Traditional dietary assessment methods, including food frequency questionnaires (FFQs), food records, and 24-hour recalls, are widely used in epidemiological research but remain limited by reliance on self-report and susceptibility to recall and reporting bias [1]. Advances in metabolomics now enable simultaneous quantification of thousands of metabolites in small biospecimen volumes, such as urine and plasma, offering objective and reproducible biomarkers of dietary intake [2]. Dietary metabolomics has identified candidate biomarkers with potential to improve dietary intake assessment, evaluate adherence to interventions, detect inter-individual variability in dietary responses, and uncover mechanisms linking diet to health outcomes [3]. Accurate biomarkers of dietary intake are essential to advance understanding of the biological effects of diet quality on health.
This randomised crossover-controlled feeding trial investigated metabolomic responses to two distinct dietary patterns: the Healthy Australian Diet (HAD), aligned with the Australian Dietary Guidelines [4], and the Typical Australian Diet (TAD), modelled from national consumption data [5]. Thirty-four healthy adults consumed each diet for two weeks, separated by a washout period, with all food provided. Plasma and spot urine samples were collected pre- and post-intervention, and metabolomic profiling was performed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Analyses explicitly accounted for within-individual variability.
Elastic net regression identified 65 discriminatory metabolites (31 plasma, 34 urine) that distinguished HAD from TAD. A composite metabolome-derived diet quality score was constructed from these metabolites and examined in relation to cardiometabolic health markers. Higher scores were significantly associated with favourable outcomes, including reductions in diastolic blood pressure (β = -0.242 mmHg, p = 0.013), systolic blood pressure (β = -0.0033 log scale, p = 0.010; ~0.33% reduction), fasting plasma glucose (β = -0.02 mmol/L, p < 0.001), LDL-cholesterol (β = -0.0138 log scale, p < 0.001; ~1.37% reduction), HDL-cholesterol (β = -0.018 mmol/L, p < 0.001), and triglycerides (β = -0.0125 log scale, p = 0.003; ~1.24% reduction). No significant association was observed with the total cholesterol-to-HDL ratio (p = 0.82). Several discriminatory metabolites corresponded to established food-specific biomarkers, while others represent novel candidates.
This study demonstrates that a metabolome-derived diet quality score can objectively distinguish dietary patterns and is associated with clinically relevant improvements in cardiometabolic markers. Future research should assess the applicability of this score in diverse populations including international cohorts to enhance its generalisability, explore links with gut microbiome composition, and evaluate its predictive capacity for long-term health outcomes. When integrated with national dietary recommendations, such a biomarker-based score could validate self-reported intake and, when used alongside traditional dietary assessment tools, improve the accuracy, efficiency, and objectivity of dietary evaluation in both research and practice.