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.

Diet is a key modifiable factor for improving suboptimal lipoprotein profiles and reducing cardiovascular disease (CVD) risk(1). Dietary patterns like the Dietary Approaches to Stop Hypertension (DASH) or the Mediterranean Diet, with varying macronutrient components, have shown positive effects on total cholesterol and low-density lipoproteins (LDL)(2). However, limited research exists on the impact of different healthy diets on lipoprotein subclass profiles, which are increasingly known to influence CVD risk. This study aims to compare the nuclear magnetic resonance (NMR)-measured 112 lipoprotein profiles across three healthy dietary patterns: a carbohydrate-rich diet (CARB), similar to the DASH diet; a protein-rich diet (PROT); and an unsaturated fat-rich diet (USFA), similar to the Mediterranean diet. Lipoprotein parameters were generated using the Bruker IVDr Lipoprotein Subclass Analysis (B.I.LISA) method(3). The lipoprotein subclasses included different molecular components of very low-density lipoprotein (VLDL, 0.950–1.006 kg/L), low-density lipoprotein (LDL, density 1.09–1.63 kg/L), intermediate-density lipoprotein (IDL, density 1.006–1.019 kg/L), and high-density lipoprotein (HDL, density 1.063–1.210 kg/L). The LDL subfraction was further divided into six density classes, and the HDL subfractions were divided into four different density classes. Plasma samples from a randomised cross-over intervention study involving 156 individuals who completed more than two dietary patterns were included for the NMR analysis (registered at www.clinicaltrials.gov as NCT00051350 and NCT03369535). The Friedman’s test with post-hoc analysis, corrected for multiple testing, showed that all healthy dietary patterns led to a reduction in overall lipoprotein subclasses known to be associated with atherogenic risk. This reduction included large and medium-sized LDL subclasses, all intermediate-density IDL subclasses, as well as total plasma cholesterol, triglycerides, apolipoprotein-B100, apo-B100/apo-A1 ratio, and LDL-cholesterol (p < 0.05). Additional variations in lipoprotein subclasses specific to each diet were also observed. The PROT diet showed a decrease in small-sized and dense LDL, large to medium VLDL subclasses, and large-sized HDL subclasses. Conversely, the CARB diet exhibited an increase in smaller-sized and denser LDL, along with a decrease in large-sized HDL and an increase in smaller-sized HDL subclasses. The USFA diet led to decreases in LDL and overall VLDL subclasses, while increasing LDL and HDL subclasses (p < 0.05). The impact of different healthy diets with differential effects on lipoproteins suggests the possibility of targeting the cholesterol status of individuals to optimise lipoprotein profiles and thereby reduce CVD risk. Preliminary exploratory analyses based on linear mixed-effect models coupled with a latent profile analysis, adjusted for cholesterol status, showed that individual lipoprotein responses to specific diets varied. Inter-individual variations in lipoprotein responses to healthy diets were evident. A small proportion of individuals only responded to specific diets, suggesting potential of personalised nutrition based on individual lipoprotein profiles. These observed variations highlight the complexity of individual responses to dietary interventions.

Current nutritional rating systems, like the health star rating, help consumers understand the nutritional value of food and were designed in an effort to combat obesity. However, these systems have limitations, especially for edible oils, which vary widely in composition(1). Coupled with the lack of standardisation in ranking edible oils, there has been advocacy for the introduction of different nutritional scores for edible oils. This study aims to develop a simple and easy-to-use nutritional scoring index based on the composition of extra virgin olive oil (EVOO). The composition includes all fatty acid parameters and total polyphenol content, measurable by nuclear magnetic resonance (NMR) spectroscopy, thereby avoiding the need for multiple analytical platforms. The development of an EVOO nutritional score involved: i) establishing a unique consensus dietary reference index (DRIs) for each component and evaluating their impact on human health(2,3); and ii) computing Scoring Reference Values (SRVs) for each component, expressed as grams of component per 100 g of EVOO, based on the assumptions of a daily energy intake of 2000 kcal, with a fat intake of 35% of total caloric intake(2,3), and considering EVOO as the only source of fat. A nutritional score (0–100) was developed based on saturated fat (SFA), trans-unsaturated fat, oleic, linoleic, alpha-linolenic acids, and polyphenols. Components with more substantial effects/evidence on human health were given greater weight in the scoring. The developed index was subsequently applied to evaluate 314 EVOOs that passed the International Olive Oil Council (IOC) quality criteria. These oils were sourced from Australia (n = 94), Greece (n = 54), Italy (n = 54), Spain (n = 69), and Tunisia (n = 43) and analysed using 400 MHz NMR spectroscopy. Nutritional scores for all samples showed a mean of 62.3 (range 13 to 94), with Australian EVOOs exhibiting the highest mean score of 65, followed by Spain, Tunisia, Italy, and Greece. EVOOs were differentiated by their SFA content and the balance between polyunsaturated (PUFA) and monounsaturated fatty acids (MUFA). MUFA and PUFA were typically inversely related, except for two Australian oils that achieved high levels of both. This novel scoring index for EVOOs, grounded in health-related compositional parameters, facilitates the differentiation of EVOOs based on their nutritional value. This enables consumers to make informed choices regarding their oil selection. Given the rising prevalence of obesity and its associated morbidity, this tool is particularly significant. Additionally, the implementation of this nutritional index encourages producers to produce oils with superior nutritional profiles.