The AUstralian multidomain Approach to Reduce dementia Risk by prOtecting brain health With lifestyle intervention study (AU-ARROW): A study protocol for a single-blind, multi-site, randomized controlled trial.

INTRODUCTION: The Finnish Geriatric Intervention Study (FINGER) led to the global dementia risk reduction initiative: World-Wide FINGERS (WW-FINGERS). As part of WW-FINGERS, the Australian AU-ARROW study mirrors aspects of FINGER, as well as US-POINTER. METHOD: AU-ARROW is a randomized, single-blind, multisite, 2-year clinical trial (n = 600; aged 55-79). The multimodal lifestyle intervention group will engage in aerobic exercise, resistance training and stretching, dietary advice to encourage MIND diet adherence, BrainHQ cognitive training, and medical monitoring and health education. The Health Education and Coaching group will receive occasional health education sessions. The primary outcome measure is the change in a global composite cognitive score. Extra value will emanate from blood biomarker analysis, positron emission tomography (PET) imaging, brain magnetic resonance imaging (MRI), and retinal biomarker tests. DISCUSSION: The finalized AU-ARROW protocol is expected to allow development of an evidence-based innovative treatment plan to reduce cognitive decline and dementia risk, and effective transfer of research outcomes into Australian health policy. Highlights: Study protocol for a single-blind, randomized controlled trial, the AU-ARROW Study.The AU-ARROW Study is a member of the World-Wide FINGERS (WW-FINGERS) initiative.AU-ARROW's primary outcome measure is change in a global composite cognitive score.Extra significance from amyloid PET imaging, brain MRI, and retinal biomarker tests.Leading to development of an innovative treatment plan to reduce cognitive decline.

Heart rate variability during slow wave sleep is linked to functional connectivity in the central autonomic network.

Reduced heart rate variability can be an early sign of autonomic dysfunction in neurodegenerative diseases and may be related to brain dysfunction in the central autonomic network. As yet, such autonomic dysfunction has not been examined during sleep-which is an ideal physiological state to study brain-heart interaction as both the central and peripheral nervous systems behave differently compared to during wakefulness. Therefore, the primary aim of the current study was to examine whether heart rate variability during nocturnal sleep, specifically slow wave (deep) sleep, is associated with central autonomic network functional connectivity in older adults 'at-risk' of dementia. Older adults (n = 78; age range = 50-88 years; 64% female) attending a memory clinic for cognitive concerns underwent resting-state functional magnetic resonance imaging and an overnight polysomnography. From these, central autonomic network functional connectivity strength and heart rate variability data during sleep were derived, respectively. High-frequency heart rate variability was extracted to index parasympathetic activity during distinct periods of sleep, including slow wave sleep as well as secondary outcomes of non-rapid eye movement sleep, wake after sleep onset, and rapid eye movement sleep. General linear models were used to examine associations between central autonomic network functional connectivity and high-frequency heart rate variability. Analyses revealed that increased high-frequency heart rate variability during slow wave sleep was associated with stronger functional connectivity (F = 3.98, P = 0.022) in two core brain regions within the central autonomic network, the right anterior insular and posterior midcingulate cortex, as well as stronger functional connectivity (F = 6.21, P = 0.005) between broader central autonomic network brain regions-the right amygdala with three sub-nuclei of the thalamus. There were no significant associations between high-frequency heart rate variability and central autonomic network connectivity during wake after sleep onset or rapid eye movement sleep. These findings show that in older adults 'at-risk' of dementia, parasympathetic regulation during slow wave sleep is uniquely linked to differential functional connectivity within both core and broader central autonomic network brain regions. It is possible that dysfunctional brain-heart interactions manifest primarily during this specific period of sleep known for its role in memory and metabolic clearance. Further studies elucidating the pathophysiology and directionality of this relationship should be conducted to determine if heart rate variability drives neurodegeneration, or if brain degeneration within the central autonomic network promotes aberrant heart rate variability.

Brain oxidative stress and cognitive function in older adults with diabetes and pre-diabetes who are at risk for dementia.

AIMS: Diabetes is an established risk factor for dementia. This study aimed to examine the relationship between various cognitive domains, brain oxidative stress and markers of diabetes in older adults at risk for dementia. METHODS: Older adults at risk for dementia underwent comprehensive neuropsychological and medical assessment. At risk was defined as those with subjective and/or objective cognitive impairment. Pre-diabetes and type 2 diabetes were defined using American Diabetes Association definitions for fasting blood glucose and HbA1c. Brain oxidative stress as indicated by glutathione (GSH) was assessed via magnetic resonance spectroscopy in the anterior cingulate cortex. RESULTS: One-hundred and forty-seven older adults completed a neuropsychological assessment and fasting blood sample with 63 also undergoing magnetic resonance spectroscopy. Those with pre-diabetes/diabetes according to FBG had impaired memory retention, set-shifting and response inhibition, compared to those with normal blood glucose. In contrast, there were no significant differences in any cognitive outcome using the HbA1c definition. Increasing glucose and HbA1c levels were associated with reduced GSH concentration in the anterior cingulate. CONCLUSIONS: This study demonstrates that in older adults at risk for dementia, having pre-diabetes or diabetes is associated with impaired memory and executive dysfunction. It also highlights the potential role of oxidative stress as a pathophysiological mechanism that may underpin the link between diabetes and cognitive dysfunction.

Sleep-Dependent Memory in Older People With and Without MCI: The Relevance of Sleep Microarchitecture, OSA, Hippocampal Subfields, and Episodic Memory.

This study aimed to determine if, relative to cognitively healthy controls, sleep-dependent memory consolidation (SDMC) is diminished in mild cognitive impairment (MCI), a group at high risk of conversion to dementia. We also sought to determine whether SDMC is associated with sleep characteristics, daytime episodic memory, and hippocampal integrity. Participants with MCI (n = 43) and controls (n = 20) underwent clinical and neuropsychological profiling. From polysomnography, apnea hypopnea index (AHI) and non-REM sleep spindle characteristics were derived. From magnetic resonance imaging, hippocampal subfield volumes were computed. Participants learned a novel 32-item word-pair prior to sleep; morning retention of the word-pairs was used to determine SDMC. Results showed that SDMC did not differ between MCI and controls, but there was a large effect size decrement in SDMC in those with multiple domain MCI (Hedge's g = 0.85). In MCI, poorer SDMC was correlated with CA1 and CA3 hippocampal atrophy, shorter spindle duration, and worse daytime episodic memory. In controls, poorer SDMC was associated with higher AHI. Impaired daytime memory consolidation, reduced hippocampal volumes, shorter sleep spindles, and greater sleep apnea severity are indicators of diminished SDMC in older adults and should be explored in future studies.

Obesity and Oxidative Stress in Older Adults At Risk for Dementia: A Magnetic Resonance Spectroscopy Study.

OBJECTIVE: This study aimed to investigate the relationship between obesity and oxidative stress in older adults at risk for dementia. It also aimed to explore the influence of physical activity on the relationship between obesity and oxidative stress in this at risk cohort. METHODS: Older adults at risk for dementia underwent comprehensive medical, neuropsychological, and psychiatric assessment. At risk was defined as participants with subjective or mild cognitive impairment. Glutathione was assessed by magnetic resonance spectroscopy in the left hippocampus and the anterior and posterior cingulate cortex. Body mass index (BMI) was calculated and classified as healthy (BMI <25 kg/m2) or overweight/obese (BMI ≥25 kg/m2). RESULTS: Sixty-five older adults (mean age=66.2 y) were included for analysis. The overweight/obese group had significantly greater glutathione in the hippocampus compared with the healthy weight group (t=-2.76, P=0.008). No significant difference in glutathione was observed between groups in the anterior or posterior cingulate. In the overweight/obese group, a higher BMI was associated with a diabetes diagnosis and lower total time engaging in physical activity (r=-0.36, P=0.025), however, glutathione did not correlate with activity levels across groups. CONCLUSION: This study demonstrates that changes in in vivo markers of oxidative stress are present in overweight/obese older adults at risk for dementia. Future research should explore the relationship with diabetes and the longitudinal relationship between BMI and oxidative stress, and response to therapeutic interventions.

Visual Hallucinations and the Role of Medications in Parkinson's Disease: Triggers, Pathophysiology, and Management.

Visual hallucinations, which are part of the syndrome of Parkinson's disease (PD) psychosis, affect patients' quality of life and increase the likelihood of residential aged-care placement. The association between visual hallucinations and dopaminergic and other medications that are necessary for the symptomatic management of motor and other symptoms of PD is a common clinical dilemma. While dopaminergic medications have long been associated with PD psychosis, a clear causal link has not been established, and other neurotransmitter systems, particularly noradrenaline, serotonin, and acetylcholine, are implicated and important. A diverse range of demographic and disease-related risk factors, some being modifiable, highlight the complexity of potential underlying pathophysiological processes but also broaden practical options for prevention and treatment that can be multifaceted and individualized. The investigators reviewed the clinical features and epidemiology of visual hallucinations and PD, explored the pathological evidence for dysfunction of multiple neurotransmitter systems that may be relevant to these phenomena, and addressed the potential of medications commonly used in PD to either trigger or treat these symptoms.

Disability in older adults across the continuum of cognitive decline: unique contributions of depression, sleep disturbance, cognitive deficits and medical burden.

OBJECTIVES: Disability in older adults is associated with a need for support in work, education, and community activities, reduced independence, and poorer quality of life. This study examines potential determinants of disability in a clinical sample of older adults across the continuum of cognitive decline, including sociodemographic, medical, psychiatric, and cognitive factors. DESIGN: This is a cross-sectional study. SETTING: Participants were recruited from a specialty clinic for adults "at risk" of or with early dementia (including subjective cognitive complaints, mild cognitive impairment, and early dementia). PARTICIPANTS: Four hundred forty-two older adults (mean age = 67.11, SD = 9.33) underwent comprehensive medical, neuropsychological, and mood assessments. MEASUREMENTS: Disability was assessed via the self-report World Health Organization Disability Assessment Schedule 2.0. A stepwise (forward) linear regression model was computed to determine factors that contribute to disability within this group. RESULTS: Depressive symptoms were the largest predictor, uniquely explaining 31.8% of the variance. Other contributing factors in the model included younger age, medical burden, and sleep quality, with all factors together accounting for a total of 50.4% of the variance in disability. Cognitive variables did not contribute to the model. CONCLUSIONS: Depressive symptoms account for a significant portion of the variance in disability, but other factors such as age, medical burden and sleep quality are also important contributors in older adults across the continuum of cognitive decline. The relative association of these variables with disability appears to differ for older (≥65 years) relative to younger (<65 years) participants. Given the relationship between disability and these risk factors, an integrative and multidisciplinary approach to risk reduction will likely be most effective, with potential carry over effects for physical and mental health.

Examining Internet and eHealth Practices and Preferences: Survey Study of Australian Older Adults With Subjective Memory Complaints, Mild Cognitive Impairment, or Dementia.

BACKGROUND: Interest in electronic health (eHealth) technologies to screen for and treat a variety of medical and mental health problems is growing exponentially. However, no studies to date have investigated the feasibility of using such e-tools for older adults with mild cognitive impairment (MCI) or dementia. OBJECTIVE: The objective of this study was to describe patterns of Internet use, as well as interest in and preferences for eHealth technologies among older adults with varying degrees of cognitive impairment. METHODS: A total of 221 participants (mean age=67.6 years) attending the Healthy Brain Ageing Clinic at the University of Sydney, a specialist mood and memory clinic for adults ≥50 years of age, underwent comprehensive clinical and neuropsychological assessment and completed a 20-item self-report survey investigating current technology use and interest in eHealth technologies. Descriptive statistics and Fisher exact tests were used to characterize the findings, including variability in the results based on demographic and diagnostic factors, with diagnoses including subjective cognitive impairment (SCI), MCI, and dementia. RESULTS: The sample comprised 27.6% (61/221) SCI, 62.0% (137/221) MCI, and 10.4% (23/221) dementia (mean Mini-Mental State Examination=28.2). The majority of participants reported using mobile phones (201/220, 91.4%) and computers (167/194, 86.1%) routinely, with most respondents having access to the Internet at home (204/220, 92.6%). Variability was evident in the use of computers, mobile phones, and health-related websites in relation to sociodemographic factors, with younger, employed respondents with higher levels of education being more likely to utilize these technologies. Whereas most respondents used email (196/217, 90.3%), the use of social media websites was relatively uncommon. The eHealth intervention of most interest to the broader sample was memory strategy training, with 82.7% (172/208) of participants reporting they would utilize this form of intervention. Preferences for other eHealth interventions varied in relation to educational level, with university-educated participants expressing greater interest in interventions related to mood (P=.01), socialization (P=.02), memory (P=.01), and computer-based exercises (P=.046). eHealth preferences also varied in association, with diagnosis for interventions targeting sleep (P=.01), nutrition (P=.004), vascular risk factors (P=.03), and memory (P=.02). CONCLUSIONS: Technology use is pervasive among older adults with cognitive impairment, though variability was noted in relation to age, education, vocational status, and diagnosis. There is also significant interest in Web-based interventions targeting cognition and memory, as well as other risk factors for cognitive decline, highlighting the urgent need for the development, implementation, and study of eHealth technologies tailored specifically to older adults, including those with MCI and early dementia. Strategies to promote eHealth use among older adults who are retired or have lower levels of education will also need to be considered.