Hamid R. Sohrabi

Introduction
Around 90% of aged care residents with dementia have hearing and/or vision impairment. These impairments frequently go unsupported, exacerbating the impact of dementia and leading to loss of independence, social isolation, anxiety, and depression. We worked with residents, family and care-workers to co-design a sensory support intervention that included a sensory champion, care-worker training, integration of hearing/vision support into daily tasks, visual reminders and hearing/vision support stations to store devices (e.g. glasses and hearing aids).

Objectives
To evaluate implementation of the co-designed hearing and vision intervention using the Theoretical Framework of Acceptability (TFA).

Method
The intervention was evaluated via a TFA (5-Likert scale) questionnaire and semi-structured interview data with care-workers in two sites. Quantitative data were analysed using descriptive statistics and qualitative data via thematic analysis guided by TFA constructs (affective attitude, perceived effectiveness, intervention coherence, self-efficacy, burden, ethicality, and opportunity costs.)

Results
Thirty-five care-workers completed the questionnaire and 13 were interviewed. Questionnaire responses indicated high acceptability (M=4.71, SD=0.46), and perceived effectiveness. Participants reported that the intervention increased provision of hearing/vison support (M=4.46, SD=0.56) and improved residents’ outcomes (M=4.66, SD=0.48). Ratings where withing the ‘neural’ range for burden (M=3.17, SD=1.25) and opportunity costs (M=3.23, SD=1.19). Thematic analysis highlighted positive attitudes, and perceived effectiveness of the intervention including greater staff awareness of hearing/vision needs, improved communication, and better management of sensory aids. Care-workers reported they had developed skills in hearing aid maintenance and cleaning, and had integrated hearing/vision support into daily care routines. Participants found that the intervention was easy to implement and suggested periodic training to sustain knowledge.

Conclusion
The intervention was perceived by care workers as being highly acceptable and effective, with care workers integrating hearing/vision support for residents into their daily routines. Ongoing training could enhance long-term sustainability of hearing/vision support in aged care settings.

Aim: To identify the optimal Aβ PET/MMSE combination for predicting progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia.

Methods: 686 MCI participants with Clinical Dementia Rating (CDR) score of 0.5 were followed for up to 7 years. Harmonized data from AIBL (n = 166) and ADNI (n = 520) were analysed using Cox proportional-hazards models, adjusted for age, sex, and APOE4 status, with the event of interest being progression to mild dementia due to AD (CDR = 1 and Aβ>20 CL). Optimal thresholds for MMSE (27) and Aβ (44 CL) were selected to maximize hazard ratios (HR) at 3 years. Combination of both MMSE and Aβ cut-offs provided four groups 1) high-cognition, low-Aβ (reference group), 2) low-cognition, low-Aβ, 3) high-cognition, high-Aβ, and 4) low-cognition, high-Aβ. Cognitive trajectories over time were modelled by harmonized Preclinical Alzheimer's Cognitive Composite (PACC) scores using linear mixed models, stratified by combined groups and adjusted for age, sex, education and APOE status.

Results: Both 44 CL and MMSE = 27 thresholds showed comparable hazard ratios (HR = 1.50 and 1.49, respectively; Figure 1). However, the MCI high-cognition group had higher progression risk (risk probability (RP) = 1-survival probability = 0.17±0.05) than MCI low-Aβ (RP = 0.01±0.01). Combining both cutoffs improved risk stratification: 75 out of 135 MCI low-cognition, high-Aβ progressed to AD within 3 years (30% survival probability, HR=2.9), while only 1 of 308 of the MCI high-cognition low-Aβ progressed to AD (RP = 0.04±0.03). The Linear mixed-effect models indicated that the low-cognition high-Aβ MCIs group showed the fastest decline with an effect size of 0.75, compared to the high-cognition, low-Aβ group.

Conclusion: Cognitive performance alone is not a sufficient substitute for Aβ cutoffs in predicting MCI-to-AD progression. However, binary classification based on Aβ can be improved by combining Aβ with MMSE to further stratify the risk of progression, providing greater prognostic information on an individual level and aiding in the design of clinical trials and therapeutic interventions for prodromal AD.
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Background
This study aims to determine the optimal threshold for Aβ PET to identify individuals with mild cognitive impairment (MCI) who are at high risk of progressing to Alzheimer's disease (AD). Additionally, it assesses whether combining β‐amyloid with Mini‐Mental State Examination (MMSE) performance can enhance risk stratification in MCI which can guide clinical decision‐making regarding early therapeutic interventions.

Methods
We included 686 MCI participants with CDR 0.5 from two cohorts, followed for up to 7 years. Harmonized data from AIBL (N=166) and ADNI (N=520) were analysed using Cox proportional‐hazards models, adjusted for sex, and APOE4 status, with the event of interest being progression to mild dementia due to AD (detected by CDR = 1 and CL>20). Optimal thresholds for MMSE (27) and Aβ (44 CL) were selected to maximize hazard ratios (HR) at 3 years, categorizing participants into low‐risk and high‐risk groups based on cognitive performance and Aβ load. Note that the MMSE score was selected as it is frequently used in clinical practice and in trials.

Results
Both thresholds showed comparable hazard ratios (Figure 1). However, the MCI high‐cognition group had a significantly higher risk of progressing to AD (measured with risk probability (RP)=1‐survival probability; RP=0.08±0.05) than MCI low‐Aβ (RP=0.01±0.01). Combining both cutoffs improved risk stratification: 51 out of 135 MCI low‐cognition, high‐Aβ progressed to AD within 3 years (50% survival probability, HR=2.00), while only 1 of 308 of the MCI high‐cognition low‐Aβ progressed to AD (RP=0.00±0.01). Furthermore, we tested other cognitive assessments, such as CVLT, which provided similar or even statistically worse results in comparison to MMSE. The low‐cognition high‐Aβ group showed the fastest decline, with an annual rate of decline of 0.34 PACC scores, and an effect size of 0.75, compared to the high‐cognition, low‐Aβ group.

Conclusion
While cognitive performance alone is not sufficient for predicting MCI‐to‐AD progression, combining Aβ with MMSE cutoffs can enhance risk stratification, providing greater prognostic information and aiding in the design of clinical trials and therapeutic interventions for prodromal AD. This study also highlights the importance of using CL>44 to identify individuals at high risk of progressing to AD.

Background
Altered plasma sphingomyelin levels have been associated with Alzheimer's disease (AD), indicating disruptions in lipid metabolism and their potential link with AD pathogenesis. Meanwhile, tau‐related neuronal damage and neurodegeneration result in the release of neuronal tau protein into the bloodstream, reflected predominantly as plasma total‐Tau. Exploring the relationship between sphingomyelin metabolism and tau release before symptom onset could offer valuable insights into the biochemical pathways linked to AD and support the development of improved diagnostic and therapeutic strategies.

Method
The current study embraced plasma sample analysis using a Biocrates‐based targeted mass‐spectrometry platform to measure sphingomyelin levels and a single‐molecule array (Simoa) platform to quantify total‐Tau levels. The participants involved in this study were from the KARVIAH cohort —100 cognitively normal (CN; MoCA≥26 & MMSE≥26) older adults who underwent positron emission tomography (PET) to assess cortical amyloid‐beta (Aβ) load and were grouped as CN Aβ‐ (normal cortical‐Aβ load) and CN Aβ+ (higher cortical‐Aβ load). This study examined cross‐sectional correlations between plasma sphingomyelins and total‐Tau levels within each group. Sphingomyelins associated with total‐Tau were further analysed for their relationship with cortical‐Aβ load. All statistically significant correlations were assessed for correction for AD‐related confounding variables, containing gender, age, body mass index (BMI), and APOE ε4 status, with additional amendments for the false discovery rate (FDR).

Result
Statistically significant positive correlations between sphingomyelins and total‐Tau levels were observed exclusively in CN Aβ+ individuals. These associations remained robust after adjusting for AD‐related confounding variables and correcting for the FDR. Further analysis revealed significant inverse associations between total‐Tau‐associated sphingomyelins and cortical‐Aβ load, observed only in CN Aβ+ individuals, both with and without adjustment for confounding variables and FDR correction.

Conclusion
Elevated plasma total‐Tau levels were associated with higher plasma sphingomyelins exclusively in CN Aβ+ individuals, suggesting a link between tau release from neuronal damage and sphingomyelin‐associated biochemical pathways in the presymptomatic stage of AD. Furthermore, higher levels of total‐Tau‐associated sphingomyelins in plasma were correlated with lower cortical‐Aβ load in CN Aβ+ individuals, likely reflecting early sphingomyelin‐mediated compensatory mechanisms against AD pathogenesis. These findings highlight the potential of total‐Tau‐associated sphingomyelins as markers for understanding the mechanisms involved in presymptomatic AD.

Background
Recent studies indicate that lifestyle interventions combining a healthy diet, physical activity, brain training and health monitoring are effective in preventing dementia and related cognitive decline. This preliminary analysis aimed to assess the baseline dietary adequacy and quality of participants of The Australian‐Multidomain Lifestyle Intervention to reduce dementia risk (AU‐ARROW) which is an ongoing 2‐year randomized clinical trial.

Method
Data from 247 cognitively unimpaired adults enrolled in AU‐ARROW were included (68% female; mean age 67±5 years). Nutrient intake and dietary adequacy at baseline were assessed through data from a self‐administered validated Cancer Council of Victoria Food Frequency Questionnaire. Dietary quality was assessed by comparing dietary intake against five food groups and discretionary foods in the Australian Dietary Guidelines (2013).

Result
Participants’ average energy intakes were 8057±2054kJ/day (females) and 8872±2060kJ/day (males) and the macronutrient contributions to energy were 40% carbohydrate, 39% fat and 21% protein, indicating higher fat and lower carbohydrate intakes compared to acceptable macronutrient distribution ranges. Total fat intake comprised 34% saturated fat, 47% monounsaturated fat and 19% polyunsaturated fat, exceeding recommended levels for saturated fat. Daily consumption of five food groups by females and males averaged 3.6 and 3.2 serves of vegetables, pulses and beans, 1.3 and 1.6 serves of fruits, 3.9 and 4.7 serves of grains/cereals foods, 3.1 and 3.2 serves of meat, poultry, fish, eggs and nuts and 1.7 serves of milk, yoghurt, cheese and/or alternatives, respectively. Discretionary food intake averaged 4.2 serves for females and 4.6 serves for males (Females:1.9 cream and butter,1.8 sweets and confectionary food, 0.3 processed‐meat, 0.2 fast‐foods; Males:2 cream and butter, 2 sweets and confectionary food, 0.4 processed‐meat, 0.2 fast‐foods). Average intake of unsaturated spreads and oils were 24.6±19.6g/day (female) and 28.2±20.0g/day (male).

Conclusion
Baseline nutrient adequacy and diet quality of AU‐ARROW participants were poor, characterized by insufficient intakes of vegetables, pulses and beans, fruits and dairy foods, but excessive intake of discretionary food, likely contributing to higher saturated fat intakes. These findings align with the diet quality of the broader Australian population. The dietary intervention of AU‐ARROW aims to address these nutrient imbalances and improve overall diet quality.

Background
Gut microbiota and their metabolites, particularly short‐chain fatty acids (SCFAs), play a vital role in the gut‐brain axis, and have been associated with neurodegenerative diseases like Alzheimer's disease (AD). However, the changes in gut microbiota composition and SCFA levels during the progression of AD are not yet well understood. This study seeks to investigate these variations to gain deeper insights into their potential role in disease development.

Method
This study examined changes in gut microbiota and SCFA across three groups; Cognitively unimpaired individuals with low amyloid‐beta ((CU) Aβ Low (n = 71)), CU Aβ High (n = 19), and those diagnosed with mild cognitive impairment (MCI) or AD (Disease Group (DG), n = 10). Participants were selected from well characterised cohorts and underwent Pittsburg compound B‐positron emission tomography to determine cerebral amyloid status. Faecal microbiota composition was assessed using shotgun metagenomics, while faecal SCFA concentrations were quantified via Gas Chromatography‐Mass Spectrometry (GC‐MS). Associations between taxa and SCFAs were assessed using Spearman correlation and MaAsLin2.

Result
Firmicutes, Proteobacteria, and Bacteroidetes exhibited significant correlations with SCFAs across all groups. In the CU Aβ Low and Disease Group (DG), Firmicutes showed Positive correlations with butyric acid. Group‐specific patterns included negative correlations between Bacteroidetes and propionic acid in the DG group, a positive correlation between Firmicutes and total SCFAs in the CU Aβ Low group, and a positive correlations between Proteobacteria and Actinobacteria with butyric acid in the CU Aβ High group, alongside notable interactions with isovaleric acid. Furthermore, specific taxa such as Corynebacterium falsenii (Phylum: Actinobacteria), Ruthenibacterium lactatiformans (Phylum: Firmicutes), and Streptomyces capitiformicae (Phylum: Actinobacteria) showed significant associations with SCFAs, particularly propionic acid and butyric acid.

Conclusion
These findings suggest that changes in gut bacteria and their metabolites vary at different stages of AD. Key results show that certain bacteria, such as Firmicutes, Bacteroidetes, and Proteobacteria, are linked to SCFAs, especially butyric acid, which plays a role in gut and brain health. This suggests that modifying gut bacteria could help regulate SCFA levels and potentially slow the progression of AD. However, more research is needed to fully understand this connection.

Background
The Western Pacific Region (WPR) currently has the third‐highest prevalence of dementia globally and is projected to have the highest prevalence by 2050, with >76 million cases. The 2024 Lancet Commission on Dementia suggests that tackling 14 modifiable risk factors could prevent 45% of cases globally1. However, the WPR is socioeconomically and culturally diverse, requiring region‐specific strategies to address dementia effectively.

Method
The population attributable risk (PAR) for nine (out of 14) Lancet Commission factors was calculated for 19 WPR countries using relative risk values from the Lancet Commission and published risk factor prevalence data. The nine factors comprised low education, hearing loss, depression, physical inactivity, diabetes, smoking, hypertension, obesity, and alcohol misuse. Mean PAR values were also calculated for high‐income, upper‐middle income, and low‐middle income WPR countries.

Results
PAR values varied across WPR countries (Table 1). The greatest differences were observed for education (18.5%) and obesity (12.0%) and smallest for depression (3.3%) and alcohol (2.1%). In low‐middle income countries, the highest mean PAR value was for education (9.75%) (Figure 1). By contrast, the highest values in middle‐high and high‐income countries were for diabetes (9.21%) and inactivity (6.42%). Smoking had the second highest mean PAR value in all three groups (range: 5.9‐9.2). Hearing loss and obesity also ranked highly across all groups.

Conclusion
Country‐specific population‐level strategies are urgently needed to effectively reduce dementia risk. Low‐middle income countries will benefit most from interventions and policies that improve access to education; middle‐high income countries from targeting diabetes, and high‐income countries from targeting physical inactivity. Targeting smoking and hearing loss will benefit the entire WPR region. Strategic partnerships between academics, policy makers and industry will ensure appropriate resources are directed to where they will have the most impact. References Livingston G et al. (2024). Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission. The Lancet, Volume 404, Issue 10452, 572‐628. Clarke AJ et al. (2024). Risk factors for the neurodegenerative dementias in the Western Pacific region. The Lancet Regional Health – Western Pacific, Volume 50,101051

Background
Alzheimer's disease (AD), the most common form of dementia, is marked by significant reductions in glucose metabolism. Such hypometabolism reflects underlying synaptic dysfunction, correlating with cognitive decline. Our study aimed to explore the impact of dietary patterns—specifically, the Western Diet and Prudent Diet—on change in glucose metabolism in brain regions associated with AD risk, [18F]Fluorodeoxyglucose positron emission tomography (FDG‐PET) imaging as a biomarker.

Method
Longitudinal data from 133 cognitively unimpaired older adults were analysed from the Western Australian Memory Study. Participants underwent dietary assessment using the Cancer Council of Victoria Food Frequency Questionnaire and completed FDG‐PET imaging up to three times over 43 months. Dietary patterns were identified through principal component analysis, yielding two patterns—named Western Diet and Prudent Diet. Pattern scores were computed by summing food group intakes weighted by their respective factor loadings. Linear mixed‐effect models evaluated the association between dietary adherence and brain glucose metabolism, including potential confounders. The cohort was stratified by apolipoprotein E (APOE) ε4 carrier status, a genetic risk factor for AD, to investigate potential differing effects.

Result
Adherence to a Western Diet, characterised by high sugars and saturated fats, was associated with a faster decline in glucose metabolism in the right fusiform gyrus among APOE ε4 carriers (β = ‐0.00012; SE = 0.00004; false discover rate adjusted p = .032), with no significant associations in APOE ε4 non‐carriers. Similarly, no significant associations were observed between the Prudent Diet, characterised by high intake of fruits, vegetables, and whole grains, and glucose metabolism, in both APOE ε4 carriers and non‐carriers.

Conclusion
Our study highlights the potential detrimental impact of a Western Diet on brain glucose metabolism, particularly for individuals at genetic risk for AD. The decline in glucose metabolism in the fusiform gyrus, a region essential for cognitive functions like facial recognition, emphasises the role of diet in brain health. Future research should examine the mechanisms linking diet to neurodegeneration and explore dietary interventions as preventive strategies against cognitive decline and dementia.