Ruey Leng Loo

Background
Preventive strategies, including adherence to specific dietary patterns, have received increasing attention as approaches to reduce cognitive decline and dementia risk. However, findings remain inconsistent, partly due to differences in dietary assessment methods, cognitive outcomes, and THE consideration of genetic susceptibility factors such as apolipoprotein E (APOE) genotype.

Methods
This study examined associations between dietary patterns and longitudinal cognitive change in 185 older adults without dementia from the Western Australia Memory Study. Participants completed a food frequency questionnaire at baseline and underwent comprehensive neuropsychological assessments at baseline and up to five follow-up visits at 18-month intervals. Composite scores were generated for six cognitive domains and the Preclinical Alzheimer’s Cognitive Composite (PACC).

Results
Western and Prudent dietary pattern scores were analysed using linear mixed-effects models stratified by APOE ε4 carrier status. Among APOE ε4 carriers, greater adherence to a Western dietary pattern was associated with a faster decline in attention (p = 0.016), whereas no significant associations were observed for the Prudent dietary pattern or among APOE ε4 non-carriers. This association was attenuated after excluding participants with possible baseline cognitive impairment (MoCA < 23).

Conclusion
These findings suggest that adherence to a Western dietary pattern may accelerate cognitive decline in individuals genetically at risk for Alzheimer’s disease, highlighting the importance of considering gene–diet interactions when developing dietary strategies for dementia prevention.

Nuclear magnetic resonance (NMR) spectroscopy is widely adopted for assessing biochemical composition in agriculture. This study evaluated the feasibility of 400 MHz NMR to detect biochemical differences in Hass avocados grown under conventional (N = 101) and regenerative (N = 105) farming practices in Southwestern Australia. Phosphite, associated with Phytophthora root rot management, was a key discriminating feature (area under ROC curve = 0.96), being detected in 90% of conventional avocados (mean: 49 mg/kg) and 6 regenerative samples (mean: 24 mg/kg). To assess translational potential, water extracts of five samples were analyzed using 80 MHz benchtop NMR. Phosphite was detectable below the strictest maximum residue limit (25 mg/kg), demonstrating the potential of NMR as a sustainable and cost-effective solution for monitoring phosphite residues. This proof-of-concept benchtop NMR approach demonstrates analytical feasibility but requires further validation before application in field-based traceability or regulatory contexts, with a potential future relevance to environmental monitoring, sustainable agriculture, and other crop systems.

Alzheimer’s disease (AD) is characterized by significant reductions in glucose metabolism, reflecting underlying synaptic dysfunction, correlating with cognitive decline. We aimed to explore the impact of dietary patterns on the change in glucose metabolism. Methods: This longitudinal, prospective study included 132 community-dwelling older adults without a diagnosed dementia history enrolled in the Western Australian Memory Study (WAMS). Participants completed a food frequency questionnaire at baseline and underwent [18F]-Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging at baseline and at up to two follow-up assessments scheduled approximately 18 months apart, over a maximum follow-up period of 43 months. Principal component analysis yielded two dietary patterns—named Western Diet and Prudent Diet. Linear mixed-effect models evaluated the association between dietary adherence and glucose metabolism, including potential confounders. Analysis was repeated stratified by sex. Results: Adherence to a Western Diet, characterized by high sugars and saturated fats, was associated with faster decline in glucose metabolism in the left fusiform gyrus (β = −0.00062; SE = 0.00025; FDR-adjusted p = 0.043), neocortex (β = −0.00063; SE = 0.00026; FDR-adjusted p = 0.047), left ventrolateral prefrontal (β = −0.00083; SE = 0.00032; FDR-adjusted p = 0.045 and inferior parietal region (β = −0.00344; SE = 0.00129; FDR-adjusted p = 0.033) in females. A Prudent Diet, characterized by a high intake of fruits, vegetables, and whole grains, showed no significant effects. Conclusions: Our study highlights the following: (a) The potential detrimental impact of a Western Diet on brain glucose metabolism, particularly for females, who are at higher risk for AD. The decline was observed in regions essential for cognitive functions, including visual processing and facial recognition, emphasizing the role of diet in brain health. (b) No significant associations were observed between adherence to a Prudent dietary pattern and changes in glucose metabolism.

Nuclear magnetic resonance (NMR) spectroscopy is increasingly employed in research to quantify lipoprotein subfractions, offering potential utility in clinical diagnostics, particularly for cardiovascular risk assessment. However, the independent validation of proprietary NMR-based lipoprotein profiling methods is crucial for verifying clinical accuracy and reliability. This study presents a posthoc evaluation of concordance between the NMR-based B.I.LISA method and standard enzymatic assays for total cholesterol (TC), triglycerides (TGs), and high-density lipoprotein cholesterol (HDL-C), measured in 620 plasma samples from the OMNI-Heart study, focusing on their performance in evaluating the dietary intervention outcomes. Despite involving independently acquired data not designed for an intermethod validation, the comparison showed a high correlation between methods (R = 0.85–0.92), with median deviations of −4, −5, and −15% for HDL-C, TC, and TGs, respectively. The larger TG deviations are attributed to known issues arising from heterogeneity in high-TG samples, although intervention outcomes remained unaffected. Albumin was identified as a potential interfering factor affecting the TC and HDL-C measurements. HDL-C could also be affected by lipoprotein degradation, contributing to divergence in comparisons of marginal intervention outcomes. Extreme discrepancies were observed in atypical hypercholesterolemia samples. These findings highlight the reliability of the NMR approach despite revealing minor but significant deviations that warrant further research.

The nutritional benefits of Extra Virgin Olive Oils (EVOOs) depend on their chemical composition. Currently, there is no simple way to compare the health benefits of different EVOOs. Samples from Australia, Greece, Italy, Spain and Tunisia (N = 423) were analyzed using proton nuclear magnetic resonance spectroscopy to screen against six quality parameters (free acidity, peroxides, K270, K232, Delta K, wax) and measure fat compositions. These fat compositions were compared against healthy eating guidelines to produce five binary descriptors, which were weighted by evidence to create an accessible Nutritional Quality Index (NQI). EVOOs were differentiated by saturated fat and balance between monounsaturated (MUFA) and polyunsaturated fat (PUFA). Most samples (56.4 %) showed poor SFA, poor PUFA and good MUFA (NQI = 56), 21 % had good SFA, poor PUFA and good MUFA (NQI = 81), and 19.4 % exhibited poor SFA, good PUFA and poor MUFA (NQI = 64). The NQI identifies EVOOs with superior nutritional value, enabling informed consumer choices.

Pooled quality control (PQC) samples are the gold standard for data quality monitoring in metabolic phenotyping studies. Typically composed of equal parts from all study samples, PQCs can be challenging to generate in large cohorts or when sample volumes are low. As an alternative, externally sourced matrix-matched surrogate QCs (sQC) have been proposed. This study evaluates the performance of sQCs against PQCs for assessing analytical variation, data pre-processing, and downstream data analysis in a targeted lipidomics workflow.
Plasma samples (n = 701) from the Microbiome Understanding in Maternity Study, along with PQC (n = 80) and sQC (n = 80) samples, were analyzed using a lipidomics assay targeting 1162 lipids. QC samples were injected throughout acquisition, and data pre-processing was performed using each strategy. For simplicity, a subset (n = 381) of the study samples was used to assess differences in downstream statistical analyses.
Both QC approaches demonstrated high analytical repeatability. While PQC and sQC compositions differed, use of PQCs retained less than 4 % more lipid species during pre-processing. Univariate analysis identified more statistically significant lipids with PQC-based pre-processing, but multivariate model performance was similar between datasets.
This study provides a comprehensive comparison of QC strategies and emphasizes the importance of careful QC workflow selection. While PQCs offer advantages, sQCs serve as a suitable alternative for quality assessment and pre-processing. Their commercial availability also supports use as intra- and inter-laboratory long-term references, aiding data harmonization across studies and laboratories.
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•Comparison of two quality control workflows; pooled study and surrogate QC samples.•In-depth assessment of lipid composition, precision, and filtering.•OPLS-DA model predictive power maintained with both QC pre-processing strategies.•Surrogate QC samples are a robust alternative to a pooled QC in targeted lipidomics.

COVID-19 vaccines are crucial in reducing SARS-CoV-2 transmission and severe health outcomes. Despite widespread administration, their long-term systemic effects on human metabolism remain inadequately understood. This longitudinal study aims to evaluate IgG responses, 34 cytokines, 112 lipoproteins, and 21 low-molecular-weight metabolites in 33 individuals receiving two to four COVID-19 vaccine doses. Changes in metabolic profiles for the first 16 days post each dose of vaccine, and up to 480 days post-initial dose, were compared to baseline (before vaccination). Additionally, metabolic profiles of vaccinated participants were compared to a reference cohort of unvaccinated individuals without prior exposure to SARS-CoV-2 infection (controls) and SARS-CoV-2 cases. Positive IgG responses were observed in 78.8% (N = 26) of participants after the first dose, reaching 100% with subsequent doses. The most common side effects were localized pain at the injection site and "flu-like" symptoms, reported by > 50% of participants. Systemic side effects, e.g., sore lymph nodes, fatigue, and brain fog, were reported but showed no significant correlations to IgG responses. Transient temporal changes were observed for cytokine IP10 (CXCL10) and glutamic acid around the third vaccine dose. Compared to the reference cohort, 497 vaccinated samples (95.0%) had profiles similar to the controls, while the remaining 26 samples with prior infection exposures were similar to mild cases of SARS-CooV-2 infection. In conclusion, COVID-19 vaccination did not induce lasting changes in inflammatory and metabolic responses, nor did it induce changes similar to mild cases of SARS-CoV-2 infection. This supports the metabolic safety of the vaccine and contributes to increased vaccine confidence. KEY MESSAGES: Minimal changes in inflammatory/metabolic markers up to 480 days post-vaccination. Transient increase in IP10 (CXCL10) and glutamic acid around the third dose. Post-vaccination IgG response did not alter metabolic profiles like SARS-CoV-2 cases. Our findings provide insights into the safety of repeated COVID-19 vaccinations.

Key messages
• Minimal changes in inflammatory/metabolic markers up to 480 days post-vaccination.
• Transient increase in IP10 (CXCL10) and glutamic acid around the third dose.
• Post-vaccination IgG response did not alter metabolic profiles like SARS-CoV-2 cases.
• Our findings provide insights into the safety of repeated COVID-19 vaccinations.

Background
Robust tissue pre-treatment and lipid extraction workflows are crucial to metabolic phenotyping studies and accurate interpretation of lipid profiles. Numerous methods for lipid extraction from tissues have been developed, and the choice of technique influences analysis. This study provides a comprehensive evaluation of six liquid-liquid extraction methods (three biphasic and three monophasic) used for lipidomic tissue analysis by liquid chromatography-mass spectrometry. Extraction methods were assessed for their suitability for comprehensive lipid profiling across diverse tissue types: adipose, liver, and heart. These techniques were compared using lyophilised and fresh frozen samples.

Results
The study revealed significant differences in the coverage and reliability of lipid species extracted using each technique, dependent on the tissue type. The optimal extraction method for adipose tissue was butanol:methanol (BUME) (3:1) which achieved the highest lipid coverage, yield and reproducibility (886 lipids with a coefficient of variation (CV) < 30 %); methyl tert-butyl ether (MTBE) with ammonium acetate was most effective for liver tissue (707 lipids CV < 30 %) and BUME (1:1) for heart tissue (311 lipids CV < 30 %). These findings showed that the most effective lipid extraction methods are highly tissue-specific, underscoring the critical need for bespoke protocols tailored to each tissue type. The optimised tissue-specific methods were validated using an intervention study in C57BL/6 mice to investigate diet-induced metabolic changes. The results demonstrated distinct discriminating lipid profiles unique to each tissue type, with 374 lipid species from 13 subclasses significantly different between high-fat diet (HFD) and normal diet (ND) in adipose tissue, while 485 lipid species from 17 subclasses were significantly different between HFD and ND in liver tissue.

Significance and novelty
This study presents a new approach to studying lipid profiles derived from diverse tissues that substantially improve comprehensive lipid species’ detection sensitivity and reliability. Our systematic evaluation provides evidence that tailored tissue-specific extraction protocols are highly valuable in comprehensive lipidomics studies, offering robust tools for reliably identifying lipid changes and facilitates a deeper understanding of tissue-specific metabolic processes in diverse research and clinical applications.
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