Biomarkers of Dietary Blueberry Intake: Insights from an Untargeted Metabolomics Study of Human Urine Using Dual-Column UHPLC-MS

  • J Agric Food Chem. 2026 Jun 10;74(22):17059-17071. doi: 10.1021/acs.jafc.6c00267.
Yifan Xu  1 ,  Peiyu Li  1 ,  Zilin Xiao  1 ,  Wanning Shang  1 ,  Nan Wang  1 ,  Tongtong Li  1 ,  Ying Wang  2 ,  Huiping Zhang  3 ,  Xuan Wang  4 ,  Hao Ma  1 ,  Geng Zong  4
Affiliations
  • 1. Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  • 2. Department of Clinical Nutrition, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
  • 3. Shanghai Applied Protein Technology Co., Ltd., Shanghai 201100, China.
  • 4. Institute of Nutrition, Fudan University, No.130 Dong-An Road, Shanghai 200032, China.
PMID: 42118677 DOI: 10.1021/acs.jafc.6c00267
Abstract

Biomarkers of food intake (BFIs) can improve dietary assessment by providing objective measures of intake, yet no validated specific biomarkers are currently available for blueberries. In a randomized, controlled, crossover feeding study, 20 healthy young adults completed a 2-day run-in and then consumed fresh blueberries with standard meals (390 g on day 3; 780 g on day 4). Urine samples were collected at fasting, postprandial, and follow-up time points. Using untargeted dual-column ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) metabolomics, together with a multistage feature selection pipeline and analysis of fruit and in vitro digested samples, we identified 28 candidate BFIs, including novel metabolites such as 4-hydroxy-3-prenylbenzaldehyde and kirenol. XGBoost models showed that a three-compound panel comprising 4-hydroxy-3-prenylbenzaldehyde, kirenol, and p-coumaric acid-4-O-glucoside best predicted recent blueberry intake (AUC 0.81) beyond 24 h after intake and showed good specificity relative to Other fruits. These findings support further development of BFIs for blueberry intake.

Keywords
UHPLC-HRMS; biomarker of food intake; blueberry; metabolomics.
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