Multidisciplinary approach combining food metabolomics and epidemiology identifies meglutol as an important bioactive metabolite in tempe, an Indonesian fermented food

• Published in: Food chemistry 2024-07, Vol.446, p.138744, Article 138744
• Main Authors: Iman, Marvin N., Haslam, Danielle E., Liang, Liming, Guo, Kai, Joshipura, Kaumudi, Pérez, Cynthia M., Clish, Clary, Tucker, Katherine L., Manson, JoAnn E., Bhupathiraju, Shilpa N., Fukusaki, Eiichiro, Lasky-Su, Jessica, Putri, Sastia P.
• Format: Article
• Language: English
• Subjects: Bioactive compounds; Food metabolomics; Functional food; Meglutol; Molecular epidemiology
• ISSN: 0308-8146; 1873-7072; 1873-7072
• DOI: 10.1016/j.foodchem.2024.138744

•Identified food bioactive metabolites using a multidisciplinary metabolomics approach.•Meglutol was characterized as an important bioactive metabolite.•Meglutol was found to be highest in tempe among known meglutol-containing foods.•Tempe made from green pea contained the highest meglutol among studied legume tempes.•Plasma meglutol was associated with lower LDL cholesterol in Hispanic participants. This study introduces a multidisciplinary approach to investigate bioactive food metabolites often overlooked due to their low concentrations. We integrated an in-house food metabolite library (n = 494), a human metabolite library (n = 891) from epidemiological studies, and metabolite pharmacological databases to screen for food metabolites with potential bioactivity. We identified six potential metabolites, including meglutol (3-hydroxy-3-methylglutarate), an understudied low-density lipoprotein (LDL)-lowering compound. We further focused on meglutol as a case study to showcase the range of characterizations achievable with this approach. Green pea tempe was identified to contain the highest meglutol concentration (21.8 ± 4.6 mg/100 g). Furthermore, we identified a significant cross-sectional association between plasma meglutol (per 1-standard deviation) and lower LDL cholesterol in two Hispanic adult cohorts (n = 1,628) (β [standard error]: −5.5 (1.6) mg/dl, P = 0.0005). These findings highlight how multidisciplinary metabolomics can serve as a systematic tool for discovering and enhancing bioactive metabolites in food, such as meglutol, with potential applications in personalized dietary approaches for disease prevention.