UHPLC-MS Uncovers Urine Biomarkers of Apple Intake

Scientists can learn a lot about what people eat by measuring chemical traces of foods in the body. These biomarkers are more reliable than asking people to remember and report what they ate, which is often inaccurate. For apples, however, the biomarkers found so far have not been very useful in practice. To fill that gap, researchers set out to find substances in urine that reveal whether someone has eaten an apple and that stay detectable for longer after eating. They tracked how these substances rise and fall over time and combined several into a single test that can identify people who ate apples recently. They collected urine at several points after apple consumption and analyzed it alongside whole apples and apples put through a simulated digestion in the laboratory using untargeted metabolomics via dual-column ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). The researchers published their findings in the journal Food Research International.¹

Why Do Scientists Need Chemical Markers to Tell What People Eat?

Finding out exactly what large numbers of people eat is surprisingly hard. The usual methods involve asking people to fill in questionnaires or recall what they ate the day before. But people often forget, misjudge portions or leave things out.² Advances in analyzing body fluids now make it possible to detect chemical traces of specific foods, giving a more accurate and objective picture of what someone has eaten.^3,4 Before these markers can be used in large population studies, though, scientists first need carefully controlled experiments. These show how the body responds to a particular food and which substances are the most promising signs of eating it.^5,6

Can a Urine Test Reveal Whether Someone Has Eaten an Apple in the Past Day or Two?

The study involved 18 healthy adults, who each took part in both the apple and comparison parts of the trial in random order. They first ate a set diet for two days, so everyone started from the same baseline. Then they ate apples once, ate them again over a repeated period, and were followed up afterwards. The researchers looked for substances in urine that stayed raised for a full day after eating apples. They also looked separately for ones that showed up quickly, within the first six hours. Finally, they used machine learning to find the best combination of substances for telling whether people going about their normal lives had eaten apples.¹

The team found five substances that were still clearly raised in urine 24 hours after eating apples. They also found 28 that appeared within the first six hours, including several already known to be linked to apples. On their own, none of the substances was a very good guide to whether someone had eaten apples in everyday life. A combination of four worked best, scoring 0.80 at spotting apple eaters from the previous one to two days, on a scale where 1 is perfect and 0.5 is no better than guessing.¹

“This study,” write the authors of the paper,¹ “identified urinary biomarkers of apple intake with a detection window extending to at least 24 hours and established a multi-biomarker panel for identifying recent apple intake.”

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References

1. Du, Y.; Xiao, Z.; Li, P. et al. Untargeted Metabolomics-based Approach to Discover Biomarkers of Apple Intake: A Randomized Controlled Trial. Food Res Int. 2026, 245 (Pt 2), 120801. DOI: 10.1016/j.foodres.2026.120801
2. Kipnis, V.; Midthune, D.; Freedman, L. et al. Bias in Dietary-report Instruments and its Implications for Nutritional Epidemiology. Public Health Nutr. 2002, 5 (6A), 915-923. DOI: 10.1079/PHN2002383
3. Cuparencu, C.; Bulmuş-Tüccar, T.; Stanstrup, J. et al. Towards Nutrition with Precision: Unlocking Biomarkers as Dietary Assessment Tools. Nat Metab. 2024, 6 (8), 1438-1453. DOI: 10.1038/s42255-024-01067-y
4. Dragsted, L. O.; Gao, Q.; Scalbert, A. et al. Validation of Biomarkers of Food Intake-critical Assessment of Candidate Biomarkers. Genes Nutr. 2018, 13, 14. DOI: 10.1186/s12263-018-0603-9
5. Chakraborty, H.; Sun, Q.; Bhupathiraju, S. N. et al. The Dietary Biomarkers Development Consortium: An Initiative for Discovery and Validation of Dietary Biomarkers for Precision Nutrition. Curr Dev Nutr. 2025, 9 (5), 107435. DOI: 10.1016/j.cdnut.2025.107435
6. Hassenberg, C.; Mack, C. I.; Favari, C. et al. A Scoring System for Validity Assessment of Biomarkers of Food Intake. Crit Rev Food Sci Nutr. 2026, 66 (25), 4848-4874. DOI: 10.1080/10408398.2026.2633561