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.

Metabolomic epidemiology has expanded rapidly, but publications often lack sufficient detail for readers to assess study design, analytical methods, sources of bias, and the robustness and reproducibility of findings. Existing reporting recommendations in epidemiology and metabolomics do not fully address the specific challenges that arise when these fields are combined. To improve the completeness and transparency of reporting, we developed the Strengthening the Reporting of Metabolomic Epidemiology (STROBE-MetEpi) statement, an extension of the original STROBE guidance for observational research. The STROBE-MetEpi checklist includes 31 items and subitems covering the Title, Abstract, Introduction, Methods, Results, Discussion, and Other Information sections of metabolomic epidemiology studies. This explanation and elaboration document is intended to complement the STROBE-MetEpi statement by explaining the rationale for each checklist item and providing published examples of transparent reporting. It applies to studies using metabolomic profiling to explore human health, but not to randomized trials, methodological studies, reviews, or multi-omics studies. As with previous STROBE explanation and elaboration documents, its purpose is to improve how studies are reported, not to prescribe how they should be conducted. The STROBE-MetEpi statement and this accompanying document should support authors, reviewers, editors, and readers in improving the reporting, appraisal, interpretation, and reproducibility of metabolomic epidemiology research.Metabolomic epidemiology has expanded rapidly, but publications often lack sufficient detail for readers to assess study design, analytical methods, sources of bias, and the robustness and reproducibility of findings. Existing reporting recommendations in epidemiology and metabolomics do not fully address the specific challenges that arise when these fields are combined. To improve the completeness and transparency of reporting, we developed the Strengthening the Reporting of Metabolomic Epidemiology (STROBE-MetEpi) statement, an extension of the original STROBE guidance for observational research. The STROBE-MetEpi checklist includes 31 items and subitems covering the Title, Abstract, Introduction, Methods, Results, Discussion, and Other Information sections of metabolomic epidemiology studies. This explanation and elaboration document is intended to complement the STROBE-MetEpi statement by explaining the rationale for each checklist item and providing published examples of transparent reporting. It applies to studies using metabolomic profiling to explore human health, but not to randomized trials, methodological studies, reviews, or multi-omics studies. As with previous STROBE explanation and elaboration documents, its purpose is to improve how studies are reported, not to prescribe how they should be conducted. The STROBE-MetEpi statement and this accompanying document should support authors, reviewers, editors, and readers in improving the reporting, appraisal, interpretation, and reproducibility of metabolomic epidemiology research.

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.

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.

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.