MCI) to dementia. This community-based study reports the association between NPS and cognitive decline over two years. Participants included 873 community dwelling adults aged 70-90 years enrolled in the Sydney Memory and Ageing Study. NPS were assessed by the Neuropsychiatric Inventory (NPI). Cognitive impairment was defined by diagnosis (MCI or incident dementia) or neuropsychological test performance across five cognitive domains. Cognitive decline was defined by progression to dementia or worse neuropsychological performance. Total NPS at baseline did not differ between those without cognitive impairment (26.2%) and those with MCI (28.8%), but agitation and apathy were associated with MCI. Only baseline depression was associated with dementia at follow-up. Total NPS at baseline was cross-sectionally associated with cognitive impairment in executive function, attention, and global cognition, but did not predict cognitive decline. Depression, anxiety, agitation, anxiety, and apathy were all associated with impairment in at least one cognitive domain, but only anxiety and agitation were significantly associated with cognitive decline. Sensitivity analyses applied more stringent criteria for NPS and cognitive impairment in MCI but did not alter interpretation of results from the main analysis. Overall rates of NPS at baseline were not associated with MCI, dementia, or cognitive decline over two years. Additional follow-up is needed to further examine this association over a longer time course.

Effects of MCI subtype and reversion on progression to dementia in a community sample

Objective: We sought to understand the trajectory of mild cognitive impairment (MCI) better by examining longitudinally different MCI subtypes and progression to dementia and reversion to normal cognition in a community sample. Methods: We evaluated the stability of MCI subtypes and risk of dementia over 4 biennial assessments as part of an ongoing prospective cohort study, the Sydney Memory and Ageing Study. Results: While prevalence of MCI and different MCI subtypes remains relatively stable across all assessments, reversion from MCI and transitions between different MCI subtypes were common. Up to 46.5% of participants classified with MCI at baseline reverted at some point during follow-up. The majority (83.8%) of participants with incident dementia were diagnosed with MCI 2 years prior to their dementia diagnosis. Both reverters and participants with stable MCI were at an increased risk of progression to dementia compared to those without MCI at baseline (HR 6.4, p = 0.02, and HR 24.7, p < 0.001, respectively); however, the risk of dementia in participants with MCI who did not revert was higher than in reverters (HR 2.5, p = 0.01). This effect was specific to amnestic subtypes (MCI reverters vs nonreverters: amnestic MCI HR 3.3, p = 0.006; nonamnestic MCI: HR 1.3, p = 0.67). Conclusion: Our findings indicate that the relevance of reversion for progression risk depends on the MCI subtype. Subtype specificity and longitudinal characterization are required for the reliable identification of individuals at high risk of developing dementia.

Operationalizing the Diagnostic Criteria for Mild Cognitive Impairment: The Salience of Objective Measures in Predicting Incident Dementia

OBJECTIVE Mild cognitive impairment (MCI) is considered an intermediate stage between normal aging and dementia. It is diagnosed in the presence of subjective cognitive decline and objective cognitive impairment without significant functional impairment, although there are no standard operationalizations for each of these criteria. The objective of this study is to determine which operationalization of the MCI criteria is most accurate at predicting dementia. DESIGN Six-year longitudinal study, part of the Sydney Memory and Ageing Study. SETTING Community-based. PARTICIPANTS 873 community-dwelling dementia-free adults between 70 and 90 years of age. Persons from a non-English speaking background were excluded. MEASUREMENTS Seven different operationalizations for subjective cognitive decline and eight measures of objective cognitive impairment (resulting in 56 different MCI operational algorithms) were applied. The accuracy of each algorithm to predict progression to dementia over 6 years was examined for 618 individuals. RESULTS Baseline MCI prevalence varied between 0.4% and 30.2% and dementia conversion between 15.9% and 61.9% across different algorithms. The predictive accuracy for progression to dementia was poor. The highest accuracy was achieved based on objective cognitive impairment alone. Inclusion of subjective cognitive decline or mild functional impairment did not improve dementia prediction accuracy. CONCLUSIONS Not MCI, but objective cognitive impairment alone, is the best predictor for progression to dementia in a community sample. Nevertheless, clinical assessment procedures need to be refined to improve the identification of pre-dementia individuals.

Alcohol Consumption and Incident Dementia: Evidence from the Sydney Memory and Ageing Study.

Alcohol consumption is a potentially modifiable risk factor for dementia, but the literature is not completely consistent. This inconsistency may be partly due to an interaction with the apolipoprotein E (APOE) genotype, an established risk factor for Alzheimers dementia. The aim of this study was to examine whether alcohol consumption is associated with incident dementia or decline in specific cognitive domains over 4 years, and if this effect is modified by APOEɛ4 status. Non-demented community dwelling older adults (70-90 years) from an ongoing longitudinal study were assessed for cognitive impairment in attention/processing speed, language, executive function, visuospatial ability, and memory. Incident dementia was diagnosed according to DSM-IV criteria. Compared to those who did not drink in the previous 12 months, neither low consumption (HR 0.64 95% CI 0.3-1.4) or risky consumption (HR 0.58 95% CI 0.2-1.5) was associated with incident dementia. Carriers of the APOEɛ4 allele were more likely to develop dementia, but there was no significant interaction with alcohol consumption.

MCI DIAGNOSIS: LESS IS MORE

involved in self-referential processes as well as functional disconnection between these regions (Perrotin et al. 2015). The present study aims at extending these findings by better understanding the neural correlates of anosognosia in the prodromal stage of AD. Thus, here we used regional brain metabolism [FDG-PET] to unravel the metabolic correlates of anosognosia in patients with amnestic mild cognitive impairment (aMCI) and subsequently resting state fMRI [rs-fMRI] to investigate the intrinsic connectivity disruption between brain regions. Methods: Thirty-one subjects (mean age: 74.1; CDR: 0.5) with aMCI were included. All subjects underwent resting state 18-F fluorodeoxyglucose positron emission tomography (FDG-PET) for glucose metabolism measurement and resting state fMRI for intrinsic connectivity measurement. An anosognosia index was obtained by calculating discrepancy scores between subjective and objective memory scores. Voxelwise correlations between anosognosia and neuroimaging data were conducted. All analyses were controlled for multiple comparison using pFDR 1⁄40.05. Results: Anosognosia in aMCI patients correlated with reduced glucose metabolism in posterior cingulate (PCC) cortices and hippocampus (Figure 1). Intrinsic connectivity analyses revealed a significant association between anosognosia and attenuated functional connectivity between the PCC seed region and orbitofrontal cortex (OFC) as well as bilateral inferior parietal lobes (IPL, Figure 2). Conclusions: These findings provide further evidence implicating cortical midline structures involved in awareness of memory deficits. MCI patients with anosognosia showed reduced metabolism as well as disconnection between OFC, PCC and hippocampus, brain regions vulnerable to changes in early Alzheimer’s disease, and therefore could be at increased risk of developing dementia. O4-06-05 MCI DIAGNOSIS: LESS IS MORE Liesbeth Aerts, John D. Crawford, Nicole A. Kochan, Megan Heffernan, Brian Draper, Julian N. Trollor, Perminder S. Sachdev, Henry Brodaty, Dementia Collaborative Research Centre, University of New SouthWales, Sydney, Australia; 2 Centre for Healthy Brain Ageing, UNSW, Sydney, Australia; 3 Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, Australia; Academic Department for Old Age Psychiatry, Prince of Wales Hospital, Randwick, Australia; 5 Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, Sydney, Australia; Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, Australia; 7 University of New South Wales, Sydney, Australia; 8 Centre for Healthy Brain Ageing UNSW Australia, Sydney, Australia; Dementia Collaborative Research Centre ABC, UNSWAustralia, Sydney, Australia. Contact e-mail: l.aerts@unsw.edu.au

Incidence, prevalence and predictors of course of mild cognitive impairment: The sydney memory and ageing study

dementia progression. MMSE derived thresholds had higher sensitivity (MMSE 96.5% vs. A-MCI 89.9%) with little difference in specificity (MMSE 61.7% vs. A-MCI 63.6%). Both groupings were associated with similar neuropathological profiles that included Alzheimer’s pathological features (neurofibrillary tangles and plaques) and vascular disease. Conclusions: In population-based studies identification of individuals at a high risk of dementia can be as accurately achieved using a simple screening tool such as the MMSEwhen compared to more detailed A-MCI criteria. Even highly refined criteria do not identify single neuropathological phenomena in this population based study.

RISK FACTORS FOR DEMENTIA IN 55-75-YEAR-OLDS ENROLLED IN A PILOT STUDY FOR MAINTAIN YOUR BRAIN, AN INTERNET PREVENTATIVE INTERVENTION

functioning. Notably, living in urban areas has been linked to lower risk of dementia. However, findings are mixed and come predominantly from higher-income countries. We examined the association of place of birth and place of residence (urban versus rural) at older age (65 and above) with cognitive functioning in a communitydwelling cohort of older adults in Lebanon (n1⁄4475; age1⁄472.50 (SD1⁄47.22); 56% women). Methods: Cognitive scores were measured using the Community Screening Instrument for Dementia (CSI-D) and Rowland Universal Dementia Assessment Scale (RUDAS). We used linear regression models, adjusted for important covariates, to assess the separate and joint associations of place of birth and residence as well as change in urban living with cognitive scores. Results: In our sample, 59% were born and 64% currently lived in urban areas; 79% of those born in urban areas also lived in urban areas at older age. Being born and residing in urban areas were each associated with lower cognitive scores (beta1⁄41.39 (95% CI1⁄4-1.86,-0.92) CSI-D and -2.13 (95% CI1⁄4-2.88,-1.38) RUDAS scores) and (beta1⁄4-1.67 (95% CI1⁄4-2.15,-1.20) CSI-D and -2.8 95% CI1⁄4-3.55,-2.07 RUDAS scores), respectively. When mutually adjusted for each other, both being born and currently residing in a city were associated with additional lower cognitive scores. Analyses examining change in living settings showed that, compared to participants born and currently residing in rural areas, those who moved (either from urban place of birth to rural residence and vice versa) were not different in their cognitive scores, but, participants born and residing in urban areas had lower cognitive scores. Urban place of birth and residence were associated with higher odds of having cognitive impairment and decline based on the cognitive scores. Further adjustment for lifestyle and medical confounders did not alter results. Conclusions:Results suggest important differences in cognitive functioning related to living conditions among Lebanese older adults. Unlike some findings in higher-income countries, being born and residing at older age in urban settings in Lebanon –which potentially entails more exposure to stress, crowdedness, and pollution– is associated with poorer cognitive functioning.

INCIDENCE OF MCI AND DEMENTIA OVER SIX YEARS IN AN AUSTRALIAN POPULATION SAMPLE

745 (86%) had complete data with non-missing scores for all cognitive domains. Of these, 517 (69%) had a typical cognitive profile, while 228 (31%) had an atypical cognitive profile (see Table 1). These proportions were essentially identical for thosewith probable and those with possible AD. There were 209 people with non-AD dementias. Of these, 94 (45%) had vascular dementia; other dementia etiologies are shown in Table 2. Conclusions:Clinical AD with a typical pattern of cognitive deficits is the most common form of incident dementia in the community. Clinical AD with an atypical pattern of cognitive deficits is more common than non-AD dementia.

THE EFFECT OF ALCOHOL CONSUMPTION AND APOLIPOPROTEIN E (APOE) 4 STATUS ON INCIDENT DEMENTIA OVER 4-YEARS IN THE SYDNEY MEMORY AND AGEING STUDY

P2-307 THE EFFECT OFALCOHOL CONSUMPTION AND APOLIPOPROTEIN E (APOE) 4 STATUS ON INCIDENT DEMENTIA OVER 4-YEARS IN THE SYDNEY MEMORYAND AGEING STUDY Henry Brodaty, Megan Heffernan, Nicole A. Kochan, Simone Reppermund, Karen Mather, Arezoo Assareh, Jing Xu, Brian Draper, Julian Trollor, Perminder S. Sachdev, Dementia Collaborative Research Centre, Sydney, Australia; Dementia Collaborative Research Centre, University of New South Wales, Sydney, Australia; Centre for Healthy Brain Ageing, School of Psychiatry UNSW Medicine, The University of New South Wales, Sydney, Australia; University of New South Wales, Sydney, Australia; University of New South Wales, Randwick, Australia; Neuroscience Research Australia, Sydney, Australia; UNSW, Sydney, Australia; University of New South Wales, Randwick, Australia; University of New South Wales, Randwick-Sydney, Australia. Contact e-mail: h.brodaty@unsw.edu.au